This paper explores the use of data modulated by a spectrally efficient frequency division multiplexing (SEFDM) waveform for sensing. We first show that, if the presence of a cyclic prefix is assumed in the transmitted signal, the problem of multiple target sensing is tantamount to the detection and estimation of an unknown number of complex two-dimensional complex tones. Then, a novel iterative estimation method, based on a maximum likelihood approach, is developed to solve the last problem. Our simulation results evidence that SEFDM represents a valid technical option over static or slowly varying channels, and that the proposed method achieves a better accuracy-complexity trade-off than other estimation techniques available in the technical literature. In particular, our numerical results show that, in various scenarios, the proposed method achieves a 15% – 50% improvement in estimation accuracy with respect to other techniques with a limited computational complexity.

This paper introduces the spectrally efficient time-frequency space (SETFS) modulation, a two-dimensional (2D) modulation extending the concepts of spectrally efficient frequency division multiplexing (SEFDM) and orthogonal time–frequency space (OTFS) modulation by increasing the spectral overlap at two levels, i.e., in both frequency and Doppler domains. This double compression improves the use of the available spectrum. Moreover, in SETFS, the periodicity in both time and frequency is maintained through the use of a double cyclic prefix (DCP) in order to simplify channel equalization and avoid 2D inter-symbol interference (ISI). However, the presence of a spectral overlap unavoidably induces 2D inter-carrier interference (ICI), that makes symbol detection more complicated. To mitigate channel estimation errors and also support high-resolution sensing, a novel channel estimator, dubbed Newton-based estimation and spectral cancellation algorithm (NESCA), is proposed. Numerical results show that SETFS achieves up to a 24% gain in the achievable communication rate with respect to OTFS at the cost of higher receiver complexity. Combined with NESCA, SETFS provides near optimal delay and Doppler estimation, outperforming other three algorithms available in the technical literature. In terms of communication performance, SETFS employing the NESCA, followed by a minimum mean square error equalizer and iterative detector with soft symbol mapping, reaches quasi optimal capacity, while throughput saturation occurs with an SNR gap of about 10 dB in favor of OTFS-DCP and increasing with less advanced estimators. Nevertheless, SETFS combined with NESCA achieves a better communication-sensing tradeoff, improving spectral efficiency up to 25% with respect to OTFS at the price of a higher detection complexity. Overall, SETFS offers a relevant tradeoff between spectral efficiency, complexity and sensing accuracy, making it a promising candidate for future wireless systems.

In this manuscript, the problem of implementing, on commercial software defined radios, a digital communication system that employs the Orthogonal Time Frequency Space (OTFS) modulation is addressed. Few available manuscripts discuss this issue and they all overlook the use of cyclic prefixes in both the time and frequency domains (i.e., the use of a double cyclic prefix), a crucial aspect to achieve robustness to doubly-selective fading channels. In this paper, we describe the implementation of the OTFS-based communication system developed in [1] on a couple of software defined radios by National Instruments. Various technical information about the signal processing algorithms employed at the transmit and receive sides is provided. Experimental results evidence that the proposed communication system is able to reliably operate in the presence of strong Doppler affecting the communication channel.

In this manuscript, a digital communication system employing the orthogonal time-frequency space modulation with a double cyclic prefix and operating over a doubly selective fading is considered. After providing some guidelines for the allocation of pilot symbols within a single orthogonal timefrequency space modulation symbol, novel algorithms for pilotaided channel estimation and equalization are illustrated. The proposed channel estimator is able to provide a description of the inner structure of the communication channel; therefore, it can be also employed at the transmit side for sensing applications. Our numerical results evidence that our algorithms outperform two technical alternatives outlined in the literature at the price of a limited increase in the required computational effort.

In the last years, substantial attention has been paid to the use of radar systems in health monitoring, due to the availability of both low-cost radar devices and computationally efficient algorithms for processing their measurements. In this article, a tutorial overview of radar-based monitoring of vital signs is provided. More specifically, we first focus on the available radar technologies and the signal processing algorithms developed for the estimation of vital signs. Then, we provide some useful guidelines that should be followed in the selection of radar devices for vital sign monitoring and in their use. Finally, we illustrate various specific applications of radar systems to health monitoring and some relevant research trends in this field.

In this manuscript, an innovative method for the detection and the estimation of multiple targets in a radar system employing orthogonal frequency division multiplexing is illustrated. The core of this method is represented by a novel algorithm for detecting multiple superimposed two-dimensional complex tones in the presence of noise and estimating their parameters. This algorithm is based on a maximum likelihood approach and combines a single tone estimator with a serial cancellation procedure. Our numerical results lead to the conclusion that the developed method can achieve a substantially better accuracy-complexity trade-off than various related techniques in the presence of closely spaced targets.

