The authors propose Markovian‐based spectrum sensing policies in a cognitive radio system that leverages past sensing outcomes of several cooperating secondary users (SUs) to decide which channel (of primary users – PUs) should be sensed by each SU at a given time. These policies are based on a new finite‐state channel model that captures the fading condition as well as the occupancy state for each primary channel. The multiuser extension of this model is useful when multiple spatially distributed SUs share their sensing outcomes. The proposed schemes allow the asynchronous sensing outcomes obtained by the SUs over different slots to be fused together and converted into a posteriori probabilities for the current states of the primary channels. As the detection threshold in a spectrum detector balances the trade‐off between the false‐alarm and miss probabilities for detecting primary signals in a single primary channel, a design parameter is introduced to allow the system designer to devise policies with different levels of aggressiveness. The authors evaluate the optimality and complexity of the proposed sensing policies and show that our schemes significantly increase secondary use of the spectrum and/or reduce interference with PUs compared to a random selection policy or a cooperative sensing policy based on a two‐state channel model.

Recent findings in neuroscience have shown that the spectral components of electroencephalogram (EEG) signals convey information regarding the mental task not only in their power but also in their phase. This calls for the utilization of complex-valued spectrum, instead of the commonly used power spectral density, in designing the brain computer interfaces. This paper studies the complex-valued spectrum of the EEG signal recorded during mental imagery tasks, and provides a statistical model for the EEG spectral components. Motivated by the results of a recent work by the authors, this paper proposes a time-varying noncircularly-symmetric Gaussian model for complex-valued EEG spectrum during a mental imagery trial. It will be shown that the mean of this Gaussian model is constant over time, whereas its variance and pseudo-variance follow an autoregressive conditional heteroscedastic (ARCH) model. The validity of this model is then verified using statistical tests.

The use of wireless body area networks requires correct delivery of the vital signs of the patient while managing precious energy in tiny biosensors. Toward these goals, we present an energy-efficient protocol suitable for the narrow band physical layer of the IEEE 802.15.6 standard in on-body sensor networks. This study considers a realistic channel model inspired by the Gilbert-Elliott channel including the erasure mode and a binary symmetric channel model. This work studies the feasibility of Raptor codes, the most efficient rateless codes, with the Frequency Shift Keying (FSK) modulation to overcome the reliability and power cost concerns in on-body sensor devices. The main advantage of using Raptor codes is to provide an inherent adaptive power management, due to the flexibility of the code rate and coding gain. Numerical results show that the Raptor coded FSK is more energy efficient and robust than that of the uncoded FSK and LDPC codes, in various channel realization, in particular, when patients make sequential position changes.

We consider a scenario where multiple collaborating cognitive radios (CR's) try to jointly detect spectrum opportunities in a wide-band spectrum within a predefined spectrum sensing time TS. Each CR is equipped with a tunable bandpass filter (BPF) and is able to sense one frequency band (channel) at a time. The sensing time consists of L sensing slots of length T. During each sensing slot, each of the collaborating CR's is assigned to sense one of the primary channels and report its observation to the other CR's. The goal is to maximize the expected number of identified idle channels by optimally choosing the channels to be sensed by each of the collaborating CR's at each sensing slot. We derive closed-form solutions for an optimal spectrum sensing policy and the associated reward function for the case of two collaborating CR's where individual sensing decisions are fused together according to the OR-rule. We show that the gain due to the optimal sensing policy is more significant when the spectrum utilization is high.

Owing to the unique characteristics of sensor devices, finding the energy-efficient modulation with a low-complexity implementation (refereed to as green modulation) poses significant challenges in the physical layer design of wireless sensor networks (WSNs). Towards this goal, the authors present an in-depth analysis on the energy efficiency of various modulation schemes using realistic models in the IEEE 802.15.4 standard to find the optimum distance-based scheme in a WSN over Rayleigh and Rician fading channels with path loss. The authors describe a proactive system model according to a flexible duty-cycling mechanism utilised in practical sensor apparatus. The present analysis includes the effect of the channel bandwidth and the active mode duration on the energy consumption of popular modulation designs. Path-loss exponent and DC–DC converter efficiency are also taken into consideration. In considering the energy efficiency and complexity, it is demonstrated that among various sinusoidal carrier-based modulations, the optimised non-coherent M-ary frequency shift keying (NC-MFSK) is the most energy-efficient scheme in sparse WSNs for each value of the path-loss exponent, where the optimisation is performed over the modulation parameters. In addition, the authors show that the on–off keying displays a significant energy saving as compared to the optimised NC-MFSK in dense WSNs with small values of path-loss exponent.

Adaptive Demodulation (ADM) is a new rate-adaptive system that operates without requiring Channel State Information (CSI) at the transmitter, instead using adaptive decision region boundaries at the receiver and encoding the data with a rateless code. This paper addresses the design and performance of an ADM scheme for two common differentially coherent schemes: M-DPSK and M-DAPSK. The optimal method for determining the most reliable bits for a given differential detection scheme is presented. In addition, simple (near-optimal) implementations are provided for recovering the most reliable bits from a received pair of differentially encoded symbols for systems using 16-DPSK and 16-DAPSK. The new receivers offer the advantages of a rate-adaptive system, without requiring CSI at the transmitter or a coherent phase reference at the receiver. Bit error analysis for the ADM system in both cases is presented along with numerical results of the spectral efficiency for the rate-adaptive systems operating over a Rayleigh fading channel.

The use of wireless implant technology requires correct delivery of the vital physiological signs of the patient along with the energy management in power-constrained devices. Toward these goals, we present an augmentation protocol for the physical layer of the medical implant communications service (MICS) with focus on the energy efficiency of deployed devices over the MICS frequency band. The present protocol uses the rateless code with the frequency-shift keying (FSK) modulation scheme to overcome the reliability and power cost concerns in tiny implantable sensors due to the considerable attenuation of propagated signals across the human body. In addition, the protocol allows a fast start-up time for the transceiver circuitry. The main advantage of using rateless codes is to provide an inherent adaptive duty cycling for power management, due to the flexibility of the rateless code rate. Analytical results demonstrate that an 80% energy saving is achievable with the proposed protocol when compared to the IEEE 802.15.4 physical layer standard with the same structure used for wireless sensor networks. Numerical results show that the optimized rateless coded FSK is more energy efficient than that of the uncoded FSK scheme for deep tissue (e.g., digestive endoscopy) applications, where the optimization is performed over modulation and coding parameters.

Due to unique characteristics of sensor nodes, choosing an energy-efficient modulation scheme with low-complexity implementation (refereed to as green modulation) is a critical factor in the physical layer of Wireless Sensor Networks (WSNs). The main goal of this paper is to analyze and compare the energy efficiency of various sinusoidal carrier-based modulation schemes using parameters in the IEEE 802.15.4 standard and state-of-the art technology to find the best scheme in a dense WSN over frequency-flat Rayleigh fading channel with path-loss. Experimental results show that M-ary Frequency Shift Keying (MFSK) with small order of M has significant energy saving compared to OQPSK and MQAM for short range scenarios, and could be considered as a realistic candidate in dense WSNs. In addition, MFSK has the advantage of less complexity and cost in implementation than the other schemes.

Cognitive radios try to exploit “blank spaces” in the licensed band which are not being used by primary users at a particular place and time. In the absence of cooperation between the primary and the secondary networks, spectrum sensing enables secondary users to monitor a licensed band in order to find idle channels for opportunistic access. In this work, we propose a two-stage spectrum detection strategy that decreases the average channel search time by allowing the spectrum detector to focus on frequency channels which are more likely to be vacant. We show that the proposed detection strategy significantly outperforms the conventional single-stage strategy when the spectrum utilization is high.

Classification of mental tasks from electroencephalogram (EEG) signals has important applications in brain-computer interfacing (BCI). However, classification of the highly redundant and high-dimensional EEG signal, with high spatial and spectral correlations, is quite challenging. Therefore, the discriminant information, especially that of the first and second data moments, need to be extracted in the form of uncorrelated features. This work addresses this need by approximating a linear minimal-dimension sufficient statistic of the EEG matrix data in both spatial and spectral domains. As a result of the two-dimensional spatio-temporal approach and the generalized sufficiency approximation, a significant improvement on the classification accuracy is achieved.

This paper proposes a new receiver structure for linear-dispersion (LD) codes, subsuming orthogonal, quasiorthogonal and V-BLAST codes. We suggest to use widely-linear minimum-mean-squared-error (WL-MMSE) estimates of transmitted symbols in lieu of the sufficient statistics for maximum likelihood (ML) detection of these symbols. Proposed structure offers both optimal (ML) and suboptimal solutions. Simulation results show that the suboptimal receiver performs close to the optimal one, while reducing the receiver's complexity. Structure of the proposed receiver is particularly studied for orthogonal and quasi-orthogonal LD codes. Specifically, it is proved that Alamouti's combining scheme provides WL-MMSE estimates of the transmitted symbols.

In this letter, a design metric of the interleaver is derived from the union bound of the bit error rate (BER) of linearly precoded orthogonal frequency division multiplexing (OFDM) systems, assuming that the power-delay profile of the channel is known at the transmitter. A new cyclic shift interleaving scheme is proposed to improve the BER performance of OFDM systems. The proposed interleaving scheme is parameterized, and it incorporates existing interleaving schemes. The simulation results indicate that the proposed interleavers outperform the existing interleavers by up to 1.5 dB in a practical scenario.

In this paper, we propose a duality-optimization based framework to maximize the weighted sum throughput for a multiple-input multiple-output (MIMO) ad hoc network. The new schemes include an approximate global optimization approach and an iterative search approach based on the duality framework. Transmitter adaptive precoding and receiver minimum mean-square-error (MMSE) detection for interference suppression are considered. Simulation results show that a significantly higher throughput is achieved for the dual optimization schemes than for the fixed mode precoding schemes and the transmit iterative waterfilling (IWF) scheme. The negative effects of transmit and receive antenna correlations are also studied. Results show that the proposed schemes are more robust against both transmit and receive correlations than the fixed-mode and IWF schemes.

The problem of iterative detection/decoding of data symbols transmitted over an additive white Gaussian noise (AWGN) channel in the presence of phase uncertainty is addressed in this paper. By modelling the phase uncertainty either as an unknown deterministic variable/process or random variable/ process with a known a priori probability density function, a number of non-Bayesian and Bayesian detection algorithms with various amount of suboptimality have been proposed in the literature to solve the problem. In this paper, a new set of suboptimal iterative detection algorithms is obtained by utilizing the variational bounding technique. Especially, applying the generic variational Bayesian (VB) framework, efficient iterative joint estimation and detection/decoding schemes are derived for the constant phase model as well as for the dynamic phase model. In addition, the relation of the VB-based approach to the optimal noncoherent receiver as well as to the classical approach via the expectation-maximization (EM) algorithm is provided. Performance of the proposed detectors in the presence of a strong dynamic phase noise is compared to the performance of the existing detectors. Furthermore, an incremental scheduling of the VB (or EM) algorithm is shown to reduce the overall complexity of the receiver.

In a wide range of communication systems, including DS-CDMA and OFDM systems, the signal-of-interest might be corrupted by an improper (F.D. Neeser et al.,1993) (also called non circularly symmetric (B. Picinbono, 1994)) interfering signal. This paper studies the maximum likelihood (ML) detection of binary signals in the presence of additive improper complex Gaussian noise. Proposing a new measure for noncircularity of complex random variables, we will derive the ML decision rule and its performance based on this measure. It will be shown that the ML detector performs pseudo correlation (F.D. Neeser et al.,1993) as well as conventional correlation of the observation to the signals-of-interest. As an alternative solution, we will propose a filter for converting improper signals to proper ones, called circularization filter, and will utilize it together with a conventional matched-filter (MF) to construct an ML detector.

