Adaptive Intelligent Cooperative Spectrum Sensing In Cognitive Radio

TL;DR

This paper proposes a neural network-based cooperative spectrum sensing method for cognitive radio, improving detection accuracy in non-stationary channels compared to traditional rule-based schemes.

Contribution

It introduces a neural network approach for cooperative spectrum sensing that enhances detection performance over existing methods like AND, OR, and Majority rule.

Findings

Neural network scheme outperforms traditional decision rules.

Significant improvement in detection accuracy observed.

Method effectively handles non-stationary channel conditions.

Abstract

Radio Spectrum is most precious and scarce resource and must be utilized efficiently and effectively. Cognitive radio is the promising solutions for the optimum utilization of the scared natural resource. The spectrum owned by the primary user should be shared among the secondary user, but primary user should not be interfered by the secondary user. In order to utilize the primary user spectrum, secondary user must detect accurately, the existence of primary in the band of interest. In cooperative spectrum sensing, the channel between the secondary users and the cognitive radio base station is non stationary and causes interference in the decision in decision fusion and in information in information due to multipath fading. In this paper neural network based cooperative spectrum sensing method is proposed, the performance of proposed method is evaluated and observed that, the neural network based scheme performance improve significantly over the AND,OR and Majority rule