本論文共分為三大部分四個章節來先後討論前瞻無線寬頻系統之效能評估及研析的研究。論文之先期研究利用基因演算法分來處理多使用者在封包排程之問題，進而將問題擴展至WiMAX IEEE 802.16e上之Subchannelization排程問題，最後針對不同的情境來評估及分析次世代行動通信系統並探討該如何提升效能、如何獲得更好的品質之方向來設計及撰寫一套系統評估系統，並利用此套評估系統來評估分析前瞻無線寬頻系統之效能。
    第一個部份：在多個頻道的網路下，封包排程(Packet Scheduling)的最佳化是一需要解決的問題，如何把多個頻道上的不同封包，密集的安排到有限且較少的頻道上，這一類有多種組合且困難的排序問題我們統稱為NP-hard問題。
    基因演算法(Genetic Algorithm)是一種模仿自然界生物演進的方式而成的演算法，其中多點搜尋以及適者生存的特性，可以幫助我們快速且有效的解決NP-hard的問題，利用這樣特別的演算法來趨近找到優秀的答案，因此在本論文中，將基因演算法的架構上提出一種改良及可實現的硬體架構，利用這樣的架構可以在提升封包排程當中找到最佳化排程的速度，更進一步的靠著實現此架構來應用在光纖通訊網路上之DWDM (Dense Wavelength Division Multiplexing)技術。
    第二部份：接續第一部分，我們提出另一種的基因演算法之架構，並應用在WiMAX (IEEE 802.16e) 上之Fast Fourier Transform subchannelization scheduling (FFTSS) 的排程解決方案。此解決方案在於能快速的收斂出在多使用者傳輸的狀況下其下傳鏈路次訊框的最短傳輸時間排列方式。論文中提出已改良及可實現的基因演算法硬體架構，利用這樣的硬體架構來實現在多使用者之傳輸狀況下，下傳鏈路次訊框的最短傳輸時間之排列方式及提升其傳輸的效能與降低所花費的成本。並將基因演算法硬體實現在FPGA上以實際驗證其收歛的結果。
    第三個部份：此部份針對分析的情境不同來評估及分析次世代行動通信系統，並探討該如何提升效能、如何獲得更好的品質，這些都是目前各無線通訊大廠以及電信營運商所希望可以達到的目標，這樣的一個目標效益已經不能只單單使用資訊排程的方式來處理，所需要的是一套包含整體模擬分析之模擬系統來分析及評估。
    由於需要模擬系統來分析及評估，故本論文整合了規格書(Standard)中所提及之模組(1.流量模型, 2.Link budget, 3.通道模型)來進行本部份之重要分析及評估並使用Matlab軟體之人機介面來設計及撰寫一套系統評估系統。評估系統中利用Traffic Model來亂數產生基地台在傳輸情況下可能之網路使用者流量，並使用基地台中的參數列表來做鏈路估算(Link Budget)，之後透過多種不同的Channel Model (包含 Urban Macrocell, Suburban Macrocell, Urban Microcell …等等)，來評估所有可能的環境及分析基地台的訊號涵蓋範圍並模擬計算出使用者在不同的情境(室外、室內、不同室內環境)及距離下所可能獲得的調變及Throughput，最後也提出為解決在室內的訊號涵蓋不足的問題，在假設加裝Repeater之設備情況下來分析此時之室內訊號涵蓋品質的評估及分析。

