2nd Technical Meeting - Lyon, France, June 13-15

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TD(22)02001Faruk Pasic, Stefan Pratschner, Stefan Schwarz, Christoph F. MecklenbräukerMultiband Wireless Channel Measurements in a Controlled High-Mobility EnvironmentNext-generation mobile communication systems employ millimeter wave (mmWave) frequency bands with high bandwidths to enable high data rate transmissions. Further, the importance of high mobility scenarios, such as vehicular communication or high-speed train scenarios, is steadily increasing. To learn how wave propagation and scattering effects change from classical sub 6 GHz to mmWave frequencies, measurements in both bands have to be conducted. We perform wireless channel measurements at 2.55 GHz, 5.9 GHz and 25.5 GHz center frequency at high mobility. To ensure a fair comparison
between these frequency bands, we perform repeatable measurements in a controlled environment. Our measurement methodology enables measurements at the same transmitter and receiver positions and velocities, but at different center frequencies. We compare measured wireless channels at the three employed frequency bands in terms of the delay-Doppler function.
TD(22)02002Esteban Egea-Lopez, Jose-Maria Molina-Garcia- Pardo, Martine Lienard and Pierre DegauqueDeterministic Polarimetric Propagation Analysis in Road TunnelsThe objective of this paper is to study the influence of the direction of polarization at the transmitter site on the characteristics of the propagation channel in a road tunnel, either empty or in presence of vehicles. The transmitting frequency being on the order of 1 GHz, the tunnel behaves as an oversized waveguide and a simulation based on ray propagation is well suited. To take vehicles into account, the ray-based software models vehicles as parallelepiped considering full polarimetric wave interaction. In the examples described in this paper, the polarization at the transmitter is either vertical, horizontal or making an angle of 45°, referred to the horizontal axis. This last orientation that is often practically encountered in mobile communication systems has, to our knowledge, not yet been studied for a road tunnel which strongly differs from urban or suburban areas due to its guiding effect. Path loss, crosspolarization discrimination factor and characteristics of the polarization ellipse at the receiving point are compared for different configurations.WG1
TD(22)02003Lianet Méndez-Monsanto Suárez, Ana García ArmadaCompensation of phase noise in 5G NR with machine learningWireless communication systems suffer from phase noise (PN), which comes from transmitter and receiver local oscillators. Orthogonal Frequency Division Multiplexing (OFDM) is a widely used modulation scheme in many radio access technologies, including the Fifth Generation (5G). However, OFDM is sensitive to PN, especially in high frequency bands. In this work, we compensate phase noise by using classical pilot based estimation and extend this method by using Machine Learning (ML) algorithms, with the purpose of reducing the number of sent pilots.WG2
TD(22)02004Anna-Malin Schiffarth, Sascha Schießl, Thomas KopaczActivities in the field of RF-EMF exposure assessment at the Institute of High Frequency Technology (RWTH Aachen University)Compliance with the safety limits for electromagnetic fields to which living beings and especially humans are exposed is of high importance to avoid undesirable and adverse health effects.
The Institute of High Frequency Technology (IHF) at RWTH Aachen University is working on the proper assessment of radio-frequency electromagnetic fields based on measurements, calculations and simulations. Recent research questions focus on the assessment of theoretically possible maximum exposure to 5G base stations with massive MIMO antennas based on the measurement of the SS/PBCH block. Additionally, the potential of a crowdsourcing-based exposure monitoring relying on signal strength indicators measured by common smartphones is investigated.
In this publication, an overview of the current activities and latest research results is given.
TD(22)02006Othman Zahid and Sana SalousLong Term Rain Attenuation Measurements at Millimeter Wave Bands for Short-Range Fixed LinksMillimeter wave (mmWave) radio links are largely affected by precipitation. In this paper, we use a custom-designed continuous wave (CW) channel sounder to record channel data at K band (25.84 GHz) and E band (77.52 GHz). A high-performance PWS100 disdrometer is utilized to collect weather data, including rain rate and rain drop size distribution (DSD) for rain attenuation study. The measured rain attenuation is compared with both the ITU-R P.838-3 model and the DSD model. The results will be useful for the design of fixed links for fifth generation (5G) mmWave communication systems over short links in the built environment.WG1
TD(22)02007Mohamed Abdelbasset Aliouane, Jean-Marc Conrat, Jean-Cristophe Cousin, Xavier BegaudIndoor Material Transmission Measurements between 2 GHz and 170 GHz for 6G Wireless Communication SystemsThe sixth-generation wireless communication research activities were launched worldwide. A tendency of some researchers to use the sub-terahertz frequency band for 6G is noticed. This frequency band is selected as a candidate for 6G due to its remarkable wide unused frequency bandwidth. In this paper, typical indoor environment material transmission measurements from 2 GHz to 170 GHz are presented. These measurements aim to further understand and compare wave-material interaction for above and below 100 GHz frequencies by providing a continuous measurement up to 170 GHz of 16 different materials e.g. glass, plasterboard, concrete, and wooden materials. The measurement system is based on a vector network analyzer, with frequency extension modules for frequencies above 50 GHz.WG1,Sub-WG1
TD(22)02008Mohamed Abdelbasset Aliouane, Jean-Marc Conrat, Jean-Christophe Cousin, Xavier BegaudMaterial Reflection Measurements in Centimeter and Millimeter Wave ranges for 6G Wireless CommunicationsResearch in the field of telecommunication is moving towards 6G. Upper mm Wave frequencies (100-300 GHz) are seen as a promising band for 6G. ITU recommendations on material characteristics are limited to 100 GHz. This study aims to further extend the currently existing knowledge on wave-material interaction and make the link between below and above 100 GHz frequencies by providing reflection measurements from 2 to 170 GHz. The material reflection coefficients of seventeen different materials e.g. glass, wood, aerated concrete, and polystyrene are continuously reported along the measured band. The measurement setup is based on a vector network analyzer with millimeter wave extension modules connected starting from 50 GHz.WG1,Sub-WG1
TD(22)02009SŁAWOMIR J. AMBROZIAK, KRZYSZTOF K. CWALINA, PIOTR RAJCHOWSKI, FILIPE D. CARDOSO, MANUEL M. FERREIRA, LUIS M. CORREIAA Cross-Polarisation Discrimination Analysis of Off-Body Channels in Passenger Ferryboat EnvironmentsThere is a need for investigating radio channels for Body Area Networks considering the depolarisation phenomenon and new types of environments, since these aspects are becoming very important for systems design and deployment. This paper presents an analysis of cross-polarisation discrimination for off-body channels based on a measurement campaign performed in a passenger ferryboat, i.e., where all walls, floors and ceilings are made of metal. Firstly, the measurement campaign, including test-bench and scenarios, as well as the analysis approach, including classification of mutual antennas’ orientation and definition of parameters are described. The analysis of results includes distance, on-body antennas location and several scenarios, addressing statistical parameters. Mean values for the cross-polarisation discrimination are in the range of [3.7, 6.8] dB while the standard deviation is around 10.0 dB. There is no dependence of the cross-polarisation discrimination on distance, within the measured range (up to 16 m). It is found that there is no correlation between radio signals received by vertically and horizontally polarised receiving antennas, hence, enabling the application of polarisation diversity in Body Area Networks. The Normal Distribution is the best fit for describing cross-polarisation discrimination, as shown by the analysis of goodness of fit parameters, since it passes many of the tests.VT1
TD(22)02010Pengxiang Xie, Ke Guan, Haofan Yi, Danping He, Jianwu Dou, and Bo SunA Modified Directional Scattering Model for Rough Surfaces in the Terahertz BandThe sixth-generation mobile communication (6G) is expected to achieve lower latency and higher transmission rate. Terahertz (THz) communication providing ultra-wide bandwidth is recognized as a key candidate to realize the promising vision of 6G. However, when the frequency increases to the THz band, a surface that is considered smooth at low frequencies will become rough for THz waves. Hence, the scattering on rough surfaces is significant in the THz wave propagation. Research on the scattering characteristics of rough surfaces is the foundation and prerequisite for channel modeling. The directional scattering (DS) model is used to characterize the scattering distribution. However, the DS model can only characterize the shape of the scattering lobe and cannot portray the effect of microstructural randomness. In this poster, the full-wave simulation method is used to obtain the scattering distribution of rough surfaces at 300 GHz. Then, the DS model is used to fit scattered electric fields in the incident plane. Through comparing the full-wave simulation results with the DS model, we propose a modified directional scattering model to characterize the effect of microstructure. Enormous channel data can be obtained by introducing the modified DS scattering model into a ray-tracing simulator verified by the measured data, which will further support the standardization of THz channel modeling.WG1,Sub-WG1
TD(22)02011HAJI M. FURQAN, MUHAMMAD SOHAIB J. SOLAIJA,  HALISE TÜRKMEN, HÜSEYIN ARSLANWireless Communication, Sensing, and REM: A Security PerspectiveThe diverse requirements of next-generation communication systems necessitate awareness, flexibility, and intelligence as essential building blocks of future wireless networks. The awareness can be obtained from the radio signals in the environment using wireless sensing and radio environment mapping (REM) methods. This is, however, accompanied by threats such as eavesdropping, manipulation, and disruption posed by malicious attackers. To this end, this work analyzes the wireless sensing and radio environment awareness mechanisms, highlighting their vulnerabilities and provides solutions for mitigating them. As an example, the different threats to REM and its consequences in a vehicular communication scenario are described. Furthermore, the use of REM for securing communications is discussed and future directions regarding sensing/REM security are highlighted.WG1
TD(22)02012François De Saint Moulin, Charles Wiame, Claude Oestges, Luc VandendorpeJoint Performance Metrics for Joint Radar Communication Systems in Automotive ScenariosIn this paper, two new metrics are presented in order to evaluate jointly the performance of radar and communication functions in scenarios involving Dual Function Radar Communication (DFRC) systems using stochastic geometry. These metrics are applied in an automotive scenario involving a two-way road with vehicles and smart traffic lights, both equipped with DFRC systems. The performance achieved with these two metrics are validated using Monte-Carlo (MC) simulations. Additionally, optimisation w.r.t. the power of the vehicles and smart traffic lights is performed based on the metrics. Finally, the model is extended to include interference cancellation for the radar and/or communication functions.WG2
