以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：44

、訪客IP：18.118.140.96

姓名	鄭南宏(Nan-Hung Cheng)  查詢紙本館藏	畢業系所	通訊工程學系
論文名稱	正交分頻多工系統之時變通道下頻率偏移估測研究 (A Study of Carrier Frequency Offset Estimation in OFDM Systems for Time-Varying Channels)
相關論文	★ 利用手持式手機工具優化行動網路系統於特殊型活動環境 ★ 穿戴裝置動態軌跡曲線演算法設計 ★ 石英諧振器之電極面設計對振盪頻率擾動之溫度相依性研究 ★ 股票開盤價漲跌預測 ★ 感知無線電異質網路下以不完美頻譜偵測進行資源配置之探討 ★ 大數量且有限天線之多輸入多輸出系統效能分析 ★ 具有元學習分類權重轉移網路生成遮罩於少樣本圖像分割技術 ★ 具有注意力機制之隱式表示於影像重建三維人體模型 ★ 使用對抗式圖形神經網路之物件偵測張榮 ★ 基於弱監督式學習可變形模型之三維人臉重建 ★ 以非監督式表徵分離學習之邊緣運算裝置低延遲樂曲中人聲轉換架構 ★ 基於序列至序列模型之 FMCW雷達估計人體姿勢 ★ 基於多層次注意力機制之單目相機語意場景補全技術 ★ 應用於3GPP WCDMA-FDD上傳鏈路系統的遞迴最小平方波束合成犛耙式接收機 ★ 調適性遠時程瑞雷衰退通道預測演算法設計與性能比較 ★ 智慧型天線之複合式到達方位-時間延遲估測演算法及Geo-location應用
檔案	[Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載] 本電子論文使用權限為同意立即開放。 已達開放權限電子全文僅授權使用者為學術研究之目的，進行個人非營利性質之檢索、閱讀、列印。 請遵守中華民國著作權法之相關規定，切勿任意重製、散佈、改作、轉貼、播送，以免觸法。
摘要(中)	正交頻分多重接取是一種基於正交頻分多工的多重接取技術。在正交頻分多重接取系統中，載波頻率偏移不僅會導致載波之間失去正交性，從而導致載波間干擾，而且還會影響該系統中的不同用戶，如多重接取干擾。因此，頻率同步是防止系統性能下降的重要任務。我們提出了三種演算法來估測時變通道下正交頻分多工系統中的載波頻率偏移。 在第一個方法中，我們提出一個針對多輸入多輸出–正交分頻多工系統進行載波頻率偏移與頻率選擇性通道響應聯合估測的方法。首先介紹多輸入多輸出–正交分頻多工系統的訊號模式，再以最大似然解為前提發展一個聯合估測演算法。該演算法可以分為三部分：在第一個部分我們利用去旋轉法估計出初始載波頻率偏移，並將之作頻域等化。第二部分以迭代法求得頻率峰值以強化載波頻率偏移估測方面的效能。第三部分採用了自適應程序，以獲取更新的載波頻率偏移估測並追踪時變參數，包括時變載波頻率偏移和時變通道。此方法在計算上的複雜度遠低於以最大似然為基礎的網格搜索法，且在模擬結果的均方差方面也極接近克拉美-羅下限。模擬結果顯示這個新提出的聯合估測演算法跟以完美情形作通道估測在位元錯誤率方面的表現極為接近。模擬結果亦表明，該方法在Jakes的通道模型中具有可靠的追踪性能。 在第二種方法當中，我們在正交分頻多重接取系統中利用一個簡單的疊代方案做為盲蔽式載波頻率偏移算法，用以降低複雜度，並以自適應方式提出了一種時變載波頻率偏移自適應估測方法。該演算法中可以分為二部分：在第一個部分使用初始粗略估測的載波頻率偏移，採用疊代法獲得載波頻率偏移的估測。第二部分是使用建議的自適應程序來獲取更新的載波頻率偏移估測並追踪時變參數。模擬結果證明，所提出的疊代及自適應方案具有效能，並且得出的均方誤差接近克拉美-羅下限。 第三個方法當中，我們提出了一種在正交分頻多重接取系統具有較強抗干擾能力的載波頻率偏移估測演算法。考慮了正交分頻多重接取中的異質網路環境。在提出的演算法的第一部分中，瞭解如何在異質網路或高密度小型基地台環境下處理接收到的信號，並開發處理載波頻率偏移估測問題。第二部分是使用建議的自適應程序來獲取更新的載波頻率偏移估測並跟踪時變參數。模擬結果證明了該方法的有效性，其性能接近克拉美-羅下限。
摘要(英)	Orthogonal frequency division multiple access (OFDMA) is a multiple access technique based on orthogonal frequency division multiplexing (OFDM). In OFDMA systems, carrier frequency offsets (CFOs) not only cause the loss of orthogonality among the carriers, which leads to the inter-carrier interference (ICI), but also influence the different users in this system, as multiple-access interferences (MAI). Hence, frequency synchronization is an important task to prevent the performance degradation of the system. We propose three algorithms for estimating CFO in OFDM Systems for Time-Varying Channels. In the first algorithm, we present a joint time-variant CFO and frequency-selective channel response estimation scheme for multiple input multiple output–orthogonal frequency-division multiplexing (MIMO–OFDM) systems for mobile users. The signal model of the MIMO–OFDM system is introduced, and the joint estimator is derived according to the maximum likelihood criterion. The proposed algorithm can be separated into three major parts. In the first part of the proposed algorithm, an initial CFO is estimated using derotation, and the result is used to apply a frequency-domain equalizer. In the second part, an iterative method is employed to locate the fine frequency peak for better CFO estimation. An adaptive process is used in the third part of the proposed algorithm to obtain the updated CFO estimation and track parameter time variations, including the time-varying CFOs and time-varying channels. In a simulation, the mean squared error performance of the proposed algorithm is close to the Cramer–Rao lower bound (CRB). The simulation results indicate that the proposed novel joint estimation algorithm provides a bit error rate performance close to that in the perfect channel estimation condition. In the second algorithm, we propose simple iteration schemes for blind CFO estimation algorithms in OFDMA systems to reduce complexity with an adaptive manner and present a time-variant CFO adaptive estimation method. In the first part of the proposed algorithm, with initial rough estimated CFOs, it