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Charles Wiame

Publications and source records attributed to Charles Wiame.

13 recordsLinked to original sources

Joint Error Correction and Fading Channel Estimation Enhancement Leveraging GRAND

We present a novel method for error correction in the presence of fading channel estimation errors (CEE). When such errors are significant, considerable performance losses can be observed if the wireless transceiver is not adapted. Instead of refining the estimate by increasing the pilot sequence length or improving the estimation algorithm, we propose two new approaches based on Guessing Random Additive Noise Decoding (GRAND) decoders. The first method involves testing multiple candidates for the channel estimate located in the complex neighborhood around the original pilot-based estimate. All these candidates are employed in parallel to compute log-likelihood ratios (LLR). These LLRs are used as soft input to Ordered Reliability Bits GRAND (ORBGRAND). Posterior likelihood formulas associated with ORBGRAND are then computed to determine which channel candidate leads to the most probable codeword. The second method is a refined version of the first approach accounting for the presence of residual CEE in the LLR computation. The performance of these two techniques is evaluated for [128,112] 5G NR CA-Polar and CRC codes. For the considered settings, block error rate (BLER) gains of several dBs are observed compared to cases where CEE is ignored.

cs.IT

Error correction in interference-limited wireless systems

We introduce a novel approach to error correction decoding in the presence of additive alpha-stable noise, which serves as a model of interference-limited wireless systems. In the absence of modifications to decoding algorithms, treating alpha-stable distributions as Gaussian results in significant performance loss. Building on Guessing Random Additive Noise Decoding (GRAND), we consider two approaches. The first accounts for alpha-stable noise in the evaluation of log-likelihood ratios (LLRs) that serve as input to Ordered Reliability Bits GRAND (ORBGRAND). The second builds on an ORBGRAND variant that was originally designed to account for jamming that treats outlying LLRs as erasures. This results in a hybrid error and erasure correcting decoder that corrects errors via ORBGRAND and corrects erasures via Gaussian elimination. The block error rate (BLER) performance of both approaches are similar. Both outperform decoding assuming that the LLRs originated from Gaussian noise by 2 to 3 dB for [128,112] 5G NR CA-Polar and CRC codes.

cs.IT

Full-Duplex V2X Integrated Sensing and Communication Scenario: Stochastic geometry, Monte-Carlo, and Ray-Tracing Comparison

In this paper, performance of an Integrated Sensing and Communication (ISAC) Vehicle-to-Everything (V2X) scenario is evaluated, in which a vehicle simultaneously detects the next vehicle ahead while receiving a communication signal from a RoadSide Unit (RSU) of the infrastructure. Univariate and joint radar and communication performance metrics are evaluated within three different frameworks, namely the Stochastic Geometry (SG), Monte-Carlo (MC), and Ray-Tracing (RT) frameworks. The parameters of the system model are extracted from the RT simulations, and the metrics are compared to assess the accuracy of the SG framework. It is shown that the SG and MC system models are relevant w.r.t. RT simulations for the evaluation of univariate communication and sensing metrics, but larger discrepancies are observed for the joint metrics.

eess.SP

On the Impact of Dynamic Beamforming on EMF Exposure and Network Coverage: A Stochastic Geometry Perspective

This paper introduces a new mathematical framework for dynamic beamforming-based cellular networks, grounded in stochastic geometry. The framework is used to study the electromagnetic field exposure (EMFE) of active and idle users as a function of the distance between them. A novel multi-cosine antenna pattern is introduced, offering more accurate modeling by incorporating both main and side lobes. Results show that the cumulative distribution functions of EMFE and coverage obtained with the multi-cosine pattern align closely with theoretical models, reducing error to less than 2\%, compared to a minimum of 8\% for other models. The marginal distribution of EMFE for each user type is mathematically derived. A unique contribution is the introduction of the SCAIU (\underline{S}patial \underline{C}DF for \underline{A}ctive and \underline{I}dle \underline{U}sers), a metric that ensures coverage for active users while limiting EMFE for idle users. Network performance is analyzed using these metrics across varying distances and antenna elements. The analysis reveals that, for the chosen network parameters, with 64 antenna elements, the impact on idle user EMFE becomes negligible beyond 60~m. However, to maintain active user SINR above 10 dB and idle user EMFE below -50~dBm at 2~m, more than 256 elements are required.

