# A CMDP-based Approach for Energy Efficient Power Allocation in Massive MIMO Systems

## TL;DR

This paper introduces a CMDP-based method for optimizing energy-efficient power allocation in massive MIMO uplink systems, balancing QoS requirements and achieving near-optimal performance through offline algorithms.

## Contribution

It formulates the power allocation problem as a CMDP and proposes an offline solution using value iteration and Q-learning to find the global optimum policy.

## Key findings

- Proposed policy closely matches ergodic optimal performance.
- Effective in managing QoS requirements for multiple users.
- Demonstrates the viability of CMDP in massive MIMO energy optimization.

## Abstract

In this paper, energy efficient power allocation for the uplink of a multi-cell massive MIMO system is investigated. With the simplified power consumption model, the problem of power allocation is formulated as a constrained Markov decision process (CMDP) framework with infinite-horizon expected discounted total reward, which takes into account different quality of service (QoS) requirements for each user terminal (UT). We propose an offline solution containing the value iteration and Q-learning algorithms, which can obtain the global optimum power allocation policy. Simulation results show that our proposed policy performs very close to the ergodic optimal policy.