A cognitive radio scenario is considered where the signals transmitted by a secondary user (SU) are relayed by multi-antenna relays using an amplify-and-forward cooperation protocol. In this paper, the optimal power allocation and beamforming scheme is derived for the SU transmitters (SU-TXs), which minimizes the exact outage probability of the SU network with relay selection, under both a transmit power constraint and a constraint on the interference power generated at every primary user receiver. After deriving the optimal structure of the beamforming matrix, several distributed resource allocation algorithms are obtained for different levels of channel state information (CSI) at the SU-TXs: perfect CSI and imperfect CSI are considered, along with the case where only channel distribution information is available. The numerical results show that the multi-antenna relays can significantly improve the performance of the SU network, which would otherwise be severely limited by the harsh interference constraints. Furthermore, we also investigate how the number of relays, the number of antennas, and the level of CSI impact the performance of the SU network. Finally, we point out that the proposed algorithms outperform several algorithms presented in the literature.

In this paper, a novel resource allocation (RA) strategy is designed for the downlink of orthogonal frequency division multiple access networks employing practical modulation and coding under quality of service constraints and retransmission techniques. Compared with previous works, two basic concepts are combined together, namely: 1) taking the goodput (GP) as performance metric and 2) ensuring maximum fairness among users. Thus, the resulting RA maximizes the GP of the worst users, optimizing subcarrier allocation (SA), per-subcarrier power allocation (PA), and adaptation of modulation and coding (AMC) of the active users, yielding a nonlinear nonconvex mixed optimization problem (OP). The intrinsic demanding difficulty of the OP is tackled by iteratively and optimally solving the AMC, PA, and SA subproblems, devoting special care to the difficult nonlinear combinatorial SA-OP. First, the optimal (yet computationally complex) solution is found by applying the branch and bound method to the optimal SA solution found in the relaxed domain, and accordingly, it is taken as benchmark. Then, an innovative suboptimal yet efficient solution based on the metaheuristic ant colony optimization (ACO) framework is derived. The proposed RA strategy is corroborated by comprehensive simulations, showing improved performance even at the cost of affordable numerical complexity.

We propose a novel resource allocation (RA) strategy for a cognitive radio packet-oriented bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM) system with decode-and-forward (DF) relays. The aim of the RA is maximizing the goodput (GP) of the source-relay-destination link, which is the number of information bits correctly received at the destination node per unit of time. Therefore, we derive an accurate analytic approximation for this figure of merit, which allows us to find the optimum constellation size, code rate and energy allocation per subcarrier. Further, this expression also serves as a novel relay selection criterion. Finally, we validate the proposed RA method, and compare its performance to capacitymaximizing algorithms through numerical simulations.

In this paper we consider a decode-and-forward cooperative network, which is active in the same bandwidth as a primary user network. The cooperative or secondary user network applies a dynamic resource allocation algorithm to maximize its own performance while limiting the interference caused at the primary user receivers. The main contribution of this paper is the proposition of a new accurate approximation for the outage probability, which takes into account that the channel state information available at the transmitter is imperfect and outdated. The accuracy of the approximation and the performance of the resource allocation scheme are validated through numerical simulations.

Compressive sampling (CS) based multiple symbol differential detectors are proposed for impulse-radio ultra-wideband signaling, using the principles of generalized likelihood ratio tests. The CS based detectors correspond to two communication scenarios. One, where the signaling is fully synchronized at the receiver and the other, where there exists a symbol level synchronization only. With the help of CS, the sampling rates are reduced much below the Nyquist rate to save on the high power consumed by the analog-to-digital converters. In stark contrast to the usual compressive sampling practices, the proposed detectors work on the compressed samples directly, thereby avoiding a complicated reconstruction step and resulting in a reduction of the implementation complexity. To resolve the detection of multiple symbols, compressed sphere decoders are proposed as well, for both communication scenarios, which can further help to reduce the system complexity. Differential detection directly on the compressed symbols is generally marred by the requirement of an identical measurement process for every received symbol. Our proposed detectors are valid for scenarios where the measurement process is the same as well as where it is different for each received symbol.

