A new MUD algorithm for smart antenna
Signal Processing
A low-complexity blind multiuser receiver for long-code CDMA
EURASIP Journal on Wireless Communications and Networking - Special issue on innovative signal transmission and detection techniques for next generation cellular CDMA systems
EURASIP Journal on Applied Signal Processing
Joint power control and blind beamforming over wireless networks: a cross layer approach
EURASIP Journal on Applied Signal Processing
Algorithms for additive clustering of rectangular data tables
Computational Statistics & Data Analysis
A unified approach to list-based multiuser detection in overloaded receivers
EURASIP Journal on Wireless Communications and Networking - Theory and Applications in Multiuser/Multiterminal Communications
Blind paraunitary equalization
Signal Processing
Blind paraunitary equalization
Signal Processing
Bounded component analysis of linear mixtures: a criterion of minimum convex perimeter
IEEE Transactions on Signal Processing
Multiuser CDMA signal extraction
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Signal detection and synchronization for interference overloaded satellite broadcast reception
IEEE Transactions on Wireless Communications
Space-Time Blind Multiuser Detection for Multiuser DS-CDMA and Oversampled Systems
Wireless Personal Communications: An International Journal
Hi-index | 35.69 |
We propose a maximum-likelihood (ML) approach for separating and estimating multiple synchronous digital signals arriving at an antenna array at a cell site. The spatial response of the array is assumed to be known imprecisely or unknown. We exploit the finite alphabet property of digital signals to simultaneously estimate the array response and the symbol sequence for each signal. Uniqueness of the estimates is established for BPSK signals. We introduce a signal detection technique based on the finite alphabet property that is different from a standard linear combiner. Computationally efficient algorithms for both block and recursive estimation of the signals are presented. This new approach is applicable to an unknown array geometry and propagation environment, which is particularly useful In wireless communication systems. Simulation results demonstrate its promising performance