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Digital receivers based on 1-bit quantization and oversampling w.r.t. the transmit signal bandwidth promise lower energy consumption. However, since 1-bit quantization is a highly non-linear operation, standard receiver algorithms cannot be applied. Thus, we derive performance bounds for phase, timing, and frequency estimation in order to gain a deeper insight into the impact of 1-bit quantization and oversampling. We identify uniform phase and sample dithering as crucial to combat the effect of the non-linearity introduced by 1-bit quantization. Since oversampling results in noise correlation, a closed form of the likelihood function is not available. Thus, we study a system model with white noise by adapting the receive filter bandwidth to the sampling rate. Considering the aforementioned dithering, we obtain very tight closed form lower bounds on the Cramer–Rao lower bound (CRLB) in the large sample regime. We show that with uniform phase and sample dithering, all large sample properties of the CRLB of the unquantized receiver are preserved under 1-bit quantization, except for an signal-to-noise ratio (SNR) dependent performance loss that can be decreased by oversampling. Numerical computations show that the properties of the CRLB for white noise still hold for colored noise except that the performance loss due to 1-bit quantization is reduced.

A new multicarrier $M$ -ary orthogonal chaotic vector shift keying with index modulation (MC-MOCVSK-IM) is presented in this paper. In this design, information bits are conveyed not only by the multiple groups of $M$ -ary information bearing signals, but also by the specific indices of the selected reference signals which depend on the incoming mapped bits. Benefiting from the favorable features of multicarrier modulation, $M$ -ary modulation and index modulation, MC-MOCVSK-IM system is capable to offer higher energy efficiency and spectral efficiency at some expense of hardware complexity. In addition, the analytical bit error rate (BER) expressions of MC-MOCVSK-IM system are derived over additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels. The BER performance comparison between MC-MOCVSK-IM system and other non-coherent chaotic communication systems is carried out to highlight the superiority of MC-MOCVSK-IM system in terms of BER performance. Considering the dramatically increased demand for high-data-rate transmission and the harsh environment of future wireless communication, MC-MOCVSK-IM system shows strong robustness and offers competitive solutions for high-data-rate non-coherent chaotic communication systems.

In this paper, we consider a single-input multiple-output (SIMO) system, in which a single-antenna transmitter communicates with a receiver having multiple antennas. It is assumed that the channel coefficients keep constant during two consecutive time slots, after which they become new independent values. For such a system, we focus on the concept of uniquely factorable constellations (UFCs) in the design of noncoherent coding schemes under two communication scenarios. The first scenario is the massive SIMO system, in which only the first and second order channel statistical information is available. The second is the traditional Rayleigh fading SIMO system. First, parameterized massive UFC (MUFC) and unitary UFC (UUFC) are designed for each scenario. It is proved that these designs ensure the unique identification of the transmitted signals when there is no additive Gaussian white noise. Second, using the Riemannian distance (RD) metric for the RD-based detector and coding gain criterion for generalized likelihood ratio test receiver, the optimal MUFCs and UUFCs of various sizes are constructed, respectively. Finally, we exploit the structures of our proposed designs to reduce the decoding complexities compared to the exhaustive search methods. Comprehensive computer simulations show that our proposed schemes outperform the current designs in literature.

The majority of modern communication systems adopts quadrature amplitude modulation (QAM) constellations as transmission schemes. Due to their square structure, however, QAM do not provide satisfying protection to phase noise effects as the number of constellation points grows, increasing at the same time their peak to average power ratio (PAPR). This requires an expensive power amplifier and oscillator at the transmitter to guarantee low distortion, complicating the adoption of dense transmission schemes in practical high-data rate systems. In this paper, we construct a coded modulation scheme based on regular amplitude and phase shift keying (RAPSK) modulations. We propose a novel multilevel coding (MLC) labeling for the constellation points separating amplitude and phase domains. We provide a novel multistage decoding (MSD) scheme allowing for a low-complexity log-likelihood ratio (LLR) calculation for soft-input decoding of component codes, along with a suitable rate design. Finally, we compare the proposed scheme with state-of-the-art QAM constellations and optimized constellations in the presence of phase noise.

