The growing number of mobile devices and data-intensive applications pose unique challenges for wireless access networks as well as datacenter networks that enable modern cloud-based services. With the enormous increase in volume and complexity of traffic from applications such as video streaming and cloud computing, the interconnection networks have become a major performance bottleneck. In this thesis, we study algorithms and architectures spanning several layers of the networking protocol stack that enable and accelerate novel applications and that are easily deployable and scalable. The design of these algorithms and architectures is motivated by measurements and observations in real world or experimental testbeds. In the first part of this thesis, we address the challenge of wireless content delivery in crowded areas. We present the AMuSe system, whose objective is to enable scalable and adaptive WiFi multicast. AMuSe is based on accurate receiver feedback and incurs a small control overhead. This feedback information can be used by the multicast sender to optimize multicast service quality, e.g., by dynamically adjusting transmission bitrate. Specifically, we develop an algorithm for dynamic selection of a subset of the multicast receivers as feedback nodes which periodically send information about the channel quality to the multicast sender. Further, we describe the Multicast Dynamic Rate Adaptation (MuDRA) algorithm that utilizes AMuSe's feedback to optimally tune the physical layer multicast rate. MuDRA balances fast adaptation to channel conditions and stability, which is essential for multimedia applications. We implemented the AMuSe system on the ORBIT testbed and evaluated its performance in large groups with approximately 200 WiFi nodes. Our extensive experiments demonstrate that AMuSe can provide accurate feedback in a dense multicast environment. It outperforms several alternatives even in the case of external interference and changing network conditions. Further, our experimental evaluation of MuDRA on the ORBIT testbed shows that MuDRA outperforms other schemes and supports high throughput multicast flows to hundreds of nodes while meeting quality requirements. As an example application, MuDRA can support multiple high quality video streams, where 90% of the nodes report excellent or very good video quality. Next, we specifically focus on ensuring high Quality of Experience (QoE) for video streaming over WiFi multicast. We formulate the problem of joint adaptation of multicast transmission rate and video rate for ensuring high video QoE as a utility maximization problem and propose an online control algorithm called DYVR which is based on Lyapunov optimization techniques. We evaluated the performance of DYVR through analysis, simulations, and experiments using a testbed composed of Android devices and o the shelf APs. Our evaluation shows that DYVR can ensure high video rates while guaranteeing a low but acceptable number of segment losses, buffer underflows, and video rate switches. We leverage the lessons learnt from AMuSe for WiFi to address the performance issues with LTE evolved Multimedia Broadcast/Multicast Service (eMBMS). We present the Dynamic Monitoring (DyMo) system which provides low-overhead and real-time feedback about eMBMS performance. DyMo employs eMBMS for broadcasting instructions which indicate the reporting rates as a function of the observed Quality of Service (QoS) for each UE. This simple feedback mechanism collects very limited QoS reports which can be used for network optimization. We evaluated the performance of DyMo analytically and via simulations. DyMo infers the optimal eMBMS settings with extremely low overhead, while meeting strict QoS requirements under different UE mobility patterns and presence of network component failures. In the second part of the thesis, we study datacenter networks which are key enablers of the end-user applications such as video streaming and storage. Datacenter applications such as distributed file systems, one-to-many virtual machine migrations, and large-scale data processing involve bulk multicast flows. We propose a hardware and software system for enabling physical layer optical multicast in datacenter networks using passive optical splitters. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Our evaluation shows that the optical multicast architecture can achieve higher throughput and lower latency than IP multicast and peer-to-peer multicast schemes with lower switching energy consumption. Finally, we study the problem of congestion control in datacenter networks. Quantized Congestion Control (QCN), a switch-supported standard, utilizes direct multi-bit feedback from the network for hardware rate limiting. Although QCN has been shown to be fast-reacting and effective, being a Layer-2 technology limits its adoption in IP-routed Layer 3 datacenters. We address several design challenges to overcome QCN feedback's Layer- 2 limitation and use it to design window-based congestion control (QCN-CC) and load balancing (QCN-LB) schemes. Our extensive simulations, based on real world workloads, demonstrate the advantages of explicit, multi-bit congestion feedback, especially in a typical environment where intra-datacenter traffic with short Round Trip Times (RTT: tens of s) run in conjunction with web-facing traffic with long RTTs (tens of milliseconds).

