Existing physical layer security schemes are inapplicable to legacy devices operating on long coherence-time channels, since they demand changes in the physical layer. To this end, a new physical-layer security scheme is developed to secure legacy clients. In this scheme, secret keys are generated by a client and transmitted to the access point (AP). To protect these keys, a separated device called secrecy protector (SP) transmits jamming signals to prevent eavesdroppers from overhearing the keys. The SP is equipped with multiple antennas, each of which transmits an independent jamming stream with a pseudo-preamble. Since the SP can share jamming signals with the AP secretly, the AP can use a certain analog network coding scheme to remove jamming signals and decode the keys. In contrast, eavesdroppers have no knowledge of jamming signals to decode the keys. However, the long coherence-time channels are vulnerable to eavesdroppers, as they can guess the channel coefficients in a brute force way and then remove the jamming signals. Thus, frequency diversity is exploited to enhance the security of the system. Moreover, the design of jamming mechanisms resists collusion among eavesdroppers. Therefore, secret keys can be secretly shared between the AP and a client. The developed scheme is implemented on a software-defined radio platform. Performance results demonstrate that it can effectively deliver secure communications without any changes to the physical layer of legacy clients.

Smart speakers allow users to interact with home appliances using voice commands and are becoming increasingly popular. While voice-based interface is intuitive, it is insufficient in many scenarios, such as in noisy or quiet environments, for users with language barriers, or in applications that require continuous motion tracking. Motion-based control is attractive and complementary to existing voice-based control. However, accurate and reliable room-scale motion tracking poses a significant challenge due to low SNR, interference, and varying mobility. To this end, we develop a novel recurrent neural network (RNN) based system that uses speakers and microphones to realize accurate room-scale tracking. Our system jointly estimates the propagation distance and angle-of-arrival (AoA) of signals reflected by the hand, based on AoA-distance profiles generated by 2D MUSIC. We design a series of techniques to significantly enhance the profile quality under low SNR. We feed the profiles in a recent history to our RNN to estimate the distance and AoA. In this way, we can exploit the temporal structure among consecutive profiles to remove the impact of noise, interference and mobility. Using extensive evaluation, we show our system achieves 1.2--3.7~cm error within 4.5~m range, supports tracking multiple users, and is robust against ambient sound. To our knowledge, this is the first acoustic device-free room-scale tracking system.

The popularity of smartphones has grown at an unprecedented rate, which makes smartphone based imaging especially appealing. In this paper, we develop a novel acoustic imaging system using only an off-the-shelf smartphone. It is an attractive alternative to camera based imaging under darkness and obstruction. Our system is based on Synthetic Aperture Radar (SAR). To image an object, a user moves a phone along a predefined trajectory to mimic a virtual sensor array. SAR based imaging poses several new challenges in our context, including strong self and background interference, deviation from the desired trajectory due to hand jitters, and severe speaker/microphone distortion. We address these challenges by developing a 2-stage interference cancellation scheme, a new algorithm to compensate trajectory errors, and an effective method to minimize the impact of signal distortion. We implement a proof-of-concept system on Samsung S7. Our results demonstrate the feasibility and effectiveness of acoustic imaging on a mobile.

With the availability of inexpensive and powerful drones, it is possible to let drones automatically follow a user for video taping. This can not only reduce cost, but also support video taping in situations where otherwise not possible (e.g., during private moments or at inconvenient locations like indoor rock climbing). While there have been many follow-me drones on the market for outdoors, which rely on GPS, enabling indoor follow-me function is more challenging due to the lack of an effective approach to track users in indoor environments. To this end, we develop a holistic system that lets a mobile phone carried by a user accurately track the drone's relative location and control it to maintain a specified distance and orientation for automatic video taping. We develop a series of techniques to (i) track a drone's location using acoustic signals with sub-centimeter errors even under strong propeller noise from the drone and complicated multipath in indoor environments, and (ii) solve practical challenges in applying model predictive control (MPC) framework to control the drone. The latter consists of developing measurement-based flight models, designing measurement techniques to provide feedback to the controller, and predicting the user's movement. We implement our system on AR Drone 2.0 and Samsung S7. The extensive evaluation shows that our drone can follow a user effectively and maintain a specified following distance and orientation within 2-3 cm and 1-3 degree errors, respectively. The videos taped by the drone during flight are smooth according to the jerk metric.

