Scalable spectrum database construction mechanisms for efficient wideband spectrum access management
Scalable spectrum database construction mechanisms for efficient wideband spectrum access management
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DOI：
10.1016/j.phycom.2021.101318
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发表时间：
2021-03
期刊：
影响因子：
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通讯作者：
Bassem Khalfi;B. Hamdaoui;M. Guizani;Abdurrahman Elmaghbub
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作者：
Bassem Khalfi;B. Hamdaoui;M. Guizani;Abdurrahman Elmaghbub
我们提出了一个新的框架，使可扩展的数据库驱动的动态频谱访问和共享异构宽带频谱。所提出的框架包括两个互补的方法，利用压缩感知理论，低秩矩阵理论和用户合作的优点，建立一个准确的异构宽带频谱图，克服占用频带的数量的时变性，需要大量的测量每个传感节点（SN），固有的无线信道的损伤，和高的报告网络开销。首先，利用附近的SN具有高度相关的频谱观测的事实，我们利用分布式压缩感知，使合作异构宽带频谱感测仅从每个SN的少量测量。其次，为了减少由于感兴趣频谱的高宽度而导致的网络开销，我们提出了一种两步方法，该方法使用占用子矩阵的局部低秩属性来执行频谱占用恢复。然后，我们联合收割机将完成的子矩阵项组合以产生整个频谱占用矩阵。通过仿真，我们表明，所提出的框架有效地实现了高检测在感测步骤，并最大限度地减少频谱占用矩阵恢复误差，同时降低了整体网络开销。
We propose a novel framework for enabling scalable database-driven dynamic spectrum access and sharing of heterogeneous wideband spectrum. The proposed framework consists of two complementary approaches that exploit the merits of compressive sensing theory, low-rank matrix theory, and user cooperation to build an accurate heterogeneous wideband spectrum map by overcoming the time-variability of the number of occupied bands, the need for a high number of measurements per sensing node (SN), the inherent wireless channels’ impairments, and the high reporting network overhead. First, exploiting the fact that close-by SNs have a highly correlated spectrum observation, we leverage distributed compressive sensing to enable cooperative heterogeneous wideband spectrum sensing only from a small number of measurements per each SN. Second, to reduce the network overhead due to the high width of the spectrum of interest, we propose a two-step approach that performs spectrum occupancy recovery using the local low-rank property of occupancy sub-matrices. Then, we combine the completed sub-matrices entries to produce the whole spectrum occupancy matrix. Through simulations, we show that the proposed framework efficiently achieves high detection in the sensing step and minimizes the spectrum occupancy matrix recovery error while reducing the overall network overhead.