Orthogonal Affine Precoding and Decoding for Channel Estimation and Source Detection in MIMO Frequency-Selective Fading Channels

Superimposed Training Designs for Spatially Correlated MIMO-OFDM Systems

“…Such an approach was proposed in [9], [10] for MIMO frequency-selective fading channel and in [2] for OFDM channel to improve detection performance. Different from [5], [9], [10], for the MIMO-OFDM systems under consideration, both non-redundancy pre-multiplying and redundant post-multiplying precoders are employed to handle antenna correlations and combat channel fading. This is described further in the following.…”

“…Specifically, the approach of superimposed training, i.e., the training signal is superimposed on linearly precoded data, is considered. It should be pointed out that SP training designs have been obtained for estimation of correlated flat fading MIMO channels in [5] and uncorrelated frequency-selective fading channels in [9], [10]. Our previous SP training designs shall be extended to the more general and challenging case of spatially correlated MIMO-OFDM.…”

“…In addition to employing a post-multiplying based precoder which introduces redundancy to guard against frequencyselective fading [9], [10], we further propose to use nonredundancy pre-multiplying based precoder to cope with the spatial correlation. This type of non-redundancy precoder was shown to efficiently combat colored noise in [11].…”

Optimal Superimposed Training Design for Spatially Correlated Fading MIMO Channels

“…Therefore there is much more freedom in the optimal design of these matrices. Indeed, the results in [22], [31] demonstrate that this design approach is superior than the designs in [14], [18], [37] in terms of estimation performance, symbol detectability and computational complexity.…”

“…This together with several complex arrangements make these matrices commutative with the channel matrix and hence, decouple the two subspaces of the data-bearing and training signals. A novel approach has also been recently developed in [22], [25], [31], where the received signal is viewed along space, i.e., as a concatenation of the rows of the received signal matrix. The most important consequence of this view is that the two subspaces of interest are independent of the channel matrix.…”