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arXiv 1007.1272cs.NIcs.ITmath.IT
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二进制是好的:认知无线电网络中主用户分离的二进制推理框架

Binary is Good: A Binary Inference Framework for Primary User Separation in Cognitive Radio Networks

Huy Nguyen, Rong Zheng, Zhu Han

摘要:

认知无线电网络中主用户分离问题是指识别和表征主用户的问题。我们认为,需要PU分离的背景下,协作频谱感知和监测选择。在本文中,我们模型的观察监视器作为布尔或混合物的潜在的二进制延迟源的PU,并设计了一种新的二进制推理算法PU分离。仿真结果表明,该算法在不需要PU活动先验知识的情况下,具有较高的推理精度。该算法的一个有趣的含义是能够有效地表示n个独立的二进制源通过(相关)二进制向量的对数长度。

英文摘要:

Primary users (PU) separation concerns with the issues of distinguishing and characterizing primary users in cognitive radio (CR) networks. We argue the need for PU separation in the context of collaborative spectrum sensing and monitor selection. In this paper, we model the observations of monitors as boolean OR mixtures of underlying binary latency sources for PUs, and devise a novel binary inference algorithm for PU separation. Simulation results show that without prior knowledge regarding PUs' activities, the algorithm achieves high inference accuracy. An interesting implication of the proposed algorithm is the ability to effectively represent n independent binary sources via (correlated) binary vectors of logarithmic length.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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