With the aim of extending the coverage and improving the performance of impulse radio ultra-wideband (UWB) systems, this paper focuses on developing a novel single differential encoded decode and forward (DF) non-cooperative relaying scheme (NCR). To favor simple receiver structures, differential noncoherent detection is employed which enables effective energy capture without any channel estimation. Putting emphasis on the general case of multi-hop relaying, we illustrate an original algorithm for the joint power allocation and path selection (JPAPS), minimizing an approximate expression of the overall bit error rate (BER). In particular, after deriving a closed-form power allocation strategy, the optimal path selection is reduced to a shortest path problem on a connected graph, which can be solved without any topology information with complexity O(N3), N being the number of available relays of the network. An approximate scheme is also presented, which reduces the complexity to O(N2) while showing a negligible performance loss, and for benchmarking purposes, an exhaustive-search based multi-hop DF cooperative strategy is derived. Simulation results for various network setups corroborate the effectiveness of the proposed low-complexity JPAPS algorithm, which favorably compares to existing AF and DF relaying methods.

In this work, we investigate the power allocation (PA) problem aimed at minimizing the users' packet error rate (PER) over a noncooperative link, i.e., a link where the set of users, employing packet-oriented bit-interleaved coded (BIC) orthogonal frequency division multiplexing (OFDM) systems, compete for the same bandwidth. For these kind of systems, the PER is not available in closed-form, but a very efficient solution is offered by the effective SNR mapping (ESM) technique. This method allows each user to evaluate a single scalar value, the effective SNR (ESNR), accounting for all the SNIRs experienced over the active subcarriers, and to univocally map it into a PER value. Thus, in order to derive a decentralized strategy allowing each user to minimize its own PER, the problem is described as a strategic game, called min-PER game, with the set of player, utilities and strategies represented by the competitive users, the ESNRs and the set of feasible power allocations, respectively. We will show both the existence of at least one Nash Equilibrium (NE) for the min-PER game and its equivalence with a Nonlinear Variational Inequality (NVI) problem. Finally, relying on the theory of contraction mappings, we will derive a distributed algorithm to reach the NE of the game.

In this contribution, a cognitive radio scenario is considered, where a secondary user (SU) cooperative network is allowed to transmit concurrently with a primary user (PU), provided that the resulting average interference power at the PU receiver is kept below a certain threshold. The SU network uses a selection amplify-and-forward protocol. An optimum and a low-complexity suboptimum dynamic energy allocation strategy are proposed, that minimize the link outage probability between the source node and the destination node of the SU network under an average interference power constraint. Because the interference channels from the SU nodes to the PU are affected by fast fading, the realistic assumption is made that each SU node has access to the root mean-square value (rather than the instantaneous value) of the gain of its own interference channel to the PU. We show that both dynamic allocation strategies considerably outperform the optimum static allocation strategy, and that the low-complexity dynamic allocation performs nearly as well as the optimum dynamic allocation. Finally, we confirm that our dynamic algorithms show a significant performance improvement as compared to the optimal dynamic algorithm under a peak interference power constraint.

This paper focuses on the issue of carrier frequency synchronization for filtered multitone wireless transmission over time-frequency selective fading channels. Rather than either relying only on known pilot symbols multiplexed within the transmitted burst or exploiting the specific signal structure in a blind mode, the estimation algorithm we pursue is derived from the maximum likelihood principle and takes advantage of both pilot symbols and also the unknown information-bearing symbols through specific differential decision-directed processing. When compared to conventional pilot-based methods, the proposed approach improves the frequency acquisition range without degrading estimation accuracy at even lower cost in terms of computational complexity.

Code-multiplexed transmitted reference (CM-TR) and code-shifted reference (CSR) have recently drawn attention in the field of ultra-wideband communications mainly because they enable noncoherent detection without requiring either a delay component, as in transmitted reference, or an analog carrier, as in frequency-shifted reference, to separate the reference and data-modulated signals at the receiver. In this paper, we propose a generalized code-multiplexing (GCM) system based on the formulation of a constrained mixed-integer optimization problem. The GCM extends the concept of CM-TR and CSR while retaining their simple receiver structure, even offering better bit-error-rate performance and a higher data rate in the sense that more data symbols can be embedded in each transmitted block. The GCM framework is further extended to the cases when peak power constraint is considered and when inter-frame interference exists, as typically occurs in high data-rate transmissions. Numerical simulations performed over demanding wireless environments corroborate the effectiveness of the proposed approach.