In this paper, we derive general asymptotic moment generating function (MGF) expressions of the GSC output signal- to-noise ratio (SNR) for generalized correlated fading channels assuming large average signal-to-noise ratio (ASNR). Based on the MGF result, the asymptotic diversity and combining gains for correlated-diversity GSC are derived. Our analytical results reveal that over correlated channels when the channel covariance matrix is full rank the diversity gain of GSC is to equivalent to that of maximum ratio combining (MRC) with independent fading branches. The combining gains for different modulation formats and fading types in correlated channels are also derived. As is known and analytically verified in this paper, for channels without line-of-sight (LoS) components, correlation generally degrades the GSC combining gain. However, we show that for Rician channels the LoS phase vector affects the performance, and near-optimal LoS phase vector brings a larger combining gain than even the independent fading channels.

Adaptive demodulation (ADM) is a new rate adaptive technique wherein the receiver demodulates only the most reliable bits and treats unreliable bits as erasures. This paper derives the optimum and simple near-optimum receivers for an ADM system operating without a coherent phase reference, where differential encoding is assumed at the transmitter (using 16-DPSK and 16-DAPSK). The new receivers offer the advantages of a rate-adaptive system, without requiring channel state information at the transmitter or a coherent phase reference at the receiver. Bit error analysis for the ADM system in both cases is presented along with numerical results of the spectral efficiency for the rate adaptive systems operating over a Rayleigh fading channel.

This paper introduces a precoder design for wireless receivers with imperfect fading channel state information (CSI). Imperfect CSI arises from inaccurate channel modelling or suboptimum channel estimation procedure. Precoders at transmitters are considered here as the means to reduce detection error. To that end, a new lower bound for pairwise error probability (PEP) is introduced. Using the proposed lower bound, precoders are optimized to improve the bit error rate (BER) performance of a receiver which uses basis expansion models (BEM) to estimate time varying channel coefficients without statistical information about the channel. Two precoder design criteria, namely pairwise coding and diversity gain are introduced through the proposed lower bound. Experimentation and theoretical analysis reported here indicate significant improvement in the BER performance of the BEM based receiver when it is used with the precoder in fading channels.

Many algorithms in signal processing and digital communications must deal with the problem of computing the probabilities of the hidden state variables given the observations, i.e., the inference problem, as well as with the problem of estimating the model parameters. Such an inference and estimation problem is encountered, for example, in adaptive turbo equalization/demodulation where soft information about the transmitted data symbols has to be inferred in the presence of the channel uncertainty, given the received signal samples anda prioriinformation provided by the decoder. An exact inference algorithm computes thea posterioriprobability (APP) values for all transmitted symbols, but the computation of App-s is known to be an NP-hard problem, thus rendering this approach computationally prohibitive in most cases. We show in this paper how may of the well-known low complexity soft-input soft-output (SISO) equalizers, including the channel matched filter based linear SISO equalizers and minimum mean square error (MMSE) SISO equalizers as well as the expectation-maximization (EM) algorithm based SISO demodulators in the presence of the Rayleigh fading channel, can be formulated as solutons to a variational optimization problem. The variational optimization is a well-established methodology for low-complexity inference and estimation, originating from statistical physics. Importantly, the imposed variational optimization framework provides an interesting link between the APP demodulators and the linear SISO equalizers. Moreover, it provides a new set of insights into the structure and performance of these widely celebrated linear SISO equalizers while suggesting some fine tuning of them as well.

Many algorithms in signal processing and digital communications must deal with the problem of computing the probabilities of the hidden state variables given the observations, i.e., the inference problem, as well as with the problem of estimating the model parameters. Such an inference and estimation problem is encountered, for e.g., in adaptive turbo equalization/demodulation where soft information about the transmitted data symbols has to be inferred in the presence of the channel uncertainty, given the received signal samples and aprioriinformation provided by the decoder. An exact inference algorithm computes the aposterioriprobability (APP) values for all transmitted symbols, but the computation of APPs is known to be an NP-hard problem, thus, rendering this approach computationally prohibitive in most cases. In this paper, we show how many of the well-known low-complexity soft-input soft-output (SISO) equalizers, including the channel-matched filter-based linear SISO equalizers and minimum mean square error (MMSE) SISO equalizers, as well as the expectation-maximization (EM) algorithm-based SISO demodulators in the presence of the Rayleigh fading channel, can be formulated as solutions to a variational optimization problem. The variational optimization is a well-established methodology for low-complexity inference and estimation, originating from statistical physics. Importantly, the imposedvariationaloptimization framework provides an interesting link between the APP demodulators and the linear SISO equalizers. Moreover, it provides a new set of insights into the structure and performance of these widely celebrated linear SISO equalizers while suggesting their fine tuning as well.

This paper presents a reduced-complexity approximate density evolution (DE) scheme for low-density parity-check (LDPC) codes in channels with memory in the form of a hidden Markov chain. This approximation is used to design degree sequences representing some of the best known LDPC code ensembles for the Gilbert-Elliott channel, and example optimizations are also given for other Markov channels. The problem of approximating the channel estimation is addressed by obtaining a specially constructed message-passing schedule in which the channel messages all approach their stable densities. It is shown that this new schedule is much easier to approximate than the standard schedule, but has the same ultimate performance in the limits of long block length and many decoding iterations. This result is extended to show that all message-passing schedules that satisfy mild conditions will have the same threshold under density evolution

A partial ordering on general finite-state Markov channels is given, which orders the channels in terms of probability of symbol error under iterative estimation decoding of a low-density parity-check (LDPC) code. This result is intended to mitigate the complexity of characterizing the performance of general finite-state Markov channels, which is difficult due to the large parameter space of this class of channel. An analysis tool, originally developed for the Gilbert-Elliott channel, is extended and generalized to general finite-state Markov channels. In doing so, an operator is introduced for combining finite-state Markov channels to create channels with larger state alphabets, which are then subject to the partial ordering. As a result, the probability of symbol error performance of finite-state Markov channels with different numbers of states and wide ranges of parameters can be directly compared. Several examples illustrating the use of the techniques are provided, focusing on binary finite-state Markov channels and Gaussian finite-state Markov channels. Furthermore, this result is used to order Gilbert-Elliott channels with different marginal state probabilities, which was left as an open problem by previous work.

Multiple-input multiple-output (MIMO) system using orthogonal frequency division multiplexing (OFDM) technique has become a promising method for reliable high data-rate wireless transmission system in which the channel is dispersive in both time and frequency domains. Due to multiple cochannel interferences in a MIMO system, the accuracy of channel estimation is a vital factor for proper receiver design in order to realize the full potential performance of the MIMO-OFDM system. A robust and improved channel estimation algorithm is proposed in this paper for MIMO-OFDM systems based on the least squares (LS) algorithm. The proposed algorithm, called improved LS (ILS), employs the noise correlation in order to reduce the variance of the LS estimation error by estimating and suppressing the noise in signal subspace. The performance of the ILS channel estimation algorithm is robust to the number of antennas in transmit and receive sides. The new algorithm attains a significant improvement in performance in comparison with that of the regular LS estimator. Also, with respect to mean square error criterion and without using channel statistics, the ILS algorithm achieves a performance very close to that of the minimum mean square error (MMSE) estimator in terms of the parameters used in practical MIMO-OFDM systems. A modification of the ILS algorithm, called modified ILS (MILS), is proposed based on using the second order statistical parameters of channel. Analytically, it is shown that the MILS estimator achieves the exact performance of the MMSE estimator. Due to no specific data sequences being required to perform the estimation, in addition to the training mode, the proposed channel estimation algorithms can also be extended and used in the tracking mode with decision-aided method.

Channel estimation accuracy has a significant impact on the performance of multiple-input multiple-output (MIMO) wireless communication systems due to cochannel interferences in MIMO channels. An improved channel estimation algorithm is presented in this paper for MIMO systems using orthogonal frequency division multiplexing (OFDM) technique based on the least squares (LS) algorithm. The proposed algorithm employs the noise correlation in order to improve the LS estimator by estimating and suppressing the noise in signal subspace. Without knowledge of the statistical parameters of channel, the new proposed algorithm attains a significant improvement in performance in comparison with that of the regular LS estimator and is also robust to the number of antennas in transmit and receive sides.

We introduce a rate-adaptive system in which the receiver demodulates only those bits that have a high probability of being correct, treating nondemodulated bits as erasures. Several sets of decision regions, derived using composite hypothesis testing, are proposed for 16-QAM and 16-phase-shift keying, which allow for the simple implementation of this demodulation strategy. We demonstrate that pre-encoding the data with a Raptor code allows for simple reconstruction of the message, regardless of the erasure pattern introduced from the nondemodulated bits. We prove the optimality of the proposed decision regions in selecting the most likely subset of bits from any received symbol in moderate-to-high signal-to-noise ratios, and we analyze the performance of demodulating with these decision regions over an additive white Gaussian noise channel. Also demonstrated is the strong performance of 16-QAM for this application, compared with other power-efficient constellations and the near-optimality of using Gray mapping, even under the proposed alternate sets of decision regions.

The Bell Labs layered space-time (BLAST) architecture is a simple and efficient multiantenna coding structure that can achieve high spectral efficiency. Many BLAST detectors require more receiver antennas than transmitter antennas. We propose two novel turbo-processing BLAST detectors that can operate in systems with fewer receiver antennas than transmitter antennas. Both detectors are based on the group-detection strategy. The first proposed detector, the reduced-dimension maximum a posteriori (RDMAP) detector uses a dynamically formed group for each bit decision, while the second proposed detector, the group maximum a posteriori (GMAP) uses a static grouping. For both detectors, a maximum a posteriori (MAP) decision is made using a group of transmitted symbols, and the remaining signal contribution is treated as interference. The interference is characterized as nonzero mean colored-noise source that is whitened before a decision is made. Both proposed detectors are generalizations of the MAP detector and the turbo-processing minimum mean-squared error (MMSE) detector in Sellathurai and Haykin, and Abe and Matsumoto. An uncoded bit-error rate analysis for an independent Rayleigh fading environment is also presented. Simulated results are presented which show that both the RDMAP and GMAP detectors have a performance improvement over the MMSE detector, especially in systems having an excess number of transmitter antennas.

Pulse shaping is examined as a means to improve the performance of a differential offset quadrature phase-shift keying system in a bandwidth-constrained environment. Through optimization with respect to a composite Nyquist criterion, the derived pulse shapes have comparable performance to a /spl pi//4-differential quadrature phase-shift keying in an additive white Gaussian noise (AWGN) channel and better performance in a hard-limited AWGN channel.

In this paper, we present a unified mathematical framework to analyze the bit-error rate (BER) performance of general linear coherent multiuser receivers with diversity reception and imperfect channel estimation for doubly selective Rician-fading asynchronous code-division multiple-access channels. BERs of linear receivers with channel state information and data-aided channel estimation are analyzed, and both exact and low-complexity approximate BER evaluation formulas are presented. Furthermore, by using a Markov chain steady-state analysis, a tight BER approximation for receivers with decision-directed channel estimation is proposed. Numerical and simulation results verify the accuracy of the proposed BER evaluation methods.

In this letter, we study the asymptotic performance of hybrid-selection/maximal-ratio combining (HS/MRC) and postdetection HS/equal-gain combining (HS/EGC) over generalized fading channels for large average signal-to-noise ratios (ASNRs). By evaluating the asymptotic moment generating function of the HS/MRC output SNR at high ASNR, we derive the diversity and coding gains for HS/MRC for a large class of modulation formats and versatile fading conditions, including different types of fading channels and nonidentical SNR statistics across diversity branches. Our analytical results reveal that the diversity gains of HS/MRC and HS/EGC are equivalent to that of MRC, and the difference in the coding gains for different modulation formats is manifested in terms of a modulation factor defined in this letter. Some new analytical results about effects of the number of combined branches for HS/MRC and noncoherent combining loss of HS/EGC are also provided.

