臺灣博碩士論文加值系統

In communication systems, the receiver down-converts the received signal and then samples the down-converted signal. The receiver uses the sampled signal to recover the transmitted signal. More information may be extracted if higher sampling rate is applied in the receiver. However, as the sampling rate increases, the power consumption and the manufacture cost also grows. Since the performance requirement of each user and the equipment cost that each user can afford is not quite the same, it is reasonable that there exist multi-level receivers in a multi-access communication system, where the receivers are distinguished by their sampling rate abilities.
In this dissertation, an orthogonal frequency division multiple access (OFDMA) cellular system with different sampling rate receivers is considered. Since the concerned OFDMA cellular system is different from the conventional one, where all receivers have the same sampling rate, some issues have to be studied further, such as soft handoff and subcarrier assignment.
First, a novel technique for diversity combining is proposed so that soft handoff can be realized for mobile stations (MSs) with different sampling rates in chapter 2. According to the available subcarriers in each cell, there may exist several appropriate choices of sampling rates for soft handoff. MSs with higher sampling rate are more flexible, and they can choose the lower appropriate sampling rate or the higher appropriate sampling rate. Lower sampling rate needs less power consumption but may cause little worse performance. Higher sampling rate needs more power consumption but accompanies with better performance.
Second, the same proposed technique in chapter 2 can be applied in many communication systems. The multi-band orthogonal frequency division multiplexing (MB-OFDM) ultra wideband (UWB) system is introduced in chapter 3 and the technique is adopted to enhance the system performance.
In literature, the subcarrier assignment problem is generally discussed with the assumption: the subcarrier channel gain (or called “channel state information (CSI)”) for every MS is available at base station (BS). However, the CSI feedback from MSs to BS causes system overhead. In addition, if MS mobility is large, the time variant channel causes the fed back CSI meaningless. Hence, subcarrier assignment problem is focused when BS does not have CSI form MSs in chapter 4. Three subcarrier assignment algorithms are proposed and discussed if MSs have different capabilities and CSI for MSs is not available at BS. A theoretical tool is provided so that the advantages and disadvantages among different subcarrier assignment algorithms can be explained.

Abstract I
Table of Content III
List of Figures V
CHAPTER 1 1
Introduction 1
CHAPTER 2 4
Diversity Combining Technique for Soft Handoff in OFDMA Cellular Systems 4
2.1 System and Channel Models 5
2.1.1 System Model 5
2.1.2 Channel Model 7
2.2 Diversity Combining Scheme for Soft Handoff 7
2.2.1 Diversity Combining 8
2.2.2 Soft Handoff Procedure 11
2.2.3 Appropriate and corresponding 11
2.2.4 Availability of Sampling Rate 23
2.3 System Performance 24
2.3.1 Analytical System Performance 26
2.3.2 Simulation Results 27
2.3.3 Non-ideal Factors Discussion 31
2.4 Conclusions 34
CHAPTER 3 36
Soft-Handoff Strategy for MB-OFDM Systems 36
3.1 System and Channel Models 36
3.1.1 Related MB-OFDM Specifications 37
3.1.2 System Model 38
3.1.3 Channel Models 40
3.2 MB-OFDM Soft Handoff Strategy 42
3.2.1 Diversity Combining 42
3.2.2 Receiving Schemes 43
3.2.3 Proposed Soft Handoff Strategy 46
3.3 System Performance and Simulation Results 47
3.3.1 Analytical Results 47
3.3.2 Simulation Results 51
3.4 Conclusions 56
CHAPTER 4 57
Subcarrier Assignment Algorithms in OFDMA Cellular Systems with Different Sampling Rate Receivers 57
4.1 System and Channel Models 58
4.1.1 System Model 58
4.1.2 Channel Model 61
4.2 Proposed Subcarrier Assignment Algorithms 62
4.2.1 Random Assignment (RA) Algorithm 63
4.2.2 High Level Grouping Assignment (HLGA) Algorithm 65
4.2.3 High Level Insertion Assignment (HLIA) Algorithm 67
4.3 System Performance 69
4.3.1 Analytical System Performance 69
4.3.2 Simulation Results 73
4.4 Conclusions 77
CHAPTER 5 79
Conclusions 79
References 80

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