We study the problem of frame synchronization over a discrete memoryless channel (DMC) in an asynchronous setup. A sync frame is transmitted at a random time $V$ with a known distribution $\{a_{v} \}$ and entropy $H$ . We seek to characterize the minimum average length or energy of the sync frame necessary for error-free frame synchronization, as $H$ tends to infinity. We present a variable length sync frame, where the length of the sync frame is adapted based on $H$ and $\{a_{v} \}$ , for the general arrival distribution and show error-free frame synchronization when the average sync frame length $\bar {N}$ scales as $\Omega (({H}/{\alpha (Q)})$ , where $\alpha (Q)$ is the synchronization threshold of the DMC. We then generalize the framework and study a tradeoff between $\bar {N}$ and $\alpha (Q)$ for optimal frame synchronization and characterize the scaling needed of both $\bar {N}$ and $\alpha (Q)$ with $H$ . We illustrate our results with the AWGN channel and discuss the adapting sync frame length and symbol power for optimal frame synchronization. Finally, using numerical work and simulations, we evaluate the results under relaxed assumptions, including the imperfect knowledge of arrival distribution and symbol timing error.

We develop several lower bounds on the capacity of binary input symmetric output channels with synchronization errors which also suffer from other types of impairments such as substitutions, erasures, additive white Gaussian noise (AWGN) etc. More precisely, we show that if the channel with synchronization errors can be decomposed into a cascade of two channels where only the first one suffers from synchronization errors and the second one is a memoryless channel, a lower bound on the capacity of the original channel in terms of the capacity of the synchronization error-only channel can be derived. To accomplish this, we derive lower bounds on the mutual information rate between the transmitted and received sequences (for the original channel) for an arbitrary input distribution, and then relate this result to the channel capacity. The results apply without the knowledge of the exact capacity achieving input distributions. A primary application of our results is that we can employ any lower bound derived on the capacity of the first channel (synchronization error channel in the decomposition) to find lower bounds on the capacity of the (original) noisy channel with synchronization errors. We apply the general ideas to several specific classes of channels such as synchronization error channels with erasures and substitutions, with symmetric q-ary outputs and with AWGN explicitly, and obtain easy-to-compute bounds. We illustrate that, with our approach, it is possible to derive tighter capacity lower bounds compared to the currently available bounds in the literature for certain classes of channels, e.g., deletion/substitution channels and deletion/AWGN channels (for certain signal to noise ratio (SNR) ranges)., Comment: Submitted to the IEEE Transactions on Information Theory

In this paper, a new algorithm is proposed for the classification of digital amplitude-phase modulated signals in flat fading channels with time-correlated non-Gaussian noise. The first-order statistics of the additive noise is modeled by a Gaussian mixture distribution and an autoregressive (AR) process is used to model the time-correlation. The proposed classifier involves the use of a whitening filter, necessary to reduce the complexity of the classification process, and maximum-likelihood classification. For the estimation of the whitening filter coefficients, a new blind technique that is based on the use of a robust H∞ filter is developed. After whitening the received signal, following a composite hypothesis testing approach, the unknown fading and noise distribution parameters are estimated. Results are presented which show that when the noise process is time-correlated non-Gaussian, the proposed classifier outperforms maximum-likelihood classifiers developed under the assumption that the noise process is either white non-Gaussian or white Gaussian. It is also shown that when the noise process is white Gaussian, the proposed classifier's performance closely approaches that of the maximum-likelihood classifier developed for white Gaussian noise channels.

Investigation into the characteristics and behaviours of Laplace noise is of crucial importance for evaluating the performance of communication systems operating in impulsive noise, as well as for ultra-wideband wireless systems operating in the presence of multi-user interference. The bit error rate performances of a binary data communication system operating in the presence of additive bandlimited white Laplace noise is analyzed theoretically. A theoretical expression for the average bit error rate is derived using the Beaulieu series for the optimal soft-limiting detector and the matched-filter detector when arbitrary pulse shapes are used. The bit error rate performance of a reduced complexity version of the optimal detector, the hard-limiting detector, and a reduced complexity version of the matched-filter detector, the sum-of-samples detector, are also analyzed. The analytical expressions for the bit error rate are validated by numerical examples.

This paper studies the effect of non-ideal estimation of channel state information (CSI) on the performance of output-threshold maximal-ratio combining (OT-MRC) diversity scheme in the presence of co-channel interference as well as white noise. The channel fading envelopes are assumed to follow slowly varying flat Rayleigh model. New closed-form expressions for the combined signal-to-interference-plus-noise ratio (SINR) distribution and outage probability performance are presented. Performance comparisons between the conventional MRC and OT-MRC for the system model described above are provided.

