Optimal power control in Cognitive MIMO systems with limited feedback

TL;DR

This paper addresses optimal power allocation in Cognitive MIMO systems with limited feedback, aiming to maximize secondary system throughput while controlling interference to primary users, using novel feedback reduction strategies.

Contribution

It introduces limited feedback algorithms for power control in Cognitive MIMO systems that improve secondary throughput under interference constraints.

Findings

Proposed algorithms effectively balance throughput and interference.

Monte Carlo simulations demonstrate performance gains.

Limited feedback strategies outperform traditional methods.

Abstract

In this paper, the problem of optimal power allocation in Cognitive Radio (CR) Multiple Input Multiple Output (MIMO) systems is treated. The focus is on providing limited feedback solutions aiming at maximizing the secondary system rate subject to a constraint on the average interference caused to primary communication. The limited feedback solutions are obtained by reducing the information available at secondary transmitter (STx) for the link between STx and the secondary receiver (SRx) as well as by limiting the level of available information at STx that corresponds to the link between the STx and the primary receiver PRx. Monte Carlo simulation results are given that allow to quanitfy the performance achieved by the proposed algorithms.