Fabrizio Pancaldi

Single-carrier frequency domain equalization

This paper present an alternative promising approach to ISI mitigation by the use of single-carrier (SC) modulation combined with frequency-domain equalization (FDE).

Block channel equalization in the frequency domain

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

Equalization algorithms in the frequency domain for continuous phase modulations

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

Statistical Modeling of Periodic Impulsive Noise in Indoor Power-Line Channels

In this paper, novel statistical models for the representation of the periodic impulsive noise generated by power loads connected to power grids in indoor scenarios are developed. Their derivation is based on a set of experimental results acquired in a measurement campaign and on deseasonalized autoregressive moving average modeling of cyclostationary random processes. Numerical results are evidence that the proposed models can provide an accurate stochastic representation of the periodic impulsive noise generated by specific appliances in the 1-30 MHz band, at the price of limited computational complexity.

A Novel Approach to Power-Line Channel Modeling

In this paper, a novel approach to statistical modeling of power-line channels is illustrated and its application to low-voltage indoor power networks is analyzed in the bandwidth 1-30 MHz. The proposed approach is based on the well-known bifilar model and on a generalization of the so-called N-branch network topology. It is shown that our model can be exploited to devise an efficient channel simulator predicting the mean impedance matrix and transfer function between an arbitrary couple of plugs in a class of indoor networks sharing multiple parameters (e.g., number of branches, minimum and maximum cable lengths, power-loading conditions). Finally, it is shown that Monte Carlo results generated by our simulator are in good agreement with a set of experimental data acquired in a measurement campaign.

Frequency-domain equalization for space-time block-coded systems

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

Wireless Communications: Algorithmic Techniques

This book introduces the theoretical elements at the basis of various classes of algorithms commonly employed in the physical layer (and, in part, in MAC layer) of wireless communications systems. It focuses on single user systems, so ignoring multiple access techniques. Moreover, emphasis is put on single-input single-output (SISO) systems, although some relevant topics about multiple-input multiple-output (MIMO) systems are also illustrated.Comprehensive wireless specific guide to algorithmic techniquesProvides a detailed analysis of channel equalization and channel coding for wireless applicationsUnique conceptual approach focusing in single user systemsCovers algebraic decoding, modulation techniques, channel coding and channel equalisation

Map-Aware Models for Indoor Wireless Localization Systems: An Experimental Study

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

On the Use of Zadeh's Series Expansion for Modeling and Estimation of Indoor Powerline Channels

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

A Game Theoretical Approach to the Management of Transmission Selection Scheme in Wireless Ad-Hoc Networks

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