Reduced complexity short-block data detection techniques for fadingtime-dispersive channels

The objective is reliable digital communications over fading channels with severe time-dispersion. Three short-block data detection techniques based on linear, nonlinear decision-directed, and maximum likelihood estimation principles are investigated. Short alternating blocks of data and training symbols are used. The training blocks are useful for both channel tracking and data block detection. In contrast to the recursive symbol-to-symbol equalization approaches usually employed, each data block is detected as a unit. Previous restrictions imposed on short-block detection schemes have been removed, resulting in reduced complexity algorithms and higher throughput efficiency. Performance is presented for BPSK and QPSK type signaling using a Rayleigh fading channel model with severe time-dispersion     

Error probability of coherent detection for trellis-coded partialresponse CPM on Rician fading channels

Trellis-coded continuous phase modulation (TC-CPM) schemes are attractive for bandwidth and power limited communication systems such as mobile satellite communications and land mobile radio communications. A coherent receiver for interleaved partial response TC-CPM is derived. A true upper bound on the bit error probability for flat fading channels is derived by showing that TC-CPM is equivalent to a trellis-coded modulation scheme. The upper bound is evaluated by defining an error-state diagram along with a set of characteristic distances and then applying transfer function bounding techniques. Comparison with simulation results shows the upper bound tight to within 1.5-2 dB     

On saving decoder states for some trellis codes and partialresponse channels

It is shown that under certain conditions, when convolutional codes with precoding are used in conjunction with a partial response channel, the number of decoder states in a maximum-likelihood decoder matched to both the code and channel is 1/2 of that predicted by J.K. Wolf and G. Ungerboeck (ibid., vol.COM-34, no.7, p.751-72, 1986)     

Computational complexity of sequential sequence estimation forintersymbol interference channels

The computational complexity of a sequential algorithm (SA) developed for intersymbol interference (ISI) channels is analyzed. To determine the computational complexity, the finite-state machine that models the channel and white matched filter system, of which the SA is a part, is interpreted as a special convolutional encoder followed by a binary symbol to Q-ary symbol mapping. It follows that the computational distribution is Pareto, and that there exists a computational cutoff rate R_comp. For the uncoded data considered, the rate is fixed and the R_comp criterion translates into a signal-to-noise ratio (SNR) criterion. An upper bound on SNR_comp is found analytically by assuming a uniform input distribution. Iteration equations developed by S. Arimoto (1976) are adapted to find the true SNR_comp numerically     

Reduced complexity delay-locked loop

In spread spectrum synchronisation the delay-locked loop (DLL) is widely used for PN-code tracking. A new DLL configuration using only one correlator to generate the timing error signal is presented. This reduces the hardware complexity of the code synchronisation. The structure of the new loop is described and performance results are shown     

Maximum likelihood sequence detection in nonlinear satellite channels

A technical study by computer simulation has been performed to assess the potential of maximum likelihood sequence detection (MLSD) in a band-limited nonlinear satellite channel with two nonlinear elements [a high-power amplifier (HPA) and a transponder traveling wave tube amplifier (TWTA)] operating in tandem. Starting with a brief background on digital modem development, this paper outlines the basic principle of MLSD and a conceptual structure suitable for satellite channel applications. The bit-error rate has been computed for a realistic nonlinear satellite channel using Forney's approach with the Viterbi algorithm. The upper bound of channel performance improvement in a typical satellite link has been identified.     

Noncoherent sequence detection in frequency nonselective slowlyfading channels

A new class of noncoherent sequence detection (NSD) algorithms for combined demodulation and decoding of any coded linear and continuous phase modulations, transmitted over additive white Gaussian noise (AWGN) channels, has been previously presented. In this paper, this class is generalized to the case of frequency nonselective Rayleigh or Rice slowly fading channels, in the presence or absence of channel state information. Coded linear modulations, namely M-ary phase shift keying (M-PSK) and quadrature amplitude modulation (M-QAM), are considered. The proposed detection schemes have a performance which approaches that of coherent detectors, are very robust to phase and frequency instabilities, and compare favorably to other solutions previously proposed in the technical literature     

Reduced complexity Schnorr-Euchner decoding algorithms for MIMO systems

A new reduced-complexity Schnorr-Euchner decoding algorithm is proposed in this letter for uncoded multi-input multi-output systems with q-QAM (q=4,16,...) modulation. Furthermore, a Fano-like metric bias is introduced to the algorithm from the perspective of sequential decoding, as well as an early termination technique. Simulation results show that these modifications reduce the algorithm complexity efficiently, with only a small degradation in bit error rate at high signal to noise ratios.     

