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首页> 外文期刊>IEEE Transactions on Cognitive Communications and Networking >Robotics Inspired Opportunistic Routing for Cognitive Radio Using Potential Fields
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Robotics Inspired Opportunistic Routing for Cognitive Radio Using Potential Fields

机译：机器人技术利用势场启发认知无线电的机会路由

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Potential field based routing is proposed for cognitive radio networks. This approach is inspired by the analogy between packet routing in cognitive radio networks and robot navigation in the presence of obstacles. Using this analogy a general framework for packet routing using potential fields is introduced, in which desired communication destinations can be considered as attractive forces and sources of interference as repulsive forces. Furthermore, three examples of how to construct such potential fields are proposed. Two optimal potential field models with respect to delay and energy and one suboptimal, but computationally simple, potential field based on virtual forces are derived. The potential field approach facilitates using physics-based models of propagation in interference modeling. This paper shows that potential field techniques from robotics can provide an attractive solution to routing in a cognitive radio network and that they can achieve good performance in terms of end-to-end delay and energy consumption.
机译：为认知无线电网络提出了基于势场的路由。这种方法的灵感来自认知无线电网络中的分组路由与存在障碍物的机器人导航之间的类比。使用这种类比，介绍了一种使用势场进行分组路由的通用框架，在该框架中，可以将所需的通信目标视为吸引力，而将干扰源视为排斥力。此外，提出了三个如何构造这样的潜在场的例子。推导了关于延迟和能量的两个最佳势场模型，以及一个基于虚拟力的次优但计算简单的势场。势场方法有助于在干扰建模中使用基于物理的传播模型。本文表明，机器人技术的潜在现场技术可以为认知无线电网络中的路由提供有吸引力的解决方案，并且在端到端延迟和能耗方面，它们可以实现良好的性能。

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