Multi-User Diversity with Optimal Power Allocation in Spectrum Sharing under Average Interference Power Constraint

TL;DR

This paper analyzes multi-user diversity with optimal power allocation in spectrum sharing under average interference constraints, proposing an iterative algorithm and evaluating performance over Rayleigh and Nakagami-m fading channels.

Contribution

It introduces a novel algorithm based on bisection for calculating Lagrange multipliers under AIP constraints and extends analysis to various fading channels with multiple primary users.

Findings

A new iterative algorithm for power allocation under AIP constraints.

Performance comparison between AIP and PIP constraints.

Impact of AIP constraint on secondary user capacity.

Abstract

In this paper, we investigate the performance of multi-user diversity (MUD) with optimal power allocation (OPA) in spectrum sharing (SS) under average interference power (AIP) constraint. In particular, OPA through average transmit power constraint in conjunction with the AIP constraint is assumed to maximize the ergodic secondary capacity. The solution of this problem requires the calculation of two Lagrange multipliers instead of one as obtained for the peak interference power (PIP) constraint and calculated using the well known water-filling algorithm. To this end, an algorithm based on bisection method is devised in order to calculate both Lagrange multipliers iteratively. Moreover, Rayleigh and Nakagami-$m$ fading channels with one and multiple primary users are considered to derive the required end-to-end SNR analysis. Numerical results are depicted to corroborate our performance analysis and compare it with the PIP case highlighting hence, the impact of the AIP constraint compared to the PIP constraint application.