This paper studies an enhanced widely linear (WL) receiver for direct-sequence code-division multiple-access (DS-CDMA) systems that employ aperiodic spreading sequences with offset quadrature phase-shift keying (OQPSK) modulation. The modulation scheme generates improper complex multiple-access interference (MAI) and necessitates the use of WL receivers. Focus is on bandlimited pulse shapes and the inherent cyclostationarity (CS) of the uncoded received signal. The enhanced WL receiver replaces the conventional chip-matched filter with new filters that exploit the CS of the received signal through frequency shifting. The proposed WL receiver is shown to outperform the classical strictly linear (SL) receiver when the interfering users are (quasi-)synchronous with respect to the user of interest. High-powered interfering users, that may exist to support high data rates, increase the performance improvement delivered by the WL receiver. Moreover, it is shown that MAI can become proper, either identically or asymptotically, when users are asynchronous and equally powered. This is despite the fact that individual interfering signals are improper. Numerical results demonstrate that the WL receiver can outperform the SL receiver by 1-3 dB under the examined scenarios with current CDMA standards settings. In asynchronous or quasi-synchronous transmission modes, performance gain of the WL receiver degrades unless the number of high-powered active users remains small. An example for implementation of the WL receiver is proposed and compared with that of the SL receiver when minimum-shift keying modulation, a special case of OQPSK, is used. The implementation is based on a fractionally spaced equalizer whose taps are updated by an adaptive algorithm. It is shown that the proposed structure is capable of delivering the maximum signal-to-noise ratio predicted by theory.

In this paper, we focus on the joint estimation of the carrier frequency offset and statistical parameters of the multipath mobile channel. By modeling the multipath fading channel with a complex bandpass autoregressive (AR) model, we show how the estimates for the frequency offset, Doppler spread, and power profile of the multipath channel can be extracted from the estimated complex AR coefficients obtained via the expectation-maximization algorithm. A main advantage of the proposed joint estimator is that while it has a capability of performing equally well in all scattering environments, it can provide accurate estimates even in high-mobility channel conditions. We also demonstrate how the complexity of the estimator can be significantly reduced, while only slightly trading off performance, by applying the mean field approximation technique. Moreover, we derive a fully adaptive joint synchronization and channel-estimation scheme, as well as a novel Kalman-smoother-based frequency-error detector that can be used in feedback frequency-recovery schemes and is particularly well suited for fast-fading channel conditions. Finally, we revisit the Cramer-Rao lower bound analysis, and show how the Fisher information matrix can be conveniently computed in the presence of a frequency-selective Rayleigh fading channel

The asymmetric signal constellation (ASC) method to break isometry is analyzed in a superimposed symbol framework with a Kalman filter estimator (KF) / maximum-likelihood (ML) detector as the receiver. Direct application of the ASC method led to a bit error floor, which motivates the proposal of combining orthogonal spreading codes with ASC to solve this problem. The proposed scheme generalizes previously proposed ASC and pilot-assisted solutions in a systematic way and results in coherent detection schemes without set bit error floors and better performance

The highly stochastic nature of wireless environments makes it desirable to monitor link loss rates in wireless sensor networks. In a wireless sensor network, link loss monitoring is particularly supported by the data aggregation communication paradigm of network traffic: the data collecting node can infer link loss rates on all links in the network by exploiting whether packets from various sensors are received, and there is no need to actively inject probing packets for inference purposes. In this paper, we present a low complexity algorithmic framework for link loss monitoring based on the recent modeling and computational methodology of factor graphs. The proposed algorithm iteratively updates the estimates of link losses upon receiving (or detecting the loss of) recently sent packets by the sensors. The algorithm exhibits good performance and scalability, and can be easily adapted to different statistical models of networking scenarios. In particular, due to its low complexity, the algorithm is particularly suitable as a long-term monitoring facility.

A new method is proposed in this paper to design the time-domain equalizer for orthogonal frequency division multiplexing systems based on maximizing signal-to-interference-plus-noise ratio (SINR) at the output of the equalizer. The method called Maximum SINR Time-domain Equalization (MSINR-TEQ) is derived based on a new formulation of SINR. Computer simulation and analytical results show the performance of the MSINR-TEQ method and its superiority in comparison with the performance of the much-used method of channel impulse response shortening.

Density evolution analysis of low-density parity-check (LDPC) codes in memoryless channels is extended to the Gilbert-Elliott (GE) channel, which is a special case of a large class of channels with hidden Markov memory. In a procedure referred to as estimation decoding, the sum-product algorithm (SPA) is used to perform LDPC decoding jointly with channel-state detection. Density evolution results show (and simulation results confirm) that such decoders provide a significantly enlarged region of successful decoding within the GE parameter space, compared with decoders that do not exploit the channel memory. By considering a variety of ways in which a GE channel may be degraded, it is shown how knowledge of the decoding behavior at a single point of the GE parameter space may be extended to a larger region within the space, thereby mitigating the large complexity needed in using density evolution to explore the parameter space point-by-point. Using the GE channel as a straightforward example, we conclude that analysis of estimation decoding for LDPC codes is feasible in channels with memory, and that such analysis shows large potential gains.

The Bell-Labs layered space-time (BLAST) architecture is a simple and efficient multi-antenna coding structure that can achieve high spectral efficiency (Foschini, G. and Gans, M., Wireless Personal Commun., vol.6, p.311-35, 1998). Many BLAST detectors require more receiver antennas than transmitter antennas. We propose a novel turbo-processing BLAST detector based on a group detection strategy that can operate in systems with fewer receiver antennas than transmitter antennas. A maximum a posteriori (MAP) decision is made using a group of transmitted symbols and the remaining signal contribution is treated as interference. The interference is characterized as a non-zero mean colored noise source that is whitened before a decision is made. The proposed detector, the group MAP (GMAP) detector, is a generalization of both the MAP detector and the turbo-processing minimum mean squared error (MMSE) detector (Sellathurai, M. and Haykin, S., 2002; Abe, T. and Matsumoto, T., 2001). A novel grouping algorithm is proposed for the GMAP detector. Simulation is used to compare the GMAP detector with the MAP detector and MMSE detector.

A novel time domain equalizer (TEQ) design approach is proposed in this paper, based on maximizing the signal-to interference plus noise ratio (SINR). To increase the bandwidth efficiency of OFDM systems, the TEQ is used to mitigate the intersymbol interference (ISI) created by a channel with longer impulse response duration than that of the cyclic prefix (CP). The true ISI, ICI and noise parts of the signal at the output of the equalizer are formulated, based on the overall impulse response (OIR) (convolution of channel impulse response and equalizer impulse response). The SINR maximizing time-domain equalization (SMTE) method estimates the tap coefficients of the equalizer by maximizing the SINR of the signal at the output of the equalizer. Computer simulation and analytical results show that the performance of the SMTE method is superior to the performance of the much-used method of channel impulse response shortening (IRS).

In this paper, we study the effect of imperfect channel estimation (ICE) on the performance of M-ary phase shift keying (M-PSK) with maximum ratio combining (MRC) in generalized Rician fading channels. Using decision variable (DV)-based and signal-to-noise ratio (SNR)-based moment generating function (MGF) approaches, error and outage probability formulas, and SNR statistics for the M-PSK MRC receiver are derived, taking into account the effects of ICE and all relevant system and channel parameters. We analytically quantify the average SNR (ASNR) loss of M-PSK caused by ICE, and provided a unified MGF expression for ICE and different M's. In addition, we point out a major approximation for a popular approach used in the literature to evaluate the adverse effect of Gaussian weighting errors.

Many algorithms in signal processing and digital communications must deal with the problem of computing the probabilities of the hidden state variables given the observations, i.e., the inference problem, as well as with the problem of estimating the unknown model parameters. In this paper, we present an unified framework for approximate joint inference and estimation in the cases where an exact inference becomes computationally intractable. Specifically, approximate inference via variational minimization technique is obtained by operating a general message-passing algorithm in the distributed factor graph where the coupling between the multiple Markov chains is removed by minimizing the Kullback-Leibler distance between the original and the variational objective functions. Importantly, we demonstrate how this framework can be exploited in deriving reduced-complexity turbo receiver structures for coded single transmit antenna and space-time coded multiple transmit antenna systems over the multipath fading channels. Despite the significant reduction in complexity, the performance simulations showed that the derived turbo receivers are able to provide close to optimal performance.

We present a reduced-complexity approximate density evolution scheme that is particularly suitable for Markov-modulated channels, based on the semiGaussian approximation. We propose a design algorithm whose complexity is comparable to the memoryless case, assuming unlimited precomputation is allowed. We also present degree sequences representing some of the best known codes in the GE channel which were designed using this technique. This design tool can be easily extended to more complicated Markov-modulated channels

In orthogonal frequency division multiplexing (OFDM) system, a cyclic prefix (CP) as redundant information is appended to each OFDM symbol in order to mitigate the impact of intersymbol interference (ISI) on data transmission over multipath channels. On the one hand, the CP interval should not be shorter than the channel impulse response (CIR) length in order to eliminate the ISI completely and on the other hand, appending the CP decreases the bandwidth efficiency of the OFDM systems. In this paper a new TEQ design method based on maximizing signal-to-interference plus noise ratio (SINR) is proposed in order to equalize the received signal partially and eliminate a potion of the ISI when the appended CP interval is shorter than the CIR length. The true SINR for the OFDM system is formulated based on a relative delay, D, between the starting point and the effective point of overall impulse response (OIR) (convolution of the CIR and the equalizer impulse response). The proposed method called maximum SINR time-domain equalization (MSINR-TEQ) estimates the tap coefficients of the equalizer by maximizing the SINR at the output of the equalizer based on the value of the relative delay, D. The MSINR performance is evaluated for data transmission over multipath fading channels with additive white Gaussian noise. Computer simulations show that when the CIR interval is longer than the CP interval, the TEQ designed based on the MSINR method improves the performance of the OFDM system significantly in comparison with the system without an equalizer.

In multiplicative fading channels, joint channel estimation and data detection (CE/DD) schemes cannot differentiate among certain sequences of amplitude- and/or phase-modulated (AM/PM) symbols drawn from rotationally invariant signal constellations. This paper identifies these so-called isometric sequences as the main source of performance degradation, and introduces a unifying framework that effectively solves the problem by using asymmetric signal constellations (ASC) and a normalized innovations-based detector. The encompassing nature of the solution is clearly demonstrated by showing that seemingly unrelated previous results, such as training-based solutions, can be viewed as special cases of the modulation-based solution discussed here. A comprehensive analysis, supported by simulation studies, of the relationships among modulation schemes, isometry, and detection performance is provided. Results indicate that the proposed ASC solution offers excellent performance without incurring significant complexity or reducing the transmission rate. Furthermore, it is shown to be robust in various fading rates, and for different signal constellations.

Continuous phase modulation schemes, such as Gaussian minimum-shift keying (GMSK), are frequently used with limiter-discriminator (LD) detectors. This paper studies how the side information derived from the signal envelope can enhance the performance of a Viterbi algorithm (VA)-based receiver operating on the LD output of a GMSK scheme. By considering the joint probability density function of envelope and frequency, different approximations yield different novel metrics for VA, using the three-variables envelope and its derivative, and frequency error in different combinations. Simulation results confirm that such envelope-aided VA gives significant performance gains, and that envelope information complements the frequency information output by the LD detector in frequency-selective fading channels.

The authors propose an efficient moment generating function (MGF)-based method to evaluate the performance of generalized selection combining (GSC) over different fading channels. Employing a recently proposed method which is, however, only applicable to GSC diversity with independent and identically distributed branches, they derive a general MGF expression for the GSC output signal-to-noise ratio (SNR) for generalized fading channels, where the channel statistics in different diversity branches may be nonidentical or even distributed according to different distribution families. The resulting MGF expression is applicable to the analysis of the error probability, the outage probability, and the SNR statistics for GSC in a number of wireless communications scenarios with generalized fading. Numerical examples are presented to illustrate the application of the new analysis.

In this paper, we study the performance of a general linear coherent multiuser receiver with decision-directed channel estimation (DDCE) for doubly-selective Rician-fading CDMA channels. Employing the multivariate Gaussian approximation (MGA) and a decision variable-based moment generating function (DV-MGF) approach, both exact and low-complexity approximate bit error probability (BEP) formulas for a linear detector with genie-aided DDCE are provided. Furthermore, using a Markov chain steady-state analysis, a tight BEP approximation for non-ideal DDCE is provided taking into account the error propagation in the decision feedback. Some new findings are illustrated by simulation results.

