Energy-efficient resource allocation strategy in ultra dense small-cell networks: A Stackelberg game approach

Abstract

This paper focuses on resource allocation in heterogeneous Ultra Dense small-cell Networks (UDNs), in which massive overlaid small cells are under the coverage of a macro cell. In UDN, both co-tier and cross-tier interference need to be taken into account. When increasing the deployment density of Small-cell Base Stations (SBSs) and the unreasonable energy usage, it results in serious interference and degrades the user's satisfaction, which encourages us to agree on maximizing the total system Energy Efficiency (EE). This problem is non-convex and cannot be solved within polynomial time. Therefore, an efficient hierarchical Resource Allocation (RA) algorithm with reduced computational complexity is proposed to decompose the EE optimization problem into two sub-optimization problems: Sub-Channel Allocation (SCA) process and Power Allocation (PA) process. To solve these two processes, thereafter, we employ a uniform pricing scheme to reduce the feedback overhead and build the PA problem into a two-stage Stackelberg game, where the Macro-cell Base Station (MBS) acts as a follower and SBSs are leaders. The obtained simulation results show that the proposed hierarchical RA algorithm and the two-stage game can achieve a higher EE and a lower computation complexity.