大型天線陣列的多輸入都輸出系統和廣意空間位移調變被
廣泛的討論在近幾年之間，前者是應用大量的天線傳輸在無線
通訊上，而後者是將資訊儲存在天線上，根據不同的天線組合
表達不同的資訊。詳細地說，大型天線陣列改善了能量效益以
及傳輸率跟傳統的多輸入多輸出系統相比。而廣意空間位移調
變技術則減少了傳輸接收端的複雜度並增強的頻寬使用效率。
如今已有大量的研究關於廣意空間位移調變技術的硬式偵測方
法。在本篇論文中，我們專注於設計軟式偵測器應用於低密度
偶查核碼上, 我們亦設計了適用於偵測端與解碼端的低密度偶
查核碼, 並將之與最大事後機率偵測器進行比。
結果, 我們的錯誤率相當接進最大事後機率偵測法.

Massive MIMO systems and Generalized space shift keying(GSSK) mod-
ulation are studied in recently years. The former uses large scale antenna
arrays in wireless communication, and the latter encodes the information
onto the selection of antenna indices. In detail, massive MIMO improves
the energy eciency and throughput compared with traditional MIMO sys-
tems, and GSSK reduces the transceiver complexity and increases spectral
eciency in massive MIMO. There are amount of researches discussed the
hard-decision detections about GSSK. In this thesis, we present the soft-
decision detections with LDPC code. Also, we compare to MAP detection
with a tight performance loss. Finally, extrinsic information transfer(EXIT)
chart is applied to design the LDPC code with each detector. We also show
the simulation result and compare with the LDPC code in AWGN channel.

Abstract I
中文摘要I
1 Introduction 1
2 Preliminaries 4
2.1 Massive MIMO . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1.1 Introduction of Massive MIMO . . . . . . . . . . . . . 4
2.1.2 The Advantages of Massive MIMO . . . . . . . . . . . 4
2.2 Generalized Space Shift Keying in MIMO systems . . . . . . . 5
2.2.1 What are Spatial Modulation and Generalized Space
Shift Keying . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2.2 The Advantages come from Spatial Modulation to Gen-
eralized Space Shift Keying . . . . . . . . . . . . . . . 6
2.3 Review of Hard-Decision Detections . . . . . . . . . . . . . . 6
2.3.1 System Model and Notations . . . . . . . . . . . . . . 6
2.3.2 Maximum Likelihood Detector . . . . . . . . . . . . . . 7
2.3.3 Match Filter Based Detector . . . . . . . . . . . . . . . 7
2.3.4 Compressed Sensing Detector by Using Orthogonal Match-
ing Pursuit . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3.5 Greedy Column Search Detector . . . . . . . . . . . . 10
2.3.6 Simulation and complexity . . . . . . . . . . . . . . . . 10
3 Soft Detections for Generalized Space Shift Keying in Large Scale
MIMO 15
3.1 System Model and Notations . . . . . . . . . . . . . . . . . . . 15
3.2 Introduction to MAP detection . . . . . . . . . . . . . . . . . 16
3.3 Tree-Search and Shrunk Set (TSSS) Algorithm . . . . . . . . . 18
3.3.1 Main Algorithm . . . . . . . . . . . . . . . . . . . . . . 18
3.3.2 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.4 Compressed Sensing Based Soft Detector . . . . . . . . . . . . 21
3.4.1 Main Algorithm . . . . . . . . . . . . . . . . . . . . . . 21
3.4.2 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.5 Match Filter Based Soft Detector . . . . . . . . . . . . . . . . 25
3.5.1 Main Algorithm . . . . . . . . . . . . . . . . . . . . . . 25
3.5.2 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . 27
4 LDPC Code Design 31
4.1 Review of Design of Low-Density Parity-Check Codes for Mod-
ulation and Detection [5] . . . . . . . . . . . . . . . . . . . . . 31
4.2 Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
5 Conclusion 41
Bibliography 42

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