Energy-and Spectral-Efficiency Trade-off in Distributed Massive-MIMO Networks

TL;DR

This paper explores the balance between energy efficiency and spectral efficiency in distributed massive MIMO networks by optimizing power, AP activation, and user association, considering comprehensive power consumption factors.

Contribution

It introduces a joint optimization framework for EE and SE in D-mMIMO systems, incorporating dynamic AP activation and association with a fractional programming approach.

Findings

Dynamic AP activation significantly affects EE-SE trade-off.

Optimal operating points balance spectral performance and energy consumption.

Adaptive resource allocation enhances energy-efficient network deployment.

Abstract

This paper investigates the energy efficiency (EE) and spectral efficiency (SE) trade-off in uplink distributed massive multiple-input multiple-output (D-mMIMO) systems. Unlike conventional approaches where power consumption focuses primarily on transmit power, we use a comprehensive system-level power consumption framework which incorporates consumption due to fronthaul signaling, distributed processing, and circuit level power, which are, themselves, critically influenced by the dynamic access point (AP) activation (ON-/OFF decisions), and AP-user equipment (UE) association strategies. Consequently, we analyze the EE-SE trade-off through the joint optimization of transmit power allocation, AP activation, and AP-UE association. We formulate an optimization problem that maximizes EE while satisfying sum-SE constraints, per-user minimum SE requirements, and fronthaul capacity limits. Our solution uses a fractional programming-based approach to simultaneously determine transmit power levels, dynamic AP-UE associations, and AP activation strategies. Numerical results demonstrate that dynamic AP activation and association substantially impact the EE-SE trade-off, revealing optimal operating points that balance spectral performance with energy consumption. The findings provide practical guidelines for energyefficient D-mMIMO deployment in next generation wireless networks, highlighting the importance of adaptive resource allocation in achieving sustainable high-performance communications.