TD(22)02013Mate Boban, Chunxu Jiao, and Mohamed GharbaMeasurement-based Evaluation of Uplink Throughput PredictionMotivated by the teleoperation and local map sharing vehicular communication use cases, we investigate whether uplink throughput can be predicted by different machine learning approaches. First, we perform measurements of the vehicle to infrastructure (V2I) uplink throughput in Munich, Germany. Then, we use the collected measurements to evaluate whether linear regression (LR), deep neural network (DNN), and random forest (RF) can predict the uplink throughput. Our results show that, while very easy to train, LR is overly simple in describing the relationship of the input features and the predicted uplink throughput. On the other hand, DNN and RF can provide a very good prediction of uplink throughput (below 0.5 Mbps mean absolute error for a 40 Mbps uplink connection), while requiring longer training. Irrespective of the employed model, our results show that the best indicator of uplink throughput is signal to interference and noise ratio (SINR). When location information is added to SINR, the prediction error can be further reduced, albeit slightly. In the absence of SINR, location information is the second best in predicting uplink throughput. However, it can be employed only for locations that were available in the training dataset. On the other hand, SINR allows for generalization to locations different to those observed in the training dataset.WG1,VT2,HA1
TD(22)02014Xiping Wang, Zhao Zhang, Danping He, Ke Guan, Dongliang Liu, Jianwu Dou, and Bo SunA Multi-Task Learning Model for Super Resolution of Wireless Channel CharacteristicsChannel modeling has always been the core part in communication system design and development, especially in 5G and 6G era. Traditional approaches like stochastic channel modeling and ray-tracing (RT) based channel modeling depend heavily on measurement data or simulation, which are usually expensive and time consuming. In this paper, we propose a novel super resolution (SR) model for generating channel characteristics data. The model is based on multi-task learning (MTL) convolutional neural networks (CNN) with residual connection. Experiments demonstrate that the proposed SR model could achieve excellent performances in mean absolute error and standard deviation of error. Advantages of the proposed model are demonstrated in comparisons with other state-of-the-art deep learning models. Ablation study also proved the necessity of multi-task learning and techniques in model design. The contribution in this paper could be helpful in channel modeling, network optimization, positioning and other wireless channel characteristics related work by largely reducing workload of simulation or measurement.WG1,WG2,VT2,VT4,HA1,HA3
TD(22)02015Dong Yan, Ke Guan, Danping He, Junhyeong Kim, Heesang Chung, Bo Sun, and Zhangdui ZhongModeling and Analysis of V2I Links for the Handover Situations at mmWave BandIn future years, the intelligent transportation system (ITS) develops rapidly and becomes a key enabling technology for improving road safety, traffic efficiency, and driving experience. To meet the high-rate data stream generation and exchange in onboard equipment, millimeter wave (mmWave) technology has become a solution to meet this requirement. Additionally, mobile stations with high data rates and high speeds lead to frequent handovers in the mobile network environment. Therefore, the successful implementation of handover and the guarantee of link stability during the handover procedure have great significance for practical applications. To satisfy the above demands, it is important to explore the mobile channel characterizations at mmWave during the handover process.
This paper uses a measurement-validated ray tracing (RT) simulator to explore the channel characteristics of vehicle-to-infrastructure (V2I) links during handover in typical urban scenarios. First, the V2I link measurement campaigns were conducted in the typical urban scenario. The measurement results can be used to calibrate RT simulators and preliminarily validate the value of beam switching techniques. Then, the channel characterizations are studied based on the extensive simulations, which consider: the mobile station moves along the curved route and the straight route in the urban scenario, respectively; the influence of different distances between the base stations on the V2I link during the handover process. Finally, the channel characteristics are studied not only by extracting the channel parameters (such as the Rician K-factor) but also by analyzing the specific parameters for the handover procedure in detail. This work aims to help researchers understand the channel characteristics of V2I links at mmWave during handover and support link-level and system-level designs for future in-vehicle communications.
TD(22)02016Mar Francis De Guzman, Pasi Koivumäki, and Katsuyuki HanedaDouble-directional Multipath Data at 140~GHz Derived from Measurement-based Ray-launcherThe double-directional model of the radio channel is an indispensable tool in the design and evaluation of wireless systems. However, double-directional channel sounding is increasingly more difficult as the carrier frequency increases due to the need to steer narrower antenna beams across azimuth and elevation angles both at transmit (Tx) and receive (Rx) ends, resulting in a huge time duration required for measuring a single Tx-Rx link. To tackle the problem, we utilized a measurement-based ray-launcher (MBRL) to estimate the double-directional path data from single-directional radio channel sounding. The latter performs beam scanning only at one of Tx or Rx ends, allowing us to perform many more Tx-Rx link measurements than double-directional sounding. The MBRL maps multipaths measured from the single-directional channel sounding on a geometry of the measurement site, allowing us to identify the reflection points and angular information of the multipaths that we were not able to measure. Double-directional multipath data covering 12 line-of-sight and 56 non-line-of-sight indoor links at 140 GHz band are the main result of this paper. The data will serve for the design and evaluation of communications links, localization and sensing at 140 GHz.WG1
TD(22)02017Marco Di RenzoReconfigurable Intelligent Surfaces (RIS): EM-Consistent Modeling and OptimizationA Reconfigurable Intelligent Surface (RIS) is a planar structure that is engineered to have properties that enable the dynamic control of the electromagnetic waves. In wireless communications and networks, RISs are an emerging technology for realizing programmable and reconfigurable wireless propagation environments through nearly passive and tunable signal transformations. RIS-assisted programmable wireless environments are a multidisciplinary research endeavor. This presentation is aimed to overview the latest research advances on modeling, analyzing, and optimizing RISs for wireless communications with focus on electromagnetically consistent models, analytical frameworks, and optimization algorithms. In addition, the interplay between RISs and holographic surface-based transceivers will be discussed with focus on near-field communications in line-of-sight channels.WG1
TD(22)02018Florin Doru Hutu and Radu Gabriel BozomituDriver’s warning notifications by using FM RDS technologyIn this communication, the use of Software Defined Radio (SDR) transceivers for broadcasting drivers’ warning notifications is tackled. More precisely, by employing the Radio Data System (RDS) protocol of a local Frequency Modulation (FM) transmission, road traffic’s dangerous areas (rail crossing, unmarked crossroads, etc.) are announced. The code of a warning message is broadcasted in the close vicinity of the dangerous area and, at the receiver side, a corresponding image is displayed on the car’s tablet PC. In order to study the coexistence of such kind of transmissions with the regional or national ones, the performance in terms of bit error rate (BER) with respect to the difference between the two received power levels is studied. Then, based on a simplified channel model, this paper gives a method to estimate the local FM transmission range, able to cover the dangerous area without transmission errors on the RDS part.VT2
TD(22)02019Yanni Zhou, Florin Doru Hutu and Guillaume VillemaudInfluence of the RF switch on the performance of a 2×2 FDSM systemFDSM (Full Duplex and Spatial Modulation) radio architectures are forecast as good candidates, able to improve the performance of massive MIMO (Multiple Input Multiple Output) communications. The main element of the SM part, the RF (radio frequency) switch, presents non idealities such as insertion losses, latency time, and isolation between the different access. These non-idealities are acting on the FDSM architecture’s overall performance. In this paper, through realistic system simulations, the impact of a realistic RF switch on the FDSM radio front-end performance is highlighted. The performance is evaluated through the BER (bit error rate) extracted as a function of the signal-to-noise ratio.Sub-WG1,WG2
TD(22)02020Hang Mi, Bo Ai, Ruisi He, Zhangfeng Ma, Mi Yang, Zhangdui ZhongMachine Learning Based Denoising for Channel MeasurementsMachine learning (ML) is playing an increasingly important role in processing large amounts of data generated by communication networks, since it can efficiently solve the problems of non-linearity and unstructured data. Recently, ML has been widely used in the processing of wireless channel data, as the noisy channel in real propagation environment is usually non-linear and unstructured. In this paper, a denoising method based on ML is presented. Two ML algorithms are used to classify and remove noise in channel impulse responses. Then, the results of the traditional noise threshold denoising are compared with ML denoising, and it is found that the denoising classifier using the bidirectional recurrent neural network has the better denoising performance. Finally, some channel parameters such as RMS delay spread are estimated based on measured channel data using different denoising methods. The results are evaluated and compared to explore the impact of denoising method on the extracted channel parameters.WG1
TD(22)02022Pasi Koivumäki, Aki Karttunen, Katsuyuki HanedaRay-Optics Simulations of Outdoor-to-Indoor Multipath Channels at 4 and 14 GHzRadio wave propagation simulations based on the ray-optical approximation have been widely adopted in coverage analysis for a range of situations, including the outdoor-to-indoor (O2I) scenario. In this work we present O2I ray-tracer simulations utilizing a complete building floor plan in the form of a point cloud. The ray-tracing simulation results are compared to measured channels at 4 and 14 GHz in terms of large scale parameters, namely path loss, delay spread and angular spread. In this work we address the importance of 1) interior walls and propagation paths originating therein, and 2) site-specific knowledge of window and interior wall structure in accurately reproducing the O2I channel, particularly the presence of a thin insulating metal film on the windows. The best agreement between measurements and simulations was observed for the most detailed simulation. For both frequencies a mean error of less than 1.5 dB is reached for path loss, and a relative error of less than 10% for delay and angular spreads. Not including the metal film in simulations increases error of estimated building entry loss considerably, whereas absence of interior walls is detrimental to reproduction of large scale parameters.WG1,VT4
TD(22)02023Lutfi Samara, Mate Boban, Thomas KürnerEVM Analysis for THz Communication Links under Antenna Misalignment and I/Q ImbalanceWe derive an analytical expression of the error vector magnitude (EVM) in terahertz (THz) communication links affected by two performance limiters, namely antenna alignment error and the receiver’s in-phase/quadrature imbalance (IQI). Through the sole use of elementary functions, we show how to compute the EVM in closed-form approximately, but accurately and efficiently. Furthermore, we show that antenna alignment errors and IQI can severely degrade the performance of THz communications. Investigations of the special and limiting cases of the regimes pertaining to high signal-to-noise ratio (SNR) and low antenna alignment error variance are carried out, where these investigations have led to the interesting observation of the possible separation of the IQI and THz channel effects on the performance of the EVM.WG2
