Space-time processing for co-channel interference (CCI) rejection and equalization with antenna arrays may provide large gains over space-only processing, especially in interference limited scenarios. However, taking thetemporal correlation of the noise and CCI process into account leads to sequence detection with highercomplexity as compared to space-only processing that neglects this correlation. We propose the use of the generalized Viterbi algorithm for sequence detection with lower complexity. Special cases include the M-algorithm and the delayed decision feedback sequence estimator. A relevant comparison between spatial andspatio-temporal processing with sequence detectors of the same complexity may thus be performed. Numerical examples show substantial gains for spatio-temporal processing as compared to space-only processing also in this case when the optimality of the sequence detector is traded for interference rejection.

In wireless communication scenarios, multipath propagation may cause angular spreading as seen from a base station antenna array. Environments where most energy incident on the array is from scatterers local to the mobile transmitters are considered, and the effects on direction of arrival (DOA) estimation with the MUSIC algorithm are studied. Previous work has studied rapidly time-varying channels and concluded that local scattering has a minor effect on DOA estimation in such scenarios. In this work, a channel that is time-invariant during the observation period is considered, and under the assumption of small angular spread, an approximate distribution for the DOA estimates is derived. The results show that local scattering has a significant impact on DOA estimation in the time invariant case. Numerical examples are included to illustrate the analysis and to demonstrate that the results may be used to formulate a simple estimator of angular spread. An extension to more general Rayleigh and Ricean fading channels is also included, In addition, results from processing experimental data collected in suburban environments are presented. Good agreement with the derived distributions is obtained.

The problem of spatial signature estimation using a uniform linear array (ULA) with unknown receiver gain and phase responses is studied. Sufficient conditions for identifying the spatial signatures are derived, and a closed-Form ESPRIT-like estimator is proposed, The performance of the method is investigated by means of simulations and on experimental data collected with an antenna array in a suburban environment. The results show that the absence of receiver calibration is not critical for uplink signal waveform estimation using a plane wave model.

In wireless communication scenarios, local scatterers in the vicinity of the sources cause angular spreading. A parameterization of the spatial signature in the presence of local scattering is presented which applies to uniform linear arrays (ULAs). The spatial signature is shown to be approximately a Vandermonde vector for a ULA inenvironments with small angular spread. An estimator of the spatial signature is formulated based on ESPRIT. Fora simple signal waveform estimator the gain may be considerable in scenarios with multiple sources, as compared with using the ideal manifold parameterized by direction of arrival (DOA).

In wireless communication scenarios, multipath propagation from local scatterers in the vicinity of mobile sources may cause angular spreading as seen from a base station antenna array. This paper studies the effects of suchlocal scattering on direction of arrival (DOA) estimation with the MUSIC and ESPRIT algorithms. Previous work has considered rapidly time-varying scenarios, and concluded that local scattering has a minor effect on DOAestimation in such scenarios. This work considers the case in which the channel is time-invariant during theobservation period. The distribution of the DOA estimates is derived, and the results show that local scatteringhas a significant impact on DOA estimation in the time-invariant case. In addition, numerical examples are included to illustrate the analysis, and to demonstrate that the results may be used to formulate simple estimators of angular spread.

The authors propose the use of a generalised array manifold for parameterised spatial signature estimation in wireless communication channels with local scattering. The array manifold commonly used for point sources is generalised to include linear combinations of the nominal array response vectors and their derivatives. The motivation behind this idea is to obtain better estimates of the spatial signatures for direction of arrival (DOA) based signal waveform estimation. The estimators proposed exploit the orthogonality between the so-called noise and signal subspaces, leading to a separable solution for the derivative coefficients. As a result, a search is required for the DOAs only. For uniform linear arrays, the spatial signatures are shown to be approximately Vandermonde vectors with damped modes, and a closed-form estimator such as ESPRIT may be used in this case. Simulation examples are included to compare the signal estimation performance obtained using the proposed generalised manifold and the conventional array manifold.

In wireless communication scenarios, local scatterers in the vicinity of the mobile sources cause angular spreading. As a result, the spatial signatures will not belong to the conventional array manifold parameterized by direction of arrival (DOA) alone. A parameterized model for spatial signatures applicable in scenarios with localscattering is presented. Several algorithms that exploit this model are proposed, and the performance of signal waveform estimators using the model is investigated via simulations. It is demonstrated that considerable gain may result as compared with using the conventional plane wave model.

In this paper, the problem of signal waveform estimation using a uniform linear array with unknown receiver gain and phase responses is considered. As is well known, it is not possible to uniquely estimate directions-of-arrival(DOAs) and receiver gain and phase simultaneously. For steering vector and signal separation this ambiguity is notcritical. An ESPRIT-like solution is presented, and the proposed method is examined on data collected with an antenna array in a suburban environment.

We consider antenna arrays equipped with cross-polarized antenna elements. The multipath propagation will affect both the spatial characteristics and the polarization of the received signals which will influence the performance of the system in terms of, for example, bit error rate or direction estimation. In this paper, we present results from field measurement data recorded at the 1800 MHz band, provided by Ericsson Radio Systems AB. The study is divided into two main parts. In the first part we introduce a diversity gain measure related to the BER of an MRC receiver. The polarization diversity introduced by the radio channel is studied, and compared to the spatial diversity. In the second part we use a parameterized model of the received polarized radio waves and illustrate the typical behavior of the estimated polarization parameters

Modern communication systems are often interferencelimited. By modeling the co-channel interference asspatially colored, temporally white Gaussian noise, itis straightforward to incorporate interference rejectionin the metric of a sequence estimator. In general, estimates of both the channels and the spatial color of theco-channel interference and the noise are needed. In thiswork, a structured model for the spatial noise covariancematrix is proposed and maximum likelihood estimates ofthe parameters are derived. The choice of model orderis also addressed. Simulation results show large gains due to the use of these structured estimates compared with the conventional, unstructured, approach.

We propose a structured, training sequence based method to find the parameters of a spatio-temporal co-channel interference (CCI) rejection filter. By exploiting the inherent structure of the CCI, it is shown that the number of parameters that are to be estimated can be made independent of the spatio-temporal filter order. It is further shown that by taking advantage of the desired user's known protocol structure, the parameters can be estimated using a semi-blind technique. Simulation results indicate that by taking the structure into account, for short training sequences, considerable gains are achievable compared to an unstructured method.

Herein, we provide an overview of the research conducted in the project "Spatio-Temporal Processing in Wireless Communications" supported by NUTEK's telecommunications program. Spatio-temporal processing at the base stations of a wireless system can provide processing gain which may be used to extend range and improve coverage of the network and/or improve signal quality and lower terminal power requirements. Furthermore, with spatially selective reception and transmission, the capacity in wireless communication systems can be increased without exploiting additional bandwidth. We will give an overview of the results of this research project to date.