employs iterative methods to obtain CFO estimates. And the second part is to use proposed adaptive process to obtain the updated CFO estimation and track the parameters’ time-variations. The simulation results demonstrate the efficacy of the proposed iteration and adaptive schemes and the Mean Squared Errors (MSEs) are near to the CRBs. The third proposed algorithm, we propose a CFO estimation algorithm with strong interference resistant capability for OFDMA systems. Heterogeneous networks (HetNet) environments in OFDMA are considered. In the first part of the proposed algorithm, how received signals are processed under the HetNet scenarios/dense small cells to deal with the CFO estimation problem is developed. And the second part is to use the proposed adaptive process to obtain the updated CFO estimation and track the parameters’ time-variations. The simulation results demonstrate the effectiveness of this method and the performances are close to the CRBs.
關鍵字(中)	★ 載波頻率偏移 ★ 正交分頻多工 ★ 時變通道	關鍵字(英)	★ Carrier frequency offset (CFO) ★ Orthogonal frequency-division multiplexing (OFDM) ★ Time-varying channels
論文目次	中 文 摘 要 xi Abstract xii 致 謝 xiv List of Contents xv List of Figures xviii List of Tables xxi List of Notations and Symbols xxii Chapter 1. Introduction 1 1.1 Motivation 1 1.2 Overview of the Dissertation 6 1.3 Dissertation Structure 7 Chapter 2. Related Work 9 2.1 Joint CFO and Channel Estimation in MIMO-OFDM Systems 9 2.2 Carrier Frequency Estimation in Multi-user OFDMA Systems 10 2.3 Carrier Frequency Offset Estimation for Interference Environments in OFDMA Uplink Systems 12 Chapter 3. Maximum-likelihood-based Adaptive Iteration Algorithm Design for Joint CFO and Channel Estimation in MIMO-OFDM Systems 13 3.1 Signal Model 14 3.2 Proposed Joint CFO and Channel Iterative Estimation Algorithm 17 3.2.1 Receiver Design 17 3.2.2 Initial CFO Estimation 18 3.2.3 Frequency-domain Equalizer 20 3.2.4 Small-step Iterative Searching 22 3.2.5 Computational Complexity and the Procedure of the Proposed Method 26 3.2.6 Adaptive Mode for Tracking the Time Variations of Parameters 29 3.3 Simulation Results 29 3.3.1 Algorithm Performance in the Iterative Mode 31 3.3.2 Algorithm Performance in the Adaptive Tracking Mode 34 3.3.3 Computational Cost 42 Chapter 4. Adaptive Iteration Methods for Blind Carrier Frequency Estimation in Multi-user OFDMA Systems 45 4.1 System Model on OFDMA Uplink 45 4.2 Proposed Algorithms 49 4.2.1 MUSIC-based Approach 49 4.2.2 Proposed Iteration Methods Based on Maximum Likelihood (ML) and Approximate Maximum Likelihood (AML) Criterions 50 4.2.3 Proposed Iteration Algorithms 52 4.2.4 Computational Complexity and the Procedure of the Proposed Method 53 4.2.5 Adaptive Mode for Tracking Time Variations of Parameters 56 4.3 Simulations Results 58 4.3.1 Algorithm Performance for the Iterative Mode 60 4.3.2 Algorithm Performance for the Adaptive Tracking Mode 64 4.3.3 Computational Cost 67 Chapter 5. Adaptive Carrier Frequency Offset Estimation for Interference Environments in OFDMA Uplink Systems 69 5.1 Signal Structure for OFDMA Uplink Systems 69 5.1.1 OFDM-Based Multiple-Access OFDMA 70 5.1.2 Single-User Signal with Interference and Effective CFO 72 5.1.3 Multiple-User Signal Structure with Interference 73 5.2 Proposed CFO Estimation Algorithms 73 5.2.1 Estimator Based on ESPRIT with Interference Resistant 73 5.2.2 Adaptive Mode for Tracking the Time Variations of Parameters 76 5.3 Simulations Results 76 5.3.1 Performance of the Algorithm Based on ESPRIT with Interference Resistant 78 5.3.2 Performance of the Algorithm in the Adaptive Tracking Mode 80 Chapter 6. Conclusion and Future Prospects 83 References 85 Appendix 94
