A Feasible Study of Cube Sensing Organization Map for Cognitive Spectrum Allocation

Quang-Dung Pham, Trong-Hop Do, Nhu-Ngoc Dao, Woongsoo Na, Chunghyun Lee, Sungrae Cho
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Abstract

Spectrum availability has been considered as one of the most crucial factors for the success of serving dense user devices in fifth generation (5G) mobile communications and beyond. To this end, cognitive spectrum sensing technologies can be utilized to detect unused wireless channels in the coverage area of the user devices, which are possibly used for deviceto-device communications efficiently. However, frequent wide range sensing of spectrum extremely exhausts energy resource of the user devices. In this paper, we propose a probabilistic cognitive spectrum sensing (PCSS) mechanism to overcome this challenge. In the PCSS mechanism, a cube sensing organization map (CSOM) is dimensionalized on the basis of channels and locations in the coverage area. Weight of each block in the CSOM represents the probability that a user device successfully senses the corresponding channel idle in the corresponding location. The weight of each block is learned after every sensing periods to reinforce the CSOM. Consequently, user devices sense the list of channels in their proximity with the probabilities indicated by the weight of the best matching CSOM blocks. Simulation results show that the PCSS mechanism overcomes the existing techniques in terms of energy efficiency and positive sensing ratio.
认知频谱分配中立方体感知组织图的可行性研究
频谱可用性被认为是在第五代(5G)及以后的移动通信中成功服务密集用户设备的最关键因素之一。为此,可以利用认知频谱感知技术检测用户设备覆盖区域内未使用的无线信道,这些信道可能有效地用于设备对设备通信。然而,频繁的宽范围频谱传感极大地消耗了用户设备的能量资源。在本文中,我们提出一种概率认知频谱感知(PCSS)机制来克服这一挑战。在PCSS机制中,基于覆盖区域内的信道和位置对立方体感知组织图(CSOM)进行了量纲化。CSOM中每个块的权重表示用户设备在相应位置成功感知到相应通道空闲的概率。在每个感知周期后学习每个块的权重,以加强CSOM。因此,用户设备用最佳匹配CSOM块的权重所指示的概率来感知其附近的信道列表。仿真结果表明,PCSS机制在能量效率和正感知比方面优于现有技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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