We propose maximum a posteriori (MAP) based noncoherent differential detector for ultra-wideband (UWB) impulse radio (IR) signals, received at a sub-Nyquist sampling rate. We build our detector for a Laplacian distributed multipath channel, which models sparsity. Our MAP based detector outperforms differential detectors based on other state-of-the-art approaches from a practical point of view. Our work highlights the critical role of different measurement matrices for the compressed differential detectors in general and the MAP based compressed differential detectors in particular.

This paper proposes a novel cooperative approach for two-hop amplify-and-forward (A&F) relaying that exploits both the signal forwarded by the relay and the one directly transmitted by the source in impulse-radio ultra-wideband (IR-UWB) systems. Specifically, we focus on a non-coherent setup employing a double-differential encoding scheme at the source node and a single differential demodulation at the relay and destination. The log-likelihood ratio based decision rule is derived at the destination node. A semi-analytical power allocation strategy is presented by evaluating a closed-form expression for the effective signal to noise ratio (SNR) at the destination, which is maximized by exhaustive search. Numerical simulations show that the proposed system outperforms both the direct transmission with single differential encoding and the non-cooperative multi-hop approach in different scenarios.

We consider a cognitive radio (CR) scenario where the signals transmitted by a secondary user are relayed using an amplify-and-forward cooperation protocol. A distributed strategy for power allocation is derived that minimizes the outage probability of the cooperative CR communication system, under the constraint that the interference power experienced by the primary receiver does not exceed a given threshold. First, assuming that each CR node has ideal channel state information about its interference channel, we show that the average interference power constraint gives better outage probability performance than the peak power constraint. Then, when only channel statistics are available for the interference channel, the outage probability is verified to lie in between the results relevant to the average and peak power constraints, respectively, with ideal channel state information.

This paper deals with carrier frequency offset recovery for burst-mode filter-bank multicarrier transmission over channels affected by severe time-frequency selective fading. Unlike previously proposed algorithms, whereby frequency is recovered either relying on known pilot symbols multiplexed with the data stream (pilot-aided, or PA, approach), or exploiting specific properties of the multicarrier signal structure in a non-pilot-aided (NPA) fashion, here we present and discuss an algorithm based on the maximum likelihood principle, which can be qualified as combined PA/NPA since it takes advantage both of pilot symbols and also indirectly of data symbols through knowledge and exploitation of their specific modulation format. The algorithm requires the availability of the statistical properties of channel fading up to second-order moments. It is shown that the above approach allows to improve on both estimation accuracy and frequency acquisition range of previously published schemes.

This paper investigates the issue of dynamic resource allocation (DRA) in the context of multi-user cognitive radio networks. We present a general framework adopting generalized signal expansion functions for representation of physical-layer radio resources as well as for synthesis of transmitter and receiver waveforms, which allow us to join DRA with waveform adaptation, two procedures that are currently carried out separately. Based on the signal expansion framework, we develop noncooperative games for distributed DRA, which seek to improve the spectrum utilization on a per-user basis under both transmit power and cognitive spectral mask constraints. The proposed DRA games can handle many radio platforms such as frequency, time or code division multiplexing (FDM, TDM, CDM), and even agile platforms with combinations of different types of expansion functions. To avoid the complications of having too many active expansion functions after optimization, we also propose to combine DRA with sparsity constraints. Generally, the sparsity-constrained DRA approach improves convergence of distributed games at little performance loss, since the effective resources required by a cognitive radio are in fact sparse. Finally, to acquire the channel and interference parameters needed for DRA, we develop compressed sensing techniques that capitalize on the sparse properties of the wideband signals to reduce the number of samples used for sensing and hence the sensing time.

In this paper, an approximate analytical expression for the peak-to-average power ratio (PAPR) of a Multi-Carrier Code Division Multiple Access (MC-CDMA) signal is derived. Then, it is demonstrated that the PAPR of a MC-CDMA system employing Walsh-Hadamard (WH) codes can be suitably reduced by resorting to a judicious strategy for the allocation of the spreading signature codes. Eventually, a low-complexity implementation of the proposed strategy is presented and the relevant benefits, in terms of peak signal occurrence and robustness against nonlinear distortions, is numerically assessed over conventional random allocation strategy.

