Information security is a non-negligible issue for wireless transmission. Covert communication provides high security by concealing the transmitted signals within environmental noise. However, existing solutions suffer from low transmission efficiency. Ambient backscatter, concealing data within ubiquitous ambient signals, provides a promising way to achieve high-efficiency covert communication. In this paper, we propose CoScatter, an efficient covert transmission system based on OFDM WiFi backscatter. Current studies rely on redundant modulation, resulting in low throughput. This paper is to increase throughput and shorten transmission time, thereby reducing exposure risk. This is the first work to realize single-sample level demodulation, efficiently eliminating the redundancy, increasing the throughput, and reducing the transmission time. We discover that the main obstacles are the additional phase offsets introduced by three independent wireless channels in backscatter systems. Based on this, we design a new backscatter channel equalization procedure to remove the channel influences while preserving all the covert information embedded by the tag, realizing an efficient covert transmission. Evaluation results show that Coscatter achieves a throughput exceeding 15.7 Mbps, which is around 64x of that of RapidRider, and 16x of that of Tscatter. Consequently, the exposure risk of CoScatter is reduced to 1/64 of that of RapidRider and 1/16 of that of Tscatter.

The demand for ultra-low-power wireless connectivity motivates the study of backscatter communication technology. There are already some related products on the market based on excitation signals from commercial radios. However, their modulation techniques, which are the key to backscatter communications, mainly focus on the phase or frequency domain while amplitude modulation is largely ignored. Most research works either deploy one finely tuned RF impedance port for every needed reflection state or connect a nonlinear device to antenna and tune the reflection amplitude by adjusting its biasing voltage, where the former is too complex and the latter is unstable under variable incident signal power, limiting the backscatter applications. For this reason, we introduce AMscatter to leverage the duty ratio of the frequency-shift wave (FS-wave) to design a novel amplitude modulation. Both theoretical analysis and experimental results show that the reflection amplitude approximates a sinusoidal function of the duty ratio. This method requires only two fixed RF impedances, making AMscatter simple and stable. Moreover, we show how to use AMscatter to design quadrature amplitude modulation (QAM) and pulse shaping to improve backscatter communication performance. Extensive experimental results show that the throughput can be as high as 3.9 Mbps, the supported operational range can reach 20 m with 16-QAM modulation, and the out-of-band interference can be suppressed by 15 dB without negatively affecting the communication performance through our pulse shaping.

Throughput is a critical performance metric in backscatter communication systems. Existing approaches either suffer from limited throughput or necessitate modifications to transmitters or receivers, leading to incompatibility with commodity radios. In this paper, we introduce SubScatter, a system that achieves both high throughput and excellent compatibility. It employs a single Complementary Code Keying (CCK)-modulated 802.11b WiFi symbol to transmit eight tag bits by manipulating the phase of the backscattered signal across eight discrete time slots within the symbol, thereby enhancing throughput. To ensure compatibility with commercial-off-the-shelf (COTS) radios, SubScatter exclusively utilizes the physical service data unit (PSDU) for recovering the backscatter modulation that conveys the tag bits. Additionally, SubScatter employs real-time Hamming distance calculations to synchronize the binary envelope from the synchronization circuit with a reference sequence, facilitating the sub-symbol backscatter modulation. In addition, we emphasize SubScatter’s versatility in adapting its modulation scheme to optimize performance across various channel conditions. Extensive experiments conducted with our prototype validate its effectiveness, achieving a throughput approximately 11 times higher than that of leading backscatter systems compatible with COTS radios. Our Hamming-distance-based synchronization method outperforms conventional designs that rely solely on signal power detection, successfully reducing the bit error rate (BER) from over 10% to below 1%. Moreover, SubScatter’s throughput can be flexibly adjusted from 11 Mbps to 1.57 Mbps, while the BER improves from 0.29% to 0.04%.

Improving transmission efficiency is a key objective in OFDM WiFi backscatter systems. A promising direction is sub-symbol-level tag modulation, which embeds more tag data within each OFDM symbol. However, we observe that fine-grained tag modulation is coupled with channel variation, which distorts the cascade structure between the two channels, transmitter-to-tag and tag-to-receiver, making the conventional channel estimation method in WiFi ineffective. Although recent systems have explored new channel estimation methods, their accuracy is limited and the modulation redundancy remains necessary. To address this problem, we present Fascatter, a high-throughput OFDM WiFi backscatter system that enables single-sample-level tag modulation without modulation redundancy. The key enabler is a new channel estimation method that independently estimates the two channels at per-subcarrier granularity. We construct channel observations from the LTF fields and reference symbols, and accurately solve the two channels through matrix decomposition. We further introduce polynomial smoothing and multi-symbol fine-tuning modules to improve estimation robustness. Experimental results demonstrate that the channel estimation results are close to the actual channel responses, and our method shows robust performance under a variety of complex channel conditions. In particular, Fascatter achieves a throughput of up to 15.9 Mbps, which is at least 3.2× over state-of-the-art systems. © 2026 IEEE.

