# Energy Efficient Power Allocation in Massive MIMO Systems based on Standard Interference Function

## TL;DR

This paper proposes an iterative algorithm based on standard interference functions to optimize energy efficiency in downlink massive MIMO systems, effectively handling non-convex constraints and interference issues.

## Contribution

It introduces a novel implicit iterative algorithm leveraging standard interference functions for energy-efficient power allocation in massive MIMO systems.

## Key findings

- The algorithm converges rapidly within a few iterations.
- Energy efficiency improves with increased number of antennas and users.
- Simulation confirms the effectiveness of the proposed method.

## Abstract

In this paper, energy efficient power allocation for downlink massive MIMO systems is investigated. A constrained non-convex optimization problem is formulated to maximize the energy efficiency (EE), which takes into account the quality of service (QoS) requirements. By exploiting the properties of fractional programming and the lower bound of the user data rate, the non-convex optimization problem is transformed into a convex optimization problem. The Lagrangian dual function method is utilized to convert the constrained convex problem into an unconstrained convex one. Due to the multi-variable coupling problem caused by the intra-user interference, it is intractable to derive an explicit solution to the above optimization problem. Exploiting the standard interference function, we propose an implicit iterative algorithm to solve the unconstrained convex optimization problem and obtain the optimal power allocation scheme. Simulation results show that the proposed iterative algorithm converges in just a few iterations, and demonstrate the impact of the number of users and the number of antennas on the EE.