Research Article
Low Complexity Iterative Interference Estimation and Decoding for OFDM-Based Cognitive Radio Systems
@INPROCEEDINGS{10.1109/CHINACOM.2009.5339889, author={Youwen Yi and Daiming Qu and Tao Jiang and Guangxi Zhu, and Jun Chen and Zhiqiang Wang}, title={Low Complexity Iterative Interference Estimation and Decoding for OFDM-Based Cognitive Radio Systems}, proceedings={ChinaCom2009-Wireless Communications and Networking Symposium}, publisher={IEEE}, proceedings_a={CHINACOM2009-WCN}, year={2009}, month={11}, keywords={}, doi={10.1109/CHINACOM.2009.5339889} }- Youwen Yi
Daiming Qu
Tao Jiang
Guangxi Zhu,
Jun Chen
Zhiqiang Wang
Year: 2009
Low Complexity Iterative Interference Estimation and Decoding for OFDM-Based Cognitive Radio Systems
CHINACOM2009-WCN
IEEE
DOI: 10.1109/CHINACOM.2009.5339889
Abstract
Coexistence of different users in cognitive radio (CR) network sharing the same frequency band can cause severe in-band interference. In this paper, we propose a novel scheme of joint interference estimation and decoding to combat the narrowband interference for OFDM-based (orthogonal frequency division multiplexing) CR systems in an iterative way. Moreover, we present some complexity reduction techniques including frequency domain partial averaging which only requires the knowledge of the number of interfered subcarriers. By exploiting the results of decoding, the proposed scheme can achieve an accurate estimation of noise plus interference variance, and a quasi-optimal bit error ratio (BER) performance. It is also robust against the variation of interference power and bandwidth, and the positive error of the knowledge of the number of interfered subcarriers.