cs.IT

Meta Distribution of Passive Electromagnetic Field Exposure in Cellular Networks

This paper focuses on the meta distribution of electromagnetic field exposure (EMFE) experienced by a passive user in a cellular network implementing dynamic beamforming. The meta distribution serves as a valuable tool for extracting fine-grained insights into statistics of individual passive user EMFE across the network. A comprehensive stochastic geometry framework is established for this analysis. Given the pivotal role of accurately modeling the main and side lobes of antennas in this context, a multi-cosine gain model is introduced. The meta distribution is closely approximated by a beta distribution derived from its first- and second-order moments, which is demonstrated to be mathematically tractable. The impact of the number of antennas in the ULA on the meta distribution is explored, shedding light on its sensitivity to this parameter.

cs.IT

Cellular Load Dependent Sleep Control for Energy Efficient HetNets with Non-Uniform User Distributions

This study proposes a novel stochastic geometry framework analyzing power control strategies in spatially correlated network topologies. Heterogeneous networks are studied, with users modeled via the superposition of homogeneous and Poisson cluster processes. First, a new expression approaching the distribution of the number of users per base station is provided. This distribution defines the load associated with each Voronoï cell, capturing non-uniformities in user locations and correlation to BSs positions. The power allocation is adjusted based on this load, allowing BSs to enter sleep mode when their activity falls below a defined threshold. Furthermore, the propagation model features millimeter wave transmission characteristics and directional beamforming. Considering these aspects, revisited definitions of coverage probability, spectral efficiency, and energy efficiency are proposed. Tractable expressions for these metrics are derived and validated using Monte-Carlo simulations. Asymptotic expressions are also proposed, providing further understanding on the influence of the system parameters. Our numerical results finally analyze the impact of the sleep control on the performance and display the optimal strategies in terms of energy efficiency.

eess.SP

On the Uplink and Downlink EMF Exposure and Coverage in Dense Cellular Networks: A Stochastic Geometry Approach

Existing studies analyzing electromagnetic field (EMFE) in wireless networks have primarily considered downlink communications. In the uplink, the EMFE caused by the user's smartphone is usually the only considered source of radiation, thereby ignoring contributions caused by other active neighboring devices. In addition, the network coverage and EMFE are typically analyzed independently for both the uplink and downlink, while a joint analysis would be necessary to fully understand the network performance and answer various questions related to optimal network deployment. This paper bridges these gaps by presenting an enhanced stochastic geometry framework that includes the above aspects. The proposed topology features base stations modeled via a homogeneous Poisson point process. The users active during a same time slot are distributed according to a mixture of a Mat\'ern cluster process and a Gauss-Poisson process, featuring groups of users possibly carrying several equipments. In this paper, we derive the marginal and meta distributions of the downlink and uplink EMFE and we characterize the uplink to downlink EMFE ratio. Moreover, we derive joint probability metrics considering the uplink and downlink coverage and EMFE. These metrics are evaluated in four scenarios considering BS, cluster and/or intracluster densifications. Our numerical results highlight the existence of optimal node densities maximizing these joint probabilities.

cs.NI

Joint Metrics for EMF Exposure and Coverage in Real-World Homogeneous and Inhomogeneous Cellular Networks

This paper evaluates the downlink performance of cellular networks in terms of coverage and electromagnetic field exposure (EMFE), in the framework of stochastic geometry. The model is constructed based on datasets for sub-6~GHz macro cellular networks but it is general enough to be applicable to millimeter-wave networks as well. On the one hand, performance metrics are calculated for $\beta$-Ginibre point processes which are shown to faithfully model a large number of motion-invariant networks. On the other hand, performance metrics are derived for inhomogeneous Poisson point processes with a radial intensity measure, which are shown to be a good approximation for motion-variant networks. For both cases, joint and marginal distributions of the EMFE and the coverage, and the first moments of the EMFE are provided and validated by Monte Carlo simulations using realistic sets of parameters from two sub-6~GHz macro urban cellular networks, i.e., 5G~NR~2100 (Paris, France) and LTE~1800 (Brussels, Belgium) datasets. In addition, this paper includes the analysis of the impact of the network parameters and discusses the achievable trade-off between coverage and EMFE.

