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首页> 外文会议>BMEI 2012;International Conference on Biomedical Engineering and Informatics >Metric-based PRT set selection in tone reservation scheme for PAPR reduction in OFDM systmes
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Metric-based PRT set selection in tone reservation scheme for PAPR reduction in OFDM systmes

机译：音调保留方案中基于度量的PRT集选择，以降低OFDM系统中的PAPR

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摘要

High peak-to-average power ratio (PAPR) is one of the main problems of orthogonal frequency division multiplexing (OFDM) systems. Tone reservation (TR) scheme employs a subset of reserved subcarriers to construct a cancellation signal for PAPR reduction, with no additional distortion, no side information, and low implementation cost. Thus, the optimal performance of TR scheme depends on the selection of the peak reduction tone (PRT) set. In the conventional TR schemes, we have known that PAPR reduction performance achieved by a randomly generated PRT set is superior to that by a consecutive PRT set and that achieved by an interleaved tone set. However, the search of optimal PRT set is a nondeterministic polynomial-time (NP)-hard problem and cannot be solved. In this paper, a metric-based PRT set selection algorithm is presented to provide good performance and fast convergence. The scheme employs a metric to measure how much each subcarrier contributes to the output signal samples of large magnitude and then subcarriers with the largest positive metrics are selected as PRT set for PAPR reduction. The simulation results show that when the reserved subcarriers number is 1.46 percent, the PAPR gain of the proposed method can achieve 0.74dB at least compared with the conventional TR schemes at the probability of 10−3.
机译：高峰均功率比（PAPR）是正交频分复用（OFDM）系统的主要问题之一。音调预留（TR）方案采用预留子载波的子集来构造用于PAPR降低的消除信号，而没有附加失真，没有辅助信息并且实现成本低。因此，TR方案的最佳性能取决于峰值降低音调（PRT）集的选择。在传统的TR方案中，我们已经知道，通过随机生成的PRT集实现的PAPR降低性能优于连续PRT集和交错音调集所实现的PAPR降低性能。但是，最佳PRT集的搜索是一个不确定的多项式时间（NP）难题，无法解决。本文提出了一种基于度量的PRT集合选择算法，以提供良好的性能和快速的收敛性。该方案采用一种度量来测量每个子载波对大幅度输出信号样本有多少贡献，然后选择具有最大正度量的子载波作为降低PAPR的PRT集。仿真结果表明，当保留的子载波数量为1.46％时，与传统的TR方案相比，该方法的PAPR增益至少可以达到0.74dB，概率为10 -3 。

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