Reduced complexity interleaver growth algorithm for turbo codes

This paper is focused on the problem of significantly reducing the complexity of the recursive interleaver growth algorithm (IGA) with the goal of extending the range of applicability of the algorithm to significantly larger interleavers for a given CPU time and processor. In particular, we present two novel modifications to IGA changing the complexity order of the algorithm from O(N/sub max//sup 4/) to O(N/sub max//sup 2/), present several further minor modifications reducing the CPU time albeit not fundamentally changing the complexity order, and present a mixed mode strategy that combines the results of complexity reduction techniques that do not alter the algorithm outcome itself, with a novel transposition value set cardinality constrained design that does modify the optimization results. The mixed strategy can be used to further extend the range of interleaver sizes by changing the complexity order from O(N/sub max//sup 2/) to O(N/sub max/) (i.e., linear in the interleaver size). Finally, we present optimized variable length interleavers for the Universal Mobile Telecommunications System (UMTS) and Consultative Committee for Space Data Systems (CCSDS) standards outperforming the best interleavers proposed in the literature.     

Reduced complexity decision feedback equalization for digitalsubscriber loops

Decision feedback equalizers (DFEs) are widely used in modern local network digital transmission systems to remove the intersymbol interference caused by slowly decaying pulse tails. A gradient descent algorithm for adapting a coefficient to model the slowly decaying portion of the tail is described. An equalization strategy is described that exploits prior knowledge of the nature of the subscriber loop channel, together with the new adaptation algorithm, to give reduced complexity DFE structures. The use of this algorithm in FIR and IIR equalizer structures is described. The use of this algorithm in FIR and IIR equalizers is quantitatively compared to a conventional DFE in terms of performance and implementation complexity. An analysis is presented describing the operation of the adaptation algorithm in the presence of noise. Simulation results illustrate the training of the algorithm and its stability in the presence of near-end crosstalk noise     

Reduced state sequence detection of full response continuous phase modulation

A reduced state sequence detector (RSSD) which combines decision feedback with Viterbi decoding is proposed for M-ary full response continuous phase modulation. The detector is analysed with minimum Euclidean distances and by simulations of the symbol error probability. It is shown that M-ary full response CPM schemes can be optimally decoded by a decoder with only two states when the modulation index is relatively small (>     

Performance analysis of Viterbi detection of class IV partialresponse for data transmission over multipair cables

Partial response class-IV signaling combined with Viterbi decoding to perform maximum-likelihood sequence detection is considered for high-speed data transmission over twisted-pair cables. In order to establish which data rates and distances can be achieved by this method, a performance evaluation is conducted. Binary and quaternary modulations are considered, and disturbance of the received signal by near-end and far-end crosstalk and additive white Gaussian noise is taken into account. A benchmark comparison with rigorously optimized symbol-by-symbol detection systems using AMI and HDB3 line coding is presented     

Low complexity multisymbol differential detection of MDPSK overflat correlated Rayleigh fading channels

Low complexity algorithms for implementing multisymbol differential detection (MSDD) over flat correlated Rayleigh fading channels are proposed, which are extensions of the low complexity MSDD over additive white Gaussian noise channels also proposed by the authors. The complexities of the proposed algorithms increase roughly linearly with block length N while optimum MSDD increases exponentially with N. Simulation results show almost the same performances for practical N     

Per-survivor processing sequence detection for DS/CDMA systems withpilot and traffic channels

A per-survivor processing (PSP) sequence detection receiver is proposed for DS/CDMA systems with pilot and traffic channels. The proposed receiver jointly estimates channel parameters and data symbols from pilot and traffic channels, and is derived by modifying the receiver of Choi (see IEEE Proc. Commun., vol.146, no.5, p.1-7, 1999). As a result, the new receiver can outperform the receiver of Choi in exchange for additional computation. Computer simulation results demonstrate the advantage of the proposed receiver over existing ones     