In this paper, we study the asymptotic performance of generalized selection combining (GSC) over different fading channels for large average signal-to-noise ratio (ASNR). Employing a moment generating function (MGF) method and the polynomial approximation of the fading channel probability density function (pdf), we derive general asymptotic MGF expressions for the GSC output SNR over generalized independent fading channels. The diversity and coding gains for GSC over different fading channels are derived. Our analytical results reveal that the diversity gain of GSC is equivalent to that of maximum ratio combining (MRC), for different modulations and generalized fading channels. We also show that the difference in the coding gains for different modulations is manifested in terms of a modulation factor defined in this paper, and thus the performance gaps between different modulations can be analytically predicted. Asymptotic performance gap between GSC and MRC is also studied in terms of the coding gain. Numerical examples are presented to illustrate the application of the new results.

In this paper, we propose an efficient moment generating function (MGF)-based method to evaluate the performance of generalized selection combining (GSC) over different fading channels. Employing a recently proposed method which is, however, only applicable to GSC diversity with independent and identically distributed (i.i.d.) branches, we derive a MGF expression of the GSC output signal-to-noise ratio (SNR) for generalized fading channels, where the channel statistics in different diversity branches may be non-identical, or even distributed according to different distribution families. The resulting MGF expression is applicable to the analysis of the error probability, the outage probability, and the SNR statistics for GSC in a lot of wireless communications scenarios with generalized fading. Numerical examples are presented to illustrate the application of the new analysis.

The performance of differential amplitude and phase-shift keying (DAPSK) with post-detection diversity combining over general fading channels is of great theoretical interest and practical importance. Hence, a general and accurate performance analysis is very useful. In this paper, we analyze the distribution of the phase and amplitude decision variable at the DAPSK receiver output by using the moment generating function (MGF) approach. Exact results for the error probability of DAPSK on general Rician and Nakagami fading channels are derived, taking into account the effects of all system and fading channel parameters including correlated signal branches and correlated noise. By using our analytical results, the effects of the ring ratio and the amplitude decision boundary, etc., on the DAPSK performance are investigated, and some new findings are presented.

In this paper, we design decision-feedback differential detection (DF-DD) schemes for channels with phase noise. If the DF-DD feedback filter is properly optimized, a performance similar to that of more complex, some reported schemes based on multiple-symbol detection [K. Kiasaleh (December 1997)] and expectation maximization (EM) [E. Chiavaccini and G.M. Vitetta (December 2001)] can be achieved. However, it is also shown that an error floor is unavoidable. In contrast to previously proposed receivers for channels with phase noise, the DF-DD receiver can be made robust against unknown frequency offsets by introducing a simple linear constraint.

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

In this letter, we design decision-feedback differential detection (DF-DD) schemes for channels with phase noise. If the DF-DD feedback filter is properly optimized, a performance similar to that of a more complex scheme, recently reported by Chiavaccini and Vitetta, based on expectation maximization, can be achieved. However, it is also shown that an error floor is unavoidable for channels with phase noise. If a constraint is introduced, the DF-DD receiver can be made robust against unknown frequency offsets.

We give a tight approximation for the bit-error rate (BER) of decision-feedback differential detection (DF-DD). The influence of error propagation is modeled by a Markov chain. A simple state reduction method is proposed to limit computational complexity. Our results show that error propagation strongly depends on the chosen feedback filter. In particular, the popular assumption that error propagation increases BER by a factor of two is not always justified.

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

RicianAccurate performance analysis for linear receivers over frequency- and time-selective asynchronous code-division multiple-access Rician-fading channels is very useful and a general approach to this topic is very desirable. In this paper, by using a decision variable-based moment generating function approach, we provide a unified bit-error probability (BEP) analysis framework for different linear detectors with binary or quaternary differential phase-shift keying and postdetection combining over Rician-fading channels, taking into account the effects of the spreading code correlation, the system and fading-channel parameters, diversity combining, and branch correlation. To reduce the complexity of the exact BEP evaluation, we furthermore provide an approximate multivariate Gaussian assumption (MGA)-based method which entails a low complexity for BEP evaluation. Ideal and approximate linear minimum mean-squared error diversity receivers for correlated Rician-fading channels are proposed. Numerical results show that the phases of the line-of-sight (LOS) components of the desired user significantly affect the receiver performance over correlated multipath Rician channels, and this may be exploited to improve performance. Also, when the LOS components are affected by a significant Doppler shift, automatic frequency control is very useful in improving the receiver performance.

In this paper, noncoherent equalization is combined with multiple receive antennas. The resulting noncoherent space-time equalization (NSTE) schemes are analyzed and compared with the corresponding coherent receivers. In particular, noncoherent linear equalization (NLE), noncoherent decision-feedback equalization (NDFE), and noncoherent sequence estimation (NSE) are considered. For NLE and NDFE novel approximations for the signal-to-distortion ratio (SDR) are derived and verified by simulations. It is shown that NSTE can suppress interfering users and exploit diversity as efficiently as coherent STE. However, NSTE is more robust against channel phase variations than the combination of coherent STE and synchronization. Robust noncoherent recursive least squares (NC-RLS) algorithms, which compare favorably with the conventional RLS algorithm with additional carrier synchronization loop, are proposed for fast filter adaptation.

In this paper, the problem of adaptive MAP symbol detection in the uncoded transmission as well as the problem of adaptive APP demodulation in the coded transmission of data symbols over the frequency-selective Rayleigh fading channel are explored within the framework of the Bayesian expectation-maximization (BEM) algorithm. In particular, two novel versions of the BEM-based detection and demodulation algorithms are derived. In contrast to the earlier developments of BEM algorithms, the formulations derived in this paper lead to the computationally efficient algorithms which avoid the matrix inversions while using sequential processing over the time and trellis branch indexes. In addition, it is shown how the recursive versions of the BEM algorithms can be combined with the well-known forward-backward processing soft-input soft-output (SISO) algorithms resulting in adaptive SISOs with soft decision directed (SDD) channel estimators. An application of the proposed algorithms to the iterative "turbo-processing" receivers illustrates how these SDD channel estimators can efficiently exploit the extrinsic information obtained from the SISO decoder in order to enhance their estimation accuracy.

The central issue to the error probability analysis of M-phase signaling is to determine the phase distribution of the received signal. In this paper, we take a novel approach by formulating the phase distribution in terms of joint moment generating functions (MGFs) of the real and imaginary parts of the decision variable at the receiver output. We further derive fast convergent formulas by using the two-dimensional (2-D) inverse Laplace transform enabling us to accurately evaluate the phase distribution. The new technique is very general, taking into account the effects of arbitrary diversity order, symbol alphabet size M, and arbitrary diversity branch correlation. Numerical results are also presented for illustration.

The problem of adaptive equalization of the time-varying frequency-selective channel is studied by using the adaptive Baum-Welch algorithm. In particular, blind LMS and blind RLS channel estimators are derived and they are combined with the well-known forward-backward processing SISO algorithm for known channels. An application of the proposed algorithms to the iterative "turbo-processing" receivers illustrated how the blind LMS and blind RLS estimators can efficiently utilize the extrinsic information obtained from the decoder SISO in order to enhance their estimation accuracy.

In this paper, noncoherent equalization is combined with multiple receive antennas. The resulting noncoherent space-time equalization (NSTE) schemes are analyzed and compared with the corresponding coherent receivers. In particular, noncoherent linear equalization (NLE) and noncoherent decision-feedback equalization (NDFE) are considered. For both NLE and NDFE novel approximations for the signal-to-distortion ratio (SDR) are given and verified by simulations. It is shown that NSTE can suppress interfering users and exploit diversity as effectively as coherent STE. However, NSTE is more robust against channel phase variations than coherent STE combined with synchronization.

Joint transmit beamforming, power control and the MMSE receiver are proposed for downlink channels of CDMA communication systems. Variability of the total transmit power while satisfying each user's quality of service is studied. We show that the total transmit power has a significant variation when we consider the combination of MMSE receiver and power control. When transmit beamforming is added, such variation is reduced significantly and great transmit power saving is achieved through the proposed scheme. The signature diversity concept is revealed for joint transmit beamforming and the MMSE receiver. An optimum MMSE, transmit beamforming and adaptive frequency hopping scheme is proposed to maximize the benefits of the MMSE receiver and transmit beamforming. Two sub-optimal algorithms are proposed to solve the optimization problem with reduced computational requirements.

A synchronized per survivor processing (PSP) maximum likelihood sequence detection (MLSD) receiver is presented for a fast frequency-selective Rayleigh fading channel and large carrier frequency offset. It is shown that, by incorporating the synchronization parameters (the timing error, carrier frequency and phase offsets) into the channel-impulse response (CIR) and modifying the resulting state-space model by a differential approach, the time-varying carrier frequency offset can be effectively tracked using a simple least mean square (LMS) estimator. New criteria are proposed based on the smoothness of the estimated channel derivatives. New criteria are proposed based on this fact that, for smoothly time-varying CIR and frequency offset, the magnitude of the CIR time derivative compared with the magnitude of CIR should be very small. It is illustrated that the new criteria and the conventional mean square error (MSE) are complementary.

A new double-filter receiver for spread spectrum wireless systems is presented. The receiver exploits the inherent diversity due to the small delay difference between the multipaths which may not be exploited by the conventional RAKE receiver. The bit error rate performances of both the coherent and the noncoherent detectors are analyzed and compared with the ideal RAKE receiver and the matched filter bound. We also examine the best and the worst cases of a three-path fading channel for the proposed receiver. Optimum pulse shapes under various channel conditions are designed. Implementation issues in code-division multiple access systems are discussed. The numerical results show that the proposed receiver achieves significant gains for a given spreading factor under a complexity constraint.

This paper discusses the performance of communication systems using binary coherent and differential phase-shift keyed (PSK) modulation, in correlated Rician fading channels with diversity reception. The presence of multiple Rician-faded cochannel users, which may have arbitrary and nonidentical parameters, is modeled exactly. Exact bit error probability (BEP) expressions are derived via the moment generating functions (MGFs) of the relevant decision statistics, which are obtained through coherent detection with maximum ratio combining for coherent PSK modulation, and differential detection with equal gain combining (EGC) for differential modulation. Evaluating the exact expressions requires a complexity that is exponential in the number of interferers. To avoid this potentially time-consuming operation, we derive two low-complexity approximate methods each for coherent and differential modulation formats, which are more accurate than the traditional Gaussian approximation approach. Two new and interesting results of this analysis are: (1) unlike in the case of Rayleigh fading channels, increasing correlation between diversity branches may lead to better performance in Rician fading channels and (2) the phase distribution of the line-of-sight or static fading components of the desired user has a significant influence on the BEP performance in correlated diversity channels.

In this article, block and convolutional coding for Gaussian minimum shift keying (GMSK) in additive white Gaussian noise (AWGN) channels is investigated. The performance improvement that can be obtained without an increase in bandwidth is found for block and convolutional codes with various block lengths and constraint lengths, respectively, when a simple suboptimal demodulation scheme is used. For a fixed system transmission bandwidth, the tradeoff between the percentage of bandwidth to use for coding and the percentage to use for modulation is examined and optimized for various values of bandwidth.

We study the interference effects in a multirate DS-code-division multiple-access (CDMA) system. Optimum chip waveform selection with arbitrary shapes is analyzed using a time domain approach. The problem is posed as an interference minimization problem under energy and time-bandwidth constraints and prolate spheroidal wave functions are used to arrive at a solution. Various factors affecting the interference are identified and the trade-off between competing factors is analyzed. The effect of the interchip interference on the optimum chip waveform design is also quantified under a practical bandwidth constraint. We study the benefits of employing two different chip waveforms for two classes of users. We compare the performance of systems employing two different chip waveforms with that of a single-chip waveform system such as IS-95. We show that when the power imbalance is large, it is advantageous to employ two different chip waveforms for different classes of users.

