期刊名称：International Journal of Wireless & Mobile Networks
印刷版ISSN：0975-4679
电子版ISSN：0975-3834
出版年度：2016
卷号：8
期号：4
页码：107
DOI：10.5121/ijwmn.2016.8407
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：A new work has been proposed in this paper in order to overcome one of the main drawbacks that found inthe Orthogonal Frequency Division Multiplex (OFDM) systems, namely Peak to Average Power Ratio(PAPR). Furthermore, this work will be compared with a previously published work that uses the neuralnetwork (NN) as a solution to remedy this deficiency.The proposed work could be considered as a special averaging technique (SAT), which consists of wavelettransformation in its first stage, a globally statistical adaptive detecting algorithm as a second stage; andin the third stage it replaces the affected peaks by making use of moving average filter process. In the NNwork, the learning process makes use of a previously published work that is based on three linear codingtechniques.In order to check the proposed work validity, a MATLAB simulation has been run and has two mainvariables to compare with; namely BER and CCDF curves. This is true under the same bandwidthoccupancy and channel characteristics. Two types of tested data have been used; randomly generated dataand a practical data that have been extracted from a funded project entitled by ECEM. From the achievedsimulation results, the work that is based on SAT shows promising results in reducing the PAPR effectreached up to 80% over the work in the literature and our previously published work. This means that thiswork gives an extra reduction up to 15% of our previously published work. However, this achievement willbe under the cost of complexity. This penalty could be optimized by imposing the NN to the SAT work inorder to enhance the wireless systems performance.
关键词：Orthogonal Frequency Division Multiplexing; Neural Network; Linear Codes; Wavelet; Moving Average;Filter.
