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: A Subspace Approach to Blind Multiuser Detection for Ultra-Wideband Communication Systems | EURASIP Journal on Applied Signal Processing 2005 3 413-425 2005 Hindawi Publishing Corporation A Subspace Approach to Blind Multiuser Detection for Ultra-Wideband Communication Systems Zhengyuan Xu Department of Electrical Engineering University of California Riverside CA 92521 USA Email dxu@ Ping Liu Department of Electrical Engineering Arkansas Tech University Russellville AR 72801 USA Email Jin Tang Department of Electrical Engineering University of California Riverside CA 92521 USA Email jtang@ Received 26 September 2003 Revised 29 January 2004 Impulse radio-based ultra-wideband UWB communication systems allow multiple users to access channels simultaneously by assigning unique time-hopping codes to individual users while each user s information stream is modulated by pulse-position modulation PPM . However transmitted signals undergo fading from a number of propagation paths in a dense multipath environment and meanwhile suffer from multiuser interference MUI . Although RAKE receiver can be employed to maximally exploit path diversity it is a single-user receiver. Multiuser receiver can significantly improve detection performance. Each of these receivers requires channel parameters. Existing maximum likelihood channel estimators treat MUI as Gaussian noise. In this paper we derive a blind subspace channel estimator first and then design linear receivers. Following a channel input output model that transforms a PPM signal into a sum of seemingly pulse-amplitude modulated signals a structure similar to a code-division multiple-access CDMA system is observed. Code matrices for each user are identified. After considering unique statistical properties of new inputs such as mean and covariance the model is further transformed to ensure that all signature waveforms lie in the signal subspace and are orthogonal to the noise subspace. Consequently a subspace technique is applicable to estimate each channel. Then minimum mean .