In affective computing, machines should detect and recognize human emotions, and adapt their behavior to them. Nowadays these objectives are mainly achieved through the exploitation of machine learning techniques. These techniques are employed to process different emotional-related features and to produce classification labels or coordinates in a valence-arousal space. This approach, however, ignores the neurophysiological processes governing implicit emotional states and, consequently, suffers from substantial limitations. Moreover, machine learning methods employed today do not benefit from the knowledge of emotional dynamics for properly adapting themselves. In this manuscript, starting from recent neuroscience and computational theories, we show how a simple mathematical description of processes governing implicit emotional dynamics can be developed. Moreover, we discuss how our mathematical models can be exploited to improve tracking, estimation and active modulation of human emotions.

The problem of bit and power loading for bit rate maximization in orthogonal frequency division multiplexing data communications over indoor powerline channels is investigated, and a simple method for bit/power allocation in half a cycle of the mains is developed. The proposed solution is based on the so-called Zadeh's representation for modeling the linear periodically time-varying behavior of powerline channels. Numerical results show the superiority of the proposed method over other solutions available in the technical literature in a real-world scenario.

Indoor powerline channels usually exhibit a cyclic input-output behavior due to the time-varying impedance of power loads. This makes typical time-invariant system models unsuitable to provide a faithful representation of such channels. In this paper, starting from the so-called Zadeh's series expansion, a discrete-time parametric representation of a linear periodically time-varying system is developed, and it is shown how a reduced-complexity version of it can be adopted to model indoor powerline channels. Then, various methods for estimating the parameters of the proposed representation are developed and compared in terms of performance and complexity. Numerical results evidence that our reduced complexity model is able to provide an accurate representation of indoor powerline channels and is of practical interest for both smart-grid applications and home area networks.

The accuracy of indoor wireless localization systems can be substantially enhanced by map-awareness, i.e., by the knowledge of the map of the environment in which localization signals are acquired. In fact, this knowledge can be exploited to cancel out, at least to some extent, the signal degradation due to propagation through physical obstructions, i.e., to the so called non-line-of-sight bias. This result can be achieved by developing novel localization techniques that rely on proper map-aware statistical modelling of the measurements they process. In this manuscript a unified statistical model for the measurements acquired in map-aware localization systems based on time-of-arrival and received signal strength techniques is developed and its experimental validation is illustrated. Finally, the accuracy of the proposed map-aware model is assessed and compared with that offered by its map-unaware counterparts. Our numerical results show that, when the quality of acquired measurements is poor, map-aware modelling can enhance localization accuracy by up to 110% in certain scenarios.

The discrete-time representation of a broadband powerline channel as a linear periodically time variant system poses serious problems in terms of computational complexity. In this paper we exploit the principles of the Zadeh's series expansion to devise a new discrete-time system model, characterized by a limited computational complexity and particularly suitable for an implementation on embedded programmable hardware. Then, we illustrate simple methods for estimating the parameters of the proposed model and apply them to the development of a broadband channel sounding tool for powerlines. Our experimental and numerical results show that the proposed model is able to provide a faithful representation of the periodically time varying behavior of indoor powerline channels.

Accuracy and complexity represent fundamental aspects of localization and tracking systems. In this manuscript the impact of a priori knowledge about agent position on the accuracy and the complexity of localization algorithms is investigated. In particular, first Cramer-Rao bounds on localization accuracy are derived under the assumption that a priori information is described by a map restricting the agent position to a specific region. Then, the computational complexity of optimal map-aware and map-unaware localization techniques is assessed. Our results evidence that: a) map-aware localization accuracy can be related to some geometrical features of the map but usually exhibits a complicated dependence on them; b) in some scenarios map-aware localization algorithms provide better accuracy than their map-unaware counterparts at comparable computational complexity.

The knowledge of the propagation environment can greatly improve the performance of indoor wireless localization systems, since it can be exploited to cancel out, at least to some extent, the effects of physical obstructions (e.g., walls) degrading the radio signals employed for localization. In indoor localization systems, the propagation environment can be described by maps (e.g., floor plans), which represent a valuable source of knowledge. In this paper a new map-aware statistical model for the measurements acquired in wireless localization systems based on received signal strength is proposed. Experimental results are processed to extract the parameters of the proposed model, which is then exploited to devise map-aware localization algorithms; these are capable of mitigating the non-line-of-sight bias introduced in the measurements by the obstructions modelled by the map. Our numerical results evidence that map-aware modelling can substantially improve localization accuracy in indoor scenarios with respect to map-unaware modelling.