We consider two nodes equipped with multiple antennas that intend to communicate i.e. both of which transmit and receive data. We model the responses of the communication channels between these nodes as linear and reciprocal (time invariant or with very slow time variations). In practice, we exploit the closed loop conversation between these nodes and present an efficient algorithm allowing to adaptively identify the Best Singular Mode (BSM) of the channel. We consider two scenarios. In the first scenario, the initial communication link is established over the BSM assuming that the exchanged data is partially known at both nodes. This scenario is suitable for channel training. In the second scenario, the BSM is adaptively updated while the real unknown data is exchanged between the nodes i.e. no capacity is wasted for channel identification. The proposed adaptive algorithm is robust to noise as the involved step-size allows a trade-off to reduce the impact of the additive noise at the expense of some estimation delay. Our computer simulations show that the proposed algorithm works efficiently in both modes of operations (training mode and simultaneous training/data transmission mode) for both static and slow fading MIMO channels and for both white and colored noises.

Fiber-wireless (Fi-Wi) access fronts can support 100s of Mb/s envisioned by 4G networks. However, a major issue associated with Fi-Wi links is the nonlinear distortion of the radio-over-fiber (ROF) link coupled with the multipath dispersion of the wireless channel. Estimation and subsequent equalization of the concatenated fiber-wireless channel needs to be done, especially at high bit rates. The uplink is severely affected due to large fluctuations in the radio signal. This paper proposes an estimation and subsequent equalization algorithm for the Fi-Wi CDMA uplink. The estimation employs the properties of pseudo noise (PN) sequences and the equalization uses a novel Hammerstein type decision feedback equalizer (HDFE). The estimation and equalization are performed in the presence of multiple access interference (MAI) and wireless and optical channel noise. The cumulative effects of multiuser interference, multipath dispersion, nonlinear distortion, and noise are all considered in our analysis. Correlation properties of white-noise like PN sequences enable decoupling of the linear (wireless) and nonlinear (optical) channel portions. Furthermore, we propose a unique algorithm to mitigate MAI. Numerical evaluations show a good estimation and equalization of both the linear and nonlinear channels. Bit error rate (BER) simulations show that this algorithm leaves only small residual MAI.

In this letter, we propose multi-antenna based spectrum sensing methods for cognitive radios (CRs) using the generalized likelihood ratio test (GLRT) paradigm. The proposed methods utilize the eigenvalues of the sample covariance matrix of the received signal vector from multiple antennas, taking advantage of the fact that in practice, the primary user signals to be detected will either occupy a subspace of dimension strictly smaller than the dimension of the observation space, or have a non-white spatial spectrum. These methods do not require prior knowledge of the primary user signals, or the channels from the primary users to the CR. By making different assumptions on the availability of the white noise power value at the CR receiver, we derive two algorithms that are shown to outperform the standard energy detector.

A numerical approach to the vector signal detection problem is proposed by using an approximate series representation for vector complex-valued random processes. This technique allows us to provide computationally feasible suboptimum receivers for the problem of detecting an improper or proper complex signal in additive white noise. Its implementation requires the knowledge of the correlation matrix of the vector process involved. The performance of the technique devised is assessed by some communication examples.

An efficient way to reduce the peak-to-average power ratio (PAPR) in OFDM systems is clipping. After the clipping in an MIMO-OFDM system, the additive noise may not be white. In this paper, we develop fast (single-symbol) ML decoding algorithms for orthogonal space-time block codes (OSTBC) and (linearly transformed) quasi orthogonal space- time block codes (QOSTBC) in clipped MIMO-OFDM systems by using a clipping noise model with Gaussian approximation. By using the statistics of the clipping distortions, our newly developed fast ML decoding algorithms improve the performance for clipped MIMO-OFDM systems with OSTBC and QOSTBC while the decoding complexities are not increased. Simulation results are presented to illustrate the improvement.

In this paper, we present quasi-chaotic (QC) schemes for secure digital communication systems, designed over Galois fields (GFs) with optimal randomness properties. Schemes with the maximum-output sequence length (all-zero input response) are presented for different GFs. Two coefficients are used to quantitatively measure the proximity of the behavior of these schemes with respect to the ideal white noise behavior. The proposed schemes outperform those presented by Frey in his paper, and achieve the optimal QC properties available for a given chaotic digital scheme. The proposed schemes have also a very little loss in bit-error rate performance so that they are a good alternative to the design of systems for which encryption and error correction are important joint goals. They can be implemented with time-variant coefficients in order to highly improve the cryptographic properties of the transmission.

