# Rate Balancing for Multiuser MIMO Systems

## TL;DR

This paper presents a novel rate balancing algorithm for multiuser MIMO downlink systems that optimizes the worst-case user rate using an alternating optimization approach based on uplink/downlink duality, outperforming existing methods.

## Contribution

It introduces an original rate balancing solution for multiuser MIMO downlink that effectively handles coupled transmit filters and improves performance over traditional MSE balancing methods.

## Key findings

- The proposed algorithm converges to a local optimum.
- Simulation results show improved worst-case user rates.
- The method outperforms existing MSE balancing approaches.

## Abstract

We investigate and solve the rate balancing problem in the downlink for a multiuser Multiple-Input-Multiple-Output (MIMO) system. In particular, we adopt a transceiver structure to maximize the worst-case rate of the user while satisfying a total transmit power constraint. Most of the existing solutions either perform user Mean Squared Error (MSE) balancing or streamwise rate balancing, which is suboptimal in the MIMO case. The original rate balancing problem in the downlink is complicated due to the coupled structure of the transmit filters. This optimization problem is here solved in an alternating manner by exploiting weighted MSE uplink/downlink duality with proven convergence to a local optimum. Simulation results are provided to validate the proposed algorithm and demonstrate its performance improvement over unweighted MSE balancing.