Establishing bounds on the accuracy achievable by localization techniques represents a fundamental technical issue. Bounds on localization accuracy have been derived for cases in which the position of an agent is estimated on the basis of a set of observations and, possibly, of some a priori information related to them (e.g., information about anchor positions and properties of the communication channel). In this paper, new bounds are derived under the assumption that the localization system is map-aware, i.e., it can benefit not only from the availability of observations, but also from the a priori knowledge provided by the map of the environment where it operates. Our results show that: a) map-aware estimation accuracy can be related to some features of the map (e.g., its shape and area) even though, in general, the relation is complicated; b) maps are really useful in the presence of some combination of low SNRs and specific geometrical features of the map (e.g., the size of obstructions); c) in most cases, there is no need of refined maps since additional details do not improve estimation accuracy.

In this paper the problem of assessing bounds on the accuracy of pilot-based estimation of a bandlimited frequency selective communication channel is tackled. Mean square error is taken as a figure of merit in channel estimation and a tapped-delay line model is adopted to represent a continuous time channel via a finite number of unknown parameters. This allows to derive some properties of optimal waveforms for channel sounding and closed form Cramer-Rao bounds.

In this paper, a novel ultrawideband system for multiuser data communications is proposed. In this system multiple users are allowed to transmit on-off keying modulated signals in the same time intervals and exploiting the same frequency subband. Time/frequency overlapped data frames sent by distinct users include low data rate training sequences characterized by different repetition periods. This transmission strategy, known as rate division multiple access in the technical literature, allows to ease two fundamental tasks at the receive side, namely joint channel estimation and timing synchronization. Channel estimates are exploited by a multiuser detector based on a zero forcing equalizer. Numerical results evidence that the proposed solution yields good error performance at the price of a limited complexity.

In this paper, game theory is exploited to derive a novel solution to manage virtual antenna array based transmissions in an ad hoc wireless network consisting of selfish nodes. In the proposed strategy each node decides, in an autonomous fashion, whether and when transmitting data packets over a shared wireless channel. The resulting transmission scheme results to be functionally equivalent to a distributed transmission selection scheme, managed, however, in a fully distributed fashion. This approach offers an higher throughput level and an higher efficiency than other communication protocols implementing selection diversity in distributed multi-antenna systems.

In this paper the problem of space-time block coding for multiple-input multiple-output communication systems employing continuous phase frequency shift keying and one-shot noncoherent detection is investigated. First, the detection problem is analysed in a maximum likelihood perspective; then, design criteria for optimal space-time codes are proposed and some error bounds are derived. Finally, some numerical results are illustrated for a couple of novel space-time block codes designed on the basis of the above mentioned criteria. Such results evidence that the use of the proposed schemes can entail a limited energy loss respect to other solutions available in the technical literature for coherent systems, with the relevant advantage, however, of a simple detection algorithm.

In this paper, the problem of node management in the presence of randomized cooperation is tackled. First, game theory is exploited to model the problem of setting up a cluster of cooperative nodes in a wireless network as a multiplayer noncooperative game. In this game the set of players is made of all the nodes belonging to a potential relay cluster an d the set of actions for each player consists of two options only (characterized by different payoffs), namely transmitting a data packet or remaining silent. Then, a novel strategy for the management of node participation to a distributed cooperative link is derived. The proposed solution is fully distributed, is characterized by autonomous choices made by each potential relay and is of significant practical interest since it guarantees the participation of a proper number of nodes to a virtual antenna array (so avoiding an energy waste associated with an excessive number of cooperating nodes) without requiring any overhead for node management.

This paper proposes a new architecture for cooperative communication in wireless ad-hoc networks particularly suitable to emergency and safety applications. The proposed solution is characterized by the following relevant features: (a) a wireless connection between each couple of network nodes is established via multiple relays; (b) each source-to-destination link is characterized by a double string topology allowing the use of specific transmit diversity techniques for reliable communications; (c) a novel utility-based and distributed routing algorithm providing a fair exploitation of the available resources is employed. Simulation results evidence that our solution offers substantial energy savings with respect to traditional ad-hoc architectures.

In this paper game theory is exploited to derive an optimal solution to the problem of cooperative data transmission based on distributed selection diversity in an ad hoc wireless network consisting of selfish nodes. First, a credit-based micro-economical model is proposed to manage node interaction; then, a transmission strategy maximizing node utility is derived. In the proposed strategy each node decides, in an autonomous fashion, whether and when transmitting data packets over a shared wireless channel. Numerical results evidence that this approach can ensure both fairness in the access to a shared medium and excellent network efficiency. In particular, it offers an higher throughput level than other communication protocols implementing selection diversity in distributed multi-antenna systems.

