认知无线网络中基于蚁群算法的下行链路资源分配
首发时间:2015-11-13
摘要:基于OFDMA的认知无线网络下行链路的资源分配问题中,约束条件通常包括认知用户对于主用户的干扰限制、认知基站发射功率限制以及子载波上认知用户的速率离散取值等等限制,对应的资源分配问题是NP问题,不存在复杂性有效的最优算法,只能考虑次优算法。本文研究这类资源分配问题,并提出了复杂性有效的次优算法求解此问题。该次优算法分为两步进行:首先,采用蚁群算法分配子载波;然后,基于平均功率的思想控制各个子载波上的发射功率。仿真结果表明,该算法能够达到更好的系统性能。
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Downlink Resource Allocation Based on Ant Colony Algorithm in Cognitive Radio Networks
Abstract:In the resource allocation problem of OFDMA based downlink cognitive radio network, the constraints always involves interference power limitation to primary users, transmitting power limitation for cognitive radio base station and the discrete value of transmittiong rate. The corresponding problem belongs to the classification of NP problem, so that there is no complexity efficient optimal solution and suboptimal algorithm should be developed. In this paper, we proposed the suboptimal algorithm which is divided into 2 steps: first, allocate sub-carriers by ant colony algorithm; and then, control the transmitting power on each sub-carrier by average power algorithm. Simulation experiments illustrate that the proposed algorithm achieves better system performance.
Keywords: information and communication engineering resource allocation ant colony algorithm
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No.4660309110694914****
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