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Ruan, Sichao. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 62-65). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Multihop Ad Hoc Wireless Networks --- p.1 / Chapter 1.1.1 --- Introduction to Multihop Ad Hoc Networks --- p.2 / Chapter 1.1.2 --- Scalability of Ad Hoc Wireless Networks --- p.3 / Chapter 1.2 --- Hidden Terminal Problem --- p.3 / Chapter 1.3 --- Exposed Terminal Problem --- p.5 / Chapter 1.4 --- Overview of the Thesis --- p.6 / Chapter 2 --- Background --- p.8 / Chapter 2.1 --- MAC Protocols for Wireless Networks --- p.8 / Chapter 2.1.1 --- Aloha --- p.8 / Chapter 2.1.2 --- CSMA/CA --- p.9 / Chapter 2.1.3 --- IEEE 802.11 DCF Standard --- p.10 / Chapter 2.2 --- Related Work --- p.12 / Chapter 2.2.1 --- Schemes for Hidden Node Problem --- p.12 / Chapter 2.2.2 --- Schemes for Exposed Node Problem --- p.13 / Chapter 2.3 --- Tradeoff between Hidden and Exposed Nodes --- p.14 / Chapter 2.4 --- The Effect of Carrier Sensing Range --- p.17 / Chapter 3 --- Analysis on Carrier Sensing Range --- p.18 / Chapter 3.1 --- Analysis Model --- p.18 / Chapter 3.1.1 --- Terminal Configurations --- p.18 / Chapter 3.1.2 --- Timing/Packet Parameters --- p.19 / Chapter 3.1.3 --- Protocol Approximation --- p.20 / Chapter 3.1.4 --- Throughput Measurement --- p.21 / Chapter 3.2 --- Derivation of Throughput --- p.21 / Chapter 3.2.1 --- Channel Modeling --- p.22 / Chapter 3.2.2 --- Actual Transmission Rate --- p.24 / Chapter 3.2.3 --- Case One --- p.24 / Chapter 3.2.4 --- Case Two --- p.26 / Chapter 3.2.5 --- Mathematical Form of Throughput --- p.28 / Chapter 3.2.6 --- Analysis Results --- p.30 / Chapter 3.3 --- Implications --- p.31 / Chapter 3.3.1 --- Value of Sensing Range in CSMA/CA --- p.31 / Chapter 3.3.2 --- Need for New MAC Protocols --- p.32 / Chapter 4 --- MAC Protocols by Congestion Control --- p.34 / Chapter 4.1 --- Motivations and Principles --- p.34 / Chapter 4.1.1 --- Balancing Hidden and Exposed Nodes --- p.35 / Chapter 4.1.2 --- Controlling Carrier Sensing Range --- p.36 / Chapter 4.1.3 --- Non-homogenous Sensing Range --- p.36 / Chapter 4.2 --- Algorithm Descriptions --- p.38 / Chapter 4.2.1 --- Core Concept --- p.38 / Chapter 4.2.2 --- LDMI Control Scheme --- p.40 / Chapter 4.2.3 --- Tahoe Control Scheme --- p.41 / Chapter 5 --- Simulation Analysis --- p.44 / Chapter 5.1 --- Simulation Configurations --- p.44 / Chapter 5.1.1 --- Geometric Burst Traffic Model --- p.45 / Chapter 5.1.2 --- Network Topology --- p.46 / Chapter 5.1.3 --- Simulation Parameters --- p.47 / Chapter 5.2 --- Throughput Comparisons --- p.48 / Chapter 5.3 --- Fairness Comparisons --- p.50 / Chapter 5.3.1 --- Situation of Unfairness --- p.50 / Chapter 5.3.2 --- Fairness Measurement --- p.52 / Chapter 5.4 --- Convergence Comparisons --- p.54 / Chapter 5.5 --- Summary of Performance Comparison --- p.55 / Chapter 6 --- Conclusions --- p.56 / Chapter A --- Categories of CSMA/CA --- p.58 / Chapter A.1 --- 1-persistent CSMA/CA --- p.58 / Chapter A.2 --- non-persistent CSMA/CA --- p.58 / Chapter A.3 --- p-persistent CSMA/CA --- p.59 / Chapter B --- Backoff Schemes --- p.60 / Chapter B.1 --- Constant Window Backoff Scheme --- p.60 / Chapter B.2 --- Geometric Backoff Scheme --- p.60 / Chapter B.3 --- Binary Exponential Backoff Scheme --- p.61 / Bibliography --- p.62