The idea of adaptive state allocation (ASA) algorithm is used in this paper to substantially reduce the computational complexity of the maximum-likelihood sequence detection and estimation (MLSD/MLSDE) receiver without a significant degradation in its performance. In the ASA algorithm, the total number of states assigned to the trellis and the number of states selected from the entire set are changed adaptively based on the short-term power of the channel impulse response (CIR) or its estimate. The ASA algorithm is a combination of two methods: adaptive threshold (AT) and adaptive state partitioning (AP). In the AT method, a threshold value is formulated based on the probability of removing the correct state in the trellis diagram. At each time, only the paths whose costs are less than the minimum cost (corresponding to the best survivor path) plus the threshold value are retained and are extended to the next trellis stage. The AT method significantly reduces the computational complexity of the regular MLSDE mostly at high signal-to-noise ratio (SNR) with a negligible loss in performance. Simulation results for fading channels show that the AT method typically selects one trellis state (the minimum possible number of states) at high SNRs. In the AP method, the branch metrics are fused and diffused adaptively by using the Kullback-Leibler (KL) distance metric invoked for quantifying the differences between the probability density functions of the correct and incorrect branch metrics in the trellis. The adaptation is done such that the channel coefficients with short-term power less than a threshold are assumed to be zero in computing the branch metrics. The AP method decreases the computational complexity of the regular MLSDE at low SNRs.

In this paper, the problem of carrier phase recovery of linearly modulated signals in the presence of unknown data symbols is studied within the expectation-maximization (EM) framework using two different approaches. First, an iterative joint maximum likelihood (ML) phase estimator and data detector is derived using conditional maximization steps. Secondly, an iterative joint ML nondata-aided (NDA) phase and power spectral density estimator is derived for uncoded and coded transmitted signals. The main difference between the approaches is that the first estimator uses hard decisions whereas the second estimator uses soft decisions about the data symbols at each iteration. Furthermore, the mean-squared performance of the second estimator is approximated by the inverse of the empirical observed Fisher information. Finally, it is shown that the recursive approximations of both estimators lead to the Costas type of loops introduced earlier in the literature.

A new double-filter receiver for spread spectrum (SS) wireless systems is presented in this paper. The receiver exploits the inherent diversity due to the small delay difference between the multipaths which may not be exploited by the conventional Rake receiver. The bit error rate (BER) performances of both the coherent and the non-coherent detectors are analyzed and compared with the ideal Rake receiver and the matched filter bound. We also examine the best and the worst cases of a three-path fading channel for the proposed receiver. Optimum pulse shapes under various channel conditions are designed, Implementation issues in CDMA systems are discussed. The numerical results show that the proposed receiver achieves significant gains for a given spreading factor under a complexity constraint.

This paper presents a maximum likelihood sequence detection (MLSD) receiver which performs joint data detection, channel equalization and synchronization over a fast frequency-selective Rayleigh fading channel. An optimal per-survivor processing (PSP) technique is employed which is a combination of statistical channel modeling and differential Kalman filter. It is shown that by incorporating the synchronization parameters into the channel impulse response and modification of the resulting state space model by a differential approach, frequency synchronization can be achieved by a simple adaptive algorithm in addition to data detection and channel estimation. It is also shown that by applying the so called approach, the differential Kalman filter could be simplified to a simple LMS estimator without any considerable lack in performance.

This paper studies the benefits of combining beamforming and power control in the downlink channel of a CDMA communication system employing a variable length orthogonal spreading code (OLSC). It is demonstrated that the high data users cause significant interference to the low data users if we do not employ beamforming. Furthermore, if we perform beamforming for both types of users, most of the gain we achieve is due to the high data users if the total power of the high data users is much higher than that of the low rate users. Thus we may reduce the computational requirement significantly if we perform beamforming for the high data users only with a small increase in total power.

Oversampled blind maximum likelihood sequence detection and estimation (MLSDE) is proposed to improve the performance and robustness of the MLSDE receiver. The performance of the MLSDE receiver depends firmly on the assumed channel model and available knowledge about the channel parameters at the receiver. A deterministic channel model is used to enhance the robustness of the receiver in a dynamic environment such as mobile communications. Oversampled joint channel estimation and data detection is proposed to improve the receiver performance which approaches the performance of the receiver knowing the channel parameters completely. The estimation part of the oversampled MLSDE leads to an RLS-type algorithm for additive colored Gaussian noise which becomes the noise model in the oversampling method. Bandwidth efficiency is achieved by using blind channel estimation (i.e. no training sequence) and two-level differentially encoded quadrature phase shift keying modulation scheme with 16 points constellation (16-DQPSK).

The conventional decision feedback equalizer (DFE) is a common solution to the frequency selective multipath propagation problem that appears in high data rate radio communications because of its simplicity and good performance. However, when limiter-discriminator (LD) is used for detection of GMSK signals, the global system has a nonlinear characteristic and the conventional DFE yield poor performance even for moderate delay-spread (DS) channels. An envelope-aided DFE is proposed that extends the use of GMSK with LD to high DS channels at a minimum increase in complexity and cost. The performance has been evaluated for both fractionally-spaced (FS) and T-spaced (TS) DFEs, using the exponential power-delay profile channel model.

Maximum likelihood sequence detection (MLSD) using the Viterbi algorithm (VA) is a widely employed detection technique for both coherent and non-coherent detection of continuous phase modulation (CPM) signals due to the inherently nonlinear behaviour of the digital channel. In particular, its application to limiter-discriminator (LD) demodulation schemes has received wide attention in the last years. Somehow, most of the VA proposed, recognize but neglect the effect of the non-Gaussian frequency noise at the output of the LD. As we show in this work this question is closely related to the signal envelope behaviour and hence becomes more important in the presence of frequency selective fading. Two simple schemes that provide a fair solution to that problem are proposed an evaluated in this contribution.

Optimum chip waveform selection with arbitrary shape is analyzed and a time domain approach is employed. The problem is posed as an interference minimization problem under energy and time-bandwidth constraints and prolate spheroidal wave functions are used to arrive at a solution. We propose to employ two chip waveforms for two classes of users. A 3 dB gain is possible for one class of users without penalizing another class of users. Various factors affecting the interference are analyzed. The tradeoff between competing factors is quantified. The effect of the interchip interference on the optimum chip waveform design is also quantified under a practical bandwidth constraint.

This paper describes a new interpretation of the maximum-likelihood sequence detector metric for a linearly modulated signal and an unknown time-varying, dispersive, Rayleigh fading channel. The metric, which involves the channel and noise autocovariances, is transformed into the intuitive Mahalanobis distance (squared Euclidean distance in white noise) between the observations and a reference estimated from them. A novel estimator, called the autocovariance preserving estimator, is obtained that trades off increased estimation bias for reduced sequence-error probability.

By using the innovations process, this paper provides a unification and extension of the existing maximum a posteriori (MAP) detectors (MAPDs). The practically important topics of linear modulations, time-varying frequency-selective channels, differential phase detection, and fractional sampling are accounted for. The MAPDs are derived under different conditions of optimality and a priori knowledge as follows: when the MAP criterion is applied to the constellation mapper's input bits or output symbols, when all observations or only a fixed number of future observations (i.e. fixed-lag MAPDs) from a transmission are available, when the time-varying channel impulse response is perfectly known, and when only the Gaussian-distributed channel's mean and autocovariance and the noise variance are known. As these quantities are actually unknown, their estimation in the context of MAP detection is also discussed. The MAPDs are characterized through simulation and a novel, unified analysis. Although MAPDs are less suited to hardware implementation than the traditional maximum-likelihood sequence detectors, the MAPDs can accept nonuniform a priori bit or symbol probabilities and provide soft outputs. In this way, the MAPDs are well suited to iterative decoding, and so they will become increasingly integral to high-performance receiver designs.

We focus on applications of low-rate Gallager (1963) (low-density parity-check) codes in code-division multiple-access schemes. The codes that we present here achieve good performance with relatively short frame-lengths in additive white Gaussian noise channels and, perhaps more importantly, in fading channels. These codes can be decoded with low complexity by using iterative decoding procedures. We present a construction that yields good short frame-length Gallager codes. Bounds on the frame-error probability for a maximum-likelihood decoder are obtained.

We focus our attention on Gallager codes with parameters compatible with the IS-95 cellular radio standard. We discuss low complexity software and hardware implementations of an iterative decoder for {N,-,3} Gallager codes. We estimate that by using Gallager codes, a factor of five improvement in the code-division multiple-access system capacity relative to an uncoded system can be achieved, equivalent to a factor of two improvement relative to state-of-the art orthogonal convolutional codes. Simulation results demonstrate the good performance of short-frame Gallager codes in the additive white Gaussian noise and certain fading channels.

This paper develops a threshold method called adaptive T-algorithm to reduce the number of states in the maximum likelihood sequence detection and estimation (MLSD/MLSDE) receivers. This algorithm removes the states whose costs are larger than the minimum cost (the cost of the best survivor path) plus a threshold at each time. The threshold value is formulated based on the probability of removing the correct state in the trellis diagram and it is a function of short-term power of the channel impulse response and the variance of the additive white Gaussian noise. Simulation results for frequency flat and selective fading channels show that the adaptive T-algorithm greatly reduces the computational complexity of the MLSD/MLSDE receivers especially at high SNR with negligible loss in their performances.

The theory of adaptive sequence detection incorporating estimation of channel and related parameters is studied in the context of maximum-likelihood (ML) principles in a general framework based on the expectation and maximization (EM) algorithm. A generalized ML sequence detection and estimation (GMLSDE) criterion is derived based on the EM approach, and it is shown how the per-survivor processing and per-branch processing methods emerge naturally from GMLSDE. GMLSDE is developed into a real time detection/estimation algorithm using the online EM algorithm with coupling between estimation and detection. By utilizing Titterington's (1984) stochastic approximation approach, different adaptive ML sequence detection and estimation (MLSDE) algorithms are formulated in a unified manner for different channel models and for different amounts of channel knowledge available at the receiver. Computer simulation results are presented for differentially encoded quadrature phase-shift keying in frequency flat and selective fading channels, and comparisons are made among the performances of the various adaptive MLSDE algorithms derived earlier.

Recursive (online) expectation-maximization (EM) algorithm along with stochastic approximation is employed in this paper to estimate unknown time-invariant/variant parameters. The impulse response of a linear system (channel) is modeled as an unknown deterministic vector/process and as a Gaussian vector/process with unknown stochastic characteristics. Using these models which are embedded in white or colored Gaussian noise, different types of recursive least squares (RLS), Kalman filtering and smoothing and combined RLS and Kalman-type algorithms are derived directly from the recursive EM algorithm. The estimation of unknown parameters also generates new recursive algorithms for situations, such as additive colored noise modeled by an autoregressive process. The recursive EM algorithm is shown as a powerful tool which unifies the derivations of many adaptive estimation methods.

It is known that spread-spectrum (SS) communications in general, and code-division multiple access (CDMA) in particular, gain certain advantages in performance, if powerful low-rate error-correcting codes are used for error-protection in such systems. We propose an innovative coding scheme for SS systems based on Gallager (low-density parity-check) codes that can be iteratively decoded with relatively low complexity. Consequently, this scheme is readily implementable in both base station and subscriber side receivers. We focus our attention on Gallager codes with parameters compatible with the IS-95 cellular radio standard. We discuss soft- and hardware implementations of iterative decoding for Gallager codes. We estimate that by using Gallager codes, a factor of five improvement in CDMA cell capacity relative to the uncoded system can be achieved, equivalent to a factor of two improvement relative to the state-of-the art orthogonal convolutional codes.

Joint data and channel estimation for mobile communication receivers can be realized by employing a Viterbi detector along with channel estimators which estimate the channel impulse response. The behavior of the channel estimator has a strong impact on the overall error rate performance of the receiver. Kalman filtering is an optimum channel estimation technique which can lead to significant improvement in the receiver bit error rate (BER) performance. However, a Kalman filter is a complex algorithm and is sensitive to roundoff errors. Square-root implementation methods are required for robustness against numerical errors. Real-time computation of the Kalman estimator in a mobile communication receiver calls for parallel and pipelined structures to take advantage of the inherent parallelism in the algorithm. In this paper different implementation methods are considered for measurement update and time update equations of the Kalman filter. The unit-lower-triangular-diagonal (LD) correction algorithm is used for the time update equations, and systolic array structures are proposed for its implementation. For the overall implementation of joint data and channel estimation, parallel structures are proposed to perform both the Viterbi algorithm and channel estimation. Simulation results show the numerical stability of different implementation techniques and the number of bits required in the digital computations with different estimators.