參考文獻	[1] M. J. Paek, W. C. Kim, M. Y. Kim, and H. K. Song, “Spatial Phase Coding With CoMP for Performance Enhancement Based on MIMO-OFDM in HetNet System”, IEEE Access, Vol. 7, pp. 62240-62250, May 2019. [2] S. Kant, M. Bengtsson, Bo Göransson, G. Fodor, and C. Fischione, “Efficient Optimization for Large-Scale MIMO-OFDM Spectral Precoding”, IEEE Transactions on Wireless Communications, Early Access, pp. 1-14, March 2021. [3] S. Kant, M. Bengtsson, G. Fodor, Bo Göransson, and C. Fischione, “EVM-Constrained and Mask-Compliant MIMO-OFDM Spectral Precoding”, IEEE Transactions on Wireless Communications, Vol. 20, No. 1, pp. 590-606, January 2021. [4] L. Xu, F. Gao, W. Zhang, and S. Ma, “Model Aided Deep Learning Based MIMO OFDM Receiver With Nonlinear Power Amplifiers”, Wireless Communications and Networking Conference (WCNC), pp. 1-6, Nanjing, China, March 2021. [5] E. Dahlman, S. Parkvall, and J. Skold, 5G NR The Next Generation Wireless Access Technology., Academic, New York, NY, USA, September 2020. [6] E. Kofidis and V. Dalakas, “Filter Bank-based Multiple Access in Next Generation Satellite Uplinks: A DVB-RCS2-based Experimental Study”, 5G World Forum (5GWF), pp. 427-430, Dresden, Germany, September 2019. [7] G. Kongara, C. He, L. Yang, and J. Armstrong, “A Comparison of CP-OFDM, PCC-OFDM and UFMC for 5G Uplink Communications”, IEEE Access, Vol. 7, pp. 157574-157594, November 2019. [8] M. Suzuki, T. Suzuki, Y. Kishiyama, and K. Higuchi, “Complexity-Reduced Algorithm for Adaptive PAPR Reduction Method Using Null Space in MIMO Channel for MIMO-OFDM Signals”, IEEE VTS Asia Pacific Wireless Communications Symposium (APWCS), pp. 1-5, Singapore, August 2019. [9] S. S. Ullah, S. C. Liew, G. Liva, and T. Wang, “Implementation of Short-Packet Physical-Layer Network Coding”, IEEE Transactions on Mobile Computing, Early Access, pp. 1-15, April 2021. [10] D. Ren and J. Li, “Joint Channel Estimation and Equalization Using New AFB Output Signal Models for FBMC/OQAM Systems”, IEEE Transactions on Communications, Early Access, pp. 1-15, March 2021. [11] Y. Shan and F. Wang, “Low-complexity and Low-overhead Receiver for OTFS via Large-scale Antenna Array”, IEEE Transactions on Vehicular Technology, Early Access, pp. 1-16, April 2021. [12] A. Rotem and Ron Dabora, “A Novel Low-Complexity Estimation of Sampling and Carrier Frequency Offsets in OFDM Communications”, IEEE Access, Vol. 8, pp. 194978-194991, October 2020. [13] Y. Meng, W. Zhang, G. L. Stüber, and W. Wang, “Blind Fast CFO Estimation and Performance Analysis for OFDM”, IEEE Transactions on Vehicular Technology, Vol. 69, No. 10, pp. 11501-11514, October 2020. [14] M. Zhou, X. Huang, Zhe Feng, and Y. Liu, “Coarse Frequency Offset Estimation in MIMO Systems Using Neural Networks: A Solution With Higher Compatibility”, IEEE Access, Vol. 7, pp. 121565-121573, August 2019. [15] A. Jhingan, L. Kansal, GS Gaba, F. Tubbal, and S. Abulgasem, “Performance Analysis of OFDM System Augmented with SC Diversity Combining Technique in Presence of CFO”, 12th International Conference on Telecommunication Systems, Services, and Applications (TSSA), Yogyakarta, Indonesia, October 2018. [16] B. Sokal, P. R. B. Gomes, A. L. F. de Almeida, and M. Haardt, “Joint Channel, Data, and Phase-Noise Estimation in MIMO-OFDM Systems Using a Tensor Modeling Approach”, International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4460-4464, Toronto, ON, Canada, June 2021. [17] T. Mao, Q. Wang, Z. Wang, and S. Chen, “Novel Index Modulation Techniques: a Survey”, IEEE Communications Surveys & Tutorials, Vol. 21, No. 1, pp. 315-348, First-quarter 2019. [18] Y. Liu, X. Zhao, H. Zhou, Y. Zhang, and T. Qiu, “Low-Complexity Spectrum Sensing for MIMO Communication Systems Based on Cyclostationarity”. EURASIP Journal on Advances in Signal Processing 2019, No. 29, June 2019. [19] K. Kavya, V. S. S. C. S. Murty, K. G. Sujanth Narayan, and J. A. Baskaradas, “Transceiver Design with Hybrid Beamforming for Sub 6 GHz MIMO Communication”, International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), pp. 143-147, Chennai, India, March 