Power consumption continues to pose a fundamental challenge for large-scale IoT tag deployment. While conventional active communication strategies struggle to mitigate peak power demands due to energy-intensive components, passive alternatives achieve microwatt-level consumption but suffer from limited operational range. This paper introducesTiga, an innovative hybrid active-passive communication system for Ambient IoT that autonomously selects optimal transmission modes. Recognizing the ambiguity inherent in the distance-based mode switching boundary, we instead adopt energy level as our boundary criterion.Tigaemploys passive communication when channel energy suffices and seamlessly transitions to active transmission when required. Our design features a novel microwatt-scale dual-function detector that performs concurrent downlink signal demodulation and RSSI computation. We further propose an adaptive four-phase blind boundary search algorithm capable of efficient execution on any low-power controller. We prototypeTigaon a four-layer PCB and evaluate its performance across various environments. Experimental results demonstrate that compared to duty-cycling active communication,Tigareduces dynamic power consumption by 1.85× to 9.42× across various distances from the gateway.

This paper presents μTag, an ultra-low-power backscatter sensor that supports high-rate sensing of a large number of targets simultaneously. The core of μTag is an RF “gene editing” technique that embeds both the identity of the sensor and the real-time motion or vibration state of the attached target intensively in the transient features of the sensor’s RF signal, in a collision-resilient manner. We provide practical techniques which i) generate such “genetic signal” with purely analog and extremely simple circuits; and ii) separate the signals from a large scale of sensors reliably. Our experimental results show that our design can support concurrent tracking of 150 targets with a 12 kHz per-tag sampling rate. We also demonstrate with multiple sensing applications that μTag can achieve high-speed and large-scale motion tracking, rotation frequency sensing, and contactless sensing. The PCB power consumption of μTag is 38∼107 μW, according to the operating frequency of the tag. Our ASIC simulation based on the 40 nm CMOS process shows that the power consumption can be further reduced to 0.13∼0.52 μW.

This paper presents mmDFRBC, a symbol-level millimeter-wave (mmWave) backscatter communication system that reuses commercial mmWave FMCW radar infrastructure as the dual-function access point (AP) without hardware modification. We propose M-ary Frequency Shift Modulation (MFSM), a lightweight encoding scheme that enables the tag to modulate information using orthogonal frequency blocks over adjacent chirps, achieving symbol-level modulation with data rates exceeding kbps. To robustly extract the modulation signals from strong radar sensing clutter, we introduce a Coherent Cancellation Demodulation (CCD) method that exploits the coherence difference between sensing signals and modulated reflections. We develop a soft synchronization strategy for operating asynchronously and requiring no synchronization or downconversion circuits at the tag, supporting kbps-level data rates with low power and cost. We implement mmDFRBC using a commercial mmWave radar and verify its performance across static and mobile scenarios, achieving BERs below$10^{-3}$over 4 meters, with strong resilience to radar clutter interference. mmDFRBC supports data rates up to 50 kbps, highlighting DFRBC’s potential to enable high-performance DFRC systems using existing infrastructure.

This paper presents Serafin, the first full-stack, sub-mW, and versatile Bluetooth-enabled RF sensor that brings transparent RF sensing to any mobile and IoT device: it independently conducts the whole RF sensing process from RF signal reception to sensing result computation in a wide variety of sensing tasks with only negligible power consumption. At the core of Serafin are our two designs that address the challenge posed by the stringent sub-mW power constraint to jointly achieving versatility and full stackness. Specifically, (i) we utilize the ambient Bluetooth advertising signal as the signal for sensing, and extract the phase difference of the sensing signals received by each antenna pair from the amplitude of their sum signal, which avoids power-hungry hardware components and intensive computation, and (ii) we employ low-power MCU as the computation hardware, and suppress its power consumption by activating it adaptively only when necessary and customizing a light-weight neural network model that still ensures satisfactory inference accuracy. Our extensive experiments on 6 representative sensing tasks show that Serafin achieves competitive sensing performance, but consumes only around 500–900μW power, which is 3–4 orders of magnitude lower than those of existing full-stack and versatile counterparts.

