Signal Processing - Special section on signal processing technologies for short burst wireless communications
Adaptive MLSE Equalizer with Per-Survivor QR Decomposition for Trellis-Coded MIMO Transmission
Wireless Personal Communications: An International Journal
Fundamentals of wireless communication
Fundamentals of wireless communication
An Investigation of MIMO Performance in the Indoor Ricean Environment
Wireless Personal Communications: An International Journal
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Introduction to Space-Time Wireless Communications
Introduction to Space-Time Wireless Communications
Blind separation of synchronous co-channel digital signals using anantenna array. I. Algorithms
IEEE Transactions on Signal Processing
Blind digital signal separation using successive interferencecancellation iterative least squares
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Training-based MIMO channel estimation: a study of estimator tradeoffs and optimal training signals
IEEE Transactions on Signal Processing
Signal detection for MIMO-ISI channels: an iterative greedy improvement approach
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing - Part I
Interference cancellation for cellular systems: a contemporary overview
IEEE Wireless Communications
Estimation of continuous flat fading MIMO channels
IEEE Transactions on Wireless Communications
Efficient joint maximum-likelihood channel estimation and signal detection
IEEE Transactions on Wireless Communications
On maximum-likelihood detection and the search for the closest lattice point
IEEE Transactions on Information Theory
Wireless Personal Communications: An International Journal
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The aim of this paper is to investigate receiver techniques for maximum likelihood (ML) joint channel/data estimation in flat fading multiple-input multiple-output (MIMO) channels, that are both (i) data efficient and (ii) computationally attractive. The performance of iterative least squares (LS) for channel estimation combined with sphere decoding (SD) for data detection is examined for block fading channels, demonstrating the data efficiency provided by the semi-blind approach. The case of continuous fading channels is addressed with the aid of recursive least squares (RLS). The observed relative robustness of the ML solution to channel variations is exploited in deriving a block QR-based RLS-SD scheme, which allows significant complexity savings with little or no performance loss. The effects on the algorithms' performance of the existence of spatially correlated fading and line-of-sight paths are also studied. For the multi-user MIMO scenario, the gains from exploiting temporal/spatial interference color are assessed. The optimal training sequence for ML channel estimation in the presence of co-channel interference (CCI) is also derived and shown to result in better channel estimation/faster convergence. The reported simulation results demonstrate the effectiveness, in terms of both data efficiency and performance gain, of the investigated schemes under realistic fading conditions.