No description available.

Yeung Man Chun. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 84-86). / Abstracts in English and Chinese. / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Graph Theory --- p.5 / Chapter 1.2 --- Classical Routing Algorithms --- p.10 / Chapter 1.2.1 --- Proactive Routing Algorithms --- p.11 / Chapter 1.2.2 --- Reactive Routing Algorithms --- p.13 / Chapter 1.3 --- Wireless Ad Hoc Routing Algorithms --- p.15 / Chapter 1.5 --- Organization of the Thesis --- p.17 / Chapter Chapter 2 --- General Routing Algorithm --- p.18 / Chapter 2.1 --- Pre-routing Cost and On-routing Cost --- p.18 / Chapter 2.2 --- Rewritten Bellman-Ford Algorithm --- p.20 / Chapter 2.3 --- A Hybrid Algorithm --- p.22 / Chapter 2.4 --- Routable Condition --- p.33 / Chapter 2.5 --- A Better Algorithm? --- p.43 / Chapter Chapter 3 --- Clique Routing Algorithm --- p.45 / Chapter 3.1 --- Clique Process --- p.45 / Chapter 3.2 --- Property --- p.49 / Chapter 3.3 --- Decentralized Construction of the Clique Process --- p.55 / Chapter 3.4 --- Construction of a Clique Process Based GRA --- p.61 / Chapter 3.5 --- Other Alternatives --- p.68 / Chapter Chapter 4 --- Simulations and Results --- p.70 / Chapter 4.1 --- Models and Assumptions --- p.70 / Chapter 4.2 --- Results --- p.72 / Chapter 4.2.1 --- Pre-routing Cost --- p.73 / Chapter 4.2.2 --- On-routing Cost --- p.76 / Chapter 4.2.3 --- Reliability --- p.77 / Chapter Chpater 5 --- Conclusions --- p.80 / References --- p.84

Cheung Cheuk Lun. / Thesis submitted in: July 2004. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 109). / Abstracts in English and Chinese. / Abstract --- p.1 / Chapter 1 --- Introduction --- p.3 / Chapter 1.1 --- Differentiation from existing products --- p.6 / Chapter 1.2 --- Problems --- p.6 / Chapter 1.3 --- Assumption --- p.9 / Chapter 2 --- Study of bulk transfer --- p.10 / Chapter 2.1 --- Simple wireless solution --- p.10 / Chapter 2.2 --- Problems of the simple wireless solution --- p.10 / Chapter 2.2.1 --- Low performance due to header overhead --- p.12 / Chapter 2.2.2 --- Low performance due to unnecessary packets --- p.12 / Chapter 2.2.3 --- Model derivation --- p.12 / Chapter 2.2.4 --- Performance study --- p.17 / Chapter 2.3 --- Packed wireless solution --- p.19 / Chapter 2.3.1 --- Example --- p.19 / Chapter 2.3.2 --- Solved problems --- p.21 / Chapter 2.3.3 --- Model derivation --- p.22 / Chapter 2.3.4 --- Performance study --- p.24 / Chapter 2.3.4 --- Performance study on the effect of the value of n --- p.25 / Chapter 2.4 --- Controllable packed wireless solution --- p.27 / Chapter 2.4.1 --- Problem --- p.27 / Chapter 2.4.2 --- Analysis --- p.27 / Chapter 2.4.3 --- Solution --- p.29 / Chapter 2.4.4 --- Model derivation --- p.33 / Chapter 2.4.5 --- Performance study --- p.35 / Chapter 2.4.6 --- Performance study on the effect of the sliding window size --- p.36 / Chapter 2.5 --- Summary of performance study --- p.41 / Chapter 2.5.1 --- Comparison of the throughput between four cases --- p.41 / Chapter 2.5.2 --- Study of how the throughput-varies with the processing time --- p.44 / Chapter 2.6 --- Simulation --- p.47 / Chapter 2.6.1 --- Measuring the packet loss rate and the throughput --- p.49 / Chapter 2.6.2 --- Studying the throughput against the distance --- p.50 / Chapter 2.6.3 --- Studying the throughput against the packet loss rate --- p.53 / Chapter 2.7 --- Conclusion --- p.54 / Chapter 3 --- Study of interrupt transfer --- p.55 / Chapter 3.1 --- Problem --- p.55 / Chapter 3.2 --- Solution --- p.56 / Chapter 3.2.1 --- Remote polling --- p.56 / Chapter 3.3 --- Feasibility of the solution --- p.58 / Chapter 3.4 --- The problem of Distributed Coordination Function collision --- p.60 / Chapter 3.5 --- Collision avoidance --- p.60 / Chapter 3.6 --- Model derivation --- p.61 / Chapter 3.6.1 --- Wired case --- p.61 / Chapter 3.6.2 --- Wireless solution (remote polling) --- p.62 / Chapter 3.7 --- Maximum allowed request generation frequency --- p.64 / Chapter 3.7.1 --- More than one interrupt transfer --- p.64 / Chapter 3.7.2 --- More than one bulk transfer --- p.64 / Chapter 3.7.3 --- Maximum allowed request generation frequency --- p.65 / Chapter 3.8 --- Conclusion --- p.65 / Chapter 4 --- System