TD(22)02024Hamid Taramit, José Jaime Camacho Escoto, Javier Gomez, Luis Orozco Barbosa, Abdelkrim HaqiqPerformance Evaluation of Wi-Fi HaLow Networks under Rayleigh Channel with CaptureThe IEEE 802.11ah standard, marketed as Wi-Fi Halow, introduces a new channel access mechanism called the Restricted Access Window (RAW), aiming to provide connectivity for the Internet of Things (IoT) applications over broad areas. RAW aspires to alleviate the contention by splitting the channel access into periods and allocating each period to a given group of stations. This paper develops an analytical framework based on Probability and Renewal theories for modeling and evaluating an IEEE 802.11ah-based network implementing the RAW mechanism. We consider a Rayleigh-fading channel with the presence of the capture effect: a realistic scenario for IoT networks deployed in dense urban environments. Considering a single-hop scenario of stations randomly distributed around an Access Point (AP) and the power attenuation of transmitted packets, we model the channel access under capture awareness. As the RAW mechanism presents a time-limited contention for channel access, we develop a counting process that tracks transmissions up to the end of the contention time interval. Henceforth, we evaluate the network performance in terms of throughput. We meticulously validate the derived analytical results through extensive campaigns of discrete-event simulations. Our study evaluates the impact of different parameters on the overall performance, including the contention time, the number of stations, the number of groups, and the capture threshold. We henceforth study the impact of the capture effect on enhancing the network performance under the grouping feature introduced by the RAW mechanism. This work contributes to developing an analytical modeling framework to evaluate the performance of time-limited random access mechanisms accurately and can be an excellent basis for proposing practical scheduling algorithms to configure the RAW mechanism under non-ideal channel conditions.WG1,WG3,VT3,VT4
TD(22)02025Vasile Bota, Vasile Ciprian Sandu, M.Sc. student, Communications Department, Technical University of Cluj-NapocaTheoretical Performance Evaluation of the Adaptive Use of FEC-Rateless Coding over Rayleigh Block-Faded ChannelsThis paper analyzes the message non-recovery probability pNR and spectral efficiency beta performance of a two-level rateless-FEC coding scheme over a Rayleigh faded channel. It derives the expressions of pNR and beta vs. SNR, in terms of the FEC coding rate Rc,, modulation and number of transmitted rateless symbols Na, and the minimum number of rateless symbols Nam needed to ensure a target pNR. Moreover,  it evaluates the performance provided by the adaptive use of a set of modulations, FEC-coding rates, and the corresponding number of rateless symbols Nam, to provide the highest spectral efficiency, while ensuring a target pNR,  according to the  channel’s SNR.
The numerical results show that the pNR provided by this coding scheme decreases very abruptly as the SNR increases, at the expense of a slight increase of the number of rateless symbols. The adaptive use of the FEC-rateless coded configurations provide high spectral efficiency and fine granularity, thus being a promising option for the Link Adaptation functionality of future transmission systems.
TD(22)02026Alister Burr and Sumaila MahamaTwo-way relaying with overhearing for infrastructureless wireless networksIn scenarios such as emergencies where fixed infrastructure such as base stations etc may be absent, degraded or unreliable, it may nevertheless be necessary to provide wireless services for a group of users, such as emergency workers.  However direct communication may not be available between all group members, and hence a relay is needed.  In this paper we consider a two-way relay network for this application, in which any pair of users may communicate via the relay, and other group members may receive signals from the relay and also overhear the transmission from at least one of the active users.  We evaluate the performance of various forms of physical layer network coding (PNC) in this network, in the presence of fading channels.  We show that the choice between linear and non-linear PNC makes a small difference to required signal to noise ratio at the relay, and that full decoding at the relay (rather than PNC) has nearly equivalent performance.  We also consider a relay equipped with two antennas, and show that second order diversity is available.WG2
TD(22)02027Danilo Radovic, Herbert Groll, Christoph F. MecklenbräukerEvaluation of stationarity regions in measured non-WSSUS 60 GHz mmWave V2V channelsDue to high mobility in multipath propagation environments, vehicle-to-vehicle (V2V) channels are generally time and frequency variant. Therefore, the criteria for wide-sense stationarity (WSS) and uncorrelated scattering (US) are just satisfied over very limited intervals in the time and frequency domains, respectively. We test the validity of these criteria in
measured vehicular 60 GHz millimeter wave (mmWave) channels, by estimating the local scattering functions (LSFs) from the measured data. Based on the variation of the LSFs, we define time-frequency stationarity regions, over which the WSSUS assumption is assumed to be fulfilled approximately. We analyze and compare both line-of-sight (LOS) and non-LOS (NLOS) V2V communication conditions.
We observe large stationarity regions for channels with a dominant LOS connection, without relative movement between the
transmitting and receiving vehicle.
In the same measured urban driving scenario, modified by eliminating the LOS component in the post-processing, the
channel is dominated by specular components reflected from an overpassing vehicle with a relative velocity of 56 km/h. Here, we observe a stationarity bandwidth of 270 MHz. Furthermore, the NLOS channel, dominated by a single strong specular component, shows a relatively large average stationarity time of 16 ms, while the stationarity time for the channel with a rich multipath profile is much shorter, in the order of 5 ms.
TD(22)02028Marco Skocaj, Lorenzo Mario Amorosa, Giorgio Ghinamo, Giuliano Muratore, Davide Micheli, Flavio Zabini, Roberto VerdoneCellular Network Capacity and Coverage Enhancement with MDT Data and Deep Reinforcement LearningRecent years witnessed a remarkable increase in the availability of data and computing resources in communication networks. This contributed to the rise of data-driven over model-driven algorithms for network automation. This paper investigates a Minimization of Drive Tests (MDT)-driven Deep Reinforcement Learning (DRL) algorithm to optimize coverage and capacity by tuning antennas tilts on a cluster of cells from TIM’s cellular network. We jointly utilize MDT data, electromagnetic simulations, and network Key Performance indicators (KPIs) to define a simulated network environment for the training of a Deep Q-Network (DQN) agent. Some tweaks have been introduced to the classical DQN formulation to improve the agent’s sample efficiency, stability, and performance. In particular, a custom exploration policy is designed to introduce soft constraints at training time. Results show that the proposed algorithm outperforms baseline approaches like DQN and best-fist search in terms of long-term reward and sample efficiency. Our results indicate that MDT-driven approaches constitute a valuable tool for autonomous coverage and capacity optimization of mobile radio networks.WG3
TD(22)02029Mohsen Ahadi and Florian Kaltenberger5GNR Indoor Positioning by Joint DL-TDoA and DL-AoDThe topic of indoor positioning of a user terminal is becoming increasingly significant in the context of mobile networks as accurate localization based on global navigation satellite systems (GNSS) is not possible inside buildings. The 5G New Radio (NR) networks based on the 3GPP have introduced several enhanced features to allow the accurate positioning of user terminals. By utilizing mmWave for the downlink positioning reference signals (DL-PRS) in a 3GPP Rel-16 5G NR system in Frequency Range 2 (FR2), we investigate the performance of a combined method consisting of Downlink Time Difference of Arrival (DL-TDoA) and Downlink Angle of Departure (DL- AoD). TDoA is a widely used horizontal positioning technique that does not require tight synchronization between base stations and mobile stations. Moreover, Multiple antennas beamforming on base stations leads to high vertical positioning accuracy with AoD. We use ray-tracing-based site-specific channel models to evaluate our joint positioning algorithm’s performance in an Indoor Factory (InF) scenario. The simulation results show sub- meter user localization error which is a significant improvement compared to applying the previous methods separately.WG2
TD(22)02030Jérome Eertmans, Claude Oestges and Laurent JacquesMin-Path-Tracing: A Diffraction Aware Alternative to Image Method in Ray TracingFor more than twenty years, Ray Tracing methods have continued to improve on both accuracy and computational time aspects. However, most state-of-the-art image-based ray tracers still rely on a description of the environment that only contains planar surfaces. They are also limited by the number of diffractions they can simulate, owing to the complexity introduced when solving for paths. In this paper, we present Min-Path-Tracing (MPT), an alternative to the well-known image method that can handle diffractions seamlessly, while also leveraging the possibility to use different geometries for surfaces or edges, such as parabolic mirrors. MPT uses implicit representations of objects to write the path finding challenge as a minimization problem. We further show that multiple diffractions can be important in some situations, which MPT is capable to simulate without increasing neither the computational nor the implementation complexity.WG1
TD(22)02032Shanshan Wang, Taghrid Mazloum, Wassim Ben Chikha, Jiang Liu and Joe WiartRF EMF exposure prediction based on artificial intelligence, drive test measurement and open access information on cellular RF networksIn this TD, we analyze the artificial neural network (ANN) ability to build a model for a spatial reconstruction of radio-frequency (RF) electromagnetic field (EMF) exposure in an urban environment. Toward this, electric (E) field strength has been measured through a drive test measurement carried out in Paris. Based on the measurement the E-field strength linked to frequency band of networks provider are assessed. The correlation between the E-fields at different frequency bands has been analyzed and results show a strong correlation for bands belonging to the same operator. ANN models have been built with input data encompassing information related to distances to N neighboring base stations (BS). These information as well as the frequency band used by these BSs, come from “Cartoradio”, an open access RF cellular network information. In this communication, we consider two different models. The first one is a fully connected ANN model (we take into account the nearest BSs ignoring the corresponding operator); the second one is a hybrid model (where we consider locally connected blocks with the N nearest BSs for each operator). As expected, we observed that the model achieves better performance than the fully connected one.WG1,Sub-VT1
TD(22)02033Mengting Li, Fengchun Zhang, Xiang Zhang, Yejian Lyu and Wei FanOmni-directional Pathloss Measurement Based on Virtual Antenna Array with Directional AntennasOmni-directional pathloss, which refers to the pathloss when omni-directional antennas are used at the link ends, are essential for system design and evaluation. In the millimeter-wave (mm-Wave) and beyond bands, high gain directional antennas are widely used for channel measurements due to the significant signal attenuation. Conventional methods for omni-directional pathloss estimation are based on directional scanning sounding (DSS) system, i.e., a single directional antenna placed at the center of a rotator capturing signals from different rotation angles. The omni-directional pathloss is obtained by either summing up all the powers above the noise level or just summing up the powers of detected propagation paths. However, both methods are problematic with relatively wide main beams and high side-lobes provided by the directional antennas. In this letter, directional antenna based virtual antenna array (VAA) system is implemented for omni-directional pathloss estimation. The VAA scheme uses the same measurement system as the DSS, yet it offers high angular resolution (i.e. narrow main beam)
and low side-lobes, which is essential for achieving accurate multipath detection in the power anglular delay profiles (PADPs) and thereby obtaining accurate omni-directional pathloss. A measurement campaign was designed and conducted in an indoor corridor at 28-30 GHz to verify the effectiveness of the proposed method.