Zheng, Xiaoting. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (p. 64-69). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Rayleigh Fading --- p.1 / Chapter 1.2 --- Transmission Schemes --- p.2 / Chapter 1.2.1 --- Frequency Division Multiple Access(FDMA) --- p.2 / Chapter 1.2.2 --- Time Division Multiple Access(TDMA) --- p.3 / Chapter 1.2.3 --- Code Division Multiple Access(CDMA) --- p.5 / Chapter 1.2.4 --- The Broadcast Channel --- p.5 / Chapter 1.3 --- Cooperative Transmissions --- p.9 / Chapter 1.3.1 --- Relaying Protocols --- p.10 / Chapter 1.4 --- Outline of Thesis --- p.12 / Chapter 2 --- Background Study --- p.13 / Chapter 2.1 --- Superposition Coding --- p.13 / Chapter 2.2 --- Cooperative Transmission --- p.15 / Chapter 2.2.1 --- Single Source Single Destination --- p.15 / Chapter 2.2.2 --- Multiple Sources Single Destination --- p.16 / Chapter 2.2.3 --- Single Source Multiple Destinations --- p.17 / Chapter 2.2.4 --- Multiple Sources Multiple Destinations --- p.17 / Chapter 2.3 --- Power Minimization --- p.18 / Chapter 2.3.1 --- Power Minimization in Code-Multiplexing System --- p.19 / Chapter 2.3.2 --- Power Minimization in Frequency-multiplexing System --- p.19 / Chapter 2.3.3 --- Power Minimization in Time-Multiplexing System --- p.20 / Chapter 3 --- Sum Power Minimization with Superposition Coding --- p.21 / Chapter 3.1 --- System Model --- p.22 / Chapter 3.2 --- Superposition Coding Scheme --- p.22 / Chapter 3.2.1 --- Optimal Superposition Coding Scheme --- p.22 / Chapter 3.2.2 --- Sub-optimal Superposition Coding Scheme --- p.27 / Chapter 3.3 --- Performance Evaluation --- p.30 / Chapter 3.4 --- Assignment Examples for Superposition Coding Scheme --- p.33 / Chapter 4 --- Source-cooperated Transmission in a Wireless Cluster --- p.42 / Chapter 4.1 --- System Model --- p.42 / Chapter 4.2 --- Selection Protocol --- p.44 / Chapter 4.2.1 --- Protocol Description and Problem Formulation --- p.44 / Chapter 4.2.2 --- Distributed Selection Algorithm --- p.46 / Chapter 4.2.3 --- Low Rate Regime --- p.50 / Chapter 4.3 --- Simulation Results --- p.52 / Chapter 4.3.1 --- Simulation Configuration --- p.53 / Chapter 4.3.2 --- Cases with a Smaller Feasible Solution Set --- p.53 / Chapter 4.3.3 --- Cases with a Larger Feasible Solution Set --- p.56 / Chapter 5 --- Conclusion and Future Work --- p.61 / Chapter 5.1 --- Conclusion --- p.61 / Chapter 5.2 --- Future Work --- p.62 / Chapter 5.2.1 --- Fairness --- p.62 / Chapter 5.2.2 --- Distributed Algorithm --- p.63 / Chapter 5.2.3 --- Game Theory --- p.63 / Chapter 5.2.4 --- Distributed Information --- p.63 / Bibliography --- p.64