cs.NI

Joint data rate and EMF exposure analysis in Manhattan environments: stochastic geometry and ray tracing approaches

The objective of this study is to jointly analyze the data rate and electromagnetic field (EMF) exposure in urban environments. Capitalizing on stochastic geometry (SG), a network level analysis is performed by modelling these environments via Manhattan Poisson line processes (MPLP). Using this framework, a number of performance metrics are derived: first moments, marginal distributions and joint distributions of the data rate and exposure. In addition, the original Manhattan model is generalized to include advanced features: corner diffraction, presence of potential blockages in streets, and users positioned at crossroads. As a second approach, deterministic ray tracing (RT) is utilized to compute the same metrics. The two methods are shown to provide close results on the condition that the model parameters are coherently selected. Furthermore, the numerical results enable to gain insight into several aspects: the role of the propagation mechanisms in the performance metrics, existing trade-offs between the rate and exposure requirements, as well as the impact of the user location (at a crossroad or in a single street). (This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible)

eess.SP

Joint data rate and EMF exposure analysis in user-centric cell-free massive MIMO networks

The objective of this study is to analyze the statistics of the data rate and of the incident power density (IPD) in user-centric cell-free networks (UCCFNs). To this purpose, our analysis proposes a number of performance metrics derived using stochastic geometry (SG). On the one hand, the first moments and the marginal distribution of the IPD are calculated. On the other hand, bounds on the joint distributions of rate and IPD are provided for two scenarios: when it is relevant to obtain IPD values above a given threshold (for energy harvesting purposes), and when these values should instead remain below the threshold (for public health reasons). In addition to deriving these metrics, this work incorporates features related to UCCFNs which are new in SG models: a power allocation based on collective channel statistics, as well as the presence of potential overlaps between adjacent clusters. Our numerical results illustrate the achievable trade-offs between the rate and IPD performance. For the considered system, these results also highlight the existence of an optimal node density maximizing the joint distributions. (This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.)

cs.IT

Joint Performance Metrics for Integrated Sensing and Communication Systems in Automotive Scenarios

In this paper, multiple metrics are presented in order to jointly evaluate the performance of the 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-lane road with vehicles and smart traffic lights, both equipped with DFRC systems. First, the performance achieved with these 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. Then, the model is extended to include interference cancellation for the radar and/or communication function in all the metrics. Either full interference cancellation is applied, or a new model is proposed for imperfect interference cancellation.

eess.SP

Stochastic Geometry-based Modelling of Mobile UAV Relay Networks under Realistic Fading

We consider a relay network based on Unmanned Aerial Vehicles (UAV). Terrestrial Base Stations (TBS) and UAV Relay Nodes (RN) are modelled using two Homogeneous Poisson Point Processes (HPPP). UAVs can hover at a fixed position or move following specific displacement schemes. The Coverage Probability (CP) of a typical user equipment (UE) is derived, either when it communicates via a direct link (from the TBS to the UE) or via a relay link (from the TBS to the UE through a UAV RN). Every link can be in Line-of-Sight (LoS) or Non Line-of-Sight (NLoS), and suffers from Rician fading with distance-dependent parameters. This coverage is calculated by means of both stochastic geometry (SG) and Monte-Carlo (MC) simulations. The benefits of the use of UAV as RNs are analysed depending on their altitude, density, and mobility scheme.

eess.SP

Stochastic geometry analysis of a distance-based JT scheme in C-RAN

This paper considers a joint transmission scheme (JT) developed for cloud radio access networks (C-RANs). This proposed scheme features cooperative sets of remote radio heads (RRH) defined in a disk around each user location. The nodes belonging to each of these sets perform a weighted maximum ratio transmission to jointly serve the user. The powers allocated to the beamformers are computed at the network baseband unit, taking into account channel gains, as well an equity criterion between the users. In comparison with the existing literature, our model includes a saturation assumption, with all transmissions taking place over the same resource block. A RRH belonging to multiple sets can hence transmit to several users simultaneously. The distributions of the network coverage and spectral efficiency are calculated by means of stochastic geometry (SG), and compared with Monte Carlo simulations. The derived expressions take into account the power allocation, the user and RRH densities, as well as the statistical correlation resulting from the set overlaps.

cs.IT