Passive IoT technology, valued for its self-sustaining and low-cost attributes, faces notable limitations in data rate, range, and power efficiency. While significant progress has been made in enhancing uplink performance through backscattering techniques, the primary performance bottleneck has now shifted to the downlink. In this paper, we propose 3in1, a novel multi-tone system that jointly optimizes wireless power delivery, high-precision clocking, and robust communication for long-range passive IoT devices. By carefully controlling the phase and frequency spacing of the multi-tone signals, 3in1 significantly improves energy harvesting efficiency, seamlessly provides wireless clocking, and enables reliable downlink communication without interrupting power transfer. Our design addresses critical challenges, including signal optimization, data encoding, and strict FCC compliance.

Ambient IoT (A-IoT) aims to connect hundreds of billions of ultra-low-power and battery-free devices, which has been included in the agenda for 6G standardization by 3GPP. Backscatter communication is considered the mainstream enabling technique for A-IoT; however, current state-of-the-art can hardly meet A-IoT's main technical requirements simultaneously: power consumption below 100 μW, communication ranges up to 100 m, and 100+ concurrency. This paper presents NanoScatter, the first backscatter network with each tag implemented using our customized backscatter communication ASIC. We propose a nanowatt wake-up receiver design and a sensitivity-driven downlink/uplink modulation mechanism to carry out the ASIC, which enables minimizing the tag's power consumption and long-range communication. NanoScatter supports concurrent communication of 6 IC-based tags with a subcarrier capacity of 512, achieving communication distances of 66 m indoors and 100 m outdoors. The tag consumes 1 μW in idle listening, with the core circuit using 58 nW and 43 μW during communication.

Ambient IoT (A-IoT) targets battery-free, ultra-low-power connectivity for massive devices, which has been a key focus in 6G standardization by 3GPP. While backscatter communication enables A-IoT, existing solutions struggle to meet its core demands simultaneously: power consumption below 100 μW, communication ranges up to 100 m, and 100+ concurrency. In this demo, we present NanoScatter, the first backscatter network with each tag implemented using our customized backscatter communication ASIC. We propose a nanowatt wake-up receiver design and a sensitivity-driven downlink/uplink modulation mechanism to carry out the ASIC, which enables minimizing the tag's power consumption and long-range communication. NanoScatter supports concurrent communication of 6 IC-based tags with a subcarrier capacity of 512, achieving communication distances of 66 m indoors and 100 m outdoors. The tag consumes 1 μW in idle listening, with the core circuit using 58 nW and 43 μW during communication.

Wi-Fi technology has emerged as a promising solution for contact-free sensing owing to the pervasiveness of Wi-Fi signals in indoor environments. However, Wi-Fi sensing faces several fundamental issues, including limited sensing range and unstable orientation-dependent sensing performance, hindering the widespread adoption of Wi-Fi sensing in real-life scenarios. In this paper, we propose RISensing, a novel system that leverages Reconfigurable Intelligent Surfaces (RIS) to address these two fundamental issues of Wi-Fi sensing and bring Wi-Fi sensing one step closer to real-world adoption. Unlike prior Wi-Fi sensing works which typically rely on a single target reflection signal to capture the target movement, RISensing utilizes two target reflection signals, i.e., the direct target reflection signal and RIS-based target reflection signal, to boost the sensing capability. RISensing characterizes the RIS-based target reflection signal, and constructively combines it with the direct target reflection. We evaluate the sensing performance of RISensing in various environments, including corridor, office and lab. Extensive experiments demonstrate RISensing can improve the sensing range of Wi-Fi from 4 m to 23 m, and effectively mitigate the orientation-dependent issue.

There has been a trend in passive IoT systems to move complexity from tag to reader for delivery of power, clock, and data [1, 2]. However, current designs either cannot deliver all these three simultaneously, or fail to do so in a co-optimized way, which leads to poor operating range and long charging time of passive IoT systems. To address this key bottleneck, we present 3in1, the first system co-design that optimizes Wireless Power Transfer (WPT) efficiency, accurate wireless clocking, and downlink communication simultaneously. We propose several novel designs: (i) an optimized multi-tone WPT waveform compliant with ISM band and FCC regulations; (ii) a robust and accurate wireless clocking mechanism integrated within the optimized waveform; (iii) a multi-tone Binary Phase Shift Keying (BPSK) downlink modulation scheme that maintains wireless clocking accuracy and WPT efficiency; and (iv) an ultra-low power receiver capable of simultaneously extracting power, clock, and data from the optimized waveform. Preliminary results demonstrate that higher WPT efficiency, precise wireless clocking, and downlink communication can be achieved simultaneously within a co-optimized waveform. We believe this paves the way for the next generation of passive IoT system design.