Lin, Xingqin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (p. 103-109). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / 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.8 / Chapter 1.3 --- Outline of the Thesis --- p.12 / Chapter 2 --- Learning for Parallel Gaussian Interference Channels --- p.14 / Chapter 2.1 --- System Model and Problem Formulation --- p.16 / Chapter 2.2 --- Stochastic Algorithm for Learning --- p.18 / Chapter 2.2.1 --- Algorithm Design --- p.18 / Chapter 2.2.2 --- Convergence Analysis --- p.21 / Chapter 2.3 --- Continuous Time Approximation --- p.26 / Chapter 2.4 --- Learning with Averaging --- p.28 / Chapter 2.5 --- Numerical Results --- p.29 / Chapter 3 --- Power Control for One-to-Many Transmissions --- p.34 / Chapter 3.1 --- System Model --- p.35 / Chapter 3.2 --- A GNEP Approach --- p.38 / Chapter 3.2.1 --- Problem Formulation --- p.38 / Chapter 3.2.2 --- Preliminary Results --- p.39 / Chapter 3.3 --- Algorithm Design --- p.42 / Chapter 3.4 --- Numerical Results --- p.46 / Chapter 4 --- Flow Allocation in Multiple Access Networks --- p.50 / Chapter 4.1 --- System Model and Problem Formulation --- p.52 / Chapter 4.1.1 --- System Model --- p.52 / Chapter 4.1.2 --- Problem Formulation --- p.53 / Chapter 4.2 --- Characterization of NE --- p.57 / Chapter 4.2.1 --- Feasibility Assumption --- p.57 / Chapter 4.2.2 --- Existence and Uniqueness of NE --- p.58 / Chapter 4.3 --- Distributed Algorithms Design --- p.60 / Chapter 4.3.1 --- D-SBRA --- p.60 / Chapter 4.3.2 --- P-SBRA --- p.61 / Chapter 4.3.3 --- Best Response and Layered Structure --- p.65 / Chapter 4.4 --- Performance Evaluation --- p.67 / Chapter 4.4.1 --- Protocol Evaluation --- p.67 / Chapter 4.4.2 --- Convergence and Performance --- p.69 / Chapter 4.4.3 --- Flow Distribution --- p.71 / Chapter 4.4.4 --- A Grid Network Simulation --- p.73 / Chapter 5 --- Relay Assignment in Cooperative Networks --- p.76 / Chapter 5.1 --- System Model and Problem Formulation --- p.77 / Chapter 5.1.1 --- Three-Node Relay Model --- p.77 / Chapter 5.1.2 --- Network Model --- p.78 / Chapter 5.1.3 --- Problem Formulation --- p.78 / Chapter 5.2 --- Centralized Scheme --- p.80 / Chapter 5.2.1 --- Generalized Relay Assignment --- p.80 / Chapter 5.2.2 --- Admission Control --- p.83 / Chapter 5.2.3 --- Iteration Algorithm and Some Remarks --- p.84 / Chapter 5.3 --- A Simple Distributed Algorithm --- p.84 / Chapter 5.4 --- Numerical Results --- p.86 / Chapter 6 --- Conclusions and Future Work --- p.88 / Chapter 6.1 --- Conclusions --- p.88 / Chapter 6.2 --- Future Work --- p.89 / Chapter A --- Proof of Theorem 21 --- p.93 / Chapter B --- Proof of Theorem 22 --- p.96 / Chapter C --- Proof of Proposition 31 --- p.98 / Chapter D --- Proof of Proposition 44 --- p.101 / Bibliography --- p.103

Lee, King Ho. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 69-72). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction to Wireless Technologies --- p.1 / Chapter 1.2 --- Wireless Systems --- p.2 / Chapter 1.3 --- Wireless Networks --- p.3 / Chapter 1.4 --- Multiple Access --- p.5 / Chapter 1.5 --- Objectives and Outlines of the Thesis --- p.8 / Chapter 2 --- Background Studies --- p.9 / Chapter 2.1 --- Introduction of Scheduling Models of Wireless Networks (Graph-based and Interference-based) --- p.10 / Chapter 2.2 --- Power Assignment in Interference-based Schedul- ing Model --- p.12 / Chapter 2.3 --- Motivation and Contribution --- p.14 / Chapter 