Distributed resource allocation in cognitive radio systems based on social foraging swarms

P. Di Lorenzo, S. Barbarossa
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引用次数: 13

Abstract

The goal of this paper is to propose a distributed resource allocation strategy for the access of opportunistic users in cognitive networks. The opportunistic, or secondary, users are modeled as a set of agents looking for the most appropriate slots to use, in the time-frequency domain, with the goal of avoiding conflicts among themselves and to yield possibly no interference to the primary users. The problem is how to coordinate the access from the secondary users in a totally decentralized fashion, requiring a minimal coordination among them. We propose a solution to this problem based on a social forage swarming model, where the search for the most appropriate slots is modeled as the motion of a swarm of agents in the resource domain (typically the time-frequency plane), looking for “forage”, representing a function inversely proportional to the interference level. The swarm tends to move in the time-frequency region where there is less interference, while satisfying one basic requirement: minimize the spread in the resource domain while avoiding collisions between the allocations of different users. These properties are enforced through the decentralized minimization of a potential function that incorporates a long-range attraction between the resources occupied by secondary users (to minimize spreading) and a short-range repulsion (to avoid conflicts)1.
基于社会觅食群的认知无线电系统分布式资源分配
本文的目标是为认知网络中机会主义用户的访问提出一种分布式资源分配策略。机会用户或次要用户被建模为一组代理,这些代理在时频域中寻找最合适的使用槽,其目标是避免它们之间的冲突,并尽可能不干扰主要用户。问题是如何以一种完全分散的方式协调次要用户的访问,使它们之间的协调最小化。我们提出了一种基于社会觅食群模型的解决方案,其中搜索最合适的槽被建模为一群智能体在资源域(通常是时频平面)中的运动,寻找“觅食”,表示与干扰水平成反比的函数。群体倾向于在干扰较少的时频区域移动,同时满足一个基本要求:最小化资源域中的传播,同时避免不同用户分配之间的冲突。这些特性是通过潜在函数的分散最小化来实现的,该函数结合了二级用户占用的资源之间的远程吸引力(以最小化传播)和短程排斥(以避免冲突)1。
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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