Federated learning (FL) has been recognized as a transformative approach in vehicular networks, enabling collaborative training between vehicles and preserving data privacy. However, the high mobility and dynamic topology changes inherent in vehicular environments pose significant challenges, primarily due to the increased communication overhead associated with exchanging model parameters. To mitigate these issues, a novel framework for decentralized wireless FL with soft clustering and 1-bit compressed sensing (SC1BCS-WFL) is proposed in this article. The framework considers vehicle position, vehicle attributes, vehicle speed, and model cosine similarity when grouping vehicles. It utilizes an adaptive threshold mechanism based on 1-bit compression to reduce uplink transmission load while maintaining FL performance. In addition, an early stopping strategy is incorporated into the proposed framework to avoid unnecessary waste of computational and communication resources. Simulation results show that the SC1BCS-WFL framework can enhance the efficiency of FL in vehicular settings, particularly with nonindependent and identically distributed data. Simulation results also validate the framework’s ability to reduce communication overhead while achieving high-model accuracy, indicating its suitability for distributed Internet of Vehicles (IoV) scenarios and contributing to the development of smarter and more efficient IoV applications.

Vehicle-to-vehicle (V2V)-enabled platooning is a promising application for future intelligent transportation systems. V2V communications allow real-time sharing of vehicle status information within the platoon, enabling vehicles to dynamically adjust their control strategies and maintain spacing between platoon members. As such, the platoon stability depends on the timeliness of the control information. However, the information timeliness can be affected by factors, such as transmission period, co-channel interference and actuator lag. In this article, the performance of the V2V communication is analyzed for the platooning, from an information timeliness perspective. First, an Age-of-Information (AoI)-based joint communication and control model is proposed to determine the requirement of the AoI to maintain the stability. Then, a large-scale V2V communication model is constructed by taking account of the V2V packet transmission and resource allocation scheme. Considering the spatiotemporal correlation among the V2V transmissions, the distribution of the average AoI and average peak AoI are investigated, by using the queuing theory and stochastic geometry. The analytical results can reveal the proportions of the stable platoons in the large-scale networks. Simulation results corroborate the analytical results and demonstrate the impact of the system parameters on the platoon stability. Furthermore, simulation results showed that the requirements of the maximum transmission period and the maximum actuator lag can be analytically obtained. More importantly, it is shown that the proposed model and the analytical results could provide insightful guidelines for designing the V2V-enabled platooning systems.

With their superior maneuverability and flexible deployment options, unmanned aerial vehicles (UAVs) present a viable solution to augment cellular network capabilities by serving as mobile base stations (BSs). Yet, the 3-D, dynamic nature of UAV deployments, along with changing aerial conditions, often results in frequent handovers, adversely affecting communication quality. Moreover, the impacts of transitions between Line-of-Sight (LoS) and Non-LoS (NLoS) links on handover and coverage probabilities in mobile UAV networks have not been thoroughly investigated. This article provides an in-depth analysis of how multitier deployment altitudes and variations in LoS link probabilities influence handover and coverage probabilities. Utilizing stochastic geometry, we consider two association strategies: 1) distance-based and 2) strongest average received signal strength (RSS)-based. For both strategies, we provide semi-closed-form expressions for handover probability and subsequently derive network coverage probabilities. Through numerical simulations, we not only unearth an optimal configuration of UAV density and deployment altitude that maximizes coverage probability for ground users but also uncover that the relative benefits of the RSS-based association strategy wane as UAV density escalates compared to the distance-based association strategy. Furthermore, our results underscore the potential for enhancing coverage performance by adopting a strategy of deploying UAVs at various altitudes, contrasting with the traditional approach of uniform altitude deployment.

Wireless powered communication (WPC) is able to provide wireless devices (WDs) practically infinite energy by using the radio frequency energy harvesting technique. The electricity of WDs for the wireless information transmission (WIT) is converted from the received electromagnetic signals of wireless energy transfer (WET). Power beacon (PB) is usually deployed as the dedicated energy source in WPC networks and the performance of WET is sensitive to the path-loss effect. Thus, both WET and WIT are significantly influenced by the locations of the PBs. To enable efficient transmission in WPC, this paper analytically investigates the impact of the PB deployment strategies on the WPC performance when WDs are clustered around the access points (APs). Specifically, we propose the PB deployment strategy based on the truncated Poisson cluster process (PCP) model. The distribution of PBs is correlated to the locations of WDs by choosing APs as their common parent points. Then, we derive the semi-closed form expressions for the energy outage probability and the transmission success probability. We further present the expressions of the meta distributions of WET and WIT, and investigate the proportion of the WDs in one cluster that achieves successful transmission while satisfying the reliability constraint. Moreover, the distance distribution between the WD and the intra-cluster PBs is analytically derived for the proposed correlated PCP model. By comparing the performance with other deployment strategies, it is shown that the preference of the PB deployment strategy depends on the PB density. The analytical and numerical results can provide insightful guidelines for designing practical WPC systems.

We present an information-theoretic analysis of a point-to-point Multiple-Input-Multiple-Output (MIMO) link affected by Rayleigh fading and multiple scattering, under perfect channel state information at the receiver. Unlike previous work addressing this setting, we investigate the Random Coding Error Exponent, its associated cutoff rate and the Expurgated Error Exponent, and derive closed-form expressions for them. Moreover, leveraging the average mutual information expression presented in [1], we derive another important metric, namely, the sum rate, under linear receive processing and independent stream decoding. In particular, we characterize the performance of the Minimum Mean Squared Error receiver in closed form, and that of the Zero Forcing receiver by resorting to bounding techniques. The bulk of the work relies on results about finite-dimensional random matrix products, a number of which are novel and detailed in the Appendices. The analysis, validated through numerical results, highlights the severe degradation in the performance of linear receivers due to multi-fold scattering. It also unveils the performance trend of multiple scattering MIMO channels as a function of the number of antennas and the number of scattering stages.

Novel reconfigurable Intelligent Surfaces (RISs) area technology can improve the communication performance by changing the wireless transmission environment. Introducing RIS technology into Vehicle-to-Vehicle (V2V) communication environments can enhance the communication reliability by creating Line-of-Sight (LoS) communication links, thereby effectively improving the communication performance. However, in RIS-assisted V2V large-scale communication networks, the stochasticity of network nodes and random interference can impact performance. In this article, we examine the outage communication transmission performance of an RIS-assisted V2V communication network. We select the signal transmission mode based on the obstacle presence between vehicles and use the stochastic geometry theory to calculate the probabilities of the two modes: direct mode and RIS-assisted mode. By deriving the communication distance distribution and the aggregate interference distribution, we evaluate V2V communication in the direct mode to assess its transmission performance in two scenarios and obtain the overall outage probability. The numerical results demonstrate a better performance in RIS-assisted V2V networks, with an improved optimal phase shift scheme over that of the original V2V network. Monte Carlo simulation validated our analytical findings.