Primary Channel Gain Estimation for Spectrum Sharing in Cognitive Radio Networks

Lin Zhang, Guodong Zhao*, Wenli Zhou, Liying Li, Gang Wu, Ying Chang Liang, Shaoqian Li

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

In cognitive radio networks, the channel gain between primary transceivers, namely, primary channel gain, is crucial for a cognitive transmitter (CT) to control the transmit power and achieve spectrum sharing. Conventionally, the primary channel gain is estimated in the primary system, and thus unavailable at the CT. To deal with the issue, two estimators are proposed by enabling the CT to sense primary signals. In particular, by adopting the maximum likelihood (ML) criterion to analyze the received primary signal, an ML estimator is first developed. To reduce the computational complexity of the ML estimator, a median-based (MB) estimator is then proposed. By comparing the ML estimator and the MB estimator from the aspects of the computational complexity as well as the estimation accuracy, both advantages and disadvantages of two estimators are revealed. Simulation results show that the estimation errors of both estimators can be as small as 0.015. Meanwhile, the ML estimator outperforms the MB estimator in terms of the estimation accuracy if the sensed primary signal at the CT is weak. Otherwise, the MB estimator is superior to the ML estimator from the aspects of both the computational complexity and the estimation accuracy.

Original languageEnglish
Article number7970169
Pages (from-to)4152-4162
Number of pages11
JournalIEEE Transactions on Communications
Volume65
Issue number10
Early online date6 Jul 2017
DOIs
Publication statusPublished - Oct 2017
Externally publishedYes

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