Related papers: Rate-Distributed Spatial Filtering Based Noise Red…
In this article we consider the problems of distributed detection and estimation in wireless sensor networks. In the first part, we provide a general framework aimed to show how an efficient design of a sensor network requires a joint…
In this paper we study the problem of distributed estimation of a Gaussian vector with linear observation model in a wireless sensor network (WSN) consisting of K sensors that transmit their modulated quantized observations over orthogonal…
Wireless sensor networks consist of sensor nodes that are physically distributed over different locations. Spatial filtering procedures exploit the spatial correlation across these sensor signals to fuse them into a filtered signal…
We study a wireless ad-hoc sensor network (WASN) where $N$ sensors gather data from the surrounding environment and transmit their sensed information to $M$ fusion centers (FCs) via multi-hop wireless communications. This node deployment…
As IoT-based wireless sensor networks (WSNs) become more prevalent, the issue of energy shortages becomes more pressing. One potential solution is the use of wireless power transfer (WPT) technology, which is the key to building a new shape…
A wireless sensor network often relies on a fusion center to process the data collected by each of its sensing nodes. Such an approach relies on the continuous transmission of raw data to the fusion center, which typically has a major…
This work studies inference-based resource allocation in ultra low-power, large-scale backscatter sensor networks (BSNs). Several ultra-low cost and power sensor devices (tags) are illuminated by a carrier and reflect the measured…
This paper investigates the problem of the minimilization of energy consumption in reallocation of wireless mobile sensors network (WMSN) to assure good communication without interference. Fix $d\in\mathbb{N}\setminus\{0\}.$ Assume $n$…
In this work, we consider the task of target localization using quantized data in Wireless Sensor Networks (WSNs). We propose an energy efficient localization scheme by modeling it as an iterative classification problem. We design coding…
Estimation problems in wireless sensor networks typically involve gathering and processing data from distributed sensors to infer the state of an environment at the fusion center. However, not all measurements contribute significantly to…
Wireless sensor networks (WSNs) are emerging as an effective means for environment monitoring. This paper investigates a strategy for energy efficient monitoring in WSNs that partitions the sensors into covers, and then activates the covers…
Wireless Sensor Network WSN is consisted of nodes with different sizes and a specific goal. Tracking applications are very important in WSNs. This study proposes a method for reducing energy consumption in WSNs, considering target tracking.…
Energy efficiency is a crucial performance metric in sensor networks, directly determining the network lifetime. Consequently, a key factor in WSN is to improve overall energy efficiency to extend the network lifetime. Although many…
This letter introduces weighted sum power (WSP), a new performance metric for wireless resource allocation during cooperative spectrum sharing in cognitive radio networks, where the primary and secondary nodes have different priorities and…
Wireless Sensor Networks (WSNs) is an emerging technology in several application domains, ranging from urban surveillance to environmental and structural monitoring. Computational Intelligence (CI) techniques are particularly suitable for…
Most studies that consider the problem of estimating the location of a point source in wireless sensor networks assume that the source location is estimated by a set of spatially distributed sensors, whose locations are fixed. Motivated by…
Wireless devices need spectrum to communicate. With the increase in the number of devices competing for the same spectrum, it has become nearly impossible to support the throughput requirements of all the devices through current spectrum…
Deep learning-based sound event localization and classification is an emerging research area within wireless acoustic sensor networks. However, current methods for sound event localization and classification typically rely on a single…
This paper presents a data compression algorithm with error bound guarantee for wireless sensor networks (WSNs) using compressing neural networks. The proposed algorithm minimizes data congestion and reduces energy consumption by exploring…
Wireless Sensor Network (WSN) is an attractive choice for a variety of applications as no wired infrastructure is needed. Other wireless networks are not as energy constrained as WSNs, because they may be plugged into the mains supply or…