On the Ergodic Rate of OFDMA Cognitive Radios under Imperfect Cross-Link Information

TL;DR

This paper analyzes the ergodic rate limits of OFDMA cognitive radios with imperfect cross-link information, proposing a novel interference management technique and an optimized resource allocation algorithm to enhance performance under interference constraints.

Contribution

It introduces a new stochastic interference management method and an optimal resource allocation algorithm for OFDMA CRs with imperfect cross-link knowledge.

Findings

The proposed RA algorithm improves CR performance under interference constraints.

An expression for the SINR CDF enables accurate ergodic rate evaluation.

Simulation results validate the effectiveness of the interference management technique.

Abstract

The ergodic rate performance and limits of orthogonal frequency-division multiple access (OFDMA) cognitive radios (CRs) is studied under imperfect cross-link knowledge. We propose a novel stochastic interference management and exploitation technique to mitigate and control the imposed interference by CRs on licensed users in underlay spectrum sharing. The optimum downlink channel-adaptive resource allocation (RA) algorithm is designed to maximize the CRs functionality subject to the satisfying average transmit and probabilistic peak interference power constraints. An expression of the cumulative density function (cdf) of CRs' received signal-to-interference-plus-noise ratio (SINR) is developed to evaluate the resultant ergodic rate. Simulation studies are conducted to examine the proposed RA algorithm and investigate the impact of parameters uncertainty on the overall system performance.