本文關(guān)鍵詞： 大規(guī)模MIMO 空間調(diào)制 子載波索引調(diào)制 空頻索引聯(lián)合調(diào)制 廣義近似消息傳遞　出處：《東南大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：大規(guī)模多輸入多輸出(Multiple-InputMultiple-Output,MIMO)技術(shù)通過增加基站側(cè)天線數(shù)目,能夠顯著提高系統(tǒng)頻譜效率和能量效率,是第五代移動通信系統(tǒng)(5thGenerationMobile Communication Systems,5G)的關(guān)鍵技術(shù)之一�？臻g調(diào)制(Spatial Modulation,SM)技術(shù)作為一種新型多天線傳輸技術(shù),只采用單一的射頻鏈路,避免了傳統(tǒng)MIMO系統(tǒng)中存在的干擾與同步問題,而且能夠在保證系統(tǒng)頻譜效率的同時提升能量效率。本論文從發(fā)送端數(shù)據(jù)傳輸?shù)膬?yōu)化設(shè)計和接收端低復(fù)雜度檢測兩個方面,對寬帶大規(guī)模MIMO系統(tǒng)空間調(diào)制相關(guān)技術(shù)展開研究。首先,研究了大規(guī)模MIMO空間調(diào)制技術(shù)。分別圍繞SM技術(shù)的調(diào)制原理、大規(guī)模MIMO SM系統(tǒng)模型、接收端檢測方法介紹了大規(guī)模MIMO SM系統(tǒng),并利用能量效率和誤比特率(Bit Error Ratio,BER)兩個性能指標對大規(guī)模MIMO SM系統(tǒng)與傳統(tǒng)大規(guī)模MIMO系統(tǒng)進行了比較,分析和仿真表明,在相等的頻譜效率下,大規(guī)模MIMOSM系統(tǒng)能夠?qū)崿F(xiàn)更高的能量效率和更優(yōu)的BER性能。此外,在BER性能和復(fù)雜度兩個方面針對大規(guī)模MIMO SM系統(tǒng)接收端幾種檢測方法進行了仿真與分析,并總結(jié)了各種檢測方法的優(yōu)缺點。接著,研究了大規(guī)模MIMO子載波索引調(diào)制(Subcarrier Index Modulation,SIM)正交頻分復(fù)用(Orthogonal Frequency Division Multiplexing,OFDM)技術(shù)。針對現(xiàn)有 SIM 技術(shù)頻譜浪費的問題,改進了發(fā)送端數(shù)據(jù)傳輸方法,并將其應(yīng)用到大規(guī)模MIMO OFDM系統(tǒng)中,建立了大規(guī)模MIMO SIM-OFDM系統(tǒng)模型,并提出了在理想信道狀態(tài)信息(Channel State Information,CSI)和存在信道估計誤差兩種場景下的廣義近似消息傳遞(Generalized Approximate Message Passing,GAMP)迭代檢測方法。通過理論分析和計算機仿真,在頻譜效率、能量效率、峰均功率比(Peak-to-Average Power Ratio,PAPR)以及BER性能方面評估了大規(guī)模MIMO SIM-OFDM系統(tǒng)性能,結(jié)果表明,改進的SIM-OFDM技術(shù)能夠在保證OFDM系統(tǒng)頻譜效率和BER性能的同時提升能量效率和PAPR性能。此外,仿真結(jié)果表明,相比于MMSE檢測方法,針對大規(guī)模MIMOSIM-OFDM系統(tǒng)兩種CSI場景下所提出的GAMP檢測方法均能夠以相對較低的復(fù)雜度實現(xiàn)更優(yōu)的性能。最后,研究了大規(guī)模MIMO空頻索引聯(lián)合調(diào)制(Space-Frequency Index Modulation,SFIM)技術(shù)。將SM技術(shù)與SIM-OFDM技術(shù)相結(jié)合,提出了一種SFIM的發(fā)射端數(shù)據(jù)傳輸方法,并將SFIM技術(shù)應(yīng)用到用戶端配置多天線的大規(guī)模MMO OFDM系統(tǒng)中,建立了大規(guī)模MIMO SFIM系統(tǒng)模型。在此基礎(chǔ)上,分別在理想的CSI和存在信道估計誤差兩種場景下,推導(dǎo)了適用于大規(guī)模MIMO SFIM系統(tǒng)的最小均方誤差(Minimum Mean Squared Error,MMSE)檢測方法和GAMP檢測方法。仿真結(jié)果表明,相比于大規(guī)模MIMO SM OFDM系統(tǒng),所提大規(guī)模MIMO SFIM系統(tǒng)能夠在不損失頻譜效率和BER性能的條件下,提升系統(tǒng)的能量效率。此外,在大規(guī)模MIMO SFIM系統(tǒng)中,相比于MMSE檢測方法,兩種CSI場景下所提出的GAMP檢測方法均能夠以相對較低的復(fù)雜度實現(xiàn)更優(yōu)的性能。
[Abstract]:Large-scale Multiple-Input Multiple-Output MIMO (Multiple-Input Multiple-Output Mimo) technology increases the number of base station side antennas. The spectrum efficiency and energy efficiency of the system can be improved significantly. Is the Fifth Generation Mobile Communication Systems. As a new type of multi-antenna transmission technology, spatial modulation technology only uses a single RF link. The problem of interference and synchronization in traditional MIMO system is avoided. And it can improve the energy efficiency while ensuring the spectrum efficiency. This thesis focuses on two aspects: the optimal design of data transmission at the transmitter and the low complexity detection at the receiver. The spatial modulation technology of wide-band large-scale MIMO system is studied. Firstly, the large-scale MIMO spatial modulation technology is studied. The large-scale MIMO SM system model and receiver detection