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协作认知无线网络中的功率优化及中继选择策略.

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Title: 协作认知无线网络中的功率优化及中继选择策略.
Alternate Title: Power optimization and relay selection strategy in cooperative cognitive radio networks.
Authors: 伍仁勇1 wurenyong@hnu.edu, 王文茹1, 李仁发1
Source: Application Research of Computers / Jisuanji Yingyong Yanjiu. May2016, Vol. 33 Issue 5, p1486-1508. 6p.
Abstract (English): How to fulfill efficient spectrum sharing among primary user (PU) and cognitive users (CUs), or in other words, how to select the suitable partners among many CUs to cooperate with PU was the key issue in cooperative cognitive radio networks (CCRN). This paper solved the problem by optimizing PU and CUs’ utility, the algorithm was called GTMRS as a result of adopting Nash equilibrium(NE). For any set of cognitive users, it formed a non-cooperative power game model among CUs, thus it CU’s optimized power allocation algorithm according to NE. On the basis of these, PU need to find a determined relay set to maximize its utility. In the process, it introduced a modified channel harmonic mean factor, whose definition was that some relay nodes with little SNR were removed in order to maximize the system SNR. Results show that more CUs are allowed to access legacy spectrum and primary user obtained larger utility and transmit rate. Therefore, GTMRS can effectively select the appropriate CUs as relays and obtain the optimization of PU and CUs’ utilities. [ABSTRACT FROM AUTHOR]
Abstract (Chinese): 如何在协作认知网络中有效地实现主要用户和认知用户的频谱共享，即如何在众多认知用户中选择合适的认知中继集是一个基本问题。通过确定并优化主要用户和认知用户效用函数来解决该问题，因采用了纳什均衡理论，故称之为基于博弈论的多中继选择算法（multiple relay selection based on game theory，GTMRS）。在任一认知中继集合中，认知用户之间能够形成非合作功率的博弈模型，可基于纳什均衡得到认知用户的优化协作功率分配算法。在寻找一组确定的中继集合来实现主要用户效用的最大化过程中，引入了修改的信道调和平均数因子，其目的是移除信噪比较小的中继节点，以最大化系统的信噪比。仿真结果显示，该算法能够使更多的认知用户接入到授权频谱中，同时使得主要用户获得更大的效用以及传输速率。因此，基于博弈的多中继选择算法能够有效选择合适的认知中继，并获得主要用户和认知用户在效用上的最优化。 [ABSTRACT FROM AUTHOR]
Database: Academic Search Index
Description
Abstract:How to fulfill efficient spectrum sharing among primary user (PU) and cognitive users (CUs), or in other words, how to select the suitable partners among many CUs to cooperate with PU was the key issue in cooperative cognitive radio networks (CCRN). This paper solved the problem by optimizing PU and CUs’ utility, the algorithm was called GTMRS as a result of adopting Nash equilibrium(NE). For any set of cognitive users, it formed a non-cooperative power game model among CUs, thus it CU’s optimized power allocation algorithm according to NE. On the basis of these, PU need to find a determined relay set to maximize its utility. In the process, it introduced a modified channel harmonic mean factor, whose definition was that some relay nodes with little SNR were removed in order to maximize the system SNR. Results show that more CUs are allowed to access legacy spectrum and primary user obtained larger utility and transmit rate. Therefore, GTMRS can effectively select the appropriate CUs as relays and obtain the optimization of PU and CUs’ utilities. [ABSTRACT FROM AUTHOR]
ISSN:10013695
DOI:10.3969/j.issn.1001-3695.2016.05.047