We derive a novel Bayesian algorithm for multiuser detection in the uplink of a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system employing stacked space-time block codes, such as the stacked Alamouti code with two transmit antennas, and a stacked quasi-orthogonal code with four transmit antennas. The proposed technique accomplishes joint estimation of the carrier frequency offset, phase noise, channel impulse response and data of each active user. Its derivation relies on the specific structure of the transmitted signal and on efficient Markov chain Monte Carlo (MCMC) methods. Simulation results evidence the robustness of the proposed algorithm in both uncoded and coded systems.

This paper provides an approximate closed form solution to the problem of data-aided joint maximum likelihood estimation of the carrier frequency offset and of the channel impulse response in an Orthogonal Frequency Division Multiplexing transmission over a multipath fading channel. This results in a novel pilot-aided feedforward estimator, that can be employed for pilot-based receiver training. It is also shown how the novel joint estimation strategy can be exploited in an iterative (turbo) receiver structure to track the fast channel and frequency offset changes occurring during the transmission of information symbols. The performance of this structure is assessed by computer simulations and is compared with that provided by other estimation/detection strategies.

This paper provides a new iterative solution to the problem of the joint estimation of phase noise and residual carrier frequency offset in an orthogonal frequency division multiplexing transmission over a multipath fading channel, in the presence of known data and channel impulse response. The proposed technique results from the application of the sum-product algorithm to a factor graph representing the joint a posteriori probability density function of the carrier frequency offset and the phase noise vector affecting a given symbol. The resulting algorithm is shown to be exploited in a coherent receiver for both data-aided training and decision-directed tracking. Its performance is assessed by computer simulations and is compared with that provided by other strategies.

This paper provides a new iterative solution to the problem of the joint estimation of phase noise and residual carrier frequency offset in an orthogonal frequency division multiplexing transmission over a multipath fading channel, in the presence of known data and channel impulse response. The proposed technique results from the application of the sum- product algorithm to a factor graph representing the joint a posteriori probability density function of the carrier frequency offset and the phase noise vector affecting a given symbol. It is also shown that this estimation algorithm can be exploited in a coherent receiver for both data-aided training and decision-directed tracking. Its performance is assessed by computer simulations and is compared with that provided by other strategies.

This paper provides an approximate closed form solution to the problem of maximum likelihood (ML) estimation of the carrier frequency offset (CFO) in an orthogonal frequency division multiplexing (OFDM) signal transmitted over a multipath fading channel. This results in a novel feedforward frequency synchronizer, requiring only an approximate statistical knowledge of the communication channel. The performance of the proposed algorithm is assessed by computer simulations and is compared with that provided by other synchronizers and with Cramer-Rao bounds.

This paper provides an approximate closed form solution to the problem of data-aided joint maximum likelihood estimation of the carrier frequency offset and of the channel impulse response in an orthogonal frequency division multiplexing transmission over a multipath fading channel. This results in a novel data-aided feedforward estimator, that can be employed for pilot-based receiver training. It is also shown how the novel joint estimation strategy can be exploited in an iterative (turbo) receiver structure to track the fast channel and frequency offset changes occurring during the transmission of information symbols. The performance of this structure is assessed by computer simulations and is compared with that provided by other estimation/detection strategies.

In this paper a novel feedforward frequency synchronizer for orthogonal frequency division multiplexing (OFDM) signals transmitted over multipath fading channels is described. Its derivation is based on maximum likelihood (ML) estimation techniques and assumes an approximate statistical knowledge of the communication channel. The performance of the proposed algorithm is assessed by computer simulations and is compared with that provided by other synchronizers and with Cramer-Rao bounds.

In this paper, novel equalization algorithms for continuous phase modulations (CPMs) are illustrated. Both conventional (linear and decision-feedback) and turbo equalization techniques are derived using the Laurent decomposition of CPM signals. All of them operate in the frequency domain and process two samples of the received signal per channel symbol. Numerical results show that on one hand, conventional equalization strategies offer good performance for binary partial response signaling over severely frequency-selective wireless channels at a moderate complexity. On the other hand, there is evidence that turbo techniques provide a small energy saving at the price of a substantial computational burden.

In this paper novel reduced complexity statistical models for the representation of directional wireless channels affected by Rayleigh fading are developed. Their derivation is based on the evaluation of Fourier integrals by means of Gaussian quadrature rules (GQRs). The proposed models represent a communication channel as a tapped-angle and -delay line with non uniform spacing between successive taps. The application of the GQR approach to three different scenarios is also illustrated. Numerical results evidence that these models can provide a simple and accurate stochastic representation of directional fading channels.

In this paper novel linear and decision feedback equalization algorithms for continuous phase modulations (CPMs) are illustrated. These algorithms operate in the frequency domain and process two samples of the received signal per channel symbol. Their derivation is based on the Laurent decomposition of CPM signals. Numerical results evidence that the proposed techniques enable the use of CPMs over severely frequency selective wireless channels.