TD(22)02034Markus Hofer, David Löschenbrand, Stefan Zelenbaba, Benjamin Rainer, Anja Dakic and Thomas ZemenWireless Vehicular-to-Vehicular Dual Band Measurements in Urban Street ScenariosIn this paper we present and discuss results of a wireless vehicular-to-vehicular dualband channel measurement campaign at center frequencies of 3.2 GHz and 34.3 GHz in different urban street scenarios. The measurement is conducted using a bandwidth of 155 MHz and a sounding repetition rate of 62.5 µs. We compare the measurements using the time-variant power delay profile (PDP) and the Doppler spectral density (DSD) and assess similarties and differences of the wireless propagation characteristics.WG1,Sub-WG1
TD(22)02035Joonas KokkoniemiPropagation Aspects of Large Reconfigurable Intelligent SurfacesReconfigurable intelligent surfaces (RISs) are seen as very promising solutions for improving signal levels in situations where line of sight (LOS) channel is not available. These surfaces have been shown in the past to give better signal levels in theoretical works, but in practical setups as well. In this TD, we give basic propagation modeling of RISs and focus on the near field analysis of those. Especially at high frequencies, generating gain at RIS is very important in order to provide meaningful signal gain. This requires large numbers of RIS elements and sufficient surface area for capturing and redirection the signal energy. With large RISs, there is a possibility to be at the near field of the RIS array. This is especially a potential problem in certain close-proximity scenarios, such as indoor scenarios. In this TD, we give some preliminary results on near field signal propagation analysis as well as some results on beam squinting in far and near fields of RISs. The focus is on achievable gain with RIS in far and near fields with different RIS setups and sizes. Analysis further considers the gain degradation in far and near field due to the beam squinting.WG1
TD(22)02036Jasper Goethals, Marjolein Brack, Leen Verloock, Günter Vermeeren, Margot Dertuyck, Denys Nikolayev, Jan Govaere, Wout JosephExperimental Characterization of In-to-Out-Body Path Loss for Health Monitoring IoT Network in Automated Goat FarmIn this work, for the first time, the in-to-out-body path loss between an antenna inside a goat’s rumen and a gateway was examined at 434 MHz. The measurements were conducted on two freshly slaughtered goats with different fat consistency to map the effect of goat morphology variations on the path loss. An extra body loss was measured of 24 dB with the fat goat in comparison with the slender goat. An average body loss of 112 dB was measured. Based on the measurements, a single-slope path loss measurement was fitted. The obtained model was used to calculate the range of a LoRa (Long Range) communication channel. Ranges up to 18 meters were predicted.WG1,VT1,VT3
TD(22)02037Muhammad Idham Habibie, Jihad Hamie, Claire GoursaudAdaptation of Grover’s Quantum Algorithm to Multiuser Detection in an OCDMA SystemTo support multiple transmissions in an optical fiber, several techniques have been studied such as Optical Code Division Multiple Access (OCDMA). In particular, the incoherent OCDMA systems are appreciated for their simplicity and reduced cost. However, they suffer from % can be classified as coherent or non-coherent, where the non-coherent family is benefiting from more capacity in assigning codes to users, but at the cost of the Multiple Access Interference (MAI), which degrades the performances.
In order to cope with this MAI, several detectors have been studied. Among them, the Maximum Likelihood (ML) detector is the optimal one but it suffers from high complexity as all possibilities have to be tested prior to decision. However, thanks to the recent quantum computing advances, the complexity problem can be circumvented. As a matter of fact, quantum algorithms, such as Grover, exploit the superposition states in the quantum domain to accelerate the computation. Thus, in this paper, we propose to adapt the quantum Grover’s algorithm in the context of Multi-User Detection (MUD), in an OCDMA system using non-orthogonal codes. We propose a way to adapt the received noisy signal to the constraints defined by Grover’s algorithm. We further evaluate the probability of success in detecting the active users for different noise levels.
Aside from the complexity reduction, simulations show that our proposal has a high probability of detection when the received signal is not highly altered. We show the benefits of our proposal compared to the classical and the optimal ML detector.
TD(22)02038Anja Dakić, Benjamin Rainer, Markus Hofer, Stefan Zelenbaba, Thomas ZemenFrame Error Rate Prediction for Vehicular Wireless CommunicationVehicular communication requires a reliable information exchange to enable road safety. We investigate a new way of obtaining the reliable coverage area for non-stationary vehicular scenarios. We propose a deep neural network (DNN) for predicting the frame error rate (FER). The DNN model is trained using a supervised method, where a time-limited sequence of channel frequency response has been labelled with a corresponding FER value. The frequency response is calculated from a geometry-based stochastic channel model (GSCM) in urban scenarios and the FER is measured by emulating frequency responses of a stationarity region using a hardware-in-the-loop setup. We show exemplary results using modems based on the IEEE 802.11p standard.WG1
TD(22)02039Michael Schweins, Nils Grupe, Thomas KürnerInvestigation of Multi Path Components with RaytracingThis paper investigates the particular impact of the different Multi Path Components (MPC). Each component is predicted by an efficient three-dimensional Raytracing algorithm. The propagation predictor is embedded in the inhouse-developed Simulator for Mobile Networks (SiMoNe). We applied the Raytracing algorithm in a realistic scenario with building data of the city Braunschweig, Germany and 5G cell site locations of the mobile network operator Deutsche Telekom AG. With the introduced analysis we are able to predict what power contribution each propagation effect has for a particular area. Along with performance measurements within the scenario, we aim to evaluate each part of the Raytracing algorithm individually.WG1
TD(22)02042Jonas Gedschold, Sebastian Semper, Michael Döbereiner, Giovanni Del GaldoDispersion-aware Ultra-Wideband Parameter EstimatorWe extent a classical multipath model for wave propagation by a model for frequency-dependent path gain and wideband Doppler effect. In this way, the model should describe dispersive paths with a certain extent in time-domain. It constitutes a sinc-interpolated transfer function for each path omitting the necessity for physical-based dispersion modelling. Additionally, we modified the RIMAX ML algorithm in a way, that it can estimate the wideband model efficiently. We already have extensive numerical evaluations i.e. comparisons to SOTA and are currently working on examples with measurement data.WG1,WG2
TD(22)02043Lélio Chetot, Malcolm Egan, Jean-Marie GorceJoint Identification and Channel Estimation for Fault Detection in Industrial IoT With Correlated Sensors

Document was submitted to and accepted by IEEE Access Journal:
L. Chetot, M. Egan and J. -M. Gorce, “Joint Identification and Channel Estimation for Fault Detection in Industrial IoT With Correlated Sensors,” in IEEE Access, vol. 9, pp. 116692-116701, 2021, doi: 10.1109/ACCESS.2021.3106736.

As industrial plants increase the number of wirelessly connected sensors for fault detection, a key problem is to identify and obtain data from the sensors. Due to the large number of sensors, random access protocols exploiting non-orthogonal multiple access (NOMA) are a natural approach. In this paper, we develop new algorithms based on approximate message passing for sensor identification and channel estimation accounting for correlation in the activity probability of each sensor and observations of physical variables (e.g., temperature) by the access point. These algorithms form the basis for data decoding, while also identifying faulty machines and estimating local values of the temperature, which can lead to a reduction in the amount of data required to be transmitted. Numerical results show that for an expected activity probability of 0.35, our algorithms improve the normalized mean-square error of the channel estimate by up to 5dB and reduce the rate of sensor identification errors by a factor of four.

TD(22)02044Eric Pierre Simon,  Nor El Islam Dahmouni,  Pierre Laly, Joumana Farah, Virginie Deniau, Emmeric Tanghe, Wout Joseph, and Davy GaillotMeasurement of the V2I channel in cell-free vehicular networks with the Distributed MIMOSA channel sounderCell-free massive MIMO (multiple-input multiple-output) networks combine the advantages of distributed systems and massive MIMO, making them potential candidates for future vehicular networks. Despite all the attention they have received recently, their attractive features have not been evaluated yet in practice from measured vehicle-to-infrastructure (V2I) propagation channels. This is the topic of this paper. A radio channel measurement campaign was conducted at the University of Lille in a typical suburban environment. A total of three distributed patch transmit (Tx) antennas were deployed along the road. An omnidirectional receive (Rx) antenna was placed on the roof of a van moving at a speed of 40 km/h.  For comparison, a co-located configuration was also considered where the three antennas were co-located.
