Per-survivor Processing Research Articles

Super-orthogonal differential space-time trellis coding and decoding

In this paper, a differential space-time trellis-coded scheme based on super-orthogonal space-time trellis codes (SOSTTCs) is proposed. It achieves full diversity and provides an improved coding gain. Based on the per-survivor processing (PSP) technique, a low-complexity suboptimal differential decoder is developed. In slow fading channels, it can approach the performance of SOSTTC with coherent decoding. Furthermore, in time-varying channels, a bank of recursive least square (RLS) type channel predictors are incorporated into the Viterbi decoder to track the channel variance and the RLS predictors do not need training data and channel statistics. The performance analysis is given. Simulation results are presented to illustrate our analytical results and they show that our scheme can achieve a good performance in both slow fading and time-varying fading channels with modest complexity.

A Multiple-Symbol Differential Detection Based on Channel Prediction for Fast Time-Varying Fading

This paper discusses a generalized concept of multiple-symbol differential detection (MDD) and analytically derives weight parameters based on channel prediction for MDD on fast time-varying channels. At first, this paper shows that adaptive maximum-likelihood sequence estimation employing per-survivor processing (PSP-MLSE) with a single channel tap is similar concept to MDD. Next, the weight parameters for MDD are derived according to the channel estimation of PSP-MLSE based on a high order channel prediction. Finally, computer simulation confirms that MDD with the analytically derived parameters mitigates floor of bit error rate (BER) on fast time-varying fading channels without channel state information.

Convergence behavior of iterative phase synchronization and detection

Serially concatenated systems with rotational invariance (RI-SCS) can tolerate certain phase ambiguities and, therefore, for these systems coherent detection is robust even when cycle slipping, false-lock and hangup exist during phase synchronization. However, the convergence behavior of iterative phase synchronization and detection is still not well-understood. In this paper, we present a simplified phase model to analyze the convergence of iterative receivers with/without occurrence of phase rotations. Particularly, an oscillatory convergence behavior due to cycle slipping is explained by means of density evolution. Moreover, based on per-survivor processing (PSP) and single-estimator processing (SEP) techniques, a family of adaptive soft-input soft-output algorithms are employed to implement joint phase tracking and demodulation in the context of maximum a posteriori symbol detection. Both analytical and simulation results show that for RI-SCS the convergence performance of the SEP method is more robust than that of the PSP method when carrier phase has high and random dynamics.

A novel RSSE-PSP equalizer with an adaptive pre-filter

A reduced-state sequence estimation (RSSE) receiver based on per-survivor processing (PSP) in conjunction with an adaptive pre-filter is proposed in this paper. In RSSEPSP, each survivor path holds an estimated value of the channel impulse response (CIR), which is updated by adaptive algorithm during the data transmission. Based on the different estimated channel values of each survivor path, corresponding pre-filters are calculated via the Levinson-Durbin algorithm, which can track the time-varying channel adaptively. Computer simulations indicate that the RSSE-PSP equalizer with the new adaptive pre-filter works much better than those with the prevenient pre-filters in ISI channel.

MMSE precoder design for diversity systems with temporal correlation

Abstract This paper describes a numerical procedure for the design of precoders for diversity systems, where temporal correlation in the channel is present, and can be well modelled by a multichannel autoregressive process. The proposed procedure yields the class of diversity codes which minimise the greatest lower bound on the achievable channel estimation error (in the mean square sense) for any receiver. The paper describes the use matrix differential calculus to derive the Jacobian (first derivative) of the trace of the optimal (MMSE) estimation error covariance matrix with respect to the channel precoder matrix. This is used to define a gradient descent algorithm to minimise this error over all unit norm precoders. Simulation results using a previously derived per-survivor processing (PSP) based receiver illustrate the improvement gained over unitary codes. The paper shows by example that the PSP receiver attains the designed lower bound even at relatively high symbol error rates, although this design does not necessarily lead on its own to optimal symbol detection error probability performance.

PSAIC decoder for space–time trellis-coded DS-CDMA system

A per-survivor adaptive interference cancellation (PSAIC) decoder is proposed for group decoding of a space–time trellis-coded DS-CDMA system. To mitigate error propagation by tentative decisions, per-survivor processing is introduced to a group decoder with adaptive interference cancellation. It is shown that the proposed decoder outperforms conventional decoders without much increase of decoding delay and complexity.

A semi-blind joint data and channel estimation based receiver for meteor burst communication

According to the analysis of meteor burst communication (MBC) mechanism, a model of signal processing based on the structure of data frame is suggested for adaptive modulation and coding (AMC) of MBC system in this paper. There are two distinct modes of operation for signal processing: acquisition and tracking. The acquisition mode is a training period to initialize the channel estimation by frame header. The tracking mode is jointly to equalize payload data and to trace channel, where the principle of per-survivor processing (PSP) for maximum likelihood sequence detection (MLSD) is performed. A suboptimal method called D-PSP is adopted to save the computational time and memory size, which agrees with the slow-fading characteristic of meteor channel and makes the MLSD possible for adaptive modulation and coding of MBC system. Computer simulation results are included to support our development.

