Resource management for advanced transmission antenna satellites
IEEE Transactions on Wireless Communications
Effective spectral efficiency for adaptive QAM with diversity and pilot assisted channel estimation
ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
Adaptive TORC detection for MC-CDMA wireless systems
IEEE Transactions on Communications
Optimized simple bounds for diversity systems
IEEE Transactions on Communications
Receive antenna selection for closely-spaced antennas with mutual coupling
IEEE Transactions on Wireless Communications
Optimal weighted antenna selection for imperfect channel knowledge from training
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Rate adaptation in MIMO antenna selection system with imperfect CSIT
COMSNETS'10 Proceedings of the 2nd international conference on COMmunication systems and NETworks
IEEE Transactions on Communications
A novel, balanced, and energy-efficient training method for receive antenna selection
IEEE Transactions on Wireless Communications
Performance of non-ideal OT-MRC with co-channel interference
IEEE Transactions on Communications
| Hi-index | 0.00 |
In modern wireless systems employing diversity techniques, combining all the available diversity branches may not be feasible due to complexity and resource constraints. To alleviate these issues, subset diversity (SSD) systems have been proposed. Here, we develop a framework for evaluating the symbol error probability for antenna SSD, where the signals from a subset of antenna elements are selected and combined in the presence of channel estimation error. We consider independent identically distributed Rayleigh fading channels and use an estimator structure based on the maximum likelihood (ML) estimate which arises naturally as the sample mean of Np pilot symbols. The analysis is valid for arbitrary two-dimensional signaling constellations. The expressions give insight into the performance losses of non-ideal SSD when compared to ideal SSD. Due to estimation error, these losses occur in branch combining as well as in branch selection. However, our analytical results show that the practical ML channel estimator still preserves the diversity order of an ideal SSD system with Nd branches. Finally, we investigate the asymptotic signal-to-noise ratio penalty due to estimation error.