2021. [20] I. W. Lai, J. W. Shih, C. W. Lee, H. H. Tu, J. C. Chi, J. S. Wu, and Y. H. Huang, “Spatial Permutation Modulation for Multiple-Input Multiple-Output (MIMO) Systems”, IEEE Access, Vol. 7, pp. 68206-68218, May 2019. [21] G. Li, T. Li, M. Xu, X. Zha, and Y. Xie, “Sparse Massive MIMO-OFDM Channel Estimation Based on Compressed Sensing over Frequency Offset Environment”, EURASIP Journal on Advances in Signal Processing 2019, No. 31, July 2019. [22] T. Ye, “Wireless Resource Scheduling in 5G Mobile Communication System”, International Conference on Information Systems and Computer Aided Education (ICISCAE), pp. 648-653, Dalian, China, October 2019. [23] H. Abdzadeh-Ziabari, W. P. Zhu, and M. N. S. Swamy, “Joint Carrier Frequency Offset and Doubly Selective Channel Estimation for MIMO-OFDMA Uplink With Kalman and Particle Filtering”, IEEE Transactions on Signal Processing, Vol. 66, No. 15, pp. 4001-4012, August 2018. [24] N. Moosavi, M. Sinaie, P. Azmi, P.H. Lin, and E. Jorswieck, “Cross Layer Resource Allocation in H-CRAN with Spectrum and Energy Cooperation”, IEEE Transactions on Mobile Computing, Early Access, pp. 1-13, April 2021. [25] M. K. Jha, N. Kumar, and Y. V. S. Lakshmi, “Performance of Zero-Biased NOMA VLC System”, 5G World Forum (5GWF), pp. 519-523, Bangalore, India, September 2020. [26] S. Fu, L. Zhao, X. Jian, and S. Wu, “Data Attachment: A Novel Type of Wireless Transmission”, IEEE Wireless Communications, Vol. 26, No. 6, pp. 126-131, December 2019. [27] P. S. Sanoopkumar, P. Muneer, and S. M. Sameer, “Joint Estimation of RF Impairments, Channel, and Low Complexity Iterative Equalization Technique for High Mobility SC-FDMAOFDMA Uplink Systems”, IEEE Transactions on Wireless Communications, Vol. 19, No. 6, pp. 4276-4289, June 2020. [28] G. Barb, M. Otesteanu, F. Alexa, and F. Danuti, “OFDM Multi-Numerology for Future 5G New Radio Communication Systems”, International Conference on Software, Telecommunications and Computer Networks (SoftCOM), pp. 1-3, Split, Croatia, September 2020. [29] M. Mahdavi, O. Edfors, V. Öwall, and L. Liu, “A Low Latency FFT/IFFT Architecture for Massive MIMO Systems Utilizing OFDM Guard Bands”, IEEE Transactions on Circuits and Systems I: Regular Papers, Vol. 66, No. 7, pp. 2763-2774, July 2019. [30] D. Kitayama, D. Kurita, M. Inomata, K. Tateishi, A. Harada, T. Imai, Y. Kishiyama, S. Itoh, H. Murai, A. Simonsson, and P. Ökvist, “5G Radio Access Experiments on Distributed MIMO Deployment for Straightly Traveling Mobile Station with Beamforming in 28-GHz Frequency Band”, Wireless Communications and Networking Conference Workshop (WCNCW), pp. 56-61, Marrakech, Morocco, April 2019. [31] J. Pang, Z. Li, X. Luo, J. Alvin, R. Saengchan, A. A. Fadila, K. Yanagisawa, Yi Zhang, Z. Chen, Z. Huang, X. Gu, Rui Wu, Yun Wang, D. You, B. Liu, Z. Sun, Y. Zhang, H. Huang, N. Oshima, K. Motoi, S. Hori, K. Kunihiro, T. Kaneko, A. Shirane, and K. Okada, “A CMOS Dual-Polarized Phased-Array Beamformer Utilizing Cross-Polarization Leakage Cancellation for 5G MIMO Systems”, IEEE Journal of Solid-State Circuits, Vol. 56, No. 4, pp. 1310-1326, January 2021. [32] A. B. Belguidoum, M. L. Tounsi, and S. Mekaoui, “Analysis of 5G Radio Parameters and their Impact on the Peak Data Rate”, European Conference on Electrical Engineering and Computer Science (EECS), pp. 66-71, Athens, Greece, December 2019. [33] D. Kurita, D. Kitayama, K. Tateishi, A. Harada, Y. Kishiyama, S. Itoh, H. Murai, J. Fwu, X. Zhuang, and K. Stewart, “Outdoor Experiments on 5G Radio Access Using BS and UE Beamforming in 28-GHz Frequency Band”, IEEE Annual Consumer Communications & Networking Conference (CCNC), pp. 1-6, Las Vegas, NV, USA, January 2019. [34] S. Han, X. Xu, Z. Liu, P. Xiao, K. Moessner, X. Tao, and P. Zhang, “Energy-Efficient Short Packet Communications for Uplink NOMA-Based Massive MTC Networks”, IEEE Transactions on Vehicular