Orthogonal multiple access over time- and frequency-selective channels

Suppression of multiuser interference (MUI) and mitigation of time- and frequency-selective (doubly selective) channel effects constitute major challenges in the design of third-generation wireless mobile systems. Relying on a basis expansion model (BEM) for doubly selective channels, we develop a channel-independent block spreading scheme that preserves mutual orthogonality among single-cell users at the receiver. This alleviates the need for complex multiuser detection, and enables separation of the desired user by a simple code-matched channel-independent block despreading scheme that is maximum-likelihood (ML) optimal under the BEM plus white Gaussian noise assumption on the channel. In addition, each user achieves the maximum delay-Doppler diversity for Gaussian distributed BEM coefficients. Issues like links with existing multiuser transceivers, existence, user efficiency, special cases, backward compatibility with direct-sequence code-division multiple access (DS-CDMA), and error control coding, are briefly discussed.     

Joint prefiltering and MLSE equalization of space-time-codedtransmissions over frequency-selective channels

The problem of designing a front-end prefilter to improve the performance and/or reduce the complexity of maximum likelihood sequence estimation equalization of space-time-coded signals is addressed in this paper. The front-end prefilter performs channel shortening without excessive noise enhancement and is constrained to be a finite impulse response filter for practical implementation. Transmission scenarios emphasized assume two transmit antennas (with delay diversity or space-time trellis coding) and either one or two receive antennas. Extensions to more antennas are straightforward. Various design parameters (such as number of prefilter taps, number of equalizer states, and decision delay) are optimized using Monte Carlo simulations in a typical urban EDGE environment     

An efficient low complexity cluster-based MLSE equalizer for frequency-selective fading channels

Recently, a novel MLSE equalizer was reported, that does not require the explicit estimation of the channel impulse response. Instead, it utilizes, in an efficient manner, the estimates of the centers of the clusters formed by the received observations. In this paper, a novel cluster tracking scheme is presented, which extends the application of this equalizer in time-varying transmission environments. The proposed algorithm is shown to be equivalent in tracking performance with the classic LMS-based MLSE equalizer, yet much simpler computationally. This is a consequence of the fact that the new method allows for an efficient exploitation of the symmetries underlying the signaling scheme.     

Pulse shaping for wireless communication over time- or frequency-selective channels

This letter investigates the influence of transmit and receive filtering on the design and associated performance of wireless communication systems. Based on derivations using power-series models of time- or frequency-selective channels, we present pulse-shaping filters which can be matched to the characteristics of the channel. The choice of filter parameters allows some degree of control over the received signal. The peak-to-average-power-ratio (PAPR) requirements in the transmitter are determined. Orthogonal frequency-division multiplexing (OFDM) represents an alternative method of achieving some of the stated objectives of the pulse-shaping methods developed. Consideration is given to PAPR, bandwidth efficiency, receiver complexity, and performance in terms of error probability for the derived pulses and related forms of OFDM.     

Adaptive combined DFE/MLSE techniques for ISI channels

By embedding a decision-feedback equalizer (DFE) into the structure of a maximum-likelihood sequence estimator (MLSE), an adaptive combined DFE/MLSE scheme is proposed. In this combined DFE/MLSE, the embedded DFE has three functions: (i) prefiltering the received signals and truncating the equivalent channel response into the desired one, (ii) compensating for channel distortions, and (iii) providing the MLSE detector with predicted values of input signals. Since the embedded MLSE detector operates on the predicted signals the detected symbols at the output of the DFE/MLSE do not suffer any delay and can be directly fed back into the embedded DFE so that the error propagation, which usually takes place in a conventional DFE, can be greatly reduced. Analytical and simulation results indicate that the performance is significantly improved by the DFE/MLSE compared to the conventional DFE while its computation complexity is much less than that of the conventional MLSE receiver. The combined DFE/MLSE can use different adaptive structures (block-updating, sliding window updating or symbol-by-symbol updating) to meet different performance objectives. Moreover, the proposed DFE/MLSE provides a trade-off between performance and complexity with a parameter m representing the MLSE detection depth as well as the number of predicting steps of the embedded DFE. For some particular values of m, this scheme is capable of emulating the conventional DFE, MLSE-VA, adaptive LE-MLSE equalizer, adaptive DDFSE, and adaptive BDFE without detection delay     