This paper demonstrates Serafin, the first full-stack, sub-mW, and versatile Bluetooth-enabled RF sensor that brings transparent RF sensing to mobile and IoT device: it independently conducts the whole RF sensing process from RF signal reception to sensing result computation in a wide variety of sensing tasks with only negligible power consumption. At the core of Serafin are our two designs that address the challenge posed by the stringent sub-mW power constraint to jointly achieving versatility and full stackness. Specifically, (i) we utilize the ambient Bluetooth advertising signal as the signal for sensing, and extract the phase difference of the sensing signals received by each antenna pair from the amplitude of their sum signal, which avoids power-hungry hardware components and intensive computation, and (ii) we employ low-power MCU as the computation hardware, and suppress its power consumption by activating it only when necessary and customizing a light-weight yet versatile neural network model.

The Wi-Fi-enabled ultra-low power communication system exhibits high asymmetry between uplink and downlink speeds. The uplink can reach up to 1 Mbps, while the downlink throughput is around 100 Kbps. In this paper, we present Wook, a novel high throughput downlink system to empower Commercial Off-The-Shelf (COTS) Wi-Fi devices to transmit high-speed OOK messages. The key innovation underpinning Wook is its ability to achieve sub-symbol level modulation, allowing a single OFDM symbol to carry multiple OOK bits. This is done by profoundly exploring the Wi-Fi PHY layer and identifying optimal input payload to achieve fine-grained Wi-Fi waveform manipulation. We fabricate a PCB prototype and employ the COTS Wi-Fi router to implement the entire system. Experimental results show that with a simulated IC power consumption 76.6μW, Wook achieves a data rate of up to 1.1 Mbps, an 8.9X improvement over state-of-the-art systems. Moreover, even at a communication distance of 95 m, Wook maintains a throughput of 82.9 Kbps.

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.

This paper presents FaB, a frequency-agile backscatter system that can optionally leverage OFDM signals on different bands as carriers for backscatter communication. Compared with existing backscatter systems that are tailored to a specific frequency band, a frequency-agile backscatter yields two critical benefits: i) it can leverage the increased availability of “free rides” across a broad range of frequency band to improve its transmission efficiency; and ii) it becomes compatible with mainstream wireless communication standards, making it applicable to heterogeneous wireless networks. Based on these two features, FaB’s circuits can be migrated to various types of backscatter communication nodes without any modification, significantly reducing design and deployment costs. To show the efficacy of our design, we implement a PCB prototype of FaB and showcase its capability of leveraging OFDM Wi-Fi and LTE signals as carrier waves. Our extensive field studies show that FaB’s multi-band modulator can produce an error vector magnitude of under -15dB in any band below 6GHz with a precision of 10mV.

LoRa backscatter achieves long-range communication at the cost of only tens of micro-watts of power when implemented in integrated circuits (ICs), which makes it a potential enabler for massive IoT. However, despite the above advantages, we find that the current tag design wastes approximately 72% of the chip functional area due to the use of large-size inductors in the impedance loads array. This inefficiency significantly increases the cost per chip during mass production. To address this die area issue, we propose OsTAG, a novel LoRa backscatter design that eliminates all inductors in the impedance loads array while maintaining the same quantization resolution. The key innovation lies in the creation of virtual impedance using oversampling. Realizing such design requires overcoming the technical challenges of mitigating approximation error and managing oversampling clock imperfections. To validate our design, we develop prototype and an IC, demonstrating promising results in terms of both performance and efficiency. OsTAG is expected to cost only 28% of the existing chip area while achieving comparable hundred-meter level communication range.

