Application-specific instruction set processor implementation of list sphere detector
EURASIP Journal on Embedded Systems
Quasi-maximum-likelihood detector based on geometrical diversification greedy intensification
IEEE Transactions on Communications
The error probability of the fixed-complexity sphere decoder
IEEE Transactions on Signal Processing
IEEE Transactions on Wireless Communications
On analytical derivations of the condition number distributions of dual non-central Wishart matrices
IEEE Transactions on Wireless Communications
A robust detection method to improve the performance of MIMO communication receivers
CSN '07 Proceedings of the Sixth IASTED International Conference on Communication Systems and Networks
A simple and optimum geometric decoding algorithm for MIMO systems
ISWPC'09 Proceedings of the 4th international conference on Wireless pervasive computing
IEEE Transactions on Communications
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Low-complexity algorithm for log likelihood ratios in coded MIMO-OFDM communications
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Variable-breadth K-best detector for MIMO systems
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Simplified ordering for fixed-complexity sphere decoder
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Markov chain Monte Carlo detection methods for high SNR regimes
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Performance: complexity comparison of receivers for a LTE MIMO-OFDM system
IEEE Transactions on Signal Processing
On the condition number distribution of complex wishart matrices
IEEE Transactions on Communications
Algorithmic Exploration and Implementation of a MIMO-OFDM Equalizer
Journal of Signal Processing Systems
Efficient Detection Algorithms for MIMO Communication Systems
Journal of Signal Processing Systems
| Hi-index | 35.69 |
It is well known that suboptimal detection schemes for multiple-input multiple-output (MIMO) spatial multiplexing systems (equalization-based schemes as well as ing-and-cancelling schemes) are unable to exploit all of the available diversity, and thus, their performance is inferior to ML detection. Motivated by experimental evidence that this inferior performance is primarily caused by the inability of suboptimal schemes to deal with "bad" (i.e., poorly conditioned) channel realizations, we study the decision regions of suboptimal schemes for bad channels. Based on a simplified model for bad channels, we then develop two computationally efficient detection algorithms that are robust to bad channels. In particular, the novel sphere-projection algorithm (SPA) is a simple add-on to standard suboptimal detectors that is able to achieve near-ML performance and significantly increased diversity gains. The SPA's computational complexity is comparable with that of ing-and-cancelling detectors and only a fraction of that of the Fincke-Phost sphere-decoding algorithm for ML detection.