Adaptive MLSE equalizers with parametric tracking for multipathfast-fading channels

We use the parametric channel identification algorithm proposed by Chen and Paulraj (see Proc. IEEE Vehicular Technology Conf., p.710-14, 1997) and by Chen, Kim and Liang (see IEEE Trans. Veh. Technol., p.1923-35, 1999) to adaptively track the fast-fading channels for the multichannel maximum likelihood sequence estimation (MLSE) equalizer using multiple antennas. Several commonly-used channel tracking schemes, decision-directed recursive least square (DD/RLS), per-survivor processing recursive least square (PSP/RLS) and other reduced-complexity MLSE algorithms are considered. An analytic lower bound for the multichannel MLSE equalizer with no channel mismatch in the time-varying specular multipath Rayleigh-fading channels is derived. Simulation results that illustrate the performance of the proposed algorithms working with various channel tracking schemes are presented, and then these results are compared with the analytic bit error rate (BER) lower bound and with the conventional MLSE equalizers directly tracking the finite impulse response (FIR) channel tap coefficients. We found that the proposed algorithm always performs better than the conventional adaptive MLSE algorithm, no matter what channel tracking scheme is used. However, which is the best tracking scheme to use depends on the scenario of the system     

Adaptive Bayesian and EM-based detectors for frequency-selective fading channels

The problems of adaptive maximum a posteriori (MAP) symbol detection for uncoded transmission and of adaptive soft-input soft-output (SISO) demodulation for coded transmission of data symbols over time-varying frequency-selective channels are explored within the framework of the expectation-maximization (EM) algorithm. In particular, several recursive forms of the classical Baum-Welch (BW) algorithm and its Bayesian counterpart (often referred to a Bayesian EM algorithm) are derived in an unified way. In contrast to earlier developments of the BW and BEM algorithms, these formulations lead to computationally attractive algorithms which avoid matrix inversions while using sequential processing over the time and trellis branch indices. Moreover, it is shown how these recursive versions of the BW and BEM algorithms can be integrated with the well-known forward-backward processing SISO algorithms resulting in adaptive SISOs with embedded soft decision directed (SDD) channel estimators. An application of the proposed algorithms to iterative "turbo-processing" receivers illustrates how these SDD channel estimators can efficiently exploit the extrinsic information obtained as feedback from the SISO decoder in order to enhance their estimation accuracy.     

Adaptive equalization for frequency-selective channels of unknown length

This paper studies adaptive equalization for time-dispersive communication channels whose impulse responses have unknown lengths. This problem is important, because an adaptive equalizer designed for an incorrect channel length is suboptimal; it often estimates an unnecessarily large number of parameters. Some solutions to this problem exist (e.g., attempting to estimate the "channel length" and then switching between different equalizers); however, these are suboptimal owing to the difficulty of correctly identifying the channel length and the risk associated with an incorrect estimation of this length. Indeed, to determine the channel length is effectively a model order selection problem, for which no optimal solution is known. We propose a novel systematic approach to the problem under study, which circumvents the estimation of the channel length. The key idea is to model the channel impulse response via a mixture Gaussian model, which has one component for each possible channel length. The parameters of the mixture model are estimated from a received pilot sequence. We derive the optimal receiver associated with this mixture model, along with some computationally efficient approximations of it. We also devise a receiver, consisting of a bank of soft-output Viterbi algorithms, which can deliver soft decisions. Via numerical simulations, we show that our new method can outperform conventional adaptive Viterbi equalizers that use a fixed or an estimated channel length.     