Passive IoT localization technology offers significant advantages across various applications due to its self-sustaining, maintenance-free, and low-cost nature. However, existing systems cannot effectively address the multipath problem in real-world deployments, leading to unreliable localization results in the severe multipath scenario. We propose to fill the gap with UWB2, the first ultra-wideband backscatter passive IoT system that can achieve centimeter-level 99th percentile accuracy even under severe multipath environments. The demo will illustrate UWB2's performance in localization accuracy, latency, operating range, and power consumption in severe multipath scenarios.

Millimeter-wave (mmWave) radar has become instrumental in diverse consumer applications. Yet current radar architectures face major limitations. While full-MIMO structures are feature-rich, their cost and complexity rise rapidly with more antennas. Phased-MIMO radars promise enhanced scalability by combining large phased arrays with a small number of RF chains. Nevertheless, the phased-MIMO research thus far primarily relies on simulation or theoretical analysis. In this paper, we introduce HybRadar, a novel programmable phased-MIMO radar platform to address this experimental gap. HybRadar repurposes the phased arrays on a low-cost 802.11ad radio to create a scalable low-cost array of phased subarrays. It further incorporates transmit/receive front-end, control channel, and hardware synchronization mechanisms to enable a modular phased-MIMO system. By extending recent MIMO array synthesis models, we optimize the placement of phased subarrays to maximize the spatial resolution. Our prototype validation and case studies confirm the capability and versatility of HybRadar.

This paper for the first time demonstrates how to enable OFDMA in Wi-Fi backscatter for capacity and concurrency enhancement. With our design, the excitation signal is reflected, modulated and shifted to lie in the frequency band of the OFDM subcarrier by the tag; OFDMA is realized by coordinating tags to convey information to the receiver with orthogonal subcarriers concurrently through backscatter. The crux of the design is to achieve strict synchronization among communication components, which is more challenging than in regular OFDMA systems due to the more prominent hardware diversity and uncertainty for backscattering. We reveal how the subtle synchronization scenarios particularly for backscattering can incur system offsets, and present a series of novel designs for the excitation signal transmitter, tag, and receiver to address the issue. We build a prototype in 802.11g OFDM framework to validate our design. Experimental results show that our system can achieve 5.2-$16Mbps$aggregate throughput by allowing 48 tags to transmit concurrently, which is 1.45-$5\times $capacity and$48\times $concurrency compared with the existing design respectively. We also design an OFDMA tag IC, with the corresponding simulation and numerical analysis results show that the tag’s power consumption is in tens of$\mu W$.

Millimeter-wave (mmWave) technologies represent a cornerstone for emerging wireless network infrastructure, and for RF sensing systems in security, health, and automotive domains. Through a MIMO array of phased arrays with hundreds of antenna elements, mmWave can boost wireless bit-rates to 100+ Gbps, and potentially achieve near-vision sensing resolution. However, the lack of an experimental platform has been impeding research in this field. We propose to fill the gap with M3 (M-Cube), the first mmWave massive MIMO software radio [1]. M3 features a fully reconfigurable array of phased arrays, with up to 8 RF chains and 256 antenna elements. Despite the orders of magnitude larger antenna arrays, its cost is orders of magnitude lower, even when compared with state-of-the-art single RF chain mmWave software radios. In this demo, we will show M3's hardware modules, and demonstrate its usage in mmWave MIMO communication and sensing.

In a modern logistics network, high-performance automation of inventory tracking and package management calls for a reliable, high-throughput and long range RFID localization system. We present RF-Chord, the first RFID localization system that simultaneously meets all these requirements. RF-Chord features a one-shot multisine-constructed wideband design that can process the RF signal with a 200 MHz bandwidth in real-time to facilitate one-shot localization at scale. In addition, multiple SINR enhancement techniques are designed for range extension. Finally, we propose a kernel-layer-based near-field localization and a multipath-suppression algorithm that reduces the 99% long-tail errors.

