Rate-Interference Tradeoff in OFDM-based Cognitive Radio Networks

TL;DR

This paper explores the balance between maximizing secondary user transmission rates and minimizing interference to primary users in OFDM-based cognitive radio networks, proposing a multiobjective optimization approach.

Contribution

It introduces a novel multiobjective optimization framework and an algorithm that balances spectrum utilization and interference management with partial channel knowledge.

Findings

The proposed algorithm effectively balances SU rate and interference levels.

Simulation results show the algorithm outperforms existing methods.

Partial CSI consideration enhances practical applicability.

Abstract

In cognitive radio (CR) networks, secondary users (SUs) are allowed to opportunistically access the primary users (PUs) spectrum to improve the spectrum utilization; however, this increases the interference levels at the PUs. In this paper, we consider an orthogonal frequency division multiplexing OFDM-based CR network and investigate the tradeoff between increasing the SU transmission rate (hence improving the spectrum utilization) and reducing the interference levels at the PUs. We formulate a new multiobjective optimization (MOOP) problem that jointly maximizes the SU transmission rate and minimizes its transmit power, while imposing interference thresholds to the PUs. Further, we propose an algorithm to strike a balance between the SU transmission rate and the interference levels to the PUs. The proposed algorithm considers the practical scenario of knowing partial channel state information (CSI) of the links between the SU transmitter and the PUs receivers. Simulation results illustrate the performance of the proposed algorithm and its superiority when compared to the work in the literature.