The real-time channel sounder MIMOSA was used for the measurement, with an 80 MHz bandwidth at 5.89 GHz, which corresponds to the frequency band offered by the ITS-G5 and C-V2X technologies considered for intelligent transport systems. The main channel characteristics for the two configurations are presented. In particular, it is shown that the cell-free architecture achieves a higher and more uniform signal-to-noise ratio (SNR) compared to the classical co-located architecture, which is an expected benefit of cell-free. It is to be noted that these results obtained for three distributed antennas are preliminary since the MIMOSA sounder will soon be equipped with more distributed antennas.
TD(22)02045Zhiqiang Yuan, Jianhua Zhang, Yilin Ji, Gert F. Pedersen, and Wei FanSpatial Non-stationary Near-field Channel Modeling and Validation for Massive MIMO SystemsMassive MIMO is envisioned as a promising technology in 5G and beyond 5G communication. Channel models are of great importance for the development and performance assessment of massive MIMO systems. Since massive MIMO systems are equipped with large-aperture antenna arrays, antenna elements at different spatial positions would observe different channel multipath characteristics, which is so-called spatial non-stationarity (SnS). The SnS property of multipaths has been observed in many reported massive MIMO channel measurements. However, characterization and explanations of SnS have not been adequate in existing statistical channel modeling, and deterministic models (e.g., Ray-tracing) are difficult to implement due to the high complexity. This paper proposes a realistic yet low-complexity SnS channel modeling framework for massive MIMO systems and its validation based on both channel measurements and Ray-tracing simulations. In this work, we firstly perform an 6 GHz-bandwidth millimeter-wave (mmWave) indoor channel measurement campaign with a 0.5 m-radius virtual uniform circular array (UCA), where the SnS phenomena are clearly observed. Then, we propose the massive MIMO channel modeling framework that captures the observed SnS property from physical multipath propagation mechanisms, i.e., blockage, reflection, and diffraction. Compared to traditional stationary channel modeling, only one extra parameter accounting for SnS has been added in the proposed framework, which is desirable for its low-complexity implementation. Finally, the proposed framework is validated with site-specific Ray-tracing simulations. The SnS phenomena observed in the measurements are reproduced well in the modeling results according to the proposed framework, and high similarities between the target channels and modeling results are achieved. The proposed framework is valuable for the development of massive MIMO systems, since it is realistic, low-complexity, and accurate.WG1
TD(22)02046S. Schieler , M. Döbereiner , S. Semper , M. LandmannEstimating Multi-Modal Dense Multipath Components using Auto-Encoders

We present a maximum-likelihood estimation algorithm for radio channel measurements exhibiting a mixture of independent dense multipath components.

The novelty of our approach is in the algorithms initialization using a deep learning architecture.
Currently, available approaches can only deal with scenarios where a single mode is present.
However, in measurements, two or more modes are often observed.
This much more challenging multi-modal setting bears two important questions: How many modes are there, and how can we estimate those?

To this end, we propose a neural-network-architecture that can reliably estimate the number of modes present in the data and also provide an initial assessment of their shape.
These predictions are used to initialize for gradient- and model-based optimization algorithm to further refine the estimates.

We demonstrate numerically how the presented architecture performs on measurement data and analytically study its influence on the estimation of specular paths in a setting where the single-modal approach fails.

TD(22)02047Ahmed Boujnoui, Abdellah Zaaloul, Luis Orozco-Barbosa, Abdelkrim HaqiqStochastic Game Analysis of Cooperation and Selfishness in an IoT Random Access MechanismThis paper introduces a general stochastic game analysis of a network scenario consisting of a mix of cooperative and non-cooperative players (i.e., users) under incomplete game information. The analysis provided by this paper can be in particular implemented for an IoT wireless network like LoRa network, where heterogeneous battery-powered devices compete for channel access. We consider that users access a shared channel using the Slotted ALOHA mechanism combined with ZigZag Decoding (SAZD). Cooperative players seek to optimize the global utility of the system (e.g., throughput, delay, loss rate) regardless of their individual interests. Whereas, non-cooperative players act selfishly and optimize their own benefits irrespective of the impact of this behavior on others and on the entire network system. The game equilibrium is characterized by the social optimum and the Nash equilibrium, where the former is adopted by cooperative players and the latter is the equilibrium strategy of non-cooperative players. We undertake a comparative study across two game scenarios with different levels of cooperation and selfishness. Our results generally show that the information possessed by a player can determine its outcome. Furthermore, our findings show that the network performance is strongly influenced by the selfish behavior, which can lead to significant disruption of the entire system. Finally, we show a possible scenario in which the network could greatly benefit from this selfish behavior thanks to the ZigZag scheme.WG3
TD(22)02048Sara Cavallero, Giampaolo Cuozzo, Francesco Pase, Marco Giordani, Joseph Eichinger, Chiara Buratti, Roberto Verdone, Michele ZorziEnabling URLLC in 5G NR IIoT Networks: A Full-Stack End-to-End AnalysisThis paper addresses the problem of enabling inter-machine ultra-reliable low-latency communication (URLLC) in 5th generation (5G) NR Industrial Internet of Things (IIoT) networks. In particular, we consider a common Standalone Non-Public Network (SNPN) architecture proposed by the 5G Alliance for Connected Industries and Automation (5G-ACIA), and formalize a full-stack end-to-end (E2E) latency analysis where semi-persistent uplink scheduling is considered in detail and compared with a baseline grant-based approach. Through simulations, we demonstrate that semi-persistent scheduling outperforms the baseline scheme and provides an E2E latency below 1 ms, thereby representing a desirable solution to allocate resources for URLLC. Notably, we provide numerical guidelines for dimensioning 3GPP-compliant IIoT networks for both periodic and aperiodic traffic applications, and as a function of the number of machines in the factory and of the offered traffic.VT3
TD(22)02049Werner G. Teich and Weikun PanDecoding of Convolutional Codes with Convolutional Neural Networks: Performance and Generalization PropertyIn the last decade, convolutional neural networks (CNNs) have shown impressive results in various fields such as image classification, speech recognition, or playing the abstract strategy board game \emph{Go}. Recently, also an increased interest in the application of deep neural networks (DNNs) to physical layer problems in digital communications can be observed. We focus on the decoding of convolutional codes (CCs). Compared to other use cases, an unlimited amount of labeled training data can be generated. However, the number of code words to be learned increases exponentially with the dimension of the code. Therefore a good generalization property is desirable.  
We use a CNN for the decoding of terminated CCs. Specifically we train a CNN for a CC with low dimension. As the CNN is matched to the dimension and structural properties of the CC, the CNN actually learns the structure of the CC. The CNN decoder can therefore easily be adapted to larger code dimensions, i.e.~it can decode code words it has never seen during the training process.