In this paper we focus on compressive sampling (CS) based ultra wideband (UWB) differential detection. We formulate an optimization problem to jointly recover the sparse received UWB signals as well as the differentially encoded data symbol. We utilize an alternating direction method of multipliers (ADMoM) to solve this joint optimization problem. Our proposed joint recovery method outperforms the straightforward separate recovery method, which recovers the sparse received UWB signals in a first step and then detects the differentially encoded symbol based on the recovered signals.

In this paper, we solve the problem of detecting the entries of a sparse finite-alphabet signal from a limited amount of data, for instance obtained by compressive sampling. While existing methods either rely on the sparsity property, the finite-alphabet property, or none of those properties to solve the under-determined system of linear equations, we capitalize on both the sparsity and the finite-alphabet features of the signal. The problem is first formulated in a Bayesian framework to incorporate the prior knowledge of sparsity, which is then shown to be solvable using sphere decoding (SD) or semi-definite relaxation (SDR) for efficient Boolean programming. A few toy simulations show how our method can outperform existing works.

An efficient and flexible air interface is the necessary condition for enabling high data rates next generation wireless systems. A practical answer to this need consists in exploiting channel state information at the transmitter for an adaptive and efficient use of the available radio link resources. This paper contributes with a novel strategy for the allocation of the sub-carrier transmit power in the case of a wireless system featuring: i) bit-interleaved coded modulation (BICM); ii) orthogonal frequency division multiplexing (OFDM); iii) multiple antenna profile (MIMO). The proposed power-allocation algorithm aims at maximizing the so-called goodput performance metric for packet transmissions employing automatic repeat request (ARQ) schemes. In addition, it is also proven to be near-optimum in maximizing the input/output mutual information of the MIMO-OFDM subchannels. Numerical simulations over typical wireless indoor scenarios confirm the effectiveness of the procedure when applied in the context of MIMO-BICM-OFDM systems.

In this paper, a novel pragmatic bit and power allocation algorithm for Non Orthogonal Frequency Division Multiplexing (NOFDM) systems is presented. It is based on the well-known Campello approach and takes into account the lack of orthogonality between adjacent waveforms. Simulation results in a typical NOFDM wireless applicative scenario show the effectiveness of the proposed algorithms.

Coded multi-antenna and multi-carrier techniques combined together with link resources adaptation algorithms are the key technologies toward efficient high-data-rate communications over wireless fading channels. The practicability of this concept, however, requires that the transmitter can perform accurate and simple evaluation of the actual link performance. This paper contributes with a novel method specifically developed to predict the link performance of bit-interleaved coded MIMO- OFDM links, which offers improved accuracy at the price of lower complexity when compared with conventional techniques. Its effectiveness is confirmed through extensive simulation results obtained over typical wireless channel environments.

In multicarrier (MC) broadband wireless networks, nonlinear power amplification is one of the main performance limiting factor, and therefore its effects have to be properly quantified during the design phase of the radio links. This letter outlines an analytical framework for the forward-link of a bandlimited MC code division multiple access that intends to fulfill this need while improving the scarce efficiency of conventional simulation-based-only design procedures. Through the extended Bussgang theorem, the approach presented herein yields a theoretical description of several time- and frequency-domain system features, such as transmitted signal power spectrum, constellation warping, nonlinear distortion noise and BER metric. Extensive simulation results verify the accuracy of the proposed analysis under typical multiple-access operating conditions.

This paper discusses the issue of dynamic resource allocation (DRA) in the context of cognitive radio (CR) networks. We present a general framework adopting generalized transmitter and receiver signal-expansion functions, which allow us to join DRA with waveform adaptation, two procedures that are currently carried out separately. Moreover, the proposed DRA can handle many types of expansion functions or even combinations of different types of functions. An iterative game approach is adopted to perform multi-player DRA, and the best-response strategies of players are derived and characterized using convex optimization. To reduce the implementation costs of having too many active expansion functions after optimization, we also propose to combine DRA with sparsity constraints for dynamic function selection. Generally, it incurs little rate-performance loss since the effective resources required by a CR are in fact sparse.

