MCFGV: Maximizing Communications and Fairness for Groups of Vehicles

• Published in: 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) pp. 1 - 7
• Main Authors: Ghosh, Pronab, Ebrahimi, Dariush, Alzhouri, Fadi, De Oliveira, Thiago Eustaquio Alves
• Format: Conference Proceeding
• Language: English
• Published: IEEE 05-09-2023
• Subjects: Interference; Land mobile radio; Mixed integer linear programming; Routing; Signal to noise ratio; Smart cities; Vehicular ad hoc networks
• ISSN: 2166-9589
• DOI: 10.1109/PIMRC56721.2023.10293941

Maximizing vehicle-to-vehicle (V2V) communications have become crucial for ever-increasing demands for more complicated vehicular applications of smart cities. In this study, the problem of establishing communications between all pairs of vehicles in a group by considering relaying data packets is investigated. The objective is to maximize the total number of communications for groups of vehicles while maintaining fairness among all V2V communication pairs (MCFGV). Reusing resource blocks under the signal-to-interference-plus-noise ratio (SINR) constraint is allowed. We first mathematically formulate the MCFGV problem to find optimal solutions. Then, due to NP-hardness of the problem, we propose a scalable method to solve it for large networks. Finally, through numerical results, the proposed method is compared with the optimum solutions for small networks, and its performance on larger instances is compared to a baseline heuristic.