TD(22)02050Cezary Adamczyk, Adrian KliksConflict Detection Framework for Conflict Mitigation in O-RAN nRT-RICSteady evolution of the Open RAN concept brings light to xApps and what are their potential use-cases in the O-RAN-compliant deployments. There are several fields of xApp utilisation that are being investigated, but the issue of detecting conflicts between decisions requires further in-depth investigation. The article defines a Conflict Detection Framework built into the existing O-RAN architecture; it enables the Conflict Mitigation component in O-RAN’s Near-Real Time Radio Intelligent Controller (nRT-RIC) to reliably detect all three conflict types distinguished in the O-RAN Alliance’s Technical Specifications. Precise flows of messages between nRT-RIC’s components are described for detection of each conflict type. Finally, example messages processed in operation of the proposed framework have been provided. It is concluded that defining a unified Conflict Detection Framework for all conflict types in nRT-RIC is the first step to provide a standardised method of conflict mitigation in O-RAN environments.WG3
TD(22)02051Haibin Zhang, Yohan Toh, Iñaki Martin Soroa, Donal Morris, Marie-Pauline Roukens5G Video and Vital Data Communication for Ambulance ServicesThe use of real-time video-audio and vital patient data significantly improves the effectiveness of remote assessment in emergencies, compared with the current audio-only pre-hospital communications. This was found during recently completed 5G trials, involving ambulance professionals. The aim of the trials was to investigate how 5G-enabled video-audio and vital patient data monitoring can benefit remote patient assessment and what are the potential implementation constraints. An indoor 5G standalone network was used for the trials, with measured round-trip time as low as 7 ms. With the trials, it was verified that the decision making was quicker and more accurate when the remotely based Chief Medical Officer of an ambulance service received real-time video-audio complimented with vital patient data (for example electrocardiogram) from the paramedic. This meant that the pre-hospital triage significantly improved accelerating patient treatment and avoiding unnecessary conveyance to the hospital. Recommendations are also given addressing the observed implementation constraints.VT1
TD(22)02052Agnes Koller, Klaus WitrisalSignal-to-Interference-plus-Noise-Ratio Radio Maps for Anchor Selection in Harsh EnvironmentsImproving performance and resource-efficiency for reliable and highly accurate indoor radio positioning in challenging environments is a problem of great interest to the research community. This applies especially if the number of anchors is scaled up in a large-scale deployment, and if harsh radio channel conditions apply, e.g. dense multipath propagation. However, little is known about determining the minimum anchor configuration to achieve targeted performance metrics. In this study, we evaluate criterion-based performance metrics in harsh environments by applying a geodetic network optimization algorithm. A radio environment map (REM) is formulated, based on a signal-to-interference-plus-noise ratio (SINR), to quantify for each anchor the expected measurement accuracy throughout the environment. These SINR REMs are used as an input for the proposed algorithm. We have found that performance metrics can be achieved by reducing the number of anchors. The results also show that radio environment maps can maximize the localization precision, while minimizing the number of distance measurements needed, which is highly beneficial for the scalability of location-aware indoor-positioning systems.WG1,WG2
TD(22)02053Marcin Hoffmann, Pawel KryszkiewiczReinforcement Learning for Energy-Efficient 5G Massive MIMO: Intelligent Antenna SwitchingTo provide users with high throughputs, the fifth generation (5G) and beyond networks are expected to utilize the Massive Multiple-Input Multiple-Output technology (MMIMO), i.e., large antenna arrays. However, additional antennas require the installation of dedicated hardware. As a result, the power consumption of a 5G MMIMO network grows. This implies, e.g., higher operator costs. From this angle, the improvement of Energy Efficiency (EE) is identified as one of the key challenges for the 5G and beyond networks. EE can be improved through intelligent antenna switching, i.e., disabling some of the antennas installed at a 5G MMIMO Base Station (BS) when there are few User Equipments (UEs) within the cell area. To improve EE in this scenario we propose to utilize a sub-class of Machine Learning techniques named Reinforcement Learning (RL). Because 5G and beyond networks are expected to come with accurate UE localization, the proposed RL algorithm is based on UE location information stored in an intelligent database named a Radio Environment Map (REM). Two approaches are proposed: first EE is maximized independently for every set of UEs’ positions. After that the process of learning is accelerated by exploiting similarities between data in REM, i.e., the REM-Empowered Action Selection Algorithm (REASA) is proposed. The proposed RL algorithms are evaluated with the use of a realistic simulator of the 5G MMIMO network utilizing an accurate 3D-Ray-Tracing radio channel model. The utilization of RL provides about 18.5% EE gains over algorithms based on standard optimization methods. Moreover, when REASA is used the process of learning can be accomplished approximately two times faster.WG2
TD(22)02054Mina Aghaei Dinani, Adrian Holzer, Hung Nguyen, Marco Ajmone Marsan,Gianluca RizzoA Gossip Learning Approach to Trajectory Nowcasting in Urban ScenariosNowcasting, i.e., short-term forecasting, of end user location is becoming increasingly important for anticipatory resource management in radio access networks (RAN). In this work, we look at the case of vehicles moving in dense urban environments, and we tackle the location nowcasting problem with a particular class of machine learning (ML) algorithms that goes under the name Gossip Learning (GL). GL is a peer-to-peer machine learning approach based on direct, opportunistic exchange of models among nodes via wireless device-to-device (D2D) communications, and on collaborative model training. It has recently proven to scale efficiently to large numbers of static nodes, and to offer better privacy guarantees than traditional centralized learning architectures. We present new decentralized algorithms for GL, suitable for setups with dynamic nodes. In
our approach, nodes improve their personalized model instance by sharing it with neighbors, and by weighting neighbors’ contributions according to an estimate of their marginal utility.
Our results show that the proposed GL algorithms are capable of providing accurate vehicle position predictions for time horizons of a few seconds, which are sufficient to implement effective anticipatory radio resource management.
TD(22)02055Jesus Argote-Aguilar, Florin-Doru Hutu, Guillaume Villemaud, Matthieu Gautier and Olivier BerderRF energy harvesting strategy for the power supply of a wake-up radio circuitNowadays, the efficiency of the Radio-Frequency (RF) energy harvesting circuits is continuously increasing and, at the same time, the energy consumption of connected devices is drastically decreasing. Despite that, collecting, storing and delivering such kind of harvested energy to the device in an appropriate manner is still a challenge. This paper focuses on a strategy of harvesting energy in an efficient way from both low and high levels of the RF field. The objective is to power an ultra-low power consumption wake-up radio requiring a regulated voltage. The starting point is the characterization of a commercial power management integrated circuit which operates with ultra-low power levels. Then, some design guidelines of the RF power rectifiers, specifically designed for our envisaged application are given.WG3,VT3,VT4
TD(22)02056Amaury Paris, Leonardo S. Cardoso, Jean-Marie GorceSlotted, synchronised and modular framework for the evaluation of channel access policies in dense IoT network using FIT/CorteXlabIoT transmissions suffer from extensive collisions when an ALOHA-style transmission policy is used. The study of new decentralized channel access policies are promising to reduce  energy consumption, latency and errors due to retransmission induced by such collisions. In this paper we describe a modular and open-source slotted framework for multi-user access protocols developed in GNU radio environment. Each node transmission to the base station is made in a shared slotted time-frame where a decentralized access policy determines which slot to use. Then, a modular and replaceable physical (PHY) layer is used to create the transmitted signal.
The IoT network can be either emulated on a local computer with a simulated channel or deployed in the FIT/CorteXlab testbed where slot synchronisation between all nodes is provided by a clock distribution module.
TD(22)02057Angesom Ataklity Tesfay, Eric Pierre Simon, Sofiane Kharbech, and Laurent ClavierDeep Learning-based receiver for Uplink in LoRa Networks with Sigfox InterferenceThe Internet of Things faces a significant scaling issue due to the rapid growth of the number of devices and asynchronous communications. Different technologies in the license-free industrial, scientific, and medical (ISM) band have been widely deployed to fill this gap. LoRa and Sigfox are the most common. Many devices can use the ISM band if they obey the regulations and cope with internal and external interference. However, when there is massive connectivity, the effect of the inter and intra-network interference between multiple networks is significant. This study uses a deep learning-based technique to decode signals and deal with the interference in the uplink of a LoRa network. Two classification-based symbol detection methods are proposed using a deep feedforward neural network (DFNN) and a convolutional neural network (CNN). The proposed receivers can decode the signals of a selected user when many LoRa users transmit simultaneously using the same spreading factor over the same frequency band (intra-spreading factor interference), and multiple Sigfox users interfere (inter-network interference). Simulation results show that both receivers outperform the conventional LoRa receiver in the presence of interference. For a target symbol error rate (SER) of 0.001, the proposed DFNN and CNN-based receivers attain around 2 dB and 3.5 dB gain, respectively.WG2
TD(22)02058Alix Jeannerot, Malcolm Egan, Lélio Chetot, Jean-Marie GorceMitigating User Identification Errors in Resource Optimization for Grant-Free Random AccessIn grant-free random access, a key question is how devices should utilize resources without coordination. One solution to this problem are schemes where devices randomly select time-slots based on an optimized allocation matrix. However, the optimization of this allocation matrix requires accurate knowledge of which devices have been active in previous frames. Unfortunately, user identification algorithms are subject to errors, which can strongly impact the expected throughput of the optimized allocation. In this paper, we propose algorithms that mitigate the impact of user identification errors. We show that when the activity distribution with and without errors is known, then our algorithm converges with probability one. When this knowledge is not available, we introduce new theoretically motivated heuristics which significantly improve the expected throughput over existing algorithms and approach the performance when errors are not present.WG2
TD(22)02059Salim Janji, Adam Samorzewski, Małgorzata Wasilewska, and Adrian KliksOn the Placement and Sustainability of Drone FSO Backhaul RelaysWe consider free-space optical (FSO) communication links for the backhaul connectivity of small cells (SCs) where a UAV with an FSO apparatus can serve as a backhaul relay node. We demonstrate how such drone relay stations (DRSs) can be deployed in a high-rise urban area in order to provide FSO line-of-sight (LOS) links that are unobstructed by buildings.
Also, in our solution we consider the case where solar panels are mounted on DRSs such that placing the DRS in a sunny location is prioritized, and we show the gain in terms of number of required trips to recharge the UAV.
