An MEC-Enabled Framework for Task Offloading and Power Allocation in NOMA Enhanced ABS-Assisted VANETs

Joint Phase Shift Design and Resource Management for a Non-Orthogonal Multiple Access-Enhanced Internet of Vehicle Assisted by an Intelligent Reflecting Surface-Equipped Unmanned Aerial Vehicle

“…The performance of the proposed sum data rate maximization scheme is evaluated via simulation. We compare it with four state-of-the-art works, namely Scheme 1 [21], Scheme 2 [35], Scheme 3 [31], and Scheme 4 [2]. Specifically, Scheme 1 involves the deployment of an IRS-equipped UAV that dynamically tracks and follows the CEVs, while simultaneously optimizing the phase shift design and subcarrier allocation.…”

“…Finally, Scheme 4 focuses on optimizing resource management within the CEVs, where the NOMA technique is directly employed for communication between CEVs and the BS. According to [2,32], the major simulation parameters set in this paper are as follows: V = [4, 40], P max = 30 dBm, φ th SIC = [20, 60] dB, B 0 = 180 KHz, σ 2 = −174 dBm/Hz, K = [2, 20], and Y = {4, 10, 16}. Additionally, as discussed in [41], the air-to-ground path loss model is 32.44 + 20 lg[d(km)] + 20 lg[ f c (MHz)], the multipath fading model follows the Rayleigh fading with 1 variance, the carrier frequency is 2.1 GHz, the speed of the IRS-equipped UAV and CEVs is 50 km/h, and the number of simulation runs is 10 4 .…”

“…An iterative optimization (IO) algorithm, employing coordinate polling, is introduced to address the non-convex nature of the problem, where the power, subcarrier, and phase shift are solved in turn. Finally, the simulation results demonstrate that our proposed scheme outperforms current state-of-the-art schemes [2,21,31,35] in terms of sum data rate. Additionally, the number of supported CEVs, and the influence of network parameters, convergence, and complexity are fully shown and discussed.…”

“…As a key enabler of intelligent transportation systems (ITS), unmanned aerial vehicles (UAVs) can be used to improve the transmission performance of the Internet of Vehicle (IoV) in rural highways [1]. Generally, the UAV is regarded as an active component of the IoV (e.g., the aerial relay) that can enhance the flexibility, robustness, and throughput [2]. By seamlessly integrating UAVs into IoV, several advantages come to the forefront, fundamentally transforming how transportation networks operate [3][4][5].…”

Resource Allocation Methods in Vanets:a Systematic Literature Review

“…One idea for addressing the dynamic needs of VANETs is to apply the use o UAVs, [82]. These solutions use aerial base stations which are utilized in similar manners as RSUs, [83]. Since the UAVs are mobile, they are able to adjust their positions to help offload congestion on taxed areas, [84].…”