Technology, Vol. 68, No. 12, pp. 12066-12078, December 2019. [35] S. Jin, S. Roy, and T. R. Henderson, “Efficient PHY Layer Abstraction for Fast Simulations in Complex System Environments”, IEEE Transactions on Communications, Early Access, pp. 1-11, May 2021. [36] K. Woradit, S. Srirai, S. Kitjarunerungroj, T. Kodmatcha, and P. Sangmahamad, “Multi-user Secrecy SWIPT for 5G OFDMA Networks with Particle Swarm Optimizations”, International Conference on Consumer Electronics - Asia (ICCE-Asia), pp. 106-110, Bangkok, Thailand, June 2019. [37] S. H. Lo, and Y. F. Chen, “Subcarrier Allocation for Rate Maximization in Multiuser OFDM NOMA Systems on Downlink Beamforming”, International Conference on Applied System Innovation (ICASI), pp. 56-61, Taitung, Taiwan, November 2020. [38] S. M. Tseng, C. S. Tsai, and C. Y. Yu, “Outage-Capacity-Based Cross Layer Resource Management for Downlink NOMA-OFDMA Video Communications Non-Deep Learning and Deep Learning Approaches”, IEEE Access, Vol. 8, pp. 140097-140107, June 2020. [39] F. B. Mismar and B. L. Evans, “Deep Learning in Downlink Coordinated Multipoint in New Radio Heterogeneous Networks”, IEEE Wireless Communications Letters, Vol. 8, No. 4, pp. 1040-1043, August 2019. [40] A. Fadel, A. Nimr, H. L. Chiang, M. Chafii, and B. Cousin, “Cross-Layer Multi-User Selection in 5G Heterogeneous Networks Based on Hybrid Beamforming Optimization for Millimeter-Wave”, IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), pp. 1-7, Istanbul, Turkey, September 2019. [41] S. N. Hasim and M. Susanto, “Performance Evaluation of Cell-Edge Femtocell Densely Deployed in OFDMA-Based Macrocellular Network”, International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), pp. 262-266, Yogyakarta, Indonesia, December 2020. [42] L. C. Wang and S. H. Cheng, “Data-Driven Resource Management for Ultra-Dense Small Cells: An Affinity Propagation Clustering Approach”, IEEE Transactions on Network Science and Engineering, Vol. 6, No. 3, pp. 267-279, July-Sept. 2019. [43] L. Xiao, H. Zhang, Y. Xiao, X. Wan, S. Liu, L. C. Wang, and H. V. Poor, “Reinforcement Learning-Based Downlink Interference Control for Ultra-Dense Small Cells,” IEEE Transactions on Wireless Communications, Vol. 19, No. 1, pp. 423-434, January 2020. [44] A. Mohammadian and C. Tellambura, “Joint Channel and Phase Noise Estimation and Data Detection for GFDM”, IEEE Open Journal of the Communications Society, Vol. 2, pp. 915-933, April 2021. [45] M. Ataeeshojai, R. C. Elliott, W. A. Krzymień, C. Tellambura, and J. Melzer, “Energy-Efficient Resource Allocation in Single-RF Load-Modulated Massive MIMO HetNets”, IEEE Open Journal of the Communications Society, Vol. 1, pp. 1738-1764, October 2020. [46] T. S. Rappaport, Y. Xing, O. Kanhere, S. Ju, A. Madanayake, S. Mandal, A. Alkhateeb, and G. C. Trichopoulos, “Wireless Communications and Applications above 100 GHz: Opportunities and Challenges for 6G and Beyond”, IEEE Access, Vol. 7, pp. 78729-78757, June 2019. [47] Z. Zhang, Y. Xiao, Z. Ma, M. Xiao, Z. Ding, X. Lei, G. K. Karagiannidis, and P. Fan, “6G Wireless Networks: Vision, Requirements, Architecture, and Key Technologies”, IEEE Vehicular Technology Magazine, Vol. 14, No. 3, pp. 28-41, September 2019. [48] S. S. Das, V. Rangamgari, S. Tiwari, and S. C. Monda, “Transmission Schemes for Backscatter Aided Wireless Communications on High Speed Rails”, IEEE Access, Vol. 9, pp. 10561-10576, January 2021. [49] A. Guidotti, A. Vanelli-Coralli, M. Conti, S. Andrenacci, S. Chatzinotas, N. Maturo, B. Evans, A. Awoseyila, A. Ugolini, T. Foggi, L. Gaudio, N. Alagha, and S. Cioni, “Architectures and Key Technical Challenges for 5G Systems Incorporating Satellites”, IEEE Transactions on Vehicular Technology, Vol. 68, No. 3, pp. 2624-2639, March 2019. [50] K. Mahata and Md M. Hyder, “A New Perspective on the Initial Uplink Synchronization Problem”, IEEE Access, Vol. 8, pp. 