Cell-Free Massive MIMO Energy Efficiency Improvement by Access Points Iterative Selection

Abstract

Cell-free massive multiple-input multiple-output (CF-MIMO) system has been considered a promising technology for 5G and 6G networks for its ability to handle the rise in demand effectively. With CF-MIMO, improved energy efficiency can be obtained from straightforward signal processing. One of the potential problems in CF-MIMO systems is high power consumption due to the large numbers of distributed Access Points (APs), which decrease energy efficiency. This research proposes a modified algorithm to improve overall energy efficiency by reducing total power consumption via using the APs selection technique while maintaining the system's sum of rate. The technique used for APs selection is the largest large-scale-based selection, where each user is served by a subset of APs that offer the best channel condition rather than by all of APs. Total energy efficiency has been calculated for three cases: without APs selection, fixed APs selection, and dynamic APs selection (proposed approach). The simulation result shows that the proposed approach significantly improves energy efficiency by 45% at the signal-to-noise ratio (SNR) equal to 6 dB than the case where the selection of APs is fixed due to the optimal APs selection for each user.

Keywords

• Dynamic APs selection
• Cell-free massive MIMO
• Zero-forcing precoding
• Energy efficiency