A family of upper bounds to error probabilities of coded systems was recently proposed by D. Divsalar (see IEEE Communication Theory Workshop, 1999; JPL TMO Prog. Rep. 42-139, 1999). These bounds are valid for transmission over the additive white Gaussian noise channel, and require only the knowledge of the weight spectrum of the code words. After illustrating these bounds, we extend them to fading channels. Contrary to the union bound, our bounds maintain their effectiveness below the signal-to-noise ratio (SNR) at which the cutoff rate of the channel equals the rate of the code. Some applications are shown. First, we derive upper bounds to the minimum SNR necessary to achieve zero error probability as the code block length increases to infinity. Next, we use our bounds to predict the performance of turbo codes and low-density parity-check codes.

This paper concerns the estimation of a frequency offset of a known (pilot) signal propagated through a slowly fading multipath channel, such that channel parameters are considered to he constant over the observation interval. We derive a maximum-likelihood (ML) frequency estimation algorithm for additive Gaussian noise and path amplitudes having complex Gaussian distribution when covariance matrices of the fading and noise are known; we consider in detail the algorithm for the white noise and Rayleigh fading, in particular, for independent fading of path amplitudes and pilot signals with diagonal autocorrelation matrices. For the latter scenario, we also derive an ML frequency estimator when the power delay profile is unknown, but the noise variance and bounds for the path amplitude variances are specified; in particular, this algorithm can be used when path delays and amplitude variances are unknown. Finally, we consider frequency estimators which do not use a priori information about the noise variance; these algorithms are also operable without timing synchronization. All the frequency estimators exploit the multipath diversity by combining periodograms of multipath signal components and searching for the maximum of the combined statistic. For implementation of the algorithms, we use a fast Fourier transform-based coarse search and fine dichotomous search. We perform simulations to compare the algorithms. The simulation results demonstrate high accuracy performance of the proposed frequency estimators in wide signal-to-noise ratio and frequency acquisition range.

For transmission of digital data over a linear channel with additive white noise, it can be shown that the optimal symbol-decision equalizer is nonlinear. The Kernel Adaline algorithm, a nonlinear generalization of Widrow's and Hoff's (1960) Adaline, is capable of learning arbitrary nonlinear decision boundaries while retaining the desirable convergence properties of the linear Adaline. This work investigates the use of the Kernel Adaline as an equalizer for such transmission channels. We show that the performance of the Kernel Adaline approaches that of the optimal symbol-decision equalizer given by Bayes theory and further, still produces useful results when the additive noise is nonwhite. A description and preliminary results of an adaptive version of the Kernel Adaline are also presented.

Channels with a sparse impulse response arise in a number of communication applications. Exploiting the sparsity of the channel, we show how an estimate of the channel may be obtained using a matching pursuit (MP) algorithm. This estimate is compared to thresholded variants of the least squares (LS) channel estimate. Among these sparse channel estimates, the MP estimate is computationally much simpler to implement and a shorter training sequence is required to form an accurate channel estimate leading to greater information throughput.

We derive new Cramer-Rao lower bounds (CRBs) for the estimation of carrier phase and frequency offset from an unmodulated carrier or from a M-PSK data signal. The new CRBs are obtained formally from the exact likelihood function for the carrier phase and frequency offset, build from a block of received phase samples, and are applicable for a general alphabet size M. The bounds are compared with other previously obtained bounds (which also take into account the effect of random phase modulation) and with the performance of some popular feedforward algorithms for carrier phase and frequency offset estimation.

In direct-sequence code-division multiple access, a code synchronization must take place before the multiuser detector. As the initial synchronization stage, a code acquisition scheme is used to estimate the relative timing phase for the desired transmission within one chip interval. In this paper, a blind code acquisition scheme using adaptive linear filtering based on a linearly constrained constant modulus algorithm (CMA) is proposed. The uncertainty of a desired user's delay is initially discretized and translated into a number of hypotheses. The lock convergence property of CMA is exploited, where the filter at the steady state can lock onto the desired user while nulling all other interfering users (i.e., a decorrelator). For each delay hypothesis, the filter is initialized as the corresponding shifted spreading sequence of the desired user. It is shown that lock convergence always occurs for the correct hypothesis, while all incorrect hypotheses will be hovered around some saddle regions, given sufficiently small step sizes. Then, the correct hypothesis is the one which has the converged filter to yield the maximum lock onto the desired user, or a maximum output energy.

