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首页> 外文期刊>Information Sciences: An International Journal >On the use of particle swarm optimization for adaptive resource allocation in orthogonal frequency division multiple access systems with proportional rate constraints
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On the use of particle swarm optimization for adaptive resource allocation in orthogonal frequency division multiple access systems with proportional rate constraints

机译:具有比例速率约束的正交频分多址系统中粒子群算法在自适应资源分配中的应用

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摘要

Orthogonal frequency division multiple access (OFDMA) is a promising technique, which can provide high downlink capacity for future wireless systems. The total capacity of OFDMA can be maximized by adaptively assigning subchannels to the user with the best gain for that subchannel, with power subsequently distributed by water-filling algorithm. In this paper we have proposed the use of a customized particle swarm optimization (PSO) aided algorithm to allocate the subchannels. The PSO algorithm is population-based: a set of potential solutions evolves to approach a near-optimal solution for the problem under study. The customized algorithm works for discrete particle positions unlike the classical PSO algorithm which is valid for only continuous particle positions. It is shown that the proposed method obtains higher sum capacities as compared to that obtained by previous works, with comparable computational complexity.
机译:正交频分多址(OFDMA)是一种很有前途的技术,可以为未来的无线系统提供高下行链路容量。通过为用户分配具有最佳增益的子信道,该子信道具有最佳增益,可以最大程度地提高OFDMA的总容量,随后通过注水算法分配功率。在本文中,我们提出了使用定制的粒子群优化(PSO)辅助算法来分配子信道的方法。 PSO算法基于人口:针对研究中的问题,一组潜在的解决方案演变为接近最佳解决方案。与传统的PSO算法不同,定制算法适用于离散的粒子位置,而经典的PSO算法仅对连续的粒子位置有效。结果表明,与以前的工作相比,所提方法具有更高的求和能力,并且具有相当的计算复杂度。

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