Performance analysis of rate adaptation in cognitive wireless network over fading channel

Authors:
Lianfen Huang;Dan Guo;Yan Yao
Affiliations:
Department of CE, Xiamen University, Xiamen, Fujian, China;Department of CE, Xiamen University, Xiamen, Fujian, China;Department of EE, Tsinghua University, Beijing, China
Venue:
ASID'09 Proceedings of the 3rd international conference on Anti-Counterfeiting, security, and identification in communication
Year:
2009

Citing 3
Cited 0

A rate-adaptive MAC protocol for multi-Hop wireless networks

Proceedings of the 7th annual international conference on Mobile computing and networking
Performance Analysis of Multi-channel DCA MAC Protocol in Cognitive Wireless Mesh Networks

CMC '09 Proceedings of the 2009 WRI International Conference on Communications and Mobile Computing - Volume 02
Performance analysis of multi-rate IEEE 802.11 networks over Gaussian channel

AsiaCSN '08 Proceedings of the Fifth IASTED International Conference on Communication Systems and Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

Currently, the cognitive wireless network draws the great attention since it can effectively improve the spectrum efficiency based on its spectrum cognition. In this paper, we extend the definition of wireless cognitive network, which focuses on the channel quality cognition. By measuring the SNR (Signal-to-Noise Ratio) of received signal, cognitive wireless network based on channel quality cognition adjusts its transmission rate, which accordingly selects different modulation and demodulation technology in Physical Layer. In this paper, we first analyze the BER (Bit Error Rate) of various modulation and demodulation methods described in IEEE 802.11b. Then, we propose Nakagami-m distribution to simulate the fading channel of cognitive wireless network. We analyze the performance of cognitive wireless network over fading channel based on the IEEE 802.11 MAC (Medium Access Control) mechanism. Finally, we validate our model through various simulations and present the impact of fading channel on cognitive wireless network.