Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Uplink User Signal Separation for OFDMA-Based Cognitive Radios | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 502369 11 pages doi 2010 502369 Research Article Uplink User Signal Separation for OFDMA-Based Cognitive Radios Mustafa E. Sahin 1 Ismail Guvenc 2 and Hiiseyin Arslan1 1The Electrical Engineering Department University of South Florida Tampa FL 33620 USA 2Wireless Access Lab DOCOMO Communications Laboratories USA Inc. Palo Alto CA 94304 USA Correspondence should be addressed to Mustafa E. Sahin msahin@ Received 9 May 2009 Revised 17 September 2009 Accepted 21 October 2009 Academic Editor Rui Zhang Copyright 2010 Mustafa E. Sahin et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Spectrum awareness of orthogonal frequency division multiple access- OFDMA- based cognitive radios CRs can be improved by enabling them to separate the primary user signals in the uplink UL . Assuming availability of information about the basic parameters of the primary system as well as time synchronization to the first arriving user signal two algorithms are proposed in this paper. The first one targets estimating the size of the frequency allocation block of the primary system. The performance of this algorithm is compared with the results of a Gaussian approximation-based approach that aims to determine the probability of correct block size estimation theoretically. The second one is a semiblind user separation algorithm which estimates the carrier frequency offsets and time delays of each block by exploiting the cross-correlations over pilot subcarriers. A two-dimensional clustering method is then employed to group the estimates where each group belongs to a different user. It is shown that the proposed algorithms can improve the spectrum opportunity detection of cognitive radios. Feasibility of the .