We present multiuser space-time receiver algorithms for synchronization, channel estimation, and data detection in the downlink of a universal mobile telecommunications system (UMTS)/time-division duplex (TDD) cellular communication system with multiple receive antennas. These algorithms were designed for use in a network monitoring device that analyzes the interference situation present, thereby allowing the operators to improve their networks. For interference analysis, we decode the broadcast channels (BCHs) of surrounding base stations. To cope with the widely differing power levels of signals received from different base stations, we combine multiuser space-time signal processing techniques with reestimation and successive cancellation schemes. Simulation results demonstrate that our algorithms enable reliable BCH data detection even at low SINR.

The conventional nulling-and-cancelling (NC) detection scheme for MIMO systems uses the layerwise post-detection mean-square errors (MSEs) as reliability measures for layer sorting. These MSEs are average measures that do not depend on the received vector. We propose a novel dynamic nulling-and-cancelling (DNC) detector that performs "dynamic" layer sorting based on the current received vector. Approximate a-posteriori probabilities (constructed by means of a Gaussian approximation for the postdetection interference) are used as measures of layer reliability. This results in an MMSE nulling technique that uses a simple layer-sorting rule with significantly improved performance. Our simulation results show that the DNC scheme can yield near-ML performance for a wide range of system sizes and signal-to-noise ratios.

We reduce the complexity of sphere decoding for space-time transmission by "guessing" the first few levels of the search tree a priori. These guesses are based on a simplified channel model. The resulting complexity is only a fraction of the original complexity while performance remains close to optimal.

A space-time detection algorithm for a UMTS/TDD downlink scenario with strong interference is proposed. Conventional space-time detection schemes based on MMSE equalization require accurate estimation of the correlation matrix of the received signal vector, which is difficult because of the time variation of the mobile radio channel. We thus develop a decision feedback detection scheme in which the correlation matrix is "detected" rather than estimated. For detection of the active data channels, a maximal invariant detection statistic is presented. Simulation results demonstrate that the proposed space-time detection algorithm features good performance for various realistic propagation scenarios even at low SINR.

It is well known that suboptimal detection schemes for MIMO spatial multiplexing systems (equalization-based as well as nulling-and-cancelling detectors) cannot exploit all of the available diversity. We show that this inferior performance is primarily caused by poorly conditioned channel realizations. We then present the novel sphere-projection algorithm (SPA) that is robust to poorly conditioned channels. The SPA is a computationally efficient add-on to standard suboptimal detectors. Simulation results show that the SPA is able to achieve near-ML performance and significantly increased diversity gains. The SPA's computational complexity is comparable to that of nulling-and-cancelling detectors and only a fraction of that of the Fincke-Phost sphere-decoding algorithm for ML detection (Fincke, U. and Phost, M., Math. of Comp., vol.44, p.463-71, 1985).

Most transmission schemes for MIMO channels assume (i) a block fading channel without delay spread and (ii) availability of channel state information at the receiver. Here, we extend the space-time matrix modulation (STMM) scheme and the iterative demodulation algorithm that we introduced previously (Arte/spl acute/s, H. and Hlawatsch, F., Proc. IEEE ICASSP-2001, p.2153-6, 2001; Proc. IEEE ICASSP-2002, p.2225-8, 2002; Arte/spl acute/s et al., Proc. 39th Allerton Conf. Commun., Contr, Comput., p.466-75, 2001) to unknown, doubly selective MIMO channels, i.e., delay/Doppler-spread MIMO channels that are unknown to the receiver. We show that the structure inherent in STMM allows perfect reconstruction of the data when transmitting over an unknown doubly selective channel (apparently, this is not currently possible with other transmission schemes). Numerical simulations demonstrate significant performance advantages of STMM over Cayley differential unitary space-time modulation.

We present space-time methods for channel estimation in the downlink of a UMTS/TDD system. The channels associated to all base stations near the mobile receiver are estimated by a multiuser, multi-antenna technique. We develop a minimum mean-square error (MMSE) channel estimator that incorporates midamble detections/estimation and least-squares channel estimation as preparatory stages. Combination of this MMSE channel estimator with a successive interference cancellation scheme allows to cope with strong co-channel interference. Simulation results indicate the good performance of our space-time channel estimator for various realistic propagation scenarios.

This paper presents methods for synchronization In the downlink of a UMTS/TDD system. Space-time processing based on multiple receive antennas is used to suppress potentially strong co-channel interference caused by other base stations. We develop a detection-based synchronization procedure exploiting the structure of UMTS/TDD, and we present three alternative detection algorithms. Simulation results using various propagation scenarios indicate the good performance of our synchronization methods in the presence of strong co-channel interference.

We extend a previously introduced space-time modulation scheme (which we call matrix modulation) to the practically important cases of rank-deficient channels and multiple users. In particular, we prove an identifiability result and present an efficient demodulation method for these cases. Our matrix modulation technique does not require channel state information at the transmitter or receiver side. Its structure is strong enough to permit joint data and channel estimation without knowledge of the data alphabet. In the multi-user case, matrix modulation yields a flexible transmission scheme that can easily be adapted to different data-rate requirements of individual users. Numerical simulations demonstrate the good performance of the matrix modulation/demodulation technique.

We present a novel precoding or modulation scheme (matrix modulation) that allows parallel transmission of several data signals over an unknown multiple-input multiple-output (MIMO) channel. We first present a theorem on unique signal demodulation and an efficient iterative demodulation algorithm for transmission over an unknown instantaneous-mixture channel. We then generalize our results to an unknown MIMO channel with memory.

We present two POCS (projections onto convex sets) algorithms for deterministic blind equalization of linear time-varying (LTV) channels. Our approach is based on a multichannel LTI representation of LTV channels. We prove a theorem on unique reconstruction/equalization, formulate a POCS algorithm for the resolution of a matrix ambiguity, and show how to cope with unequal subchannel lengths. We also present an alternative POCS algorithm for equalization that avoids a singular value decomposition. Both algorithms are guaranteed to converge to the desired solution.