Related papers: Narrowband Interference Detection via Deep Learnin…
Noise is the major problem while working with wireless LAN. In this paper we analyze the noise by using active receiving antenna and also propose the detection mechanism based on RF energy duration. The standard back off mechanism of 802.11…
We present a method for separating collided signals from multiple users in the presence of strong and wideband interference/jamming signal. More specifically, we consider a massive connectivity setup where few, out of a large number of…
The future Six-Generation (6G) envisions massive access of wireless devices in the network, leading to more serious interference from concurrent transmissions between wireless devices in the same frequency band. Existing interference…
Security threats such as jamming and route manipulation can have significant consequences on the performance of modern wireless networks. To increase the efficacy and stealthiness of such threats, a number of extremely challenging,…
Wireless networks are vulnerable to jamming attacks due to the shared communication medium, which can severely degrade performance and disrupt services. Despite extensive research, current jamming detection methods often rely on simulated…
Deep Neural Networks (DNNs) are notoriously vulnerable to adversarial input designs with limited noise budgets. While numerous successful attacks with subtle modifications to original input have been proposed, defense techniques against…
The idea of ultra-wideband (UWB) communications for short ranges (up to a few tens of meters) has been around for nearly three decades. However, despite significant efforts by the industry, UWB deployment has not yet reached its predicted…
Detection of radar signals without assistance from the radar transmitter is a crucial requirement for emerging and future shared-spectrum wireless networks like Citizens Broadband Radio Service (CBRS). In this paper, we propose a supervised…
Wireless sensor networks (WSNs) have great practical importance for surveillance systems to perform monitoring by acquiring and sending information on any intrusion in a secured area. Requirement of very little human intervention is one of…
Future wireless multiple-input multiple-output (MIMO) systems will integrate both sub-6 GHz and millimeter wave (mmWave) frequency bands to meet the growing demands for high data rates. MIMO link establishment typically requires accurate…
Recently, deep learning (DL) has been emerging as a promising approach for channel estimation and signal detection in wireless communications. The majority of the existing studies investigating the use of DL techniques in this domain focus…
Towards sixth-generation networks (6G), satellite communication systems, especially based on Low Earth Orbit (LEO) networks, become promising due to their unique and comprehensive capabilities. These advantages are accompanied by a variety…
Sensing will be an important service of future wireless networks to assist innovative applications such as autonomous driving and environment monitoring. Perceptive mobile networks (PMNs) were proposed to add sensing capability to current…
The unlicensed spectrum has been utilized to make up the shortage on frequency spectrum in new radio (NR) systems. To fully exploit the advantages brought by the unlicensed bands, one of the key issues is to guarantee the fair coexistence…
Given the increased growing of Internet of Things networks and their presence in critical aspects of human activities, the security of devices connected to these networks becomes critical. Machine Learning approaches are becoming prominent…
As wireless systems grow rapidly worldwide, one of the most important things, wireless systems designers and service providers faces is interference. Interference decreases coverage, capacity [1], and limits the effectiveness of both new…
Wireless jamming identification, which detects and classifies electromagnetic jamming from non-cooperative devices, is crucial for emerging low-altitude wireless networks consisting of many drone terminals that are highly susceptible to…
The current state of the art on jamming detection relies on link-layer metrics. A few examples are the bit-error-rate (BER), the packet delivery ratio, the throughput, and the increase in the signal-to-noise ratio (SNR). As a result, these…
In the global navigation satellite system (GNSS), identifying not only single but also compound jamming signals is crucial for ensuring reliable navigation and positioning, particularly in future wireless communication scenarios such as the…
Machine learning finds rich applications in Internet of Things (IoT) networks such as information retrieval, traffic management, spectrum sensing, and signal authentication. While there is a surge of interest to understand the security…