Related papers: The micro-Doppler Attack Against AI-based Human Ac…
When wireless communication signals impinge on a moving human they are affected by micro-Doppler. A passive receiver of the resulting signals can calculate the spectrogram that produces different signatures depending on the human activity.…
This work presents a simulation framework to generate human micro-Dopplers in WiFi based passive radar scenarios, wherein we simulate IEEE 802.11g complaint WiFi transmissions using MATLAB's WLAN toolbox and human animation models derived…
The rising demand for detecting hazardous situations has led to increased interest in radar-based human activity recognition (HAR). Conventional radar-based HAR methods predominantly rely on micro-Doppler spectrograms for recognition tasks.…
In this paper we propose a method for defending against an eavesdropper that uses a Deep Neural Network (DNN) for learning the modulation of wireless communication signals. Our method is based on manipulating the emitted waveform with the…
This paper proposes a novel low probability of intercept (LPI) waveform design approach for orthogonal frequency-division multiplexing (OFDM)-based integrated sensing and communication systems by introducing artificial phase and Doppler…
The newly established IEEE 802.11bf Task Group aims to amend the WLAN standard to support advanced sensing applications such as human activity recognition (HAR). Although studies have demonstrated the potential of sub-7 GHz Wi-Fi Channel…
Orthogonal frequency division multiplexing (OFDM) is a modulation technique susceptible to source, channel and amplifier nonlinearities because of its high peak-to-average ratio (PAPR). The distortion gets worse by increasing the average…
Automatic modulation classification (AMC) aims to improve the efficiency of crowded radio spectrums by automatically predicting the modulation constellation of wireless RF signals. Recent work has demonstrated the ability of deep learning…
This study reveals the vulnerabilities of Wireless Local Area Networks (WLAN) sensing, under the scope of joint communication and sensing (JCAS), focusing on target spoofing and deceptive jamming techniques. We use orthogonal…
We consider a wireless communication system that consists of a transmitter, a receiver, and an adversary. The transmitter transmits signals with different modulation types, while the receiver classifies its received signals to modulation…
Orthogonal Frequency Division Multiplexing (OFDM) is the dominant waveform in modern wireless systems, but suffers performance degradation in high-mobility environments due to Doppler-induced inter-carrier interference and unreliable…
Automatic Modulation Classification (AMC) is a vital component in the development of intelligent and adaptive transceivers for future wireless communication systems. Existing statistically-based blind modulation classification methods for…
Device free activity recognition and monitoring has become a promising research area with increasing public interest in pattern of life monitoring and chronic health conditions. This paper proposes a novel framework for in-home Wi-Fi…
We present a Trojan (backdoor or trapdoor) attack that targets deep learning applications in wireless communications. A deep learning classifier is considered to classify wireless signals using raw (I/Q) samples as features and modulation…
Human activity recognition (HAR) is essential in healthcare, elder care, security, and human-computer interaction. The use of precise sensor data to identify activities passively and continuously makes HAR accessible and ubiquitous.…
This paper considers human activity classification for an indoor radar system. Human motions generate nonstationary radar returns which represent Doppler and micro-Doppler signals. The time-frequency (TF) analysis of micro-Doppler signals…
Future wireless communication systems must simultaneously address multiple challenges to ensure accurate data detection, deliver high Quality of Service (QoS), adding enable a high data transmission with low system design. Additionally,…
Integrated Sensing and Communication (ISAC) will be one key feature of future 6G networks, enabling simultaneous communication and radar sensing. The radar sensing geometry of ISAC will be multistatic since that corresponds to the common…
Deep learning based automatic modulation classification (AMC) has received significant attention owing to its potential applications in both military and civilian use cases. Recently, data-driven subsampling techniques have been utilized to…
The sixth generation (6G) systems will likely employ orthogonal frequency division multiplexing (OFDM) waveform for performing the joint task of sensing and communication. In this paper, we design an OFDM system for integrated sensing and…