architecture issues --- p.66 / Chapter 4.1 --- USB network --- p.66 / Chapter 4.1.1 --- Problems --- p.66 / Chapter 4.1.2 --- Solution --- p.66 / Chapter 4.1.3 --- Conclusion --- p.69 / Chapter 4.2 --- Security --- p.70 / Chapter 4.2.1 --- Suggested solution --- p.70 / Chapter 4.2.2 --- Conclusion --- p.72 / Chapter 4.3 --- Cost --- p.72 / Chapter 4.4 --- Power supply --- p.73 / Chapter 5 --- Conclusion --- p.75 / Appendix --- p.77 / Chapter A. --- Wireless USB (WUSB) --- p.77 / Chapter B. --- Introduction of USB --- p.83 / Chapter C. --- Framing details of 802.11 --- p.99 / Chapter D. --- A case study of a USB device --- p.102 / Chapter E. --- Reference of notations used in figures --- p.106 / Chapter F. --- Values of all symbols --- p.107 / Reference i --- p.109

對於無線網絡運營商來說，聯合優化其經濟和技術方面的決策以獲得商業成功正在變得越來越重要。一個運營商的決策可能包括對技術的選取和部署時間的把握、資源投資的數量，以及針對他所提供的服務的定價。考慮到這些決策彼此之間有關聯，我們需要對這些決策進行聯合優化，特別當運營商面對有限的資源、不成熟的技術和市場競爭時，該優化會變得困難。本論文綜合考慮兩類網絡中的這些因素。注意到在所有絨線技術中蜂窩網絡擁有最廣泛的市場佔有率，我們先研究蜂窩網路中的經濟學。然後我們研究認知無線電中的經濟學，考慮到該技術代表了未來無線技術發展的一個主要趨勢。 / 在本論文的第一部分，我們研究一個蜂窩網絡運營商在經濟和技術方面的決策，涉及到網路升級、服務分類和社交應用。首先，我們提出了一套博弈論模型來研究互相競爭的運營商從目前3G 蜂窩技術升級為未來一代(4G) 技術的部署時間。我們的分析指出運營商通常會選擇不同的升級時間以避免激烈的競爭。升級早的運營商在市場佔有方面有優勢，而升級晚的運營商只需承擔少量的升級成本並將面對一個更成熟的4G市場。其次，我們研究一個運營商是否有經濟動機在他已有的蜂窩基站C(macrocell)的基礎上再鋪設家庭基站(femtocell)。家庭基站能解決4G 網絡中室內用戶信號接收差的問題，但是該服務會佔用運營商原本就有限的頻譜資源。最後，我們嘗試去理解一個運營商該如何為異構的智慧手機用戶提供經濟刺激來鼓勵他們協助社交應用(比如，信息收集和分布式計算)的建立。在信息不對稱的情況下，我們設計了有效的激勵機制來根據智慧手機用戶不同的隱私損失、使用能耗和計算效率來提供獎勵。 / 在本論文的第二部分，我們在認知其在線電網絡中研究投資的便利性、頻譜感知的不確定性和安全性將如何影響一個次級(沒有頻譜執照的)運營商的決策。首先，我們研究一個可以通過動態頻譜租賞和頻譜感知兩種靈活方式來獲得絨線頻譜的次級運營商。我們聯合研究該運營商的投資選擇和對底層用戶的定價策略來使其利益最優。與動態頻譜租貸相比，頻譜感知不穩定但是能節約投資成本。其次，我們考慮一個包含兩個運營商的競爭市場，並研究他們之間在投資和定價方面的競爭。我們指出該競爭會給底層用戶帶來顯著好處而給運營商們帶來的收益總損失不會超過25% 。最後，一個運營商可能想利用多用戶合作式頻譜感知技術來提高感知的精確性但是該技術容易遭受數據偽造攻擊(data falsification attacks) 。我們通過合適的攻擊檢測和懲罰設計了有效的機制以防範攻擊。 / It is becoming increasingly important for wireless network operators to jointly optimize economic and technological decisions for business success. An operator's decisions may involve the choices and timings of technology adoptions, the amount of resources to invest, and the prices to set for his services. These decisions are coupled with each other and need to be jointly optimized, and such optimization will be challenging when the operator faces limited resources, immature technology, and market competition. This thesis focuses on such issues in two types of networks. We first study the economics of cellular networks, which have the largest market occupancy among all wireless technologies. We then look at the economics of cognitive radios networks, which represent one of the main development trends for wireless technologies in the near future. / In the first part of this thesis, we study a cellular operator's economic and technological decisions related to network upgrade, service differentiation, and social applications. First, we develop a game theoretic model for studying competitive operators' upgrade timing decisions from the existing 3G cellular technology to the next generation (4G) technology. Our analysis shows that operators often select different upgrade times to avoid severe competition. The operator upgrading earlier has advantage in increasing market share, while the one upgrading later benefit from decreased upgrade cost and a more mature 4G market. Second, we study an operator's economic incentive of deploying femtocell service on top of his existing macrocell service. The femtocell can resolve the issue of poor signal receptions for indoor users in 4G networks, but need to occupy the operator's limited spectrum resources. Finally, we try to understand how an operator can provide economic incentives for the heterogeneous smartphone users to collaborate in social applications (e.g., data acquisition and distributed computing). Under asymmetric information, we design effcient incentive mechanisms that reward smartphone users according to their different sensitivities to privacy loss, energy and computing effciencies. / In the second part of this thesis, we study how investment flexibility, sensing uncertainty, and sensing security in cognitive radio networks affect a secondary (unlicensed) operator's decisions. First, we study a secondary operator, who can flexibly acquire