Yuhan Dong

Adaptive energy-harvesting aware clustering routing protocol for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are energy-constrained. However, recent advances in ambient energy harvesting technology have made it possible for sensor nodes to harvest energy from ambient environment and serve as a supplement or the only energy source. And most of current routing protocols are specially designed for battery-powered WSNs, may not be suitable for energy harvesting WSNs (EH-WSNs), especially for those entirely powered by harvesting energy. In this paper, we propose an Adaptive Energy Harvesting Aware Clustering (AEHAC) routing protocol for EH-WSNs, which takes node energy state into cluster head election algorithm and can adjust its parameter according to the network deploying environment. We analyze and evaluate the routing performance in terms of two metrics available node number and network throughput. Simulation results show that AEHAC maintains available nodes about 15% and networks throughput 19% more than traditional LEACH.

Recommend a profitable cruising route for taxi drivers

Every time after the taxi drivers drop off their previous passengers, they have to decide how to search for the next passengers. It may lead to poor performance if the taxi drivers cruise according to their own experience, especially for the freshmen. Therefore, it is valuable to recommend a profitable cruising route for the taxi drivers in order to increase their income and reduce waste in fuel. In this paper, we propose to use a system of linear equations to calculate the score of each road segment based on a large-scale real-world GPS data set. The score of each road segment consists of 1) the total income of the road segment and 2) the attractiveness of the drop-off location with respect to the next pick-up. Then, we get the profitable cruising route based on the score of each road segment using skyline computation. We build our system using historical data set generated by 12,000 taxis of Beijing in November 2012. Finally, we demonstrate that taxi driver who follows our recommendation can enhance their income compared to the ground truth.

A Wi-Fi/GPS integrated system for urban vehicle positioning

Providing an anytime, ubiquitous and reliable vehicular positioning system plays a key role in increasing road safety and transportation efficiency. Although the Global Positioning System (GPS) has been widely used in vehicle navigation, urban vehicle positioning is still a challenge because of the unavailability of GPS in dense metropolitan areas. To solve this problem, an advanced integration of Wi-Fi and GPS is presented in this paper. It uses Wi-Fi Received Signal Strength (RSS), GPS measurement and vehicle kinematics to estimate the vehicle position. To leverage the strength of Wi-Fi and GPS, a structure based on Kalman Filter (KF) and Particle Filter (PF) is proposed. Besides, outdoor experiments have been carried out in real environment to test performance of proposed system. Numerical results suggest that the proposed system can achieve higher accuracy and more reliability than existing GPS system.

The Impact of Mutual Coupling on MIMO Maximum-Ratio Combining

We consider the impact of transmitter correlation and mutual coupling on MIMO MRC systems. We present optimal transmission strategies for three input power metrics as well as formulas for the resulting outage probabilities. Numerical results suggest that, regardless of the power metric, most of the performance benefits of MIMO MRC can be obtained with transmit antennas spaced as close as 0.2 - 0.3 wavelengths.

Effects of mutual coupling and noise correlation on downlink coordinated beamforming with limited feedback

We consider the impact of receiver correlation, antenna coupling, matching, and noise on the performance of coordinated beamforming systems. We present a new coordinated beamforming technique for two receivers that is suitable for MIMO broadcast channels with signal and noise correlation at the receiver. We then apply this technique to the specific type of signal and noise correlation that occurs in the presence of receiver mutual coupling. Numerical results suggest that, even in the presence of strong coupling, most of the benefits of coordinated beamforming can be preserved by using appropriate matching networks and linear beamforming. Moreover, these benefits can be achieved even when feedback is limited.

Asynchronous track fusion in a multi-scale sensor environment

Track fusion is an important and attractive part in multisensor multitarget tracking for its robustness and flexibility compared with measurement fusion. Much research on track fusion has been done under the common assumption that the sensors in system are synchronous (with no communication delays) or have similar sensor accuracies. Unfortunately, in many multisensor systems, situations often fall short of the above assumption due to the mobility of targets and/or sensors, the communication restrictions, and the type and resource limitations of the individual sensors. The aim of this paper is to propose an asynchronous approach for track fusion in a multi-scale sensor environment, which we refer to as asynchronous hierarchical track fusion (AHTF). It is shown that the proposed AHTF approach provides a solution to combining tracks reported by multi-scale sensors, which are dissimilar in their data rates and resolving capacities. Simulations in a typical maritime surveillance scenario are presented to validate the performance of the proposed approach.

Adaptive route guidance based on real-time information in stochastic time-dependent transportation networks

Owing to time-varying and stochastic properties of transportation networks, modeling transportation networks as stochastic time-dependent (STD) graphs has became a trend. In this paper, by applying multi-lognormal distribution, we develop a mathematical framework that can incorporate the concept of real-time information into the discussion of adaptive route guidance in STD networks.We address some basic aspects about adaptive route guidance based on real-time information in STD networks, such as definition of real-time information, impact of real-time information and spatial-temporal Markov property and so on. Based on least mean-square estimation method, we propose two time-adaptive decision rules with consideration of real-time information. Simulation results on an artificial STD network are given and the effectiveness of our algorithms is verified. At last, some basic conclusions are also validated and the future work is discussed.

Mutual Coupling Effects in MIMO MRC Systems with Limited Feedback

We consider the impact of transmitter correlation, mutual coupling and matching networks on the design and performance of MIMO MRC systems with limited feedback. We present codebook design techniques for three measures of transmitted power and we investigate the impact of antenna matching on the performance of these codebooks. Numerical results suggest that, regardless of the power measure and matching networks, the benefits of MIMO MRC with limited feedback can be achieved with antennas spaced as close as 0.2 - 0.3 wavelengths apart.