212258-212279, November 2020. [51] J. D. Roth, D. A. Garren, and R. C. Robertson, “Integer Carrier Frequency Offset Estimation in OFDM with Zadoff-Chu Sequences”, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4850-4854, Toronto, ON, Canada, June 2021. [52] S. B. Amor, S. Affes, F. Bellili, and D. N. Jayakody, “ML-type EM-based Estimation of Fast Time-varying Frequency-selective Channels over SIMO OFDM Transmissions”, IEEE Access, Vol. 7, pp. 148265-148277, October 2019. [53] F. Yang, P. Cai, H. Qian, and X. Luo, “Pilot Contamination in Massive MIMO Induced by Timing and Frequency Errors”, IEEE Trans. Wirel. Commun., Vol. 17, No. 7, pp. 4477-4492, July 2018. [54] W. C. Huang, Y. S. Yang, and C. P. Li, “A New Pilot Architecture for Sub-band Uplink OFDMA Systems”, IEEE Transactions on Broadcasting, Vol. 59, No. 3, pp. 461-470, September 2013. [55] W. Zhang, F. Gao, H. Minn, and H. M. Wang, “Scattered Pilots-based Frequency Synchronization for Multiuser OFDM Systems with Large Number of Receive Antennas”, IEEE Transactions on Communication, Vol. 65, No. 4, pp. 1733-1745, April 2017. [56] Z. Cao, U. Tureli, and Y. Yao, “Deterministic Multiuser Carrier-frequency Offset Estimation for Interleaved OFDMA Uplink”, IEEE Transactions on Communications, Vol. 52, No. 9, pp. 1585-1594, September 2004. [57] L. Kuang, J. Lu, Z. Ni, and J. Zheng, “Non-pilot-aided Carrier Frequency Tracking for Uplink OFDMA Systems”, Proceedings in IEEE International Conference on Communications, pp. 3193-3196, Paris, France, June 2004. [58] J. van de Beek, P. O. Borjesson, M. Boucheret, D. Landstrom, J. M. Arenas, P. Odling, C. Ostberg, M. Wahlqvist, and S. K. Wilson, “A Time and Frequency Synchronization Scheme for Multiuser OFDM”, IEEE Journal on Selected Areas Communications, Vol. 17, No. 11, pp. 1900-1914, November 1999. [59] S. S. Li and S. M. Phoong, “Blind Estimation of Multiple Carrier Frequency Offsets in OFDMA Uplink Systems Employing Virtual Carriers”, IEEE Access, Vol. 8, pp. 2915-2923, January 2020. [60] A. Li, Yi Ma, S. Xue, Na Yi, R. Tafazolli, and T. E. Dodgson, “Unsupervised Deep Learning for Blind Multiuser Frequency Synchronization in OFDMA Uplink”, IEEE International Conference on Communications (ICC), Shanghai, China, May 2019. [61] AJ Coulson, “Maximum Likelihood Synchronization for OFDM Using a Pilot Symbol: Algorithm”, IEEE J. Sel. Areas Commun., Vol. 19, No. 12, pp. 2486-2494, December 2001. [62] A. Kumar, S. Saha, Abhiranjan, and R. Bhattacharya, “Neural Network Based Joint Carrier Frequency Offset and Sampling Frequency Offset Estimation and Compensation in MIMO OFDM-OQAM Systems”, General Assembly and Scientific Symposium of the International Union of Radio Science, pp. 1-4, Rome, Italy, September 2020. [63] Wei Xu and Zhe Zhao, “Research on Sparse Channel Estimation Algorithm Based on MIMO-OFDM System”, International Conference on Communications, Information System and Computer Engineering (CISCE), pp. 403-406, Kuala Lumpur, Malaysia, July 2020. [64] I. Ziskind and M. Wax, “Maximum Likelihood Localization of Multiple Sources by Alternating Projection”, IEEE Trans. Acoust. Speech Signal Process. Vol. 36, No. 10, pp. 1553-1560, October 1988. [65] X. Chen, A. Wolfgang, and A. Zaidi, “MIMO-OFDM for Small Cell Backhaul in the Presence of Synchronization Errors and Phase Noise”, IEEE International Conference on Communications Workshops (ICC Workshops), Paris, France, May 2017. [66] S. Salari, M. Heydarzadeh, and J. P. Cances, “Joint Maximum-likelihood Frequency Synchronization and Channel Estimation in MIMO-OFDM Systems with Timing Ambiguity”, International Symposium on Wireless Communication Systems (ISWCS), pp. 954-958, Paris, France, August 2012. [67] Min Huang, Lei Huang, W. Sun, W. Bao, and J. Zhang, “Sparse Bayesian Learning Assisted CFO Estimation Using Nonnegative Laplace Priors”, IEEE Transactions on Vehicular Technology, Vol. 68, No. 