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首页> 外文期刊>Communications, IET >Fast and efficient parallel-shift water-filling algorithm for power allocation in orthogonal frequency division multiplexing-based underlay cognitive radios
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Fast and efficient parallel-shift water-filling algorithm for power allocation in orthogonal frequency division multiplexing-based underlay cognitive radios

机译:基于正交频分复用的底层认知无线电中功率分配的快速高效并行移位注水算法

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摘要

Water-Filling (WF) is widely applied in power allocation in multichannel wireless communications. By mathematically linearising the optimal WF expression, the authors observe an intrinsic parallel-shift property of WF, based on which a fast and efficient WF algorithm is proposed. Compared with the conventional WF algorithms, it greatly simplifies WF execution by removing the Lagrange multiplier (or water-level) searching process. The authors further apply the proposed parallel-shift WF to solve the power allocation problem in orthogonal frequency division multiplexing (OFDM)-based underlay cognitive radios (CRs), with the objective of maximising the secondary user's throughput over all OFDM sub-channels under the transmit power and the interference constraints. To this end, the existing algorithm adopts an iterative binary searching process to find the solution, where the conventional WF algorithm with Lagrange multiplier searching is invoked in each iteration. In contrast, the authors propose a new power allocation algorithm to remove the iterative binary searching process. It runs the simplified parallel-shift WF only once, and then directly calculates the final solution using a power adjustment process (with the parallel-shift property as the underlying enabling mechanism). Numerical results show that both the proposed parallel-shift WF and the OFDM-based CR power allocation algorithms can run multiple times faster than the existing counterparts, and the gap on the running time increases with the total number of OFDM sub-channels in the system.
机译:注水(WF)被广泛应用于多通道无线通信的功率分配中。通过对最优WF表达式进行数学线性化,作者观察到WF的固有并行移位特性,在此基础上提出了一种快速有效的WF算法。与传统的WF算法相比,它通过消除Lagrange乘数(或水位)搜索过程大大简化了WF执行。作者进一步将提出的并行移位WF应用于解决基于正交频分复用(OFDM)的底层认知无线电(CR)中的功率分配问题,目的是在OFDM下所有OFDM子信道上最大化次要用户的吞吐量。发射功率和干扰约束。为此,现有算法采用迭代二进制搜索过程来找到解决方案,其中在每次迭代中均调用具有拉格朗日乘数搜索的常规WF算法。相反,作者提出了一种新的功率分配算法,以消除迭代二进制搜索过程。它仅运行简化的并行移位WF一次,然后使用功率调整过程(以并行移位属性作为基础启用机制)直接计算最终解决方案。数值结果表明,所提出的并行移位WF和基于OFDM的CR功率分配算法的运行速度都比现有的同类算法快很多倍,并且运行时间上的差距随着系统中OFDM子信道总数的增加而增加。 。

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  • 来源
    《Communications, IET 》 |2013年第12期| 1-1| 共1页
  • 作者

    Ling; X.; Wu; B.; Wen; H.; Pan; L.;

  • 作者单位

    National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China|c|;

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