使用路径时间编码的弹性大规模认知无线电自组织网络

Yi-Chi Chen, I-Wei Lai, Kwang-Cheng Chen
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引用次数: 0

摘要

认知无线电自组织网络(CRAHNs)作为一种频谱高效的网络技术出现,可以实现大量物联网设备之间的自主机器对机器通信。然而,频谱共享导致机会链路,CRAHN成为一种机会网络。为了降低CRAHN中的时延,避免大量的反馈信令,达到整体的频谱效率,开环物理层传输的CRAHN在大规模运行下开辟了一条新的途径。与这种新型crahn相关的新技术挑战在于仅使用本地网络信息进行错误控制,而不依赖于对每个机会链路的反馈控制。在网络层上虚拟实现多输入多输出的路径时码解决了这一难题。然而,考虑干扰的有效多径路由仍然不清楚。本文在考虑网络拓扑因素和干扰的情况下,解析导出信噪比近似,设计功率控制和多径贪婪路由。通过随机几何分析,我们还证明了路径时间编码可以促进大规模crahn的弹性操作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Resilient large-scale cognitive radio ad hoc networking using path-time codes
Cognitive radio ad hoc networks (CRAHNs) emerge as a spectrum efficient networking technology to enable autonomous machine-to-machine communication among massive number of IoT devices. However, spectrum sharing results in opportunistic links and CRAHN becomes a kind of opportunistic networks. To reduce latency in CRAHN and to achieve overall spectrum efficiency by avoiding tremendous feedback signaling, CRAHNs of open-loop physical layer transmission open a new avenue under massive operations. The new technology challenge associated with such new CRAHNs lies in error control with only local networking information without relying on feedback control over each opportunistic link. Path-time codes virtually realizing multi-input-multi-output over network layer have been innovated to resolve such a dilemma. However, effective multipath routing considering interference remains unclear. In this paper, be taking network topological factors and interference into account, we analytically derive SINR approximations to design power control and multi-path greedy routing. By stochastic geometry analysis, we also show that the resilient operation for large-scale CRAHNs can be facilitated with the aid of path-time codes.
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