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Distributed Spectrum Cartography for Cognitive Radio Network with Convex Optimization

机译：具有凸优化的认知无线电网络的分布式频谱制图

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摘要

Cognitive radio is a new technology used to solve the problem of spectrum resource shortage, which includes spectrum sensing and spectrum allocation. Spectrum sensing is the perception of wireless environment, which can be regarded as the field estimation problem of a certain spatial region. The visualization of the field estimation problem is spectrum cartography or spectrum mapping. Spectrum cartography based on convex optimization has been studied, but distributed projection subgradient solution has not been applied yet. In this paper, a cognitive radio spectrum cartography technology based on distributed projection subgradient is established, which focuses on the sensing of spectrum information of the transmitting source. Considering the unknown quantities in space and frequency domain of this question, this paper uses two assumptions of virtual grid and basis expansion model to transform the problem into a convex optimization equation with sparsity, and then solve the problem by the distributed projection subgradient algorithm.
机译：认知无线电是一种用于解决频谱资源短缺问题的新技术，包括频谱感测和频谱分配。光谱感测是无线环境的感知，其可以被视为特定空间区域的场估计问题。场估计问题的可视化是频谱制图或频谱映射。已经研究了基于凸优化的频谱制图，但尚未应用分布式投影分布式解决方案。本文建立了一种基于分布式投影研究的认知无线电谱制图技术，专注于发送源的光谱信息的感测。考虑到这个问题的空间和频域中未知数量，本文使用了虚拟网格和基础扩展模型的两个假设，将问题转换为具有稀疏性的凸优化方程，然后通过分布式投影子缩放算法解决问题。

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