Cellular vehicle-to-everything (C-V2X) facilitates direct communication between vehicles and other user equipment (UE) to improve the efficiency of the Internet of vehicles communication through sidelink. In addition, in the new radio vehicle-to-everything (NR-V2X) Mode 2, users can automatically select resources using the conventional sensing-based semi-persistent scheduling (SB-SPS) resource selection algorithm. This mechanism allows users to generate a list of available resources after a sensing window, after which the users can randomly select resources, and the resource can be used continuously over multiple periods before reselection. However, during the sensing window, neighbors may generate a similar list of available resources, and random selection may lead to resource conflicts. This phenomenon may lead to deteriorated communication performance and increased latency due to incorrect reception. Therefore, this paper proposes a reuse distance-aided resource selection (RD-RS) method which integrates resource reuse distance judgement with SB-SPS to mitigate resource conflicts and interference caused by random selection. Moreover, the reuse distance judgement is performed before the final resource selection, and whether the user will select the current resource depends on the reuse distance between that user and other occupiers. Furthermore, the performance of the proposed scheme is compared with other algorithms. Simulation results show that the proposed RD-RS not only achieves a higher packet reception ratio (PRR) but also effectively reduces the inter-packet gap (IPG). Moreover, in specific scenarios, the proposed method outperforms conventional schemes by 9% in terms of PRR and 70% in terms of Range.
An integral equation-fast Fourier transformation (IE-FFT) with grid-robust higher order vector basis functions (BFs) are presented. A conformal mesh is required for traditional BFs based on common edges between adjacent elements. This is a very rigorous requirement for large and complicated electrical geometries. Instead of a conformal mesh, grid-robust higher-order vector BFs are used here. It maintains the flexibility of geometry modelling and reduces the number of the unknowns owing to the property of point BFs. An IE–FFT algorithm based on a flexible floating stencil topology is proposed to accelerate the solution of the IE. Comparing the IE–FFT with traditional RWG BFs, the present method has a much lower error of interpolation, and the matrix is also simpler to implement. Numerical results are presented to demonstrate the accuracy and efficiency of this method.
Cellular vehicle-to-everything (C-V2X) enables short-distance communication between vehicles and other users to improve road safety through data sharing. Conventional research on C-V2X typically assumes that vehicles travel at the same speed with a fixed inter-vehicle distance (). However, this assumption does not reflect the real driving environment or promote road traffic efficiency. Conversely, assigning different speeds to vehicles without a structured approach inevitably increases the collision risk. Therefore, determining appropriate speeds for each vehicle in the C-V2X framework is crucial. To this end, considering the road environment and mobility, this study introduces an adaptive speed mechanism based on the congestion level of a zone and . First, the given scenario is divided into several zones. Subsequently, based on the congestion level of a zone and the level, an adaptive speed is defined for each vehicle. This approach ensured that vehicles adopt lower speeds in congested situations to reduce the collision probability and higher speeds in sparse traffic cases to improve traffic efficiency. The performance of the proposed adaptive speed scheme is compared with that of conventional fixed-speed settings. The results show that the adaptive speed control scheme outperforms conventional fixed-speed schemes in terms of the packet reception ratio (PRR) and collision ratio (CR). Specifically, the proposed mechanism can reduce the CR to 0 and ensure that the PRR is higher than 0.98 in low-density scenarios.