Detection of signals in correlated interference using a predictive VA

In this paper, we address the problem of optimally detecting signals in correlated noise using a predictive Viterbi algorithm (PVA). We derive expressions for the probability of error for both coded and uncoded systems employing the PVA, which are corrupted by coloured noise. As an application, the PVA is used in conjunction with a fractionally spaced linear equalizer (LE-PVA), thereby improving the bit-error-rate performance by as much as 11 dB, over the conventional decision feedback equalizer with estimated decisions, when the channel has spectral nulls. The LE-PVA is also about 1 dB better than the DFE that uses per-survivor processing. Simulation results also show that the performance difference between the LE-PVA and the decision feedback equalizer with correct decisions fed back (ideal DFE), is just 1 dB, even when the channel has spectral nulls. Simulation results are also presented for multipath fading channels, where we again demonstrate that the LE-PVA is just 1 dB inferior to the ideal DFE and about 1 dB better than the DFE using per-survivor processing. Thus, we clearly demonstrate the superiority of the LE-PVA over a practical DFE.

Joint Space-Time Trellis Decoding and Channel Estimation in Correlated Fading Channels

This letter addresses the issue of joint space-time trellis decoding and channel estimation in time-varying fading channels that are spatially and temporally correlated. A recursive space-time receiver which incorporates per-survivor processing (PSP) and Kalman filtering into the Viterbi algorithm is proposed. This approach generalizes existing work to the correlated fading channel case. The channel time-evolution is modeled by a multichannel autoregressive process, and a bank of Kalman filters is used to track the channel variations. Computer simulation results show that a performance close to the maximum likelihood receiver with perfect channel state information (CSI) can be obtained. The effects of the spatial correlation on the performance of a receiver that assumes independent fading channels are examined.

Joint channel estimation and data detection under fading on reconfigurable fabric

Advanced equalization techniques are required for data transmission over fading channels in a mobile communication system. Joint data and channel estimation can be realized by employing a Viterbi detector along with channel estimators, which estimate the channel impulse response estimation over frequency selective Rayleigh fading channels. Maximum likelihood sequence detection is implemented using per-survivor processing method. Square-root solutions are proposed to combat the problems of numerical errors and round-off noise. Parallel and highly pipelined architectures are proposed for recursive least squares algorithm that acts as channel estimator and an overall architecture is proposed to implement the joint channel estimation and data detection on FPGA.

Beat interference suppression techniques by means of transmission diversity and adaptive equalization

AbstractIn this paper, we discuss techniques for transmitting signals over the same frequency by synchronizing multiple base stations in order to achieve both high communication quality and excellent spectral efficiency in broadcast (P‐MP: Point to Multipoint) communication (single‐frequency, multistation simultaneous transmission). Specifically, in this paper, we propose a communication technique that uses the concept of transmission diversity and converts beat interference to intersymbol interference to suppress beat interference, which becomes a problem in single‐frequency, multistation simultaneous transmission. The proposed technique features (1) controlling the transmit timing or waveform of the signal transmitted from each base station, and (2) using an adaptive equalizer to compensate for intersymbol interference produced during transmission. Finally, we assume a high‐speed Rayleigh fading environment in addition to a beat interference environment in computer simulations and demonstrate the effectiveness of the proposed technique when maximum likelihood sequence estimation based on per‐survivor processing is adopted. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 87(6): 12–21, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.10167

Free-Space Heterochronous Imaging Reception of Multiple Optical Signals

We consider free-space optical communication between a distributed collection of nodes (e.g., a distributed network of sensor nodes) and a central base station with an imaging receiver. This paper studies both synchronous and asynchronous reception of the optical signals from the nodes at the imaging receiver. Synchronous reception is done using a symbol-by-symbol maximal-ratio combining technique. We describe a low-complexity asynchronous reception scheme for the uplink that allows the nodes to transmit at a bit rate slightly lower than the frame rate. Since the two rates are nominally different, the scheme is said to be heterochronous. Our heterochronous detection algorithm uses joint maximum-likelihood sequence detection of multiple trellises, which can be implemented using the Viterbi algorithm, as well as the per-survivor processing technique. We develop an approximate upper bound for the average bit-error probability and compare it to Monte Carlo simulation results.

Further results on differential space-time modulations

Some novel results on the space-time differential modulation schemes described by B.M. Hochwald and W. Sweldens (see ibid., vol.48, p.2041-52, 2000) and V. Tarokh and H. Jafarkhani (IEEE J. Select. Areas Commun., vol.18, p.1169-74, 2000), are derived under the assumption of a quasi-static multiple-antenna channel. First, the optimality (in the maximum-likelihood sense) of the one-shot detection algorithms of Hochwald and Sweldens and of Tarokh and Jafarkhani is proved. Then, the expression of the pairwise error probability for these detectors is derived, and, as a particular case, the bit-error rate is computed for the binary phase-shift keyed scheme of Tarokh and Jafarkhani. Finally, a per-survivor processing (PSP) detection algorithm for this class of modulations is illustrated. Numerical results evidence both the superiority of the PSP strategy over the one-shot space-time differential detectors and the accuracy of the above-mentioned bit-error rate formula.