A new transceiver for data transmission over multipath fading channels employing precoding and differential detection is investigated. This precoding scheme effectively functions as a decision feedback equalizer (DFE) for differentially coherent demodulation. The main advantage of the proposed scheme over the conventional DFE is its ability to compensate for fast channel phase variations.

Modern data acquisition systems record large volumes of data which are often not suitable for direct computer processing-a first stage of preprocessing (or data "editing") is usually needed. In earlier work G. Noriega et al. (1992) the authors have developed an algorithm for multichannel data preprocessing, based on Kalman filtering and suitable for real-time geophysical data collection applications. The present work presents results of further investigations in the area of adaptive methods for estimation of noise covariance matrices Q and R, within the time-variant, fixed-lag Kalman filtering framework of the original problem. An algorithm is developed whereby asymptotically normal, unbiased, and consistent estimates are produced based on the correlation-innovations method introduced by Mehra (1970). This provides for direct estimation of R, and leads to a set of (n.m/sup 2/) equations, not linearly independent, from which an appropriate subset must be selected to achieve estimation of up to (n.m) unknowns in Q. For the model considered (n=m.M, with M=4 the single-channel system order, and n and m the state and measurement vector dimensions respectively), an explicit algorithm has been developed far estimation of the (m.m) unknowns in Q, based on a least squares fit of a subset of the equations available. A new approach is also introduced to ensure positive-definiteness of the covariance matrices. Since the time variant nature of the model prevents direct application of the adaptive algorithm, a parallel implementation is proposed. A first processor implements the time variant Kalman filter, using estimates of Q and R updated every N/sub s/ samples. A second processor computes these estimates, operating on the output of a steady state Kalman filter based on a simplified model, in which data editing features, responsible for rendering the model time variant, have been removed. A spike/step removal filter, and a Riccati equation solver are also implemented by this second processor. Computational requirements are analyzed and compared against those of other approaches. Simulations demonstrate the performance of the method proposed, and show it to be superior to other alternatives. An example showing application to real geophysical data is also presented.

The use of head movements in control applications leaves the hands free for other tasks and utilizes the mobility of the head to acquire and track targets over a wide field of view. We present the results of applying a Kalman filter to generate prediction estimates for tracking head positions. A simple kinematics approach based on the assumption of a piecewise constant acceleration process is suggested and is shown to track head positions with an rms error under 2 degrees for head movements with accelerations smaller than 3000 degrees /s. To account for the wide range of head dynamic characteristics, an adaptive approach with input estimation is developed. The performance of the Kalman filter is compared to that based on a simple polynomial predictor.

A modified multicarrier (MC) direct-sequence code-division multiple-access (DS-CDMA) system has been proposed for use over slow multipath fading channels with frequency selectivity in the reverse link transmission of a cellular network. Instead of transmitting data substreams uniformly through subchannels, data substreams hop over subchannels with the hopping patterns adaptively adjusted to the channel fading characteristics. The problem of determining the optimal hopping pattern is formulated as a multiobjective optimization problem, for which an efficient algorithm, based on the water-filling (WF) principle, is designed to solve the problem practically. Simulation results show that the performance in terms of the average bit-error probability (BEP) (over all users) is better than that of single carrier RAKE receiver systems, conventional MC CDMA systems applying moderate error protection, or diversity systems with different combining techniques.

A nonlinear decision-based adaptive equalizer compatible with differentially coherent phase shift keying (PSK) is proposed for frequency-selective fading channels. This equalization scheme is appropriate whenever conventional equalizers are not capable of tracking phase variations in selective fading channels. The received signal is first converted to a baseband signal and then sent through a differential detector. A nonlinear processor before the equalizer generates the needed nonlinear terms that are weighted and summed in the equalizer. Nonlinear intersymbol interference at the output of the differential detector is dealt with by minimizing an error signal between the output of the equalizer and the detected data. The adaptation algorithm can be any algorithm currently used for conventional equalizers. Our simulation results confirm that for channels with spectral nulls, equalization is achieved successfully with the proposed scheme, whereas, linear equalizers, either with coherent or noncoherent detection, fail.

A modified multi-carrier (MC) DS-CDMA system has been proposed for use over slow multi-path fading channels with frequency selectivity in the reverse link transmission of the cellular network. Instead of transmitting data sub-streams uniformly through sub-channels, data sub-streams hop over sub-channels with the hopping patterns adaptively adjusted to the channel fading characteristics. The problem of determining the optimal hopping pattern is formulated as a multi-objective optimization problem, for which an efficient algorithm is designed to solve the problem practically. Simulation results show that the performance in terms of the average system bit error probability (BER) is better than that of a single carrier RAKE system, conventional MC CDMA systems applying moderate error protection and diversity systems with different combining techniques.

We employ a fractionally spaced decision feedback equalizer for indoor fading channels and give the relevant analytical and simulated performance results in terms of Doppler frequency. An upper limit is determined for the channel variations which can be tracked by the equalizer. Also, the effect of error propagation on the performance is evaluated. Finally, a nonlinear decision-based equalizer compatible with differentially coherent PSK is proposed. This equalization scheme is appropriate whenever conventional equalizers are not able to track channel phase variations. Our simulation results indicate that, for channels with spectral nulls, equalization will be achieved successfully with the proposed scheme, whereas linear equalizers, either with coherent or non-coherent detection, fail.

This paper presents a general framework for computing the asymptotic error probability (i.e., at high average SNRs) of M-ary and binary signaling schemes over Rician and Rayleigh fading diversity channels. A general theorem (Theorem 1) relates the asymptotic error rate of multipath and multichannel receivers (over AWGN, ISI free channels) to the multidimensional integral of the conditional error probability. Two other theorems are presented for the particular cases where the conditional error probability is a function of the sum of received SNRs (Theorem 2) or received amplitudes (Theorem 3). Theorems 2 and 3 are related for linear coherent systems, and closed form expressions are obtained for equal gain combining systems. Detection structures for typical diversity schemes (coherent/noncoherent maximal ratio and equal gain combining, and quadratic noncoherent combining) are considered. We analyze the asymptotic error rates of some M-ary signaling schemes (MPSK/MPAM with Kth order diversity and orthogonal signals with K=1 and with coherent and noncoherent detection). Binary signaling is also considered in our study.

Considers a code division multiple access (CDMA) cellular network and proposes sub-optimal multiuser detectors which exploit a type of diversity inherent in the system and are based on the processing of signals received at multiple base stations. The authors investigate the performance of conventional matched-filter, linear, and decision-based detection schemes, using this diversity scheme, for both synchronous and asynchronous systems. The detection of user signals is based on tracking the signals at several base stations. The optimal detector would operate on all the signals received at all the base stations but would have a high degree of complexity. The authors discuss the case where the detection of a given signal is based on received signals at a small subset of base stations. They show that with judicious selection of this smaller set of base stations, good performance can be obtained without much increase in complexity.>

This paper deals with the use of the innovations approach for developing a general and practical MLSE algorithms for signals transmitted over Rayleigh fading channels. The proposed MLSE receiver can be implemented by a bank of FIR time-invariant filters followed by a Viterbi processor and is applicable to any practically modulated signal over either frequency-nonselective or selective, fast or slowly fading channels. Simulation results are presented that demonstrate the superiority of the innovations-based receiver over differential detection in the presence of fast fading. To further improve the error performance, the derived MLSE receiver is combined with diversity reception. The simulation also shows that the diversity technique results in a significant improvement of the error performance. A unified interpretation of MLSE of signals transmitted over both Gaussian noise channels in the presence of ISI and Rayleigh fading channels is obtained by using the innovations approach.>

Indoor wireless communication in the 20-60 GHz band requires schemes that are biased toward power efficiency rather than bandwidth efficiency and use simple, robust detectors. Using the two-wave Rayleigh-fading channel as a model for the indoor wireless channel, the optimum detector structure is derived, and a simple suboptimum detector is developed. This suboptimum detector is a straightforward extension of the optimum detector for the single-wave Rayleigh-fading channel. The suboptimum detector is optimum for the channel when the delay of the second wave is known, and whenever the equal energy signals have a normalized complex autocorrelation of either zero or unity at that delay. The performance of this suboptimum detector on the two-wave Rayleigh-fading channel with known delay is studied. An exact expression for the probability of error is derived for uniformly orthogonal, equal energy, binary signals. This expression, which is in terms of the average signal-to-noise ratios in the waves and the complex autocorrelation of the signals, explicitly exhibits the presence of a diversity-like effect when the delay between the waves is non zero, and is an approximation for the probability of error when the complex cross-correlation is small. When the suboptimum detector is used, wideband signals, such as chirp signals and variants, perform well on this channel, enhancing the diversity-like effect. Such signals are also shown to make the suboptimum detector nearly optimal in structure.>

In this paper, the problem of signal design for continuous phase modulation is examined. Using the performance measures of effective bandwidth and minimum distance, "optimal" signal shapes are calculated for various receiver observation intervals for full and partial response signalling. For the partial response case, the optimization could only be done for receiver observation interval of one symbol due to the difficulty of the optimization. Therefore, a family of signals based on previously calculated optimal signals is introduced. The tradeoffs that result between bandwidth and bit error rate are then compared as a function of the receiver observation interval and as a function of the memory length of the signalling scheme. Then, the signals introduced in this paper are compared to well known signals in terms of their effective bandwidth-minimum distance tradeoffs, power spectra and percent-in-band-power. The signals obtained by the optimization process are found to have good spectral properties in relation to well known signals.>

The problem of practical realization of the optimal fixed-delay symbol-by-symbol detection algorithm, which is optimum in the sense of minimizing the symbol error probability, given a delay constraint D, is investigated. A fully-parallel structure is developed, and through systematic reformulations of the algorithm, the computational requirements are reduced considerably. In addition, the problems associated with a large dynamic range such as overflow (or underflow) are (practically) removed. A number of approximations are applied to this simplified parallel symbol (SPS) detector that lead to the derivation of suboptimal detectors. One such suboptimal detector is shown to be the same as the minimum-metric Viterbi detector. A brief comparison of the SPS detector and the Viterbi detector shows that the former has a slightly better performance at low values of signal-to-noise ratio (SNR) and the latter performs a smaller number of computations (particularly) at higher values of SNR; otherwise, the two detectors are comparable in performance and complexity.>

A matched code is a convolutional code chosen in such a way that when combined with modulation with memory the resulting receiver for the coded modulation has the smallest possible number of states. In the paper, the matched coding technique is applied to coded tamed frequency modulation (TFM) schemes and a formal procedure is developed to find the best combination of a code and a modulation. The optimization criterion is the maximum free Euclidean distance for a given code rate and a given number of states in the Viterbi receiver used for the coded modulation. A search for the best codes was carried out for code rates 1/2 and 2/3, and for receivers with up to 256 and 64 states, respectively. Good coding gains (more than 7 dB for rate 1/2) were achieved. Some of the best codes were catastrophic, yet the coded modulation was not. The codes obtained using the matched coding approach were in many cases better than those obtained using traditional optimization techniques.>

Multidimensional constellation shaping with a family of regions called truncated polydiscs is studied. This family achieves maximum shaping gain for a given two-dimensional peak-to-average energy ratio or a given two-dimensional constellation expansion ratio. An efficient algorithm for mapping data words to constellation points is described that requires O(N log N) arithmetic operations and O(N/sup 2/) lookup table space. Truncated polydisc shaping can easily be incorporated into standard coded modulation schemes.>

Communication over the additive white Gaussian channel, subject to a discrete phase ambiguity at the receiver, is considered. When this phase ambiguity is considered as a discretely distributed random variable, the channel is termed the acoherent additive white Gaussian (AAWG) channel. It is shown that the optimum decoder for the AAWG channel is not practically implementable and a suboptimum decoder that is asymptotically optimum at high signal-to-noise ratio is developed. The low signal-to-noise ratio performance of the suboptimum decoder is also examined. By considering the structural possibilities for this decoder, it is shown that one implementation leads to rotationally invariant codes. Other implementations, based on a rotationally disjoint property, lead to a variety of solutions that offer a general framework for communication over this channel. Some of these solutions use a parallel receiver configuration. Various solutions are compared in terms of implementation and performance.>