This paper presents μTag, an ultra-low-power backscatter sensor that supports high-frequency sensing of a large number of targets simultaneously. The core of μTag is an RF "gene editing" technique that embeds both the identity of the sensor and the real-time motion state of the attached target intensively in the transient features of the sensor's RF signal, in a collision-resilient manner. We provide practical techniques which i) generate such "genetic signal" with purely analog and extremely simple circuits; and ii) separate the signals from a large scale of sensors reliably. Our experimental results show that our design can support concurrent tracking of 150 targets with a 12kHz per-tag sampling rate. We also demonstrate with multiple sensing applications that μTag can achieve high-speed and large-scale motion tracking and rotation frequency sensing. The PCB power consumption of μTag is 38~107μW, according to the operating frequency of the tag. Our ASIC simulation based on the 40nm CMOS process shows that the power consumption can be further reduced to 0.13~0.52μW.

This paper presents FaB, a frequency-agile backscatter system that can optionally leverage OFDM signals on different bands as carriers for backscatter communication. Compared with existing backscatter systems that are tailored to a specific frequency band, a frequency-agile backscatter yields two critical benefits: i) it can leverage the increased availability of "free rides" across a broad range of frequency band to improve its transmission efficiency; and ii) it becomes compatible with mainstream wireless communication standards, making it applicable to heterogeneous wireless networks. Based on these two features, FaB's circuits can be migrated to various types of backscatter communication nodes without any modification, significantly reducing design and deployment costs. To show the efficacy of our design, we implement a PCB prototype of FaB and showcase its capability of leveraging OFDM Wi-Fi and LTE signals as carrier waves. Our extensive field studies show that FaB's multi-band modulator can produce an error vector magnitude of under -15dB in any band below 6GHz with a precision of 10mV.

This paper presents dual-band Wi-Fi backscatter (DBscatter), which is the first system supporting 2.4GHz and 5GHz Wi-Fi backscatter simultaneously in a single tag. Our key insight is that most existing Wi-Fi devices communicate in the clean 5GHz band. The 5GHz band provides more chances for ”free riding” with less interference, while the 2.4GHz band presents better NLoS performance. DBscatter combines the strengths of the existing 2.4GHz band with the unexplored 5GHz backscatter in a unified design, developing a robust and high-throughput ambient Wi-Fi backscatter system. We make the following technical contributions: (1) We design a dual-band RF frontend to support dual-band Wi-Fi signals. (2) We propose a tag data demodulation algorithm, which merges the common phase error in multi-antenna received signals, improving the tag transmission reliability while reducing the number of required receivers. (3) We build a prototype of DBscatter system using COTS FPGAs and SDRs. Compared to TiScatter and FreeRider, DBscatter boosts Wi-Fi backscatter throughput by 3.74X and 7.35X, and energy efficiency by 1.78X and 1.38X respectively.

This paper presents MobiScatter, which enhances capacity of CSS based backscatter networks for accommodating drone-carried access points (APs). CSS based backscatter design has favorable features including long range and high concurrency. However, the concurrency of the network can be reduced by 34% when the drone-carried AP is introduced due to the mobility and fast fading. In order to maintain high concurrency, MobiScatter presents a series of new designs. In particular, we propose to enhance concurrency of the CSS based backscatter network with symmetric upchirps and downchirps, which neutralizes the impact of imperfect frequency orthogonality. Then, to mitigate the impact of fast fading on decoding, we present a novel half-period chirp modulation scheme for crossed chirps. Finally, we provide a power management method for tags by controlling transmitting time of chirps. We construct a MobiScatter prototype, which contains a drone-carried AP implemented with a mobile USRP and 200 tags. We deploy those tags in an area of$200 m\times 180 m$on a meadow. Experimental results show that MobiScatter can support 160 concurrent backscatter transmissions when the AP moves at$15 m/s$.

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$.

Reconfigurable reflective arrays can be used to program the radio propagation environment in order to form favorable wireless channel conditions. Previous designs have used large-scale arrays containing hundreds to thousands of reflecting elements located external to the receiving node, with the reflection coefficients of all array elements managed by a controller. However, these designs can be costly to deploy and are challenging to quickly adapt to the time-varying nature of wireless channels caused by mobility.

