Vincenzo Lottici

Channel estimation for ultra-wideband communications

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.

RF power amplifier linearization through amplitude and phase predistortion

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.

Turbo synchronization: an EM algorithm interpretation

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].

Code-Aided Turbo Synchronization

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-called turbo-synchronization algorithms. 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.

Multiple symbol differential detection for UWB communications

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.

Carrier phase recovery for turbo-coded linear modulations

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.

Adaptive pre- and post-compensation of nonlinear distortions for high-level data Modulations

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.

TEDS: A high speed digital mobile communication air interface for professional users

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. Multicarrier-based modulation format, powerful payload and header encoding and link adaptation methods are among techniques employed for this purpose. The above enhancements are efficiently combined with improved higher layer protocols enabling a number of new services such as multiple multimedia access with QoS re-negotiation during the session, various priority mechanisms, provision of scheduled access for delay-sensitive applications and support for sectored antenna usage. The aim of this paper is to give a comprehensive overview of the TEDS features with particular emphasis on the physical layer and medium access control features together with representative link and system performance results

Low-complexity ML timing acquisition for UWB communications in dense multipath channels

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.

Detection of sparse signals under finite-alphabet constraints

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.