Game‐Theoretic Social‐Aware Resource Allocation for Device‐to‐Device Communications Underlaying Cellular Network

Abstract

Device-to-Device communication underlaying cellular network can increase the spectrum efficiency due to direct proximity communication and frequency reuse. However, such performance improvement is influenced by the power interference caused by spectrum sharing and social characteristics in each social community jointly. In this investigation, we present a dynamic game theory with complete information based D2D resource allocation scheme for D2D communication underlaying cellular network. In this resource allocation method, we quantify both the rate influence from the power interference caused by the D2D transmitter to cellular users and rate enhancement brought by the social relationships between mobile users. Then, the utility function maximization game is formulated to optimize the overall transmission rate performance of the network, which synthetically measures the final influence from both power interference and sociality enhancement. Simultaneously, we discuss the Nash Equilibrium of the proposed utility function maximization game from a theoretical point of view and further put forward a utility priority searching algorithm based resource allocation scheme. Simulation results show that our proposed scheme attains better performance compared with the other two advanced proposals.

Game-Theoretic Resource Allocation Algorithms for Device-to-Device Communications in Fifth Generation Cellular Networks: A Review

“…Wang et al (2018) investigated game-theoretic social-aware resource allocation for D2D communications underlaying cellular networks [36]. In the resource allocation scheme, the authors quantified both the rate enhancement brought by the social relationships between mobile devices and the rate influence from the power interference created by the D2D transmitter to cellular devices.…”

Efficient Radio Channel Allocation in Integrated mmWave/Sub-6 GHz UAV-Assisted Disaster Relief Networks

“…However, those schemes are not suitable for larger-scale networks since they work in a centralized manner. us, some typical decentralized resource allocation schemes [21][22][23] have been developed. In decentralized scenarios, there are two kinds of theories used widely in solving the channel allocation problem: game theory and graph theory.…”

“…Among the works adopting game theory, the authors of [21] proposed a channel allocation method by using an anticoordination game for interference management in a highly dynamic network. Based on the one-to-one matching theory, the authors of [22] introduced a priority searching algorithm based resource allocation to achieve the utility maximization for D2D communication underlying cellular networks. Combining the matching game and Stackelberg game together, the authors of [23] modeled a decentralized channel-power scheme based on the channel signal information.…”

“…Get x i',m' that matches x k' (19) Get link i' ⟶ m' according to x i',m' (20) Delete i' ⟶ m' and the corresponding edge from AIG(t) ( 21) Else (22) Get x j,n that matches x k' (23) Get link j ⟶ n according to x j,n (24) Add…”