因為今天四通八達的無線通信網絡對高速高質量通信的要求,加之無線通信資源的稀缺,使得資源分配在無線通信領域的地位越發的重要.多種多樣的無線通信資源和不同的設計要永使得資源分配問題變得很複雜,我們也很難找到一個通用的方法去解決所有的資源分配問題.在本文中, 我們研究一些典型的資源分配問題,通過最優化設計,給出恰當的高效的算法予以解決.本文中將會涉及集中化算法和分佈式算法。 / 在本文中, 我們首先研究協作通信中的功率分配和中繼選擇問題。這個問題因為其問題的組合性而變得很複雜。為了保證系統的性能並且同時避免過量的冗餘信息, 我們提出了一個新的概念"中繼選擇自由度"。更重要的是, 為了使我們的方法能夠適用於集中信息很難的大型通信系統, 我們提出了分佈式的解決方案。該方法在實際中可以比較簡單的實現。 / 我們接著研究多用戶接入網絡的"軟"服務質量控制問題。我們這裡考慮的情形是:用戶們有各自的服務質量要求, 比如有一個目標速率。因為系統的資源總是有限的, 如果有過多用戶, 那麼同時滿足所有用戶的服務質量要求有時候是不可能的。我們的目標是在這種情況發生的時候,優化整個系統的資源分配。我們提出了分佈式算法來解決這一個問題。 / 最後, 我們研究下行鏈中的波束成形問題。這裡我們出於實際情況考慮,系統中存在兩種用戶:優先用戶和非優先用戶。我們想要盡可能最大化的提升非優先用戶的性能,同時必須首先滿足優先用戶的服務質量用要求。我們這裡用不同的波束成形向量來完成這個任務。這個問題是NP問題,我們做了必要的一些放鬆處理來得到有效的較優的解。 / Due to the limited resources and high performance requirements in today’s wireless networks, optimization methods in resource allocation play a significant role in reaping the benefits from wireless communications. Various available resources and different design goals make the resource allocation problem complex and we are unlikely to find a generic approach for all problems. Thus in this thesis, we investigate several resource allocation problems and propose the proper optimization methods and algorithms that can efficiently give us desired solutions. Also, both centralized and distributed methods will be shown in this thesis. / We first study the joint power allocation and relay selection problem in cooperative communication. This problem is complex due to its combinatorial nature. In order to avoid high information overhead and system complexity while at the same time maintain system performance, we introduce a new concept called “relay selection degree bound“. Moreover, since in large scale cooperative communication network, collecting information and centralized control would be very difficult, we resort to distributed algorithms that can be easily implemented in practice. / We further consider the soft QoS control problem in multiple access network. Here we consider the situation where the users have quality of service(QoS) requirements, i.e., each user has a target rate for its application. Since the resources in the system are limited, these requirements will result in the infeasibility of the whole system if there are too many users. We aim at optimizing the performance of the whole system while this kind of infeasibility happens. We will see how distributed algorithms can work for this problem and give us desired results. / We finally consider the downlink beamforming problem where there are two kind of users in the system: priority users and non-priority users. We maximize the non-priority users performance while at the same time satisfying the priority users’ QoS requirements first. Here we adopt heterogeneous beamforming scheme to complete the task. Since the problem is NP hard, relaxation is done for efficient solutions. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Fang, Haoran. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 76-81). / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Background --- p.3 / Chapter 1.2.1 --- Wireless Communication Schemes --- p.3 / Chapter 1.2.2 --- Mathematical Preliminaries --- p.9 / Chapter 1.3 --- Outline of the Thesis --- p.11 / Chapter 2 --- Resource Allocation for Cooperative Communication Networks --- p.13 / Chapter 2.1 --- Chapter Introduction --- p.13 / Chapter 2.2 --- system model and problem formulation --- p.16 / Chapter 2.3 --- optimal power allocation scheme for arbitrary configuration --- p.20 / Chapter 2.4 --- Relay selection in the MAC layer --- p.24 / Chapter 2.4.1 --- Algorithm Design --- p.24 / Chapter 2.4.2 --- Distributed Implementation of The Relay Selection Algorithm --- p.29 / Chapter 2.5 --- Numerical Results --- p.33 / Chapter 2.5.1 --- The Convergence of Distributed Power Allocation Algorithm --- p.33 / Chapter 2.5.2 --- Performance of The Overall Cross Layer Solution --- p.34 / Chapter 2.5.3 --- Improvements of Heuristic Markov algorithm --- p.36 / Chapter 2.6 --- Chapter Conclusions --- p.38 / Chapter 3 --- Soft QoS Control in Multiple Access Network --- p.39 / Chapter 3.1 --- Introduction --- p.39 / Chapter 3.2 --- system model --- p.41 / Chapter 3.3 --- Feasibility check and soft QoS control --- p.43 / Chapter 3.3.1 --- Feasibility Check --- p.43 / Chapter 3.3.2 --- Soft QoS Control --- p.45 / Chapter 3.3.3 --- Distributed Soft QoS Control --- p.47 / Chapter 3.3.4 --- Numerical Results --- p.53 / Chapter 3.4 --- Chapter Conclusion --- p.57 / Chapter 4 --- Heterogeneous resource allocation via downlink beamforming --- p.58 / Chapter 4.1 --- Introduction --- p.58 / Chapter 4.2 --- system model --- p.60 / Chapter 4.3 --- heterogeneous resource allocation via beamforming --- p.62 / Chapter 4.3.1 --- Relaxation and problem analysis --- p.62 / Chapter 4.3.2 --- Randomization for final solutions --- p.66 / Chapter 4.4 --- Numerical Results --- p.69 / Chapter 4.5 --- Conclusion --- p.70 / Chapter 5 --- Conclusions and Future Work --- p.73 / Chapter 5.1 --- Conclusions --- p.73 / Chapter 5.2 --- Future Work --- p.74 / Bibliography --- p.76
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_328640 |
| Date | January 2012 |
| Contributors | Fang, Haoran., Chinese University of Hong Kong Graduate School. Division of Information Engineering. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, bibliography |
| Format | electronic resource, electronic resource, remote, 1 online resource (x, 81 leaves) : ill. (some col.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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