Distributed Fuzzy Optimal Spectrum Sensing In Cognitive Radio

TL;DR

This paper proposes a distributed fuzzy cooperative spectrum sensing method for cognitive radio networks that improves detection performance and robustness against malicious users, addressing errors in reporting channels.

Contribution

It introduces a novel fuzzy detection-based spectrum sensing scheme that enhances accuracy and resilience compared to traditional fusion rules, especially with malicious secondary users.

Findings

Significant performance improvement over AND, OR, and majority rules.

Achieves optimal spectrum sensing with only one-third malicious users.

Outperforms existing methods in the presence of malicious secondary users.

Abstract

The spectrum is a scarce resource and must utilize efficiently, the cognitive radio is a prospective solution for underutilized spectrum. The spectrum sensing is a key functionality to alleviate interference of secondary user to primary. The cognitive radios must detect the existence of the primary user and vacate the band for the primary immediately if the primary user detected. In cooperative sensing, every cognitive radio communicates their decision to fusion center via reporting channel. The reporting channels are not error free, which results corruption in the secondary's decision or information due to multipath fading and shadowing. This paper investigates the distributed fuzzy optimal cooperative spectrum sensing. The data and decision fusion with fuzzy detection is investigated in this paper. The simulation result shows the significant improvement in sensing performance over AND, OR and majority rules. The optimality in spectrum sensing is achieved by the proposed method with 1/3 of total malicious secondary users. The proposed scheme outperforms in the presence of malicious users.