论文成果

An Efficient MAC Protocol With Selective Grouping and Cooperative Sensing in Cognitive Radio Networks

发布时间:2021-06-24  点击次数:

DOI码:10.1109/TVT.2013.2258952

发表刊物:IEEE Transactions on Vehicular Technology

摘要:In cognitive radio (CR) networks, spectrum sensing is a crucial technique for discovering spectrum opportunities for secondary users (SUs). The quality of spectrum sensing is evaluated by both sensing accuracy and sensing efficiency. Here, sensing accuracy is represented by the false-alarm probability and the detection probability, whereas sensing efficiency is represented by the sensing overhead and network throughput. In this paper, we propose a group-based cooperative medium access control (MAC) protocol called GC-MAC, which addresses the tradeoff between sensing accuracy and efficiency. In GC-MAC, the cooperative SUs are grouped into several teams. During a sensing period, each team senses a different channel while SUs in the same team perform the joint detection on the targeted channel. The sensing process will not stop unless an available channel is discovered. To reduce the sensing overhead, an SU-selecting algorithm is presented to choose selectively the cooperative SUs based on the channel dynamics and usage patterns. Then, an analytical model is built to study the sensing accuracy-efficiency tradeoff under two types of channel conditions: a time-invariant channel and a time-varying channel. An optimization problem that maximizes achievable throughput is formulated to optimize the important design parameters. Both saturation and nonsaturation situations are investigated with respect to throughput and sensing overhead. Simulation results indicate that the proposed protocol is able to significantly decrease sensing overhead and increase network throughput with guaranteed sensing accuracy.

第一作者:Y. Liu, S. Xie, R. Yu, Y. Zhang, C. Yuen

论文类型:期刊论文

卷号:62

期号:8

ISSN号:1939-9359

是否译文:

发表时间:2013-04-18

上一条:Toward cloud-based vehicular networks with efficient resource management 下一条:Cognitive machine-to-machine communications: visions and potentials for the smart grid

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