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Woojae Jeong, Jinhwan Jung (KAIST); Yuanda Wang (Michigan State University); Shuai Wang (George Mason University); Seokwon Yang (KAIST); Qiben Yan (Michigan State University); Yung Yi, Song Min Kim (KAIST)
With the explosive increase in wireless devices, physical-layer signal analysis has become critically beneficial across distinctive domains including interference minimization in network planning, security and privacy (e.g., drone and spycam detection), and mobile health with remote sensing. While SDR is known to be highly effective in realizing such services, they are rarely deployed or used by the end-users due to the costly hardware∼1K USD (e.g., USRP). Low-cost SDRs (e.g., RTL-SDR) are available, but their bandwidth is limited to 2-3 MHz and operation range falls well below 2.4 GHz – the unlicensed band holding majority of the wireless devices. This paper presents SDR-Lite, the first zero-cost, software-only soft-ware defined radio (SDR) receiver that empowers commodity WiFi to retrieve the In-phase and Quadrature of an ambient signal. With the full compatibility to pervasively-deployed WiFi infrastructure (without any change to the hardware and firmware), SDR-Lite aims to spread the blessing of SDR receiver functionalities to billions of WiFi users and households to enhance our everyday lives. The key idea of SDR-Lite is to trick WiFi to begin packet reception (i.e., the decoding process) when the packet is absent, so that it accepts ambient signals in the air and outputs corresponding bits. The bits are then reconstructed to the original physical-layer waveform, on which diverse SDR applications are performed. Our comprehensive evaluation shows that the reconstructed signal closely reassembles the original ambient signal (>85% correlation). We extensively demonstrate SDR-Lite effectiveness across seven distinctive SDR receiver applications under three representative categories: (i) RFfingerprinting, (ii) spectrum monitoring, and (iii) (ZigBee) decoding. For instance, in security applications of drone and rogue WiFi AP detection, SDR-Lite achieves 99% and 97% accuracy, which is comparable to USRP.
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Srikar Kasi, Kyle Jamieson (Princeton University)
We present Quantum Belief Propagation (QBP), a Quantum Annealing (QA) based decoder design for Low Density Parity Check (LDPC) error control codes, which have found many useful applications in Wi-Fi, satellite communications, mobile cellular systems, and data storage systems. QBP reduces the LDPC decoding to a discrete optimization problem, then embeds that reduced design onto quantum annealing hardware. QBP's embedding design can support LDPC codes of block length up to 420 bits on real state-of-the-art QA hardware with 2,048 qubits. We evaluate performance on real quantum annealer hardware, performing sensitivity analyses on a variety of parameter settings. Our design achieves a bit error rate of 10^{-8}10 in 20 μs and a 1,500 byte frame error rate of 10^{-6}10 in 50 μs at SNR 9 dB over a Gaussian noise wireless channel. Further experiments measure performance over real-world wireless channels, requiring 30 μs to achieve a 1,500 byte 99.99% frame delivery rate at SNR 15-20 dB. QBP achieves a performance improvement over an FPGA based soft belief propagation LDPC decoder, by reaching a bit error rate of 10^{-8}10 and a frame error rate of 10^{-6}10 at an SNR 2.5--3.5 dB lower. In terms of limitations, QBP currently cannot realize practical protocol-sized (\textit{e.g.,}e.g., Wi-Fi, WiMax) LDPC codes on current QA processors. Our further studies in this work present future cost, throughput, and QA hardware trend considerations.
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Manideep Dunna, Chi Zhang (UC San Diego); Daniel Sievenpiper, Dinesh Bharadia (University of California San Diego)
In the last decade, the bandwidth expansion and MIMO spatial multiplexing have promised to increase data throughput by orders of magnitude. However, we are yet to enjoy such improvement in real-world environments, as they lack rich scattering and preclude effective MIMO spatial multiplexing. In this paper, we present ScatterMIMO, which uses smart surface to increase the scattering in the environment, to provide MIMO spatial multiplexing gain. Specifically, smart surface pairs up with a wireless transmitter device say an active AP and re-radiates the same amount of power as any active access point (AP), thereby creating virtual passive APs. ScatterMIMO avoids the synchronization, interference, and power requirements of conventional distributed MIMO systems by leveraging virtual passive APs, allowing its smart surface to provide spatial multiplexing gain, which can be deployed at a very low cost. We show that with optimal placement, these virtual APs can provide signals to their clients with power comparable to real active APs, and can increase the coverage of an AP. Furthermore, we design algorithms to optimize ScatterMIMO's smart surface for each client with minimal measurement overhead and to overcome random per-packet phase offsets during the measurement. Our evaluations show that with commercial off-the-shelf MIMO WiFi (11ac) AP and unmodified clients, ScatterMIMO provides a median throughput improvement of 2x over the active AP alone.
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Minhao Cui, Yuda Feng (University of Massachusetts Amherst); Qing Wang (Delft University of Technology); Jie Xiong (University of Massachusetts Amherst)
Visible light communication (VLC) is gaining a significant amount of interest as a new paradigm to meet rapidly increasing demands on wireless capacity required by a digitalized world. VLC is considered as a secure wireless communication scheme because VLC signals can be easily constrained within physical boundaries. In this paper, for the first time, we show that VLC is not as secure as people thought: VLC can be sniffed through walls! The key principle behind this is that in VLC transmissions, a VLC transmitter not only emits visible light signals but also leaks out "side channel RF signals". The leaked RF signals can be sniffed by a receiver to decode the VLC transmissions even the receiver is blocked (e.g., by walls) from the VLC transmitter. In this work, we establish a theoretical model to quantify the amplitude of the leaked RF signal and verify the model with comprehensive experiments. We design and implement a VLC sniffing system including receiver coil design, signal processing and frame decoding, spanning across hardware and software. Field studies show that with a cheap receiver design, our system can simultaneously sniff transmissions from multiple VLC transmitters 6.4 meters away with a 14 cm concrete wall in between, where the distance exceeds the communication range of most state-of-the-art VLC systems. By simply twining a wired earphone on the arm, we can sniff the VLC transmission 1.9 meters away.