On the SNR penalty for antenna subset diversity
Proceedings of the 2006 international conference on Wireless communications and mobile computing
A stochastic geometry approach to coexistence in heterogeneous wireless networks
IEEE Journal on Selected Areas in Communications - Special issue on stochastic geometry and random graphs for the analysis and designof wireless networks
IEEE Transactions on Communications
IEEE Transactions on Wireless Communications
Low complexity SNR estimation for transmissions over time-varying flat-fading channels
WCNC'09 Proceedings of the 2009 IEEE conference on Wireless Communications & Networking Conference
Optimized rate-adaptive PSAM for MIMO MRC systems with transmit and receive CSI imperfections
IEEE Transactions on Communications
Optimized simple bounds for diversity systems
IEEE Transactions on Communications
Robust power allocation algorithms for wireless relay networks
IEEE Transactions on Communications
IEEE Transactions on Wireless Communications
| Hi-index | 0.01 |
In this paper, we present a framework for evaluating the bit error probability of Nd-branch diversity combining in the presence of non-ideal channel estimates. The estimator structure presented is based on the maximum-likelihood (ML) estimate and arises naturally as the sample mean of Np pilot symbols. The framework presented requires only the evaluation of a single integral involving the moment generating function of the norm square of the channel-gain vector, and is applicable to channels with arbitrary distribution, including correlated fading. Our analytical results show that the practical ML channel estimator preserves the diversity order of an Nd-branch diversity system, contrary to conclusions in the literature based upon a model that assumes a fixed correlation between the channel and its estimate. Finally, we investigate the asymptotic signal-to-noise ratio penalty due to estimation error and reveal a surprising lack of dependence on the number of diversity branches.