Extended MLSE diversity receiver for the time- andfrequency-selective channel

This paper develops a maximum-likelihood sequence estimation (MLSE) diversity receiver for the time- and frequency-selective channel corrupted by additive Gaussian noise when linear constellations (M-ASK, M-PSK, M-QAM) are employed. The paper extends Ungerboeck's derivation of the extended MLSE receiver for the purely frequency-selective channel to the more general channel. Although the new receiver structure and metric assume ideal channel-state information (CSI), the receiver can be used wherever high-quality CSI is available, such as a comb of pilot tones or time-isolated symbols. The major contributions of this paper are as follows: (1) the derivation of a finite-complexity diversity receiver that is maximum likelihood (ML) for all linear channel models and sources of diversity, as long as ideal CSI is available; (2) a benchmark, in that the new receiver's performance is a lower bound on the performance of practical systems, which either lack ideal CSI or are not ML; (3) insight into matched filtering and ML diversity receiver processing for the time- and frequency-selective channels; and (4) bounds on the new receiver's bit-error rate (BER) for ideal CSI and pilot tone CSI, in a fast Rayleigh-fading channel with multiple independently faded paths. The new receiver can seamlessly tolerate square-root Nyquist pulses without a fading-induced ISI error floor     

An adaptive receiver for the time- and frequency-selective fadingchannel

An adaptive receiver is presented in this paper for the reception of linearly modulated signals transmitted over a time- and frequency-selective fading channel. The channel is modeled as a truncated power series which represents the dispersive fading channel as a sum of three elementary flat-fading channels. The proposed receiver consists of a sequence estimator with a parallel channel estimator. The channel estimator recovers the instantaneous fading processes associated with each elementary channel and filters them to generate one-step predictions of each fading process. Some implementation difficulties and solutions are also discussed. Computer simulations using quadrature phase-shift keying (QPSK) and channels with moderate delay spreads and fade rates have been used to evaluate the performance of the receiver. The results show that our technique has potential in channels with delay spread of about 20%, signal-to-noise ratio (SNR) greater than 15 dB, and applications requiring bit-error rates (BER's) less than 10^-2     

Generalized cutoff rate of time- and frequency-selective fadingchannels

The generalized cutoff rate of time- and frequency-selective fading channels is evaluated for M-ary frequency-shift keying (MFSK) and M-ary differential phase-shift keying (MDPSK) modulation with soft decoding. The optimal signaling rate and code rate for dispersive channels are evaluated. The guard time effect, is used in multipath spread channels, is evaluated for frequency-selective channels, and the optimal combination of signaling rate, code rate, and guard time is presented. Special attention is given to CCIR (International Radio Consultative Committee) HF channel models     

Interleaved TC 8DPSK/OFDM with decision-directed channel estimationon frequency-selective Rayleigh fading channels

Trellis-coded modulation (TCM) is a power and bandwidth efficient signaling scheme. In this letter, we propose interleaved trellis-coded (TC) 8DPSK/OFDM combined with decision-directed (DD) channel estimation on frequency-selective Rayleigh fading channels. We use a subchannel block interleaver in an OFDM symbol interval to randomize the burst errors due to the correlated dispersive fading channel. We also use DD channel estimation using the previous detected 8DPSK symbols in the temporal direction to improve the performance at fast fading. Computer simulations show that the proposed technique has good performance at fast fading     

MLSE equalization and decoding for multipath-fading channels

The performance of a receiver using a combined MLSE (maximum likelihood sequence estimation) equalizer/decoder and D-diversity reception is analyzed for multipath Rayleigh fading channels. An upper bound on the (decoded) bit error probability is derived. Comparisons to simulation results show that this upper bound is quite tight when the system has a high signal-to-noise ratio or when diversity reception is used. The upper bound involves an infinite series that must be truncated at a point where the remainder can be safely assumed to be small. An algorithm based on a one-directional stack algorithm is proposed for this calculation because it makes efficient use of computer memory     

Modulation diversity for frequency-selective fading channels

In this article, modulation diversity (MD) for frequency-selective fading channels is proposed. The achievable performance with MD is analyzed and a simple design criterion for MD codes for Rayleigh-fading channels is deduced from an upper bound on the pairwise error probability (PEP) for single-symbol transmission. This design rule is similar to the well-known design rule for MD codes for flat fading and does not depend on the power-delay profile of the fading channel. Several examples for MD codes with prescribed properties are given and compared. Besides the computationally costly optimum receiver, efficient low-complexity linear equalization (LE) and decision-feedback equalization (DFE) schemes for MD codes are also introduced. Simulations for the widely accepted COST fading models show that performance gains of several decibels can be achieved by MD combined with LE or DFE at bit-error rates (BERs) of practical interest. In addition, MD also enables the suppression of cochannel interference.     

