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This paper deals with the optimal design of training sequences to estimate multiple-input multiple-output orthogonal frequency division multiplexing channels in the presence of spatial fading correlations. The optimal design criterion is the maximization of the mutual information between the unknown channel state information and the received signal in the training period. In contrast to previous methods...
High transmission data rate, spectral efficiency, and reliability are necessary for future wireless communications systems. In this paper, we study the performance of multi-user multiple-input multiple-output channel estimation methods using training sequences. We consider the popular linear least square (LS) and minimum mean-square-error (MMSE) approaches. The results of computer simulation show...
This paper investigates the problem of designing reverse channel training sequences for a TDD-MIMO spatial-multiplexing system. Assuming perfect channel state information at the receiver and spatial multiplexing at the transmitter with equal power allocation to the m dominant modes of the estimated channel, the pilot is designed to ensure an estimate of the channel which improves the forward link...
This paper reports on investigations into the effects of spatial correlation on channel estimation and capacity of a multiple input multiple output (MIMO) system. Minimum mean square error (MMSE) method is applied for channel estimation under a correlated channel scenario. Simulation results for a 4 times 4 MIMO system with the Jakes model describing a channel between a base station and a mobile station...
Effects of improved channel estimation are studied for a proposed IEEE 802.11n OFDM MIMO system. Three channel estimation methods are considered: maximum likelihood (ML), time-domain truncation (TDT) and model-based (MB). TDT and MB are particularly useful when the channel delay spread is short. For an MMSE receiver, MB shows a 1-2.5 dB improvement over ML on the packet error rate performance for...
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