Per-survivor processing-based decoding for space-time trellis code

The problem of adaptive decoding of space-time trellis codes on time-variant wireless channels is considered. We show that per-survivor processing (PSP) can be adopted to obtain approximated adaptive maximum-likelihood sequence detection (MLSD) of space-time trellis codes when there is no periodically inserted orthogonal pilot sequence. Then we propose a self-tuning least mean square (LMS)-based PSP decoder and a second-order LMS-based one. The former has the advantage that there are only fading rate-independent parameters to be predetermined, while the latter can offer fairly good performance on moderately fast time-varying channels.

On low-complexity space-time coding for quasi-static channels

We propose a new space-time coding scheme for the quasi-static multiple-antenna channel with perfect channel state information at the receiver and no channel state information at the transmitter. In our scheme, codewords produced by a trellis encoder are formatted into space-time codeword arrays such that decoding can be implemented efficiently by minimum mean-square error (MMSE) decision-feedback interference mitigation coupled with Viterbi decoding, through the use of per-survivor processing. We discuss the code design for the new scheme, and show that finding codes with optimal diversity is much easier than for conventional trellis space-time codes (STCs). We provide an upper bound on the word-error rate (WER) of our scheme which is both accurate and easy to evaluate. Then, we find upper and lower bounds on the information outage probability with discrete independent and identically distributed (i.i.d). inputs (as opposed to Gaussian inputs, as in most previous works) and we show that the MMSE front-end yields a large advantage over the whitened matched filter (i.e., zero-forcing) front-end. Finally, we provide a comprehensive performance/complexity comparison of our scheme with coded vertical Bell Labs layered space-time (V-BLAST) architecture and with the recently proposed threaded space-time codes. We also discuss the concatenation of our scheme with block space-time precoders, such as the linear dispersion codes.

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.

Markov chain model in maximum-likelihood sequence detection for free-space optical communication through atmospheric turbulence channels

In free-space optical communication links using intensity modulation and direct detection (IM/DD), atmospheric turbulence-induced intensity fluctuations can significantly impair link performance. Communication techniques can be applied to mitigate turbulence-induced intensity fluctuations (i.e., signal fading) in the regime in which the receiver aperture D/sub 0/ is smaller than the fading correlation length d/sub 0/ and the observation interval T/sub 0/ is smaller than the fading correlation time /spl tau//sub 0/. If the receiver has knowledge of the joint temporal statistics of the fading, maximum-likelihood sequence detection (MLSD) can be employed, but at the cost of high computational complexity. We introduce a single-step Markov chain (SMC) model for the fading correlation and use it to derive two low-complexity, suboptimal MLSD algorithms based on per-survivor processing (PSP). Simulations are presented to verify the SMC model and the performance improvement achieved using these suboptimal per-survivor processing (PSP) algorithms.

Sequence error probability lower bounds for joint detection and estimation

A commonly used lower bound on the probability of error of joint detection and estimation (JDE) algorithms is derived under the assumption that estimation is performed using the transmitted sequence, in a genie-aided fashion. Although it seems reasonable that this genie-aided receiver performs better than the original receiver, a proof of this fact is not available in the literature. In this letter, the validity of this bound is established for a general class of JDE algorithms, as well as for an important special case when the maximum-likelihood sequence detection criterion is used. The results are then extended to a well-known suboptimal JDE algorithm, namely, the T-algorithm. It is shown, however, that the technique used to prove this bound is not sufficient for establishing the validity of the bound for the M-algorithm and the per-survivor processing algorithm.

Second-Order LMS Based Per-Survivor Processing Decoder for Space-Time Trellis Code

An adaptive space-time trellis code (STTC) decoder with the second-order LMS (SOLMS) based channel tracking is studied in this paper. We first show that per-survivor processing (PSP) can be adopted as the approximation of the adaptive maximum likelihood sequence detection (MLSD) of STTC when there are no periodically inserted orthogonal pilot sequences (PIOPS). With this presupposition, we propose a new decoder for STTC, called SOLMS based PSP decoder, in which we use min-max optimum SOLMS algorithm for channel tracking when some ``boundary'' statistical knowledge of the fading channel is available. Intensive computer simulations have been done to compare the performance of the proposed decoder with other known decoding methods as applied to long burst transmissions.

Iterative reduced-state multiuser detection for asynchronous coded CDMA

The conventional maximum a posteriori receiver for coded code-division multiple-access (CDMA) systems has exponential computational complexity in terms of the number of users and the memory of the channel code. In this letter, we propose a low-complexity soft-input soft-output (SISO) multiuser detector based on the reduced-state a posteriori probability algorithm. Per-survivor processing and soft interference cancellation are used to remove the residual past and future interference in the branch metric computation. The complexity of the proposed receiver is related to the reduced memory of the CDMA channel and can be adjusted according to the complexity/performance tradeoff. Simulation results show that for asynchronous convolutionally coded systems, the proposed receiver can achieve the near-single-user performance for moderate to high signal-to-noise ratios.