wireless spectrum through both dynamic spectrum leasing and spectrum sensing. We jointly study an operator's investment choices and pricing strategy to the end users to maximize his profit. Compared to spectrum leasing, spectrum sensing is unreliable but has a small cost. Second, we consider a competitive market with two operators, and study their competition in both investment and pricing. We show that end users significantly benefit from such market competition, and the operators' total profit loss due to competition is lower bounded by 25% of the maximum. Finally, an operator may want to deploy collaborative spectrum sensing to improve sensing accuracy, but this approach is vulnerable to data falsification attacks. We design effective attack prevention mechanisms through proper attack detection and punishment. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Duan, Lingjie. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 310-336). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Economics of Cellular Networks --- p.3 / Chapter 1.2 --- Economic Viability of Cognitive Radio Networks --- p.5 / Chapter 1.3 --- Outline and Contributions --- p.9 / Chapter I --- Economics of Cellular Networks --- p.13 / Chapter 2 --- Economics of 4G Cellular Network Upgrade --- p.14 / Chapter 2.1 --- Introduction --- p.14 / Chapter 2.1.1 --- Related Work --- p.18 / Chapter 2.2 --- System Model --- p.19 / Chapter 2.2.1 --- Value of Cellular Networks --- p.19 / Chapter 2.2.2 --- User Churn during Upgrade from 3G to 4G Services --- p.23 / Chapter 2.2.3 --- Operators' Revenues and Upgrade Costs --- p.25 / Chapter 2.3 --- 4G Monopoly Market --- p.26 / Chapter 2.4 --- 4G Competition Market: Duopoly Model and Game Formulation --- p.32 / Chapter 2.4.1 --- Operators' Long-term Profits --- p.34 / Chapter 2.4.2 --- Duopoly Upgrade Game --- p.37 / Chapter 2.5 --- 4G Competition Market: No Inter-network switching --- p.39 / Chapter 2.6 --- 4G Competition Market: Practical Inter-network Switching Rate --- p.40 / Chapter 2.7 --- Summary --- p.50 / Chapter 2.8 --- Appendix --- p.50 / Chapter 2.8.1 --- Proof Sketch of Theorem 2 --- p.50 / Chapter 2.8.2 --- Proof Sketch of Theorem 3 --- p.52 / Chapter 3 --- Economics of Femtocell Service Provision --- p.55 / Chapter 3.1 --- Introduction --- p.55 / Chapter 3.1.1 --- Related Work --- p.60 / Chapter 3.2 --- Benchmark: Macrocell Service Only --- p.62 / Chapter 3.2.1 --- Users' Bandwidth Demands in Stage II --- p.63 / Chapter 3.2.2 --- Operator's Pricing in Stage I --- p.65 / Chapter 3.3 --- Provision of Femtocell Service --- p.67 / Chapter 3.3.1 --- Users' Service Choices and Bandwidth Demands in Stage II --- p.71 / Chapter 3.3.2 --- Operator's Spectrum Allocations and Pricing in Stage I --- p.73 / Chapter 3.4 --- Impact of Users' Reservation Payoffs --- p.75 / Chapter 3.5 --- Impact of Femtocell Frequency Reuse --- p.82 / Chapter 3.6 --- Impact of Femtocell Operational Cost --- p.84 / Chapter 3.7 --- Impact of Limited Femtocell Coverage --- p.89 / Chapter 3.8 --- Summary --- p.95 / Chapter 4 --- Smartphone Collaboration on Social Applications --- p.96 / Chapter 4.1 --- Introduction --- p.96 / Chapter 4.1.1 --- Related Work --- p.100 / Chapter 4.2 --- Collaboration on Data Acquisition Application --- p.102 / Chapter 4.2.1 --- System Model of Data Acquisition --- p.102 / Chapter 4.2.2 --- Collaboration under Complete Information --- p.105 / Chapter 4.2.3 --- Collaboration under Symmetrically Incomplete Information --- p.106 / Chapter 4.2.4 --- Collaboration under Asymmetrically Incomplete Information --- p.109 / Chapter 4.3 --- Collaboration on Distributed Computing Application --- p.117 / Chapter 4.3.1 --- System Model on Distributed Computation --- p.117 / Chapter 4.3.2 --- Contractual Interactions between Client and Users --- p.119 / Chapter 4.3.3 --- Contract Design under Complete Information --- p.120 / Chapter 4.3.4 --- Client's Contract Design under Asymmetrically Incomplete Information --- p.123 / Chapter 4.4 --- Summary --- p.133 / Chapter 4.5 --- Appendix --- p.134 / Chapter 4.5.1 --- Discussion of Model (4.2) in Different Information Scenarios --- p.134 / Chapter 4.5.2 --- Proof of Theorem 9 --- p.135 / Chapter 4.5.3 --- Proof of No Collaboration and Pure