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CLC number: TN914.51

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Received: 2009-01-10

Revision Accepted: 2009-05-06

Crosschecked: 2009-11-30

Cited: 7

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Journal of Zhejiang University SCIENCE C 2010 Vol.11 No.3 P.175-186


Cooperative spectrum sensing in cognitive radio systems with limited sensing ability

Author(s):  Hui HUANG, Zhao-yang ZHANG, Peng CHENG, Ai-ping HUANG, Pei-liang QIU

Affiliation(s):  Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China; more

Corresponding email(s):   ning_ming@zju.edu.cn

Key Words:  Cognitive radio, Cooperative spectrum sensing, Limited sensing ability, Throughput

Hui HUANG, Zhao-yang ZHANG, Peng CHENG, Ai-ping HUANG, Pei-liang QIU. Cooperative spectrum sensing in cognitive radio systems with limited sensing ability[J]. Journal of Zhejiang University Science C, 2010, 11(3): 175-186.

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%DOI 10.1631/jzus.C0910027

T1 - Cooperative spectrum sensing in cognitive radio systems with limited sensing ability
A1 - Hui HUANG
A1 - Zhao-yang ZHANG
A1 - Peng CHENG
A1 - Ai-ping HUANG
A1 - Pei-liang QIU
J0 - Journal of Zhejiang University Science C
VL - 11
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SP - 175
EP - 186
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.C0910027

In cognitive radio systems, the design of spectrum sensing has to face the challenges of radio sensitivity and wide-band frequency agility. It is difficult for a single cognitive user to achieve timely and accurate wide-band spectrum sensing because of hardware limitations. However, cooperation among cognitive users may provide a way to do so. In this paper, we consider such a cooperative wide-band spectrum sensing problem with each of the cognitive users able to imperfectly sense only a small portion of spectrum at a time. The goal is to maximize the average throughput of the cognitive network, given the primary network’s collision probability thresholds in each spectrum sub-band. The solution answers the essential questions: to what extent should each cognitive user cooperate with others and which part of the spectrum should the user choose to sense? An exhaustive search is used to find the optimal solution and a heuristic cooperative sensing algorithm is proposed to simplify the computational complexity. Inspired by this optimization problem, two practical cooperative sensing strategies are then presented for the centralized and distributed cognitive network respectively. Simulation results are given to demonstrate the promising performance of our proposed algorithm and strategies.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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