Satellite-based automatic dependent surveillance-broadcast (ADS-B) enables global-scale aircraft tracking, but introduces significant challenges in packet detection due to the severe signal attenuation experienced along the propagation path. This paper investigates detection strategies for satellite ADS-B receivers based on the generalized likelihood ratio test (GLRT), providing a statistically sound alternative to existing heuristic solutions. To enhance robustness against residual frequency offsets, we exploit the modulus of the received samples, which is invariant to phase distortions. Additionally, we extend the observation window beyond the packet preamble to improve detection performance. To reduce the computational cost of an exact GLRT implementation, we explore several alternatives, including an asymptotic approximation of the Rician distribution and a Gaussian model for the observation data. Simulation results show that the proposed schemes achieve reliable detection even at low signal-to-noise ratios, and outperform existing methods by leveraging both the preamble and part of the data payload.

Clock recovery and channel parameter estimation are essential functions for reliable communications over a free-space optical (FSO) link. Thanks to its large bandwidth, FSO ensures high-speed transmissions with data rates similar to those enabled by optical fiber links. In such a case, synchronization procedures that operate at symbol rate are highly desirable, since signal oversampling would require expensive and power consuming analog-to-digital converters (ADCs). In this work we investigate the problem of bit synchronization and channel estimation in an FSO link that employs on-off keying (OOK) signaling and is plagued by a mixture of thermal noise, shot noise and background radiation. In doing so we resort to the least-square (LS) estimation principle and look for some feedforward solution that can operate in a non-data-aided (NDA) fashion using symbol-spaced samples. Since the true LS estimator leads to a computationally intractable multi-dimensional optimization problem, we develop suitable approximations that can be implemented with affordable complexity. The accuracy of the proposed schemes is assessed through computer simulations and compared with the relevant modified Cramér-Rao bound (MCRB). Thanks to their ability to operate at symbol rate, they represent a promising solution for blind synchronization in high-speed FSO communications.

We consider a free-space optical (FSO) communication system employing on-off keying (OOK) signaling in the presence of background radiation and intersymbol interference (ISI) arising as a consequence of a sampling clock offset. The receiver has no prior information about the instantaneous channel coefficient, and shot noise with signal-dependent power is inserted by the photodetector device. In such a harsh scenario, suitable estimates of the timing error, channel attenuation and noise parameters are needed for reliable data detection. In this work, we employ the Expectation-Maximization (EM) algorithm for the joint estimation of all the aforementioned parameters. In order to obtain a feasible scheme, the maximization step of the EM procedure is split into a sequence of simpler optimization tasks according to the Expectation-Conditional Maximization (ECM) principle. The resulting algorithm operates in a non-data-aided fashion using symbol-spaced samples, which is particularly advantageous in high-speed FSO communications where signal oversampling may require sophisticated hardware equipment. Computer simulations indicate that the accuracy of the proposed scheme is close to the relevant modified Cramér-Rao bounds (MCRBs), which amounts to saying that no room is left for a further improvement of the system performance.

Fast and reliable synchronization in free-space optical (FSO) communications is a crucial task that has received little attention so far. Since in these applications the data rate is much higher than in traditional radio-frequency (RF) systems, novel technological constraints may arise in the design of the synchronization algorithms, as for example the need to operate at symbol rate instead with an oversampled data stream. In this work, we consider an FSO link and investigate the problem of channel estimation, symbol timing recovery and frame detection using a known synch pattern. The modulation format is on-off keying (OOK) and the received signal is plagued by a mixture of thermal and shot noise. By applying the least-squares criterion, we derive a novel synchronization scheme that can jointly retrieve all the unknown parameters using symbol-spaced samples. Although designed without taking the noise statistics into account, the estimator performance is assessed in a realistic scenario where shot noise is present. Comparisons are made with the relevant Cramér-Rao bound for the joint estimation of the synchronization parameters and signal-dependent noise variances. Numerical simulations and complexity analysis indicate that the resulting scheme performs satisfactorily with an affordable processing load. Hence, it represents a promising solution for fast synchronization in high-speed FSO communications.

We consider a free-space optical (FSO) communication link for packet-based transmissions over a turbulence fading channel. The modulation format is on-off keying (OOK) and a unique-word (UW) composed by a known synch pattern is periodically inserted in the data stream to identify the start of frame. Since an avalanche photo-diode (APD) is used for direct detection of the OOK symbols, the photocurrent signal provided by the APD is plagued by a mixture of thermal and shot noise with signal-dependent power. Our goal is the detection of the UW position in the received stream, along with the estimation of the unknown channel attenuation and noise variances. The aforementioned problem has recently been studied by ignoring any information conveyed by data symbols surrounding the UW. In this work, further investigation is conducted in order to determine the maximum likelihood (ML) solution that, in addition to the UW, exploits all the information-bearing symbols belonging to the observation window. The relevant Cramér-Rao bound (CRB) is also evaluated to establish the ultimate accuracy achievable in the estimation process. Since the true ML estimator leads to a computationally intractable multi-dimensional optimization problem, we develop suitable approximations that enable accurate frame synchronization with affordable complexity. We also present an iterative solution to refine the channel and noise power estimates provided by the UW detection procedure. Numerical simulations demonstrate the superiority of the proposed synchronization and estimation schemes with respect to existing alternatives.

Sinusoidal frequency estimation in the presence of white Gaussian noise plays a major role in many engineering fields. Significant research in this area has been devoted to the fine tuning stage, where the discrete Fourier transform (DFT) coefficients of the observation data are interpolated to acquire the residual frequency error$\varepsilon $. Iterative interpolation schemes have recently been designed by employing two$q$-shifted spectral lines symmetrically placed around the DFT peak, and the impact of$q$on the estimation accuracy has been theoretically assessed. Such analysis, however, is available only for some specific algorithms and is mostly conducted under the assumption of a vanishingly small frequency error, which makes it inappropriate for the first stage of any iterative process. In this work, further investigation on DFT interpolation is carried out to examine some issues that are still open. We start by evaluating the Cramér-Rao bound (CRB) for frequency recovery by interpolation of two$q$-shifted spectral lines and assess its dependence on$\varepsilon $and$q$. Such a bound is of primary importance to check whether existing schemes can provide efficient estimates at any iteration or not. After determining the optimum value of$q$for a given$\varepsilon $, we eventually derive the maximum likelihood (ML) DFT interpolator. Since the latter exhibits the best performance at any step of the iteration process, it might attain the desired accuracy just at the end of the first iteration, which is especially advantageous in terms of computational load and processing time.

Frequency estimation of a single complex exponential signal embedded in additive white Gaussian noise is a major topic of research in many engineering areas. This work presents further investigations on this problem with regards to the fine estimation task, which is accomplished through a suitable interpolation of the discrete Fourier transform (DFT) coefficients of the observation data. The focus is on fast real-time applications, where iterative estimation methods can hardly be applied due to their latency and complexity. After deriving the analytical expression of the Cramér-Rao bound (CRB) for general values of the system parameters, we present a new DFT interpolation scheme based on the weighted least-squares (WLS) rule, where the optimum weights are precomputed through a numerical search and stored in the receiver. In contrast to many existing alternatives, the proposed method can employ an arbitrary number of DFT samples so as to achieve a good trade-off between system performance and complexity. Simulation results and theoretical analysis indicate that, at sufficiently high signal-to-noise ratios, the estimation accuracy is close to the relevant CRB at any value of the frequency error. This provides some advantage with respect to non-iterative competing schemes, without incurring any penalty in processing requirement.

