协同底层认知系统的最优功率控制

Marwa Chami, M. Pischella, D. L. Ruyet
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引用次数: 2

摘要

本文提出了一种新的底层协作式认知无线电系统,该系统允许主、次系统之间的付费合作。为了最大限度地提高认知系统的识别率,我们考虑了从接收端解码策略和功率效率优化问题。次要用户必须在主传输存在的情况下与接收器通信,并受两个约束:总功率预算和对主用户的干扰限制。本文研究了当二次系统采用叠加编码策略时,用梯度下降法优化分配最大允许功率的效用。解码策略是一种启发式方法,考虑到交织和潜在的认知无线电约束,以最大限度地提高主用户和辅助用户的和速率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal power control for cooperative underlay cognitive system
This paper proposes a new underlay cooperative cognitive radio system, where a paid cooperation between the primary and the secondary systems is allowed. We consider both decoding strategy at the secondary receiver and the power efficiency optimization problem, in order to maximize the rate of the cognitive system. The secondary user has to communicate to the receiver in the presence of primary transmission, under two constraints: the total budget of power and the interference limit at the primary user. In this paper, we investigate the utility to optimally distribute the maximum allowed power with Gradient Descent method, when the Superposition Coding strategy is applied at the secondary system. The decoding strategy is a heuristic method that aims to maximize the sum rate of both the primary and the secondary users, taking into account the interweave and underlay cognitive radio constraints.
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