Millimeter-wave (mmWave) backscatter has emerged as a compelling low-power communication paradigm for high-bandwidth IoT applications. However, existing systems rely on specialized readers, such as FMCW radars, which limits their scalability and practical deployment. On the other hand, commodity mmWave backscatter integrates the tags directly into the mmWave networks with devices like APs and clients, and the protocol frames are retrofitted to enable seamless communication with the tags. Despite its potential, such bistatic backscatter communication suffers from low SNR and short communication range. In this work, we present B3, a bistatic backscatter beamforming framework that operates entirely on commodity mmWave infrastructure such as 802.11ad/ay. B3 introduces a lightweight multibeam backscatter technique that enables tags to embed both ID and channel information directly into standard beamforming frames via pulse position and on-off keying modulations. The design yields high-gain beams towards the tag in bistatic settings and supports concurrent multi-tag beamforming within a single training round. We prototype a multibeam 60 GHz backscatter tag and achieve a 13 dB SNR improvement compared to codebook-based beamforming, supporting backscatter communication at distances of up to 11 m with BER ≤ 10− 3. Our evaluation shows that B3 enables high-SNR backscatter even with blockages and NLoS conditions. Our tag prototype consumes only 2.5 mW of power, making it a practical and scalable solution.

As we move towards a future of connected and autonomous vehicles, high-speed and low-latency connectivity between vehicles is becoming increasingly important. This paper investigates enabling high data rate mmWave links in vehicle-to-vehicle (V2V) scenarios using street view images. We find that mmWave V2V links in urban settings suffer from frequent and prolonged blockages, resulting in unreliable connection and high beamforming overhead. Our work proposes mmSV, a system that creates 3D reflection profiles from street view images to assist vehicles in finding mmWave reflections from the environment in real-time. mmSV consists of two key components: material identification which identifies materials from street view images to determine their reflectivity and create 3D reflection map, and environment-driven ray-tracing and beamsearching which finds a high-SNR beam using predicted 3D material maps. Our extensive experimental results on the mmWave testbed show that mmSV can provide highly reliable V2V mmWave connectivity with low beamforming overhead.

Massive connectivity is a key to the success of the Internet of Things. While mmWave backscatter has great potential, substantial signal attenuation and overwhelming ambient reflections impose significant challenges. We present OmniScatter, a practical mmWave backscatter with an extreme sensitivity of -115 dBm. The performance is theoretically comparable to the popular commodity RFID EPC Gen2 (900 MHz), and is empirically validated via evaluations under various practical settings with abundant ambient reflections and blockages - e.g., In an office where a tag is locked in a wooden closet 6m away, as well in libraries and retail stores where a tag is placed across two rows of metal shelves. At the heart of OmniScatter is the new High Definition FMCW (HD-FMCW), which interplays with the tag (FSK) signal to disentangle the ambient reflections from the tag signal in the frequency domain, essentially offering immunity to ambient reflections. To further support practical deployment, OmniScatter offers coordination-free Frequency Division Multiple Access (FDMA) that effortlessly scales to thousands of concurrent tags. The readers were built on commodity radars and the tags were prototyped on PCB. The trace-driven evaluation demonstrates concurrent communication of 1100 tags with the BER < 1.5%, paving a pathway towards practical mmWave backscatter for everyday and anywhere use.

Low power IoT suffers from performance degradation due to severe cross-technology interference (CTI) such as WiFi. In this demo, we present a novel ZigBee system that effectively maintains high reliability even under saturated WiFi traffic. This is achieved by placing a ZigBee packet on the guard band of ongoing, ambient WiFi traffic. Guard band is designed to be kept clear of interference from other WiFi, thereby safeguarding the ZigBee within. Our system effectively captures WiFi (802.11b) guard band on the fly, using physical layer information accessible on commodity ZigBee RF. We demonstrate real-time guard band detection and robust ZigBee communication, showcasing a practical pathway to operating low power IoT under excessive CTI.

Cross-technology interference (CTI) from dense and prevalent wireless has become a primary threat to low-power IoT. This paper presents G-Bee, a CTI avoidance technique that uniquely places ZigBee packet on the guard band of ongoing WiFi traffic, which effectively safeguards the packet from WiFi interference. Such design ensures reliable ZigBee communication even under saturated WiFi traffic where traditional ZigBee is considered inoperable. Technical highlight is in lighweight WiFi guard band capture mechanism using ZigBee PHY layer samples directly accessible in various commercial ZigBee chip. Another exclusive feature of G-Bee is spectrum-synchronized low duty cycling - by utilizing guard bands of periodic WiFi beacons, active slots are effectively synchronized to spectrum availability (i.e., guard band) for significant delay improvement. Extensive evaluations on our prototype system demonstrates G-Bee PRR over 95% where legacy ZigBee drops to below 15% under significant interference with hundreds WiFi users and reduction of low duty cycle delay by 87.5%, all of which are achieved with a light computational overhead of 0.3%.