Energy-Efficient Resource Allocation for Underlay Spectrum Sharing in Cell-Free Massive MIMO

Abstract

Cell-free massive multiple-input-multiple-output (CF-mMIMO) networks incorporate a cell-free architecture with distributed antennas in a geographical area, and aim to deliver high data rates and support large numbers of users. It is crucial that such networks operate in an energy-efficient manner within the available spectrum. Thus, we focus on maximizing the energy efficiency (EE) of a CF-mMIMO network, which coexists with a collocated primary network in underlay mode. The EE maximization is a non-convex problem and to compute a power allocation policy efficiently, we propose a weighted minimum-mean-square-error (WMMSE) based Dinkelbach’s algorithm. Besides this, we also provide a simplified algorithm for maximum-ratio precoding in which we approximate the non-convex EE objective function with a lower bound, transforming the non-convex EE problem into a convex problem. Subsequently, we propose a policy for downlink power allocation that maximizes the EE of the secondary CF-mMIMO network while adhering to power constraints at each access point and interference constraints at each primary user. We also compare with some heuristic power allocation policies. The results demonstrate that the proposed WMMSE based power allocation scheme outperforms the heuristic power allocation schemes to a significant degree.

Keywords

• Beyond 5G
• cell-free massive MIMO
• downlink
• energy efficiency
• spectrum sharing
• optimization