Comparison of interference control methods in large heterogeneous networks

Abstract

Efficient interference control is a prerequisite for realizing the possible capacity gains in large heterogeneous networks. An efficient way to do this is to mute some Base Station (BS) transmissions in some time frames to let other BSs serve their users. Two approaches for doing this is studied; a simple one similar to the schemes used in current mobile technologies and a more complex one with higher performance gains. The complex approach jointly optimizes user attachment, scheduling and muting and requires that a large convex optimization problem is solved. By exploiting structure and sparseness properties it is shown that the computational complexity can be significantly reduced, so that the method can be feasible even in relatively large networks. The performance of the two approaches were compared in a simulation study. It was found that the simple method gave significant performance improvements compared to the case without interference control and that it offered flexibility to trade off improved edge user throughput against a lower average user throughput. The more complex approach gave better performance, even though the muting configuration candidates were selected randomly. The results indicate that significant improvements are possible by selecting the configuration candidates in a more optimal way.