Given the limited computing capabilities on autonomous vehicles, onboard processing of large volumes of latency-sensitive tasks presents significant challenges. While vehicular edge computing (VEC) has emerged as a solution, offloading data-intensive tasks to roadside servers or other vehicles faces communication-computing bottleneck, such as signal blockage from other large vehicles and limited computing resources of roadside servers. To address these challenges, Reconfigurable Intelligent Surface (RIS) can be leveraged to create line-of-sight channels, mitigate interference on the ground, and extend connectivity to more edge servers by elevating RIS adaptively. To this end, we propose RAISE, an optimization framework for RIS placement in multi-server VEC systems. Specifically, RAISE optimizes RIS altitude and tilt angle together with the optimal task assignment to maximize task throughput under deadline constraints. To find a solution, a two-layer optimization approach is proposed, where the inner layer exploits the unimodularity of the task assignment problem to derive the efficient optimal strategy while the outer layer develops a near-optimal hill climbing (HC) algorithm for RIS placement with low complexity. Extensive experiments demonstrate that the proposed RAISE framework consistently outperforms existing benchmarks.

Existing IoT systems suffer from restricted communication distances, high deployment costs, and frequent battery replacements, making them ineffective for managing healthcare data. This paper presents Prometheus, a self-powered wristband for reporting personal health status over long distances and intelligently managing healthcare data. Prometheus backscatters ambient BLE and ZigBee signals for low-power communication while incorporating a multi-source energy harvester to convert ambient RF, light, and heat into electricity. It also features a biochemical sensor array for monitoring sweat biochemical markers. Prototyped on a flexible PCB, Prometheus demonstrates impressive efficiency, consuming only 5.8 mW for sweat sensing, with BLE and ZigBee transmission energies significantly lower than standard electrochemical workstations and commercial alternatives. Our experiments show consistent signal quality at distances up to 20 meters. In summary, Prometheus emerges as a convenient, efficient, and self-powered wristband, promising to provide ubiquitous healthcare data management in our lives.

WiFi backscatter has attracted intensive attention because the large population of WiFi radios can provide plenty of excitation signals. However, WiFi backscatter communication has imposed unwanted constraints on either exciters or receivers since its inception. In this paper, we present Chameleon, a native WiFi backscatter system, where WiFi tags can generate native WiFi packets using uncontrolled productive WiFi signals as carriers. Our tag-only design requires no particular excitation patterns and no changes in software/hardware on WiFi network interface cards (NICs). The key idea is for the Chameleon tag to demodulate the productive WiFi signal and backscatter it into a full-function packet using on-the-fly modulation. To align tag decoding and modulation with excitation symbols, we design a time synchronization and clock compensation scheme suitable for low-power tags. We prototype WiFi tags using ultra-low-power FPGAs and evaluate them in real-world scenarios where excitations are ambient traffic and backscatter receivers are a wide range of commercial off-the-shelf (COTS) NICs. Comprehensive field studies show that the maximal backscatter throughput of Chameleon is almost 1 Mbps, which is over$125\times $and$1000\times $higher than what WiTAG and FS-Backscatter tags could achieve, respectively. We also show that Chameleon can natively communicate with various COTS WiFi devices on Windows, iOS, and Android platforms. We believe that this design will enable ubiquitous WiFi connectivity for billions of IoT devices via widely available mobile gadgets and existing wireless infrastructure.

Generally, image acquisition and storage requires a considerable amount of energy. To address this issue, we present an innovative approach towards developing a battery-free WiFi camera. Our system uses FRAM and DMA to cache images quickly, select appropriate color modes, and make some optimizations to the code, allowing for the acquisition and storage of a grayscale image of 144 × 176 pixels using only 6mJ of energy in 96ms. Our proposed system provides a promising step towards the realization of a battery-free WiFi camera, enabling energy-efficient image acquisition and storage in applications such as environmental monitoring, surveillance, and IoT.

WiFi backscatter communication has required unwanted constraints on either excitations or receivers since its inception eight years ago. We present Chameleon, the first native WiFi backscatter system where WiFi tags can generate native WiFi packets using uncontrolled productive WiFi as carriers. Our tag-only solution requires no particular excitation patterns and no change for software/hardware on WiFi NICs. The key insight is that the Chameleon tag can demodulate productive WiFi and backscatter this arbitrary carrier into a full-function packet using on-the-fly modulation. We prototype WiFi tags using ultra-low-power FPGAs and evaluate them in real-world scenarios where excitations are ambient traffic and backscatter receivers are a range of COTS NICs. Comprehensive field studies show that the maximal backscatter throughput of Chameleon is almost 1 Mbps, which is over 125× and 1000× better than WiTAG and FS-Backscatter. Also, we show that Chameleon can natively communicate with various COTS WiFi devices on Windows, iOS, and Android platforms. We believe this native WiFi backscatter design will enable ubiquitous WiFi connectivity for billions of IoT devices via widely available mobile gadgets and existing wireless infrastructure.

