Joint Optimization of Cache Placement, User Association, and Channel Selection in Cache-Enabled Multicasting Small-Cell Networks

Abstract

Caching and multicasting are two promising methods to alleviate redundant data transmissions and improve transmission capability in wireless networks. In this article, we focus on the joint resource optimization of cache placement, user association, and channel selection in cache-enabled multicasting small-cell networks. First, we present two weighted hypergraphs to analyze the complex transmission and interference relationships among mobile users (MUs) and small-cell base stations (SBSs) with different files multicasting in different channels. Then, we formulate the combinatorial problem as a nonlinear optimization problem. Considering the hierarchical actions of SBSs and MUs, we further divide the complicated combinatorial optimization problem into following two subproblems, i.e., i) the joint cache placement and channel selection, and ii) the user association. Simultaneously, we propose two potential games <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$G1$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$G2$</tex-math></inline-formula> to analyze the two subproblems, respectively. Thanks to the better response property of potential games, we propose a hierarchical resource allocation game <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$G_w$</tex-math></inline-formula> by combining <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$G1$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$G2$</tex-math></inline-formula> to optimize wireless resources iteratively. Lastly, we propose two hierarchical better response algorithms, which can converge to the hierarchical Nash equilibria. Simulation results show that our proposed distributed game method achieves good expectations of global accumulated downloading files.