A Hybrid Segmentation Pattern of Partial Transmission in Computer Networks to Reduce the Complexity Level

Partial transmission sequence (PTS) is seen as a related project in the framework of the Orthogonal Frequency Division ‎Multiplexing (OFDM) to suppress the medium to high Peak-to-Average Power Ratio problem. The PTS chart data is based on dividing the back into subdivisions and their weight by combining step-by-step factors. Despite the fact that PTS can reduce the high specifications. The Computational Complexity Level (CC) limits the scope of application to match PTS use with ground applications. In PTS, there are three main distribution schemes. Interleaving projects (IL-PTS), arbitrary and alternate (PR-PTS) and Ad-PTS. In this paper, another algorithm called the Hybrid Pseudo-Random and Interleaving Cosine Wave Shape ‎‎(H-PRC-PTS) is presented and the PR-PTS equilibrium is established by stabilizing the cousin waveform between languages (S-IL-C- PTS), which was suggested in the previous work. The results showed that the proposed algorithm could reduce the validity of PAPR as a PR-PTS scheme, although the CC level was significantly reduced

New methods of partial transmit sequence for reducing the high peak-to-average-power ratio with low complexity in the ofdm and f-ofdm systems

The orthogonal frequency division multiplexing system (OFDM) is one of the most important components for the multicarrier waveform design in the wireless communication standards. Consequently, the OFDM system has been adopted by many high-speed wireless standards. However, the high peak-to-average- power ratio (PAPR) is the main obstacle of the OFDM system in the real applications because of the non-linearity nature in the transmitter. Partial transmit sequence (PTS) is one of the effective PAPR reduction techniques that has been employed for reducing the PAPR value 3 dB; however, the high computational complexity is the main drawback of this technique. This thesis proposes novel methods and algorithms for reducing the high PAPR value with low computational complexity depending on the PTS technique. First, three novel subblocks partitioning schemes, Sine Shape partitioning scheme (SS-PTS), Subsets partitioning scheme (Sb-PTS), and Hybrid partitioning scheme (H-PTS) have been introduced for improving the PAPR reduction performance with low computational complexity in the frequency-domain of the PTS structure. Secondly, two novel algorithms, Grouping Complex iterations algorithm (G-C-PTS), and Gray Code Phase Factor algorithm (Gray-PF-PTS) have been developed to reduce the computational complexity for finding the optimum phase rotation factors in the time domain part of the PTS structure. Third, a new hybrid method that combines the Selective mapping and Cyclically Shifts Sequences (SLM-CSS-PTS) techniques in parallel has been proposed for improving the PAPR reduction performance and the computational complexity level. Based on the proposed methods, an improved PTS method that merges the best subblock partitioning scheme in the frequency domain and the best low-complexity algorithm in the time domain has been introduced to enhance the PAPR reduction performance better than the conventional PTS method with extremely low computational complexity level. The efficiency of the proposed methods is verified by comparing the predicted results with the existing modified PTS methods in the literature using Matlab software simulation and numerical calculation. The results that obtained using the proposed methods achieve a superior gain in the PAPR reduction performance compared with the conventional PTS technique. In addition, the number of complex addition and multiplication operations has been reduced compared with the conventional PTS method by about 54%, and 32% for the frequency domain schemes, 51% and 65% for the time domain algorithms, 18% and 42% for the combining method. Moreover, the improved PTS method which combines the best scheme in the frequency domain and the best algorithm in the time domain outperforms the conventional PTS method in terms of the PAPR reduction performance and the computational complexity level, where the number of complex addition and multiplication operation has been reduced by about 51% and 63%, respectively. Finally, the proposed methods and algorithms have been applied to the OFDM and Filtered-OFDM (F-OFDM) systems through Matlab software simulation, where F-OFDM refers to the waveform design candidate in the next generation technology (5G)

A Novel Search Method to Reduce PAPR of an OFDM Signal Using Partial Transmit Sequences

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[[alternative]]A novel search method to reduce PAPR of an OFDM signal using partial transmit sequences

碩士[[abstract]]正交分頻多工(OFDM)的主要缺點之一在於在傳送OFDM訊號過程中會產生高的峰值對均值功率比，以致於訊號經過功率放大器之後會造成非線性失真。部份傳輸序列法(PTS-partial transmit sequence)可以有效改善OFDM訊號的PAPR。但傳統的PTS調變技術必須搜尋相位因子的所有可能組合，其搜尋複雜度會隨著子區間的數量和相位因子的種類呈現指數形式增加。本論文中，我們提出新的PTS技術僅需要些微效能的降低卻能有效減少大量傳統PTS的高計算複雜度的缺點。[[abstract]]One of the main drawbacks of orthogonal frequency division multiplexing (OFDM) is the high peak-to-average power ratio (PAPR) of the transmitted OFDM signal. Partial transmit sequence (PTS) technique can improve the PAPR statistics of an OFDM signal. As ordinary PTS technique requires an exhaustive search over all combinations of allowed phase factors, the search complexity increases exponentially with the number of sub-blocks. In this paper, we propose a novel PTS technique with reduced complexity that achieves significant reduction in search complexity with little performance degradation.[[tableofcontents]]目錄 第一章 概論 P.1 第二章 正交分頻多工系統介紹 P.6 第三章 正交分頻多工系統的峰值對平均值功率比 P.14 3.1 峰值對平均值功率比 P.14 3.2 降低PAPR的方法 P.18 第四章 部分傳輸序列法 P.24 4.1 原始的部分傳輸序列法 P.24 4.2 反覆翻轉運算法 P.27 4.3 漸進倍增反相法 P.28 4.4 結論 P.33 第五章 模擬與分析 P.41 5.1 數值分析結果P.41 5.2 結論 P.43 第六章 結論 P.51 圖目錄 圖1.1 多載波系統圖 P.5 圖2.1 ASK, FSK及PSK三種基本調變波形 P.10 圖2.2 次載波完全正交 P.11 圖2.3 OFDM通訊系統的方塊圖 P.12 圖2.4 OFDM傳輸示意圖 P.13 圖3.1 載波疊加及PAPR的產生 P.21 圖3.2 4個次載波利用BPSK調變訊號振幅分布的情形 P.22 圖3.3 PAPR依N大小不同所呈現的CDF分布圖形 P.23 圖4.1 PTS技術的方塊圖 P.35 圖4.2 QPSK調變情形 P.36 圖4.3 反覆翻轉運算法流程圖 P.37 圖4.4 反覆翻轉運算法N = 64 P.38 圖4.5 反覆翻轉運算法N = 128 P.39 圖4.6 漸進倍增反相法流程圖 P.40 圖5.1 N = 64，M = 4時各種PAPR調降方法的CCDF P.45 圖5.2 N = 128，M = 4時各種PAPR調降方法的CCDF P.46 圖5.3 N = 64，M = 8時各種PAPR調降方法的CCDF P.47 圖5.4 N = 128，M = 8時各種PAPR調降方法的CCDF P.48 圖5.5 N = 64，M = 4, 8, 16之CCDF P.49 圖5.6 N = 128，M = 4, 8, 16 CCDF P.50 表目錄 表1 各方法計算量的比較 P.35[[note]]學號: 692351058, 學年度: 9