Underlay multi-hop cognitive networks with orthogonal access

A. Marques, Sergio Molinero, G. Giannakis
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引用次数: 0

Abstract

Stochastic algorithms to allocate resources across different layers in an underlay multi-hop cognitive radio with primary and secondary users are presented. The algorithms aim to maximize the utility of the secondary users, while adhering to average interfering power constraints and accounting for the presence of imperfections in the state information. Interference among secondary users is modeled using a binary conflict graph, so that close-by secondary devices cannot transmit simultaneously. The optimal resource allocation dictates the power transmitted by each user, the rates at the transport, network and physical level, and the links to be activated. The design is casted as a nonlinear constrained optimization, and the solution is obtained using stochastic dual decomposition. Nu- merical experiments validate the theoretical claims.
基于正交接入的底层多跳认知网络
提出了一种具有主、从用户的底层多跳认知无线电系统中资源跨层分配的随机算法。该算法以二次用户的效用最大化为目标,同时遵守平均干扰功率约束,并考虑到状态信息中存在的缺陷。次要用户间的干扰采用二值冲突图建模,使邻近的次要设备不能同时传输。最佳资源分配决定了每个用户传输的功率,传输、网络和物理层的速率,以及要激活的链路。将设计转化为非线性约束优化,并采用随机对偶分解方法求解。数值实验验证了理论结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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