In long-term evolution (LTE) systems, there is an option to extend the size of the cyclic-prefix (CP) when the propagation environment is characterized by severe time dispersion. Such a peculiar feature makes the system more resilient against multipath distortions, but inevitably complicates the downlink synchronization task, which cannot be accomplished through conventional techniques devised for a specified CP size. In this paper, we study the problem of CP length detection in the LTE downlink in the presence of a timing uncertainty and frequency offset. In contrast to previous investigations based on heuristic arguments, our approach relies on the maximum likelihood (ML) estimation criterion. Furthermore, it accounts for the irregular LTE symbol (characterized by a different CP size), which is present in the normal CP operation mode. The resulting scheme operates in the time-domain and computes a different metric for each possible position of the irregular symbol within the observation window. Due to its flexibility, the proposed ML approach can be applied to any future multicarrier standard for the design of a CP length detection algorithm, either in the presence or in the absence of irregular symbols.

Massive multiple-input multiple-output (MIMO) systems, where base stations (BSs) are equipped with hundreds of antennas, are an attractive way to handle the rapid growth of data traffic. As the number of user equipments (UEs) increases, the initial access and handover in contemporary networks will be flooded by user collisions. In this paper, a random access protocol is proposed that resolves collisions and performs timing estimation by simply utilizing the large number of antennas envisioned in massive MIMO networks. UEs entering the network perform spreading in both time and frequency domains, and their timing offsets are estimated at the BS in closed form using a subspace decomposition approach. This information is used to compute channel estimates that are subsequently employed by the BS to communicate with the detected UEs. The favorable propagation conditions of massive MIMO suppress interference among UEs, whereas the inherent timing misalignments improve the detection capabilities of the protocol. Numerical results are used to validate the performance of the proposed procedure in massive MIMO networks, under uncorrelated and correlated fading channels. With$2.5 \times 10^{3}$UEs that may simultaneously become active with probability 1%, a total of 16 frequency–time codes, and 100 antennas, a given UE is detected with probability 75%, and the accuracy of its timing estimate is on the order of few samples.

Direct conversion receivers (DCRs) are an effective means to obtain user terminals with reduced cost, size, and power consumption. Their major drawback is the possible insertion of I/Q imbalances in the demodulated signal, which can seriously degrade the performance of conventional synchronization algorithms. In this paper, we investigate the problem of carrier frequency offset (CFO) recovery in an OFDM receiver equipped with a DCR front-end. Our approach is based on the best linear unbiased estimation (BLUE) theory and aims at jointly estimating the CFO, the useful signal component, and its mirror image. In doing so, we exploit knowledge of the pilot symbols transmitted within a conventional repeated training preamble appended in front of each data packet. Two solutions are proposed, and both of them provides the CFO in closed-form, thereby avoiding any grid-search procedure. The accuracy of the proposed methods is assessed in a scenario compliant with the 802.11a WLAN standard. Compared with existing solutions, the novel schemes achieve improved performance at the price of a marginal increase of the processing load.

The direct conversion receiver (DCR) architecture has received much attention in the last few years as an effective means to obtain user terminals with reduced cost, size, and power consumption. A major drawback of a DCR device is the possible insertion of in-phase/quadrature imbalances in the demodulated signal, which can seriously degrade the performance of conventional synchronization algorithms. In this paper, we investigate the problem of carrier frequency offset (CFO) recovery in an orthogonal frequency-division multiplexing receiver equipped with a DCR front-end. Our approach is based on maximum likelihood (ML) arguments and aims at jointly estimating the CFO, the useful signal component, and its mirror image. In doing so, we exploit knowledge of the pilot symbols transmitted within a conventional repeated training preamble appended in front of each data packet. Since the exact ML solution turns out to be too complex for practical purposes, we propose two alternative schemes which can provide nearly optimal performance with substantial computational saving. One of them provides the CFO in closed-form, thereby avoiding any grid-search procedure. The accuracy of the proposed methods is assessed in a scenario compliant with the 802.11a WLAN standard. Compared to existing solutions, the novel schemes achieve improved performance at the price of a tolerable increase of the processing load.

Before establishing a communication link with the serving base station (eNodeB), user equipment (UE) operating in a long-term evolution (LTE) multi-cellular network must acquire some specific information, including the sector identity and cell group identity. For this purpose, two training sequences called primary synchronization signal (PSS) and secondary synchronization signal (SSS) are periodically transmitted in the downlink to convey such information. In this work, we present a novel maximum likelihood (ML) approach for SSS detection assuming that the PSS has been successfully identified at an earlier stage. As we shall see, the resulting scheme turns out to be too complex for practical implementation as it requires perfect knowledge of the channel covariance matrix. Therefore, we look for simpler solutions and propose two reduced-search methods that operate in a mismatched mode. The first scheme exploits channel state information emerging from both the primary and secondary synchronization signals, while the second scheme operates using only the secondary synchronization signal. Numerical analysis indicates that the proposed methods outperform existing alternatives and can be successfully applied even in a severe propagation scenario. The price for such an advantage is a certain increase of the processing requirement.

Massive MIMO systems, where base stations are equipped with hundreds of antennas, are an attractive way to handle the rapid growth of data traffic. As the number of users increases, the initial access and handover in contemporary networks will be flooded by user collisions. In this work, we propose a random access procedure that resolves collisions and also performs timing, channel, and power estimation by simply utilizing the large number of antennas envisioned in massive MIMO systems and the inherent timing misalignments of uplink signals during network access and handover. Numerical results are used to validate the performance of the proposed solution under different settings. It turns out that the proposed solution can detect the collisions with a probability higher than 90%, while providing reliable timing and channel estimates at the same time. Moreover, numerical results demonstrate that it is robust to overloaded situations.

This paper investigates the problem of carrier frequency offset (CFO) recovery in an OFDM receiver affected by frequency-selective in-phase/quadrature (I/Q) imbalances. The analysis is based on maximum-likelihood (ML) methods and relies on the transmission of a training preamble with a repetitive structure in the time domain. After assessing the accuracy of the conventional ML (CML) scheme in a scenario characterized by I/Q impairments, we review the joint ML (JML) estimator of all unknown parameters and evaluate its theoretical performance. In order to improve the estimation accuracy, we also present a novel CFO recovery method that exploits some side-information about the signal-to-interference ratio. It turns out that both CML and JML can be derived from this scheme by properly adjusting the value of a design parameter. The accuracy of the investigated methods are compared with the relevant Cramer-Rao bound. Our results can be used to check whether conventional CFO recovery algorithms can work properly or not in the presence of I/Q imbalances and also to evaluate the potential gain attainable by more sophisticated schemes.