A semianalytical (SA) simulation method is proposed as a means to improve the efficiency of computer simulation in estimating block-error rates (BKERs) in the presence of Doppler fading and additive white Gaussian noise. Frequency-nonselective Rayleigh, Rician, and Nakagami fading with diversity combining for binary noncoherent frequency-shift keying (NCFSK) modulation are considered. The reduction in required computer simulation time of the SA method compared to the conventional Monte Carlo (MC) simulation is assessed.

The performances of selection diversity receiver structures in a slow flat Rayleigh-fading environment are assessed. A number of new and interesting results are obtained. Binary digital signaling using noncoherent frequency-shift keying (NCFSK), differential phase-shift keying (DPSK), coherent phase-shift keying (CPSK), and coherent frequency-shift keying (CFSK) is considered. The traditional analysis (the traditional selection diversity model) of a selection diversity system is based on choosing the branch with the largest signal-to-noise (SNR) power ratio while assuming that the noise power is constant across all branches. However, many practical selection systems choose the branch based on a largest signal-plus-noise (S+N selection) sample of a filter output. This paper comprises accurate analyses of such S+N selection systems. Results show that S+N selection systems perform better than predicted by the traditional selection diversity model. This is because the former includes the statistical nature of the noise, whereas the latter does not. The performance difference between the two models increases as the number of diversity branches increases. For each of DPSK and CPSK, the dual diversity equal gain (EG) combining and S+N selection systems perform identically. For each of NCFSK and CFSK, receiver structures which are equivalent when there is no diversity perform differently in a diversity environment. Certain dual diversity S+N selection systems give the same performances as EG combining or square law combining. The results are contingent upon perfect cophasing for the EG combining. In systems where estimates of the combining carrier phases contain noise, S+N selection outperforms EG combining for dual diversity.

The focus of this paper is on the initial acquisition of a direct sequence (DS) spread-spectrum signal utilizing a purely parallel search strategy. A parallel search strategy is utilized because it reduces the acquisition time compared to either serial or partially parallel strategies. In particular, the purpose of this paper is to derive the optimal decision rule, based on the maximum-likelihood criterion, for frequency-selective fading channels. The performance of the conventional decision rule, optimized for additive white Gaussian noise and flat-fading channels, the optimal decision rule derived, and a suboptimal decision rule, also presented in this paper, are compared. It is shown that the optimal and suboptimal decision rules for Rayleigh-fading channels outperform the conventional decision rule. For Rician-fading channels, it is shown both that the optimal decision rule outperforms the conventional decision rule, and that the optimum decision rule for Rayleigh-fading channels, when implemented on a Rician-fading channel, yields approximately optimum performance.

The problem of asynchronous classification of M-ary frequency-shift keying (MFSK) signals when contaminated by additive white Gaussian noise (AWGN) is addressed. Two approaches are adopted. The first is based on the classical likelihood-ratio theory, which provides performance that is optimal, but sensitive to unknown frequency offsets. The second completely eliminates the fixed-frequency structure and instead utilizes measurements made strictly in the higher order correlation (HOC) domain. Assessed are the sensitivity gaps in performance incurred by the synchronous rules when the unknown signal time of arrival or epoch offsets are introduced. This sensitivity is ameliorated by averaging over a reduced-uncertainty epoch model. Fairly satisfactory results are reported with a small number of the discretized epoch uncertainty levels.

This paper develops a receiver structure to perform jointly maximum-likelihood (ML) synchronization, equalization, and detection of a linearly modulated signal transmitted over a time-varying frequency-selective Rician-faded channel, corrupted by additive white Gaussian noise (AWGN). The receiver is particularly suited to a fast-fading channel, where other receivers that rely on estimating the channel cannot track it quickly enough. The signal mean and autocovariance are needed, and a scheme is proposed for estimating these quantities adaptively. The receiver processes the specular and diffuse components (corresponding to the signal mean and autocovariance) separately. Processing the known specular component is the classical detection problem. The unknown diffuse component is processed by predictors. We show that the predictors can achieve synchronization in a novel manner, if synchronization is required. A union bound on the receiver's bit-error rate (BER) is derived, and it tightly bounds simulated BERs in fast-fading at high signal-to-noise ratios (SNRs).

