Abstract

With the rapid development of wireless technologies, wireless access networks have entered their Fifth-Generation (5G) system phase. The heterogeneous and complex nature of a 5G system, with its numerous technological scenarios, poses significant challenges to wireless resource management, making radio resource optimization an important aspect of Device-to-Device (D2D) communication in such systems. Cellular D2D communication can improve spectrum efficiency, increase system capacity, and reduce base station communication burdens by sharing authorized cell resources; however, can also cause serious interference. Therefore, research focusing on reducing this interference by optimizing the configuration of shared cellular resources has also grown in importance. This paper proposes a novel algorithm to address the problems of co-channel interference and energy efficiency optimization in a long-term evolution network. The proposed algorithm uses the fuzzy clustering method, which employs minimum outage probability to divide D2D users into several groups in order to improve system throughput and reduce interference between users. An efficient power control algorithm based on game theory is also proposed to optimize user transmission power within each group and thereby improve user energy efficiency. Simulation results show that these proposed algorithms can effectively improve system throughput, reduce co-channel interference, and enhance energy efficiency.

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