Before establishing a communication link in a cellular network, the user terminal must activate a synchronization procedure called initial cell search in order to acquire specific information about the serving base station. To accomplish this task, the primary synchronization signal (PSS) and secondary synchronization signal (SSS) are periodically transmitted in the downlink of a long term evolution (LTE) network. Since SSS detection can be performed only after successful identification of the primary signal, in this work, we present a novel algorithm for joint PSS detection, sector index identification, and integer frequency offset (IFO) recovery in an LTE system. The proposed scheme relies on the maximum likelihood (ML) estimation criterion and exploits a suitable reduced-rank representation of the channel frequency response, which proves robust against multipath distortions and residual timing errors. We show that a number of PSS detection methods that were originally introduced through heuristic reasoning can be derived from our ML framework by simply selecting an appropriate model for the channel gains over the PSS subcarriers. Numerical simulations indicate that the proposed scheme can be effectively applied in the presence of severe multipath propagation, where existing alternatives provide unsatisfactory performance.

This paper addresses the problem of maximum likelihood (ML) estimation of slot timing, integer carrier frequency offset and primary sequence index for the downlink of Long Term Evolution (LTE) systems. The proposed algorithm is designed to exploit the knowledge of the pilot Zadoff-Chu sequence embedded in the primary synchronization signal (PSS). The estimation process is affected by the presence of a large set of nuisance parameters, which need to be estimated jointly with the parameters of interest. As a consequence, the exact ML solution is extremely complex and we have developed a suboptimal algorithm designed to provide a good balance between estimation accuracy and complexity. In particular, a key finding is a reduced-rank representation for the frequency response of the channel, which is required by the ML estimator but is not available at receiver prior to having acquired synchronization. Compared to existing alternatives, the resulting scheme exhibits improved accuracy in the estimation of all three parameters of interest.

In this work we investigate the joint estimation of the integer carrier frequency offset (CFO) and the preamble index in a multicarrier system compliant with the WiMAX specifications. Since the exact ML solution is prohibitively complex in its general formulation, a suboptimal algorithm is developed to provide a reasonable trade-off between estimation accuracy and processing load. Compared to existing alternatives, the resulting scheme exhibits improved accuracy and reduced sensitivity to residual timing errors.

In multi-cellular WiMAX systems based on orthogonal frequency-division multiple-access (OFDMA), the training preamble is chosen from a set of known sequences so as to univocally identify the transmitting base station. Therefore, in addition to timing and frequency synchronization, preamble index identification is another fundamental task that a mobile terminal must successfully complete before establishing a communication link with the base station. In this work we investigate the joint maximum likelihood (ML) estimation of the carrier frequency offset (CFO) and preamble index in a multicarrier system compliant with the WiMAX specifications, and derive a novel expression of the relevant Cramer-Rao bound (CRB). Since the exact ML solution is prohibitively complex in its general formulation, suboptimal algorithms are developed which can provide a reasonable trade-off between estimation accuracy and processing load. Specifically, we show that the fractional CFO can be recovered by combining the ML estimator with an existing algorithm that attains the CRB in all practical scenarios. The integral CFO and preamble index are subsequently retrieved by a suitable approximation of their joint ML estimator. Compared to existing alternatives, the resulting scheme exhibits improved accuracy and reduced sensitivity to residual timing errors. The price for these advantages is a certain increase of the system complexity.

We investigate the problem of carrier frequency offset (CFO) recovery in an OFDM direct-conversion receiver plagued by both dc-offset and frequency-selective I/Q imbalance. In order to enlarge the frequency acquisition range, the CFO is divided into an integer part, which is multiple of the subcarrier spacing, plus a remaining fractional part. The fractional CFO is firstly estimated by resorting to the least-squares (LS) principle using a suitably designed training sequence. Since the exact LS solution requires a complete search over the frequency uncertainty range, we propose a simpler scheme that dispenses from any peak-search procedure. We also derive an approximated closed-form expression of the estimation accuracy that reveals useful for assessing the impact of various design parameters on the system performance. After computing the fractional CFO, the integer frequency error is eventually retrieved by following a weighted LS approach. Numerical simulations and theoretical analysis indicate that the proposed scheme can be used to obtain accurate CFO estimates with affordable complexity.

The IEEE 802.16 family of standards for nomadic wireless metropolitan area networks adopts orthogonal frequency-division multiple-access as an air interface. In these systems, timing errors between the uplink signals and the base station time reference give rise to interchannel interference as well as multiple-access interference with an ensuing degradation of the error-rate performance. To mitigate this problem, users that intend to establish a communication link go through a synchronization procedure called Initial Ranging (IR) by which uplink signals can arrive at the base station synchronously and with approximately the same power level. In this work, a novel IR scheme compliant with the IEEE 802.16 specifications is presented. In contrast to existing methods, our solution operates on the basis of a generalized likelihood ratio test (GLRT) and provides improved timing and power estimates by properly taking into account the channel correlation across the signal bandwidth. In order to increase the resilience to multiple access interference, the GLRT approach is also exploited to derive a two-stage interference cancellation scheme. Numerical simulations and theoretical analysis are used to demonstrate the effectiveness of the proposed solutions and to make comparisons with existing alternatives.

We consider an OFDM system employing bit-interleaved coded-modulation (BICM) and investigate the problem of reliable data detection in the presence of narrowband interference (NBI). Such a scenario may arise in many practical contexts, including cellular applications and wireless transmissions over unlicensed frequency bands. It is known that conventional BICM decoding strategies suffer from significant performance degradation when the received signal is plagued by NBI. To overcome this difficulty, in the present work we model the interference power on each subcarrier as a nuisance parameter which is averaged out from the likelihood function. This approach results into a novel bit-metric that makes use of a suitable estimate of the NBI power obtained from previous data decisions. Numerical simulations indicate that the error rate performance of the proposed scheme is close to that of a maximum likelihood (ML) Viterbi decoder having perfect knowledge of the NBI power across the signal spectrum.

Wireless communications over unlicensed frequency bands are expected to suffer from significant co-channel interference, which inevitably limits the error-rate performance. In this letter, an orthogonal frequency-division multiplexing system employing bit-interleaved coded-modulation is considered and the problem of reliable decoding in the presence of unknown narrowband interference (NBI) is addressed. The proposed solution operates in an iterative fashion according to the expectation-maximization algorithm and is derived by modeling the interference power on each subcarrier as a random variable with an inverse gamma distribution. Computer simulations indicate that the resulting scheme is effective against NBI and, compared to existing alternatives, it achieves a better trade-off in terms of error rate performance, computational complexity and system overhead.

The direct-conversion architecture is a promising solution for the design of low-cost mobile terminals. However, it introduces extra RF impairments that greatly complicate fundamental receiver functions, including the synchronization task. This work deals with pilot-aided carrier frequency offset (CFO) recovery in an OFDM direct-conversion receiver plagued by frequency-selective I/Q imbalance. Since the exact maximum likelihood (ML) solution of this problem requires a complete search over the frequency uncertainty range, we propose a simpler scheme that dispenses from any peak-search procedure. Numerical simulations and theoretical analysis indicate that the proposed scheme attains the relevant Cramer-Rao bound at all signal-to-noise ratios of practical interest.

