Power Control for Maximum Throughput in Spectrum Underlay Cognitive Radio Networks

TL;DR

This paper proposes an iterative power control algorithm for spectrum underlay cognitive radio networks to maximize total throughput while ensuring primary users' QoS, demonstrating improved network performance through simulations.

Contribution

It introduces a novel iterative algorithm based on sequential geometric programming for power allocation in spectrum underlay networks, addressing non-convex optimization challenges.

Findings

Secondary users increase overall network throughput.

Primary user throughput loss is minimized with secondary access.

Total primary transmit power decreases with secondary user admission.

Abstract

We investigate power allocation for users in a spectrum underlay cognitive network. Our objective is to find a power control scheme that allocates transmit power for both primary and secondary users so that the overall network throughput is maximized while maintaining the quality of service (QoS) of the primary users greater than a certain minimum limit. Since an optimum solution to our problem is computationally intractable, as the optimization problem is non-convex, we propose an iterative algorithm based on sequential geometric programming, that is proved to converge to at least a local optimum solution. We use the proposed algorithm to show how a spectrum underlay network would achieve higher throughput with secondary users operation than with primary users operating alone. Also, we show via simulations that the loss in primary throughput due to the admission of the secondary users is accompanied by a reduction in the total primary transmit power.