6, pp. 6151-6155, June 2019. [68] J. Lee, S. Lee, K. Bang, S. Cha, and D. Hong, “Carrier Frequency Offset Estimation Using ESPRIT for Interleaved OFDMA Uplink Systems”, IEEE Trans. on Vehicular Technology, Vol. 56, No. 5, pp. 3227-3231, September 2007. [69] R. Roy and T. Kailath, “ESPRIT─Estimation of Signal Parameters via Rotational Invariance Techniques”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol. 37, No. 7, pp. 984-995, July 1989. [70] P. Stoica and R. Moses, Introductions to Spectral Analysis., NJ: Prentice-Hall, Englewood Cliffs, 1997. [71] S. H. Chiu, K. C. Fu, and Y. F. Chen, “A Modified Algorithm for Joint Frequency Offset and Channel Estimation in OFDM Systems”, International Conference on Communications in China (ICCC), pp. 327-332, Xi′an, China, August 2013. [72] M. Morelli and U. Mengali, “Carrier-frequency Estimation for Transmissions over Selective Channels”, IEEE Trans. Commun., Vol. 48, No. 9, pp. 1580-1589, September 2000. [73] S. Ohno, E. Manasseh, and M. Nakamoto, “Preamble and Pilot Symbol Design for Channel Estimation in OFDM Systems with Null Subcarriers”, EURASIP Journal on Wireless Communications and Networking 2011, No. 2, June 2011. [74] H. Hojatian, M. J. Omidi, H. Saeedi-Sourck, and A. Farhang, “Joint CFO and Channel Estimation in OFDM-based Massive MIMO Systems”, International Symposium on Telecommunications (IST), pp. 343-348, Tehran, Iran, September 2016. [75] Ly V. Nguyen, A. Lee Swindlehurst, and Duy H. N. Nguyena, “Linear and Deep Neural Network-based Receivers for Massive MIMO Systems with One-Bit ADCs”, IEEE Transactions on Wireless Communications, Early Access, pp. 1-14, May 2021. [76] H. W. Chan, W. C. Lee, K. L. Chiu, C. W. Jen, and S. J. Jou, “A Digital Two-Stage Phase Noise Compensation and rCFO/rSCO Tracking Module for mmW Single Carrier Systems”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Vol. 29, No. 5, pp. 904-914, May 2021. [77] P. Ciblat, P. Bianchi, and M. Ghogho, “Training Sequence Optimization for Joint Channel and Frequency Offset Estimation”, IEEE Transactions on Signal Processing, Vol. 56, No. 8, pp. 3424-3436, August 2008. [78] Y. F. Wang and Y. F. Chen, “Iterative Methods for Blind Carrier Frequency Offset Estimation in OFDMA Uplink”, EEE International Conference on Circuits and Systems for Communications (ICCSC), pp. 430-433, Shanghai, China, May 2008. [79] Y. T. Niu and Y. H. Shen, “Blind CFO Tracking in MIMO-OFDM Systems at Low SNR”, International Conference on Communications, Circuits and Systems (ICCCAS), pp. 273-277, Fujian, China, May 2008. [80] M. Morelli, “Timing and Frequency Synchronization for the Uplink of and OFDMA System”, IEEE Transactions on Communications, Vol. 52, No. 2, pp. 296-306, March 2004. [81] R. Stacey, “Proposed TGax draft specification”, IEEE 802.11-16/0024r1, pp. 1-159, 2016. [82] P. Stoica and A. Nehorai, “MUSIC, Maximum Likelihood, and Cramer-Rao Bound”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 37, No. 5, pp. 720-741, May 1989. [83] Y. Bresler and A. Macovski, “Exact Maximum Likelihood Parameter Estimation of Superimposed Exponential Signals in Noise”, IEEE Transactions on Acoustics, Speech, Signal Processing, Vol. 34, No. 5, pp. 1081-1089, October 1986. [84] R. Kumaresan and A. Shaw, “High Resolution Bearing Estimation without Eigen Decomposition”, Proceedings in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 576-579, Tampa, FL, USA, May 1985. [85] R. Kumaresan, L. Scharf, and A. Shaw, “An Algorithm for Pole-zero Modeling and Spectral Analysis”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 34, No. 3, pp. 637-640, June 1986. [86] D. Starer and A. Nehorai. “Maximum Likelihood Estimation of Exponential Signals in Noise using a Newton Algorithm”, Proceedings in 4th ASSP Workshop on Spectrum Estimation and Modeling, pp. 240-245, Minneapolis, MN, USA, August 1988. [87] M. Wax, “Detection and Estimation of Superimposed