This paper investigates the estimation of multiple residual carrier frequency offsets (RCFOs) and sampling frequency offsets (SFOs) in the uplink of a multiuser OFDM network with space division multiple access (SDMA). The proposed solutions are based on the presence of some dedicated pilot tones within the signal spectrum, which are traditionally employed in OFDM systems to track channel variations and residual frequency errors. The main obstacle is the large number of parameters involved in the estimation process, which makes the uplink synchronization a rather challenging task. A practical solution to this problem relies on the separation of the received signals before the estimation procedure is started. This way, the RCFOs and SFOs of different users are estimated independently with affordable complexity. We propose two alternative approaches for users' separation. The former is based on the use of orthogonal pilot sequences, while the latter exploits the distinct spatial signatures of the uplink signals. Computer simulations and theoretical analysis are employed to assess the performance of the proposed schemes and to make comparison with existing alternatives.

This paper investigates the joint pilot-assisted estimation of the residual carrier frequency offset (RCFO) and sampling frequency offset (SFO) in an orthogonal frequency division multiplexing (OFDM) system. As it is known, the exact maximum-likelihood (ML) solution to this problem involves a bidimensional grid-search that cannot be pursued in practice. After introducing an enlarged set of auxiliary unknown parameters, however, the RCFO and SFO recovery tasks can be decoupled and the bidimensional search is thus replaced with a simpler mono-dimensional search. This results into an estimation algorithm of reasonable complexity which is suitable for practical implementation. To further reduce the processing load, we also present an alternative scheme yielding frequency estimates in closed-form. Numerical simulations indicate that the proposed methods outperform existing estimators available in the literature in terms of both estimation accuracy and error-rate performance.

Frequency estimation in the uplink of an orthogonal frequency-division multiple-access system is a challenging task due to the presence of multiple carrier frequency offsets. Many existing solutions are too complex for practical implementation, while others are restricted to a specific subcarrier assignment strategy. Motivated by the above consideration, in this letter we propose a novel frequency estimator that allows flexible subcarrier assignment while requiring a low computational burden. Our scheme exploits the repetitive structure of the users' training sequences, which are properly designed so as to minimize the multiple-access interference arising in the presence of frequency errors. Computer simulations are used to assess the effectiveness of the proposed method and to make comparisons with competing alternatives.

Frame detection and timing acquisition are challenging tasks in orthogonal frequency-division multiplexing systems plagued by narrowband interference (NBI). Most existing solutions operate in the time domain by exploiting the repetitive structure of a training symbol and suffer from considerable performance loss in the presence of NBI. In this work, a novel solution in which frame detection is accomplished in the frequency domain on the basis of a suitable likelihood ratio test is presented. In order to increase the resilience to NBI, the interference power is treated as a nuisance parameter that is averaged out from the corresponding likelihood functions. The resulting test statistic depends on the fractional carrier frequency offset (CFO), which is easily estimated. An alternative scheme that dispenses from CFO estimation is also proposed. After frame detection, the test statistic is employed as a timing metric to accurately locate the position of the training symbol within the received data stream. Computer simulations indicate that the proposed solutions are remarkably robust to NBI and outperform existing alternatives in a severe interference scenario. The price for this advantage is a substantial increase in the computational burden.

The IEEE 802.16e standard for nomadic wireless metropolitan area networks adopts orthogonal frequency-division multiple-access (OFDMA) as an air interface. In these systems, residual carrier frequency offsets (CFOs) between the uplink signals and the base station local oscillator give rise to interchannel interference (ICI) as well as multiple access interference (MAI). Accurate CFO estimation and compensation is thus necessary to avoid a serious degradation of the error-rate performance. In this work, we address the problem of CFO tracking in the IEEE 802.16e uplink and present a closed-loop solution based on the least-squares (LS) principle. In doing so, we exploit a set of pilot tones that are available in each user's subchannel. The resulting scheme can be implemented with affordable complexity and is able to reliably track the CFOs of all active users. When used in conjunction with a frequency offset compensator, it can effectively mitigate ICI and MAI, thereby allowing channel equalization and data detection to follow directly. Numerical simulations are used to demonstrate the effectiveness of the proposed solution in the presence of residual time-varying frequency offsets.

In this paper we present two algorithms for SNR estimation for transmissions over flat-fading time-varying channels. The first method exploits a polynomial approximation of the time-varying channel to derive a joint maximum likelihood estimator of the signal power and noise variance. The second technique is based on a subspace decomposition approach and exploits the inherent properties of the signal correlation matrix. Both algorithms can be implemented with affordable complexity and exhibit excellent performance.

Uplink synchronization in orthogonal frequency division multiple-access (OFDMA) systems is a challenging task. In IEEE 802.16-based networks, users that intend to establish a communication link with the base station must go through a synchronization procedure called Initial Ranging (IR). Existing IR schemes aim at estimating the timing offsets and power levels of ranging subscriber stations (RSSs) without considering possible frequency misalignments between the received uplink signals and the base station local reference. In this work, a novel IR scheme is presented for OFDMA systems where carrier frequency offsets, timing errors and power levels are estimated for all RSSs in a decoupled fashion. The proposed frequency estimator is based on a subspace decomposition approach, while timing recovery is accomplished by measuring the phase shift between the usersiquest channel responses over adjacent subcarriers. Computer simulations are employed to assess the effectiveness of the proposed solution and to make comparisons with existing alternatives.

In this letter, an initial ranging scheme for orthogonal frequency-division multiple-access systems is proposed by which users that intend to establish a communication link with the base station (BS) perform spreading in both the time and frequency domains and their synchronization parameters are estimated at the BS in closed-form using the ESPRIT algorithm. Compared to existing alternatives, the resulting scheme exhibits increased robustness against residual frequency offsets without involving computationally demanding peak search procedures.

We investigate the problem of channel estimation in an orthogonal frequency-division multiplexing (OFDM) system plagued by unknown narrowband interference (NBI). Such scenario arises in many practical contexts, including cellular applications and emerging spectrum sharing systems, where coexistence of different types of wireless services over the same frequency band may result into remarkable co-channel interference. Estimation algorithms devised for conventional OFDM transmissions are expected to suffer from significant performance degradation in the presence of NBI. To overcome this difficulty, in the present work we follow a novel pilot-aided approach where the interference power on each pilot subcarrier is treated as a nuisance parameter which is averaged out from the corresponding likelihood function. The latter is then maximized in an iterative fashion according to the expectation-maximization (EM) principle or by applying the Jacobi-Newton algorithm. The resulting schemes have affordable complexity and are inherently robust to NBI. Their accuracy is investigated by means of computer simulations and compared with the relevant Cramer- Rao bound.