We consider a communication channel corrupted by thermal noise and by an unknown and arbitrary interference of bounded energy. For this channel, we derive a simple upper bound to the worst-case error probability suffered by a direct sequence (DS) communication system with error-correction coding, pseudorandom interleaving, and a correlation receiver. This bound is exponentially tight as the block length of the error correcting code becomes large. Numerical examples are given that illustrate the dependence of the bound on the choice of error correcting code, the type of interleaving used, and the relative energy of the Gaussian noise and arbitrary interference.

This paper investigates tracking of direct-sequence spread-spectrum (DS/SS) signals based on an adaptive filtering technique. It is shown that a previously proposed hardware for code acquisition is also capable of code-tracking, and, hence, by performing both acquisition and tracking with the same circuitry, a significant simplification in the overall DS/SS receiver structure is gained. Analytical results show that the proposed scheme has a good tracking performance, as measured by the hold-in time and the false alarm penalty time, and is less sensitive to variations in the signal-to-noise ratio (SNR) compared to conventional delay-locked loops (DLLs). Moreover, simulation results show that the proposed adaptive filter tracking scheme has a smaller residual tracking error than that produced by a conventional maximum-likelihood estimator (MLE).

Analytical expressions for bit-error probability are derived for a fast frequency-hopping binary frequency-shift keying (FFH/BFSK) spread-spectrum communication system over a fading channel with worst-case band multitone jamming (MTJ) and additive white Gaussian noise (AWGN). An FFH system employing either a linear-combining receiver or a clipper receiver is investigated. The desired signal and MTJ are assumed to undergo independent fading, and our analysis, validated with simulation results, shows that the performance of the system is slightly improved as the severity of the MTJ fading is increased. The clipper receiver is found to be superior to the linear-combining receiver when the jamming power is strong. The worst-case MTJ is shown to be more harmful than the corresponding worst-case partial-band noise jamming over a fading channel with AWGN.

In this paper we extend the scalar modified Cramer-Rao bound (MCRB) to the estimation of a vector of nonrandom parameters in the presence of nuisance parameters. The resulting bound is denoted with the acronym MCRVB, where "V" stands for "vector". As with the scalar bound, the MCRVB is generally looser than the conventional CRVB, but the two bounds are shown to coincide in some situations of practical interest. The MCRVB is applied to the joint estimation of carrier frequency, phase, and symbol epoch of a linearly modulated waveform corrupted by correlated impulsive noise (encompassing white Gaussian noise as a particular case), wherein data symbols and noise power are regarded as nuisance parameters. In this situation, calculation of the conventional CRVB is infeasible, while application of the MCRVB leads to simple useful expressions with moderate analytical effort. When specialized to the case of white Gaussian noise, the MCRVB yields results already available in the literature in fragmentary form and simplified contexts.

The locally optimum Bayes detection (LOBD) framework for nonadditive non-Gaussian noise is applied to a particular additive and signal-dependent noise model where the noise components are correlated. Under the proposed observation model, the performance of the LOB detectors is compared with that of well-known conventional receivers.

The expectation-maximization (EM) algorithm was first introduced in the statistics literature as an iterative procedure that under some conditions produces maximum-likelihood (hit) parameter estimates. In this paper we investigate the application of the EM algorithm to sequence estimation in the presence of random disturbances and additive white Gaussian noise. As examples of the use of the EM algorithm, we look at the random-phase and fading channels, and show that a formulation of the sequence estimation problem based on the EM algorithm can provide a means of obtaining ML sequence estimates, a task that has been previously too complex to perform.

A new approach for the decision feedback equalizer (DFE) based on the functional-link neural network is described. The structure is applied to the problem of adaptive equalization in the presence of intersymbol interference (ISI), additive white Gaussian noise, and co-channel interference (CCI). It is shown through simulation results for a severe amplitude distorted co-channel system that the decision feedback functional-link equalizer (DFFLE) provides significantly superior bit-error rate (BER) performance characteristics compared to the conventional DFE, the linear transversal equalizer (LTE), the nonlinear radial basis function (RBF) neural-network-based structures and the feed-forward functional-link equalizer (FFLE)-based structures. The DFFLE is also shown to have a significantly simpler computational requirement relative to the RBF and the FFLE.

The encoding and decoding schemes presented are aimed at enabling the transfer of data through a channel in which two types of interference are added to the transmitted signal and the sum is quantized. One of these interferences is known (or can be estimated), whereas the second is an additive white Gaussian noise (AWGN). Since the input of the quantizer is not accessible, the known interference can not be removed from the received signal. We show that the error rate for an uncoded transmission through this channel is unacceptably large, even for low noise levels and linear quantization. It is also shown that the problem becomes even more severe when a nonlinear quantization is present. Therefore, coding is essential and a huge coding gain is achievable in this application. An upper-bound on the error rate, contributed by the component codes of a multilevel code, has been developed for multistage decoding. Results of computer simulations of a practical case with optimal and suboptimal decoding algorithms, both developed in this paper, are presented.

