Andrea M. Tonello

Space-time bit-interleaved coded modulation with an iterative decoding strategy

A space-time coding approach for wireless communications deploying multiple transmit and multiple receive antennas is presented. The approach is based on the concatenation of a convolutional encoder, a bit interleaver, and a space-time signal constellation mapper that combines multi-level/phase modulation with multiple transmit antennas. The decoding strategy follows an iterative (turbo-like) algorithm where soft information is exchanged between a soft-in soft-out demapper and a soft-in soft-out convolutional decoder. It is applicable with one or more receive antennas, and shows that spectral efficient/reliable communications are possible with few iterations. We address the performance analysis in both block and fast flat Rayleigh fading in order to provide insight into the space-time code construction criteria for the approach that we propose. Finally, simulation results are reported for schemes with 2 bits/s/Hz and 4 bits/s/Hz.

Analysis of the uplink of an asynchronous multi-user DMT OFDMA system impaired by time offsets, frequency offsets, and multi-path fading

We study through analysis the joint effect of time offsets, frequency offsets, and multi-path fading in the uplink of an asynchronous multi-user system for wireless communications deploying discrete multi-tone modulation and demodulation. We derive analytical expressions for the multiple access interference, and we quantify its detrimental effects through the evaluation of both the average SINR, and the symbol-error-rate performance. As a result it is shown that the MAI strongly depends not only on the aforementioned impairments but also on the tone assignment algorithm used to multiplex the users. Based on our analysis, the insertion of appropriate time and frequency guard intervals and the accurate selection of the tone assignment algorithm effectively reduce the MAI, so that a proper trade off with spectral efficiency can be met to optimize system performance.

Bottom-Up Statistical PLC Channel Modeling—Part I: Random Topology Model and Efficient Transfer Function Computation

We propose an efficient bottom-up power-line communication (PLC) channel simulator that exploits transmission-line theory concepts and that is able to generate statistically representative in-home channels. We first derive from norms and practices a statistical model of European in-home topologies. The model describes how outlets are arranged in a topology and are interconnected via intermediate nodes referred to as derivation boxes. Then, we present an efficient method to compute the channel transfer function between any pair of outlets belonging to a topology realization. The method is based on a systematic remapping technique that leads to the subdivision of the network in elementary units, and on an efficient way to compute the unit transfer function referred to as the voltage ratio approach. The difference from the more conventional and complex ABCD matrix approach is also discussed. We finally show that the simulator can be configured with a small set of parameters and that it offers a theoretical framework to study the statistical PLC channel properties as a function of the topology characteristics, which is discussed in Part II of this work.

Improved Nyquist pulses

In this letter, we propose two new Nyquist (intersymbol interference free) pulses that exhibit better error probability performance in the presence of sampling errors than the popular raised-cosine and a recently proposed pulse by Beaulieu, Tan, and Damen. The new pulses are also robust to the root and truncation operations.

Wideband Impulse Modulation and Receiver Algorithms for Multiuser Power Line Communications

We consider a bit-interleaved coded wideband impulse-modulated system for power line communications. Impulse modulation is combined with direct-sequence code-division multiple access (DS-CDMA) to obtain a form of orthogonal modulation and to multiplex the users. We focus on the receiver signal processing algorithms and derive a maximum likelihood frequency-domain detector that takes into account the presence of impulse noise as well as the intercode interference (ICI) and the multiple-access interference (MAI) that are generated by the frequency-selective power line channel. To reduce complexity, we propose several simplified frequency-domain receiver algorithms with different complexity and performance. We address the problem of the practical estimation of the channel frequency response as well as the estimation of the correlation of the ICI-MAI-plus-noise that is needed in the detection metric. To improve the estimators performance, a simple hard feedback from the channel decoder is also used. Simulation results show that the scheme provides robust performance as a result of spreading the symbol energy both in frequency (through the wideband pulse) and in time (through the spreading code and the bit-interleaved convolutional code).

