A Lightweight QoS-Aware Resource Allocation Method for NR-V2X Networks

Vehicle-to-Everything (V2X) communication, which includes Vehicle-to-Infrastructure (V2I), Vehicle-to-Vehicle (V2V), and Vehicle-to-Pedestrian (V2P) networks, is gaining significant attention due to the rise of connected and autonomous vehicles. V2X systems require diverse Quality of Service (QoS) provisions, with V2V communication demanding stricter latency and reliability compared to V2I. The 5G New Radio-V2X (NR-V2X) standard addresses these needs using multi-numerology Orthogonal Frequency Division Multiple Access (OFDMA), which allows for flexible allocation of radio resources. However, V2I and V2V users sharing the same radio resources leads to interference, necessitating efficient power and resource allocation. In this work, we propose a novel resource allocation and sharing algorithm for 5G-based V2X systems. Our approach first groups Resource Blocks (RBs) into Resource Chunks (RCs) and allocates them to V2I users using the Gale-Shapley stable matching algorithm. Power is then allocated to RCs to facilitate efficient resource sharing between V2I and V2V users through a bisection search method. Finally, the Gale-Shapley algorithm is used to pair V2I and V2V users, maintaining low computational complexity while ensuring high performance. Simulation results demonstrate that our proposed Gale-Shapley Resource Allocation with Gale-Shapley Sharing (GSRAGS) achieves competitive performance with lower complexity compared to existing works while effectively meeting the QoS demands of V2X communication systems.

A QoS-Aware Joint Uplink Spectrum and Power Allocation with Link Adaptation for Vehicular Communications in 5G networks

In this work, we have proposed link adaptation based joint spectrum and power allocation algorithms for uplink cellular vehicle-to-everything (C-V2X) communication for OFDMA based 5G systems. In C-V2X, vehicle-to-vehicle (V2V) users share radio resources with vehicle-to-infrastructure (V2I) users. Existing works primarily focus on the optimal pairing of V2V and V2I users under the assumption that each V2I user needs a single resource block (RB); minimizing any interference through power allocation. In contrast, in this work, we have considered that the number of RBs needed by the users is a function of their channel condition and Quality of Service (QoS) - a method called link adaptation. It is effective in compensating for the incessant channel quality fluctuations at the high frequencies of operation of 5G. The first proposed resource allocation scheme of this work greedily allocates RBs to V2I users using link adaptation and then uses Hungarian algorithm to pair V2V with V2I users, while minimizing interference through power allocation. To reduce the complexity, the second scheme groups RBs into resource chunks (RCs); then uses Hungarian algorithm twice - first to allocate RCs to V2I users, and then to pair V2I users with V2V users. Extensive simulations reveal that link adaptation increases the number of satisfied V2I users as well as their sum-rate, while also improving QoS of individual users, thereby making it indispensable for C-V2X system. We have also considered the presence of best-effort users, and the diverse QoS has been provided through the multi-numerology frame structure of 5G.