Visible Light Communication (VLC) technology uses light-emitting diodes (LEDs) as a signal transmitting source to simultaneously realize lighting and data communication, and the spectrum resources are abundant. Since the visible light communication system with a photodiode (PD) as the receiver has some weaknesses, such as narrow field of view (FOV), inaccurate alignment in moving state, and inadaptability for indoor communication environments, an optical camera communication (OCC) system based on target detection algorithm is proposed in this paper. The system applies a LED array mounted on a moving AGV (automated guided vehicle) as the signal transmitter and a CCD camera as the receiver to realize data transmission in an outdoor environment. In this paper, a VLC MIMO channel model is constructed to verify that simultaneous communication of multiple LEDs through MIMO channels can effectively reduce bit error rate. The designed OCC system utilizes an image processing algorithm based on target detection to detect and identify light signals, realizing relatively stable and reliable communication in the state of motion. The distance from the signal transmitter to the receiver ranges from 6m to 14m.

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Abstract. With quick developments of new application patterns and network technologies, network anomalies have an important impact on network operations. How to accurately detect network anomalies has become the hot topic in current communication networks. This paper proposes a new detection approach to diagnose the anomaly in network traffic. Firstly, we use the Bayes learning theory to describe network traffic properties. By the learning process, normal network traffic can correctly be modeled. Secondly, the feature extraction is used to differentiate abnormal network traffic from normal huge traffic. Thirdly, the detail detection algorithm is presented to find the anomalous component in network traffic. Finally, we carry out the detailed simulation experiments. Simulation results indicate that our approach is effective.

Abstract. Dynamic spectrum access can effectively improve network frequency resource utilization in current wireless networks. However, for energy-efficient cognitive wireless access networks, traditional dynamic spectrum access technologies face new challenges. This paper proposes a new dynamic spectrum access approach to improve both frequency resource utilization and network energy efficiency. We model this problem as an optimal model. In such a case, network frequency resource sharing and energy efficiency are combined into the optimal process to solve our model. Based on theory analysis, we propose our dynamic spectrum access algorithm to build highly energy-efficient cognitive wireless networks. Finally, we conduct a large amount of tests to validate our approach. Simulation results show that the proposed approach is effective and feasible.

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