Variable-rate data transmission schemes in which constellation points are selected according to a nonuniform probability distribution are studied. When the criterion is one of minimizing the average transmitted energy for a given average bit rate, the best possible distribution with which to select constellations points is a Maxwell-Boltzmann distribution. In principle, when constellation points are selected according to a Maxwell-Boltzmann distribution, the ultimate shaping gain ( pi e/6 or 1.53 dB) can be achieved in any dimension. Nonuniform signaling schemes can be designed by mapping simple variable-length prefix codes onto the constellation. Using the Huffman procedure, prefix codes can be designed that approach the optimal performance. These schemes provide a fixed-rate primary channel and a variable-rate secondary channel, and are easily incorporated into standard lattice-type coded modulation schemes.>

This work analyzes the performances of Bessel, Gaussian, Butterworth, and Chebyshev (0.1-dB ripple) filters for synchronous baseband digital transmission. Numerical results showing the effects of system parameters such as signal rate, filter bandwidth, filter order, and pulse duty-cycle are presented. For rectangular inputs, linear phase filters perform better than those with nonlinear phase, from the viewpoint of the Nyquist 1 criterion. In terms of the Nyquist 2 criterion, linear phase filters perform better when the input duty-cycle is unity. For lower duty-cycles, there are symbol rate ranges over which nonlinear phase filters perform better. From the viewpoint of symbol time synchronization, the performances of the two types of filter are essentially the same. Linear phase filters are more robust to sampling clock jitter than nonlinear ones when the symbol rate is higher than the bandwidth. Furthermore, it is shown that for linear phase filters it is possible to increase the transmitting rate while keeping the filter bandwidth constant and with only a minor increase in degradation, by using low duty-cycle inputs.>

It is shown that there is a close relation between known noncoherent minimum shift keying (MSK) demodulation structures, such as envelope and differential receivers, and schemes derived from the noncoherent maximum-likelihood block estimation (N-MLBE) principle. When the observation interval is increased, the performance of MSK with N-MLBE tends to that of binary coherently detected orthogonal binary frequency shift keying. A new demodulation strategy, reduced block noncoherent estimation (RBNE), is introduced and shown to improve the performance of noncoherent MSK, beyond that of coherently detected orthogonal FSK. When RBNE is used with MSK and the observation interval is increased, the performance approaches that of antipodal signaling. The key feature of all these structures is multisymbol noncoherent processing with exploitation of the MSK inherent coding properties induced by its phase continuity. The use of binary block codes for MSK with N-MLBE is considered. It is shown that simple binary block codes with low bandwidth expansion that exploit the inherent MSK memory can give significant gains.>

This work considers noncoherently orthogonal signaling with full response digital phase modulation and focuses on the phase function shaping problem. A criterion for the phase function that ensures noncoherent orthogonality of the modulated signal over one symbol interval is introduced. Furthermore, a new family of phase modulated signals is presented. This new orthogonal modulation format lacks the well-known spectral lines of noncoherently orthogonal FSK and hence uses the power efficiently to convey information.>

An algorithm for automatic preprocessing of multiple data sequences in real-time is proposed. Based on a fixed-lag Kalman filter approach, it models the signal using a state vector that consists of the signal, its first three differences, and a special variable used to implement data editing functions. The smoothed output lessens some of the noise problems encountered in practice, and the method provides mechanisms for identification and removal of spikes, identification and measurement of steps, and filling of data gaps. Two versions of the algorithm are developed, one based on the conventional form of the Kalman filter, and one using a sequential processing technique. The computational requirements of each are analyzed and compared. An alternate approach for fixed-lag smoothing based on a one-step forward predictor and an L-step backward sweep, with L being the fixed lag, is also considered. It is shown that despite the greater complexity of the model used in the algorithms proposed, for L>30 the computational requirements are very similar to those of the alternate method.>

Tables of good ternary and quaternary codes are presented, and they are used in the construction of dense sphere packings. Results include (1) tables of the best ternary and quaternary constacyclic codes (including cyclic codes) up to block length 50; (2) a class of optimal (n, 2) codes over GF(q); (3) the (u+v+w mod 2u+v mod u) construction, a new ternary code construction technique that can be used to construct the ternary Reed-Muller codes (and others); and (4) tables of linear ternary and quaternary codes obtained by modifying and combining various codes here and in the literature. Packings are generated in even dimensions up to 100 using these codes and a sphere-packing construction. In dimensions 36 and 60, new record densities appear to have been achieved.>

The structure and performance of the maximum likelihood (ML) estimator of slowly varying time delays when the received signals are contaminated by additive noise containing a strongly directional component, due to the presence of a fixed, localized source of interference in the acoustic environment is investigated. The ML estimator is obtained by maximizing the output of the log-likelihood processor. The latter is shown to consist of a slowly varying noise canceler followed by a minimum mean square error estimator of the source signal and a correlator. Closed-form expressions are obtained for the Cramer-Rao lower bound (CRLB) on the error covariance matrix of time-varying delay estimators. The effects of directional interference on the CRLB are investigated numerically for a simplified configuration consisting of two sensors and linearly varying time delays.>

The authors consider trellis-coded M-ary phase shift keying (MPSK) when used with differentially coherent demodulation over a carrier-phase-noise dominated channel. A tight upper-bound to the probability of error is introduced. This bound shows the presence of an irreducible probability of error. When compared to coherently demodulated trellis-coded MPSK, the irreducible probability of error of the differentially coherent scheme is much lower. This improved robustness to carrier-phase-noise is obtained at the expense of signal-to-noise-ratio (SNR), coding gain. Numerical results for two Ungerboeck codes with differentially coherent MPSK demodulation show poor SNR coding gain. A modification of Ungerboeck codes which makes them more suitable for use with differentially coherent demodulation is shown to increase the SNR gain while maintaining good robustness to carrier-phase-noise.>

The problem of optimum space-time processing for multiple Gaussian source signals transmitted through a slowly-varying linear channel and monitored with a passive array of sensors in the presence of spatially correlated noise is addressed. To solve this problem, a new class of linear systems (LS), referred to as semistationary, is introduced. These LS are characterized by time-frequency representations whose variations in time occur over intervals much larger than the corresponding system correlation time. The general conditions under which semistationary LS can be used in array processing are investigated and shown to be satisfied in many applications. By modeling the slowly varying linear channel as a semistationary LS and using the factorization properties of the optimum processor, closed form expressions are obtained for the log-likelihood function of the array output and for the associated Cramer-Rao lower bound on estimator variance.>

In the realization of code-division multiple access based on a spread-spectrum communication system, i.e. spread-spectrum multiple access (SSMA), reduction of cochannel interference is an important problem. An adaptive array antenna system is proposed that includes a cancellor of cochannel interference, which can improve performance by a combination of temporal and spatial filtering. While the adaptive array suppresses interference sources with arrival angles different from those of the desired user, the adaptive digital filter-canceller rejects those whose arrival angles are the same as those of the desired user. The proposed system can achieve stable acquisition and low error rate of demodulated data even in a heavy-interference channel where a conventional array antenna system cannot achieve satisfactory acquisition.>

The authors propose and investigate an adaptive canceller of intersymbol and cochannel interference due to channel distortion and cross-correlation among pseudonoise sequences assigned to individual users of a DS-SSMA (direct-sequence spread-spectrum multiple-access) system. In order to implement a local area network (LAN) by using a power line installed in a building wall as a transmission channel, the authors have investigated utilization of DS-SSMA which has advantages such as robustness against narrow-band interference and noise and realization of asynchronous code division multiple access. In a power line, however, restriction of transmission bandwidth for communications makes it difficult to suppress cochannel interference and the channel is also time-varying due to fluctuation of loads. Since the proposed canceller adaptively eliminates cochannel interference as well as intersymbol interference, it can facilitate synchronization and increase the number of the simultaneously accessing users on a power line with restricted processing gain. The error probability in the output of the canceller is theoretically calculated for the steady-state case by using a Markov model. Computer simulations illustrate stable convergence properties of the canceller.>

The authors present an exact solution to the problem of maximum-likelihood time-delay estimation over arbitrary observation time T. That is, the standard assumption T>> tau /sub c/+d/sub max/ made in the derivation of the asymptotic maximum-likelihood (AML) estimator, where t/sub c/ is the correlation time of the various processes involved and d/sub max/ the maximum permissible delay, is relaxed. The exact maximum-likelihood (EML) processor is shown to consist of a special finite-time beamformer, followed by a scalar postprocessor based on the eigenvalues and eigenfunctions of a certain integral equation. The solution of this integral equation is obtained for the case of stationary signals with rational power spectral densities (PSD). The performance of EML and AML are compared by means of computer simulations for a first-order low-pass PSD. The results show that EML can lead to a significant improvement in performances (bias, variance, large errors) when the condition T>> tau /sub c/+d/sub max/ is not satisfied.>

The authors propose an automatic equalizer, applicable to trellis-coded modulation, that includes a Viterbi decoder and a carrier-phase controller and achieves reliable high-speed voiceband data transmission at 14.4 kb/s and above. The equalizer can perform the operations of equalization, demodulation, and decoding. Since the system reduces misadjustment of tap values and estimated carrier-phase shift due to decision errors, stable convergence can be achieved. Also presented is a method to utilize the reliability of decoded data in order to minimize misadjustment of the adaptive digital filters and the phase controller owing to undetected errors and miscorrected data in decoding.>

Construction of efficient block-encoded M-ary phase-shift-keying (M-PSK) schemes is investigated. An algebraic approach is adopted in which the basic modulation signals are associated with the elements of a finite group. Using some of the properties of group partition chains, the algebraic properties of the linear codes are studied. From this analysis, a class of codes called blocked coset codes is obtained. Distance properties of the block coset codes are obtained in terms of the distance properties of the underlying group partition chain. A particular choice of coset representations yields the standard block coset code construction, which is applicable to M-PSK for M of the form 2/sup k/*3/sup l/. The standard block coset code construction is seen to be equivalent to block code constructions previously reported in the literature, and it is modified to account for the fact that the 4-PSK constellation forms a Hamming space. The modification results in substantial improvements in some cases. A table of some examples of 2/sup k/*3/sup l/ PSK block coset codes is included.>

Several non-minimum-bandwidth partial-response-signaling (PRS) techniques were compared in the above paper (ibid., vol.COM-35, p.475-80, April 1987). One of the criteria used for the comparison was the robustness to the timing jitter. The commenter shows that according to this criterion the duobinary signaling technique is superior to the dicode scheme at low values of the roll-off factor, in contradiction to the conclusion in the original study. In reply the author agrees that the comment is correct and that unnormalized and normalized figure-of-merit plots show different aspects of timing jitter sensitivity as a function of excess bandwidth.>

The optimization of receivers constrained to consist of a (linear) filter and level slicer is considered for general data communication signals in additive white Gaussian noise. Special consideration is given to the two limiting cases of arbitrarily low and high signal-to-noise ratios (SNRs). The low-SNR case results in an average matched filter receiver; the high-SNR filter is shown to be the solution to a specific nonlinear mathematical problem with a simple geometric interpretation. An efficient algorithm is developed to solve the problem. The results are illustrated for a duobinary minimum-shift-keyed signal observed over an interval of three-symbol-period duration.>

Some results are presented regarding the asymptotic distribution of the phase of a vector perturbed by Gaussian noise. It is shown that for large signal-to-noise ratio, the asymptotic distribution of the phase is of the Tikhonov type. This framework is then used for the synthesis of differentially coherent receiver structures, one for M-ary phase-shift keying (MPSK) and the other for minimum-shift keying (MSK). The first structure bridges the performance gap between coherent and differentially coherent demodulation of MPSK. The MSK receiver uses matched filtering with differential demodulation.>

The structure of combinations of (l,k) binary trellis encoders and fast frequency-shift keying (FFSK) modulation is studied. A novel method for the optimization of these combinations is proposed. It is concluded that, regardless of the particular realization, the best combinations can always be obtained by using a so-called matched convolutional code. Optimum FFSK codes of rates 1/2 and 2/3 for up to 64 and 32 states, respectively, are reported. It is shown that the best matched encoders for FFSK modulation are also matched and best for any FFSK-type scheme, where the pulse shape is required to satisfy Nyquist's third criterion.>

This paper introduces a novel class of detectors, which has a symbol-by-symbol, multisample, transversal filter-based structure. The essence of the proposed detectors is based on a noise estimationcancellation technique. By exploiting the noise correlation among the received samples, a linear minimum mean-squared estimate of the existing noise is made and subsequently cancelled. As an illustration of the detection principle, partial response signaling systems of the form1 \pm D^{m}are considered. The effects of the system bandwidth, the number of exploited samples and filtering allocation, on the system performance are thoroughly examined. It is shown that with optimum filtering allocation, the proposed detectors, while having simple structures, give substantial performance gains over conventional one-sample detectors.

