Frequency-selective Fading MIMO Channel Research Articles

Generalized Reduced-State Vector Sequence Detection

A multi-dimensional set-partitioning scheme is proposed for joint reduced-state sequence detection (JRSSD) of vector sequences corrupted by intersymbol interference (ISI) and additive white Gaussian noise (AWGN). The existing multi-dimensional set-partitioning schemes result in complexity exponential in the dimensionality of the vectors in the vector sequence. The proposed set-partitioning scheme allows the construction of reduced-state trellises with very few states even when the vectors are of high dimensionality. One of the key requirements of the JRSSD algorithm is an efficient algorithm for spatial multi-symbol detection, for which we propose the reduced-state tree (RST) detection algorithm. In addition to performance improvement, the inclusion of RST algorithm for spatial multi-symbol detection provides a common framework for designing receivers for both flat-fading and frequency-selective fading MIMO channels.

Precoding for Orthogonal Space–Time Block-Coded OFDM Downlink: Mean or Covariance Feedback?

This paper presents linear and nonlinear precoding design for error-rate improvement in orthogonal space-time block-coded (OSTBC) multiple-input-multiple-output (MIMO) orthogonal frequency-division-multiplexed (OFDM) downlink, where both the conditional mean of the channel gain matrix and the channel gain covariance matrix may be available at the transmitter. The conditional means of the channel matrix are derived for a general transmit-antenna-correlated frequency-selective fading MIMO channel with estimation errors and feedback delay. Mean-feedback linear precoding and nonlinear Tomlinson-Harashima precoding (THP) are developed to maximize the signal-to-noise power ratio (SNR). The intuition that when the mean feedback becomes accurate the mean-feedback precoding outperforms covariance precoding is confirmed. Dual-mode precoding is also proposed, in which the novel mean-feedback precoding or covariance precoding is adaptively chosen at the receiver. The precoding-mode switching metric is the maximized SNR, which is an indicator of the error rate. The receiver calculates its metric, selects the mode that achieves a higher SNR, and decides whether mean feedback is necessary. Our proposed precoders (both mean feedback and adaptive) significantly reduce the system error rate. Nonlinear precoding is shown to outperform linear precoding. Adaptive precoding outperforms both mean-feedback precoding and covariance precoding if individually applied in OSTBC OFDM.

On the Ergodic Capacity of Rank-$1$ Ricean-Fading MIMO Channels

This paper investigates the ergodic capacity of Ricean-fading multiple-input-multiple-output (MIMO) channels with rank-1 mean matrices under the assumption that the channel is unknown at the transmitter and perfectly known at the receiver. After introducing the system model and the concept of ergodic capacity of MIMO channels, we derive the explicit expressions for the expected values of the determinant and log-determinant of complex noncentral Wishart matrices. Subsequently, we obtain new upper and lower bounds on the ergodic capacity of rank-1 Ricean-fading MIMO channels at any signal-to-noise ratio (SNR). We show that our bounds are tighter than previously reported analytical bounds, and discuss the impact of spatial fading correlation and Ricean K-factor with the help of these bounds. Furthermore, we extend the analysis of ergodic capacity to frequency selective spatially correlated Ricean-fading MIMO channels. We demonstrate that the calculation of ergodic capacity of frequency selective fading MIMO channels can be converted to the calculation of the one of equivalent frequency flat-fading MIMO channels. Finally, we present numerical results that confirm the theoretical analysis

Training Sequence Design and Parameter Estimation of MIMO Channels with Carrier Frequency Offsets

This letter addresses the carrier frequency offsets and channel gains estimation problem for MIMO channels with multiple carrier frequency offsets that are not assumed to be equal for all transmit-receive antenna pairs. Training sequences are proposed for both flat fading and frequency selective fading MIMO channels. Under the proposed training sequences, sub-optimal performance of parameter estimation can be achieved by a subspace-based method with reasonable computational complexity. The method can also provide flexible tradeoff between complexity and performance

Joint spatial and temporal channel-shortening techniques for frequency selective fading MIMO channels

It is well understood that the maximum likelihood estimator is a powerful equalisation technique for frequency selective fading channels, and in particular for MIMO systems. The complexity of this estimator, however, grows exponentially with the number of users and multipath taps, hence limiting the use of this algorithm in MIMO systems. In the paper, the authors propose a joint spatial and temporal channel-shortening filter as a pre-processor to reduce significantly the complexity of a maximum likelihood estimator. Their design is based on both minimum mean square error and maximum signal-to-noise ratio criteria. They compare the performance of their proposed schemes with the existing methods that employ channel-shortening techniques only in the spatial or temporal dimension, and thereby demonstrate the advantage of using joint spatial and temporal channel shortening in terms of complexity and bit error rate performance.