With the advantages of easy deployment and flexible usage, Unmanned Aerial Vehicle (UAV) has advanced the Multi-Target Tracking (MTT) applications. The UAV-MTT system has great potentials to execute dull, dangerous, and critical missions for frontier defense and security. A key challenge in UAV-MTT is how to coordinate multiple UAVs to track diverse invading targets accurately and consecutively. In this paper, we propose a UAV swarm-based cooperative tracking architecture to systematically improve the UAV tracking performance. We design an intelligent UAV swarm-based cooperative algorithm for consecutive target tracking and physical collision avoidance. Moreover, we design an efficient cooperative algorithm to predict the trajectory of invading targets accurately. Our simulation results demonstrate that the swarm behaviors stay stable in realistic scenarios with perturbing obstacles. Compared with state-of-the-art solutions such as the matched deep Q-network, our algorithms can increase tracking accuracy by 60%, reduce tracking delay by 23%, and achieve physical collision-avoidance during the tracking process.

Artificial lighting has been used mainly for illumination for more than a century. Only recently, we have started to transform our lighting infrastructure to provide new services such as sensing and communication. These advancements have two key requirements: the ability to modulate light sources (for data transmission) and the presence of photodetectors on objects (for data reception). These requirements assume that the system has direct control over the transmitter and receiver, as in any traditional communication system. But not all lights can be modulated, and most objects do not have photodetectors. To overcome these limitations, researchers are developing novel networks that (i) exploit passive light sources that cannot be directly modulated, such as the sun, and (ii) leverage reflections from the external surfaces of objects to create a new generation of sensing and communication networks with visible light that is sustainable and does not require active control over the system. In this survey, we propose a taxonomy to analyze state-of-the-art contributions. We also identify the overarching principles, challenges, and opportunities of this new rising area.

We propose a concept of coverage-bounding and 'visual' wireless communication-HODOR 1-to secure the Internet of Things (IoT). Coverage-bounding means the communication coverage is controlled accurately in 3-dimensions. 'Visual' implies that the communication coverage and process are visible to user, representing an important and user-friendly side-channel for se-curing IoT. HODOR can provide secure wireless communication both psychologically (visible to users) and technically (nodes only communicate with each other within their delimited coverage). It can benefit IoT applications for secure wireless communications, especially those that demand secure interactions in proximity.

Visible Light Communication (VLC) is a promising technology for future wireless communications. By modulating the visible light - -that has about 10,000x larger frequency band than that of radios - -to transmit data, VLC has the potential to provide ultra-high-speed wireless connectivities. However, it also has limitations such as i) surrounding objects can easily block VLC links, and ii) intense ambient light can saturate the photodiodes of VLC receivers. In this work, from a different angle compared with state-of-the-art solutions, we utilize the side channel of VLC - -a Radio Frequency (RF) channel created unintentionally during the transmission process of VLC - -to break the above-mentioned VLC limitations. The key enabler is that the side RF channel also contains the data information transmitted in the VLC link. When the VLC link is blocked or saturated, we can utilize the side channel, capable of penetrating through blockages and not affected by ambient light, to assist VLC transmissions. Thus a user service relying on VLC transmissions will not be interrupted. Besides the simple Single-Input Single-Output (SISO) case, we consider challenging scenarios where multiple VLC chains are synchronized to form Multiple-Input Multiple/Single-Output (MIMO/MISO) transmission strategies. To make our system practical, we address several challenges spanning from hardware to software. Compared to state-of-the-art design, we reduce the size of the receiving coil by nearly 90%. Experimental evaluations show that our system can decode overlapped RF signals created by a 3X3 MIMO VLC network five meters away, with various blockages in between. Our system also works under intense ambient light conditions (> 100,000 lux).

A massive MIMO network can serve ten's of users simultaneously. However, in dense scenarios the users are potentially closely-spaced, potentially resulting in substantial inter-user interference. Scheduling can overcome this by selecting the users that lead to the highest combined spectral efficiency. As scheduling comes with a significant pilot overhead, an alternative strategy could minimize user correlation by distributing the antenna elements in space. In this paper, we propose a comprehensive system study including antenna topology and distribution, user scheduling and pilot overhead reduction. Our user scheduling and pilot reduction algorithms are evaluated using system level simulations relying on indoor line-of-sight channel measurements from a 64 antenna base station at 2.61GHz. To have a thorough evaluation of the proposed algorithm, we consider four different antenna topologies, including co-located and distributed placement of the base station arrays. Our evaluation shows that in a conference room with 64 densely deployed users, our proposed low complexity algorithm can improve the spectral efficiency by at least 14% compared to random user selection with the best antenna distribution strategy. Finally, our results show that by relying on channel hardening, we reduce the pilot overhead by 3.2 \times.

Visible Light Communication (VLC) based on LEDs has been a hot topic investigated for over a decade. However, most of the research efforts assume the intensity of LED light is constant. This hypothesis is not true when Smart Lighting is introduced to VLC, which requires LEDs to adapt their brightness based on the intensity of natural ambient light. Smart lighting saves power consumption and improves user comfort. However, intensity adaptation severely affects the throughput performance of data communication. In this paper, we propose SmartVLC, a system that can maximize the throughput (benefit communication) while still maintaining the LEDs' illumination function (benefit smart lighting). A novel Adaptive Multiple Pulse Position Modulation (AMPPM) scheme is proposed to support fine-grained dimming levels to avoid flickering while maximizing the throughput under each dimming level. SmartVLC is implemented on off-the-shelf commodity hardware. Several real-life challenges in both hardware and software are addressed to make it a robust real-time system. Comprehensive experiments are carried out to evaluate the system performance under multifaceted scenarios. Experimental results demonstrate that SmartVLC supports a communication distance up to 3.6m, and improves the throughput achieved with two state-of-the-art approaches by 40 and 12 percent on average, respectively, without bringing any flickering to users.

LED luminaries are now deployed densely in indoor areas to provide uniform illumination. Visible Light Communication (VLC) can also benefit from this dense LED infrastructure. In this paper, we propose DenseVLC, a cell-free massive MIMO networking system enabled by densely distributed LEDs, that forms different beamspots to simultaneously serve multiple receivers. This is a cell-free system, as there is no notion of autonomous cells and transmitters cooperate to jointly serve the users. Given a power budget for communication, DenseVLC assigns the power budget among the distributed LEDs to optimize the system throughput and user fairness. We formulate an optimization problem to derive the optimal policy for the power allocation. Our insights from the optimal policies allow us to simplify DenseVLC's system design and propose a heuristic algorithm that can reduce the complexity by 99.96%. Besides, we propose a novel synchronization method using non-line-of-sight VLC to synchronize all the transmitters that will form a beamspot to serve the same receiver. We implement DenseVLC with off-the-shelf devices, solve practical challenges in the system design, and evaluate it with extensive and realistic experiments in a system of 36 transmitters and 4 receivers in an area of\:\text{m}\,\,\times 3\:\text{m}$. Our results show that DenseVLC can improve the average system throughput by 45%, or improve the average power efficiency by 2.3 times, while maintaining the requirement for uniform illumination. Finally, we demonstrate that DenseVLC is robust against blockage.

We analyze and optimize the performance of a new type of channel that exploits sunlight for wireless communication. Recent advances on visible light backscatter have shown that if mobile objects attach distinctive reflective patterns to their surfaces, simple photosensors deployed in our environments can decode the reflected light signals. Although the vision is promising, only initial feasibility studies have been performed so far. There is no analysis on how much information this channel can transmit or how reliable the links are. Achieving this vision is a complex endeavour because we have no control over (i) the sun or clouds, which determine the amount and direction of light intensity, and (ii) the mobile object, which determines the modulated reflection of sunlight. We investigate the impact of the surrounding light intensity and physical properties of the object (reflective materials, size and speed) to design a communication system that optimizes the encoding and decoding of information with sunlight. Our experimental evaluation, performed with a car moving on a regular street, shows that our analysis leads to significant improvements across many dimensions. Compared to the state of the art, we can encode seven times more information, and decode this information reliably from an object moving three times faster (53km/h) at a range that is four times longer (4m) and with three times lower light intensity (cloudy day).

Localization based on visible light is gaining significant attention. But most existing studies rely on a key requirement: the object of interest needs to carry an optical receiver (camera or photodiode). We remove this requirement and investigate the possibility of achieving accurate localization in a passive manner, that is, without requiring objects to carry any optical receiver. To achieve this goal, we exploit the reflective surfaces of objects and the unique propagation properties of LED luminaires. We present geometric models, a testbed implementation, and empirical evaluations to showcase the opportunities and challenges posed by this new type of localization. Overall, we show that our method can track with high accuracy (few centimeters) a subset of an object’s trajectory and it can also identify passively the object’s ID.

We introduce the OpenVLC1.2 platform for research in Visible Light Communication (VLC) systems. The platform builds on top of previous versions, that has attracted dozens of users from the research community. We maintain its advantages such as the support for communication with TCP/IP layers, software-based and programmable MAC and PHY layers, and low-cost front-end. In this new version, we make an effort to increase data rate and its overall performance. OpenVLC1.2 is available to the research community.