The problem of bit and power loading for bit rate maximization in orthogonal frequency division multiplexing data communications over indoor powerline channels is investigated, and a simple method for bit/power allocation in half a cycle of the mains is developed. The proposed solution is based on the so-called Zadeh's representation for modeling the linear periodically time-varying behavior of powerline channels. Numerical results show the superiority of the proposed method over other solutions available in the technical literature in a real-world scenario.

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 Zadeh's 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.

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.

The discrete-time representation of a broadband powerline channel as a linear periodically time variant system poses serious problems in terms of computational complexity. In this paper we exploit the principles of the Zadeh's series expansion to devise a new discrete-time system model, characterized by a limited computational complexity and particularly suitable for an implementation on embedded programmable hardware. Then, we illustrate simple methods for estimating the parameters of the proposed model and apply them to the development of a broadband channel sounding tool for powerlines. Our experimental and numerical results show that the proposed model is able to provide a faithful representation of the periodically time varying behavior of indoor powerline channels.

The knowledge of the propagation environment can greatly improve the performance of indoor wireless localization systems, since it can be exploited to cancel out, at least to some extent, the effects of physical obstructions (e.g., walls) degrading the radio signals employed for localization. In indoor localization systems, the propagation environment can be described by maps (e.g., floor plans), which represent a valuable source of knowledge. In this paper a new map-aware statistical model for the measurements acquired in wireless localization systems based on received signal strength is proposed. Experimental results are processed to extract the parameters of the proposed model, which is then exploited to devise map-aware localization algorithms; these are capable of mitigating the non-line-of-sight bias introduced in the measurements by the obstructions modelled by the map. Our numerical results evidence that map-aware modelling can substantially improve localization accuracy in indoor scenarios with respect to map-unaware modelling.

In this paper, a novel ultrawideband system for multiuser data communications is proposed. In this system multiple users are allowed to transmit on-off keying modulated signals in the same time intervals and exploiting the same frequency subband. Time/frequency overlapped data frames sent by distinct users include low data rate training sequences characterized by different repetition periods. This transmission strategy, known as rate division multiple access in the technical literature, allows to ease two fundamental tasks at the receive side, namely joint channel estimation and timing synchronization. Channel estimates are exploited by a multiuser detector based on a zero forcing equalizer. Numerical results evidence that the proposed solution yields good error performance at the price of a limited complexity.

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.

In this paper the problem of space-time block coding for multiple-input multiple-output communication systems employing continuous phase frequency shift keying and one-shot noncoherent detection is investigated. First, the detection problem is analysed in a maximum likelihood perspective; then, design criteria for optimal space-time codes are proposed and some error bounds are derived. Finally, some numerical results are illustrated for a couple of novel space-time block codes designed on the basis of the above mentioned criteria. Such results evidence that the use of the proposed schemes can entail a limited energy loss respect to other solutions available in the technical literature for coherent systems, with the relevant advantage, however, of a simple detection algorithm.

This paper proposes a new architecture for cooperative communication in wireless ad-hoc networks particularly suitable to emergency and safety applications. The proposed solution is characterized by the following relevant features: (a) a wireless connection between each couple of network nodes is established via multiple relays; (b) each source-to-destination link is characterized by a double string topology allowing the use of specific transmit diversity techniques for reliable communications; (c) a novel utility-based and distributed routing algorithm providing a fair exploitation of the available resources is employed. Simulation results evidence that our solution offers substantial energy savings with respect to traditional ad-hoc architectures.

In this paper game theory is exploited to derive an optimal solution to the problem of cooperative data transmission based on distributed selection diversity in an ad hoc wireless network consisting of selfish nodes. First, a credit-based micro-economical model is proposed to manage node interaction; then, a transmission strategy maximizing node utility is derived. In the proposed strategy each node decides, in an autonomous fashion, whether and when transmitting data packets over a shared wireless channel. Numerical results evidence that this approach can ensure both fairness in the access to a shared medium and excellent network efficiency. In particular, it offers an higher throughput level than other communication protocols implementing selection diversity in distributed multi-antenna systems.

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.

In this paper novel reduced complexity statistical models for the representation of directional wireless channels affected by Rayleigh fading are developed. Their derivation is based on the evaluation of Fourier integrals by means of Gaussian quadrature rules (GQRs). The proposed models represent a communication channel as a tapped-angle and -delay line with non uniform spacing between successive taps. The application of the GQR approach to three different scenarios is also illustrated. Numerical results evidence that these models can provide a simple and accurate stochastic representation of directional fading channels.

In this paper novel linear and decision feedback equalization algorithms for continuous phase modulations (CPMs) are illustrated. These algorithms operate in the frequency domain and process two samples of the received signal per channel symbol. Their derivation is based on the Laurent decomposition of CPM signals. Numerical results evidence that the proposed techniques enable the use of CPMs over severely frequency selective wireless channels.

In this paper the problem of unitary rate space-time block coding for multiple-input multiple-output communication systems employing continuous phase frequency shift keying is investigated. First, one-shot noncoherent detection is analysed in a maximum likelihood perspective; then, design criteria for optimal space-time codes are proposed and some error bounds for the devised coding schemes are derived. Numerical results evidence that the use of the proposed coding schemes can entail a limited energy loss with respect to other solutions available in the technical literature for coherent systems, with the relevant advantage, however, of a simple detection algorithm

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.

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.

In this paper, a novel reduced complexity statistical models for the representation of wide sense stationary-uncorrelated scattering directional wireless channels affected by Rayleigh fading are developed. Their derivation is based on the so-called Gaussian quadrature rule approach illustrated by E. Chiavaccini and G. M. Vitetta (June 2001) for non directional channels. Numerical results evidence, that the proposed models provide a simple and accurate stochastic representation of directional fading channels.

In this work various channel equalization algorithms 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 PSK transmissions show the efficacy of the proposed equalization techniques and their superiority over other existing frequency domain equalization strategies.

In this paper novel reduced complexity statistical models for the representation of wide sense stationary-uncorrelated scattering directional wireless channels affected by Rayleigh fading are developed. Their derivation is based on the so-called Gaussian quadrature rule approach illustrated in E Chiavaccini et al. (2001). for non directional channels. Numerical results evidence that the proposed models can provide a simple and accurate stochastic representation of directional fading channels.