JOURNAL ARTICLE

Energy-Efficient Partial-Cooperative Spectrum Sensing in Cognitive Radio over Fading Channels

Abstract

Energy efficiency in cooperative spectrum sensing in cognitive radio is investigated in this paper, where a novel approach is proposed for reducing the energy consumed in spectrum sensing and improving the resultant energy efficiency of the cognitive transmission. The proposed approach is based on limiting the number of users that participate in the spectrum sensing task. The participation decision of each user is taken individually by the user itself, where each user estimates the expected amount of consumed energy based on its distance from the base station, and compares it to a predefined threshold. The user will participate only if the estimated energy is less than the threshold. Besides reducing energy consumption, our proposal increases the amount of successfully transmitted data as well. Moreover, an optimization of the threshold is carried out through simulation in order to optimize the energy efficiency. Our results show a considerable amount of reduction in energy consumption (up to 80%) compared to the conventional approach.

Keywords:
Cognitive radio Energy consumption Computer science Fading Efficient energy use Energy (signal processing) Transmission (telecommunications) Base station Limiting Reduction (mathematics) Energy conservation Telecommunications Real-time computing Electronic engineering Computer network Wireless Channel (broadcasting) Engineering Electrical engineering Mathematics Statistics

Metrics

21
Cited By
2.90
FWCI (Field Weighted Citation Impact)
20
Refs
0.92
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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