Other affiliations: Shanghai Jiao Tong University
Bio: Sihui Han is an academic researcher from University of Michigan. The author has contributed to research in topics: Signal & Channel state information. The author has an hindex of 6, co-authored 6 publications receiving 269 citations. Previous affiliations of Sihui Han include Shanghai Jiao Tong University.
••18 May 2015
TL;DR: The extensive evaluation results show that V-Sense is accurate in determining and differentiating various steering maneuvers, and is thus useful for a wide range of safety-assistance applications without additional sensors or infrastructure.
Abstract: Detecting how a vehicle is steered and then alarming drivers in real time is of utmost importance to the vehicle and the driver's safety, since fatal accidents are often caused by dan- gerous steering. Existing solutions for detecting dangerous maneuvers are implemented either in only high-end vehicles or on smartphones as mobile applications. However, most of them rely on the use of cameras, the performance of which is seriously constrained by their high visibility requirement. Moreover, such an over/sole-reliance on the use of cameras can be a distraction to the driver. To alleviate these problems, we develop a vehicle steering detection middleware called V-Sense which can run on commodity smartphones without additional sensors or infrastructure support. Instead of using cameras, the core of V-Sense/ senses a vehicle's steering by only utilizing non-vision sensors on the smartphone. We design and evaluate algorithms for detecting and differentiating various vehicle maneuvers, including lane-changes, turns, and driving on curvy roads. Since V-Sense does not rely on use of cameras, its detection of vehicle steering is not affected by the (in)visibility of road objects or other vehicles. We first detail the design, implementation and evaluation of V-Sense and then demonstrate its practicality with two prevalent use cases: camera-free steering detection and fine-grained lane guidance. Our extensive evaluation results show that V-Sense is accurate in determining and differentiating various steering maneuvers, and is thus useful for a wide range of safety-assistance applications without additional sensors or infrastructure.
TL;DR: This paper investigates the coverage and energy consumption control in mobile heterogeneous wireless sensor networks (WSNs) and proposes the equivalent sensing radius (ESR) for both cases and derives the critical ESR correspondingly.
Abstract: In this paper, we investigate the coverage and energy consumption control in mobile heterogeneous wireless sensor networks (WSNs). By term heterogeneous, we mean that sensors in the network have various sensing radius, which is an inherent property of many applied WSNs. Two sensor deployment schemes are considered-uniform and Poisson schemes. We study the asymptotic coverage under uniform deployment scheme with i.i.d. and 1-D random walk mobility model, respectively. We propose the equivalent sensing radius (ESR) for both cases and derive the critical ESR correspondingly. Our results show that the network performance largely depends on ESR. By controlling ESR, we can always promise the network achieve full coverage, regardless of the total number of sensors or the sensing radius of a single senor under random mobility patterns, which is a much easier and more general way to operate coverage control. Meanwhile, we can operate a tradeoff control between coverage performance and energy consumption by adjusting ESR. We demonstrate that 1-D random walk mobility can decrease the sensing energy consumption under certain delay tolerance, though requires larger ESR. Also, we characterize the role of heterogeneity in coverage and energy performance of WSNs under these two mobility models, and present the discrepancy of the impact of heterogeneity under different models. Under the Poisson deployment scheme, we investigate dynamic k-coverage of WSNs with 2-D random walk mobility model. We present the relation between network coverage and the sensing range, which indicates how coverage varies according to sensing capability. Both k -coverage at an instant and over a time interval are explored and we derive the expectation of fraction of the whole operational region that is k-covered, which also identifies the coverage improvement brought by mobility.
••03 Nov 2014
TL;DR: A revision of the current CSI feedback scheme is suggested and a novel CSI feedback system is proposed to prevent CSI forging without requiring any modification at the client side, thus facilitating its deployment.
Abstract: Multiple-In-Multiple-Out (MIMO) offers great potential for increasing network capacity by exploiting spatial diversity with multiple antennas. Multiuser MIMO (MU-MIMO) further enables Access Points (APs) with multiple antennas to transmit multiple data streams concurrently to several clients. In MU-MIMO, clients need to estimate Channel State Information (CSI) and report it to APs in order to eliminate interference between them. We explore the vulnerability in clients' plaintext feedback of estimated CSI to the APs and propose two advanced attacks that malicious clients can mount by reporting forged CSI: (1) sniffing attack that enables concurrently transmitting malicious clients to eavesdrop other ongoing transmissions; (2) power attack that enables malicious clients to enhance their own capacity at the expense of others?. We have implemented and evaluated these two attacks in a WARP testbed. Based on our experimental results, we suggest a revision of the current CSI feedback scheme and propose a novel CSI feedback system, called the CSIsec, to prevent CSI forging without requiring any modification at the client side, thus facilitating its deployment.
TL;DR: A distributed-centralized and incentive-aware spectrum sharing scheme for the multiple-PU scenario, which introduces a Random Leader who is elected randomly from SUs or PUs, which obtains the socially optimal throughput while accounting for both SUs' and PUs' incentives.
Abstract: In Cognitive Radio Networks (CRNs), Primary Users (PUs) can share their idle spectra with Secondary Users (SUs) under certain mechanisms. In this paper, we propose a distributed-centralized and incentive-aware spectrum sharing scheme for the multiple-PU scenario, which introduces a Random Leader who is elected randomly from SUs or PUs. The distributed aspect of our scheme lies in that it requires no central control entities, which can be independently implemented within a distributed spectrum market. The centralized aspect is that the leader draws up and assigns the socially optimal contracts for all PUs and SUs in a centralized manner, which maximizes the throughput of the whole network and attains the economic robustness (including Incentive Compatibility and Individual Rationality). Analysis shows that the proposed scheme takes in the advantages of both centralized and distributed schemes but overcomes their weaknesses. We use the proposed scheme to study two sharing scenarios: the short-term and the long-term spectrum sharing. The Short-Term Sharing (STS) focuses on distributing PUs' idle spectra within one time slot while the Long-Term Sharing (LTS) considers multiple slots, where the spectrum mobility must be investigated. As an integrated design of both STS and LTS, our scheme not only fulfils SUs' heterogeneous spectrum requirements but also obtains the socially optimal throughput while accounting for both SUs' and PUs' incentives.
••01 May 2017
TL;DR: OptRe is proposed which optimally places metallic reflectors — providing a highly reflective surface that can reflect impinging signals almost 100% — in indoor environments to reduce the reflection loss and enhance wireless transmissions.
Abstract: Signal decay is the fundamental problem of wireless communications, especially in an indoor environment where line-of-sight (LOS) paths for signal propagation are often blocked and various indoor objects exacerbate signal fading. There are three reasons for signal decay: long transmission distance, signal penetration, and reflection. In this paper, we propose OptRe which optimally places metallic reflectors — providing a highly reflective surface that can reflect impinging signals almost 100% — in indoor environments to reduce the reflection loss and enhance wireless transmissions. It enhances both WiFi signal and low-power IoT devices without changing their configurations or network protocols. To enable OptRe, we first develop an empirical signal propagation model that can accurately estimate the signal strength and adapt itself to the reflectors' location. Using micro-benchmarks, our empirical signal propagation model is shown to be more accurate than the other existing path loss models. We also optimally place reflectors to maximize the worst-case signal coverage within the target indoor areas. Our extensive experimental evaluation results have shown OptRe to enhance signal strength for different types of wireless signals by almost 2x.
TL;DR: This paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies which are adaptive, distributed, asynchronous, and verifiably correct.
Abstract: This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.
TL;DR: The HyperSurface tiles as discussed by the authors can effectively re-engineer electromagnetic waves, including steering towards any desired direction, full absorption, polarization manipulation, and more, by using planar meta-materials.
Abstract: Electromagnetic waves undergo multiple uncontrollable alterations as they propagate within a wireless environment. Free space path loss, signal absorption, as well as reflections, refractions and diffractions caused by physical objects within the environment highly affect the performance of wireless communications. Currently, such effects are intractable to account for and are treated as probabilistic factors. The paper proposes a radically different approach, enabling deterministic, programmable control over the behavior of the wireless environments. The key-enabler is the so-called HyperSurface tile, a novel class of planar meta-materials which can interact with impinging electromagnetic waves in a controlled manner. The HyperSurface tiles can effectively re-engineer electromagnetic waves, including steering towards any desired direction, full absorption, polarization manipulation and more. Multiple tiles are employed to coat objects such as walls, furniture, overall, any objects in the indoor and outdoor environments. An external software service calculates and deploys the optimal interaction types per tile, to best fit the needs of communicating devices. Evaluation via simulations highlights the potential of the new concept.
TL;DR: A novel coverage control algorithm based on Particle Swarm Optimization (PSO) is presented that can effectively improve coverage rate and reduce energy consumption in WSNs.
Abstract: Wireless Sensor Networks (WSNs) are large-scale and high-density networks that typically have coverage area overlap. In addition, a random deployment of sensor nodes cannot fully guarantee coverage of the sensing area, which leads to coverage holes in WSNs. Thus, coverage control plays an important role in WSNs. To alleviate unnecessary energy wastage and improve network performance, we consider both energy efficiency and coverage rate for WSNs. In this paper, we present a novel coverage control algorithm based on Particle Swarm Optimization (PSO). Firstly, the sensor nodes are randomly deployed in a target area and remain static after deployment. Then, the whole network is partitioned into grids, and we calculate each grid’s coverage rate and energy consumption. Finally, each sensor nodes’ sensing radius is adjusted according to the coverage rate and energy consumption of each grid. Simulation results show that our algorithm can effectively improve coverage rate and reduce energy consumption.
TL;DR: This paper designs an iterative double-auction mechanism that ensures the efficient operation of the market by maximizing the differences between the MNOs' offloading benefits and APs' Offloading costs.
Abstract: The unprecedented growth of mobile data traffic challenges the performance and economic viability of today's cellular networks and calls for novel network architectures and communication solutions. Mobile data offloading through third-party Wi-Fi or femtocell access points (APs) can significantly alleviate the cellular congestion and enhance user quality of service (QoS), without requiring costly and time-consuming infrastructure investments. This solution has substantial benefits both for the mobile network operators (MNOs) and the mobile users, but comes with unique technical and economic challenges that must be jointly addressed. In this paper, we consider a market where MNOs lease APs that are already deployed by residential users for the offloading purpose. We assume that each MNO can employ multiple APs, and each AP can concurrently serve traffic from multiple MNOs. We design an iterative double-auction mechanism that ensures the efficient operation of the market by maximizing the differences between the MNOs' offloading benefits and APs' offloading costs. The proposed scheme takes into account the particular characteristics of the wireless network, such as the coupling of MNOs' offloading decisions and APs' capacity constraints. Additionally, it does not require full information about the MNOs and APs and creates non-negative revenue for the market broker.
TL;DR: This paper provides an overview of the theoretical problems the sensor network monitoring systems for smart cities face, and what possible approaches may be used to solve these problems.
Abstract: In last two decades, various monitoring systems have been designed and deployed in urban environments, toward the realization of the so called smart cities. Such systems are based on both dedicated sensor nodes, and ubiquitous but not dedicated devices such as smart phones and vehicles’ sensors. When we design sensor network monitoring systems for smart cities, we have two essential problems: node deployment and sensing management. These design problems are challenging, due to large urban areas to monitor, constrained locations for deployments, and heterogeneous type of sensing devices. There is a vast body of literature from different disciplines that have addressed these challenges. However, we do not have yet a comprehensive understanding and sound design guidelines. This paper addresses such a research gap and provides an overview of the theoretical problems we face, and what possible approaches we may use to solve these problems. Specifically, this paper focuses on the problems on both the deployment of the devices (which is the system design/configuration part) and the sensing management of the devices (which is the system running part). We also discuss how to choose the existing algorithms in different type of monitoring applications in smart cities, such as structural health monitoring, water pipeline networks, traffic monitoring. We finally discuss future research opportunities and open challenges for smart city monitoring.