We consider an orthogonal frequency-division multiplexing (OFDM) system and address the problem of carrier frequency estimation in the presence of narrowband interference (NBI) with unknown power. This scenario is encountered in emerging spectrum sharing systems, where coexistence of different wireless services over the same frequency band may result into a remarkable co-channel interference, and also in digital subscriber line transmissions as a consequence of the cross-talk phenomenon. A possible solution for frequency recovery in OFDM systems plagued by NBI has recently been derived using the maximum-likelihood criterion. Such scheme exhibits good accuracy, but involves a computationally demanding grid-search over the uncertainty frequency range. In the present work, we derive an alternative method that provides frequency estimates in closed-form by resorting to the expectation-maximization algorithm. This makes it possible to achieve some computational saving while maintaining a remarkable robustness against NBI.

In a recent study, solutions have been proposed for completely suppressing the multiple access interference (MAI) arising in the uplink of a quasi-synchronous multicarrier code-division multiple-access network as a consequence of multipath distortions and carrier frequency offsets. This result is achieved by employing exponential orthogonal codes or selecting a particular subset of the Walsh-Hadamard code family without the need for any channel state information at the transmitter side. In the present letter, we revisit this problem and show that MAI suppression can be achieved by following a different line of reasoning which leads to a transmission scheme exhibiting a lower peak-to-average power ratio.

An efficient scheme for initial ranging has recently been proposed by X. Fu et al. in the context of orthogonal frequency-division multiple-access (OFDMA) networks based on the IEEE 802.16e-2005 standard. The proposed solution aims at estimating the power levels and timing offsets of the ranging subscriber stations (RSSs) without taking into account the effect of possible carrier frequency offsets (CFOs) between the received signals and the base station local reference. Motivated by the above problem, in the present work we design a novel ranging scheme for OFDMA in which the ranging signals are assumed to be misaligned both in time and frequency. Our goal is to estimate the timing errors and CFOs of each active RSS. Specifically, CFO estimation is accomplished by resorting to subspace-based methods while a least-squares approach is employed for timing recovery. Computer simulations are used to assess the effectiveness of the proposed solution and to make comparisons with existing alternatives.

Decentralized slot synchronization protocols inspired from nature have recently gained considerable interest. By adjusting the internal time reference of a node in response to the detected timing of a received synchronization word, and by following simple rules, synchronization emerges from an initially completely uncoordinated situation. However these protocols typically assume that synchronization words are detected error free. In this paper the performance of biologically inspired slot synchronization is investigated when a realistic timing synchronization scheme is employed. We consider an ad hoc network where nodes communicate over an orthogonal frequency-division multiplexing (OFDM) air interface. The transmission is organized in frames, and each frame is preceded by a synchronization preamble with known repetitive parts. Specifically one common synchronization preamble is employed for all transmitting terminals, as, e.g., for the wireless LAN standard 802.11. Computer simulations verify that provided a sufficiently long synchronization word, reliable slot synchronization is maintained using a practical synchronization unit.

This paper investigates the joint Tx-Rx design of a multicarrier multiple-input multiple-output (MIMO) system employing Tomlinson-Harashima precoding (THP). The optimality criterion is the minimization of the mean-square-error (MSE) at the receiver side under a constraint on the overall transmitted power. Theoretical analysis and computer simulations are used to assess the performance of the proposed scheme in terms of bit-error-rate (BER) and minimum achievable MSE. It is shown that non-linear precoding may provide much better results than linear pre-filtering, especially when the number of parallel data streams is close to the number of transmitting and receiving antennas. Compared with other existing methods based on THP, our scheme is different in that the preceded symbols are linearly prefiltered before being launched over the MIMO channel. This results into a power loading operation over the channel eigenmodes, which leads to a remarkable improvement of the error-rate performance.

Carrier frequency offset (CFO) in OFDM systems is normally estimated in two steps. The fractional part of the CFO is recovered first and the remaining ambiguity is subsequently resolved by detecting the integer frequency offset (IFO). Conventional IFO recovery algorithms for OFDM signals are sensitive to multipath distortions as they are derived without explicitly taking into account the frequency selectivity of the transmission channel. In this paper, we propose a novel scheme in which the channel response and IFO are jointly estimated using a maximum likelihood (ML) approach. In doing so we exploit one or more pilot blocks placed at the beginning of the frame and carrying known symbols. Since the complexity of the resulting ML algorithm may be relatively large, we also suggest suboptimal solutions unifying various earlier proposals. Computer simulations are used to demonstrate the superiority of the proposed schemes over existing alternatives. It is shown that excellent performance can be achieved with affordable complexity even in the presence of highly dispersive channels.

Cognitive radio employs spectrum sensing to facilitate coexistence of different communication systems over a same frequency band. A peculiar feature of this technology is the possible presence of interference within the signal bandwidth, which considerably complicates the synchronization task. This paper investigates the problem of carrier frequency estimation in an orthogonal frequency-division multiplexing (OFDM)-based cognitive radio system that operates in the presence of narrowband interference (NBI). Synchronization algorithms devised for conventional OFDM transmissions are expected to suffer from significant performance degradation when the received signal is plagued by NBI. To overcome this difficulty, we propose a novel scheme in which the carrier frequency offset (CFO) and interference power on each subcarrier are jointly estimated through maximum likelihood (ML) methods. In doing so we exploit two pilot blocks. The first one is composed of several repeated parts in the time-domain and provides a CFO estimate which may be affected by a certain residual ambiguity. The second block conveys a known pseudo-noise sequence in the frequency-domain and is used to resolve the ambiguity. The performance of the proposed algorithm is assessed by simulation in a scenario inspired by the IEEE 802.11g WLAN system in the presence of a Bluetooth interferer.

Orthogonal frequency division multiple access (OFDMA) has recently attracted vast research attention from both academia and industry and has become part of new emerging standards for broadband wireless access. Even though the OFDMA concept is simple in its basic principle, the design of a practical OFDMA system is far from being a trivial task. Synchronization represents one of the most challenging issues and plays a major role in the physical layer design. The goal of this paper is to provide a comprehensive survey of the latest results in the field of synchronization for OFDMA systems, with tutorial objectives foremost. After quantifying the effects of synchronization errors on the system performance, we review some common methods to achieve timing and frequency alignment in a downlink transmission. We then consider the uplink case, where synchronization is made particularly difficult by the fact that each user's signal is characterized by different timing and frequency errors, and the base station has thus to estimate a relatively large number of unknown parameters. A second difficulty is related to how the estimated parameters must be employed to correct the uplink timing and frequency errors. The paper concludes with a comparison of the reviewed synchronization schemes in an OFDMA scenario inspired by the IEEE 802.16 standard for wireless metropolitan area networks.

We consider a unified framework comprising both multicarrier code-division multiple-access (MC-CDMA) and orthogonal frequency-division multiple-access (OFDMA), and discuss nonlinear prefiltering for downlink transmissions based on Tomlinson-Harashima precoding. The base station (BS) is equipped with multiple transmitting antennas and channel state information is assumed to be available at the transmit side. We design the prefiltering matrices so as to minimize the sum of the mean square errors at all mobile terminals when a conventional single-user data detector is employed at the receiver side. In this way, most of the computational burden is moved to the BS, where power consumption and computational resources are not critical requirements. Computer simulations are used to assess the performance of the proposed scheme under different operating scenarios. It turns out that OFDMA outperforms MC-CDMA when the system resources (subcarriers and/or spreading codes) are optimally assigned to the active users according to the channel quality.

