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A Bio-Inspired Swarming Algorithm for Decentralized Access in Cognitive Radio

机译:认知无线电中分散访问的生物启发算法

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The goal of this paper is to propose a bio-inspired radio access mechanism for cognitive networks mimicking the behavior of a flock of birds swarming in search for food in a cohesive fashion without colliding with each other. The equivalence between swarming and radio resource allocation is established by modeling the interference distribution in the resource domain, e.g., frequency and time, as the spatial distribution of food, while the position of the single bird represents the radio resource chosen by each radio node. The swarming mechanism is enforced by letting every node allocate its resources (power/bits) in the time-frequency regions where the interference is minimum (the food density is maximum), avoiding collisions with other nodes (birds), yet limiting the spread in the time-frequency domain (i.e., maintaining the swarm cohesion). The solution is given as the distributed minimization of a functional, borrowed from social foraging swarming models, containing the average interference plus repulsion and attraction terms that help to avoid conflicts and maintain cohesiveness, respectively.
机译:本文的目的是为认知网络提出一种受生物启发的无线电访问机制,该机制模仿一群蜂群的行为,以一种凝聚的方式寻找食物而不会相互碰撞。通过将资源域中的干扰分布(例如频率和时间)建模为食物的空间分布,来建立群集和无线电资源分配之间的等价关系,而单只鸟的位置代表每个无线电节点选择的无线电资源。通过让每个节点在干扰最小(食物密度最大)的时频区域中分配其资源(功率/比特),从而避免与其他节点(鸟)发生冲突,但又限制了传播,从而实现了群集机制。时频域(即保持群体凝聚力)。解决方案是从社会觅食群体模型借用的功能的分布式最小化,其中包含平均干扰以及排斥和吸引项,分别有助于避免冲突和保持凝聚力。

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