报告摘要: In this seminar novel concepts are introduced for finding the relationship between multiuser detection (MUD) and multiuser transmission (MUT), so that the study in MUT can benefit from the well-built theory in MUD. Our study shows that, for any given linear MUD scheme, there exists a counterpart linear MUT scheme, which can be readily designed from the original linear MUD. Based on our observations, a range of MUT algorithms are derived in correspondence with the well-known linear signal processing schemes in the fields of MUD and array processing, including matched-filtering (MF), zero-forcing (ZF), minimum mean-square error (MMSE), minimum variance distortionless response (MVDR), minimum power distortionless response (MPDR) and maximum signal-to-interference-plus-noise ratio (MSINR), respectively. Furthermore, the physical principles behind the MUD and MUT schemes are explained with the aid of the concepts of altruistic-optimization and egocentric-optimization.

Additionally, in order to gain insight into the effect of noise power on the achievable performance of a MUT scheme, a noise-suppression factor is introduced to those MUT schemes, such as MMSE, requiring the knowledge of the noise variance. Our study shows that the achievable performance of this kind MUTs is generally loosely depended on the noise-suppression factor. This finding may result in extremely low-complexity wireless transceivers in time-division duplex (TDD) cellular systems, where, at base-stations (BSs), the uplink MUD and downlink MUT can be implemented based on one adaptive signal processing scheme.

报告人简介: Professor Lie-Liang Yang, University of Southampton, UK; BEng MEng PhD, Senior Member IEEE, Member IET; Reader of the Communications Research Group.

Generally, he is interested in working in the rich field of communications and signal processing. Some of his specific research interests are listed as follows.

Adaptive wireless transceivers including research in the fields of adaptive signal processing, adaptive channel estimation and prediction, adaptive multiuser detection, adaptive-rate transmissions, etc.  Multiuser detection, adaptive detection, blind detection, transmitter multiuser detection and turbo detection in CDMA and SDMA, etc. systems; Interference suppression, diversity combining, noncoherent multiuser detection, etc. in fast frequency-hopping multiple-access (FFHMA) systems; Joint diversity combining, equalization and time-frequency analysis; Multicarrier wireless communications including OFDM, multicarrier CDMA, etc.; Networking information theory, networking coding, intelligent wireless networking, cooperative wireless networking, cellular wireless systems, self-organizing wireless ad-hoc networking, etc.;  Smart antennas, space-time coding, transmitter diversity, adaptive and MIMO (Multiple-in-Multiple-out) techniques; Wideband, broadband, ultra-wideband wireless communications, ultra-wideband impulse radio. Symmetrical, non-symmetrical and unidirectional channel coding, modulation and coding, turbo coding, iterative decoding, Redundant Residue Number System (RRNS) based coding, etc.; Parallel processing and transmission, Residue Number System (RNS), OFDM, Multicarrier CDMA; Pseudo-noise (PN) code acquisition and tracking as well as synchronization techniques in spread-spectrum systems; Source coding, joint source-channel coding/decoding;