Reduced complexity closest point decoding algorithms for random lattices

Abstract-Closest point algorithms find wide applications in decoding block transmissions encountered with single- or multiuser communication links relying on a single or multiple antennas. Capitalizing on the random channel and noise models typically encountered in wireless communications, the sphere decoding algorithm (SDA) and related complexity-reducing techniques are approached in this paper from a probabilistic perspective. With both theoretical analysis and simulations, combining SDA with detection ordering is justified. A novel probabilistic search algorithm examining potential candidates in a descending probability order is derived and analyzed. Based on probabilistic search and an error-performance-oriented fast stopping criterion, a computationally efficient layered search is developed. Having comparable decoding complexity to the ing-canceling (NQ algorithm with detection ordering, simulations confirm that the novel layered search achieves considerable error-performance enhancement.     

Reduced complexity two-phase micropipeline latch controller

A latch control circuit for two-phase micropipelines is presented. The circuit avoids the complex toggle element used in previous circuits and is verified using Milner's Calculus of Communicating Systems process algebra. SPICE net-list simulations show the circuit to be faster and to consume less power than previous two-phase alternatives and to compare favorably with four-phase latch controllers     

Multiresolution sequence detection in rapidly fading channels basedon focused wavelet decompositions

The problem of detecting a sequence using the maximum-likelihood strategy, when the time-varying multipath channel is unknown, can be in principle solved using the generalized likelihood detector (GLD). The GLD metric involves finding the orthogonal projection of the received signal onto the subspace of the transmitted signal distorted by the multipath channel: the faded signal corresponding to one of the transmitted sequences is in fact known to lie in a subspace but its exact location is not known, because the channel parameters are unknown. This detector (which in the case of a static channel collapses to the per-survivor processing method), is also called a matched subspace detector because its statistic is “matched” to the a priori known signal subspace. Unfortunately, the computation of the (perfectly matched) orthogonal projection of the received signal onto the multipath faded signal subspace is, in the general time-varying case, impossible. We introduce in this work the idea of using new wavelet-based subspaces that approximate the original signal subspace. The nested sequence of linear vector spaces, defined by a wavelet-based multiresolution decomposition of the fading channel time variations, provides a set of subspaces that, at an increasingly high level of detail, are “efficient” representations of the original signal subspace. For each of these representations sequence detection at different levels of resolution can be performed     

Blind adaptive detection of DS/CDMA signals on time-varyingmultipath channels with antenna arrays using high-order statistics

A new approach based on multiscale decomposition and higher-order statistics is presented for the simultaneous solution of multiuser interference and time-varying multipath propagation in the uplink of a cellular direct-sequence spread-spectrum code-division multiple-access (DS/CDMA) system. Each channel between the mobile transmitter and the base-station receiver is unknown and arbitrarily varying with time. The optimum filter achieving separation and multipath compensation is time-variant. The typical approach in many multiuser detectors previously proposed is to assume that the channel is almost static (time invariant) and attempt detection according to this model. Slow variations of the channels are then compensated using adaptive algorithms that force the estimates (of the channels or of the separating filters) to be constantly in search of a convergence point. If the channel coefficients variations in time are fast with respect to the convergence time of the adaptive algorithm, significant degradation may result. In this work, we depart from this traditional approach and we investigate new kernels that more accurately can characterize the time-varying nature of the detection problem. As a first step, we show that the super-exponential framework can still be applied in a time-variant environment. Then, we describe a multiresolution decomposition of the filter components, essentially constraining its variations in time to remain within the solution subspace. The resulting algorithm overcomes some of the drawbacks associated with slow convergence and insufficient tracking capability typical of many blind approaches and several nonblind methods based on the slow fading assumption     

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.     

Reduced complexity decision feedback equalization for multipathchannels with large delay spreads

Two modified decision feedback equalization (DFE) structures are presented for the efficient equalization of long sparse channels with strong precursor, such as those encountered in high-speed communications over multipath channels with large delay spread. Unlike the conventional DFE, these structures allow the channel's sparseness to be exploited by simple tap allocation, before the sparseness is degraded by feedforward filtering. Both structures yield large reductions in complexity while maintaining performance comparable to the conventional DPE, hence overcoming a key computational bottleneck when equalizers are implemented in hardware for speed. Fast channel estimate-based algorithms for computing the modified DFE coefficients are derived. Simulation results are presented for data rates and channel profiles of the type considered for the proposed North American high definition television (HDTV) terrestrial broadcast mode