Next generation devices, such as virtual reality (VR), augmented reality (AR), and smart appliances, demand a simple and intuitive way for users to interact with them. To address such needs, we develop a novel acoustic based device-free tracking system, called Strata, to enable a user to interact with a nearby device by simply moving his finger. In Strata, a mobile (e.g., smartphone) transmits known audio signals at inaudible frequency, and analyzes the received signal reflected by the moving finger to track the finger location. To explicitly take into account multipath propagation, the mobile estimates the channel impulse response (CIR), which characterizes signal traversal paths with different delays. Each channel tap corresponds to the multipath effects within a certain delay range. The mobile selects the channel tap corresponding to the finger movement and extracts the phase change of the selected tap to accurately estimate the distance change of a finger. Moreover, it estimates the absolute distance of the finger based on the change in CIR using a novel optimization framework. We then combine the absolute and relative distance estimates to accurately track the moving target. We implement our tracking system on Samsung Galaxy S4 mobile phone. Through micro-benchmarks and user studies, we show that our system achieves high tracking accuracy and low latency without extra hardware.

Video games, Virtual Reality (VR), Augmented Reality (AR), and Smart appliances (e.g., smart TVs) all call for a new way for users to interact and control them. This paper develops high-preCision Acoustic Tracker (CAT), which aims to replace a traditional mouse and let a user play games, interact with VR/AR headsets, and control smart appliances by moving a smartphone in the air. Achieving high tracking accuracy is essential to provide enjoyable user experience. To this end, we develop a novel system that uses audio signals to achieve mm-level tracking accuracy. It lets multiple speakers transmit inaudible sounds at different frequencies. Based on the received sound, our system continuously estimates the distance and velocity of the mobile with respect to the speakers to continuously track it. At its heart lies a distributed Frequency Modulated Continuous Waveform (FMCW) that can accurately estimate the absolute distance between a transmitter and a receiver that are separate and unsynchronized. We further develop an optimization framework to combine FMCW estimation with Doppler shifts and Inertial Measurement Unit (IMU) measurements to enhance the accuracy, and efficiently solve the optimization problem. We implement two systems: one on a desktop and another on a mobile phone. Our evaluation and user study show that our system achieves high tracking accuracy and ease of use using existing hardware.

Video games, virtual reality, augmented reality, and smart appliances all call for a new way for users to interact and control them. This paper develops high-preCision Acoustic Tracker (CAT), which aims to replace a traditional mouse and let a user control various devices by moving a smartphone in the air. At its heart lies a distributed Frequency Modulated Continuous Waveform (FMCW) that can accurately estimate the distance between a transmitter and a receiver that are separate and unsynchronized. We further develop an optimization framework to combine FMCW estimation with Doppler shifts to enhance the accuracy. We implement CAT on a mobile phone. The performance evaluation and user study show that our system achieves high tracking accuracy and ease of use using existing hardware.

Analog network coding (ANC) is effective in improving spectrum efficiency. To coordinate ANC among multiple nodes without relying on complicated scheduling algorithm and network optimization, a new random access MAC protocol, called ANC-ERA, is developed to dynamically form ANC-cooperation groups in an ad hoc network. ANC-ERA includes several key mechanisms to maintain high performance in medium access. First, network allocation vectors (NAV) of control frames are properly set to avoid over-blocking of channel access. Second, a channel occupation frame (COF) is added to protect vulnerable periods during the formation of ANC cooperation. Third, an ACK diversity mechanism is designed to reduce potentially high ACK loss probability in ANC-based wireless networks. Since forming an ANC cooperation relies on bi-directional traffic between the initiator and the cooperator, the throughput gain from ANC drops dramatically if bi-directional traffic is not available. To avoid this issue, the fourth key mechanism, called flow compensation, is designed to form different types of ANC cooperation among neighboring nodes of the initiator and the cooperator. Both theoretical analysis and simulations are conducted to evaluate ANC-ERA. Performance results show that ANC-ERA works effectively in ad hoc networks and significantly outperforms existing random access MAC protocols.

