Distributed joint power and rate adaptation in ad hoc networks

F. Awuor, Karim D Djouani, G. Noel
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Abstract

Ad hoc networks are dynamic and scalable entities that autonomously adapt to nodes entering the network (i.e. increasing interference) or exiting the network (i.e. due to energy depletion), poor connectivity among others. In such networks, nodes exhibit individualistic behaviours where nodes selfishly compete for the limited network resources (i.e. energy and bandwidth) to maximize their own utilities. This consequently degrades network performance leading to low data rates, poor power efficiency, loss of connectivity etcetera. This paper considers a network utility maximization (NUM) strategy based on coupled interference minimization to adapt the transmission power and data rates in ad hoc networks. The proposed distributive joint power and rate adaptation (JRPA) algorithm employs costing (and reward) mechanisms to promote users' cooperation such that both users' local and network global optimum is always attained. This is similar to a super-modular game hence the optimality and convergence of JRPA is analysed using super-modular game theory. Simulation results show that the proposed algorithm improves network performance since users' are compels to transmit at optimal data rates and power levels just enough to sustain the transmission.
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自组网中的分布式联合功率和速率自适应
自组织网络是动态和可扩展的实体,可以自主适应节点进入网络(即增加干扰)或退出网络(即由于能量耗尽),连通性差等。在这样的网络中,节点表现出个人主义行为,节点自私地竞争有限的网络资源(即能量和带宽),以最大化自己的效用。这最终会降低网络性能,导致低数据速率,低电源效率,失去连接等。本文提出了一种基于耦合干扰最小化的网络效用最大化策略,以适应自组织网络中的传输功率和数据速率。提出的分布式联合功率和速率自适应(JRPA)算法采用成本(和奖励)机制来促进用户的合作,从而始终达到用户的局部和网络的全局最优。这类似于一个超模博弈,因此使用超模博弈理论分析了JRPA的最优性和收敛性。仿真结果表明,该算法提高了网络性能,因为用户被迫以最佳的数据速率和功率水平传输,以维持传输。
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