Social-Aware Joint Uplink and Downlink Resource Allocation Scheme Using Genetic Algorithm

This paper investigates a joint uplink and downlink resource allocation problem for a 5G use case. We explore the social-awareness of the network operators to efficiently match users during any form of peer-to-peer communication. Thus, we proposed a peer-selection scheme to improve the overall utility of the network amid limited spectral resources while exploiting the social-ties of network users’. Consequently, we formulate a utility maximization problem as a mixed-integer non-linear programming (MINLP) problem to be solved using genetic algorithm. We perform extensive Monte-Carlo simulations alongside several meta-heuristic algorithms for comparison. The results reveal that our proposed scheme is a good candidate to appreciably and significantly improve the expected utility and network performance.