In this thesis it consists of three parts with four chapters to consider the system performance evaluation and system development of the advanced broadband wireless communication system. We first use the Genetic Algorithm (GA) to solve and manage packets scheduling problem for multi-users system. Then, the algorithm is extended to solve the sub-channelization scheduling issue in the WiMAX IEEE802.16e. Finally, we evaluate and analyze the system performance of the next generation mobile communication system under various transmission environments and to design a system performance evaluation guide from the consideration of how to improve the system performance and how to get better transmission quality;  it then utilizes this guide to evaluate and analyze the system performance of the next generation wireless communication system.
    In part one, a common design issue in the transmission of packets through a network with multiple channels is how to optimally design a packets scheduling algorithm. In the packets scheduling it tries to rearrange the packets that are generated from multiple channels and reassemble them into the finite and less available output channels. This is generally classified as an NP-hard problem.
    The Genetic Algorithm (GA) is one of the most efficient ways to solve NP-hard scheduling problem. It endeavors to find a suitable solution to our problem through multiple processors by applying GA characteristic to search for the fittest survivor. Modified and feasible hardware architecture of GA is presented in this part. By utilizing this kind of architecture it not only increases the processing speed in the search of optimal packets scheduling but also utilizes this technique to enhance the efficiency of DWDM (Dense Wavelength Division Multiplexing) in optical fiber communication networks.
    In part two, we continue the consideration of the technique as stated in part one by proposing a method of using a heuristic Genetic Algorithm (GA) to solve the Fast Fourier Transform sub-channelization scheduling (FFTSS) problem in WiMAX (IEEE 802.16e) broadband wireless access system. By utilizing this algorithm it can in the shortest time interval to quickly search and find the optimal scheduling of sub-frames in the transmission of the multi-user information through the channel. Modified and feasible GA-based hardware architecture is then proposed in the search for the best configurations of the uplink and/or downlink sub-frames so as to obtain the optimal system throughput as well as to maintain the quality of services. The hardware architecture is finally realized through Field-Programmable Gate-Array (FPGA) to verify the convergence and performance of the designed algorithm.
    In part three, system performances under various transmission environments for next generation mobile communications system are evaluated and analyzed; it also investigates the methodology of how to improve the performance and get better quality of service; these are the main tasks that the current wireless communication companies and system service providers currently emphasize on. These tasks can not be achieved by simply utilizing the conventional GA scheduling algorithm a complete and novel system simulation tool to simulate and analyze the whole system behavior and performance is required. 
    In the development of system simulation tool we integrate the modules as depicted in the IEEE 802.16m standard, such as the traffic flow module, the link budget module and the channel model module, to perform the system analysis and performance evaluation. It also utilizes the main-machine interface of MATLAB software to design and prepare a system evaluation system. In this evaluation system it randomly generates the traffic flows, following the statistical distributions as stated in the 802.16m standard, at the base station at any time instant and then the traffics are transmitted through various channel models to simulate the various RF transmission environments, either indoor or outdoor, and then utilizes the link budget formulas and system parameters to evaluate the system coverage area, system throughput and other system performance characteristics. Finally in the thesis it also proposes several methods to solve the problem of insufficient RF coverage encountered in the indoor receiving; it then evaluates the possible system performance improvement when a repeater is added in the outdoor-indoor transmission.

TABLE OF CONTENTS

CHINESE ABSTRACT	I
ENGLISH ABSTRACT	III
TABLE OF CONTENTS	V
LIST OF FIGURES	VIII
LIST OF TABLES	X
CHAPTER 1	INTRODUCTION	1
1.1	Study Motivation	1
1.1.1	Review the Hardware Genetic Algorithm	2
1.1.2	Review the Implementation of Subchannelization Scheduler	3
1.1.3	Software Simulation Tool for the Capacity Analysis of WiMAX Base Stations	5
1.1.4	System Performance Evaluation for Advanced Broadband Wireless Communication System	6
1.2	Organization	7
CHAPTER 2	HARDWARE IMPLEMENTATION OF GENETIC ALGORITHM IN OPTIMAL PACKET SCHEDULING	11
2.1	Introduction	11
2.2	Application of GA for Optimal Packet Scheduling	12
2.2.1	Optimization of Packet Scheduling	12
2.2.2	Application of GA	14
2.2.3	MATLAB Simulation	16
2.3	Hardware Architecture	18
2.3.1	Main Architecture	18
2.3.2	Genetic Crossover and Mutation Unit	19
2.3.3	Selection Unit	20
2.3.4	Collector Unit	22
2.3.5	Random Generator Unit	23
2.3.6	Register Allocation Unit	23
CHAPTER 3	SUBCHANNEL SCHEDULING IN IEEE 802.16 BROADBAND WIRELESS ACCESS SYSTEMS	25
3.1	Introduction	25
3.2	Scheduler Architecture Design	26
3.2.1	Subscriber Station Source Data	26
3.2.2	Design FFTSS by Using a Genetic Algorithm	29
3.2.2.1	Chromosomes of Parent Generation	30
3.2.2.2	Crossover and Mutation	33
3.3	Analysis and Implementation FFTSS	36
3.3.1	Analysis of FFTSS	36
3.3.2	Implementation of FFTSS	38
3.4	Simulation Results	40
3.4.1	Hardware Architecture of FFTSS	40
3.4.2	Co-simulation of FFTSS	42
CHAPTER 4	CAPACITY ANALYSIS OF WIMAX BASE STATIONS	46
4.1	Introduction	46
4.2	WiMAX Traffic Model	47
4.2.1	VoIP Model	47
4.2.2	Video Streaming	48
4.2.3	FTP	49
4.2.4	HTTP	50
4.3	Chanel Path Loss Model	51
4.3.1	COST-231 Model	51
4.3.2	SUI Model	52
4.4	Link Budget	53
4.5	The Software Design for the Simulation and Analysis of WiMAX Base Station Capacity	56
4.6	Calibration Analysis	58

CHAPTER 5	SYSTEM PERFORMANCE EVALUATION FOR WIRELESS COMMUNICATION SYSTEM	63
5.1	Introduction	63
5.2	Channel Model Description	64
5.2.1	Urban Macrocell	65
5.2.2	Suburban Macrocell	65
5.2.3	Urban Microcell	65
5.2.4	Indoor Small Office	66
5.2.5	Indoor Hot Spot	66
5.2.6	Outdoor to indoor	66
5.2.7	Shadowing factor	67
5.3	Performance Evaluation System Architecture Distribution	68
5.3.1	System Link Budget	68
5.3.2	Steps or procedures in the Link Budget calculation	72
5.3.3	Calculation the SNR and Distance and PER	74
5.4	System Performance	77
5.4.1	Fist Case: Signal Coverage Range of Ideal Base Station	77
5.4.2	Second Case: Signal Coverage Range Model of Near Real Base Station	79
5.4.3	Third Case: Repeater is included	82
CHAPTER 6	CONCLUSIONS AND FUTURE WORKS	86
REFERENCES	91