This paper presents EmoRI, a novel single-chip mmWave radar-based egomotion estimation approach that works in challenging scenarios where moving objects exist in radar's Field of View (FoV). Essentially, estimating a mobile platform's egomotion using an on-board mmWave radar requires inferring the relative motion between radar and the points of the stationary objects (PSOs) in the radar point cloud. However, in practice, there could be no PSOs because of the blockage of moving objects. Even if PSOs exist, precisely identifying them is still challenging due to (i) the large quantity of points generated by the moving objects, and (ii) the huge angle estimation errors of the conventional point cloud generation algorithm. We empower EmoRI to overcome the above challenges incurred by moving objects with three core techniques, which include (i) a hybrid FFT-MUSIC algorithm that improves the angle estimation accuracy of single-chip mmWave radar, (ii) a multiple stationary target consensus algorithm that precisely selects the PSOs from the radar point cloud, and (iii) a simultaneous fusion and calibration mechanism that introduces an IMU as the auxiliary sensor, meticulously calibrates IMU accelerations with radar measurements, and complimentarily fuses these two modalities to obtain the 6-DoF egomotion. Our extensive experiments validate that EmoRI pushes the limit of single-chip mmWave radar-based egomotion estimation with moving objects in radar's FoV by reducing the per-meter destination error from decimeter to centimeter level.

In this paper, we for the first time show how to enable software-defined PHY (SD-PHY) to achieve agile reprogrammability in wireless backscatter networks. This can facilitate innovations in this field by relieving researchers from unnecessary engineering work. With SD-PHY, the tag's PHY-layer behavior can be neatly defined by configuring a set of parameters, which allows the common hardware to generate backscattered signals complying with various wireless protocols. The SD-PHY architecture is based on the key insight that the tag's PHY-layer behavior is essentially determined by reflection coefficient sequence.

OFDMA downlink design allowing parallel processing OFDM subcarriers is adopted by a number of commercial wireless standards such as LTE, 5G, and 802.11ax. However, the widespread adoption of OFDMA downlink on low-end IoT devices is stymied due to the existing digital receiver framework's ≈100mW power consumption, which is mainly incurred by LO+mixer, ADC, and complex digital processing. In this paper, we present an ultra-low-power OFDMA downlink demodulation design, which achieves ≈100 μW receiving power. Our basic idea is to transform the current digital demodulation approach into the analog one based on filtering, which avoids those power-hungry components. We achieve this by proposing a series of novel RF front-end hardware designs: 1) a μW-level two-stage mixing scheme that enables adjustable and precise subcarrier filtering, 2) a quartz crystal-based filter circuit incurring negligible insertion loss, and 3) a passive phase-to-envelope conversion technique enabling low-power non-coherent phase demodulation. We build a prototype to verify the proposed schemes. Experimental and IC simulation results show that: our new design can achieve 130 -- 1500 times power savings depending on the number of subcarriers that need to be processed in parallel, compared with the traditional all-digital design.

Recently proposed OFDMA backscatter could improve both concurrency and spectrum allocation flexibility for backscatter systems based on OFDM. However, we find that it is remarkably inefficient for the existing design to scale up in prototyping: it requires one-by-one offline computation to obtain tags' operating parameters, in order to ensure orthogonality among subcarriers in the system; moreover, the tag hardware has to be dedicatedly modified offline before being assigned multiple subcarriers. The inefficiency is caused by the current analog frequency synthesis design for the tag. This paper proposes DigiScatter, an OFDMA backscatter system realizing digital frequency synthesis, which provides an efficient prototyping approach for large-scale OFDMA backscatter networks. In DigiScatter, we for the first time integrate IDFT into the tag design; such a simple but effective improvement enables the system to support high concurrency and flexible spectrum resource allocation through pure software configurations in an online manner. We build a prototype and conduct comprehensive experiments to validate our design. DigiScatter physically realizes 100 and 300 concurrent OFDMA backscatter transmissions in 2.4GHz and 900MHz respectively, and provides frequency synthesis capability for supporting 1019 concurrent transmissions.

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.