Energy-Efficient Resource Allocation in Ultra-Dense Networks with Massive MIMO

Abstract

We study the energy-efficient resource allocation in ultra-dense networks (UDNs) with massive multiple- input multiple-out (MIMO), where the densely deployed BSs are equipped with massive antenna arrays to communicate with multiple users. Aiming to design a practical resource allocation scheme in the presence of strong interference in UDNs, we propose a semi-distributed interference-aware (IA) resource allocation to achieve high energy efficiency (EE). In particular, a coordinator is introduced to collect the local interference-information estimated by each BS and then fed back the synthesized global interference-information to each BS to enable parallel and cell-wise optimizations. Focusing the capability of massive MIMO in UDNs, we further propose a joint optimization of the active BS antennas, user scheduling and transmission power within the IA resource allocation framework for EE. Numerical results show our IA joint optimization scheme significantly improves the EE performance over the conditional interference-unaware scheme in UDNs with massive MIMO.