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Sparse-matrix-based compressed sensing for spectrum sensing in Flexible Wireless System

机译:基于稀疏矩阵的压缩感知,用于柔性无线系统中的频谱感知

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The Flexible Wireless System (FWS) has been proposed as a networked system for a User-Centric Wireless Networks (UCWN). UCWNs allow users to make network connections easily at all times without being conscious of any upgrades or differences in wireless systems. The FWS is a unified wireless platform that simultaneously deals with various types of wireless signals. It consists of flexible access points and a wireless signal processing platform. Various types of wireless signals are received at a distributed flexible access point and transferred to a server in the wireless signal processing platform through the wired access line. Transferred signals are separated and demodulated at the server. To achieve highly flexible and efficient radio wave data transfer between the access point and the server, this paper proposes a sparse-matrix-based compressed sensing method under the framework of the belief propagation and cavity method. Low cost implementation using interlevers and adders is also proposed. An empirical study with real data shows the proposed method achieves greater efficiency and reduced calculation cost compared to the conventional compressed sensing method.
机译:柔性无线系统(FWS)已经被提出作为以用户为中心的无线网络(UCWN)的联网系统。 UCWN允许用户始终轻松地建立网络连接,而无需注意无线系统的任何升级或差异。 FWS是一个统一的无线平台,可同时处理各种类型的无线信号。它由灵活的接入点和无线信号处理平台组成。在分布式灵活访问点处接收各种类型的无线信号,并通过有线访问线路将其传输到无线信号处理平台中的服务器。传输的信号在服务器上被分离和解调。为了在接入点和服务器之间实现高度灵活,高效的无线电波数据传输,在信度传播和腔法的框架下,提出了一种基于稀疏矩阵的压缩感知方法。还提出了使用交织器和加法器的低成本实现。实际数据的经验研究表明,与传统的压缩传感方法相比,该方法具有更高的效率和更低的计算成本。

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