在下世代行動通訊(又稱為第五代行動通訊，5G)的標準中，延伸使用更高頻率的毫米波(Millimeter Wave, mmWave)頻段已成為無線通訊的新興研發趨勢。然而毫米波訊號相較微波頻段有著更高的路徑損失與訊號衰減率等問題，為了解決這樣的困境，高頻譜效益的大規模多天線列陣系統技術被引入，大量的天線單元提供了大量的多天線增益，並提供波束成形技術發展的機會。然而，傳統多輸入多輸出天線系統的傳輸模式較為僵硬且缺乏靈活性，無法因應新世代通訊多樣化的需求，如節能、高傳輸速率和快速移動等特性。索引調變是近年來受矚目的多天線技術，相比傳統多天線系統的傳輸模式，其具有高能源效率以及高靈活度的特色，目前分為兩種主流的研究方向：空間調變技術以及正交分頻多工索引調變。
在本篇論文中，我們結合了包括空間調變、波束成形和大規模多天線系統等技術特色，提出了「波束索引空間調變」技術。此技術解決了空間調變不相容於正交分頻多工系統的困境，並消除了其在傳輸速率上的限制；與正交分頻多工索引調變技術相比，此技術也充分運用了多天線系統通道中的自由度，並擁有較佳的頻譜效率。我們的研究成果顯示，相較於傳統的多輸入多輸出波束成形天線系統，此技術在不同的通道模型中，皆可以達到更高的能量效率(每單位能量單位頻寬可傳的位元率)，同時在中低傳輸速率和使用較低調變階數時，能保有較好的頻譜效率(每單位頻寬可傳的位元率)。此技術也提供更彈性的設計，讓使用者針對其需求以及當前的通道環境，選擇最適用的系統配置。此外，我們也考量了實際的應用情況，將此技術拓展於多使用者的情況，並結合了混合式波束成形技術來降低系統之複雜度。透過我們的分析以及模擬結果，發現提出的波束索引空間調變技術可以良好的套用在上述的情境下，並且保有其高於傳統多天線波束成形技術的優勢，這意味著此波束索引空間調變方案可能成為下世代無線通訊系統的潛力技術之一。

For the next generation of wireless communication systems, also known as 5th Generation (5G), the attractive spectrum named millimeter wave (mmWave) channel will be explored. The mmWave channel has higher continuous frequency spectrum ranging but suffers from large path loss and limited scattering environment. In order to confront the above shortcomings, the technology of beamforming and massive Multi-Input Multi-Output (MIMO) becomes a potential solution in the 5G wireless systems. However, the transmission strategy of classical MIMO technology is fixed and stiff that cannot provide the flexibility between several application features and requirements. In the recent years, the Index Modulation (IM), which is applied in the dimension of antennas, called spatial modulation (SM), and in the dimension of subcarriers, called orthogonal frequency division multiplexing-index modulation (OFDM-IM), has been studied. The IM technology effectively improves the energy efficiency in the multi-antenna or multicarrier communication systems and can flexibly adjust the system parameters for application demands.
We combine the features of SM technique, beamforming technology and conventional MIMO system to propose the design of IM technique in the dimension of eigen-beam named as “Beam-Index Spatial Modulation (BISM)”. The BISM scheme responses the issues of both SM and OFDM-IM and keeps the merits of the index modulation, such as flexibility and energy efficiency. Comparing to the SM scheme, BISM is compatible to the OFDM communication system and the index modulation can be implemented in the baseband at symbol rate as fast as the sampling speed. Comparing to the OFDM-IM scheme, BISM exploits the degrees-of-freedom of the MIMO channels and the spectral efficiency can be improved further.
Our analysis and simulation results show that compared to the conventional MIMO with beamforming technology (MIMO BF), BISM has higher energy efficiency and simultaneously retains advantages of spectral efficiency at low, medium transmission rate and low modulation order over different channels. The BISM scheme also provides the flexibility for selecting suitable configuration based on user requirements and channel environment. For practical considerations and reducing complexity, we extend BISM to multi-user system and hybrid beamforming architecture. Our results show that BISM can maintain its edge for these scenarios and can be applied to the specific application and mainstream researches of 5G, which means the proposed BISM is a potential technology for the next generation of wireless communication systems.

CHAPTER 1 INTRODUCTION 1
1.1 Foreword 1
1.2 Research Motivation and Objective 3
1.3 Thesis Organization 5
CHAPTER 2 BACKGROUNDS 6
2.1 Massive MIMO 6
2.2 Spatial Modulation (SM) 7
2.3 Generalized Spatial Modulation (G-SM) 8
2.4 OFDM-Index Modulation (OFDM-IM) 10
2.5 Hybrid Beamforming (HBF) 12
CHAPTER 3 PROPOSED BEAM-INDEX SPATIAL MODULATION 13
3.1 System Model 13
3.1.1 Rayleigh Fading Channel 14
3.1.2 Extended Saleh-Valenzuela Model 14
3.2 Single-user Beam-Index Spatial Modulation (SU-BISM) 16
3.2.1 BISM Modulator 17
3.2.2 BISM Detector with Maximum-Likelihood 19
3.2.3 Efficiency Analysis 21
3.2.4 Performance Analysis 28
3.3 Multi-user Beam-Index Spatial Modulation (MU-BISM) 31
3.3.1 System Description 31
3.3.2 Multi-user Precoder Design 32
3.3.3 Capacity Analysis 33
3.4 BISM with Hybrid Beamforming (HBF) Technology 34
3.4.1 System Description 35
3.4.2 Spatially Hybrid Precoder and Combiner Design 36
3.4.3 Capacity Analysis 40
CHAPTER 4 SIMULATION RESULTS 42
4.1 Single-user BISM (SU-BISM) 42
4.1.1 Ergodic Capacity Performance 42
4.1.2 Bit Error Rate (BER) Performance 46
4.2 Multi-user BISM (MU-BISM) 52
4.2.1 Ergodic Capacity Performance 52
4.2.2 Bit Error Rate (BER) Performance 54
4.3 BISM with Hybrid Beamforming (HBF) Technology 57
CHAPTER 5 CONCLUSIONS 61

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