, Volume 18, Issue 4, pp 567-577
Date: 24 Mar 2013

Energy-Efficiency Study for Two-tier Heterogeneous Networks (HetNet) Under Coverage Performance Constraints

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Abstract

Recently, heterogeneous networks (HetNet) have been widely studied as an effective approach to provide high network capacity and coverage, which jointly utilizes the technologies of cognitive radio and cooperative communications. However, the dense and random deployment of small-cells (e.g., micro, pico and femtocells) raises important questions about the energy consumption for HetNets. In this paper, we study the optimal energy efficiency of a two-tier heterogeneous network consists of a macro-cell and many small-cells under coverage performance constraints for different spectrum deployments (including orthogonal and co-channel spectrum deployments). Firstly, we derive the closed-form expressions of coverage performance for each tier based on stochastic geometry. Then the relationship between energy efficiency and the density of small-cells for the two-tier network is evaluated, the optimal density of small-cells that maximize energy efficiency under coverage performance constraints for the two-tier network is obtained. The theoretical analysis is validated by simulations.The results show that the energy efficiency of the two-tier networks with orthogonal spectrum deployment is better than that with co-channel spectrum deployment. The results also show that the optimal density of small-cells for maximal energy efficiency is only dependent on the coverage performance of small-cells in orthogonal spectrum deployment scenario. However, in co-channel spectrum deployment scenario, the optimal density of small-cells for maximal energy efficiency is jointly decided by the coverage performance of both macro-cell and small-cell. This work provides an essential understanding for successful deployment of green heterogeneous networks.

This work is supported by National 973 Program of China under grant 2012CB316005, and by National Science Foundation of China (NSFC) under grant 61001117, U1035001.