Strategy NE in Theorem 10 --- p.136 / Chapter 4.5.4 --- Proof of Existence And Uniqueness of Equilibrium Threshold in Theorem 12 --- p.137 / Chapter 4.5.5 --- Proof of Theorem 13 --- p.139 / Chapter 4.5.6 --- Proof of Theorem 14 --- p.141 / Chapter 4.5.7 --- The proof of Proposition 1 --- p.142 / Chapter 4.5.8 --- Approximated Algorithm to Solve Problem (4.23) --- p.146 / Chapter II --- Economics of Cognitive Radio Networks --- p.149 / Chapter 5 --- Monopoly Spectrum Market Using Cognitive Radios --- p.150 / Chapter 5.1 --- Introduction --- p.150 / Chapter 5.1.1 --- Related Work --- p.155 / Chapter 5.2 --- Network Model --- p.157 / Chapter 5.2.1 --- Background on Spectrum Sensing and Leasing --- p.157 / Chapter 5.2.2 --- Notations and Assumptions --- p.159 / Chapter 5.2.3 --- A Stackelberg Game --- p.163 / Chapter 5.3 --- Backward Induction of the Four-stage Game --- p.164 / Chapter 5.3.1 --- Spectrum Allocation in Stage IV --- p.165 / Chapter 5.3.2 --- Optimal Pricing Strategy in Stage III --- p.167 / Chapter 5.3.3 --- Optimal Leasing Strategy in Stage II --- p.171 / Chapter 5.3.4 --- Optimal Sensing Strategy in Stage I --- p.173 / Chapter 5.4 --- Equilibrium Summary and Numerical Results --- p.179 / Chapter 5.4.1 --- Robustness of the Observations --- p.185 / Chapter 5.5 --- The Impact of Spectrum Sensing Uncertainty --- p.187 / Chapter 5.6 --- Learning the Distribution of Sensing Realization Factor α --- p.191 / Chapter 5.6.1 --- Performance Evaluation of Machine Learning --- p.193 / Chapter 5.7 --- Summary --- p.195 / Chapter 5.8 --- Appendix --- p.196 / Chapter 5.8.1 --- Proof of Theorem 18 --- p.196 / Chapter 5.8.2 --- Proof of Theorem 19 --- p.197 / Chapter 5.8.3 --- Supplementary Proof of Theorem 21 --- p.198 / Chapter 6 --- Competitive Spectrum Market Using Cognitive Radios --- p.204 / Chapter 6.1 --- Introduction --- p.204 / Chapter 6.1.1 --- Related Work --- p.209 / Chapter 6.2 --- Network and Game Model --- p.211 / Chapter 6.2.1 --- Users' and Operators' Models --- p.213 / Chapter 6.3 --- Backward Induction of the Three-Stage Game --- p.215 / Chapter 6.3.1 --- Spectrum Allocation in Stage III --- p.217 / Chapter 6.3.2 --- Operators' Pricing Competition in Stage II --- p.221 / Chapter 6.3.3 --- Operators' Leasing Strategies in Stage I --- p.226 / Chapter 6.4 --- Equilibrium Summary --- p.231 / Chapter 6.4.1 --- How Network Dynamics Affect Equilibrium Decisions --- p.234 / Chapter 6.5 --- Equilibrium Analysis under General SNR Regime --- p.237 / Chapter 6.6 --- Impact of Operator Competition --- p.239 / Chapter 6.6.1 --- Maximum Profit in the Coordinated Case --- p.239 / Chapter 6.6.2 --- Impact of Competition on Operators' Profits --- p.242 / Chapter 6.6.3 --- Impact of Competition on Users' Payoffs --- p.244 / Chapter 6.7 --- Summary --- p.245 / Chapter 6.8 --- Appendix --- p.246 / Chapter 6.8.1 --- Proof of Theorem 24 --- p.246 / Chapter 6.8.2 --- Proof of Theorem 25 --- p.250 / Chapter 7 --- Security Protection in Collaborative Spectrum Sensing --- p.256 / Chapter 7.1 --- Introduction --- p.256 / Chapter 7.1.1 --- Related Work --- p.260 / Chapter 7.2 --- Preliminary --- p.261 / Chapter 7.2.1 --- CRN Model and Assumptions --- p.261 / Chapter 7.2.2 --- Spectrum Sensing and Opportunistic Access Model --- p.264 / Chapter 7.2.3 --- Collision Penalty --- p.265 / Chapter 7.2.4 --- Decision Fusion Rule --- p.266 / Chapter 7.3 --- Attackers' Behaviors Without Punishment --- p.268 / Chapter 7.3.1 --- All SUs sense the channel idle --- p.270 / Chapter 7.3.2 --- All honest SUs sense the channel idle, but some attacker(s) senses the channel busy --- p.270 / Chapter 7.3.3 --- Some honest SUs sense the channel busy --- p.272 / Chapter 7.4 --- Attack-Prevention Mechanism: A Direct Punishment --- p.273 / Chapter 7.5 --- Attack-Prevention Mechanism: An Indirect Punishment --- p.277 / Chapter 7.6 --- Summary --- p.286 / Chapter 7.7 --- Appendix --- p.286 / Chapter 7.7.1 --- Relaxation of Assumptions A1 and A3 --- p.286 / Chapter 7.7.2 --- Attack Prevention in Case:AT of Section 7.5 --- p.293 / Chapter 7.7.3 --- Proof of Lemma 6 --- p.297 / Chapter 8 --- Conclusion and Future Work --- p.299 / Chapter 8.1 --- Conclusion --- p.299 / Chapter 8.2 --- Extensions of 4G Network Upgrade in Chapter 2 --- p.302 / Chapter 8.3 --- Extensions of Femtocell Service Provision in Chapter 3 --- p.303 / Chapter 8.4 --- Extensions of Smartphone Collaboration on Social Applications in Chapter 4 --- p.304 / Chapter 8.5 --- Extensions of Monopoly Spectrum Market in Chapter 5 --- p.305 / Chapter 8.6 --- Extensions of Competitive Spectrum Market in Chapter 6 --- p.306 / Chapter 8.7 --- Extensions of Security Protection in Collaborative Spectrum Sensing in Chapter 7 --- p.308 / Bibliography --- p.310