The applicability of analog network coding (ANC) to a wireless network is constrained by several limitations: 1) some ANC schemes demand fine-grained frame-level synchronization, which cannot be practically achieved in a wireless network; 2) others support only a specific type of modulation or require equal frame size in concurrent transmissions. In this paper, a new ANC scheme, called restriction-free analog network coding (RANC), is developed to eliminate the above limitations. It incorporates several function blocks, including frame boundary detection, joint channel estimation, waveform recovery, circular channel estimation, and frequency offset estimation, to support random concurrent transmissions with arbitrary frame sizes in a wireless network with various linear modulation schemes. To demonstrate the distinguished features of RANC, two network applications are studied. In the first application, RANC is applied to support a new relaying scheme called multi-way relaying, which significantly improves the spectrum efficiency as compared to two-way relaying. In the second application, RANC enables random-access-based ANC in an ad hoc network where flow compensation can be gracefully exploited to further improve the throughput performance. RANC and its network applications are implemented and evaluated on universal software radio peripheral (USRP) software radio platforms. Extensive experiments confirm that all function blocks of RANC work effectively without being constrained by the above limitations. The overall performance of RANC is shown to approach the ideal case of interference-free communications. The results of experiments in a real network setup demonstrate that RANC significantly outperforms existing ANC schemes and achieves constraint-free ANC in wireless networks.

No abstract available.

Maximum power point tracking (MPPT) achieves maximum power output for a photovoltaic (PV) system under various environmental conditions. It significantly improves the energy efficiency of a specific PV system. However, when an increasing number of PV systems are connected to a distribution grid, MPPT poses several risks to the grid: 1)over-voltage problem, i.e., voltage in the distribution grid exceeds its rating; and 2)reverse power-flow problem, i.e., power that flows into the grid exceeds an allowed level. To solve these problems, power point tracking of all PV systems in the same distributed grid needs to be coordinated via a communication network. Thus, coordinated power point tracking (CPPT) is studied in this paper. First, an optimization problem is formulated to determine the power points of all PV systems, subject to the constraints of voltage, reverse power flow, and fairness. Conditions that obtain the optimal solution are then derived. Second, based on these conditions, a distributed and practical CPPT scheme is developed. It coordinates power points of all PV systems via a communication network, such that: 1) voltage and reverse power flow are maintained at a normal level; and 2) each PV system receives a fair share of surplus power. Third, a wireless mesh network (WMN) is designed to support proper operation of the distributed CPPT scheme. CPPT is evaluated through simulations that consider close interactions between WMN and CPPT. Performance results show that: 1) CPPT significantly outperforms MPPT by gracefully avoiding both overvoltage and reverse power-flow problems; 2) CPPT achieves fair sharing of surplus power among all PV systems; and 3) CPPT can be reliably conducted via a WMN.

A multi-antenna access point (AP) can communicate simultaneously with multiple clients, however, this multi-user MIMO (MU-MIMO) capability is underutilized in conventional 802.11 wireless LANs (WLANs). To address this problem, researchers have recently developed a CSMA/CA-based MAC protocol to support concurrent transmissions from different clients. In this paper, we propose an analytical model to characterize the saturation throughput and mean access delay of this CSMA/CA-based MAC protocol operating in an MU-MIMO WLAN. We also consider and model a distributed opportunistic transmission scheme, where clients are able to contend for the concurrent transmission opportunities only when their concurrent rates exceed a threshold. Comparisons with simulation results show that our analytical model provides a close estimation of the network performance. By means of the developed model, we evaluate the throughput and delay performance with respect to different network parameters, including the backoff window sizes, the number of AP's antennas, the network size, and the threshold of the opportunistic transmission scheme. Performance optimization over key parameters is also conducted for the transmission schemes.