MobiCom 2023 Papers

Managing network configuration and improving service experience effectively is essential for cellular service providers (CSPs). This is challenging because of cellular networks' large scale and complexity, the wide variety of configuration parameters, and the performance impact tradeoffs resulting across multiple metrics and geographical locations. This paper focuses on learning and using network contexts to recommend performance-improving configurations. While learning contexts, one must carefully account for the configuration parameter dependency, performance impact confusion that can arise due to co-occurring unrelated changes, and uneven change deployment distribution across locations. We present a new solution Chroma that addresses the above challenges. Using real-world data collected from a large operational LTE and 5G cellular service provider, we thoroughly evaluate and demonstrate the efficacy of Chroma. We successfully trial Chroma on an operational cellular network and highlight its benefits in practical settings.

Notification-based authentication is an emerging Two-Factor Authentication (2FA) and passwordless solution that leverages interactive notifications on mobile devices to establish an additional layer of security beyond passwords. This method has gained popularity due to its convenience and ease of deployment in organizational settings. In this work, we aim to evaluate the effectiveness of notification-based authentication systems when a malicious entity is present on the user's computer, such as a keylogger or malicious extension, without compromising the mobile devices or communication channels. Furthermore, we investigate how the lack of information provided to users during the authentication workflow can lead to the approval of malicious authentication requests. Notably, we highlight the vulnerability of cross-service attacks, where an attacker authenticates to Service B while the user is attempting to authenticate to Service A. Our proof-of-concept attack program demonstrates the susceptibility of various notification-based authentication systems, and our user study reveals an alarming 82.2% cross-service attack success rate. These findings suggest a potential vulnerability in notification-based authentication systems, where the attacker compromise user account without compromising possession-factor device, such as smartphones.

Cameras are widely adopted as the sensing device in fiducial marker systems. The captured videos however may expose sensitive information to attackers. We propose a privacy-preserving fiducial marker system, ReMark, which is based on retroreflector and single-pixel imaging (SPI), and captures only the minimal information needed for positioning and identifying markers. ReMark is built upon a state-of-the-art light-weight neural network (NN), which recovers the scene in the SPI system. Another light-weight NN is proposed for pose estimation of markers. They are trained with synthesized large datasets, and proved to adapt well to real-world data. The pose estimation NN adopts a specialized output embedding to address the symmetry-related issues, and soft-decision decoding is used to mitigate the distortion in recovered scenes. Detailed evaluation shows that, with 4.8 cm markers at 3.00 m distance and 1.0 W LED power, ReMark achieves a decode error rate of 2.1% with tilt angle ≤ 30°, searching in a dictionary of size 1,000. Evaluation of worst-case scenarios shows that an attacker could hardly acquire sensitive information even with access to raw data.

This paper proposes Meta-Speaker, an innovative speaker capable of projecting audible sources into the air with a high level of manipulability. Unlike traditional speakers that emit sound waves in all directions, Meta-Speaker can manipulate the granularity of the audible region, down to a single point, and can manipulate the location of the source. Additionally, the source projected by Meta-Speaker is a physical presence in space, allowing both humans and machines to perceive it with spatial awareness. Meta-Speaker achieves this by leveraging the fact that air is a nonlinear medium, which enables the reproduction of audible sources from ultrasounds. Meta-Speaker comprises two distributed ultrasonic arrays, each transmitting a narrow ultrasonic beam. The audible source can be reproduced at the intersection of the beams. We present a comprehensive profiling of Meta-Speaker to validate the high manipulability it offers. We prototype Meta-Speaker and demonstrate its potential through three applications: anchor-free localization with a median error of 0.13 m, location-aware communication with a throughput of 1.28 Kbps, and acoustic augmented reality where users can perceive source direction with a mean error of 9.8 degrees.

With the potential for connecting billions of WiFi devices to low-power Bluetooth/FSK devices, WiFi-Bluetooth cross-technology communication (CTC) has drawn significant interests from academia and industry. However, state-of-the-art CTC solutions either are limited to one-way communication, or require multiple chips with hardware modifications.

This paper presents MilliSign, a guidance system based on a batteryless tag to support unmanned aerial vehicles in all-weather conditions. Conventional batteryless guidance systems using visual signs fail to work in inclement weather due to poor visibility. The need for all-weather operation with long-range readability encourages the use of millimeter wave (mmWave) radar, which poses challenges in providing a wide 3-D read range and low-cost operation. To address these challenges, we introduce a corner reflector (CR) array-based chipless RFID tag and a one-shot slant range reading procedure with COTS mmWave radar. We establish a novel design method for the shape and alignment of CR units to decrease the tag's size and expand the 3-D read range. Additionally, we develop a signal-processing pipeline based on Root-MUSIC to achieve accurate power and spatial estimation, which facilitate automatic tag detection. Our evaluation demonstrates that the tag, measuring 292 mm × 600 mm × 19 mm and storing 8 bits, can be read by mmWave radar from a distance of more than 10 m with a viewing angle of more than 30° in elevation and azimuth. Moreover, its performance remains stable in poor visibility conditions and multipath-rich environments.

