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عنوان فارسی مقاله:
شبکه موجک برای کاهش نوسانات پاکت در سیستم WirelessMan-OFDM
عنوان انگلیسی مقاله:
Wavelet networks for reducing the envelope fluctuations in WirelessMan–OFDM systems
سال انتشار : 2016
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مقدمه انگلیسی مقاله:
1. Introduction
The WiMAX technology has recently gained in popularity due to its scalability in both radio access and network architecture as well as high-throughput broadband connection over long distances. For better service quality in terms of bandwidth and available frequency spectrum, the WirelessMan–OFDM based on IEEE 802.16d is associated with high speed modulation such as OFDM [1,2]. The OFDM is a multicarrier modulation technique that has many advantages such as high bandwidth efficiency, robustness to the selective fading problem, use of a small guard interval, and the ability to combat the inter-symbol interference problem [3]. However, it suffers from a serious weakness, the approximately Gaussian-distributed output samples cause large envelope fluctuations. Therefore, WiMAX hardware equipment is exposed to non-linearity caused by the problem of the high PAPR in OFDM multi-carrier signals. In the last decade, several techniques and algorithms for PAPR reduction have stimulated great interest [4]. These techniques include amplitude clipping and filtering, coding [1], Tone Reservation (TR) and Tone Injection (TI), Active Constellation Extension (ACE) [5], Partial Transmit Sequence (PTS), Selected Mapping (SLM) [6,7], and the Sequential Quadratic Programming (SQP) algorithm [8]. These differ in terms of the requirements and restrictions they impose on the system. Other methods based on artificial intelligence techniques, notably fuzzy neural networks, have also been proposed in [9,10]. These methods give good performance in terms of PAPR reduction with low complexity, although high density modulations such as 64-QAM were not taken into account by the authors. In this paper, we extend the method proposed in [10] by considering the PAPR problem in WirelessMan–OFDM systems and by using Wavelet Networks (WNs) to construct a scheme able to reduce the PAPR. On the other hand, we tested the validity of our proposal for high density modulations such as 64-QAM. The WNs are a new class of networks that take advantage of high resolution wavelets, learning and the feed forward nature of neural networks [11]. A motivation for using Wavelet Networks is its great success in a wide range of applications [12]. The training data of the WNs is obtained from the ACE-AGP method since it provides considerable envelope reductions without the need for side information, so that the data rate is not compromised. Its only weakness is its slow convergence that requires a long processing time to obtain the desired signal. This paper is organized as follows: In Section 2, we present the PAPR problem in the OFDM system. Section 3 introduces the principle of Wavelet Networks. The proposed models are then detailed and analyzed in Section 4. The performance of the proposed models for WirelessMan–OFDM PHY-layer is presented and discussed in Section 5. Finally, the conclusions are given in Section 6.
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کلمات کلیدی:
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