In 3GPP New Radio (NR) Vehicle-to-Everything (V2X), the new standard for next-generation vehicular networks, vehicles can autonomously select sidelink resources for data transmission, which permits network operations without cellular coverage. However, standalone resource allocation is uncoordinated, and is complicated by the high mobility of the nodes that may introduce unforeseen channel collisions (e.g., when a transmitting vehicle changes path) or free up resources (e.g., when a vehicle moves outside of the communication area). Moreover, unscheduled resource allocation is prone to the hidden node and exposed node problems, which are particularly critical considering directional transmissions. In this paper, we implement and demonstrate a new channel access scheme for NR V2X in Frequency Range 2 (FR2), i.e., at millimeter wave (mmWave) frequencies, based on directional and beamformed transmissions along with Sidelink Control Information (SCI) to select resources for transmission. We prove via simulation that this approach can reduce the probability of collision for resource allocation, compared to a baseline solution that does not configure SCI transmissions.

In this paper, we address the complex task of estimating the parameters for multiple propagation paths of realistic millimeter wave (mmWave) channels. We propose a solution with a reasonable computational complexity while providing high accuracy, which is required for precise positioning in joint localization and communication systems. We introduce an innovative method termed ESPRIT-D - beamspace Estimation of Signal Parameters via Rotational Invariance Techniques with a Dictionary based solution. It exploits a model for the mmWave multipath channel accounting for filtering effects, represented as a 5D tensor. Our solution develops a modification of beamspace ESPRIT that can operate with analog beamforming to extract the directions of departure and arrival in azimuth and elevation, while retrieving the delay estimates by a greedy sparse recovery method. We evaluated the proposed method using channel realizations generated by ray-tracing simulation of an outdoor environment, demonstrating an average angular error below 0.01° for line-of-sight (LoS) paths and 0.1° for nonline-of-sight (NLoS) components. The accuracy in delay estimation achieves an average of$3\mathrm{e}^{-10}\mathrm{s}$. Compared with state-of-the-art (SOTA), our algorithm exhibits a 10× improvement in estimation accuracy.

Neural network (NN)-based receivers for orthogonal frequency division multiplex (OFDM) excel through promising performance and benefits in their applicability. In this paper we analyze their capabilities when they are imposed with practical constraints that have to be considered when implementing such a receiver on hardware. Specifically, we focus on the effects of uniform linear affine quantization and it is shown which performance can be achieved by utilizing quantization-aware training (QAT) with trainable quantizers. In order to reduce the computational complexity of the NN-based receiver different pruning methods are investigated. We showcase that a reduction of the number of floating-point operations (FLOPs) by more than 50% is possible at the cost of less than 0.25 dB difference. Finally, an intuition on joint pruning and quantization is given.

Vehicle to vehicle communication is a part of essential use cases to further improve the vehicular traffic safety and efficiency. The 3rd Generation Partnership Project (3GPP) Rel-16 5G New Radio (NR) sidelink (SL) supports up to 31 blind Hybrid Automatic Repeat reQuest (HARQ) retransmissions for the SL broadcast communication with one of the goals to improve the communication reliability. We simulate a 6 lane highway scenario for low, medium and high traffic density to evaluate the effects of number of HARQ retransmissions on information age (IA). The results indicate a non-linear relationship between number of HARQ retransmissions and the improvement of IA, thus contributing to next stage of selection of appropriate number of HARQ retransmissions. We also analyse the complexities in the existing framework due to various network and system configurations according to Rel-16 standards.

The Intelligent Transportation System has become one of the most globally researched topics, with Connected and Autonomous Vehicles(CAV) at its core. The CAV applications can be improved by the study of vehicle platooning immune to real-time traffic and vehicular network losses. In this work, we explore the need to integrate the Network model and Platooning system model for highway environments. The proposed platoon model is designed to be adaptive in length, providing the node vehicles to merge and exit. This overcomes the assumption that all the platoon nodes should have a common source and destination. The challenges of the existing platoon model, such as relay selection, acceleration threshold, are addressed for highly modular platoon design. The presented algorithm for merge and exit events optimizes the trade-off between network parameters such as communication range and vehicle dynamic parameters such as velocity and acceleration threshold. It considers the network bounds like SINR and link stability and vehicle trajectory parameters like the duration of the vehicle in the platoon. This optimizes the traffic throughput while maintaining stability using the PID controller. The work tries to increase the vehicle inclusion time in the platoon while preserving the overall traffic throuahput.

Wireless Body Area Network (WBANs) would benefit reasonable after the introduction of mmWaves in the communication. The high frequency spectrum can enhance channel capacity and reduce the package area. It however makes the communication link susceptible to noise interference. As the noise level increases, it restricts the use of mmWave spectrum for high SNR level applications. The paper proposes a method of spectrum switching to tap into advantages of mmWave only when necessary thus minimizing the drawbacks on the overall performance. The hybrid approach of using multiple spectrum exploits the characteristics of high channel capacity and high noise immunity which are found at the extreme ends of the spectrum. This paper compares different threshold parameters to conclude SNR as a more reliable factor. We develop an algorithm based on this threshold and simulate spectrum switching from 5 GHz to 60 GHz where the User Equipment is in constant motion over a range of 100 m. We present the graphical results of variance of SNR, Friis model for path loss and numerically prove a significant increase in the average channel capacity using Shannon's theorem while maintaining SNR above the threshold limit. The paper also presents the challenges reflected by this spectrum switching on the supporting parameters like directivity, energy consumption and beamforming array structures.