A mimo turbo equalizer for frequency-selective channels with unknown interference (original) (raw)

Space-time turbo equalization in frequency-selective mimo channels

IEEE Transactions on Vehicular Technology, 2003

A computationally efficient space-time turbo equalization algorithm is derived for frequency-selective multiple-input-multiple-output (MIMO) channels. The algorithm is an extension of the iterative equalization algorithm by Reynolds and Wang for frequency-selective fading channels and of iterative multiuser detection for code-division multiple-access (CDMA) systems by Wang and Poor. The proposed algorithm is implemented as a MIMO detector consisting of a soft-input-soft-output (SISO) linear MMSE detector followed by SISO channel decoders for the multiple users. The detector first forms a soft replica of each composite interfering signal using the log likelihood ratio (LLR), fed back from the SISO channel decoders, of the transmitted coded symbols and subtracts it from the received signal vector. Linear adaptive filtering then takes place to suppress the interference residuals: filter taps are adjusted based on the minimum mean square error (MMSE) criterion. The LLR is then calculated for adaptive filter output. This process is repeated in an iterative fashion to enhance signal-detection performance. This paper also discusses the performance sensitivity of the proposed algorithm to channel-estimation error. A channel-estimation scheme is introduced that works with the iterative MIMO equalization process to reduce estimation errors.

Iterative receivers for STTrC-coded MIMO turbo equalization

2004 IEEE 59th Vehicular Technology Conference. VTC 2004-Spring (IEEE Cat. No.04CH37514), 2004

The problem of iterative multiuser detection in single-carrier broadband multiple-input multiple-output (MIMO) system is studied in this paper. Two minimum mean squared error (MMSE) multiuser receivers are proposed for space-time trellis coded systems in frequency selective channels. The first receiver uses the MMSE criterion both for multiuser detection and equalization. The second one uses the MMSE criterion only for multiuser detection, while the equalization part is an optimal maximum a posteriori (MAP) equalizer. The second receiver significantly outperforms the first one both in the presence and in the absence of the unknown co-channel interference, at the expense of increased complexity.

Reduced-Complexity Time-Domain Equalization for Turbo-MIMO Systems

IEEE Transactions on Communications, 2000

ABSTRACT A reduced-complexity time-domain equalization scheme for wideband turbo-multiple-input multiple-output (turbo-MIMO) systems is presented. This scheme, called iterative trellis search equalization, is based on a modified version of the M-Bahl-Cocke-Jelinek-Raviv (M-BCJR) algorithm, applied to a suitably chosen trellis representation of the wideband MIMO channel process. Exploiting the properties of quadrature amplitude modulation (QAM) signal constellations with block-partitionable labels, this modified M-BCJR algorithm has complexity per bit that is independent of the constellation size, and polynomial in the number of transmit antennas and channel memory. Results from computer simulations show that the new scheme successfully mitigates intersymbol interference even if only a very small fraction of trellis state transitions is considered. It is also demonstrated that asynchronous transmission of the spatially multiplexed symbol streams can result in considerable performance improvement compared to synchronous MIMO systems.

Iterative Channel Estimation for Turbo Equalization of Time-Varying Frequency-Selective Channels

IEEE Transactions on Wireless Communications, 2004

We investigate turbo equalization, or iterative equalization and decoding, as a receiver technology for systems where data is protected by an error-correcting code, shuffled by an interleaver, and mapped onto a signal constellation for transmission over a frequency-selective channel with unknown time-varying channel impulse response. The focus is the concept of soft iterative channel estimation, which is to improve the channel estimate over the iterations by using soft information fed back from the decoder from the previous iteration to generate "extended training sequences" between the actual transmitted training sequences.

Performance of frequency domain multiuser-MIMO turbo equalization without cyclic prefix

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2017

Multiuser (MU)-multiple-input multipleoutput (MIMO) receivers often need to take iterative strategies to cancel multiuser-interference (MUI). Frequency domain turbo equalization is one of the most promising solutions to the MUI problem. It offers a reasonable trade-off between the receiver performance and the computational complexity by assuming cyclic prefix (CP)-transmission. Nevertheless, CP-transmission is not preferable for the battery life of user terminals. Therefore, this paper proposes a new frequency domain multiuser-detection (MUD) technique by extending the chained turbo equalization (CHATUE) to MU-MIMO systems. Simulation results verify that the proposed MU-MIMO CHATUE algorithm is a more reliable option to improve the spectral-and/or energy-efficiency by eliminating the necessity of CP-transmission than by shortening the training sequences or puncturing the coded data bits. Index Terms-Spectral efficiency, multiuser interference (MUI), cyclic prefix (CP), overlap-and-add.

MIMO decision-feedback equalization with direct channel estimation

IEEE 5th Workshop on Signal Processing Advances in Wireless Communications, 2004.

This paper addresses the problem of channel intersymbol interference suppression in the presence of multiple sources. The approach, based on multiple-input/multiple-output (MIMO) decisionfeedback equalization (DFE), extends a known singleuser architecture that is well suited for operation in severely distortive channels. By working with a direct channel model to remove postcursor interference, the receiver can readily take advantage of known properties of the channel, such as sparsity of its impulse response, to improve the computational efficiency or tracking ability. Similarly to other MIMO equalizers, the finite-length coefficient matrices are optimized under an exact minimum mean-square error (MMSE) criterion. The MIMO setting offers additional flexibility relative to single-user scenarios that enables partial feedback of decisions pertaining to the current data block, in addition to previous blocks. Simulation results illustrate the performance of this DFE in single-carrier multiuser communication and single-user multicarrier modulation.

Turbo aided maximum likelihood channel estimation for space-time coded systems

2002

In this paper we propose a novel approach to estimating Multiple-Input-Multiple-Output (MIMO) channels in space-time coded systems. The channel is assumed to introduce dispersion in both the spatial and temporal dimensions. The channel estimator is obtained by applying the Maximum Likelihood principle not only over a known pilot sequence, as it is done in the classical Least-Squares approaches, but over all the symbols (both known and unknown) in a data frame. Since this results in an optimization problem without closedform solution, we utilize an iterative method, the Expectation-Maximization (EM) algorithm, to calculate the solution. The resulting channel estimator is particularly suitable to be used in a Turbo equalizing structure because it gets benefit from the a posteriori probabilities about the transmitted symbols computed at each decoding iteration of the Turbo process.