Bottom-Up Statistical PLC Channel Modeling—Part II: Inferring the Statistics

We investigate the statistical behavior of power-line communication (PLC) channels. It is inferred from the results obtained with a statistical bottom-up channel simulator (described in Part I of this paper) that uses an in-home topology model derived from the observation of wiring practices and norms. It computes channel transfer functions via the application of transmission-line theory. The comprehensive study includes the analysis of the statistics of the path-loss profile, the average channel gain, the root-mean-square delay spread, and the channel capacity. We highlight the dependency on topological information as the network layout area, the intensity of outlets, the backbone length, etc. We furthermore propose a channel classification based either on average capacity or topological information (e.g., the belonging of outlets to rooms served by the same derivation box). We show that the developed channel simulator constitutes a powerful theoretical framework for the generation and analysis of statistically representative channels with a strong connection to physical reality and close match to the results obtained in the measurements campaigns.

An MTL Theory Approach for the Simulation of MIMO Power-Line Communication Channels

We propose a bottom-up power-line communication (PLC) channel simulator for networks that deploy multiconductor cables and enable establishing a multiple-input multiple-output (MIMO) communication link between two nodes. We show that the fundamental multiconductor transmission-line (MTL) relations are a matrix form extension of the two-conductor transmission-line equations, and that they allow the application of the voltage ratio approach for the computation of the channel transfer function (CTF). Thus, any complex network can be remapped to obtain a simple representation in terms of MTL elementary units. Then, the MIMO CTF is computed as the product of the insertion loss of the units. We discuss the analytical computation of the per-unit-length (p.u.l.) parameters for two electrical cables, that we refer to as symmetric and ribbon. Further, we propose using an improved cable model for ribbon cables that accounts for the dielectric nonuniformity. We report the comparison between simulation and experimental measures for two test networks. The results are in good agreement. This validates the proposed MIMO PLC channel simulation approach.

A Fitting Algorithm for Random Modeling the PLC Channel

The characteristics of the power-line communication (PLC) channel are difficult to model due to the heterogeneity of the networks and the lack of common wiring practices. To obtain the full variability of the PLC channel, random channel generators are of great importance for the design and testing of communication algorithms. In this respect, we propose a random channel generator that is based on the top-down approach. Basically, we describe the multipath propagation and the coupling effects with an analytical model. We introduce the variability into a restricted set of parameters and, finally, we fit the model to a set of measured channels. The proposed model enables a closed-form description of both the mean path-loss profile and the statistical correlation function of the channel frequency response. As an example of application, we apply the procedure to a set of in-home measured channels in the band 2-100 MHz whose statistics are available in the literature. The measured channels are divided into nine classes according to their channel capacity. We provide the parameters for the random generation of channels for all nine classes, and we show that the results are consistent with the experimental ones. Finally, we merge the classes to capture the entire heterogeneity of in-home PLC channels. In detail, we introduce the class occurrence probability, and we present a random channel generator that targets the ensemble of all nine classes. The statistics of the composite set of channels are also studied, and they are compared to the results of experimental measurement campaigns in the literature.

MIMO MAP equalization and turbo decoding in interleaved space-time coded systems

Decoding of space-time codes in frequency-selective fading channels is considered. The approach is based on iterative soft-in soft-out equalization and decoding. It is applicable to space-time coded systems that deploy symbol/bit interleavers. We focus on the equalization stage by extending the Ungerboeck equalizer formulation to a multiple-input multiple-output time-variant channel. The resulting structure comprises a bank of matched filters, followed by an a posteriori probabilities calculator that runs the Bahl-Cocke-Jelinek-Raviv/maximum a posteriori algorithm with an appropriate metric. Simulation results are reported for space-time bit-interleaved codes designed over the enhanced data rates for GSM evolution (EDGE) air interface.

GREEND: An energy consumption dataset of households in Italy and Austria

Home energy management systems can be used to monitor and optimize consumption and local production from renewable energy. To assess solutions before their deployment, researchers and designers of those systems demand for energy consumption datasets. In this paper, we present the GREEND dataset, containing detailed power usage information obtained through a measurement campaign in households in Austria and Italy. We provide a description of consumption scenarios and discuss design choices for the sensing infrastructure. Finally, we benchmark the dataset with state-of-the-art techniques in load disaggregation, occupancy detection and appliance usage mining.