Signals”, Ph.D. dissertation, Stanford University, Stanford, CA, 1985. [88] K. C. Sharman, “Maximum Likelihood Parameter Estimation by Simulated Annealing”, Proceedings in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 2741-2744, New York, USA, April 1988. [89] M. Feder and E. Weinstein, “Parameter Estimation of Superimposed Signals using the EM Algorithm”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 36, No. 4, pp. 477-489, April 1988. [90] P. Stoica and K. C. Sharman, “Maximum Likelihood Methods for Direction-of-arrival Estimation”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 38, No. 7, pp. 1132-1143, July 1990. [91] P. Stoica and A. Nehorai, “MUSIC, Maximum Likelihood, and Cramer-Rao Bound Further Results and Comparisons”, IEEE Transactions on Acoustics, Speech, and Signal Processing, Vol. 38, No. 12, pp. 2140-2150, December 1990. [92] S. Haykin, Adaptive Filter Theorem., Pearson, Boston, Massachusetts, United States, 2014. [93] J. Miguez and L. Castedo, “Iterative Space-time Soft Detection in Time-varying Multiaccess Wireless Channels”, IEEE Signal Processing Workshop on Statistical Signal Processing (SSP), pp. 114-117, Singapore, August 2001. [94] C. C. Chen and Y. F. Chen, “Carrier Frequency Offset Estimation Under Interference Environments for OFDMA Uplink Systems”, in Proc. of 13th IEEE VTS Asia Pacific Wireless Communications Systems Conference (APWCS 2016), pp. 25-26, Tokyo, Japan, August 2016. [95] T. J. Shan, M. Wax, and T. Kailath, “On Spatial Smoothing for Direction-of-Arrival Estimation of Coherent Signals”, IEEE Trans. on Acoustics, Speech, and Signal Processing, Vol. 33, No. 4, pp. 806-811, August 1985. [96] Q. Zhang, L. Guo, C. Sun, X. An, and X. Chen, “Joint Power Control and Component Carrier Assignment Sschemein Heterogeneous Network with Carrier Aggregation”, IET Communications (Institution of Engineering & Technology), Vol. 8, No. 10, pp. 1831-1836, July 2014. [97] C. S. Bontu, J. Ghimire, and A. El-Keyi, “Optimum Resource Allocation in MU-MIMO OFDMA Wireless Systems”, 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring), pp. 1-5, Antwerp, Belgium, May 2020. [98] H. Sato and K. Nishimori, “Study on Simple Performance Evaluation for MU-MIMO-OFDMA”, 2020 International Symposium on Antennas and Propagation (ISAP), pp. 513-514, Osaka, Japan, January 2021. [99] S. Avallone, P. Imputato, G. Redieteab, C. Ghosh, and S. Roy, “Will OFDMA Improve the Performance of 802.11 WiFi Networks”, IEEE Wireless Communications, Early Access, pp. 1-8, June 2021. [100] R. Shrestha, R. Bajracharya, and S. Kim, “6G Enabled Unmanned Aerial Vehicle Traffic Management A Perspective”, IEEE Access, Vol. 9, pp. 91119-91136, June 2021. [101] S. KA. A. Yaklaf, K. S. Tarmissi, and N. A. A. Shashoa, “6G Mobile Communications Systems Requirements, Specifications, Challenges,Applications, and Technologies”, 2021 IEEE 1st International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, pp. 513-514, Tripoli, Libya, May 2021. [102] M. M. Aslam, J. Zhang, B. Qureshi, and Z. Ahmed, “Beyond6G- Consensus Traffic Management in CRN, Applications, Architecture and key Challenges”, 2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC)2021 IEEE 11th International Conference on Electronics Information and Emergency Communication (ICEIEC), pp. 182-185, Beijing, China, June 2021. [103] B. Hassan, S. Baig, and M. Asif, “Key Technologies for Ultra-Reliable and Low-Latency Communication in 6G”, IEEE Communications Standards Magazine, Vol. 5, No. 2, pp. 106-113, June 2021. [104] B. Ji, Y. Han, S. Liu, F. Tao, G. Zhang, Z. Fu, and C. Li, “Several Key Technologies for 6G Challenges and Opportunities”, IEEE Communications Standards Magazine, Vol. 5, No. 2, pp. 44-51, June 2021.
指導教授	陳永芳(Yung-Fang Chen)	審核日期	2021-7-12
推文	facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu
網路書籤	Google bookmarks   del.icio.us   hemidemi   myshare