3 --- Model --- p.16 / Chapter 4 --- Nonlinear Power Assignment Scheduling Algorithm --- p.22 / Chapter 4.1 --- Nonlinear Power Control Scheduling Algorithms --- p.22 / Chapter 4.2 --- Low-Disturbance Scheduling Protocol --- p.26 / Chapter 4.3 --- Fundamental Limitation of LDS --- p.28 / Chapter 4.4 --- Chapter Conclusion --- p.31 / Chapter 5 --- Step-Establishing Algorithm --- p.33 / Chapter 5.1 --- Step-Establishing Algorithm --- p.33 / Chapter 6 --- "Performances of LDS, SRA, and SEA" --- p.45 / Chapter 6.1 --- Simulation --- p.45 / Chapter 6.2 --- Exponential Chain Topology --- p.46 / Chapter 6.3 --- Fixed-Transmission-Length Random Network --- p.47 / Chapter 6.4 --- Cluster Chain Topology --- p.50 / Chapter 6.5 --- General Random Network --- p.53 / Chapter 6.6 --- Running Time Complexity --- p.55 / Chapter 7 --- Conclusion --- p.60 / Chapter A --- Step-Removal Algorithm --- p.62 / Chapter A.1 --- Step-Removal Algorithm[1] --- p.62 / Chapter A.2 --- Illustration of the efficiency of SRA --- p.63 / Chapter B --- Low-Disturbance Scheduling Algorithm --- p.65 / Chapter B.1 --- Low-Disturbance Scheduling Algorithm --- p.65

Le, Jilin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (p. 57-59). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- How Many Packets Can We Encode? --- p.2 / Chapter 1.2 --- Coding-Aware Routing --- p.3 / Chapter 2 --- Related Work --- p.6 / Chapter 3 --- Performance Analysis of COPE --- p.8 / Chapter 3.1 --- Introduction --- p.8 / Chapter 3.2 --- Coding Structure: Characterization and Properties --- p.9 / Chapter 3.2.1 --- Assumptions and notations --- p.9 / Chapter 3.2.2 --- Optimum Throughput in a Coding Structure --- p.10 / Chapter 3.2.3 --- The Upper Bound of Maximum Encoding Number --- p.11 / Chapter 3.3 --- Coding Performance under Random Access Link-Scheduling --- p.14 / Chapter 3.3.1 --- Key Intuition --- p.14 / Chapter 3.3.2 --- Calculating the Average Encoding Number --- p.15 / Chapter 3.3.3 --- Case Studies --- p.18 / Chapter 3.3.4 --- Will Delaying Strategy at the Coding Node Help? --- p.21 / Chapter 3.4 --- Fundamental Limits of the Coding Scheme --- p.22 / Chapter 3.5 --- Verification of the Analysis --- p.27 / Chapter 3.5.1 --- Simulation Results in a Single Coding Structure --- p.27 / Chapter 3.5.2 --- Simulation Results under 802.11 and General Networks --- p.29 / Chapter 3.6 --- Potential Applications --- p.31 / Chapter 3.7 --- Conclusion --- p.31 / Chapter 4 --- Distributed Coding-Aware Routing --- p.33 / Chapter 4.1 --- Introduction --- p.33 / Chapter 4.2 --- "The ""CodingH+Routing"" Discovery" --- p.34 / Chapter 4.2.1 --- Assumptions --- p.34 / Chapter 4.2.2 --- General Coding Conditions --- p.35 / Chapter 4.2.3 --- "Distributed ""Coding+Routing"" Discovery" --- p.36 / Chapter 4.2.4 --- An Illustrative Example --- p.38 / Chapter 4.2.5 --- Overheads of Coding+Routing Discovery --- p.39 / Chapter 4.3 --- Defining Coding-Aware Routing Metric --- p.40 / Chapter 4.3.1 --- Review of Current Routing Metrics --- p.40 / Chapter 4.3.2 --- Desirable Properties of Coding-aware Routing Metric --- p.42 / Chapter 4.3.3 --- Assumptions on Encoded Transmission --- p.42 / Chapter 4.3.4 --- "Interpreting the ""Free-Ride"" Benefit" --- p.43 / Chapter 4.3.5 --- Modified Queue Length --- p.44 / Chapter 4.3.6 --- MIQ: Modified Interference Queue Length --- p.46 / Chapter 4.3.7 --- CRM: Coding-aware Routing Metric --- p.47 / Chapter 4.4 --- Implementation Details --- p.48 / Chapter 4.5 --- Simulation Results --- p.49 / Chapter 4.5.1 --- Results from Illustrative Scenarios --- p.50 / Chapter 4.5.2 --- Results from Mesh Networks --- p.52 / Chapter 4.6 --- Conclusion --- p.55 / Chapter 5 --- Conclusion --- p.56 / Bibliography --- p.57

This thesis investigates the fundamental building blocks of physical-layer network coding (PNC). Most prior work on PNC focused on its application in a simple two-way-relay channel (TWRC) consisting of three nodes only. Studies of the application of PNC in general networks are relatively few. This thesis attempts to fill this gap by three steps: / In first step, we put forth two ideas: 1) A general network can be decomposed into small building blocks of PNC, referred to as the PNC atoms, for scheduling of PNC transmissions. 2) We identify nine PNC atoms, with TWRC being one of them. / In second step, we formulate the PNC scheduling problem as a linear program based on the atom-decomposition. Three major results are got from performance valuation: First, the throughput performance of PNC is shown to be significantly better than those of the traditional multi-hop scheme and the conventional network coding scheme. For example, under heavy traffic volume, PNC can achieve 100% throughput gain relative to the traditional multi-hop scheme. Second, PNC decomposition based on a variety of different PNC atoms can yield much better performance than PNC decomposition based on the TWRC atom alone. Third, three out of the nine atoms are most important to good performance. Specifically, the decomposition based on these three atoms is good enough most of the time, and it is not necessary to use the other six atoms. We have also designed a low-overhead MAC protocol to coordinate the transmissions of different nodes according to the scheduling results of PNC decomposition. / In third step, we investigate ARQ (Automatic Repeat request) designs for PNC systems (building blocks). The above building blocks studies assumed what is sent always get received. In practice, that is not the case. Error control is needed to ensure reliable communication. Here, we focus on the use of ARQ to ensure reliable PNC communication. In some of PNC building blocks, receivers can obtain side information through overhearing. Although such overheard information is not the target information that the receivers desire, the receivers can exploit the overheard information together with a network-coded packet received to obtain a desired native packet. This leads to throughput gain. The availability of overhead information and its potential exploitation make the ARQ design of a network-coded system different from that of a non-network-coded system. In this these, we lay out the fundamental considerations for such ARQ design: 1) We address how to track the stored coded packets and