動態頻譜共享(dynamic spectrum sharing) 允許不具有執照的無線電用戶(坎級用戶)擇機使用具有執照的無線電用戶(主用戶)的頻譜，因此被認為是一種有效解決頻譜低效利用問題的方案。本論文研究次級用戶如何智能地實現高效率的動態頻譜共享。我們考慮兩種智能共享模式:社交智能(social intelligence) 以及個體智能(individual intelligence) 。 / 對於社交智能，次級用戶基於社交互動(social interactions) 來協作地共享頻譜。受到電子商務工業的推薦系統(recommendation sYstem) 的啟發，我們提出了一種基於推薦的社交頻譜共享機制。其中，次級用戶相互協作，彼此推薦良好的信道， 并動態接入信道。我們設計了種基於馬爾科夫決策過程( Markovdecision process) 的自適應信道推薦算法。該算法可突現良好的系統通信性能。同時，我們也提出種基於模仿(imitation) 的社交頻譜分享機制。其中，次級用戶根據自身觀察來估計自己的期望通信速率并彼此分享。如果鄰近用戶的期望通信速率更高，該用戶則模仿鄰近用戶的信道接入。我們證明該機制能夠有效地收斂到模仿均衡。如果次級用戶的數目較多，收斂的模仿均衡即是納什均衡(Nashequilibrium) 。該均衡是個次級用戶相互滿意的頻譜共享結果。 / 對於個體智能，次級用戶基於策略互動(strategic interactions) 來競爭地共享頻譜。對於基於空間複用(spatial reuse) 的競爭性頻譜共享，我們提出了種新穎的空間頻譜接入博弈框架。我們研究了不同的干擾圖形結構對於納什均衡的存在性的影響。同時，我們設計了種基於用戶自身觀察的分佈式學習算法。該算法適用於所有空間頻譜接入博弈，并能夠有效地收斂到近似納什均衡(approximateNash equilibrium) 。對於基於數據庫的電視頻譜(white-space spectrum) 無線AP(access point)網絡，我們運用博弈理論方法為分佈式AP 信道選擇問題以及分佈式次級用戶AP 連接問題建立理論模型。我們證明了分佈式AP信道選擇博奔以及分佈式次級用戶AP 連接博弈屬於勢博弈(potential game) 的範疇。基於勢博莽的有限改進性質(finite improvement property) ，我們設計了分佈式算法能夠有效地收斂到納什均衡。 / Dynamic spectrum sharing enables unlicensed secondary wireless users to opportunistically share the spectrum with licensed primary users, and thus is envisioned as a promising solution to address the spectrum under-utilization problem. This thesis explores the intelligence of secondary users for achieving efficient distributed spectrum sharing. We consider two types of intelligences: social intelligence and individual intelligence. / For the social intelligence, secondary users share the spectrum collaboratively based on social interactions. Inspired by the recommendation system in the electronic commerce industry, we propose a recommendation-based social spectrum sharing mechanism, where secondary users collaboratively recommend "good" channels to each other and access accordingly. We devise an adaptive channel recommendation algorithm based on Markov decision process, which achieves a good system communication performance. We then propose an imitation-based social spectrum sharing mechanism, where each secondary user estimates its expected throughput based on local observations, and imitates another neighboring user’s channel selection if neighbor’s estimated throughput is higher. We show that the mechanism can converge to an imitation equilibrium. When the number of users is large, the convergent imitation equilibrium corresponds to a Nash equilibrium, which is a mutually satisfactory spectrum sharing solution. / For the individual intelligence, secondary users share the spectrum competitively based on strategic interactions. To formulate the competitive spectrum sharing with spatial reuse, we propose a framework of spatial spectrum access game on general directed interference graphs. We investigate the impact of the underlying interference graph structure on the existence of a Nash equilibrium. We also design a distributed learning algorithm based on local observations that can converge to an approximate Nash equilibrium for any spatial spectrum access games. We then apply the game theoretic approach for modeling the distributed channel selection problem among the APs and distributed AP association problem among the secondary users in database-assisted white-space AP networks. We show that both the distributed AP channel selection game and the distributed AP association game are potential games. We then design distributed algorithms for achieving Nash equilibria by utilizing the finite improvement property of potential game. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Chen, Xu. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 180-188). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Abstract --- p.i / Acknowledgement --- p.v / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation and Overview --- p.1 / Chapter 1.2 --- Thesis Outline --- p.5 / Chapter I --- Social Intelligence For Distributed Spectrum Sharing --- p.7 / Chapter 2 --- Recommendation-based Social Spectrum Sharing --- p.8 / Chapter 2.1 --- Introduction --- p.8 / Chapter 2.2 --- System Model --- p.12 / Chapter 2.3 --- Introduction To Channel Recommendation --- p.13 / Chapter 2.3.1 --- Review of Static Channel Recommendation --- p.14 / Chapter 2.3.2 --- Motivations For Adaptive Channel Recommendation --- p.16 / Chapter 2.4 --- Adaptive Channel Recommendation With Channel Homogeneity --- p.18 / Chapter 2.4.1 --- MDP Formulation For Adaptive Channel Recommendation --- p.19 / Chapter 2.4.2 --- Existence of Optimal Stationary Policy --- p.21 / Chapter 2.5 --- Model Reference Adaptive Search For Optimal Spectrum Access Policy --- p.22 / Chapter 2.5.1 --- Model Reference Adaptive Search Method --- p.23 / Chapter 2.5.2 --- Model Reference Adaptive Search For Optimal Spectrum Access Policy --- p.24 / Chapter 2.5.3 --- Convergence of Model Reference Adaptive Search --- p.29 / Chapter 2.6 --- Adaptive Channel Recommendation With Channel Heterogeneity --- p.30 / Chapter 2.7 --- Numerical Results --- p.33 / Chapter 2.7.1 --- Simulation Setup --- p.33 / Chapter 2.7.2 --- Homogeneous Channel Recommendation --- p.34 / Chapter 2.7.3 --- Heterogenous Channel Recommendation --- p.35 / Chapter 2.8 --- Chapter Summary --- p.38 / Chapter 2.9 --- Appendix --- p.39 / Chapter 2.9.1 --- Proof of Lemma 2.1 --- p.39 / Chapter 2.9.2 --- Derivation of Transition Probability --- p.40 / Chapter 2.9.3 --- Proof of Theorem 2.1 --- p.41 / Chapter 2.9.4 --- Proof of Theorem 2.2 --- p.42 / Chapter 2.9.5 --- Proof of Theorem 2.3 --- p.47 / Chapter 2.9.6 --- Proof of Theorem 2.4 --- p.50 / Chapter 3 --- Imitation-based Social Spectrum Sharing --- p.52 / Chapter 3.1 --- Introduction --- p.52 / Chapter 3.2 --- Spectrum Sharing System Model --- p.55 / Chapter 3.3 --- Imitative Spectrum Access Mechanism --- p.58 / Chapter 3.3.1 --- Expected Throughput Estimation --- p.59 / Chapter 3.3.2 --- Information Sharing Graph --- p.63 / Chapter 3.3.3 --- Imitative Spectrum Access --- p.63 / Chapter 3.4 --- Convergence of Imitative Spectrum Access --- p.65 / Chapter 3.4.1 --- Cluster-based Representation of Information Sharing Graph --- p.65 / Chapter 3.4.2 --- Dynamics of Imitative Spectrum Access --- p.67 / Chapter 3.4.3 --- Convergence of Imitative Spectrum Access --- p.71 / Chapter 3.5 --- Imitative Spectrum Access with Innovation --- p.73 / Chapter 3.6 --- Imitative Spectrum Access With User Heterogeneity --- p.75 / Chapter 3.7 --- Simulation Results --- p.77 / Chapter 3.7.1 --- Large User Population --- p.78 / Chapter 3.7.2 --- Small User Population --- p.82 / Chapter 3.7.3 --- Markovian Channel Environment --- p.85 / Chapter 3.7.4 --- Imitative Spectrum Access With User Heterogeneity --- p.88 / Chapter 3.8 --- Chapter Summary --- p.88 / Chapter 3.9 --- Appendix --- p.89 / Chapter 3.9.1 --- Proof of Theorem 3.1 --- p.89 / Chapter 3.9.2 --- Proof of Theorem 3.2 --- p.91 / Chapter II --- Individual Intelligence For Distributed Spectrum Sharing --- p.93 / Chapter 4 --- Spatial Spectrum Access Game --- p.94 / Chapter 4.1 --- Introduction --- p.94 / Chapter 4.2 --- System Model --- p.97 / Chapter 4.3 --- Spatial Spectrum Access Game --- p.101 / Chapter 4.4 --- Existence of Nash Equilibria --- p.102 / Chapter 4.4.1 --- Existence of Pure Nash Equilibria on Directed Interference Graphs --- p.103 / Chapter 4.4.2 --- Existence of Pure Nash Equilibria on Undirected Interference Graphs --- p.108 / Chapter 4.5 --- Distributed Learning For Spatial Spectrum Access --- p.113 / Chapter 4.5.1 --- Expected Throughput Estimation --- p.114 / Chapter 4.5.2 --- Distributed Learning Algorithm --- p.115 / Chapter 4.5.3 --- Convergence of Distributed Learning Algorithm --- p.117 / Chapter 4.6 --- Numerical Results --- p.121 / Chapter 4.7 --- Chapter Summary --- p.126 / Chapter 4.8 --- Appendix --- p.127 / Chapter 4.8.1 --- Proof of Theorem 4.2 --- p.127 / Chapter 4.8.2 --- Proof of Theorem 4.3 --- p.129 / Chapter 4.8.3 --- Proof of Lemma 4.4 --- p.131 / Chapter 4.8.4 --- Proof of Lemma 4.5 --- p.133 / Chapter 4.8.5 --- Proof of Theorem 4.5 --- p.136 / Chapter 4.8.6 --- Proof of Theorem 4.6 --- p.139 / Chapter 5 --- Distributed AP Channel Selection Game --- p.141 / Chapter 5.1 --- Introduction --- p.141 / Chapter 5.2 --- Distributed AP Channel Selection --- p.144 / Chapter 5.2.1 --- Problem Formulation --- p.144 / Chapter 5.2.2 --- Distributed AP Channel Selection Game --- p.146 / Chapter 5.3 --- Distributed AP Channel Selection Algorithms --- p.149 / Chapter 5.3.1 --- Distributed AP Channel Selection Algorithm With Information Exchange --- p.149 / Chapter 5.3.2 --- Distributed AP Channel Selection Algorithm Without Information Exchange --- p.151 / Chapter 5.4 --- Numerical Results --- p.157 / Chapter 5.4.1 --- Distributed AP Channel Selection With Information Exchange --- p.157 / Chapter 5.4.2 --- Distributed AP Channel Selection Without Information Exchange --- p.159 / Chapter 5.5 --- Chapter Summary --- p.161 / Chapter 5.6 --- Appendix --- p.162 / Chapter 5.6.1 --- Proof of Theorem 5.2 --- p.162 / Chapter 6 --- Distributed AP Association Game --- p.165 / Chapter 6.1 --- Introduction --- p.165 / Chapter 6.2 --- Distributed AP Association --- p.166 / Chapter 6.2.1 --- Channel Contention Within an AP --- p.167 / Chapter 6.2.2 --- Distributed AP Association Game --- p.168 / Chapter 6.2.3 --- Distributed AP Association Algorithm --- p.170 / Chapter 6.3 --- Numerical Results --- p.172 / Chapter 6.4 --- Chapter Summary --- p.175 / Chapter 7 --- Conclusions and Future Work --- p.176 / Bibliography --- p.180

Zhang Liang. / "August 2004." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references. / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Finally, to obtain a long network lifetime without sacrificing crucial aspects of quality of service (area coverage, sensing reliability, and network connectivity) in wireless sensor networks, we present sensibility-based sleeping configuration protocols (SSCPs) with two sensing models: Boolean sensing model (BSM) and collaborative sensing model (CSM). (Abstract shortened by UMI.) / Furthermore, we extend the traditional reliability analysis. Wireless networks inherit the unique handoff characteristic which leads to different communication structures of various types with a number of components and links. Therefore, the traditional definition of two-terminal reliability is not applicable anymore. We propose a new term, end-to-end mobile reliability, to integrate those different communication structures into one metric, which includes not only failure parameters but also service parameters. Nevertheless, it is still a monotonically decreasing function of time. With the proposed end-to-end mobile reliability, we could identify the reliability importance of imperfect components in wireless networks. / The emerging mobile wireless environment poses exciting challenges for distributed fault-tolerant (FT) computing. This thesis develops a message logging and recovery protocol on the top of Wireless CORBA to complement FT-CORBA specified for wired networks. It employs the storage available at access bridge (AB) as the stable storage for logging messages and saving checkpoints on behalf of mobile hosts (MHs). Our approach engages both the quasi-sender-based and the receiver-based message logging techniques and conducts seamless handoff in the presence of failures. / Then we extend the analysis of the program execution time without and with checkpointing in the presence of MH failures from wired to wireless networks. Due to the underlying message-passing communication mechanism, we employ the number of received computational messages instead of time to indicate the completion of program execution at an MH. Handoff is another distinct factor that should be taken into consideration in mobile wireless environments. Three checkpointing strategies, deterministic, random, and time-based checkpointing, are investigated. In our approach, failures may occur during checkpointing and recovery periods. / Chen Xinyu. / "June 2005." / Adviser: Michael R. Lyu. / Source: Dissertation Abstracts International, Volume: 67-07, Section: B, page: 3889. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (p. 180-198). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract in English and Chinese. / School code: 1307.