Adaptive signal detection over fast frequency-selective fading channels under class-A impulsive noise

The problem of adaptive detection of signals contaminated with Middleton's class-A impulsive noise and transmitted over a fast time-varying frequency-selective fading channel is addressed. Adaptive algorithms are derived to update the estimate of the channel parameters to the detector. A theoretical performance evaluation of the detector is provided. Computer simulations are performed to validate the theoretical developments.     

Universal decoding for frequency-selective fading channels

We address the problem of universal decoding in unknown frequency-selective fading channels, using an orthogonal frequency-division multiplexing (OFDM) signaling scheme. A block-fading model is adopted, where the bands' fading coefficients are unknown yet assumed constant throughout the block. Given a codebook, we seek a decoder independent of the channel parameters whose worst case performance relative to a maximum-likelihood (ML) decoder that knows the channel is optimal. Specifically, the decoder is selected from a family of quadratic decoders, and the optimal decoder is referred to as a quadratic minimax (QMM) decoder for that family. As the QMM decoder is generally difficult to find, a suboptimal QMM decoder is derived instead. Despite its suboptimality, the proposed decoder is shown to outperform the generalized likelihood ratio test (GLRT), which is commonly used when the channel is unknown, while maintaining a comparable complexity. The QMM decoder is also derived for the practical case where the fading coefficients are not entirely independent but rather satisfy some general constraints. Simulations verify the superiority of the proposed QMM decoder over the GLRT and over the practically used training sequence approach.     

Differential space-time coding for frequency-selective channels

We introduce two space-time transmission schemes which allow full-rate and full-diversity noncoherent communications using two transmit antennas over fading frequency-selective channels. The first scheme operates in the frequency domain where it combines differential Alamouti (seeIEEE J. Select. Areas Commun., vol.16, p.1451-58, Nov. 1998) space-time block-coding (STBC) with OFDM. The second scheme operates in the time domain and employs differential time-reversal STBC to guarantee blind channel identifiability without the need for temporal oversampling or multiple receive antennas     

Sphere-constrained ML detection for frequency-selective channels

The maximum-likelihood (ML) sequence detection problem for channels with memory is investigated. The Viterbi algorithm (VA) provides an exact solution. Its computational complexity is linear in the length of the transmitted sequence, but exponential in the channel memory length. On the other hand, the sphere decoding (SD) algorithm also solves the ML detection problem exactly, and has expected complexity which is a low-degree polynomial (often cubic) in the length of the transmitted sequence over a wide range of signal-to-noise ratios. We combine the sphere-constrained search strategy of SD with the dynamic programming principles of the VA. The resulting algorithm has the worst-case complexity determined by the VA, but often significantly lower expected complexity.     

Adaptive channel estimation for multichannel MLSE receivers

The performance of multichannel coherent maximum-likelihood sequence estimation (MLSE) reception in the presence of co-channel interference is limited by the channel estimation accuracy. An adaptive channel estimation approach is developed which improves the performance through interference cancellation. Significant performance gains (up to 8 dB) are demonstrated for the Digital Advanced Mobile Phone Service (D-AMPS) (IS-136) digital cellular system     

On MLSE algorithms for unknown fast time-varying channels

We consider maximum-likelihood sequence estimation (MLSE) algorithms for unknown, time-varying intersymbol interference communication channels. We assume a statistical channel model, and marginalize over model parameters to derive expectation-maximization (EM) algorithms for both time-independent Gaussian and Gauss-Markov models, and we contrast these with direct MLSE and computationally efficient per-survivor processing implementations. We identify a general concern associated with the convergence of EM-based discrete parameter (e.g., symbol) estimators.