In this correspondence, the effect of pulse shape on the performance of nonminimum bandwidth partial response signaling (PRS) systems is studied, using the measures of speed tolerance, eye width, and robustness to sampling phase jitter. In general, in modified duobinary(1- D^{2})and dicode(1 - D)systems, linear rolloff pulse shaping performs better than raised cosine rolloff, while the raised cosine rolloff pulse spectrum is better in the duobinary(1 + D)system.

With trellis-coded MPSK schemes, reference phase errors have a major impact on the system performance. This paper analyzes the interrelation among the coded-modulation format, the reference phase tracker, and the carrier phase noise. A tight upper bound to the error probability of a maximum likelihood decoder is introduced. This bound reveals eight new distance-type functions which, along with the wellknown minimum Euclidean distance, characterize the coded-modulation scheme. Relationships between the new distance-type functions and the various system parameters as well as the irreducible probability of error are pointed out. Numerical results for uncoded QPSK and three Ungerboeck encoded 8-PSK schemes showy that excessive smoothing of the reference phase in presence of carder phase noise can degrade the performance of coded 8-PSK modulation considerably.

Continuous phase modulation (CPM) schemes, using Nyquist 3 pulse shaping and correlative codes, are popular candidates for mobile radio applications. This paper presents a detailed study of the effects of Nyquist 3 pulse shaping on the spectral characteristics of CPM schemes with a modulation index of 1/2. The influence of pulse parameters such as its shape, bandwidth, coding polynomial, and truncation length on spectral characteristics such as main lobe, fractional power bandwidths, and out-of-band power levels is thoroughly investigated; error performance is also briefly analyzed. Among uncoded schemes, a new scheme using a pulse satisfying both Nyquist 3 and Nyquist 2 criteria is pointed out as a promising candidate and as a good compromise between spectral and power efficiencies.

Effective utilization of an error-correcting code (ECC) is proposed in order to make a low-hit-rate adaptive differential PCM (ADPCM) system robust against bit errors in noisy channels, such as mobile radio. In 16 kb/s ADPCM systems, the inverse-quantizers with a small number (four) of levels lead to large offsets in stepsizes due to channel errors, and high-order all-pole predictors are very sensitive to them. For the purpose of solving these problems, we present a robust ADPCM system using an ECC, in which the reliability of words decoded by the ECC decoder is utilized to control the updating of the inverse-quantizer and also to stabilize the predictor in the receiver. Moreover, on condition that a sampling rate of the system is reduced from 8 to 6.4 kHz, the proposed system is compared with a forward adaptation system [8]. A computer simulation shows a maximum of 1.8 dB improvement over an usual system using the same ECC in segmental SNR forBER\geq10^{-2}.

In this paper, the use of adaptive beamforming prior to generalized correlation (GC) is demonstrated as a means of time delay estimate (TDE) bias reduction in interference dominated environments. Analysis of GC TDE bias with both minimum variance distortionless response and conventional delay-and-sum beamforming is given. At high interference-to-noise ratios, theoretical and simulation results indicate that the adaptive structure can facilitate improved delay estimation performance compared to conventional methods.

It is shown that a band-limited Nyquist 3 pulse is expressible as a weighted infinite sum of delayed versions of a corresponding Nyquist 1 pulse. Weightings are derived explicitly for the minimum-bandwidth case. Also, a baseband system using Nyquist 3 shaping and integration at the receiver (over one symbol interval) is studied. An optimal band-limited Nyquist 3 system using integration at the receiver is shown to have the same error performance as that of an optimal Nyquist 1 system which uses sampling at the receiver.

This paper demonstrates that the LMS adaptive line enhancer (ALE) can be used to enhance estimation-performance in situations where source signal spectra have tonal components. Time delay estimation obtained by using ALE's as pre-filters followed by a cross correlator (ALE-CC) achieve better performance than the smoothed coherence transform (SCOT) when tonals are present while achieving the basic cross-correlation performance in purely broadband conditions.

In this paper we show that many spectrally efficient modified MSK schemes, termed generalized MSK, although not representable as OQPSK, may nevertheless be (suboptimally) demodulated using anI-Qreceiver with a proper choice of carrier-phase offset. Correlatively coded MSK schemes withI-Qreceivers are studied, and it is concluded that duobinary MSK and(1 + 2D + D^{2})/4MSK represent good performance-bandwidth tradeoffs among first- and second-order correlative coding polynomial schemes. The optimal design of these receivers are considered subject to the constraint of a finite duration impulse response, especially for asymptotic cases of arbitrarily small and large SNR. Filter design based on a zero-intersymbol interference constraint for PAM-based approximations of the signals is also considered. The optimized linearI-Qreceivers for(1 + D)/2MSK and(1 + D)^{2}/4MSK are presented. These receivers are only 0.28 and 1.24 dB poorer than the optimal (Viterbi) receivers at high SNR.

This paper provides a comparison of the LMS adaptive filter versus conventional Generalized Correlation (GC) methods of time delay estimation in terms of their mean-square-error performance. The treatment is restricted to broadband stationary inputs with finite observation time without a priori knowledge of the processor input statistics. The time delay estimator probability distribution, variance, and error probability are derived for the LMS adaptive filter approach. Further, a performance index is given which is optimized with respect to choice of step size. The simulation results presented indicate that without a priori knowledge of the input statistics, both approaches yield similar sub-optimal results. On the other hand, optimal processing of the adaptive filter weights can yield an estimator with variance similar to that of the minimum variance GC method which approaches the Cramer-Rao Lower Bound.

It is pointed out that the sufficiency portion of Theorem 3 in the above paper concerning the existence of discrete spectral components is not proved and, in fact, is not true. A counterexample is provided.

This paper studies the problem of designing a suitable pulse shape for teletext data transmission. The following four criteria are used: 1) Nyquist I criterion, 2) Nyquist II criterion, 3) degree of overshoots in the channel signal, and 4) robustness to sampling phase jitter. For system bandwidths less than the inverse-baud rate, it is not possible to satisfy all these criteria simultaneously; tradeoffs that have to be made are illustrated. Several candidate pulse shapes are given and a composite criterion developed. A pulse shape, which satisfies the Nyquist I criterion and is closest to satisfying the Nyquist II criterion, in a sum-of-squares-of-deviations sense, is recommended.

For a raised cosine pulse spectrum with pulse shaping fully at the transmitter, several enhanced receivers for pulse amplitude modulation are presented which recover some of the 1.76 dB SNR lost due to nonmatched filtering reception. Three receivers using concepts such as double-the-symbol-rate sampling, the partial response-type property of the pulse, and soft decisions are analyzed; they recover 0.6, 0.97, and 1.21 dB SNR, respectively. An error monitoring scheme is also proposed.

Various pulse shapes have been proposed for teletext data transmission. The effect of apportioning the different pulse shapes between the transmitter and the receiver is studied for the cases of a constraint on the power and a constraint on the peak value of the channel signal.

Chirp (linear FM) signals provide an attractive wideband digital modulation scheme in applications where interference rejection is important. This paper evaluates the error rate (performance) of coherent binary continuous phase chirp (CPC) receivers operating on the additive white Gaussian noise (AWGN) channel and determines the improvement in performance made possible by multiple bit observation. In particular, it is shown that a receiver with two bit observation, giving up to 1.75 dB signal-to-noise ratio (SNR) improvement over the optimum single bit chirp receiver, provides a good compromise between SNR gain and system complexity. Furthermore, a simple, suboptimum, average matched filter (AMF) receiver is analyzed, and it is shown that a two-bit observation is optimum, giving a performance equivalent to that of antipodal phaseshift keying (PSK). An implementation of this receiver in the form of in-phase and quadrature demodulators is also derived.

Previous work has shown that coherent multiple bit observation of binary continuous phase chirp (CPC) signals gives improved error rate performance compared to the conventional bit-by-bit detection scheme. This paper determines bounds on the error rate improvement made possible by multiple bit observation for optimum and suboptimum [average matched filter (AMF)] noncoherent detection of binary CPC signals in additive white Gaussian noise (AWGN). For the same observation interval, it is shown that noncoherent CPC receivers provide higher signal-to-noise (SNR) gain than coherent receivers compared to the respective optimum single bit schemes. In particular, the three-bit noncoherent AMF receiver is shown to yield 3 dB SNR gain over a wide range of signal parameters.

Many signals ocurring in data communications can be described by Markovian models. Expressions for the mean power spectral density function of a signal driven by a stationary discrete-parameter finite-state Markov chain are derived and discussed, both for irreducible and reducible chains. Two examples are presented to illustrate the application of the results.

The effects of changing the allocation of filtering on the performance of a modified duobinary partial response system are examined. Two classes of filtering as well as two types of decoders are considered. The precoded system is, in general, superior to the system with decision feedback decoding, except at low values of the signal-to-noise-ratio and large fractions of the filtering at the receiver.

Pseudoerror monitoring techniques, besides providing a precursive, measure of system degradation, can also be used in extrapolation schemes to estimate the actual bit error rate of a digital link. This study examines pseudoerror techniques as applied to a precoded, modified duobinary system. Two known methods of pseudoerror generation, namely, threshold modification and sampling offset, are compared with two new monitors using controlled amounts of amplitude and phase distortion. The threshold modification monitor is most robust to channel degradations, while amplitude or phase distortion monitors seem to be more accurate in estimating the actual error rate but less robust. The sampling offset monitor seems to be less robust than the other monitors due to its unavoidable sensitivity to degradations affecting the system phase. Methods of improving the estimation accuracy by the choice of degradation parameters are also examined.

This paper studies the effect of a demodulator carrier phase error on the performance of a synchronous data transmission system. Various single sideband-partial response systems are ranked on the basis of their sensitivity to the phase error. Mean-square distortion due to the phase error and the vertical eye opening of the resulting eye patterns are used as performance measures of comparison. The influence of system bandwidth on the system performance is also studied.

Minimum shift keying (MSK)-type signals, while possessing all the advantages of MSK, allow input data pulse shaping in order to obtain more desirable spectral behavior. This paper presents a set of conditions on the pulse shape which enable an MSK-type signal to have a fast spectral rolloff. AnMth order shaping function, resulting in an asymptotic spectral falloff as| f |^{-(4M + 4)}, is presented. Previously considered schemes such as MSK and sinusoidal frequency shift keying (SFSK) are shown to be special eases of this shaping function.

This paper presents a unified study of partial-response signaling (PRS) systems and extends previous work on the comparison of PRS schemes. A PRS system model is introduced which enables the investigation of PRS schemes from the viewpoint of spectral properties such as bandwidth, nulls, and continuity of derivatives. Several desirable properties of PRS systems and their relation to system functions are indicated and a number of useful schemes, some of them not previously analyzed, are presented. These systems are then compared using as figures of merit speed tolerance, minimum eye width, and signal-to-noise ratio (SNR) degradation over ideal binary transmission. A new definition of speed tolerance, which takes into account multilevel outputs and the effect of sampling time, is introduced and used in the calculation of speedtolerance figures. It is shown that eye width, a performance measure that has not been used previously in comparing PRS systems, can be calculated analytically in many cases. Exact values as well as bounds on the SNR degradation for the systems under consideration are presented. The effect of precoding on system performance is also analyzed.