The problem of frequency synchronization, channel estimation, and data detection for all active users in the uplink of an OFDMA system is investigated in this work. Since the exact maximum likelihood (ML) solution to this problem turns out to be too complex for practical purposes, we derive an alternative scheme that operates in an iterative fashion. At each step, the superimposed signals arriving at the base station (BS) are separated by means of the space-alternating generalized expectation-maximization (SAGE) algorithm. Each separated signal is then passed to an expectation-conditional maximization (ECM)-based processor that updates frequency estimates and performs channel estimation and data detection for each user. The resulting architecture is reminiscent of the parallel interference cancellation (PIC) receiver, where interference is generated and removed from the received signal to improve the system performance. Simulations indicate that the proposed scheme outperforms other benchmark solutions at the price of increased computational complexity

An efficient non-linear pre-filtering technique based on Tomlinson-Harashima pre-coding (THP) has recently been proposed by Liu and Krzymien in the context of multiple-antenna multi-user systems. The algorithm is based on the zero-forcing (ZF) criterion and is derived under the assumption that the number of users is equal to the number of transmit antennas. In contrast to other existing methods, it ensures the same signal-to-noise-ratio (SNR) at each mobile terminal so as to guarantee a fair treatment of all active users. In multimedia applications, however, several types of information with different quality-of-service (QoS) requirements must be sent simultaneously on different subchannels. Motivated by the above problem, in the present work we design a THP-based pre-filtering algorithm for multiple-antenna multi-user systems in which the base station allocates the transmit power according to the QoS requirement of each active user. Compared to existing alternatives, the proposed scheme is simpler to implement and suited for practical situations where the number of active users may be less than the number of transmit antennas

A frequency-domain pre-equalization scheme for single-carrier space-division multiple-access (SC-SDMA) downlink transmissions is proposed in this work. In the system of our interest, both the base station (BS) and mobile terminals (MTs) are equipped with multiple antennas. It operates in a time-division-duplex (TDD) mode and the channel reciprocity between alternative uplink and downlink transmissions is exploited to feed the channel state information (CSI) back to the transmit side. Pre-filtering coefficients are designed so as to minimize the sum of mean-squared-errors at all MTs under an overall transmit power constraint. Several strategies are investigated for linearly combining the received signals at each MT in the frequency domain. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

In this paper we propose a novel dynamic subcarrier assignment algorithm for the downlink of an OFDMA system. In conventional schemes, subcarriers are assigned to the active users independently of the actual channel conditions. On the other hand, in a frequency-selective fading environment the users are characterized by different channel responses on each subcarrier. Thus, it makes sense to look for an efficient subcarrier allocation algorithm that fully exploits the inherent multiuser diversity and dynamically assigns a set of subcarriers to each user according to some optimality criterion. The proposed algorithm is based on a mini/max approach and aims at minimizing the error probability of the user with the most attenuated allocated subcarrier. Simulation indicate that the resulting scheme can achieve large improvements with respect to other existing alternatives in terms of either error probability or power consumption

For the uplink transmission of a coded OFDMA system, we present an iterative receiver that performs joint frequency offset acquisition, channel estimation and maximum a posteriori (MAP)-based decoding for each active user in this work. The proposed receiver attempts to separate users' combined signals by resorting to the space-alternating generalized expectation-maximization (EM) algorithm. Each separated user's signal is then passed to an expectation-conditional maximization (ECM)-based processor that jointly performs frequency acquisition, channel estimation and decoding at each iteration. As compared with conventional OFDMA systems that employ hard- decision equalization and decoding, the proposed receiver can exploit the soft-decision feedback derived from the MAP decoder to provide more reliable synchronization, channel estimation and interference suppression. Simulations indicate that the proposed scheme provides accurate decoding for unsynchronized OFDMA uplink transmissions over frequency-selective fading channels.

Combined equalization has recently been proposed to enhance the error rate performance of conventional multicarrier code-division multiple-access (MC-CDMA) systems. This technique applies pre-equalization at the transmitter in conjunction with post-equalization at the receiver, thereby splitting the overall equalization process into two separate parts. In this way, efficient power allocation over the available subcarriers is possible at the transmitter, while leaving the interference cancellation task at the receiver. In this paper, we consider the uplink of an MC-CDMA system employing combined equalization. As the users transmit from different locations, the uplink signals arrive at the base station after passing through different multipath channels and the goal is to estimate the pre-equalized channel frequency response of each user. This is pursued following two different approaches. The first operates in the frequency-domain and treats the channel gains over adjacent subcarriers as independent unknown parameters. The second operates in the time-domain and achieves better performance by reducing the number of unknown parameters. Both schemes are based on maximum-likelihood reasoning and require knowledge of the transmitted symbols. Numerical examples are given to highlight the effectiveness of the proposed methods.

Maximum-likelihood estimation of the carrier frequency offset (CFO), timing error, and channel response of each active user in the uplink of an orthogonal frequency-division multiple-access system is investigated in this study, assuming that a training sequence is available. The exact solution to this problem turns out to be too complex for practical purposes as it involves a search over a multidimensional domain. However, making use of the alternating projection method, we replace the above search with a sequence of mono-dimensional searches. This results in an estimation algorithm of a reasonable complexity which is suitable for practical applications. As compared with other existing semi-blind methods, the proposed algorithm requires increased overhead but has more flexibility as it can be used with any subcarrier assignment scheme. Simulations indicate that the accuracy of the CFO estimates asymptotically achieves the Cramer-Rao bound.

In this work we consider the uplink of an OFDMA system and present a novel receiver that performs joint frequency offset acquisition, channel estimation and data detection for each active user. The proposed receiver can be used with any subcarrier assignment scheme, and it operates in an iterative fashion. Users' separation is accomplished at the base station through space-alternating generalized-expectation (SAGE) techniques. Each separated user's signal is then passed to an expectation-conditional maximization (ECM)-based processor that jointly performs frequency acquisition, channel estimation and data detection at each iteration. Compared to conventional OFDMA systems, the proposed receiver allows significant reduction of the synchronization overhead as it dispenses from the need of returning estimated frequency offsets back to active users for frequency adjustment. Simulations indicate that the proposed scheme provides accurate data detection for unsynchronized OFDMA uplink transmissions over doubly-selective fading channels.

We consider the downlink of a multi-carrier code-division multiple-access (MC-CDMA) system operating in a time division duplexing (TDD) mode and propose a non-linear pre-filtering scheme based on Tomlinson-Harashima pre-coding. In designing the pre-filtering matrices we adopt a minimum mean square error (MMSE) approach under a constraint on the overall transmit power since multiple access interference and multipath distortions are pre-compensated at the base station, low-complex receivers can be employed at the mobile units. Compared to other existing solutions, the proposed scheme provides better error rate performance

We consider the uplink of an OFDMA system and address the problem of estimating the carrier frequency offset, timing error and channel response of each active user. In doing so we follow a maximum likelihood (ML) approach and assume that a training sequence is available. Unfortunately, joint ML estimation of all the above parameters involves a multi-dimensional grid-search that is difficult to implement in practical systems. Therefore we resort to the alternating-projection algorithm and replace the multidimensional search with a sequence of one-dimensional searches. Compared to other existing methods, the proposed estimator has more flexibility since it can be used with any subcarrier assignment scheme. Simulations indicate that the accuracy of the frequency estimates asymptotically achieve the relevant Cramer-Rao bound (CRB).