For pt.I see ibid., vol.45, no.1, p.64-72, 1997. We use the construction technique proposed in part I to construct multidimensional trellis coded modulation (TCM) codes for both the additive white Gaussian noise (AWGN) and the fading channels. Analytical performance bounds and simulation results show that these codes perform very well and achieve significant coding gains over uncoded reference modulation systems. In addition, the proposed technique can be used to construct codes which have a performance/decoding complexity advantage over the codes listed in literature.

Communication over a waveform channel corrupted by additive white Gaussian noise and by an unknown and arbitrary interference of bounded power is considered. For this channel, an upper bound is presented for the worst-case error probability of a communication system comprising a direct-sequence spread spectrum modulator and a nonlinear correlation receiver. It is shown that this bound is exponentially tight as the number of chips used in the modulator becomes large. This bound is evaluated for several detector nonlinearities. Numerical examples and comparisons to the performance of a pure Gaussian noise channel are also given.

This paper presents a method for improving the performance of differential detection of differentially encoded phase shift keying (DPSK). The structure of the proposed detection scheme consists of a conventional differential detection circuit equipped with an infinite impulse response (IIR) filter combined with decision feedback. The results of theoretical analysis and computer simulation show that performance of the proposed detection method can approach that of coherent detection of DPSK under additive white Gaussian noise (AWGN) conditions without any increase in architectural complexity. Furthermore, a parameter of the proposed detector can be varied to optimize performance for static or fading conditions. An adaptive scheme suitable for time varying Rician-fading channel conditions is presented, and performance results obtained by computer simulation are given.

A new technique for soft synchronization of direct-sequence spread-spectrum (DSSS) signals is presented. The technique, referred to as the dominant mode despreading (DMDS) algorithm, exploits the eigenstructure of a frequency-channelized DSSS signal to estimate the spreading code and underlying message sequence of the signal. Unlike other despreading techniques, the estimate of the code and data improves steadily with the number of code repeats. The technique is applicable to arbitrary spreading codes and message sequences and can operate in environments containing arbitrary levels of white background noise, and for signals with arbitrary unknown timing phase or carrier frequency offset. The technique requires the DSSS signal to have a constant-modulus spreading code and unrelated message and code-repeat rates. This paper introduces the basic technique, theoretically analyzes the algorithm to prove convergence under infinite time-average conditions, and demonstrates the algorithm via computer simulation for a single DSSS signal received in the presence of white Gaussian noise.

This paper presents and analyzes a technique for reducing the spurious signal content in digital sinusoid synthesis. Spur reduction is accomplished through dithering amplitude and phase values prior to wordlength reduction. The analytical approach developed for analog quantization is used to produce new bounds on spur performance in these dithered systems. Amplitude dithering allows output wordlength reduction without introducing additional spurs. Effects of periodic dither similar to that produced by a pseudo-noise (PN) generator are analyzed. This phase dithering method provides a spur reduction of 6(M+1) dB per phase bit when the dither consists of M uniform variates. While the spur reduction is at the expense of an increase in system noise, the noise can be made white, making the noise power spectral density small. This technique permits the use of a smaller number of phase bits addressing sinusoid look-up tables, resulting in an exponential decrease in system complexity. Amplitude dithering allows the use of less complicated multipliers and narrower data paths in purely digital applications, as well as the use of coarse-resolution, highly-linear digital-to-analog converters (DAC's) to obtain spur performance limited by the DAC linearity rather than its resolution. >

Impulsive noise bursts in communication systems are traditionally handled by incorporating in the receiver a limiter which clips the received signal before integration. An empirical justification for this procedure is that it generally causes the signal-to-noise ratio to increase. Recently, very accurate models of impulsive noise were presented, based on the theory of symmetric /spl alpha/-stable probability density functions. We examine the performance of optimum receivers, designed to detect signals embedded in impulsive noise which is modeled as an infinite variance symmetric /spl alpha/-stable process, and compare it against the performance of several suboptimum receivers. As a measure of receiver performance, we compute an asymptotic expression for the probability of error for each receiver and compare it to the probability of error calculated by extensive Monte-Carlo simulation. >

