# Sum-Rate Maximization of Multicell MISO Networks with Limited Information Exchange

## TL;DR

This paper introduces a non-iterative cooperative beamforming scheme for multicell MISO networks that maximizes sum-rate with minimal information exchange, closely approaching optimal performance across various SNR regimes.

## Contribution

It presents a novel non-iterative beamforming design requiring only quantized scalar information, reducing exchange and computational complexity compared to existing methods.

## Key findings

- Scheme closely achieves the optimal sum-rate bound in most SNR regimes.
- Requires only local CSI and limited quantized scalar information.
- Outperforms or matches existing schemes with less information exchange.

## Abstract

Although there have been extensive studies on transmit beamforming in multi-input single-output (MISO) multicell networks, achieving optimal sum-rate with limited channel state information (CSI) is still a challenge even with a single user per cell. A novel cooperative downlink multicell MISO beamforming scheme is proposed with highly limited information exchange among the base stations (BSs) to maximize the sum-rate. In the proposed scheme, each BS can design its beamforming vector with only local CSI based on limited information exchange on CSI. Unlike previous studies, the proposed beamforming design is non-iterative and does not require any vector or matrix feedback but requires only quantized scalar information. The proposed scheme closely achieves the optimal sum-rate bound in almost all signal-to-noise ratio regime based on non-iterative optimization with lower amount of information exchange than existing schemes, which is justified by numerical simulations.