An improved recursive algorithm for BLAST
Signal Processing
Performance based receive antenna selection for V-BLAST systems
IEEE Transactions on Wireless Communications
Low-complexity systolic V-BLAST architecture
IEEE Transactions on Wireless Communications
On fast recursive algorithms for V-BLAST with optimal ordered SIC detection
IEEE Transactions on Wireless Communications
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Some results for the fast MMSE-SIC detection in spatially multiplexed MIMO systems
IEEE Transactions on Wireless Communications
Improved fast recursive algorithms for V-BLAST and G-STBC with novel efficient matrix inversion
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Parallel detection algorithm with selective interference cancellation for V-BLAST systems
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
IEEE Transactions on Communications
IEEE Transactions on Communications
Efficient Detection Algorithms for MIMO Communication Systems
Journal of Signal Processing Systems
Practical aspects of preprocessing techniques for K-Best tree search MIMO detectors
Computers and Electrical Engineering
A Novel DST-based Packet Combining Scheme for MIMO-HARQ Systems
Wireless Personal Communications: An International Journal
Low-complexity adaptive decision-feedback equalization of MIMO channels
Signal Processing
Computationally efficient near-optimal combined antenna selection algorithms for V-BLAST systems
Digital Signal Processing
| Hi-index | 35.68 |
Bell Laboratories layered space-time (BLAST) wireless systems are multiple-antenna communication schemes that can achieve very high spectral efficiencies in scattering environments with no increase in bandwidth or transmitted power. The most popular and, by far, the most practical architecture is the so-called vertical BLAST (V-BLAST). The signal detection algorithm of a V-BLAST system is computationally very intensive. If the number of transmitters is M and is equal to the number of receivers, this complexity is proportional to M4 at each sample time. We propose a very simple and efficient algorithm that reduces the complexity by a factor of M.