In this paper the problem of unitary rate space-time block coding for multiple-input multiple-output communication systems employing continuous phase frequency shift keying is investigated. First, one-shot noncoherent detection is analysed in a maximum likelihood perspective; then, design criteria for optimal space-time codes are proposed and some error bounds for the devised coding schemes are derived. Numerical results evidence that the use of the proposed coding schemes can entail a limited energy loss with respect to other solutions available in the technical literature for coherent systems, with the relevant advantage, however, of a simple detection algorithm

In this paper, channel equalization algorithms processing two samples of the received signal per channel symbol and operating in the frequency domain are described in a unifying framework. First, minimum mean-square error linear and decision-feedback equalizers are derived, and a synthesis technique based on the well-known Levinson-Durbin algorithm is proposed for the latter. Then, iterative linear and decision-feedback equalization algorithms for turbo processing are devised. Performance results for both uncoded and coded phase-shift keying transmissions show the efficacy of the proposed equalization techniques and their superiority over other existing frequency-domain equalization strategies.

In this paper, conventional and turbo-channel-equalization algorithms processing two samples of the received signal per channel symbol and operating in the frequency domain are proposed for space-time block-coded systems. In the class of conventional equalization techniques, minimum-mean-square-error (MMSE) linear and decision-feedback equalizers (DFE) are derived and a synthesis technique based on the well-known Levinson-Durbin algorithm is proposed for the latter. Similarly, iterative linear and decision-feedback-equalization algorithms for turbo receivers are devised. Performance results show the efficacy of the proposed equalization techniques and their superiority over other frequency-domain-equalization strategies.

In this paper, some novel results on adaptive space-time-frequency (STF) coding schemes for multiple-input multiple-output (MIMO) OFDM systems are illustrated. Such schemes result from the concatenation of conventional channel codes with orthogonal space-time block codes (STBCs). In the proposed channel codes, adaptivity can be implemented by adjusting the constellation/energy of the inner STBC code on a subcarrier by subcarrier basis via a space-frequency water-filling procedure and/or modifying some parameters, like the code rate and codeword size, of the outer code. Numerical results show that, in a MIMO OFDM systems with one or two receive antennas, using Alamouti's STBC, and without outer coding, STBC adaptivity can yield an appreciable energy gain over an unloaded system operating at the some data rate. The use of an additional outer code can provide a further substantial gain, at least for high signal-to-noise ratios.

A novel soft-in soft-out detector for space-time block coded OFDM systems operating over multipath fading channels is derived using the Bayesian expectation-maximization (BEM) technique. It exploits statistical information about the communication channel and can he easily incorporated in iterative receivers when outer coding is adopted at the transmitter. Numerical results evidence the efficacy of the proposed algorithm, even in the presence of significant channel variations.

In this paper, a novel reduced complexity statistical models for the representation of wide sense stationary-uncorrelated scattering directional wireless channels affected by Rayleigh fading are developed. Their derivation is based on the so-called Gaussian quadrature rule approach illustrated by E. Chiavaccini and G. M. Vitetta (June 2001) for non directional channels. Numerical results evidence, that the proposed models provide a simple and accurate stochastic representation of directional fading channels.

In this work various channel equalization algorithms operating in the frequency domain are described in a unifying framework. First, minimum mean square error linear and decision-feedback equalizers are derived and a synthesis technique based on the well-known Levinson-Durbin algorithm is proposed for the latter. Then, iterative linear and decision feedback equalization algorithms for turbo processing are devised. Performance results for both uncoded and coded PSK transmissions show the efficacy of the proposed equalization techniques and their superiority over other existing frequency domain equalization strategies.

In this paper, a novel feedback frequency synchronizer for orthogonal frequency-division multiplexing signals transmitted over multipath fading channels is described. Its derivation is based on maximum-likelihood estimation techniques and assumes an approximate statistical knowledge of the communication channel. The performance of the proposed algorithm is assessed by computer simulation, and is compared with that provided by other synchronization algorithms and with Cramer-Rao bounds.

The expectation-maximization algorithm for maximum a posteriori (MAP) estimation of a random vector is applied to the problem of detection of orthogonal space-time block codes over time-selective Rayleigh fading channels. This results in a soft-in soft-out detection algorithm suitable for iterative detection/decoding schemes. Simulation results show that the error performance of the proposed detection algorithm is very close to that of a MAP detector endowed with an ideal knowledge of the channel state if the fading rate is not too fast.