This paper deals with the power allocation problem for coded multicarrier transmission. Specifically, we focus on a bit interleaved coded modulation (BICM) packet transmission implemented with orthogonal frequency division multiplexing (OFDM) and in the presence of automatic repeat request (ARQ) protocol. Capitalizing on the binary-input output-symmetric (BIOS) nature of the BICM channel it is provided a simple upper-bound of the rate of information bits received without any error, the so called goodput. Based on this theoretical characterization, we develop a power allocation strategy among the different subcarriers so that the system goodput performance metric is maximized. The effectiveness of the proposed method is numerically testified for BICM-OFDM transmission in the context of the typical WLAN scenario.

This paper contributes with an adaptive modulation scheme intended for bit interleaved coded (BIC) orthogonal frequency division multiplexing (OFDM) packet transmission in the presence of automatic repeat request (ARQ) protocol. The basic idea consists in properly combining the power allocation strategy with a bit-loading procedure among the different subcarriers so that the rate of information bits received without any error is maximized. Numerical simulations corroborate the effectiveness of the proposed scheme when operating over typical wireless environments.

An efficient and flexible air interface is the necessary condition to achieve the ambitious goals of next generation broadband wireless networks. Multicarrier code division multiple access (MC-CDMA) is a practical answer to this need, but the considerable vulnerability to nonlinear distortions induced by high power amplifiers at the transmitter side hinders its appealing features, thereby demanding for adequate countermeasures. The current paper contributes to this issue with a novel multiuser data predistortion (MUDP) procedure aimed at mitigating the performance degradation of a MC-CDMA forward-link in the presence of a nonlinear channel. The proposed MUDP resides entirely at the transmitter of the base station, and simply requires a set of modified constellations, which are jointly and iteratively optimized so that the distortions experienced by each active user are significantly reduced. The required computational complexity is then kept at affordable levels by resorting to a suboptimal yet effective scheme based on the identification of the strongest interfering users combined with the set-partitioning and the symmetry properties of their constellations. Numerical simulation results corroborate the effectiveness of the MUDP in improving the link performance under typical demanding multiple-access operating conditions.

Multiple symbol differential detection (MSDD) offers high-performance symbol recovery and bypasses training or channel estimation, which are highly desired features in low- power ultra-wideband (UWB) communications. However, UWB impulse radios entail distinct signaling structures and stringent performance-complexity requirements, giving rise to the need for a new MSDD scheme capable of coping with dense multipath UWB channels and detecting a large block of symbols at practical complexity. To this end, this paper develops a novel MSDD-based UWB receiver that attains the desired performance advantages by jointly detecting blocks of received symbols based on the autocorrelation principle. To enable practical implementations at desired performance versus complexity tradeoffs, new optimization formulations are introduced to derive fast implementation algorithms inspired by powerful signal processing tools including sphere decoding and Viterbi algorithm, in both soft- and hard-decision versions. Extensive simulations testify the realistic performance of the proposed detectors in the presence of multiple access interference, timing synchronization errors and low-resolution digital-to-analog conversion.

Rapid and reliable timing synchronization is a demanding task in the receiver design for ultra-wideband (UWB) communication systems, especially when concurrent multiple access is called for. This paper derives a maximum likelihood based timing synchronization scheme for UWB multiple access. Relying on a set of user-specific training sequences, the novel concept of weighted average template is introduced, leading to a multiple access timing synchronizer that works in the absence of any channel knowledge and is resilient to both multiple access interference and noise. Simulation runs testify the effectiveness of the proposed scheme in terms of mean square timing estimation errors and bit-error-rate detection performance when operating in multiple access and dense multipath scenarios.

In this paper we deal with carrier frequency estimation for filter-bank multicarrier burst transmission over time-frequency selective fading channels. Three open-loop algorithms are discussed, all based on the use of known pilot symbols. The first scheme is derived from the maximum likelihood principle, while the second one consists of its low-SNR approximation, and both of them require knowledge of the fading covariance matrix. The third scheme is ad-hoc and is based on the well-known delay-multiply concept. Theoretical analysis and simulation results are employed to assess the above algorithms in a time-frequency selective mobile wireless scenario.