Recent years have witnessed a tremendous amount of interest in wireless sensing, i.e., instead of employing traditional sensors, wireless signal is utilized for sensing purposes. Contact-free wireless sensing has been successfully demonstrated using various RF signals such as WiFi, RFID, LoRa, and mmWave, enabling a large range of applications. However, limited by hardware thermal noise, the granularity of RF sensing is still relatively coarse. In this paper, instead of using the macro signal power/phase for sensing, we propose the first quantum wireless sensing system, which uses the micro energy level of atoms for sensing, improving the sensing granularity by an order of magnitude. The proposed quantum wireless sensing system is capable of utilizing a wide spectrum of frequencies (e.g., 2.4 GHz, 5 GHz and 28 GHz) for sensing. We demonstrate the superior performance of quantum wireless sensing with two widely-used signals, i.e., WiFi and 28 GHz millimeter wave. We show that quantum wireless sensing can push the sensing granularity of WiFi from millimeter level to sub-millimeter level and push the sensing granularity of millimeter wave to micrometer level.

Low-earth-orbit (LEO) satellite mega-constellations, such as SpaceX Starlink, are under rocket-fast deployments and promise broadband Internet to remote areas that terrestrial networks cannot reach. For mission safety and sustainable uses of space, Starlink has adopted a proprietary onboard autonomous driving system for its extremely mobile LEO satellites. This paper demystifies and diagnoses its impacts on the LEO mega-constellation and satellite networks. We design a domain-specific method to characterize key components in Starlink's autonomous driving from various public space situational awareness datasets, including continuous orbit maintenance, collision avoidance, and maneuvers between orbital shells. Our analysis shows that, these operations have mixed impacts on the stability and performance of the entire mega-constellation, inter-satellite links, topology, and upper-layer network functions. To this end, we investigate and empirically assess the potential of networking-autonomous driving co-designs for the upcoming satellite networks.

Acoustic sensing on smartphones has gained extensive attention from both industry and research communities. Prior studies suffer from one fundamental limit, i.e., audio sampling rates on smartphones are constrained at 48 kHz. In this work, we present PowerPhone, a software reconfiguration to support higher sampling rates on both microphones and speakers of smartphones. We reverse-engineered more than 100 smartphones and found that their sampling rates can be reconfigured to 192 kHz. We conducted benchmark experiments and showcased field studies to demonstrate the unleashed sensing capability using our reconfigured smart-phones. First, we improve the sensing resolution from 7 cm to 1cm and enable multi-finger gesture recognition on smart-phones. Second, we push the sensing granularity of subtle movements to 2 μm and show the feasibility of turning the smartphone into a micrometer-level machine vibration meter. Third, we increase the sensing range to 6 m and showcase room-scale human presence detection using a smartphone. Finally, we demonstrate that PowerPhone can enable new applications that were previously infeasible. Specifically, we can detect the home appliance status by analyzing ultrasonic leakages above 24 kHz from the wireless charger while charging a smartphone. Our open-source artifacts can be found at: https://powerphone.github.io.

In this paper, we propose a new paradigm in intelligent surface design for field programming and multi-point focusing. We approach this problem from an entirely different vantage point by leveraging edges and the corresponding Geometrical Theory of Diffraction (GTD), allowing us to avoid the use of highly specialized and expensive element designs. More specifically, we show that a lattice of edge elements (i.e., cheap, thin, rectangular metal plates with length long enough as compared to width) can provide a rich repertoire for programming the RF field. When a wave is incident on an edge, a cone of outgoing rays emerges, known as a Keller cone. When considering a lattice of such edge elements, we then have a rich set of "knobs" for RF field programming, via changing the orientation of the edge elements and exploiting the exiting Keller cones. We then show how to electromagnetically model and design a practical edge element. We further propose an efficient algorithm to configure the orientations of the edges to achieve the desired multi-point focusing. We build sample prototypes of our proposed paradigm, using off-the-shelf material (i.e., 7 cent metal plates). We then show several real-world experiments in three different indoor areas, where an edge lattice focuses the transmitted wave of a WiFi card of a laptop on up to and including 4 focal points (maximum achieved in the literature albeit with much more expensive element designs). Overall, the paper shows the rich potential of edges for RF field programming.

Virtual devices based on device emulation have been widely used in lab research of mobile app testing for their efficiency and low cost. However, it remains controversial to use virtual devices for app testing in industry, given the inherent difficulties of high-fidelity emulation across diverse mobile systems and devices. Hence, mobile app companies still rely on physical device farms or services like AWS Device Farm.