method are introduced in this paper, and the energy efficiency and bit error rate (bit Error Ratio) are used to describe the large scale MIMO SM system. After comparing the large-scale MIMO SM system with the traditional large-scale MIMO system by two performance indexes, the analysis and simulation show that under the same spectral efficiency. Large scale MIMOSM systems can achieve higher energy efficiency and better BER performance. In the aspects of BER performance and complexity, several detection methods on the receiving end of large-scale MIMO SM system are simulated and analyzed, and the advantages and disadvantages of various detection methods are summarized. The large scale MIMO subcarrier index modulation (MIMO) subcarrier Index Modulation is studied. Simm orthogonal Frequency Division Multiplexing. OFDM (OFDM) technology. Aiming at the waste of spectrum of the existing SIM technology, the data transmission method of the transmitter is improved, and it is applied to the large-scale MIMO OFDM system. The large-scale MIMO SIM-OFDM system model is established, and the channel State Information is proposed in the ideal channel state information. Generalized Approximate Message Passing in two scenarios: CSI) and the presence of channel estimation errors. Through theoretical analysis and computer simulation, the spectrum efficiency, energy efficiency and peak-to-average Power Ratio are obtained. The performance of large scale MIMO SIM-OFDM system is evaluated in terms of PAPR and BER performance, and the results show that. The improved SIM-OFDM technology can improve the energy efficiency and PAPR performance while ensuring the spectrum efficiency and BER performance of the OFDM system. Compared with MMSE detection method. The proposed GAMP detection methods for two CSI scenarios in large-scale MIMOSIM-OFDM systems can achieve better performance with relatively low complexity. Finally. Space-Frequency Index Modulation (Space-Frequency Index Modulation) modulated by large scale MIMO space-frequency index is studied. SFIM technology. Combining SM technology with SIM-OFDM technology, a data transmission method of SFIM transmitter is proposed. The SFIM technology is applied to the large-scale MMO OFDM system with multiple antennas on the client side, and the large-scale MIMO SFIM system model is established. In two scenarios, ideal CSI and channel estimation error, respectively. The minimum mean square error and minimum Mean Squared Error for large-scale MIMO SFIM systems are derived. MMSE) detection method and GAMP detection method. The simulation results show that compared with the large-scale MIMO SM OFDM system. The proposed large-scale MIMO SFIM system can improve the energy efficiency of the system without losing spectrum efficiency and BER performance. In addition, in large-scale MIMO SFIM systems. Compared with MMSE detection methods, the proposed GAMP detection methods in both CSI scenarios can achieve better performance with relatively low complexity.
【學(xué)位授予單位】：東南大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN919.3

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