NDLI: On Results’ Reporting of Cooperative Spectrum Sensing in Cognitive Radio Networks

Content Provider	Springer Nature Link
Author	Althunibat, Saud Granelli, Fabrizio
Copyright Year	2015
Abstract	One of the main challenges of cooperative spectrum sensing in cognitive radio networks is the overhead in terms of high energy consumption especially when reporting the individual sensing results to a common receiver. Such issue becomes more challenging for battery-powered users, because of its direct influence on achievable performance represented by detection accuracy. Thus, energy efficiency in cognitive radio networks has received a lot of attention during recent years. In this paper, we present a novel reporting scheme for spectrum sensing results, which significantly reduces the energy consumption without any effect on the detection accuracy. The proposed scheme allows the fusion center to terminate the reporting process whenever the received results are enough to make a decision according to the employed fusion rule (FR). Hence, the energy consumed in results’ reporting is reduced as the number of reporting users is lower, and the data transmission can be started earlier, which enhances the achievable throughput. Moreover, the proposed scheme is consistent with many other energy-efficient approaches, leading to improve the energy efficiency achieved by these approaches. Mathematical expressions for the average number of reporting users for several FRs are obtained. Simulation and analytical results show a significant improvement in the energy efficiency.
Starting Page	569
Ending Page	580
Page Count	12
File Format	PDF
ISSN	10184864
Journal	Telecommunication Systems
Volume Number	62
Issue Number	3
e-ISSN	15729451
Language	English
Publisher	Springer US
Publisher Date	2015-10-09
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Cognitive radio networks Specturm sensing Cooperative specturm sensing Energy efficiency IT in Business Computer Communication Networks Artificial Intelligence (incl. Robotics) Probability Theory and Stochastic Processes
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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