The design of ultra-wideband (UWB) impulse radio receivers has to cope with complex signal propagation environments with dense multipath fading, which complicate channel estimation and multipath energy capture. As the date transmission rate increases, additional interference between adjacent symbols arises which may further degrade the detector performance. To address these problems, this paper presents a multi-symbols differential detector that is capable of mitigating inter-symbol interference (ISI) without requiring training or costly channel estimation. A reduced-complexity implementation based on the Viterbi algorithm is proposed, which offers adjustable parameters to balance between performance and complexity. Simulations under typical indoor operating environments demonstrate that the proposed UWB detection scheme is remarkably robust against the effects of both channel noise and ISI.

This paper deals with receiver design issues for filter-bank multicarrier burst transmission over time- and frequency selective fading channels, with emphasis on synchronization and channel estimation aspects. Specifically, the proposed symbol timing recovery algorithm relies on the transmission of a short known preamble, whilst carrier synchronization is implicitly carried out by a properly modified Bayesian channel estimation algorithm relying on pilot symbols uniformly spaced throughout the subcarriers. The above schemes are assessed and their impact on the receiver performance in terms of frame error rate is evaluated in typical mobile wireless channel conditions. In particular, the sensitivity of the receiver to a frequency offset affecting the input signal is investigated.

The TETRA enhanced data service (TEDS) standard has been developed within the Technical Committee TETRA of the European Telecommunications Standards Institute as a major upgrade to the existing narrow-band ETSI TETRA system to supply professional users with high-speed IP packet data services over wireless mobile channels. TEDS includes a number of innovative key features such as multicarrier-based modulation format, powerful payload and header encoding, link adaptation and others. The aim of this paper is to give a comprehensive overview of the TEDS standard with particular emphasis to the physical layer features. Upper layer protocols are treated in a companion paper. Representative link performance results obtained via computer simulations are given for typical wireless environment setups.

The introduction of turbo and low-density parity-check (LDPC) codes with iterative decoding that almost attain Shannon capacity challenges the synchronization subsystems of a data modem. Fast and accurate signal synchronization has to be performed at a much lower value of signal-to-noise ratio (SNR) than in previous less efficiently coded systems. The solution to this issue is developing specific synchronization techniques that take advantage of the presence of the channel code and of the iterative nature of decoding: the so-calledturbo-synchronizationalgorithms. The aim of this paper within this special issue devoted to the turbo principle is twofold: on the one hand, it shows how the many turbo-synchronization algorithms that have already appeared in the literature can be cast into a simple and rigorous theoretical framework. On the other hand, it shows the application of such techniques in a few simple cases, and evaluates improvement that can be obtained from them, especially in the low-SNR regime.

Ultra-wideband (UWB) wireless channels are typically characterized by dense multipath scattering, which on the one hand provides very large multipath diversity, but on the other hand complicates UWB impulse radio receiver design as far as channel estimation and multipath energy capture are concerned. In this paper, we present a multi-symbols differential detector (MSDD) in which blocks of M received symbols are jointly processed based on the autocorrelation detection principle, bypassing training or costly channel estimation. As the block size M increases, the detection performance improves, but maximum- likelihood MSDD quickly becomes computationally impractical when M is over 10. To circumvent high complexity, we derive a new implementation of the MSDD decision rule based on the sphere decoding (SD) algorithm. The proposed SD approach to MSDD offers attractive detection performance based on a simple receiver structure and at affordable computational complexity polynomial in M.

This paper presents an analytical framework for the theoretical characterization and performance evaluation of an MC-CDMA forward-link in the presence of nonlinear distortions induced by transmitter's high-power amplifiers. The analytical characterization of the signal features, both in the time and frequency domains, is carried out through the application of the Bussgang theorem. Simulation results are derived to validate the accuracy of the proposed method under typical operating conditions

In I/Q receivers characterized by direct conversion or low-IF operations, phase imbalance between the I and Q branches stands for a substantial issue which may degrade significantly the overall link performance. An alternative solution to high cost analog components with small tolerances which make the I/Q imbalance effect negligible is to estimate and compensate it digitally. In this paper we present a novel data aided (DA) joint estimator of the carrier phase offset and the I/Q phase imbalance derived following the maximum likelihood (ML) criterion. The performance accuracy analysis proves that the proposed estimator is efficient and achieves its vector Cramer-Rao lower bound (VCRLB). Simulation results in terms of BER performance of uncoded and turbo coded systems show that the proposed imbalance compensation method, at the cost of a low additional implementation complexity of the digital receiver, allows negligible performance degradation in the context of multi-level modulation formats, such as 16-QAM and 64-QAM.