Du Yinggang. / "September 2004." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (p. 113-119). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Cheng Wang Chi. / "October 2004." / Thesis (Ph.D.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (p. 135-139) / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web. / Abstracts in English and Chinese.

Different from multiple-input multiple-output (MIMO) systems, a major challenge for cooperative communications is the problem of synchronization because multiple transmissions undertaken by cooperative systems may not be synchronized in time and/or frequency. With synchronization errors, conventional space-time (ST) codes may not be directly applicable any longer. To tackle the problem of timing synchronization, space-frequency (SF) coded orthogonal frequency division multiplexing (OFDM) cooperative systems have recently been proposed to achieve asynchronous diversity due to their insensitivity to timing errors. However, these systems still need to face the problem of multiple carrier frequency offsets (CFOs). Since each node in a cooperative system is equipped with its own oscillator, the received signals from different relay nodes may have multiple CFOs which cannot be compensated simultaneously at the destination node. For SF coded OFDM cooperative systems, this problem becomes more complicated because CFOs can lead to inter-carrier interference (ICI). To address this challenge, in this thesis we consider the signal detection problem in cooperative systems having multiple CFOs. / First, we investigate the effect of multiple CFOs on two classic ST codes. They are delay diversity and the Alamouti code. For delay diversity, we find that both its achieved diversity order and diversity product are not decreased by multiple CFOs arising from maximum-likelihood (ML) detection. For the Alamouti code, the diversity product may be decreased by multiple CFOs. In the worst case situation, full diversity order 2 cannot be achieved. / For deeper insights into the SF coded communication system with multiple CFOs, we then carry out diversity analysis. By treating the CFOs as part of the SF codeword matrix, we show that if all the absolute values of normalized CFOs are less than 0.5, then the full diversity order for the SF codes are not affected by the multiple CFOs in the SF coded OFDM cooperative system. We further prove that this full diversity property can still be preserved if the zero forcing (ZF) method is used to equalize the multiple CFOs. This method, by some reasonable approximations, is actually equivalent to the MMSE-F detection method. To improve the robustness of the SF codes to multiple CFOs, we propose a novel permutation method. With this method, the achieved diversity order of SF codes remains the same even when the absolute values of normalized CFOs are equal to or greater than 0.5. To reduce computational complexity, we further propose two full diversity achievable detection methods, namely the ZF-ML-Zn and ZF-ML-PIC detection methods, which are suitable for the case when the ICI matrix is singular. / In summary, in this study, we demonstrate that with proper design, the SF coded OFDM approach can be made robust to both timing errors and CFOs in a cooperative communication system. / Since OFDM systems are robust to timing errors, we turn to an SF coded cooperative communication system with multiple CFOs, where the SF codes are rotational based and can achieve both full cooperative and full multipath diversity orders. We begin with the traditional way of ICI mitigation. To preserve the performance of the SF code, we suggest increasing the SINR of each subcarrier but not equalizing the SF precoding matrix. By exploiting the structure of the SF codes, we propose three signal detection methods to deal with the multiple CFOs problem in SF coded OFDM systems. They are the minimum mean-squared filtering (MMSE-F) method, the two-stage simple frequency shift Q taps (FS-Q-T) method, and the multiple fast Fourier transform (M-FFT) method, all of which offer different tradeoffs between performance and computational complexity. Our simulation results indicate that the proposed detection methods perform well as long as the CFOs between nodes are small. / Tian, Feng. / Adviser: Ching Pak-Chung. / Source: Dissertation Abstracts International, Volume: 71-01, Section: B, page: 0559. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2009. / Includes bibliographical references (leaves 146-160). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese.