My research style is interdisciplinary in general. Particularly, I am leveraging machine learning and data analytics related techniques to tackle the healthcare, sensing, security, system, network related problems. My work has a strong and balanced emphasis on algorithm development, system implementation and validation with real-world scenarios.
Some recent on-going projects:
Some Past Projects:
My research interests lie in the broad areas of general distributed systems and wireless Internet technologies, including next-generation wireless networks and systems, cognitive and cooperative wireless networking, sensor networking, large-scale peer-to-peer systems, and multimedia communications. I joined HKUST in Sept. 2005, before that I had worked in Microsoft Research Asia for about 6 years. During the past 10 years, I had the opportunity to collaborate with many brilliant postgraduate students, visiting students, and excellent researchers, which is definitely the most valuable experience for me. The following is a brief description of my research activities.
Cognitive and Cooperative Wireless Networking
With the rapid growth in wireless services, the demand for more spectrum resources is steadily increasing. The electromagnetic spectrum is a limited resource that has been regulated with static allocation policies and resulting in poor utilization. There is a need for new market-based policies to allow and encourage secondary users to dynamically access and opportunistically reuse the under-utilized spectrum owned by the primary licensed users. To realize the paradigm of dynamic spectrum management, cognitive radio network is a promising way. Align this direction, we have focused on dynamic spectrum management and cognitive radio networking, under a unified framework including both economic and technological aspects.
Economical feasibility of dynamic spectrum management
For wireless service providers, the emergence of dynamic spectrum access brings new opportunities and challenges. The flexible spectrum acquisition gives a particular provider the chance to easily adapt its system capacity to fit end users' demand. However, the competition among several providers for both spectrum and end users complicates the situation. We have proposed a general three-layer spectrum market model for the future dynamic spectrum access system, in which the interaction among spectrum holder, wireless service providers and end users are considered. We studied a duopoly situation, where two wireless service providers participate in bandwidth competition in spectrum purchasing and price competition to attract end users, with the aim of maximizing their own profit.
To improve spectrum utilization, it is important to incentivize the primary license holders to open up their under-utilized spectrum for sharing. We proposed a secondary spectrum market where a primary license holder can sell access to its unused or under-used spectrum resources in the form of certain fine-grained spectrum-space-time unit. Secondary wireless service providers can purchase such contracts to deploy new service, enhance their existing service, or deploy ad hoc service to meet flash crowds demand. Within the context of this market, we investigate how to use auction mechanisms to allocate and price spectrum resources so that the primary license holder's revenue is maximized.
Core technologies for efficient dynamic spectrum access
The heterogeneity of both spectrum availability and traffic demand in secondary users has brought significant challenge for efficient spectrum allocation in cognitive radio networks. Observing that spectrum resource can be better matched to traffic demand of secondary users with the help of relay node that has rich spectrum resource, we exploited a new research direction for cognitive radio networks by utilizing cooperative relay to assist the transmission and improve spectrum efficiency.
Under dynamic spectrum access, unlicensed wireless users (secondary users) can dynamically access the licensed bands from legacy spectrum holders (primary users) on an opportunistic basis. While most primary users in existing works assume secondary transmissions as negative interference and don’t actively involve them into the primary transmission, in this work, motivated by the idea of cooperative communication, we propose a cooperative cognitive radio framework, where primary users, aware of the existence of secondary users, may select some of them to be the cooperative relay, and in return lease portion of the channel access time to them for their own data transmission. Secondary users cooperating with primary transmissions have the right to decide their payment made for primary user in order to achieve a proportional access time to the wireless media. Both primary and secondary users target at maximizing their utilities in terms of their transmission rate and revenue/payment.
Cognitive radio has many advanced features, such as agilely sensing the existence of primary users and utilizing multiple spectrum bands simultaneously. However, in practice such capabilities are constrained by hardware cost. We discussed how to conduct efficient spectrum management in ad hoc cognitive radio networks while taking the hardware constraints (e.g., single radio, partial spectrum sensing and spectrum aggregation limit) into consideration. A hardware-constrained cognitive MAC, HCMAC, is proposed to conduct efficient spectrum sensing and spectrum access decision. We identified the issue of optimal spectrum sensing decision for a single secondary transmission pair, and formulate it as an optimal stopping problem. A decentralized MAC protocol was then proposed for the ad hoc cognitive radio networks.
Mining Spectrum Usage Data: a Large-scale Spectrum Measurement Study
The increasing volume of literature for dynamic spectrum access calls for a deeper understanding of the characteristics of current spectrum utilization. We present a detailed spectrum measurement study, with data collected in the 20MHz to 3GHz spectrum band and at four locations concurrently in Guangdong province of China. We examine the first and second order statistics of the collected data, including channel occupancy/vacancy statistics, channel utilization within each individual wireless service, and the temporal, spectral, and spatial correlation of these measures. Main findings include that the channel vacancy durations follow an exponential-like distribution, but are not independently distributed over time, and that significant spectral and spatial correlations are found between channels of the same service. We then exploit such spectrum correlation to develop a 2-dimensional frequent pattern mining algorithm that can accurately predict channel availability based on past observations.
Mobile assisted wireless sensor networks
Double Mobility: Coverage of the Sea Surface with Mobile Sensor Networks
We are interested in the sensor networks for scientific applications to cover and measure statistics on the sea surface. In our application, we face a unique double mobility coverage problem. That is, there is an uncontrollable mobility, U-Mobility, by the flows which breaks the coverage of the sensor network. Moreover, there is also a controllable mobility, C-Mobility, by the mobile nodes which we can utilize to reinstall the coverage. Our objective is to build an energy efficient scheme for the sensor network coverage issue with this double mobility behavior.
Delay Tolerant Event Collection for Underground Coal Mine using Mobile Sinks
There is a growing interest in using wireless sensor networks for security monitoring in the underground coal mines. In such applications, the sensor nodes are deployed to detect interested events, e.g., the density of certain gas at some locations is higher than the predefined threshold. These events are then reported to the base station outside. Using conventional multi-hop routing for data reporting, however, will result in imbalance of energy consumption among the sensors. Even worse, the unfriendly communication condition underground makes the multi-hop data transmission challenging, if not impossible. In this work, we thus propose to leverage tramcars as mobile sinks to assist event collection and delivery. We further observe that the sensor readings have spatial and temporal correlation. More precisely, the same event may be observed by multiple neighboring sensor nodes and/or at different time. Obviously, it can be more energy-efficient if the data are selectively reported.
Relative Distance Based Localization for Mobile Sensor Networks
Leveraging node mobility, in this work, both static constrain set by transmission range and velocity constrain set by node movement are introduced. Based on these two types of constrain, we propose a range-free Mobile Inequality Localization (MIL) algorithm, which uses ring inequalities to restrict and estimate the possible location in numerical method.
Probabilistic Coverage Map for Mobile Sensor Networks
We consider the coverage problem in mobile sensor networks under a very general framework, in which all the sensors are moving all the time with any specified movement model. We propose a scheme that can provide a Real-time Coverage-Map According to Probability (RC-MAP) of the mobile sensor networks.
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