Filterbank multicarrier modulation (FBMCM) is an attractive technology for high-speed twisted-pair transmission and for broadband wireless communications, as well. In wireline applications, signal transmission takes place at baseband, so the issue of carrier acquisition and tracking for coherent demodulation does not apply. In wireless communications, on the contrary, carrier-frequency recovery reveals the Achille's heel of multicarrier modulation, so that robust signal processing algorithms are needed in this respect. In this paper, we derive a nondata-aided carrier-frequency offset recovery method for wireless FBMCM modems. In particular, we illustrate how to derive a low-complexity closed-loop tracker starting from a maximum-likelihood approach. We then show that the proposed simplifications do not entail large performance losses. In this respect, we derive the standard performance metrics of a closed-loop tracker (S-curve, root mean square estimation error, acquisition time) both on the additive white Gaussian noise channel and on a typical static frequency-selective wireless channel. We also demonstrate by simulation good robustness of the frequency tracker with respect to FBMCM symbol-timing errors.

Timing acquisition for ultrawideband (UWB) communication systems operating in dense multipath environments faces major challenges due to the stringent requirements to resolve and capture ultrashort transmitted pulses. This paper develops low-complexity maximum-likelihood (LC-ML) acquisition methods that offer explicit design options to trade off acquisition accuracy and complexity. The proposed schemes are based on a tapped delay line (TDL) model whose tap spacing is set in accordance with a low frame-level rate. By avoiding subpulse rate sampling, the LC-ML methods achieve low complexity and fast acquisition speed and at the same time retain good estimation accuracy due to the underlying ML principle. Both the data-aided (DA) and nondata-aided (NDA) versions are derived. It is also demonstrated by simulations that the proposed synchronizers are markedly robust with respect to the effects of both multipath channel and multiple access interference.

Filter bank (FB) multicarrier modulation exhibits several properties which make it an attractive approach not only for high speed copper wire communications networks but also for broadband wireless applications. In this paper, we derive a nondata aided carrier frequency offset recovery algorithm for wireless FB-based systems. The estimator is based on a maximum likelihood approach and has a feedback loop structure. A number of proper simplifications make the problem tractable and allow to reduce the computational complexity. The algorithm accuracy is examined by computer simulation for AWGN and frequency selective multipath channel showing an considerable robustness against timing errors.

In this paper, we introduce a low-complexity carrier phase estimation algorithm to be integrated into the data decoder of a turbo-coded modem employing a linear modulation. The estimator is based on a pseudo-maximum-likelihood approach and makes iterative use of soft decisions provided by the soft-in/soft-out decoders within the overall turbo-decoding scheme. In doing so, iterative decoding and carrier phase recovery go together iteration after iteration in a "soft decision-directed" mode. This allows performing reliable blind phase estimation and almost ideal coherent detection for values of the signal-to-noise ratio down to a few decibels only, and without the need to resort to narrowband phase-locked loops with large acquisition time. Performance in terms of mean estimated value, root mean-squared estimation error, and overall decoder bit-error rate as derived by simulation are also reported.

Many frequency-recovery algorithms for orthogonal frequency-division multiplexing systems are geared to recover offsets up to half the distance of the subcarriers. If the error is larger, an ambiguity of an integer number of subcarrier spacings is left. This paper develops a blind algorithm for ambiguity resolution that works effectively over frequency-selective radio channels. Simulation results show a sizable improvement over existing techniques, expecially at high signal-to-noise ratios.

