认知数字家庭中联合信道和RAT分配的分布式算法

Tianming Li, N. Mandayam, A. Reznik
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引用次数: 3

摘要

无线电设计和无线网络的进步,以及多媒体家庭娱乐技术的发展,正在创造一个需要各种设备和网络的网络频谱共存的认知数字家庭的概念。最近在[1]中的工作考虑了认知数字家庭(CDH)中的资源分配框架,该框架具有多种无线电接入技术(RAT),如认知无线电和支持异构应用的传统无线电设备。一个名为home genie node (HG)的频谱管理器用于协调不同业务之间的频谱共存,其自由度范围从频率、带宽和功率等传输参数到无线电接入技术本身的选择。本文利用部分拉格朗日分解技术,设计并研究了CDH中资源分配问题的分布式算法,即总和率最大化和服务容量最大化,这些问题在文献[1]中采用集中式方法解决。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed algorithms for joint channel and RAT allocation in a cognitive digital home
The advances in radio design and wireless networking, along with the growth of multimedia home entertainment technologies, is creating the concept of a cognitive digital home requiring spectrum coexistence of various devices and networks of networks. Recent work in [1] has considered a framework for resource allocation in a cognitive digital home (CDH) with a multiplicity of radio access technologies (RAT) such as cognitive radios and legacy radio devices supporting heterogeneous applications. A spectrum manager, named the home genie node (HG), is used to coordinate spectrum coexistence across different services, with degrees of freedom ranging from transmission parameters such as frequency, bandwidth, and power, to the choice of radio access technology itself. Distributed algorithms for the resource allocation problems in a CDH, namely maximizing sum rate and maximizing service capacity, which have been previously solved using centralized approaches in [1], are designed and studied using partial Lagrangian decomposition techniques in this paper.
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