Conference Paper

Error-entropy based channel state estimation of spatially correlated MIMO-OFDM.

University of New South Wales, Sydney, Australia
DOI: 10.1109/ICASSP.2011.5947132 Conference: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic
Source: DBLP

ABSTRACT This paper deals with optimized training sequences to estimate multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) channel states in the presence of spatial fading correlations. The optimization criterion is the entropy minimization of the error between the high multi-dimensional and correlated channel state and its estimator. The globally optimized training sequences are exactly solved by a semi-definite programming (SDP) of tractable computational complexity O((M t (M t + 1)/2)2.5), where M t is the transmit antenna number. With new tight two-sided bounds for the objective function, the optimal value of the generic SDP can be approximately solved by the standard water-filling algorithm. Intensive simulation results are provided to illustrate the performance of our methods.

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    ABSTRACT: This paper deals with the capacity behavior of wireless orthogonal frequency-division multiplexing (OFDM)-based spatial multiplexing systems in broad-band fading environments for the case where the channel is unknown at the transmitter and perfectly known at the receiver. Introducing a physically motivated multiple-input multiple-output (MIMO) broad-band fading channel model, we study the influence of physical parameters such as the amount of delay spread, cluster angle spread, and total angle spread, and system parameters such as the number of antennas and antenna spacing on ergodic capacity and outage capacity. We find that, in the MIMO case, unlike the single-input single-output (SISO) case, delay spread channels may provide advantages over flat fading channels not only in terms of outage capacity but also in terms of ergodic capacity. Therefore, MIMO delay spread channels will in general provide both higher diversity gain and higher multiplexing gain than MIMO flat fading channels
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    ABSTRACT: The optimal training sequence for channel estimation in spatially correlated multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems has not been found for an arbitrary signal-to-noise ratio (SNR). Only one class of training sequences was proposed in the literature in which the power allocation is given only for the extreme conditions of low and high SNR. Provided in this paper are (i) a necessary and sufficient condition for the optimal training sequence together with a convex programming to find the solution, and (ii) efficient procedures to find the optimal training sequence. Simulation results confirms the superiority of the proposed design over the existing one.
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