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.

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.

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 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.

Shallow waters hold ecological and economic importance. Traditional reflectance forward models, such as Hydrolight and Monte Carlo (MC), are difficult to access or time-consuming. Two-stream models show great performance in radiative transfer simulation, but most of them are applied in other mediums, or ignore the asymmetry scattering characteristic of shallow water. In this paper, we propose a general multilayer analytical radiative transfer-based (GMART) model considering the realistic volume scattering function of water body, which is theoretically applicable for various shallow waters. GMART results are validated against Hydrolight and MC. The mean absolute percentage error (MAPE) of GMART and Hydrolight remote sensing reflectance (Rrs) among different combinations of the bottom depth, solar zenith angle and wind speed spans in ranges of 5.37%-28.86%, 3.37%-39.28%,and 4.91%-26.73%, with root mean square error (RMSE) values from 1.73×10-4-4.49×10-3, 2.68×10-4-1.85×10-2and 1.59×10-4-2.92×10-3sr-1, respectively, for the coral, sand, and seagrass bottom. Comparisons of the bidirectional reflectance function with Hydrolight and MC indicate the capacity of GMART to compute bidirectional reflectance. Additionally, a comparison with field measurements is carried out. The minimum MAPE and RMSE between the modeled and measured normalizedRrsamong several stations in the Sanya coastal area are 13.99%, and 0.061, respectively. The mean MAPE and RMSE among 6 stations are 21.38% and 0.083, respectively. The field validation underscores the feasibility of the model in shallow water radiative transfer. Compared with MC, the computational efficiency of GMART is much higher. The new model is shown to be an alternative and efficient tool capable of addressing shallow water-related challenges across diverse environmental conditions.

Proximity-based apps have been changing the way people interact with each other in the physical world. To help people extend their social networks, proximity-based nearby-stranger (NS) apps that encourage people to make friends with nearby strangers have gained popularity recently. As another typical type of proximity-based apps, some ridesharing (RS) apps allowing drivers to search nearby passengers and get their ridesharing requests also become popular due to their contribution to economy and emission reduction. In this paper, we concentrate on the location privacy of proximity-based mobile apps. By analyzing the communication mechanism, we find that many apps of this type are vulnerable to large-scale location spoofing attack (LLSA). We accordingly propose three approaches to performing LLSA. To evaluate the threat of LLSA posed to proximity-based mobile apps, we perform real-world case studies against an NS app named Weibo and an RS app called Didi. The results show that our approaches can effectively and automatically collect a huge volume of users’ locations or travel records, thereby demonstrating the severity of LLSA. We apply the LLSA approaches against nine popular proximity-based apps with millions of installations to evaluate the defense strength. We finally suggest possible countermeasures for the proposed attacks.