A Novel Algorithm for Rate/Power Allocation in OFDM-based Cognitive Radio Systems with Statistical Interference Constraints

TL;DR

This paper introduces a new algorithm for OFDM-based cognitive radio systems that optimizes throughput and power while ensuring interference constraints without needing perfect channel information, demonstrating near-optimal performance with lower complexity.

Contribution

A novel joint rate and power allocation algorithm for OFDM-based cognitive radios that operates under statistical interference constraints without requiring perfect CSI.

Findings

Performance approaches that of exhaustive search for optimal allocations.

Significantly reduced computational complexity compared to optimal methods.

Effective in maintaining interference constraints without perfect channel information.

Abstract

In this paper, we adopt a multiobjective optimization approach to jointly optimize the rate and power in OFDM-based cognitive radio (CR) systems. We propose a novel algorithm that jointly maximizes the OFDM-based CR system throughput and minimizes its transmit power, while guaranteeing a target bit error rate per subcarrier and a total transmit power threshold for the secondary user (SU), and restricting both co-channel and adjacent channel interferences to existing primary users (PUs) in a statistical manner. Since the interference constraints are met statistically, the SU transmitter does not require perfect channel-state-information (CSI) feedback from the PUs receivers. Closed-form expressions are derived for bit and power allocations per subcarrier. Simulation results illustrate the performance of the proposed algorithm and compare it to the case of perfect CSI. Further, the results show that the performance of the proposed algorithm approaches that of an exhaustive search for the discrete global optimal allocations with significantly reduced computational complexity.