This paper provides a new closed form expression for calculating the probability that an MPSK signal will lie in a particular decision region when received over N independent and identically distributed Rayleigh fading channels corrupted by additive white Gaussian noise. This expression is applied to provide a unified method to derive the exact symbol error rate and bit error rate for MPSK signals considering N channel diversity reception. The N channel diversity reception techniques considered are maximal ratio combining (MRC) and selection combining. MRC with identical channels and dissimilar channels is considered. The results for MRC can be extended to provide an approximation for the error rates of MPSK under equal gain combining. >

This article deals with the analysis of a decision-directed echo canceller working in a baseband data communication link. This guided scheme, as known in self-adaptive equalization systems, introduces stable local minima in the error surface thus dissuading any gradient search procedure. Regardless of this drawback, the article studies two stochastic gradient algorithms in a multimodal error surface context. They are based in the minimization of absolute and quadratic norms (L/sub 1/ and L/sub 2/) of an improved error reference signal. The analysis assumes bipolar data contaminated with a residual intersymbol interference plus background white noise. The article introduces a new perspective on the analysis of conditions that guarantees convergence towards any desired steady state even with the existence of local minima. It uses a dynamic bounding function for the adaption step dependent on the residual echo variance that allows tracking of the global convergence-condition in the working range. Furthermore, the analysis makes it also possible to predict whether the algorithm will converge or whether it could be trapped in any stable stationary point. It also shows the risky dependence of the convergence towards an undesired steady state on some internal and working variables, such as initial filter settings, interference level, etc. >

Analyzes the sensitivity of equalizers to white gaussian noise mismatch, which exists whenever the noise power observed during training differs from that observed during detection. A closed-form solution for the mean-square error is obtained for linear and decision feedback equalizers as a function of the channel spectrum and degree of noise mismatch. The results show that increasing equalizer complexity may actually degrade performance in the presence of channel mismatch. >

A unified treatment is presented for the problem of detecting binary data transmitted over an L-fold diversity complex non-Gaussian channel further disturbed by additive white Gaussian noise. The data is extracted using a quadratic form detector driven by the outputs from a cross-correlation detector matched to the transmitted signals. By employing a probability density function (PDF) expansion technique, the bit error probability is decomposed into a Gaussian and a non-Gaussian component. Our results, being valid for the doubly dispersive (space and time) channels, are reduced to expressions which characterize the performance for other channel types, viz., the wide-sense stationary uncorrelated scattering (WSSUS), the temporally-dispersive spatially-nondispersive, the temporally-nondispersive spatially-dispersive, and the totally nondispersive channel. A coherence matrix is defined which allows us to treat three types of diversity reception, vis., noncoherent, partially coherent, and coherent detection with a noisy phase reference. Detailed performance analysis of the noncoherent case is presented and used to numerically evaluate system performance over a non-Gaussian channel modeled by the Middleton (1977) class A PDF. >

We propose a recursive algorithm to compute the joint maximum a-posteriori (MAP) probability of a subblock of N consecutive symbols (i.e., a sliding window of length N) of a finite-state discrete-time Markov process of length K/spl ges/N observed in white noise given the whole block is received. This "optimal subblock-by-subblock detector" (OBBD, "vector MAP") is a generalization of the "optimal symbol-by-symbol detector" (OSSD, "symbol-by-symbol MAP"), which is obtained for N=1. The new algorithm improves applications with outer stage processing. This is indicated by investigating the average mutual information of a convolutional coding system. An example shows that the gain (in terms of average mutual information) by using joint probabilities could even exceed the gain by delivering soft OSSD outputs instead of hard outputs. >

A method is presented for the calculation of M-ary DPSK error probability in partial-band multitone jamming and white gaussian noise. Both unfaded and faded signals and jamming tones may be analyzed by the method. The fading considered is frequency-flat, time selective, Rician fading. The results have application in mobile, slow frequency-hopped, military, satellite systems. The method uses the Pawula-Rice-Roberts (1982) method for calculating the probability distribution function of the phase angle between two vectors when they are perturbed by noise. The worst case error probability in partial-band jamming with fading is efficiently computed using Houston's (1975) approach. A fundamental parameter, independent of the actual jammer power being used on the system, is identified. The effect of the ratio of the direct signal energy to the faded (indirect) signal energy is shown by example, as is the effect of fading bandwidth and Doppler shift. For practical values of the parameters, jammer fading was not found to be significant. Results for M=2, 4, and 8 are given. >