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Bearing measurements,as the most common modality in nature, have recently gained traction in multi-robot systems to enhance mutual localization and swarm collaboration. Despite their advantages, challenges such as sensory noise, obstacle…
We provide a theoretical algorithm for checking local optimality and escaping saddles at nondifferentiable points of empirical risks of two-layer ReLU networks. Our algorithm receives any parameter value and returns: local minimum,…
The world is moving towards faster data transformation with more efficient localization of a user being the preliminary requirement. This work investigates the use of a deep learning technique for wireless localization, considering both…
This paper addresses a detection problem where several spatially distributed sensors independently observe a time-inhomogeneous stochastic process. The task is to decide between two hypotheses regarding the statistics of the observed…
One of the major issues in Wireless Body Area Sensor Networks (WBASNs) is efficient localization. There are various techniques for indoor and outdoor environments to locate a person. This study evaluating and compares performance of…
Localization of a wireless mobile device or a robot in indoor and GPS-denied environments is a difficult problem, particularly in dynamic scenarios where traditional cameras and LIDAR-based alternative sensing and localization modalities…
Wireless Sensor Networks (WSN) support data collection and distributed data processing by means of very small sensing devices that are easy to tamper and cloning: therefore classical security solutions based on access control and strong…
The reliability of information in participatory sensing (PS) systems largely depends on the accuracy of the location of the participating users. However, existing PS applications are not able to efficiently validate the position of users in…
In this paper, localization using narrowband communication signals are considered in the presence of fading channels with time of arrival measurements. When narrowband signals are used for localization, due to existing hardware constraints,…
Visual place recognition techniques based on deep learning, which have imposed themselves as the state-of-the-art in recent years, do not generalize well to environments visually different from the training set. Thus, to achieve top…
Unmanned Aerial Vehicles (UAVs) are suited as cost-effective and adaptable platforms for carrying Wi-Fi Access Points (APs) and cellular Base Stations (BSs). Implementing aerial networks in disaster management scenarios and crowded areas…
This study considers a UAV-assisted multi-user massive multiple-input multiple-output (MU-mMIMO) systems, where a decode-and-forward (DF) relay in the form of an unmanned aerial vehicle (UAV) facilitates the transmission of multiple data…
A neural network (NN)-based approach for indoor localization via cellular long-term evolution (LTE) signals is proposed. The approach estimates, from the channel impulse response (CIR), the range between an LTE eNodeB and a receiver. A…
Accurate wireless localization underpins applications from autonomous systems to smart infrastructure. We study the mean-squared error (MSE) and conditional MSE (CMSE) of a practical fusion-based estimator in d-dimensional, stationary…
This paper studies a networked sensing system with multiple base stations (BSs), which collaboratively sense the unknown and random three-dimensional (3D) location of a target based on the target-reflected echo signals received at the BSs.…
This paper investigates a machine learning-based power allocation design for secure transmission in a cognitive radio (CR) network. In particular, a neural network (NN)-based approach is proposed to maximize the secrecy rate of the…
In the Wireless Localization Matching Problem (WLMP) the challenge is to match pieces of equipment with a set of candidate locations based on wireless signal measurements taken by the pieces of equipment. This challenge is complicated by…
In many signal processing applications, including communications, sonar, radar, and localization, a fundamental problem is the detection of a signal of interest in background noise, known as signal detection [1] [2]. A simple version of…
Accurate and ubiquitous localization is crucial for a variety of applications such as logistics, navigation, intelligent transport, monitoring, control, and also for the benefit of communications. Exploiting millimeter-wave (mmWave) signals…
As the increase in satellite number and variety, satellite ground stations should be required to offer user services in a flexible and efficient manner. Network function virtualization (NFV) can provide a new paradigm to allocate network…