TD(22)02060Pasi Koivumäki, Katsuyuki HanedaPoint Cloud Ray Launching Simulation of Indoor Multipath Channels at 60 GHzIn this work we present a novel ray launching method for field prediction utilizing a laser-scanned point cloud model of the environment. The method takes advantage of the high level of detail found in the point cloud to simulate propagation of rays as they undergo reflection and transmission through local surfaces represented by points of the point cloud. The method is implemented using MATLAB’s Parallel Computing Toolbox and its GPU Computing library for straightforward parallelization and acceleration of computations. Indoor multipath channels are simulated at the 60 GHz band and compared to their measured counterparts to study accuracy of the presented method. We show that the method is accurate for single and double interactions, but higher order interactions suffer in accuracy, likely due to compounding effect of errors in estimated reflection and transmission coefficients.WG1,VT4
TD(22)02061Mohammed Mallik, Benjamin Allaert, Joe Wiart, Davy Gaillot, Laurent ClavierEME-GAN : A method to reconstruct Outdoor Electromagnetic Field Exposure Map using image to image translation based on Generative Adversarial NetworkFor fifth-generation (5G) mobile network deployment, radiofrequency electromagnetic field exposure limits have become a critical concern. In specific countries and regions, regulations are not coordinated and it goes far off the guidelines set by the World Health Organization (WHO) and International Commission on Non-Ionizing Radiation Protection (ICNIRP) . Moreover, accurate radiofrequency received power estimation and electromagnetic field exposure map reconstruction in a geographic region is computationally expensive and a challenge. This paper presents a fast and accurate deep learning method to reconstruct outdoor electromagnetic field exposure map using an adversarial image to image translation network. In this work, signal power is converted into pixel intensity of an image and power map estimation task is transformed into a image to image translation task using adversarial network. The proposed EME-GAN algorithm learns and uses accurate radio propagation characteristics from the training process and simulation results shows that trained adversarial image to image translation network produces more accurate estimation than the conventional method.Sub-VT1
TD(22)02062Dheeraj Raja Kumar, Carles Anton-Haro, Xavi MestreDeep Learning-based Channel Estimation and Data Detection for Multi-Antenna SystemsIn this paper, we investigate how to efficiently design a point-to-point multi-input multi-output (MIMO) system by using deep neural networks (DNNs). The first DNN performs MIMO channel estimation (regression task), and the resulting estimate is then fed to the second DNN that performs symbol detection (classification task). Simulation results show that the proposed scheme outperforms the conventional zero-forcing detector benchmark and is close to (optimal) max-likelihood detector. The analysis also includes an extension of the use of DNNs for symbol detection in a downlink rate splitting multiple access (RSMA) setting. RS approaches involve a common message to be decoded by all the users, followed by their respective individual private messages. Here, the use of two successive DNNs has been evaluated for addressing successive interference cancellation (SIC) and symbol detection for users in such RSMA settings.WG2
TD(22)02063Andres Navarro, Leonardo Vargas, Adriana Arteaga, Patricia Madrinan, Nicolas Salazar, Hugo Juan Camilo Clavijo-MoranKinect v2 and Orbbec Astra Pro Cameras for Gait Analysis: a Preliminary ComparisonIn this paper, we compare the concordance in spatiotemporal variables from two RGB-D cameras with the aim to assess similarity and interchangeability. For this, we obtain measurements for two devices, the Orbbec Astra Pro and MS Kinect v2, which has been validated in previous studies. Then, we apply previously tested DSP methods to obtain spatiotemporal variables from gait and arm signals. Finally, we compare the results obtained using both devices with a statistical test to measure the concordance between both groups of variables. The results obtained suggest that this new and unexplored RGB-D camera could be used to measure some spatiotemporal variables, relevant in the clinical context and useful for rehabilitation, although with some disadvanteges respect the Kinect v2.VT1
TD(22)02064Andres Navarro, Leonardo Vargas, Adriana ArteagaA Critical View About Connecting the Unconnected with 6GIn this paper, we make a quick view of the challenges that we face in remote rural areas in the “Global South” to provide connectivity and make acritical analysis about the proposal made in some 6G documents about this matter. We will discuss some ideas regarding the use of low bands like VHF or TV UHF with advanced 3GPP technologies vs the use of more conservative approaches.WG1,WG3
TD(22)02066Botond Tamás Csathó, Bálint Péter HorváthFinite Element Method-based Analysis of Controlled Reflections from RISIn this paper, we analyze the reflection from a reconfigurable intelligent surface
with the finite element method. The studied design is based on an already realized prototype described in the literature. We only consider periodic configurations; consequently, the possible directions of propagation correspond to discrete modes. Subsequently, we tune the surface to have a propagating mode delivering significant power dissimilar from the specular. Based on the reflection properties of one meta-atom, we create a control parameter set. Afterward, scenarios with different period sizes are considered, and with an exhaustive search, we identify advantageous configurations that enable anomalous reflection and cause minimal interference.
TD(22)02067Diego Dupleich, Alexander Ebert, Giovanni Del Galdo, Reiner ThomäMeasurement-based Analysis of Multi-band Assisted Beam-forming at mmWave in Industrial ScenariosThe mmWave and sub-THz bands are foreseen as candidates to achieve the data-rate demands in the beyond 5G and 6G wireless communication networks. The co-existence of multiple radio interfaces at several bands enables data fusion and the utilization of the similarities and differences on propagation and system properties for communication and sensing applications. MmWave radio interfaces rely on directive beams that require high training overhead for beam steering. Sensors in the network infrastructure and co-located radio interfaces at sub-6 GHz and mmWave can be used to assist the beam-forming process at mmWave. In the present paper we investigate the performance of multi-band assisted beam-forming in an industrial environment. We empirically demonstrate from real-world measurements that even in NLOS, the direction of the beams estimated at sub-6 GHz can be used to established a link at mmWave.WG1,Sub-WG1,WG2
TD(22)02068Pekka Kyösti, Peize Zhang, Mar Francis de Guzman, Katsuyuki Haneda, Nuutti Tervo, Aarno PärssinenBeamforming Impact on Delay Spread in Measured D-Band Radio ChannelsTime dispersion of the radio channel is an important characteristics in waveform and other system design of wireless communication links. In this TD we present delay spreads and maximum excess delays analysed using data from single directional propagation measurements at 141-145 GHz radio frequency both in outdoor and indoor environments. Since upper mm-wave radio links necessitate high antenna gains, we consider beam steered radio channel as the basis of our analysis, i.e., beam gains are multiplied with the measured propagation path gains prior to the analysis. Preliminary results show 1.5-11 ns median rms delay spreads and 85-105 ns median values of maximum excess delays, depending on the LOS/NLOS condition, environment, link distance, and used beam width.WG1
TD(22)02069Teodora Kocevska, Tomaž Javornik, Aleš Švigelj, Ke Guan, Aleksandra Rashkovska Koceva, Andrej HrovatML algorithms comparison and hyperparameters tuning for wall material prediction based on CIR dataFor specific design and planning of an indoor radio system, optimization of wireless networks and development of new radio services a detailed knowledge of the indoor site (geometry, materials, furniture, other objects etc.) is required. In the area of indoor characterization, much research has been done on geometry mapping based on surrounding scanning. One of the open research questions is how to improve the environmental description with information about the materials used for the faces constraining the space. The use of established ML approaches and propagation data collected from indoor radio links labeled with the material of each face is one possible research direction. In this paper we describe the procedure for generating an indoor propagation dataset from square rooms with different sizes and labeling it with the wall materials, select features based on radio-propagation expertise, and use nested cross-validation to tune the hyperparameters of four machine learning algorithms and to compare their performance in different scenarios regarding the room size. Our results show that the collected propagation data contains signature of the indoor environment and common ML algorithms can extract knowledge from it, however the prediction performance depends on the link positions relative to the walls.WG1,Sub-WG1,VT4
TD(22)02070Wim Kotterman, Reiner ThomäReverberance in Projection-OTA set-upsProjection-OTA uses reconfigurable passively reflecting screens for emulating spatio-temporally variant EM fields as an alternative to wave-field synthesis or radiated two-stage testing. Consequently, (large) reflecting structures surround the device under test, potentially introducing reverberance in an otherwise anechoic room. This TD investigates the relation between geometry and the reverberance it causes.WG1
TD(22)02071Adam Samorzewski, Adrian KliksEnergy models for wireless networks with mobile access nodesThe paper considers modeling the energy cycle for mobile access nodes in heterogeneous wireless systems. Access points are drone-type devices that are characterized by the ability to obtain energy from Renewable Energy Sources (RES), and more specifically from solar radiation. The simulation tests were conducted in order to check the amount of energy generated by a drone-type device in relation to its energy demand at a given time of the day and year. In order to diagnose the impact of weather conditions on the amount of obtained energy, the absorption of solar radiation for various types of sky cloudiness was also taken into account.WG1,WG3
TD(22)02072Bing Xue, Pasi Koivumäki, Lauri Vähä-Savo, Katsuyuki Haneda, Clemens IchelnImpacts of Real Hands on 5G Millimeter-Wave Mobile Phone Antennas: Measurements and Electromagnetic ModelsMobile terminals into markets require their robust operation in time-varying radio environments, especially for millimeter wave communications. Human effects on cellphones are very important changes in physical environments, which influence the communication qualities to a large extent. Among human effects, hand effects on antenna arrays of mobile phones are crucial and direct. In this paper, a measurement method and measurement justifications of real hand effects are studied. Firstly, two frequencies (28 GHz and 39 GHz) are chosen to design antenna arrays on a cellphones chassis, respectively. The near field scanning of the two prototypes is implemented to obtain the loss because of feed lines, measurement system, and so forth.  Simplified models of them for simulations are built up and make a comparison with measurement results in terms of radiation patterns in free space. Next, the measurement approach of real-hand effects is proposed and the measurements of antenna arrays with hand effects are done. The measurement results have a close agreement with simulation results from far field data and near field data. The whole experiment can indicate that the hand modeling method is valid and measurement approach is proper, which can be used in hand effects in the future.WG1,Sub-WG1,Sub-VT1
TD(22)02073Stefano Moro, Vineeth Teeda, Davide Scazzoli, Luca Reggiani, Maurizio MagariniUAV-based Localization of a Ground RF Emitter in 865 MHz and 2.4 GHz Bands with RSSI measuresUnmanned Aerial Vehicles (UAVs) can be used in several applications as low altitude platforms. In this paper, we propose their use to localize a ground Radio Frequency (RF) emitter by collecting the Received Signal Strength Indicator (RSSI) measures at different positions. The work’s main contribution consists of the definition of an experimental setup for the simultaneous measures of RSSI and UAV position. An actual transceiver takes the RSSI measures, the Adalm Pluto Software Defined Radio (SDR) development board, programmed with
the open-source software GNU Radio. The GPS and Inertial Measuring Unit (IMU) sensors on the
the drone provides the position. The measures are acquired in two different unlicensed bands, the 865 MHz Short Range Device (SRD) and 2.4 GHz Industrial Scientific Medical (ISM). The SRF band is exploited to collect RSSI measures with less interference than the ISM measures where different interference sources are present (e.g. Wi-Fi access points and UAV controller). A maximum likelihood (ML) algorithm is applied to the collected data to estimate the transmitter location. We show that, for the considered setup, the mean absolute localization error is around 4 m without interference and 5 m with interference. A threshold-based technique is proposed to improve the accuracy in the presence of interference.