We present multiscatter, a novel battery-free backscatter design that can simultaneously work with multiple excitation signals for personal IoT sensors. Specifically, we show for the first time that the backscatter tag can identify various excitation signals in an ultra-low-power way, including WiFi, Bluetooth, and ZigBee. Further, we employ a new modulation approach, overlay modulation, that can leverage those excitation signals to convey tag data on top of productive data, which makes decoding both data possible with only a single personal radio. Moreover, we introduce a low-power listening scheme to improve energy efficiency. Since 2.4 GHz signals and personal radios are everywhere, multiscatter is readily deployable in our everyday IoT applications. We prototype multiscatter using an FPGA and various commodity radios. Extensive experiments show that for mixed 802.11b&n, Bluetooth and ZigBee signals, the average identification accuracy of four protocols is more than 93%. The maximal aggregate throughput of both productive and tag data is 278.4 kbps with a single Bluetooth radio. When the transmitter-to-tag distance is increased from 0.2 to 1.8 m, the maximal communication for BLE drops from 71 m to 29 m. And it can leverage excitation diversity to provide uninterrupted communication and greater throughput gains, whereas the single-protocol tag being idle when carrier signals are unavailable. With indoor office light as harvesting sources, the low-power listening scheme can support backscatter rate at 12 pkts/s.

Throughput is one of the key performance indicators in backscatter communication systems. Existing works either have limited throughput or modify the transmitter or receiver to fit the backscatter tag, thereby causing incompatibility with commodity radios. In this paper, we present SubScatter, which realizes a high throughput and keeps compatibility at the same time. For high throughput, SubScatter uses one CCK-modulated 802.11b WiFi symbol to carry eight tag bits by manipulating the phase of the backscattered signal in eight-time slots of a symbol separately. For compatibility with commercial-off-the-shelf (COTS) radios, SubScatter leverages only the physical service data unit (PSDU) to recover the backscatter modulation in which the tag bits are conveyed. And still, to fit the sub-symbol backscatter modulation, SubScatter calculates the Hamming distance between the binary envelope provided by the synchronization circuit and a reference sequence in real-time for synchronization. Extensive experiments in our prototype have proven the effectiveness of SubScatter. SubScatter achieves a throughput of about 11× over state-of-the-art backscatter systems compatible with COTS radios. The Hamming-distance-based synchronization outperforms the design of merely detecting the change of signal power and helps reduce the bit error rate from over 10% to below 1%.

We present CAB, a content-agnostic backscatter system that can demodulate both tag and ambient data from ambient backscattered WiFi alone. In contrast to prior ambient backscatter systems that use ambient data (content) as tag-data carriers, we focus on zero-subcarriers, which are invariant and independent for any ambient OFDM WiFi. The idea of using zero-subcarriers to convey tag data is simple and elegant. Not only does it for the first time remove the dependency of tag-data demodulation on ambient data, but it also significantly improves the practicality of ambient backscatter.

Existing backscatter systems using commodity radios all have a limited throughput, which prevents their usage in high-rate scenarios. We present SubScatter, which realizes a high throughput and keeps commodity-radio compatibility at the same time. Specifically, SubScatter boosts throughput for 11× by using 802.11b WiFi as excitation (11/8×) and designing sub-symbol modulation (8×).

We present Apollo, a self-powered wireless biochemical system that is wearable and can continuously monitor personal health states. It has three key enablers. First, we design an ultra-low-power Bluetooth backscatter module, which can effectively take BLE signals as excitations and transmit sensor data at high data rates to smartphones. Further, at the core of self-power management is a novel multi-source harvester that can transform RF, light, and thermal energies into electrical energy. Moreover, we introduce a biochemical sensor array that can accurately measure sweat metabolites and electrolytes.We prototype Apollo on a compactly integrated flexible PCB using all commercial off-the-shelf components. Through extensive experiments and field studies, we show that it is able to measure the glucose level in sweat within 5% error rate while consuming 5.8 mW for sensing and 720 pJ/bit for wireless transmissions. This translates to over 1700x lower power than standard electrochemical workstations, and 26x lower power than existing commercial BLE chipsets. We believe Apollo marks an important step towards the dream of ubiquitous healthcare for everyone as it provides a highly convenient, self-managed, and fully integrated way for health monitoring.

We present multiscatter, a novel backscatter design that can simultaneously work with multiple excitation signals for personal IoT sensors. Specifically, we show for the first time that the backscatter tag can identify various excitation signals in an ultra-low-power way, including WiFi, Bluetooth, and ZigBee. Further, we employ a new modulation approach, overlay modulation, that can leverage those excitation signals to convey tag data on top of productive data, which makes decoding both data possible with only a single personal radio. Since 2.4 GHz signals and personal radios are everywhere, multiscatter is readily deployable in our everyday IoT applications.