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Fingerprinting Localization Solutions (FPSs) enjoy huge popularity due to their good performance and minimal environment information requirement. Considered as a data-driven approach, many modern data analytics can be used to improve its performance. In this paper, we propose tow learning algorithms, namely a deep learning architecture for regression and Support Vector Machine (SVM) for classification,...
In this paper we study the performance bound of a wireless sensor network which is capable of estimating the true values of several active targets. We assume that sensors can observe each target separately, assuming either targets are orthogonal in frequency or physically distinguishable. The aforementioned assumption is of practical relevance for targets with different physical nature, e.g., heat,...
In this paper we present optimal power allocation, together with optimal linear signal fusion, considering a passive distributed radar sensor network system. The goal of a passive distributed radar is to obtain a reliable estimation from a source signal, by collecting and combining the individual observations from the network of sensor nodes (SN)s in a fusion center (FC). In this respect, a linear...
Since in emergency zones the communication network has to be rapidly established, the usage of autonomous drones, forming an ad-hoc network, is an interesting alternative. By using the mentioned drones, the main technical challenge to face is the difficulty of powering the drones for a long service time, having in mind that they are not wired to any infrastructure and the batteries are not designed...
With the abundance of mobile connected devices and coexisting networks, localization solutions are inevitably subject to interference. In this paper, effects of interference on the performance of Fingerprinting Localization Algorithms (FPS) are studied both theoretically and through experimentation. The previously introduced theoretical framework based on Hypothesis Testing (HT) problem is employed...
This paper presents a model and some simulations of vehicle-to-pedestrian/infrastructure (V2P/I) communication channel performances at the seaport, whereas vehicles are taken as front-lifts and pedestrians as on port workers. More precisely, the aim of the paper is to study the important radio channel features between end nodes in order to optimize the network deployment and, at the same time, to...
The increasing penetration of measurement and communication infrastructures in power grids has led to the development of new applications and use cases in the utility sector, such as demand side management and virtual power plants. The success of such applications, however, depends on a proper interplay of the underlying communication network and the power grid. For this reason, integrated planning...
Spectrum sensing is a crucial component of opportunistic spectrum access schemes, which aim at improving spectrum utilization by allowing for the reuse of idle licensed spectrum. Sensing a spectral band before using it makes sure the legitimate users are not disturbed. To that end, a number of different spectrum sensing method have been developed in the literature. Cyclostationary detection is a particular...
Various spectrum sensing approaches have been shown to suffer from a so-called signal-to-noise ratio (SNR)-wall, an SNR value below which a detector cannot perform robustly no matter how many observations are used. Up to now, the eigenvalue-based maximum-minimum-eigenvalue (MME) detector has been a notable exception. For instance, the model uncertainty of imperfect knowledge of the receiver noise...
In this paper, the channel-aware optimal location algorithm for the data concentrator unit placement in smart grid systems is proposed. The M/M/1/K queuing model is adopted for analyzing the averaged throughput and delay. The optimization algorithm based on a minimum hop count approach with the acceptable averaged throughput and delay constraints, and the optimal DCU localization methodology are proposed...
The censored channel is one of the fundamental channels in information theory, which belongs to the class of non-linear channels. It is modeled by cascading an additive noise channel with a clipping operator. This paper is concerned with the information theoretic capacity of this channel. A necessary and sufficient condition for optimality of the input distribution is derived and it is shown that...
The paper proposes vehicular communication principles in order to increase workers and pedestrians crossroads safety at the seaport. A hybrid environment-based approach for modeling the vehicular communication channel is used. It is based on a combination of a deterministic ray-launching algorithm (PIROPA) to model large-scale parameters, and a stochastic model to obtain small-scale ones. Simulation...
In this paper we address a worst-case weighted sum rate maximization problem for a full-duplex (FD) and point-to-point (P2P) system. The effects of channel-state information (CSI) error, as well as the signal distortion due to hardware impairments are jointly taken into account. Due to the intractable structure of the resulting problem, a weighted minimum mean squared error (WMMSE) method is applied...
This paper introduces a multi-level cooperative scheme for autonomous vehicles, using the sensors equipped on-board and a communication scheme with the deployed infrastructures. The proposed model focuses on the communication elements, delving into the cooperative aspect between the network components. The first level of the proposed scheme is composed of a multi-sensor data fusion framework using...
In this paper we address a sum secrecy rate maximization problem for a multi-carrier and MIMO communication system. We consider the case that the receiver is capable of full-duplex (FD) operation and simultaneously sends jamming signal to a potential eavesdropper. In particular, we simultaneously take advantage of the spatial and frequency diversity in the system in order to obtain a higher level...
We present a real-time TDOA localization testbed utilizing software defined radio and GPS based synchronization. A distributed software stack enables the localization of unknown signals by transporting the recorded baseband samples of several sensors over a backhaul network for centralized signal processing in a fusion center. To overcome the relatively large drifts of synchronization signals provided...
Given any $J\times J\,\,(J>3)$ square matrix over $\textbf {Z}_{P}$ such that the differences of any two row vectors contain each element in $\textbf {Z}_{P}$ at most once, a class of $(3,L)$ -regular quasi-cyclic low-density parity-check codes is explicitly constructed with lengths $PJL^{2}$ and girth 12, where $L$ is any integer satisfying $3<L\leq J$ . Simulation results show...
We present a novel algorithm for self-localization in sensor networks without any prior knowledge on the locations of the sensors. We assume that all sensors in the network can receive and transmit, thus we obtain time difference of arrival measurements for all combinations of sensors. Using the full set of these differences in arrival times in the network we are able to obtain the relative location...
So called hinge functions play an important role in many applications, e.g., deep learning, support vector machines, regression, classification and others. A thorough theory, which explains why some of these applications are so successful for their respective purpose, is still missing. This paper aims at filling a knowledge gap by answering the question of how much information can be conveyed across...
In this paper, we consider one-bit output quantization of an amplitude bounded input-signal subject to arbitrary additive noise. Capacity is then represented in various ways, each demonstrating that finding the optimum quantization threshold q is an extremely difficult problem. For a class of noise distributions, of which a typical representative is the uniform distribution, it is shown that the optimum...
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