Multiuser Detection
Space-Time Coding
EURASIP Journal on Wireless Communications and Networking - Special issue on multiuser MIMO networks
Practical aspects of preprocessing techniques for K-Best tree search MIMO detectors
Computers and Electrical Engineering
Linear transmit processing in MIMO communications systems
IEEE Transactions on Signal Processing - Part I
Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels
IEEE Transactions on Signal Processing
Transceiver optimization for multiuser MIMO systems
IEEE Transactions on Signal Processing
A transmit preprocessing technique for multiuser MIMO systems using a decomposition approach
IEEE Transactions on Wireless Communications
A novel prefiltering technique for downlink transmissions in TDD MC-CDMA systems
IEEE Transactions on Wireless Communications
Performance analysis of maximum ratio transmission based multi-cellular MIMO systems
IEEE Transactions on Wireless Communications
Asynchronous Interference Mitigation in Cooperative Base Station Systems
IEEE Transactions on Wireless Communications
On the Ergodic Capacity of MIMO Triply Selective Rayleigh Fading Channels
IEEE Transactions on Wireless Communications
Block diagonalization for multi-user MIMO with other-cell interference
IEEE Transactions on Wireless Communications
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The performance of cellular uplink multiple-input multiple-output systems, where co-channel interference (CCI) at the base stations (BSs) is a major performance impairment, is investigated in this correspondence principally from a multi-user transmitter preprocessing (MUTP) perspective over correlated frequency-selective channels. Transmitter preprocessing at the mobile station is formulated by singular value decomposition (SVD) of only the individual user's channel state information (CSI) while post-processing exploits all the users' CSI using BS cooperation. Our simulations show that this approach completely removes CCI and also outperforms classical zero-forcing multi-user detection, which has about the same detection complexity. Further, the results show that our system, coupled with the optimal 'water-filling' strategy for power allocation, results in higher capacity than the maximum signal-to-noise ratio strategy. Furthermore, SVD-based MUTP outperforms dirty paper coding and Tomlinson-Harashima precoding in terms of achievable symbol error rate.