In this paper, a soft-in soft-out multiuser detector for synchronous co-channel signals transmitted over frequency-flat Rayleigh-fading channels is described. The derivation of the proposed algorithm is based on a generalization of the expectation-maximization (EM) algorithm, called Bayesian EM. Performance results for both uncoded and coded phase shift keying transmissions show the efficacy of the proposed multiuser detection technique over slowly time-varying fading channels in a two-user system.

In this paper novel reduced complexity statistical models for the representation of wide sense stationary-uncorrelated scattering directional wireless channels affected by Rayleigh fading are developed. Their derivation is based on the so-called Gaussian quadrature rule approach illustrated in E Chiavaccini et al. (2001). for non directional channels. Numerical results evidence that the proposed models can provide a simple and accurate stochastic representation of directional fading channels.

In this paper a novel soft-in soft-out (SISO) multiuser detector for co-channel signals transmitted over frequency-flat Rayleigh fading channels is described. The derivation of the proposed algorithm is based on a generalization of the expectation-maximization (EM) algorithm, called Bayesian EM (BEM). Performance results for both uncoded and coded PSK transmissions show the efficacy of the proposed multiuser detection technique over slowly time-varying fading channels in a two user system.

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

In this paper, the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation of a random vector is applied to the problem of symbol detection for continuous phase modulation signals transmitted over time-selective Rayleigh-fading channels. This results in a soft-in-soft-out detection algorithm suitable for iterative detection/decoding schemes. Simulation results show that the error performance provided by the proposed solution is very close to that of a MAP detector endowed with an ideal knowledge of the channel state both in uncoded and coded transmissions.

In this paper the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation of a random vector is applied to the problem of detection of space-time block coded (STBC) signals over time-selective Rayleigh fading channels. This results in a soft-in soft-out (SISO) detection algorithm suitable for iterative detection/decoding schemes. Simulation results show that the error performance of the proposed detection algorithm is very close to that of a MAP detector endowed with an ideal knowledge of the channel state if the fading rate is not too fast.

Novel results on the space-time differential detection technique described by V. Tarokh and H. Jafarkhani (see IEEE J. Select. Areas Commun., vol.18, no.7, p.1169-74, 2000) are derived. First, the optimality of the one-shot detection algorithm proposed by Tarokh and Jafarkhani is proved under some assumptions about the channel model and an accurate bit error rate formula for this detector is derived in a particular case. Finally, a per-survivor processing (PSP) receiver, substantially outperforming Tarokh's detector, is derived. Numerical results show both the superiority of the PSP receiver over the one-shot detector and the accuracy of the above mentioned error rate formula.

A soft-input soft-output (SISO) multiuser detection algorithm for synchronous direct sequence-code division multiple access (DS-CDMA) systems operating over a slow Rayleigh fading channel is illustrated. Its derivation is based on the Bayesian expectation maximization (BEM) technique. The proposed detector estimates the fading channel in an iterative fashion and produces the a posteriori probabilities (APPs) of the transmitted symbols. Its error performance is assessed by computer simulation and is compared with that provided by other multiuser detectors.

In this paper the expectation-maximization (EM) algorithm for maximum a posteriori (MAP) estimation of a random vector is applied to the problem of symbol detection for CPM signals transmitted over time-selective Rayleigh fading channels. This results in a soft-in soft-out (SISO) detection algorithm suitable for iterative detection/decoding schemes. Simulation results show that the error performance provided by the proposed solution is very close to that of a MAP detector endowed with an ideal knowledge of the channel state.

In this paper a novel feedback frequency synchronizer for OFDM signals transmitted over multipath fading channels is described. Its derivation is based on maximum likelihood (ML) estimation techniques and assumes an approximate statistical knowledge of the communication channel. The performance of the proposed algorithm is assessed by computer simulation and is compared with that provided by other synchronization algorithms and with Cramer-Rao bounds.

In this paper an expectation-maximization (EM) technique for maximum a posteriori (MAP) estimation is employed to devise novel soft-in soft-out (SISO) algorithms for symbol detection over frequency-flat Rayleigh fading channels. An application of these algorithms to iterative decoding of coded PSK signals is proposed and some performance results are illustrated.

In this paper, reduced complexity statistical models for the representation of wide sense stationary-uncorrelated scattering doubly selective fading channels are developed. Their derivation is based on the evaluation of Fourier integrals by means of Gaussian quadrature rules. The accuracy and the complexity of the proposed models is assessed, and is then compared to that provided by other modeling techniques available in the literature.

In this paper, optimum one-shot detection over known and partially known doubly selective Rayleigh fading channels is investigated. Reduced complexity channel models based on Gauss quadrature rules and Taylor power series are derived and are employed to develop novel analytical tools for the performance analysis of one-shot detectors. Numerical results allow to assess the implicit diversity gain provided by both channel multipath and signal fading and the energy loss due to the mismatch of the receiver filter.