Typical passive internet of things (IoT) localization systems, such as those based on UHF RFID, adopt narrow bandwidth signal and bind the localization function with energy harvesting and communication waveform. Due to the signal bandwidth and waveform constraints, the systems can not meet crucial requirements of practical IoT use cases. In this poster, we identify the fundamental challenges and analyze why the existing systems fall short. Based on the analysis, we propose to adopt dual band backscatter design and identify different design choices on frequency band, waveform and tag modulation. Finally, we build an ultra-wideband FMCW signal based prototype UWB2 to verify the feasibility of our proposal. Our results show that the system can achieve low tail error and realize one shot localization even under harsh multipath scenarios.

Millimeter-wave (mmWave) technologies represent a cornerstone for emerging wireless network infrastructure, and for RF sensing systems in security, health, and automotive domains. Through a MIMO array of phased arrays with hundreds of antenna elements, mmWave can boost wireless bit-rates to 100+ Gbps, and potentially achieve near-vision sensing resolution. However, the lack of an experimental platform has been impeding research in this field. This paper fills the gap with M3 (M-Cube), the first mmWave massive MIMO software radio. M3 features a fully reconfigurable array of phased arrays, with up to 8 RF chains and 288 antenna elements. Despite the orders of magnitude larger antenna arrays, its cost is orders of magnitude lower, even when compared with state-of-the-art single RF chain mmWave software radios. The key design principle behind M3 is to hijack a low-cost commodity 802.11ad radio, separate the control path and data path inside, regenerate the phased array control signals, and recreate the data signals using a programmable baseband. Extensive experiments have demonstrated the effectiveness of the M3 design, and its usefulness for research in mmWave massive MIMO communication and sensing.

Millimeter-wave (mmWave) technologies represent a cornerstone for emerging wireless network infrastructure, and for RF sensing systems in security, health, and automotive domains. Through a MIMO array of phased arrays with hundreds of antenna elements, mmWave can boost wireless bit-rates to 100+ Gbps, and potentially achieve near-vision sensing resolution. However, the lack of an experimental platform has been impeding research in this field. We propose to fill the gap with M3 (M-Cube), the first mmWave massive MIMO software radio. M3 features a fully reconfigurable array of phased arrays, with up to 8 RF chains and 256 antenna elements. Despite the orders of magnitude larger antenna arrays, its cost is orders of magnitude lower, even when compared with state-of-the-art single RF chain mmWave software radios. In this demo, we will show M3's hardware modules, and demonstrate its usage in mmWave MIMO communication and sensing.

Current UHF RFID systems suffer from two long-standing problems: 1) miss-reading non-line-of-sight or misoriented tags and 2) cross-reading undesired, distant tags due to multi-path reflections. This paper proposes a novel system, NFC+, to overcome the fundamental challenges. NFC+ is a magnetic field reader, which can inventory standard NFC tagged objects with a reasonably long range and arbitrary orientation. NFC+ achieves this by leveraging physical and algorithmic techniques based on magnetic resonance engineering. We build a prototype of NFC+ and conduct extensive evaluations in a logistic network. Comparing to UHF RFID, we find that NFC+ can reduce the miss-reading rate from 23% to 0.03%, and cross-reading rate from 42% to 0, for randomly oriented objects. NFC+ demonstrates high robustness for RFID unfriendly media (e.g., water bottles and metal cans). It can reliably read commercial NFC tags at a distance of up to 3 meters which, for the first time, enables NFC to be directly applied to practical logistics network applications.

In this paper, we for the first time demonstrate how to enable OFDMA in Wi-Fi backscatter for capacity and concurrency enhancement. With our approach, the excitation signal is reflected, modulated and shifted to lie in the frequency band of the OFDM subcarrier by the tag; OFDMA is realized by coordinating tags to convey information to the receiver with orthogonal subcarriers concurrently through backscatter. The crux of the design is to achieve strict synchronization among communication components, which is more challenging than in regular OFDMA systems due to the more prominent hardware diversity and uncertainty for backscattering. We reveal how the subtle asychnronization scenarios particularly for backscattering can incur system offsets, and present a series of novel designs for the excitation signal transmitter, tag, and receiver to address the issue. We build a prototype in 802.11g OFDM framework to validate our design. Experimental results show that our system can achieve 5.2-16Mbps aggregate throughput by allowing 48 tags to transmit concurrently, which is 1.45-5x capacity and 48x concurrency compared with the existing design respectively. We also design an OFDMA tag IC, and the simulation and numerical analysis results show that the tag's power consumption is in tens of μW.