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Research On Vertical Handoff Between Visible Light Communication And Radio Communication

Posted on:2016-08-07Degree:MasterType:Thesis
Country:ChinaCandidate:H T ZhengFull Text:PDF
GTID:2308330482979062Subject:Communication and Information System
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In the heterogeneous wireless network integrated with visible light communication(VLC) and radio communication, to ensure the continuous and effective communication of terminal, the vertical handoff between visible light communication and radio communication becomes the key point of research. Considering the characteristic of visible light communication, traditional vertical handoff methods are not suitable for the vertical handoff between visible light communication and radio communication. There mainly lie three problems in the existing researchs: 1) Lacking effective interference detection methods, without knowing the interference detection result, terminal can’t make the right handoff decision; 2) Lacking effective perception and comparison methods of network quality of service between VLC and radio communication networks in existing vertical handoff algorithms for mobile interference case; 3) Existing handoff decision algorithms for blocking interference case are too single and lack the ability to adapt to different environment. Aiming at these problems, this paper relies on the National 863 High Tech Program to research on the vertical handoff between visible light communication and radio communication.This paper firstly studies on the detection methods of different types of interference and further puts forward a kind of vertical handoff p re-decision scheme based on interference detection. Then according to the problems in existing algorithms for mobile interference case and blocking interference case, two vertical handoff algorithms respectively based on the equivalent SINR for mobile interference case and RBF fuzzy neural network for blocking interference case are proposed. The main research achievements are as follows:1. We propose a vertical handoff pre-decision scheme based on interference detection. The effects of different types of interference on the performance of VLC MIMO communication system are firstly studied. According to the results, we present interference detection methods suitable for VLC MIMO communication system. Further, a vertical handoff pre-decision scheme based on interference detection is proposed. Simulation results show that when the mean density of pedestrians increases to 0.1m2, the probability of fail detection of our interference detection method is only 4.7%.2. We propose a vertical handoff algorithm based on equivalent signal to interference plus noise ratio(SINR) for mobile interference case. Firstly, it converses VLC SIN R to equivalent radio communication SIN R under the condition that both reach the same maximum rate. Then, it calculates the difference between target and service network SIN R, handoff triggering is done according to comparison of the difference and set threshold. Finally, a timer is introduced to help to make handoff decision. Experimental results show that the algorithm can ensure users always get the maximum rate and have desired adaptability for different VLC network layout and optical noise strength changes.3. We propose a vertical handoff decision- making algorithm based on RBF fuzzy neural network. Firstly, the impact parameters of handoff decision- making for blockage case are studied; then, the acquisition method of different parameters are analyzed; finally, the three most important parameters are put into RBF fuzzy neural network for fuzzy reasoning and handoff decision is made according to the exact output value. Simulation results show that the algorithm can make reasonable handoff decisions, ensuring small transfer delay under different conditions, also reducing about 50% handoff times compared with immediate handoff in the case of frequent blockage.
Keywords/Search Tags:Visible light communication, Vertical handoff, Interference detection, Equivalent SINR conversion, Optimal handoff time, Handoff time interval, RBF fuzzy neural network, Information transmission delay
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