1,063 research outputs found
Hybrid analog-digital processing system for amplitude-monopulse RSSI-based MiMo wifi direction-of-arrival estimation
We present a cost-effective hybrid analog digital system to estimate the Direction of Arrival (DoA) of WiFi signals. The processing in the analog domain is based on simple wellknown RADAR amplitude monopulse antenna techniques. Then, using the RSSI (Received Signal Strength Indicator) delivered by commercial MiMo WiFi cards, the DoA is estimated using the socalled digital monopulse function. Due to the hybrid analog digital architecture, the digital processing is extremely simple, so that DoA estimation is performed without using IQ data from specific hardware. The simplicity and robustness of the proposed hybrid analog digital MiMo architecture is demonstrated for the ISM 2.45GHz WiFi band. Also, the limitations with respect to multipath effects are studied in detail. As a proof of concept, an array of two MiMo WiFi DoA monopulse readers are distributed to localize the two-dimensional position of WiFi devices. This costeffective hybrid solution can be applied to all WiFi standards and other IoT narrowband radio protocols, such us Bluetooth Low Energy or Zigbee.This work was supported in part by the Spanish National Projects TEC2016-75934-C4-4-R, TEC2016-76465-C2-1-R and in part by Regional Seneca Project 19494/PI/14
SoK: Inference Attacks and Defenses in Human-Centered Wireless Sensing
Human-centered wireless sensing aims to understand the fine-grained
environment and activities of a human using the diverse wireless signals around
her. The wireless sensing community has demonstrated the superiority of such
techniques in many applications such as smart homes, human-computer
interactions, and smart cities. Like many other technologies, wireless sensing
is also a double-edged sword. While the sensed information about a human can be
used for many good purposes such as enhancing life quality, an adversary can
also abuse it to steal private information about the human (e.g., location,
living habits, and behavioral biometric characteristics). However, the
literature lacks a systematic understanding of the privacy vulnerabilities of
wireless sensing and the defenses against them.
In this work, we aim to bridge this gap. First, we propose a framework to
systematize wireless sensing-based inference attacks. Our framework consists of
three key steps: deploying a sniffing device, sniffing wireless signals, and
inferring private information. Our framework can be used to guide the design of
new inference attacks since different attacks can instantiate these three steps
differently. Second, we propose a defense-in-depth framework to systematize
defenses against such inference attacks. The prevention component of our
framework aims to prevent inference attacks via obfuscating the wireless
signals around a human, while the detection component aims to detect and
respond to attacks. Third, based on our attack and defense frameworks, we
identify gaps in the existing literature and discuss future research
directions
Passive Respiration Detection via mmWave Communication Signal Under Interference
Recent research has highlighted the detection of human respiration rate using
commodity WiFi devices. Nevertheless, these devices encounter challenges in
accurately discerning human respiration amidst the prevailing human motion
interference encountered in daily life. To tackle this predicament, this paper
introduces a passive sensing and communication system designed specifically for
respiration detection in the presence of robust human motion interference.
Operating within the 60.48 GHz band, the proposed system aims to detect human
respiration even when confronted with substantial human motion interference
within close proximity. Subsequently, a neural network is trained using the
collected data by us to enable human respiration detection. The experimental
results demonstrate a consistently high accuracy rate over 90\% of the human
respiration detection under interference, given an adequate sensing duration.
Finally, an empirical model is derived analytically to achieve the respiratory
rate counting in 10 seconds.Comment: Submitted to WCNC2024 Worksho
Millimeter Wave Communications
Millimeter wave (mmWave) technologies promise to revolutionize wireless networks by enabling multi-gigabit data rates. However, they suffer from high attenuation, and hence have to use highly directional antennas to focus their power on the receiver. Existing radios have to scan the space to find the best alignment between the transmitter’s and receiver’s beams, a process that takes up to a few seconds. This delay is problematic in a network setting where the base station needs to quickly switch between users and accommodate mobile clients.
We present Agile-Link, the first mmWave beam steering system that is demonstrated to find the correct beam alignment without scanning the space. Instead of scanning, Agile- Link hashes the beam directions using a few carefully chosen hash functions. It then identifies the correct alignment by tracking how the energy changes across different hash functions. Our results show that Agile-Link reduces beam steering delay by orders of magnitude.National Science Foundation (U.S.
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