 
LIST OF FIGURES

Figure 1-1   The Organization of Chapter Dissertation	7
Figure 1-2   The Organization of Architectures Dissertation	8
Figure 2-1   First example of packet scheduling	14
Figure 2-2   Second example of packet scheduling	14
Figure 2-3   Schematic diagram of the conventional architecture in the implementation of genetic algorithm	17
Figure 2-4   Simulation result of packet scheduling using MATLAB software	17
Figure 2-5   Main hardware architecture	19
Figure 2-6   Architecture of crossover hardware	21
Figure 2-7   Architecture of mutation hardware	22
Figure 2-8   Architecture of random number generator	23
Figure 3-1   Functional Block Diagrams for Design and Simulation	30
Figure 3-2   Illustration of the Representation of a Chromosome	32
Figure 3-3   Illustration of Crossover (a) Before Crossover (b) After Crossover	34
Figure 3-4   Illustration of Mutation	35
Figure 3-5   Relationship between Users and Generations	37
Figure 3-6   Hardware Architecture for Implementing Genetic Algorithm	39
Figure 3-7   ALTERA Stratix EP1S80 DSP Development Board	41
Figure 3-8   Timing Sequence Diagrams for Processing 20 Users	41
Figure 3-9   Simulation Platform	44
Figure 3-10  Actual Simulation Platform	44
Figure 3-11  Percentages of Packages Served	45
Figure 4-1   Typical Phone Conversation Profile	48
Figure 4-2   Video Streaming Traffic Model	49
Figure 4-3   FTP Traffic Patterns	49
Figure 4-4   HTTP Traffic Pattern	50
Figure 4-5   GUI of the Software for the Simulation and Analysis of WiMAX Base Station Capacity	56
Figure 4-6   The Functional Block Diagram in the Optimizing Operation of	59
Figure 4-7   Transmission Efficiency Before Calibration (16 QAM)	60
Figure 4-8   RSSI vs. CINR	61
Figure 4-9   Throughput vs. CINR	61
Figure 4-10  The Transmission Efficiency after Calibration (16 QAM)	62
Figure 4-11  Report Profile of the Simulation Result	62
Figure 5-1   Transmitter and Receiver Channel Model	64
Figure 5-2   Performance Evaluation System Architecture	69
Figure 5-3   Receiver SNR vs. Distance (Channel Model: Urban Macrocell)	75
Figure 5-4   MS received PER vs. Distance (Channel Model: Urban Macrocell)	76
Figure 5-5   Signal Coverage Range Model for The Ideal Base Station	78
Figure 5-6   First Case Performance Evaluation Result	79
Figure 5-7   Signal Coverage Range Model of The Near Real Base Station	80
Figure 5-8   The Path Loss vs. Distance of The Second Model	80
Figure 5-9   Evaluated System Performance of the Second Case	81
Figure 5-10  Evaluated System Performance of the Second Case	81
Figure 5-11  Signal Coverage Range Model of a Repeater	83
Figure 5-12  The fundamental characteristics of a sample repeater	84
Figure 5-13  Third Case Performance Evaluation Result	84
Figure 5-14  Third Case Performance Evaluation Result	85
Figure 6-1   The Organization of Future Works	90

 
LIST OF TABLES

Table 2-1  Register allocation	24
Table 3-1  Link Parameters	28
Table 3-2  Maximum Number of Users in Different Transmission Conditions	29
Table 3-3  User’s Amount of Information and Their Corresponding Number of Symbols	31
Table 3-4  Sub-Channel Assignments for Users, from sub-channel 1 to sub-channel 8, Based on the Outcomes of Random Number Generator	33
Table 3-5  Convergent Rates in Various Generations (%)	38
Table 3-6  Hardware Synthesized and Simulation Results	42
Table 3-7  Convergent Time and the Number of Symbols Transmitted	42
Table 3-8  Simulated Transmission Results between the Ideal and FFTSS Hardware System	42
Table 4-1  VoIP Traffic Model Parameters Specification	47
Table 4-2  Near Real Time Video Streaming Traffic Model Parameters	48
Table 4-3  FTP Traffic Parameters	49
Table 4-4  HTTP Traffic Parameters	50
Table 4-5  Environment Parameters	53
Table 4-6  Link Budget Template	54
Table 4-7  WiMAX Field Trial Data at Fixed Location	60
Table 5-1  Standard deviation of shadow fading distribution	67
Table 5-2  Link Budget Template	70
Table 5-3  PER Simulation Parameter	76
Table 5-4  The Simulation Parameters	77
Table 5-5  The Threshold Parameter with the Modulation Relation	78

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