Related papers: Explainable and Hardware-Efficient Jamming Detecti…
Native jamming mitigation is essential for addressing security and resilience in future 6G wireless networks. In this paper a resilient-by-design framework for effective anti-jamming in MIMO-OFDM wireless communications is introduced. A…
The proliferation of fake news, i.e., news intentionally spread for misinformation, poses a threat to individuals and society. Despite various fact-checking websites such as PolitiFact, robust detection techniques are required to deal with…
While Time-Sensitive Networking (TSN) enhances the determinism, real-time capabilities, and reliability of Ethernet, future industrial networks will not only use wired but increasingly wireless communications. Wireless networks enable…
In this paper, we tackle the challenge of jamming attacks in Ultra-Reliable Low Latency Communication (URLLC) within Non-Orthogonal Multiple Access (NOMA)-based 5G networks under Finite Blocklength (FBL) conditions. We introduce an…
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…
Diagnosis of bearing faults is paramount to reducing maintenance costs and operational breakdowns. Bearing faults are primary contributors to machine vibrations, and analyzing their signal morphology offers insights into their health…
Using finite-state machines to learn patterns, Tsetlin machines (TMs) have obtained competitive accuracy and learning speed across several benchmarks, with frugal memory- and energy footprint. A TM represents patterns as conjunctive clauses…
Remote patient monitoring is crucial in modern healthcare, but current systems struggle with real-time analysis and prediction of vital signs. This paper presents a novel architecture combining deep learning with 5G network capabilities to…
Cognitive radio is an intelligent and adaptive radio that improves the utilization of the spectrum by its opportunistic sharing. However, it is inherently vulnerable to primary user emulation and jamming attacks that degrade the spectrum…
In millimeter-wave (MMW) multiple-input multiple-output (MIMO) communications, users and their corresponding base station (BS) have to align their beam during both initial access and data transmissions to compensate for the high propagation…
The Tsetlin Machine (TM) is a recent machine learning algorithm with several distinct properties, such as interpretability, simplicity, and hardware-friendliness. Although numerous empirical evaluations report on its performance, the…
Convolutional Neural Networks are extensively used in a wide range of applications, commonly including computer vision tasks like image and video classification, recognition, and segmentation. Recent research results demonstrate that…
In this paper, we investigate the problem of jamming detection and channel estimation during multi-user uplink beam training under random pilot jamming attacks in beamspace massive multi-input-multi-output (MIMO) systems. For jamming…
The Tsetlin Machine (TM) is a machine learning algorithm founded on the classical Tsetlin Automaton (TA) and game theory. It further leverages frequent pattern mining and resource allocation principles to extract common patterns in the…
This paper investigates the application of fast-convolution (FC) filtering schemes for flexible and effective waveform generation and processing in the fifth generation (5G) systems. FC-based filtering is presented as a generic multimode…
This paper deals with the design of non-coherent jamming strategies capable of ensuring spectral compatibility with friendly radio frequency (RF) emitters. The goal is achieved via a cognitive approach, which, after recognizing the presence…
Accurate and adaptive network throughput prediction is essential for latency-sensitive and bandwidth-intensive applications in 5G and emerging 6G networks. However, most existing methods rely on centralized training with uniformly collected…
Suppressing the deliberate interference for wireless networks is critical to guarantee a reliable communication link. However, nullifying the jamming signals can be problematic when the correlations between transmitted jamming signals are…
Personalized ubiquitous healthcare solutions require energy-efficient wearable platforms that provide an accurate classification of bio-signals while consuming low average power for long-term battery-operated use. Single lead…
We study jamming of an OFDM-modulated signal which employs forward error correction coding. We extend this to leverage reinforcement learning with a contextual bandit to jam a 5G-based system implementing some aspects of the 5G protocol.…