In this letter, we show how different signal processing techniques can be combined to optimize the performance of a typical wideband nonlinear satellite link with spectrally efficient high-level modulation techniques. In particular, we follow two concurrent approaches: on one side, we pursue signal optimization in the form of special amplitude and phase shift keying (APSK) constellations to reduce the effect of nonlinear distortions, while on the other, we analyze the feasibility of adaptive data predistortion (DP) at the transmitter and adaptive nonlinear equalization (NLE) at the receiver. We demonstrate that the use of such optimized constellations relieves the complexity of the nonlinearity compensation techniques, and we also show that by clever adoption of these techniques the sensitivity to nonlinear distortion of both uncoded and turbo coded quadrature amplitude modulation and APSK constellations is greatly reduced.

This paper is devoted to turbo synchronization, that is to say the use of soft information to estimate parameters like carrier phase, frequency offset or timing within a turbo receiver. It is shown how maximum-likelihood estimation of those synchronization parameters can be implemented by means of the iterative expectation-maximization (EM) algorithm [A.P. Dempster, et al., 1977]. Then we show that the EM algorithm iterations can be combined with those of a turbo receiver. This leads to a general theoretical framework for turbo synchronization. The soft decision-directed ad-hoc algorithm proposed in V. Lottici and M. Luise, [2002] for carrier phase recovery turns out to be a particular instance of this implementation. The proposed mathematical framework is illustrated by simulations reported for the particular case of carrier phase estimation combined with iterative demodulation and decoding [S. ten Brink, et al., 1998].

In this paper, we present a low-complexity carrier phase estimation algorithm suited for turbo-coded 16-QAM modems. The estimator is based on a maximum likelihood (ML) approach, and unlike previously published work, makes iterative use of soft decisions provided by the soft-in soft-out decoders within the overall iterative turbo decoding scheme, yielding negligible degradation with respect to ideal phase synchronization. Performance in terms of mean estimated value, mean-squared estimation error, and overall decoder bit error rate (BER) as derived by simulation are also reported.

This paper deals with channel estimation in ultra-wideband communications operating in a multipath environment and in the presence of multiaccess interference. The channel parameters are the attenuations and delays incurred by the signal echoes along the propagation paths. Time-hopping modulation with binary symbols is assumed. The estimation method is based on the maximum-likelihood criterion and is applied to two different scenarios: either with known symbols (DA estimation) or with unknown symbols (NDA estimation). The effects of the estimation errors on the performance of a RAKE receiver are assessed by simulation by comparing the receiver bit-error rate with either perfect channel estimates or imperfect estimates as obtained from the proposed algorithms. The results show that the degradations are tolerable as long as the number of users is limited. They also show that the DA method has an edge over the NDA in that it can handle a larger number of users for a fixed degradation. The number of users that can be accommodated in practice is found for some values of the system parameters.

The linearization technique known as amplitude and phase (A&P) predistortion, proposed by D'Andrea and Lottici, is applied to the orthogonal frequency-division multiplexing (OFDM) transmission context with nonlinear radio-frequency high-power amplification. The above technique is shown to provide a major enhancement in power efficiency in comparison with the unprotected system, as well as a nonnegligible gain over an alternative linearization strategy, identified as minimum mean-square-error (MMSE) predistortion, presented in the literature for application to OFDM. The relative performance of the A&P and the MMSE predistorter schemes is assessed over the additive white Gaussian noise channel and also in a frequency-selective fading environment. The impact of adjacent channel interference is also discussed.

The linearization technique known as amplitude and phase (A&P) predistortion, proposed by D'Andea et al. (1996), is applied to the OFDM transmission context with nonlinear RF high-power amplification. The above technique is shown to provide a major enhancement in power efficiency in comparison with the unprotected system, as well as a nonnegligible gain over an alternative linearization strategy, identified as minimum mean square error (MMSE) predistortion, presented by Di Benedetto and Mandarini (1995) for application to OFDM (Benedetto and Mandarino 1996). The relative performance of the A&P and the MMSE PD schemes is assessed over the AWGN channel and also in a frequency-selective fading environment.

This paper presents a novel technique for power amplifier linearization in digital microwave radio systems. The proposed technique is based on the use of a predistortion circuit, whose AM/AM and AM/PM responses are separately implemented as polynomial approximations of the respective responses of the ideal linearizer. The proposed scheme is shown to attain superior performance in comparison with other well-known predistortion structures, such as those based on the cancellation of third or fifth order distortion, with no substantial aggravation in implementation complexity.