A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.

Maximum Likelihood Decoding (MLD) is computationally complex technique for decoding received information in multiple input multiple output (MIMO) systems. Tree search algorithms such as sphere decoding (SD) and QR decomposition with M survivals (QRD-M) are used to reduce the complexity keeping the performance near ML. This paper presents two techniques for reducing the computational complexities of the tree search algorithms further. The first technique is based on selecting the initial radius for sphere decoding. The main contribution of this paper is that the greedy best first search is used to compute initial radius, instead of Babai estimate. The second contribution is, QRD-M algorithm is modified to prune the nodes in the current layer based on maximum metric of child nodes of smallest surviving node. The performance of the proposed techniques is tested for different MIMO systems in terms of bit error rates (BER) and average number of nodes visited. The proposed schemes have improved computational complexity with no degradation of performance.

This paper presents a combined approach to channel estimation for multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM). It uses both time domain and frequency domain information in the received signal to estimate the channel. Initial estimate of the channel is obtained using pilot assisted least square (LS) channel estimation. The estimate is further enhanced by extracting information through the received data symbols. A frequency domain approach is used to estimate the channel using pilots whereas time domain approach is used to enhance the estimate of the channel. The performance of the proposed estimator is studied under various channel models. The simulation study shows that this approach outperforms the pilot assisted least square channel estimation method. General Terms ChannelEstimation, MIMO-OFDM, Wireless Communication. KeywordsMultiple input multiple output, orthogonal frequency division multiplexing, pilot assisted least square channel estimation, space frequency block coding.

A new approach to Semi-Blind Channel Estimation (SBCE) technique for Multiple Input Multiple Output (MIMO) wireless communication system is proposed. It combines the Least Square (LS) and Minimum Mean Square Error (MMSE) Training Based Channel Estimation (TBCE) scheme with whitening rotation based orthogonal pilot maximum likelihood (OPML) semi-blind channel estimation (SBCE) scheme. In the new approach the whitening matrix is obtained from blind data and rotation matrix is obtained from LS estimated channel. Another modification suggested in this contribution is the use of whitening matrix for MMSE estimate. The channel correlation matrix required for MMSE estimation can be obtained based on latest channel statistics and hence is more reliable. At high SNR this scheme offers better performance than the OPML SBCE method. These advantages are achieved at the cost of negligible reduction in performance in low SNR regime.

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