JOURNAL ARTICLE

Optimal Secondary Users Selection for Cooperative Spectrum Sensing in Cognitive Radio Networks

Abstract

The Secondary Users (SUs) in cognitive radio networks, are required to perform transmissions such that they do not interfere with the Primary User's (PU) transmission. This requires identification of the PU with the help of different spectrum sensing techniques. In recent years, Cooperative Spectrum Sensing (CSS), which is meant to improve the trust of decisions made busy or idle channel and to overcome the hidden terminal problem, has gained a lot of attention. However, cooperative sensing incurs sensing overhead due to communication and energy consumption during sensing. This work considers the selection of an optimal number of SUs, which can guarantee reliable sensing operation while reducing the unnecessary energy consumption. To perform this selection, all the SUs receiving good Signal to Noise Ratio (SNR) from the PU are selected first. Second, all uncorrelated SUs are selected from the first phase such that the shadowing effect is minimized. It is indicative in the simulation results that the proposed scheme can achieve a good probability of detection, with low probability of false alarm.

Keywords:
Cognitive radio Computer science False alarm Overhead (engineering) Channel (broadcasting) Transmission (telecommunications) Energy consumption Idle Energy (signal processing) Selection (genetic algorithm) Computer network Identification (biology) Signal-to-noise ratio (imaging) Real-time computing Telecommunications Wireless Artificial intelligence Engineering

Metrics

12
Cited By
2.33
FWCI (Field Weighted Citation Impact)
27
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Cognitive Radio Networks and Spectrum Sensing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Distributed Sensor Networks and Detection Algorithms
Physical Sciences →  Computer Science →  Computer Networks and Communications
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering

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