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In this letter, we investigate the problem of frame synchronization in a free-space optical (FSO) communications link, where a known synch pattern is periodically embedded in the transmitted bitstream. The modulation format is on-off keying (OOK) and the electrical signal provided by the photo-detector is plagued by a mixture of thermal and shot noise with signal-dependent power. Due to atmospheric turbulence, channel attenuation can exhibit large random fluctuations, so that no prior knowledge of the signal level and noise variances is assumed. These parameters, together with the start-of-frame, are jointly estimated using a simplified maximum likelihood (ML) approach. Numerical simulations indicate that the proposed scheme is able to effectively exploit the presence of shot noise to improve its detection capability, and outperforms the standard frame synchronization method tailored for an AWGN channel with signal-independent noise power.

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 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 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 base station in closed-form using a subspace decomposition approach. This information is used to compute channel estimates that are subsequently employed by the base station 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 cellular networks under uncorrelated and correlated fading channels. With $2.5\times10^3$ UEs that may simultaneously become active with probability 1\% and a total of $16$ frequency-time codes (in a given random access block), it turns out that, with $100$ antennas, the proposed procedure successfully detects a given UE with probability 75\% while providing reliable timing estimates., 30 pages, 6 figures, 1 table, submitted to Transactions on Communications

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.

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.

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.

In-phase/quadrature (I/Q) imbalances are front-end impairments which may greatly complicate the synchronization task in a low-cost direct-conversion receiver (DCR). In this paper we investigate the possibility of using the space-alternating generalized expectation-maximization (SAGE) algorithm to recover the carrier frequency offset in OFDM terminals with a DCR architecture. Our study leads to a novel scheme that operates in a recursive fashion and exploits a conventional OFDM training preamble composed by several repeated parts. At each iteration, interference arising from I/Q impairments is subtracted from the received samples before updating the frequency estimate. The performance of the new scheme is assessed in terms of estimation accuracy and processing load by considering a wireless local area network (WLAN) compliant with the IEEE 802.11a standard. The main goal is to check whether the SAGE approach exhibits some advantages compared to existing alternatives.

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.

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.

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.

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.

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.

The use of antenna arrays in wireless communications makes it possible to estimate the directions of arrival (DOAs) of impinging waveforms. The latter can be exploited to enhance channel estimation accuracy or as an input for advanced mobile positioning systems. In this paper, we consider the uplink of a multicarrier code-division multiple-access (MC-CDMA) network in which the base station is endowed with multiple receiving antennas arranged in a uniform linear array. Transmission takes place over a multipath channel, and the goal is the joint estimation of the channel responses and DOAs of the uplink signals. In doing so, we follow a maximum-likelihood (ML) approach and assume that users transmit orthogonal training sequences to facilitate the task of separating the signals. This way, all unknown parameters are estimated independently of each other with affordable complexity. Theoretical analysis and computer simulations are used to assess the performance of the proposed scheme and make comparisons with existing alternatives.

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.

Massive MIMO systems, where the 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 all collisions with a probability higher than 90%, at the same time providing reliable timing and channel estimates. Moreover, numerical results demonstrate that it is robust to overloaded situations., submitted to IEEE Globecom 2016, Washington, DC USA

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.

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.

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.

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.

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.

In this paper we describe a procedure for the study and management of rockfall affected areas. During the MASSA project, we defined a procedure for the management of the first emergency phase after the gravitational phenomenon, describing what it could be done for a first analysis and monitoring of the instable areas. In particular, the developed methodology considered three important aspects that should begin during the first 48–72 h: (i) preliminary morphological/structural analysis; (ii) detection and monitoring of instable areas during the emergency phase; (iii) communication strategies for the event management and divulgation to the population. Starting from the defined methodology, we also describe the first results of the application of this method to the Quincinetto rockfall test site, Piedmont, Italy.

Novel non data—aided (NDA) algorithms are proposed for joint estimation of timing and carrier phase in MSK—type modulations. They are based on maximum likelihood methods and have a feedforward structure which is suitable to fully digital implementation. Performance with MSK and Gaussian MSK. (GMSK) is assessed by computer simulations and compared with that of other existing estimation schemes.

In this paper, an investigation on the potential extension of the Aeronautical Mobile Airport Communications System (AeroMACS) to different operating scenarios is illustrated. We analyze the performance of the system during the approach, landing, and takeoff aircraft phases. A novel airport channel model describing the main wireless propagation phenomena of the new aircraft phases is implemented for accessing the performance of AeroMACS in term of error rate, and a detailed synchronization analysis is also provided. The numerical results obtained for the forward link case in the runway and airborne channel scenarios indicates that AeroMACS is able to cope with the new operational phases and its use can be extended beyond airport surface applications.

Estimation of noise power and signal-to-noise ratio (SNR) are fundamental tasks in wireless communications. Existing methods to recover these parameters in orthogonal frequency-division multiplexing (OFDM) are derived by following heuristic arguments and assuming perfect carrier frequency offset (CFO) synchronization. Hence, it is currently unknown how they compare with an optimum scheme performing joint maximum likelihood (ML) estimation of CFO, noise power and SNR. In the present work, the joint ML estimator of all these parameters is found by exploiting the repetitive structure of a training preamble composed of several identical parts. It turns out that CFO recovery is the first task that needs to be performed. After CFO compensation, the ML estimation of noise power and SNR reduces to a scheme that is available in the literature, but with a computational saving greater than 60% with respect to the original formulation. To assess the ultimate accuracy achievable by the ML scheme, novel expressions of the Cramer-Rao bound for the joint estimation of all unknown parameters are provided.

