Maximizing First Order Approximate Mean of SINR under Imperfect Channel State Information for Throughput Enhancement of MIMO Interference Networks

TL;DR

This paper proposes a new method to maximize the approximate mean of SINR in MIMO interference networks with imperfect CSI, improving throughput by leveraging network reciprocity and filter optimization.

Contribution

It introduces a novel approach that maximizes the estimated mean SINR under imperfect CSI, enhancing throughput in MIMO interference networks.

Findings

The proposed algorithm improves sum rate performance.

Monte Carlo simulations verify the effectiveness.

Maximizes expected SINR with reciprocity-based optimization.

Abstract

In this research paper approximate mean of signal-to-interference-plus-noise ratio (SINR) under imperfect channel state information (CSI) is computed and maximized for throughput enhancement of MIMO interference networks. Each transmitter and receiver has respectively M and N antennas and network operates in a time division duplex mode. Each transceiver adjusts its filter to maximize the expected value of SINR. The proposed New Approach for Throughput Enhancement under imperfect CSI utilizes the reciprocity of wireless networks to maximize the estimated mean. The sum rate performance of the proposed algorithm is verified using Monte Carlo simulations.