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Time reversal (TR) recently emerged as an interesting communication technology capable of providing a good spatio-temporal signal focusing effect. New generations of large-bandwidth devices with reduced cost leverage the use of TR wideband communication systems. While TR is usually implemented in the time domain, the same benefit can be obtained in an orthogonal frequency division multiplexing (OFDM) system by precoding the information in the frequency domain. Besides using multiple antennas, the focusing effect of TR also comes from the use of a high rate back-off factor (BOF), which is the signal up-sampling (or down-sampling) rate in the original time-domain TR precoding. However, a frequency-domain TR precoding in the literature has only considered BOF of one, which does not fully exploit the focusing property of TR. In this paper, we discuss how to properly implement different BOFs using frequency-domain TR precoding in the OFDM system. Moreover, we demonstrate that increasing the BOF and/or the number of transmit antennas significantly improves the focusing gain at the intended position. In contrast, the unintended positions receive less useful power. Furthermore, closed-form approximations of the mean-square-errors (MSEs) of equalized received signals at either intended or unintended positions are derived, expressing the focusing gain as a function of the BOF and the number of antennas. Numerical simulations with multi-path channels are carried out to validate the MSE expressions., 19 pages, 6 figures

Future generations of communications systems will target a very wide range of applications. Each application comes with its own set of requirements in terms of data rate, latency, user density, reliability... Accommodating this large variety of specifications implies the need for a novel physical layer technology. In this regard, the most popular modulation nowadays, namely, the orthogonal frequency division multiplexing modulation, is characterized by a poor time-frequency localization, implying strong limitations. In the light of these limitations, communications using new waveforms, relying on more sophisticated signal processing techniques and providing improved time-frequency localization, have attracted a lot of attention for the last decade. At the same time, the higher complexity of these new waveforms, not only in terms of implementation but also conceptually, creates an entrance barrier that slows down their adoption by industries, standardization bodies and more generally in the telecommunication community. The WaveComBox toolbox, freely available at www.wavecombox.com, is a user-friendly, open-source and well documented piece of software aiming at considerably lowering the entrance barrier of recently proposed waveforms. This article first describes the general abstract structure of the toolbox. Secondly, examples are given to illustrate how to use the toolbox and to show some more advanced functionalities.

To accurately match a finite-impulse response (FIR) graph filter to a desired response, high filter orders are generally required leading to a high implementation cost. Autoregressive moving average (ARMA) graph filters can alleviate this problem but their design is more challenging. In this paper, we focus on ARMA graph filter design for a known graph. The fundamental aim of our ARMA design is to create a good match to the desired response but with less coefficients than a FIR filter. Our design methods are inspired by Prony’s method but using proper modifications to fit the design to the graph context. Compared with FIR graph filters, our ARMA graph filters show better results for the same number of coefficients.

Randomized gossip (RG) based distributed averaging has been popular for wireless sensor networks (WSNs) in multiple areas. With RG, randomly two adjacent nodes are selected to communicate and exchange information iteratively until consensus is reached. One way to improve the convergence speed of RG is to use greedy gossip with eavesdropping (GGE). Instead of randomly selecting two nodes, GGE selects the two nodes based on the maximum difference between nodes in each iteration. To further increase the convergence speed in terms of transmissions, we present in this paper a synchronous version of the GGE algorithm, called greedy gossip with synchronous communication (GGwSC). The presented algorithm allows multiple node pairs to exchange their values synchronously. Because of the selection criterion of the maximum difference between the values at the nodes, there is at least one node pair with different information, such that the relative error must be reduced after each iteration. The convergence rate in terms of the number of transmissions is demonstrated to be improved compared to GGE. Experimental results validate that the proposed GGwSC is quite e↵ective for the random geometric graph (RGG) as well as for several other special network topologies.

In this paper, we propose two time of arrival estimators for ultra wideband signals based on the phase difference between the discrete Fourier transforms (DFT) of the transmitted and received signals. The first estimator is based on the slope of the unwrapped phase and the second one on the absolute unwrapped phase. We derive the statistics of the unwrapped phase. We show that slope-based estimation almost achieves asymptotically the baseband Cramer-Rao lower bound (CRLB), while the absolute-phase-based estimator achieves asymptotically the passband CRLB. We compare the proposed estimators to the time-domain maximum likelihood estimator (MLE). We show that the MLE achieves the CRLB faster than the DFT-based estimator, while the DFT-based estimator outperforms the MLE for low signal to noise ratios. We describe also how to use the proposed estimators in multipath UWB channels.

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