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.

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 scale reference give rise to interchannel interference as well as multiple-access interference, which severely degrade the error-rate performance. In this work, we present a novel ranging scheme for initial uplink synchronization in an IEEE 802.16 based system. In contrast to existing alternative methods, our approach provides better results by properly taking into account the effects of multipath distortions on the received waveform. Numerical simulations are used to demonstrate the effectiveness of the proposed solution.

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.

In this paper we consider the problem of maximum-likelihood decoding of a coded orthogonal frequency-division multiplexing (OFDM) transmission plagued by the presence of narrowband interference. The presence of NBI characterizes 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. The coding scheme is the bit-interleaved coded modulation (BICM). Conventional maximum likelihood (ML) decision strategies for BICM-OFDM transmissions suffer from significant performance degradation in the presence of NBI. To overcome this difficulty, in this work we develop a new bit-metric for the decoding of the transmitted data that achieves near-optimum results.

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.

Future wireless communications systems are expected to coexist with different commercial applications over the same frequency bands. This gives rise to co-channel interference, which strongly affects the error-rate performance. In this work, an orthogonal frequency-division multiplexing system with bit-interleaved coded-modulation is considered and the problem of data detection in the presence of unknown narrowband interference (NBI) is addressed. In particular, an iterative detector that operates according to the expectation-maximization algorithm is derived under the assumption that the interference power on each subcarrier can be modeled as a random variable with an inverse gamma distribution. Computer simulations indicate that the proposed solution is remarkably robust to NBI and outperforms existing alternatives in severe interference environments.

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.

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 work deals with the problem of carrier-frequency offset estimation in orthogonal frequency-divisionmultiplexing-based cognitive radio systems. In particular, we propose an iterative algorithmwhich provides frequency estimates in closed form without involving any computationally demanding grid-search. Computer simulations are used to assess the effectiveness of the proposed solution and to make comparisons with existing alternatives.

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.

This paper deals with training-assisted carrier frequency offset (CFO) estimation in multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. The exact maximum likelihood (ML) solution to this problem is computationally demanding as it involves a line search over the CFO uncertainty range. To reduce the system complexity, we divide the CFO into an integer part plus a fractional part and select the pilot subcarriers such that the training sequences have a repetitive structure in the time domain. In this way, the fractional CFO is efficiently computed through a correlation-based approach, while ML methods are employed to estimate the integer CFO. Simulations indicate that the proposed scheme is superior to the existing alternatives in terms of both estimation accuracy and processing load.

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.

An efficient algorithm has been proposed by Schmidl and Cox (see IEEE Trans. Commun., p.1613-21, 1997) for carrier frequency estimation in orthogonal frequency division multiplexing systems. The scheme is based on the transmission of a training symbol composed of two identical halves in the time domain. Its accuracy is close to the Cramer-Rao bound and its estimation range, which is originally limited to the distance between two adjacent subcarriers, can be widened by exploiting a second training symbol containing some suitable pseudonoise sequence. In this paper we extend this algorithm by considering a training symbol composed of L>2 identical parts. This makes it possible to achieve a better accuracy at the cost of some increase in computational load. Furthermore, the estimation range can be widened in proportion to L without the need of a second training symbol.

This work presents a novel Initial Ranging scheme for orthogonal frequency-division multiple-access networks. Users that intend to establish a communication link with the base station (BS) are normally misaligned both in time and frequency and the goal is to jointly estimate their timing errors and carrier frequency offsets with respect to the BS local references. This is accomplished with affordable complexity by resorting to the ESPRIT algorithm. Computer simulations are used to assess the effectiveness of the proposed solution and to make comparisons with existing alternatives., Comment: 5 pages, 3 figures; Proceedings of the Ninth IEEE Workshop on Signal Processing Advances in Wireless Communications, Recife, Brazil, July 6 - 9, 2008

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 subspacebased 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., Comment: 6 pages, 3 figures, To appear in the Proceedings of the 2008 IEEE International Conference on Communications, Beijing, May 19 - 23, 2008

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.

We consider the uplink of a multicarrier code-division multiple-access (MC-CDMA) network and assume that the base station is endowed with a uniform linear array. Transmission takes place over a multipath channel and the goal is the estimation of the directions of arrival (DOAs) of the signal from the active users. In a multiuser scenario, difficulties are primarily due to the large number of parameters involved in the estimation of the DOAs which makes this problem much more challenging than in single-user transmissions. The solution we propose allows estimating the DOAs of different users independently, thereby leading to a significant reduction in the system complexity. In the presence of multipath propagation, however, estimating the DOAs of a given user through maximum-likelihood methods remains a formidable task since it involves a search over a multidimensional domain. Therefore, we look for simpler solutions and discuss two alternative schemes based on the SAGE and ESPRIT algorithms.

This paper investigates the joint maximum likelihood (ML) estimation of the carrier frequency offset, timing error, and carrier phase in burst-mode satellite transmissions over an AWGN channel. The synchronization process is assisted by a training sequence appended in front of each burst and composed of alternating binary symbols. The use of this particular pilot pattern results into an estimation algorithm of affordable complexity that operates in a decoupled fashion. In particular, the frequency offset is measured first and independently of the other parameters. Timing and phase estimates are subsequently computed through simple closed-form expressions. The performance of the proposed scheme is investigated by computer simulation and compared with Cramer-Rao bounds. It turns out that the estimation accuracy is very close to the theoretical limits up to relatively low signal-to-noise ratios. This makes the algorithm well suited for turbo-coded transmissions operating near the Shannon limit.