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Reconfigurable intelligent surfaces (RISs) have attracted enormous interest thanks to their ability to overcome line-of-sight blockages in mmWave systems, enabling in turn accurate localization with minimal infrastructure. Less investigated…
Indoor localization is the process of determining the location of a person or object inside a building. Potential usage of indoor localization includes navigation, personalization, safety and security, and asset tracking. Commonly used…
A simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) assisted simultaneous wireless information and power transfer (SWIPT) system is proposed. More particularly, an STAR-RIS is deployed to assist in the…
This paper addresses the problem of reliable transmission of data through a sensor network. We focus on networks rapidly deployed in harsh environments. For these networks, important design requirements are fast data transmission and rapid…
Machine learning (ML) solutions to indoor localization problems have become popular in recent years due to high positioning accuracy and low cost of implementation. This paper proposes a novel local nonparametric approach for solving…
Optimal maintenance of sensor nodes in a Wireless Rechargeable Sensor Network (WRSN) requires effective scheduling of power delivery vehicles by solving the Charging Scheduling Problem (CSP). Deploying Unmanned Aerial Vehicles (UAVs) as…
This paper introduces a novel approach to efficient localization in next-generation communication systems through a base station (BS)-enabled passive beamforming utilizing beyond diagonal reconfigurable intelligent surfaces (BD-RISs).…
This paper considers a single-hop wireless network where a central node (or fusion center, FC) collects data from a set of m energy harvesting (EH) nodes (e.g. nodes of a wireless sensor network). In each time slot, k of m nodes can be…
Lightweight aerial swarms have potential applications in scenarios where larger drones fail to operate efficiently. The primary foundation for lightweight aerial swarms is efficient relative localization, which enables cooperation and…
Indoor localization systems are most commonly based on Received Signal Strength Indicator (RSSI) measurements of either WiFi or Bluetooth-Low-Energy (BLE) beacons. In such systems, the two most common techniques are trilateration and…
Radio maps (RMs) provide a spatially continuous description of wireless propagation, enabling cross-layer optimization and unifying communication and sensing for integrated sensing and communications (ISAC). However, constructing…
An increasingly important requirement for many novel applications is sensing the positions of people, equipment, etc. GPS technology has proven itself as a successfull technology for positioning in outdoor environments but indoor no…
The paper presents a distributed algorithm, called Prediction-based Opportunistic Sensing for Resilient and Efficient Sensor Networks (POSE.R), where the sensor nodes utilize predictions of the targets positions to probabilistically control…
Indoor localization has drawn much attention owing to its potential for supporting location based services. Among various indoor localization techniques, the received signal strength (RSS) based technique is widely researched. However, in…
Compression has emerged as one of the essential deep learning research topics, especially for the edge devices that have limited computation power and storage capacity. Among the main compression techniques, low-rank compression via matrix…
Increasing sources of sensor measurements and prior knowledge have become available for indoor localization on smartphones. How to effectively utilize these sources for enhancing localization accuracy is an important yet challenging…
Due to power attenuation, improving transmission efficiency in the radio-frequency (RF) band remains a significant challenge, which hinders advancements in various fields of the Internet of Things (IoT), such as wireless power transfer…
Relative localization is a crucial capability for multi-robot systems operating in GPS-denied environments. Existing approaches for multi-robot relative localization often depend on costly or short-range sensors like cameras and LiDARs.…
We present UbiSLAM, an innovative solution for real-time mapping and localization in dynamic indoor environments. By deploying a network of fixed RGB-D cameras strategically throughout the workspace, UbiSLAM addresses limitations commonly…
A novel simultaneous localization and radio mapping (SLARM) framework for communication-aware connected robots in the unknown indoor environment is proposed, where the simultaneous localization and mapping (SLAM) algorithm and the global…