We discuss channel acquisition and tracking in the uplink of a multi-carrier code-division multiple-access (MC-CDMA) system. Channel acquisition is performed jointly with noise power estimation following two different approaches. The first assumes independently faded subcarriers while the second exploits the fading correlation across the signal bandwidth to improve the system performance. Both schemes are based on maximum likelihood (ML) reasoning and exploit some training blocks carrying known symbols. Channel tracking is pursued through least-mean square (LMS) techniques, using data decisions provided by a partial parallel interference cancellation (PPIC) receiver.

This paper deals with channel acquisition and tracking for the uplink of direct-sequence code-division multiple-access systems. The transmission medium is characterized by multipath propagation, and the goal is to estimate the time-varying channel impulse response (CIR) for a new user entering the system. Channel acquisition is pursued through maximum-likelihood techniques. The resulting scheme may be too complex in some applications, as it requires the online inversion of a large matrix. Therefore, we also consider a simpler solution based on the least-squares (LS) criterion. Channel tracking is performed through weighted LS methods. At each signaling interval, the CIR estimate is updated using data decisions and exploiting the inverse of the interference covariance matrix to mitigate the near-far problem. Performance is assessed by simulation in a scenario inspired by the frequency-division duplexing component of the universal mobile telecommunications system. The acquisition/tracking algorithms are found to be resistant to multiuser interference and suitable for transmissions over fast-fading channels.

Maximum likelihood sequence estimation for orthogonal frequency division multiplexing (OFDM) transmissions over unknown multipath fading channels is analytically infeasible for lack of efficient methods to maximize the likelihood function. A practical solution to this problem has been recently proposed in the context of space-time block-coded OFDM by resorting to the expectation-maximization (EM) algorithm. The resulting detector operates iteratively, exploiting knowledge of the channel statistics and the operating signal-to-noise ratio (SNR). In this work, we address the problem of estimating the above quantities and propose a recursive solution based on ad hoc reasoning. Simulations indicate that the EM detector employing the estimated SNR and channel statistics has better performance than other schemes operating in a mismatched mode. Also, the performance loss with respect to a system with perfect channel knowledge is negligible at SNR values of practical interest.

We discuss a prefiltering technique for interference mitigation in the downlink of a time division duplex (TDD) multicarrier code-division multiple access (MC-CDMA) system. The base station (BS) is equipped with multiple transmit antennas, and channel state information (CSI) is obtained at the transmitter side by exploiting the channel reciprocity between uplink and downlink transmissions. The prefiltering coefficients are designed so as to minimize a proper cost function that depends on the signal-to-interference-plus-noise ratios (SINRs) at the mobile terminals (MTs). The resulting scheme allows using a simple despreading receiver, thereby eliminating the need for channel estimation and equalization. Numerical results show the advantages of the proposed scheme over some existing solutions.

Maximum likelihood sequence detection for OFDM transmissions over unknown multipath fading channels is a challenging task for lack of efficient methods to maximize the likelihood function. A feasible solution to this problem based on the expectation-maximization (EM) algorithm has been recently proposed in the context of space-time block-coded OFDM. The resulting detector operates iteratively and exploits knowledge of the channel statistics and the operating signal-to-noise ratio (SNR). In this work we address the problem of estimating the above quantities in a recursive fashion. Simulations indicate that the EM detector employing the estimated SNR and channel statistics has better performance than other existing schemes that operate in a mismatched mode. Also, the performance loss with respect to a system with perfect channel knowledge is negligible at SNR values of practical interest.

We consider the uplink of a direct-sequence code-division multiple-access system operating over a multipath fading channel, and we aim at estimating the propagation delay and the frequency offset of a new user entering the network. The joint estimation of these parameters is investigated using a weighted-least-squares approach. The exact solution turns out to be too complex for practical purposes, as it involves a numerical search over a bidimensional domain. As an alternative, we propose a suboptimal procedure, in which the propagation delay is first computed with a monodimensional search and then is exploited to derive the frequency offset in closed form. Both data-aided and nondata-aided estimation methods are considered. The proposed synchronizers have a reasonable complexity and are suited for third-generation cellular systems. Their performance is assessed by simulation in a scenario inspired by the specifications of the frequency-division duplexing component of the Universal Mobile Telecommunications Systems standard. It is found that they provide accurate estimates and are useful even in applications over rapidly varying channels.

This paper deals with timing and frequency recovery for the uplink of an orthogonal frequency-division multiple access (OFDMA) system. The frequency estimator is derived from ad hoc reasoning, whereas the timing estimator is based on the maximum-likelihood criterion. Both schemes rely on the repetition of a fixed pilot symbol. Their main feature is that they provide feedforward estimates and allow synchronization in only two OFDM blocks. In contrast to other existing methods, they do not require that the subcarriers of a given user occupy adjacent positions in the signal bandwidth. This makes it possible to interleave subcarriers of different users so as to optimally exploit the frequency diversity of the channel. Theoretical analysis and computer simulations are used to assess the performance of the proposed synchronizers. It is found that the degradations due to residual frequency and timing errors are negligible at signal-to-noise ratios of practical interest.

The time-division duplex (TDD) component of the universal mobile telecommunications system (UMTS) employs synchronous code-division multiple-access techniques with orthogonal spreading codes to provide protection against cochannel interference. In the presence of multipath propagation, however, the code orthogonality is lost and multiaccess interference is generated at the receiver. In such conditions, an estimate of the channel impulse response is required for reliable detection. In this paper, we propose and compare two pilot-assisted schemes for channel estimation in the downlink of the UMTS-TDD system. Both algorithms also provide estimates of the users' energies, which are needed to perform multiuser detection. Theoretical analysis and computer simulations are used to assess the channel estimation performance in terms of mean-squared errors and bit-error rate. It is shown that the accuracy of the proposed estimators attains the Cramer-Rao bound at intermediate/high signal-to-noise ratios.

We consider the uplink of a direct-sequence code-division multiple-access system and we assume that the base station is endowed with a linear antenna array. Transmission takes place over a multipath channel and the goal is to estimate the channel parameters (path gains and delays) and the directions of arrival of the signal echoes from a user entering the network. We propose an estimator that operates in an iterative fashion and exploits knowledge of the transmitted symbols (training sequence). Compared to other existing schemes, it is simpler to implement as it reduces a complicated multidimensional optimization problem to a sequence of one-dimensional searches. Computer simulations indicate that the proposed scheme is useful even in applications over rapidly varying channels where the training sequence must be short compared with the channel decorrelation time.

This paper investigates channel acquisition and tracking for the uplink of a DS-CDMA system. The transmission medium is characterized by multipath propagation and the goal is the estimate the time-varying channel impulse response (CIR) of a new user entering the system. Channel acquisition is pursued through maximum likelihood techniques while channel tracking is performed through weighted least squares methods. At each signaling interval the CIR estimate the inverse of the interference covariance matrix to mitigate the near-far problem. Performance is assessed by simulation in a scenario inspired by the UMTS system.

We consider the uplink of a DS-CDMA system and we assume that the base station is endowed with a linear antenna array. Transmission takes place over a multipath channel and the goal is to estimate the channel parameters and the directions of arrival of the signals from a user entering the network. Maximum likelihood estimation of all these parameters is not feasible as it involves a search over a multidimensional domain. Through suitable approximations we replace the above search by a sequence of mono-dimensional searches. This results in an estimation algorithm of reasonable complexity of third-generation cellular applications. The performance of the algorithm is assessed by simulation in a scenario inspired by the specification of the FDD component of the UMTS standard. It is found that the channel parameters and the directions of arrival can be estimated with accuracy close to the Cramer-Rao bound.

This paper deals with channel estimation in the uplink of a direct-sequence code-division multiple-access system operating in a multipath environment. The parameters of interest are the delays and the complex attenuations incurred by the signal echoes along the propagation paths. We propose an iterative approach for estimating the channel parameters of a new user entering the system. The method is based on the space-alternating generalized expectation-maximization algorithm and exploits a training sequence. In comparison to other estimation algorithms, it reduces a complicated multidimensional optimization problem to a sequence of one-dimensional problems. In addition, it can be effectively used in applications over fast-fading channels. Computer simulations are employed to assess the performance of the proposed scheme. It is found that it is resistant to multiuser interference and has accuracy close to the Cramer-Rao lower bound even with very short training sequences.

This paper investigates channel estimation in the uplink of a DS-CDMA system. The transmission medium is characterized by the presence of multipath components and the parameters of interest are the delays and complex gains of the propagation paths. We propose a new method for estimating the channel parameters of a user entering the system. The method is based on the maximum likelihood criterion and exploits a training sequence. In comparison with other estimation algorithms it has two advantages. First, it reduces a complicated multidimensional optimization problem to a sequence of one-dimensional problems. Secondly, it has better capability to resolve closely-spaced multipath components. Computer simulations are used to assess its performance. It is found that it is resistant to multiuser interference and can be effectively used in third generation mobile cellular networks.

We propose a new algorithm for Doppler rate estimation in burst-mode phase shift keying (PSK) transmissions. This issue may arise in mobile radio links when the received signal experiences significant time-varying Doppler distortion, as in low-earth-orbit satellite systems. The algorithm is based on the transmission of a training sequence and has a feedforward structure that is easy to implement in digital form. Its estimation accuracy is close to the Cramer-Rao bound even at SNR values as low as 0 dB. Comparisons with earlier methods are discussed.

We propose a carrier frequency recovery scheme for the downlink of the time-division duplex (TDD) component of the Universal Mobile Telecommunications System (UMTS). The frequency estimator exploits the midamble of the common control channel and takes into account that the frequency offset allowed in the UMTS-TDD is small compared to the chip rate. Simulations are used to assess the accuracy of the proposed scheme assuming diversity reception and a frequency selective channel. It is found that good performance can be achieved with a limited computational load.

The time division duplex (TDD) component of the Universal Mobile Telecommunications System (UMTS) employs synchronous CDMA techniques with orthogonal spreading codes to provide protection against cochannel interference. In the presence of multipath propagation, however, the code orthogonality is lost and multiaccess interference is generated at the receiver. In such conditions an estimate of the channel impulse response is required for reliable detection. In this paper we propose a method for channel estimation in the downlink of the UMTS-TDD system. In addition to the channel impulse response, the algorithm provides estimates of the users' powers, which may be needed to perform multiuser detection. Theoretical analysis and computer simulations are used to assess the performance in terms of mean squared estimation error. It is shown that the accuracy of the proposed estimator attains the Cramer-Rao bound (CRB) at signal-to-noise ratios of practical interest.

This paper deals with carrier-frequency estimation for burst transmissions over frequency-selective channels. Three estimation schemes are proposed, all based on the use of known training sequences. The first scheme employs an arbitrary sequence and provides joint maximum-likelihood (ML) estimates of the carrier frequency and the channel response. Its implementation complexity is relatively high but its accuracy achieves the Cramer-Rao bound. The second scheme is still based on the ML criterion, but the training sequence is periodic, which helps to reduce the computational load. The third scheme also employs periodic sequences, but its structure comes from heuristic reasoning. Theoretical analysis and simulations are employed to assess the performance of the three schemes.

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.

This paper is concerned with the estimation of two synchronization parameters that play a key role in multi-h continuous-phase modulation receivers-the ordinary symbol timing phase and the so-called superbaud timing phase. The recovery of symbol and superbaud timing is implemented by means of feedforward nondata-aided algorithms. The novelty of the proposed method is that it can be applied to any modulation format, either full or partial response, with binary or multilevel symbols and with arbitrary modulation indices.

We investigate a novel nondata-aided method for jointly estimating timing and carrier frequency offset in MSK-type modulation. The algorithm has a feedforward structure and lends itself to a simple digital implementation. Its estimation accuracy depends on a design parameter that may be varied to trade performance for computational complexity. Setting the parameter to unity yields a synchronization scheme already known in the literature. Computer simulations are used to assess the synchronizer performance on AWGN Rayleigh fading channels with MSK and Gaussian MSK modulation.

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.

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.

Burst transmission of digital data is employed in several applications such as satellite time-division multiple access (TDMA) systems and terrestrial mobile cellular radio. We propose a new algorithm for carrier frequency estimation in burst-mode phase shift keying (PSK) transmissions. The algorithm is data-aided and clock-aided and has a feedforward structure that is easy to implement in digital form. Its estimation range is large, about /spl plusmn/20% of the symbol rate and its accuracy is close to the Cramer-Rao bound (CRB) for a signal-to-noise ratio (SNR) as low as 0 dB. Comparisons with earlier methods are discussed.

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.

Symbol timing in continuous phase modulated signals is investigated making use of maximum likelihood estimation methods. Nondata-aided algorithms are proposed with a feedforward structure. They are suitable for digital implementation and can be employed with either full or partial response signaling. Multilevel symbol alphabets are allowed and the modulation index may be arbitrary. The performance is assessed by analysis and simulation. It turns out that full response schemes are comparatively easier to synchronize. Difficulties arise with partial response signaling especially with long frequency pulses.

It is widely known that minimum shift keying (MSK) may be seen as a PAM signaling scheme and that the same is true, albeit approximately, with MSK-like modulations. It is also known (perhaps not so widely) that any binary continuous phase-modulated (CPM) signal may be exactly decomposed into the sum of a few PAM waveforms. In this paper we show that this property extends to multilevel CPM signaling. Features of a PAM decomposition are discussed as a function of the alphabet size, the modulation index, and the frequency response of the system. It is found that, especially with signaling schemes with a long memory, the decomposition has so many terms that it becomes unmanageable. For these cases an approximation is proposed with a limited number of terms.>