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 utili...

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Bibliographic Details
Main Authors: Ekwe, Stephen O., Akinyemi, Lateef A., Oladejo, Sunday O., Ventura, Neco
Format: Conference Proceeding
Language:English
Subjects:
Downlink
genetic algorithm
matching
Measurement
Monte Carlo methods
Peer-to-peer computing
Privacy
Programming
resource allocation
Resource management
Social-aware
Online Access:Request full text
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Summary: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.
ISSN:2153-0033
DOI:10.1109/AFRICON51333.2021.9570887