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Device-to-Device (D2D) communication is considered to be a promising form of technology to distribute video contents to nearby users and devices at a high data rate and with few delays. In this paper, we propose utilizing the D2D services and cache of mobile devices as a bootstrapping system in a cellular network. The main objective of a bootstrapping-D2D (BD2D) system is to improve the quality of service in terms of achieving the minimum startup-time of popular video files in a cellular network. To achieve our objective, we propose a new caching concept for D2D communication in which each mobile device can cache and share the initial video portion or initial segments of the popular video files to other proximate users via a D2D communication link. We formulate an optimization problem that maximizes the cache-hit ratio of initial segments of the most popular video contents. The basic aim is to move the initial segments as close as possible to the wireless users. We also propose a network-assisted D2D architecture called mobile content delivery network-assisted-BD2D and algorithms that assist the BD2D system in the discovery of devices that have cached the initial segments of the requested video files, in cache placement decisions, and also in the registration of potential D2D devices at the core network. We evaluate the performance of the BD2D system and propose algorithms through extensive simulations under real wireless network conditions, such as interference, fading, and shadowing. Our concluding simulation results demonstrate that bootstrapping the initial segments using the short range BD2D system can significantly reduce the average startup-time of video files in comparison with bootstrapping the initial segments from the traditional cellular system.

The walking state monitoring is indispensable during the robot-aided walking of people with lower limb dysfunctions. In this paper, the existence of human-robot coordination state is first statistically verified in the process of using a walking-aid cane-type robot during walking. Based on this coordination, a new walking state monitoring method is proposed by using the principal component analysis (PCA). The abnormal or emergency walking state is promptly detected if the new sample data are found to deviate from an off-line PCA model, which is generated from plentiful normal walking data of different subjects. Furthermore, a state diagnosis algorithm based on the contribution plot is also developed for the walking state recognition and diagnosis. In this way, typical abnormal states like the leg restrictions can be distinguished from the emergency states including falls and the stumbling. Moreover, the human-robot coordination analysis can be performed using less sensors built-in the robot without needing the posture information of full human body. The effectiveness of the proposed method is proven by experiments. Better recognition rate and real-time performance of the method are also verified by comparing with conventional center of pressure based monitoring method.

In this paper, we study the power control and resource allocation problem in downlink orthogonal frequency division multiplexing networks, where mutual interference exists among cells. This mutual relation is characterized by the load coupling model. Both cell load and transmit power, where cell load measures the average proportion of resource usage in the cell, interact via the coupling model. We consider three kinds of problems, sum power minimization, sum rate maximization, and sum energy efficiency maximization. For each problem, we develop a correspondingly distributed power control and resource allocation algorithm with low complexity. Numerical results verify the effectiveness of our proposed algorithms compared with the existing algorithm.