In this paper, an expectation-maximization (EM) technique for maximum a posteriori estimation is employed to devise novel soft-in soft-out algorithms for symbol detection over frequency-flat Rayleigh fading channels. An application of these algorithms to iterative decoding of coded PSK signals is proposed and some performance results are illustrated.

An expectation-maximization (EM) technique for maximum a posteriori (MAP) estimation of a random parameter is employed to devise a per-survivor phase-tracking algorithm for phase-shift-keyed signals transmitted over channels with phase jitter. Simulation results show that the proposed algorithm can provide substantial performance gains over recursive and nonrecursive phase estimators in the presence of a strong phase jitter.

In this paper optimum one-shot detection over known and partially known doubly-selective Rayleigh fading channels is investigated. The performance analysis of the detection algorithms is based on GQR (Gauss quadrature rules) and power series channel models. The proposed methods allow to assess the implicit diversity gain provided by both channel multipath and signal fading and the energy loss due to the mismatch of the receiver filter.

A simple method for the evaluation of the error rate performance of OFDM signals transmitted over doubly-selective fading channels is described. The accuracy of the proposed technique is exemplified by simulation results. Power series models for multipath channels are employed to derive simple expressions for the average signal-to-interference ratio (SIR) and the average error probability.

In this paper reduced complexity statistical models for the representation of wide sense stationary-uncorrelated scattering (WSS-US) doubly-selective fading channels are developed. Their derivation is based on the evaluation of Fourier integrals by means of Gaussian quadrature rules (GQRs). The accuracy and the complexity of the proposed models are assessed and are compared with that provided by other modelling techniques available in the literature.

Novel nondata-aided algorithms are proposed for joint estimation of timing and carrier phase in minimum-shift keying (MSK)-type modulations. The performance with MSK and Gaussian MSK is assessed by computer simulations and compared with that of other existing estimation schemes.

Linearly time-varying fading models are used to investigate both noncoherent detection of FSK signals and differential detection of PSK signals over frequency-flat fading channels. The structure of the optimal FSK and DPSK detectors is derived and an analytical technique is proposed to compute their error performance in fast fading.

Novel algorithms for block equalization of M-ary phase shift keying (PSK) signals transmitted over multipath fading channels in the presence of an interferent cochannel signal are introduced and analyzed. The algorithms exploit the intrinsic statistical properties of cochannel interference (CCI) in order to mitigate its effects. Both linear and decision feedback equalizers (DFEs) are derived under the assumption that the overall channel impulse responses of both the useful and the inteferent signal are known. Simulation results show that: (a) whereas zero-forcing block equalizers yield a large noise enhancement effect, a minimum mean-square block DFE (MMSE-BDFE) can efficiently compensate for the distortion in the useful channel and reduce the effect of CCI at the same time, and (b) the MMSE-BDFEs outperform conventional DFEs, at least in the idealized conditions of our analysis.

Novel symbol-by-symbol differential detection algorithms are proposed for minimum-shift keying signals transmitted over additive white Gaussian noise and frequency-flat Rayleigh fading channels. They are derived as approximations to the maximum likelihood noncoherent detection strategy. Their error performance is assessed by computer simulation and is compared with that of other noncoherent detectors. It is shown that, with fading channels, the new algorithms outperform the traditional methods.

Linearly time-varying fading models are used to investigate differential detection of PSK signals transmitted over frequency-flat fading channels. The structure of the optimal differential PSK detector is derived and an analytical technique is developed to compute its error performance. Results obtained by computer simulation are in excellent agreement with the analytical predictions.

A novel detection algorithm for orthogonal frequency division multiplexing (OFDM) signals transmitted over frequency-selective channels is introduced and analyzed. Simulation results show that the proposed detection strategy, implemented via a standard Viterbi algorithm, provides improved performance over differential detection with a moderate increase in receiver complexity, and without requiring the periodic transmission of a training block.

Linearly time-varying fading models are used to investigate the differential detection of PSK signals transmitted over frequency-flat fading channels. The structure of an optimal differential PSK detector is derived and an analytical technique is proposed to compute its error performance. The results obtained by computer simulation are in excellent agreement with the analytical predictions.

