Joint Optimization of Clustering and Resource Allocation based on Game Theory for Ultra-Dense Networks
2022 IEEE Ninth International Conference on Communications and Electronics (ICCE)(2022)
摘要
In this paper, we consider the amalgamation of clustering and resource allocation based on game theory in ultra-dense networks (UDNs) which consist of a vast number of randomly distributed small cells. In particular, to mitigate the inter-cell interference, we propose a coalition game (CG) for clustering small cells with the utility function to be the ratio of signal to interference. Then, resource allocation is divided into two sub-problems such as sub-channel allocation (SCA) and power allocation (PA). We use the Hungarian method, which is efficient for solving binary optimization problems, for assigning the sub-channels to users in each cluster of SBSs. Additionally, an iterative algorithm to solve the convex optimization is provided to maximize the network sum-rate. Numerical results prove that the game-based clustering method outperforms the traditional clustering method (with and without PA optimization) and random clustering method in terms of the sum-rate.
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关键词
Game theory,ultra-dense network,game-based clustering,sum-rate maximization,nonconvex optimization
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