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Physical Layer and MAC Design for Self-Reliant Cognitive Multicast Networks Using LTE Resources
IEEE Transactions on Cognitive Communications and Networking ( IF 7.4 ) Pub Date : 2020-12-18 , DOI: 10.1109/tccn.2020.3045738
Brian W. Stevens , Mohamed F. Younis

Existing Long Term Evolution (LTE) networks have untapped radio frequency resources, also known as white space, that can be repurposed for cognitive radio applications. A secondary network can opportunistically interweave communication within the white space of an existing LTE signal by leveraging cognitive radio. In this article, we present CIAO-LTE, a novel framework for forming a cognitive interwoven self-reliant secondary network with no additional physical infrastructure, collaboration from the existing primary network, and software or hardware changes in the primary LTE network. For medium access control, CIAO-LTE uses an adapted version of Slotted ALOHA with a no-back-off contention. We analyze parameter settings and conduct extensive simulations to validate performance. The simulation results show that CIAO-LTE achieves throughputs as high as 4.75 Mb/s on a 5MHz LTE signal and approximately 19Mb/s with a 20MHz LTE signal, and average packet delays within a few milliseconds.

中文翻译:

使用 LTE 资源的自依赖认知组播网络的物理层和 MAC 设计

现有的长期演进 (LTE) 网络具有未开发的射频资源,也称为空白空间,可以重新用于认知无线电应用。辅助网络可以利用认知无线电在现有 LTE 信号的空白空间内随机交织通信。在本文中,我们介绍了 CIAO-LTE,这是一种新颖的框架,用于在没有额外物理基础设施、现有主网络的协作以及主 LTE 网络中的软件或硬件更改的情况下,形成认知交织的自依赖辅助网络。对于媒体访问控制,CIAO-LTE 使用具有无退避争用的时隙 ALOHA 的改编版本。我们分析参数设置并进行广泛的模拟以验证性能。
更新日期:2020-12-18
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