A novel equalization/detection algorithm for orthogonal frequency division multiplexing (OFDM) signals transmitted over frequency-selective channels is introduced and investigated. The algorithm stems from the recognition that the Fourier transform processing inherent in OFDM turns a single wideband frequency-selective channel into a set of correlated narrowband frequency-flat fading channels. This suggests that sequence detection techniques, such as those discussed by Vitetta et al. (see IEEE Trans. Commun., vol.43, p.2750-8, 1995, IEEE Trans. Commun., vol.43, pt.II, p.1256-9, 1995, and Proc. IEEE Commun. Theory Mini-Conf (Globecom '96), London, UK, p.153-7, 1996), for time-selective flat-fading channels, can be also profitably utilized for joint equalization and decoding of OFDM signals in the frequency domain. Simulation results show that the proposed detection strategy, implemented via a standard Viterbi algorithm, provides improved performance over differential detection, with a moderate increase in receiver complexity and without requiring the periodic transmission of training blocks.

We compute the error performance of noncoherent detection receivers for FSK signals transmitted over fast frequency-flat Rician fading channels. Linearly time-varying fading models are used to derive closed-form expressions for the error probability of binary FSK signaling. Error bounds are established for the performance of M-ary orthogonal FSK. Simulation results are in excellent agreement with analytical predictions.

We describe an algorithm for joint timing and carrier phase recovery with CPM signaling. The proposed method may be employed with any CPM format and with either full or reduced state detectors. It can be implemented in digital form with a limited computational complexity. Simulation results show that its tracking performance is excellent. However, when operated in its simplest form, it may exhibit false locks during acquisition. In particular, this happens with multilevel partial response formats. A simple solution to false locks is proposed.

Linearly time-varying fading models are used to investigate noncoherent detection of FSK signals transmitted over frequency-flat fading channels. The structure of the optimal noncoherent FSK detector is derived and a novel analytical technique is proposed to compute the error performance of noncoherent FSK detectors in fast fading. Error performance results obtained by computer simulation are in excellent agreement with the analytical predictions.

We describe joint carrier phase and timing recovery algorithms for CPM signaling. They may be employed with any CPM format, and with either full or reduced state detectors. Their implementation is fully digital, and involves a limited computational complexity. Simulation results show that these algorithms have excellent tracking performance. When operated in their simplest form, however, they may exhibit false locks. In particular, this occurs with multilevel and partial response formats. A simple solution to the false lock problem is proposed.

Linearly time-varying fading models are used to investigate noncoherent detection of frequency shift keying (FSK) signals transmitted over frequency-flat fading channels. The structure of the optimal noncoherent FSK detector is derived and a novel analytical technique is proposed to compute the error performance of noncoherent FSK detectors in fast fading. Error performance results obtained by computer simulation are in excellent agreement with the analytical predictions.

An algorithm, based on previous work [Vitetta and Taylor 1994, 1995], for the detection of coded and uncoded PSK sequences transmitted on a frequency-flat fading channel is investigated. It is based on the Viterbi algorithm and processes more than one signal sample per signaling interval. Its performance is evaluated by means of computer simulations for both uncoded and coded systems.

This paper describes novel detection algorithms for coded and uncoded M-ary phase shift keying (M-PSK) signals transmitted over frequency-flat fading channels. Fading distortion is estimated with per-survivor methods using the sampled outputs of two receive filters. Some of the proposed algorithms do not require information on the fading statistics and are dubbed blind algorithms. The error rate performance of blind and nonblind algorithms is assessed by simulation for uncoded and trellis-coded phase shift keying (PSK) and is compared to the performance of other detection schemes proposed in the literature.

The problem of maximum likelihood (ML) detection for uncoded and coded M-PSK signals on Rayleigh fading channels is investigated. It is shown that, if the received signal is sampled at baud-rate, a ML receiver employing per-survivor processing can be implemented. The error rate performance of this receiver is evaluated by means of computer simulations and its limitations are discussed. In addition, it is shown that, on a fast fading channel, the error floor in the BER curve can be appreciably lowered if more than one received signal sample per symbol interval is processed by the receiver algorithm, Finally, a sub-optimum two-stage receiver structure for interleaved coded PSK systems is proposed. Its error rate performance is assessed for simple trellis-coded modulation schemes and compared to that provided by other receiver structures.

Maximum Likelihood (bit) detection of differentially encoded M-PSK signals on Rayleigh fading channels is investigated. It is shown that the solution to this problem can be related to previous results [Vitetta and Taylor, 1994] and leads to the implementation of a receiver structure based on the Viterbi algorithm and employing per-survivor processing. The error rate performance of this receiver is evaluated by means of computer simulations for both trellis-coded and uncoded systems.>

An approximate method is discussed for maximum likelihood estimation of coded PSK sequences in the presence of an unknown carrier phase. This method makes use of the Viterbi algorithm to find an optimum path in the encoder trellis diagram. Phase estimation is embedded into the structure of the detection algorithm and the branch metrics in the trellis are modified with respect to those employed with known carrier phase. Comparisons with traditional decoding schemes show that the proposed solution has better performance in terms of acquisition time and cycle slips.>