Game Theory Based Resource Allocation in D2D Communication with Traffic Aware Beam Selection in 5G Networks
Keywords:
D2D links, resource utilization, beam configuration, Game theory, resource block, throughputAbstract
Device to Device (D2D) communication is an advanced technology to increase cellular network efficiency, improving factors such as spectral efficiency, battery life, and coverage. The foundation of the 5G cellular network, striving for a network availability of 99.999%, relies heavily on D2D communication. When multiple D2D pairs connect to various base stations, the complexities of resource allocation for D2D links become apparent. In this paper, a resource allocation strategy based on game theory is introduced, with special focus on resource block (RB) sharing between multi-cell mobile phone networks involving D2D and handset users. In this approach, D2D user pairs engage in strategic games with nearby base stations, aiming to optimize their utility by thoughtfully distributing their initially allocated resources. Interuser interference may arise from side lobes in the antenna array. To address this challenge, the paper presents a traffic-aware beam configuration method combined with game theory-based resource allocation. This approach optimizes the allocation of beams across all Resource Blocks (RBs) to efficiently meet the traffic demands of User Equipment (UE). Each intercell D2D player simultaneously participates in a game with the base stations. The study reveals that by introducing an additional penalty factor for swift adherence, the duration of penalties for players deviating from the optimal strategy can be minimized. Additionally, the research identifies the ideal number of initial RBs that should be orthogonal and allocates them to both Device to Device (D2D) and cellular users. Evaluate the proposed approach compared to existing methods like multicast content sharing-based resource allocation (MCSRA), Quality of Experience-aware resource allocation (QoERA), and Mobile Edge Computing-based resource allocation (MECRA), showcases substantial improvements in resource utilization, throughput, and traffic demand management across the entire system. According to experimental analysis, the proposed system achieves a remarkable 96% increase in resource utilization, a 95% increase in throughput, and effectively addresses 97% of traffic demands.
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