Noncoherent sequence detection of continuous phase modulations

In this paper, noncoherent sequence detection, proposed in a companion paper by Colavolpe and Raheli (see ibid. vol.47, no.9, p.1376-85, 1999), is extended to the case of continuous phase modulations (CPMs). The results in the companion paper on linear modulations with intersymbol interference (ISI) are used here because a CPM signal is mathematically equivalent to a sum of ISI-affected linearly modulated components, according to the Laurent decomposition. The proposed suboptimal detection schemes have a performance which approaches that of coherent detection with acceptable complexity, allow for time-varying phase models, and compare favorably with previously proposed solutions     

On noncoherent sequence detection of coded QAM

New noncoherent sequence detection algorithms for combined demodulation and decoding of coded linear modulations transmitted over additive white Gaussian noise channels are presented. These schemes may be based on the Viterbi algorithm and have a performance which approaches that of coherent detection for increasing complexity. The tradeoff between complexity and performance is simply controlled by a parameter referred to as implicit phase memory and the number of trellis states     

Design and performance of turbo Gallager codes

The most powerful channel-coding schemes, namely, those based on turbo codes and low-density parity-check (LDPC) Gallager codes, have in common the principle of iterative decoding. However, the relative coding structures and decoding algorithms are substantially different. This paper shows that recently proposed novel coding structures bridge the gap between these two schemes. In fact, with properly chosen component convolutional codes, a turbo code can be successfully decoded by means of the decoding algorithm used for LDPC codes, i.e., the belief-propagation algorithm working on the code Tanner graph. These new turbo codes are here nicknamed "turbo Gallager codes." Besides being interesting from a conceptual viewpoint, these schemes are important on the practical side because they can be decoded in a fully parallel manner. In addition to the encoding complexity advantage of turbo codes, the low decoding complexity allows the design of very efficient channel-coding schemes.     

Improved differential detection of chip-level differentiallyencoded direct-sequence spread-spectrum signals

In a paper by Cavallini et al. (see IEEE Trans. Commun., vol. 45, p.456-63, Apr. 1997), chip-level differential encoding/detection for direct-sequence spread-spectrum signals was proposed to cope with frequency-nonselective fast fading channels. It was shown that, unlike in the additive white Gaussian noise channel, in time-varying fading channels the system performance may be considerably improved, especially when the spreading factor is increased. In this paper, noncoherent sequence detection, recently proposed by the authors, is the starting point for the derivation of receivers with improved performance with respect to that of standard differential detection. For M-ary phase-shift keying signals, a theoretical analysis is performed and the results are confirmed by means of computer simulation. The performance advantage of taking into account a larger phase memory, with respect to the minimum accounted for by differential detection, is demonstrated. In particular, the amount of phase memory is optimized as a function of the Doppler spread for a Rayleigh frequency-nonselective fading channel. The robustness in the presence of phase noise is also investigated by means of computer simulation     

Soft-Output Decoding of Rotationally Invariant Codes Over Channels With Phase Noise

We consider rotationally invariant (RI) trellis-coded modulations (TCMs) transmitted over channels affected by phase noise. To describe the main ideas of this paper, we first concentrate, as a case study, on the simplest RI scheme, namely the differentially encoded M-ary phase-shift keying (M-PSK) signal. For this problem, we use the framework based on factor graphs (FGs) and the sum-product algorithm (SPA), to derive the exact maximum a posteriori (MAP) symbol detection algorithm. By analyzing its properties, we demonstrate that it can be implemented by a forward-backward estimator of the phase probability density function, followed by a symbol-by-symbol completion to produce the a posteriori probabilities of the information symbols. To practically implement the forward-backward phase estimator, we propose a couple of schemes with different complexity. The resulting algorithms exhibit an excellent performance and, in one case, only a limited complexity increases with respect to the algorithm that perfectly knows the channel phase. The properties of the optimal decoder and the proposed practical decoding schemes are then extended to the case of a generic RI code. The proposed soft-output algorithms can also be used in iterative decoding schemes for concatenated codes employing RI inner components. Among them, in the numerical results, we consider repeat-accumulate (RA) codes and other serially concatenated schemes recently proposed in the technical literature.     

Reduced-Complexity BCJR Algorithm for Turbo Equalization

We propose novel techniques to reduce the complexity of the well-known Bahl, Cocke, Jelinek, and Raviv (BCJR) algorithm when it is employed as a detection algorithm in turbo equalization schemes. In particular, by also considering an alternative formulation of the BCJR algorithm, which is more suitable than the original one for deriving reduced-complexity techniques, we describe three reduced-complexity algorithms, each of them particularly effective over one of the three different classes of channels affected by intersymbol interference (minimum-phase, maximum-phase, and mixed-phase channels). The proposed algorithms do not explore all paths on the trellis describing the channel memory, but they work only on the most promising ones, chosen according to the maximum a posteriori criterion. Moreover, some optimization techniques improving the effectiveness of the proposed solutions are described. Finally, we report the results of computer simulations showing the impressive performance of the proposed algorithms, and we compare them with other solutions in the literature.     

A Robust Metric for Soft-Output Detection in the Presence of Class-A Noise

Digital communications over channels impaired by impulse noise are considered. We first address the problem from an information-theoretical viewpoint, discussing the performance limits imposed by the channel model. Then, we describe and compare a couple of practical communication schemes employing powerful channel codes and iterative decoding, with focus on a very simple and robust detection scheme that does not require the estimation of the statistics of the impulse noise.     

On the application of factor graphs and the sum-product algorithm to ISI channels

In this paper, based on the application of the sum-product (SP) algorithm to factor graphs (FGs) representing the joint a posteriori probability (APP) of the transmitted symbols, we propose new iterative soft-input soft-output (SISO) detection schemes for intersymbol interference (ISI) channels. We have verified by computer simulations that the SP algorithm converges to a good approximation of the exact marginal APPs of the transmitted symbols if the FG has girth at least 6. For ISI channels whose corresponding FG has girth 4, the application of a stretching technique allows us to obtain an equivalent girth-6 graph. For sparse ISI channels, the proposed algorithms have advantages in terms of complexity over optimal detection schemes based on the Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm. They also allow a parallel implementation of the receiver and the possibility of a more efficient complexity reduction. The application to joint detection and decoding of low-density parity-check (LDPC) codes is also considered and results are shown for some partial-response magnetic channels. Also in these cases, we show that the proposed algorithms have a limited performance loss with respect to that can be obtained when the optimal "serial" BCJR algorithm is used for detection. Therefore, for their parallel implementation, they represent a favorable alternative to the modified "parallel" BCJR algorithm proposed in the literature for the application to magnetic 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.     

Adaptive iterative detection for the phase-uncertain channel: limited-tree-search versus truncated-memory detection

In this paper, we consider iterative detection over bandpass channels that introduce an unknown phase rotation in the transmitted signal. This work focuses on the comparison between two adaptive detection strategies for trellis-based coded modulation: limited-tree-search (LTS) detection, obtained by reducing a tree search to a limited trellis search, and truncated-memory (TM) detection, based on channel-memory truncation, which automatically leads to a trellis search. Both strategies are used to derive trellis-based forward-backward (FB) algorithms. A quantitative analysis based on simulations, with various coding and modulation schemes, is carried out to evaluate and compare the two approaches. The results show that the channel-phase dynamics should significantly influence the choice of the detection strategy: For low-phase variations, LTS algorithms are a simple and reasonable choice, while for moderate to fast phase variations, TM algorithms show a considerable robustness.