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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…
RF sensor networks are wireless networks that can localize and track people (or targets) without needing them to carry or wear any electronic device. They use the change in the received signal strength (RSS) of the links due to the…
Time-of-flight, i.e., the time incurred by a signal to travel from transmitter to receiver, is perhaps the most intuitive way to measure distances using wireless signals. It is used in major positioning systems such as GPS, RADAR, and…
Real-time frequency measurement for non-repetitive and statistically rare signals are challenging problems in the electronic measurement area, which places high demands on the bandwidth, sampling rate, data processing and transmission…
A novel cross-domain attentional multi-task architecture - xDom - for robust real-world wireless radio frequency (RF) fingerprinting is presented in this work. To the best of our knowledge, this is the first time such comprehensive…
Neural nets are a powerful method for the classification of radio signals in the electromagnetic spectrum. These neural nets are often trained with synthetically generated data due to the lack of diverse and plentiful real RF data. However,…
mmWave radars have recently gathered significant attention as a means to track human movement within indoor environments. Widely adopted Kalman filter tracking methods experience performance degradation when the underlying movement is…
Federated Learning (FL) has evolved as a promising technique to handle distributed machine learning across edge devices. A single neural network (NN) that optimises a global objective is generally learned in most work in FL, which could be…
This paper addresses a critical preliminary step in radar signal processing: detecting the presence of a radar signal and robustly estimating its bandwidth. Existing methods which are largely statistical feature-based approaches face…
High-accuracy positioning has gained significant interest for many use-cases across various domains such as industrial internet of things (IIoT), healthcare and entertainment. Radio frequency (RF) measurements are widely utilized for user…
Finetuning wireless receivers to a specific deployment scenario can yield significant error-rate performance improvements without increasing processing complexity. However, site-specific finetuning has so far only been demonstrated on…
Radio-frequency (RF) impairments, that exist intimately in wireless communications systems, can severely degrade the performance of traditional multiple-input multiple-output (MIMO) systems. Although compensation schemes can cancel out part…
The FMCW radars are widely used for automotive radar systems. The basic idea for FMCW radars is to generate a linear frequency ramp as transmit signal. The difference frequency, (i.e., beat frequency) between the transmitted and received…
Monitoring Wireless Sensor Networks (WSNs) are composed of sensor nodes that report temperature, relative humidity, and other environmental parameters. The time between two successive measurements is a critical parameter to set during the…
In this paper we develop a new technique for estimating fine clock errors and range between two nodes simultaneously by two-way time-of-arrival measurements us- ing impulse-radio ultra-wideband signals. Estimators for clock parameters and…
Recently, location-based services (LBS) have steered attention to indoor positioning systems (IPS). WLAN-based IPSs relying on received signal strength (RSS) measurements such as fingerprinting are gaining popularity due to proven high…
This study demonstrates a WiFi indoor positioning system using Deep Learning algorithms. A new method using fitting function in MATLAB will be utilized to compute the path loss coefficient and log-normal fading variance. To reduce the…
Remote physiological measurement (RPM) has emerged as a promising non-invasive method for monitoring physiological signals using the non-contact device. Although various domain adaptation and generalization methods were proposed to promote…
The main challenge in wireless sensor network is to improve the fault tolerance of each node and also provide an energy efficient fast data routing service. In this paper we propose an energy efficient node fault diagnosis and recovery for…
As positioning solutions integrate multiple components to improve accuracy, the number of parameters that require calibration has increased. This paper studies a calibration-free positioning technique using Wi-Fi ranging and pedestrian dead…