TD(22)02074Greta Vallero, German Castellanos, Michela Meo, Margot Deruyck, Wout JosephCooperative Caching in Unmanned Aerial Vehicle Base Station NetworksMounting the Base Station (BS) equipment on Unmanned Aerial Vehicles (UAV)  is considered an effective solution  to dynamically provide additional capacity, content providers and computing servers, in order to bring these platforms in proximity to users and meet the large traffic demand and the strict delay requirement of some applications. The solution is promising, but the challenge related to the frequent saturation of the backhaul (BH) link, needed for the communication between them and the Core Network (CN) has to be addressed. In our previous works, we propose the usage of the Multi-Access Edge Computing (MEC) technology, consisting of the placement of servers, providing computing platforms and storage, directly at the edge of these networks, e.g. on the UAV-BSs. In order to improve the performance of this solution, in this paper, we use cooperative caching, which leverages the enlargement of the set of cached contents. To further exploit it, different dedicated MEC cache update strategies and user association approaches are proposed, which allows users to be served by different UAV-BSs, based on the contents they require and contents which are cached on each UAV-BS.WG3,VT4
TD(22)02075Carsten SmeenkICAS Simulation FrameworkIn integrated communication and sensing (ICAS), the radar and communication functionality share the same channel and resources. Therefore resource allocation strategies are needed to satisfy radar and communication performance simultaneously. This TD introduces an ICAS simulation framework to quantify the ICAS performance in a mobile network for a given multi-dimensional resource allocation to develop new ICAS resource allocation strategies. The considered domains are time-frequency, spatial, and network. The aim is to have an appropriate trade-off between computational complexity and realistic results for proper training of machine learning techniques. Therefore the ISAC-nodes base stations (BS), user equipment (UE), and radar targets are represented in a geometrical environment to determine the relevant channel parameters, while clutter components are modeled stochastically. Furthermore, ICAS signal processing steps are implemented in a modular way. This End-to-End simulation allows the evaluation of the ICAS performance in terms of detection and data transmission by modeling effects like multi-path propagation and the impact of antenna directivity.WG2
TD(22)02076Steffen Schieler, Sebastian Semper, Reza FaramarzahangariGrid-free Parameter Estimation using Convolutional Neural NetworksParameter estimation with multiple signal sources is a common signal processing task in many applications, such as radar localization or array signal processing.
Recent publications have introduced the use of deep neural networks as a promising technique in this area by demonstrating their use to estimate parameters on a predefined grid.\par
In contrast, this work demonstrates a grid-less approach capable of direct parameter estimation without on-grid limitations.
Our approach combines deterministic and well-established pre-processing steps to reduce the network complexity and combine existing signal processing techniques in a novel fashion.
It does not require a prior estimate of the number of sources, giving it a distinct complexity advantage compared to existing solutions.
TD(22)02077Jozef Lukac, Jan SykoraDetection of XOR HNC map of 2 nonsynchronous BPSK sources in H-MAC — testbed verificationIn the report, we deal with the detection of symbol-wise xor HNC map of 2 non-synchronous BPSK sources. The relative delay of frames is an integer multiple of the symbol period. We assume the second source to be delayed by n0 symbols w.r.t. the first source. It is shown that the detection can be decomposed to n0 independent subsequences/parts; further we propose three approximate detectors. Next we show that singular fading that is resolved by HNC map for synchronous sources is not resolved for channels with integer-symbol-period delay for the same HNC map. Neither simple differential encoding will help to resolve it. Finally, we mention that a HNC map should also resolve singular fading in the H-MAC channel with delay and we propose one such simple HNC map — the map with cyclic shift of one frame. A demonstration of the detection on experimental testbed is presented.WG2
TD(22)02078M. Fabiani, E. M. Vitucci, V. Degli-EspostiRAY-BASED EVALUATION OF RF COVERAGE IN PRESENCE OF LARGE INTELLIGENT SURFACESIn the present work a Huygens-based, antenna-array-like macroscopic model for scattering from metasurfaces is described, embedded into a ray tracing tool and used to perform realistic RF coverage evaluations in a reference indoor environment. In particular the RF-coverage gain that can be obtained by using a distribution of anomalous reflectors or a single, 4x2m focalizing reflector on a building wall is evaluated. Results show that a gain of about 10-15 dB can be achieved in the first case and of up to 20 dB in the second case in term of average or peak path-loss reduction, respectively.WG1
TD(22)02079Kenan Turbic, Luis M. CorreiaOn the Second-Order Statistics of Non-Stationary Channels: Off-Body Communications PerspectiveThis paper considers second-order statistics of non-stationary channels with arbitrary mobile antenna motion, by relaxing the constant velocity assumption inherent to stationary channel models. By assuming obstructed Line-of-Sight and horizontal signal propagation, analytical expressions for the Level-Crossing Rate (LCR) and Average Fade Duration are derived for non-uniform isotropic scattering scenarios with Von Mises Distribution of angles of arrival. The obtained expressions are employed to investigate an off-body communications scenario with the user walking and the wearable antennas placed on the torso, wrist and lower leg. While the torso antenna yields an essentially stationary channel, for the latter two antenna locations the fading dynamics change periodically over the walking cycle. Two distinct phases with faster and slower signal variations are observed, with the former yielding 4.64 times higher LCR for the lower leg antenna.WG1,VT1
TD(22)02080Hussein Ezzeddine, Julien Huillery, Arnaud Bréard and Yvan DurocA Waveform Design Methodology for UHF RFID Systems: A Hybrid Simulation ApproachIn this work, we propose a waveform design methodology for ultra-high frequency radio frequency identification (UHF RFID) systems based on the quantitative analysis of the backscattered signal. Specifically, the backscattered response of the UHF RFID tag is leveraged to, first, probe the wireless propagation channel, then, allocate power accordingly to frequency components, and finally, design channel-adaptive multisine signals. UHF RFID system performance is evaluated based on the DC power harvested at the output of the rectifying circuit of the RFID tag. To this end, a flexible hybrid simulation model with modular architecture is developed via the ANSYS platform to study UHF RFID system performance. Simulation results show that the designed waveforms provide improved energy efficiency, especially in highly reflective environments.WG1,WG2
TD(22)02081Francesca Conserva, Roberto VerdoneMathematical Description of User Satisfaction for UAV-Aided Vehicular NetworksFuture mobile radio networks require a degree of flexibility that technologies like Unmanned Aerial Vehicles (UAVs) (a.k.a. drones) carrying Base Stations (BSs) can provide. In particular, UAVs acting as flying BSs create what we can refer to as the 3D Networks paradigm. In this perspective, we foresee the employment of Unmanned Aerial Base Stations (UABSs) to enable indirect V2V (Vehicle-to-Vehicle) communications via drones. In this way the vehicular users can enhance the perception of their surroundings beyond what their own sensors can detect, running extend sensing applications. The objective of this work is to built a mathematical model that provides the vehicular users’ satisfaction in terms of offered user throughput. This latter is analyzed and compared for different values of involved parameters such as those related to the UAV’s on-board antenna design. Moreover, the evaluation of the latency for the uplink transmission, together with the introduction of the user Access Probability, allowed to measure the impact of the beam sweeping interval duration upon the network performance. Therefore, numerical results provide optimal values for some of the design parameters (such as the UABS’ aperture angle, the number of UABS’ antenna active beams and the UABS altitude), allowing to reach the desired level of user satisfaction.WG3
TD(22)02083Yann Maret, Jean-Frederic Wagen, Mohsin Raza, Franck Legendre, Junyuan Wang, Nik BessisSimple flow control approach in MANETs for acknowledged message serviceCongestion in wireless communication system can be mitigated by an appropriate routing algorithm assuming a basic resource allocation scheme. The traffic can be rerouted using alternative routes to avoid local congestion in a network. The resource on node can serve the incoming user traffic to forward the packets to the next neighbour. A limited number of resources are available to send and retransmit the user traffic. The large incoming user traffic can congest the network locally even with an efficient routing protocol. Before devising a novel flow control mechanism or improving on a better flow control scheme than TCP, the effect of simple but omniscient flow control is of interest. The paper presents a simple flow control approach for time varying user traffic in dynamic MANETs. The Omniscient Flow Control (OFC) mechanisms mitigates the congestion on nodes by reducing the traffic generated by the source nodes. OFC is able to detect unreachable links and it prevents data losses between disconnected clusters. Preliminary performance has been conducted on the vignette 2 Anglova CP1 scenario with an omniscient routing protocol and OLSRv2d. The assessments have been performed with and without fading. Work in progress reported.WG3
TD(22)02084Jean-Frédéric Wagen and Yann MaretWG1&3 INTERACTions on realistic pathloss and fading for emulations and simulations: how to do it?In WG3, accurate multiusers system simulations or emulations appears to be increasingly important to demonstrate the benefits or limitations of new schemes in all advanced communications systems. In WG1, accurate modeling of the radio propagation and of the radios Tx/Rx characteristics are of major interest. As ideal as impractical: WG1 would measure single links and WG3 would use measurement replays. With current computing power channel models using building, terrain and usage maps is only slightly less impratical. Statistical channel models are then derived but usually only for single links and usually not for mobile to mobile links. Multiusers systems simulations use (1) a Probability Of Reception (POR = 1-Packet Error Rate)-vs-SINR fitted to the radio system and the environment, including short term fading, and (2) a simple, or complex, path loss model in dB with or without an additional Gaussian random variable to simulate the effect “slow” fading.
Some results from past TDs and new results from the realistic Anglova.net MANET scenario will be discussed. Providing our “fading datasets” might be of interest: to be discussed too.
TD(22)02085Julian Karoliny, Thomas Blazek, Hans-Peter Bernhard, Andreas SpringerPredicting the Channel Access of Bluetooth Low EnergyBluetooth Low Energy (BLE) is one of the key enablers for low-power and low-cost applications in consumer electronics and the Internet of Things. The latest features such as audio and direction finding will introduce more and more devices that rely on BLE for communication. However, like many other wireless standards, BLE relies on the unlicensed 2.4\,GHz frequency band where the spectrum is already very crowded and a channel access without collisions with other devices is difficult to guarantee. For applications with high reliability requirements, it will be beneficial to actively consider channel access from other devices or standards.
In this work, we present an approach to estimate connection parameters of multiple BLE connections outside our control and knowledge by passively listening to the channel. With this, we are able to predict future channel access of these BLE connections that can be used by other wireless networks to avoid collisions. We show the applicability of our algorithm with measurements from which we are able to identify three unknown BLE connections, reconstruct their specific connection parameters, and predict their future channel access.