overheard packets to increase the chance of packet extraction, and derive the throughput gain achieved by tracking 2) We investigate two variations of PNC ARQ, coupled and non-coupled ARQs, and prove that non-coupled ARQ is more efficient; 3) We show how to optimize parameters in PNC ARQ—specifically the window size and ACK frequency—to minimize the throughput degradation caused by ACK feedback overhead and wasteful retransmissions due to lost ACK. Our throughput analyses and performance evaluations indicate that for our investigated atoms, our PNC ARQ yield considerable throughput gains. / In a conclusion, the decomposition based on a variety of different PNC atoms that we investigated can yield much better performance than the traditional multi-hop scheme and the conventional network coding scheme. In practical wireless systems where transmission errors can occur, adopting our PNC ARQ design can efficiently maintain the throughput gain achieved by PNC atom decomposition. / 本論文致力於研究基於物理層網絡編碼（PNC, Physical-layer Network Coding）的基礎構建模塊。現有的物理層網絡編碼的研究大都基於最簡單的雙向中繼信道（TWRC）系統上。TWRC是一個由三節點組成的小型通信網絡——兩個終端節點通過一個中繼節點通信。而基於大型網絡應用的PNC研究卻非常少見。為了填補這一空白，本論文分三步驟進行PNC研究: / 研究第一步，我們提出兩個問題： 1）為了PNC網絡調度，一個網絡可以被分解成若干小的PNC基礎構建模塊。 2）我們發現了除9個基本的PNC構建模塊（包含PNC TWRC）。 / 研究第二步，我們通過建立基於模塊分解的線性規劃方程來解決PNC網絡的調度問題。從性能評估中我們發現了三個重要結論： 第一，PNC分解的輸出效率遠高於傳統的多步傳輸和普通的網絡編碼傳輸。例如，在網絡運輸量很重的情況下，相比于傳統的多步傳輸，PNC分解傳輸可以取得100%輸出增益。第二，基於多種不同PNC模塊的分解傳輸，其效率高於只基於PNC TWRC的分解傳輸。第三，在我們研究的九個模塊中，三個模塊對輸出的貢獻最多。我們同時為PNC調度專門設計了介質訪問控制（MAC）的網絡協議。 / 研究第三步，我們研究了PNC系統的自動重傳請求（ARQ）設計。上述的PNC模塊研究假設了網絡的傳送總能被成功接收。但不符合實際的網絡狀況。需要採取錯誤控制來保護實際傳輸的穩定性。這裡，我們致力於研究用ARQ來保證PNC系統的穩定傳輸。在一些PNC模塊中，接受點可以利用旁聽到的信息包裹來解碼編碼過的包裹以獲得需要的自然包裹。這種對於旁聽信息的利用可以增加網絡的傳輸效率。同時也使PNC系統的ARQ設計不同於傳統網絡。在本論文中，我們列舉了三個基本的PNC ARQ設計原則： 1）我們強調了如何追蹤存儲的和旁聽到的信息包裹來增加提取有效包裹的機會并推導出了由此取得效率增益。 2）我們研究了兩種PNC ARQ系統，一種是綁定的ARQ，一種是非綁定的ARQ,并證明非綁定的ARQ效率更高。 3）我們展示了如何優化PNC ARQ的參數設置——傳輸窗口的大小和確認通知（ACK）的頻率——以最小化由ACK開銷和不必要的重傳引起的輸出損失。 / 總結來講，基於不同PNC模塊的網絡分解調度方法比傳統的多步傳輸方法和普通的網絡編碼傳輸更有效率。在實際的無線網絡中，當網絡傳輸出現錯誤時，採用我們的PNC自動重傳設計可以有效的保留PNC模塊分解所取得網絡增益。 / He, Jianghao. / Thesis Ph.D. Chinese University of Hong Kong 2015. / Includes bibliographical references (leaves 126-128). / Abstracts also in Chinese. / Title from PDF title page (viewed on 24, October, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

Xu, Ceng. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (p. 68-71). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.3 / Chapter 1.2 --- Contributions --- p.5 / Chapter 1.3 --- Thesis Scope --- p.5 / Chapter 2 --- Background Study --- p.6 / Chapter 2.1 --- Wireless Mesh Networks --- p.6 / Chapter 2.1.1 --- Overview of Wireless Mesh Networks --- p.6 / Chapter 2.1.2 --- Challenges of Wireless Mesh Networks --- p.9 / Chapter 2.1.3 --- Capacity Analysis of Wireless Mesh Net- works --- p.11 / Chapter 2.2 --- Network Coding --- p.13 / Chapter 2.2.1 --- Overview of Network Coding --- p.13 / Chapter 2.2.2 --- Network Coding in Wireless Networks --- p.17 / Chapter 3 --- Throughput Analysis --- p.19 / Chapter 3.1 --- Introduction --- p.19 / Chapter 3.2 --- Preliminaries --- p.20 / Chapter 3.3 --- Proof of Theorem 3.2.1 when n = m --- p.23 / Chapter 3.4 --- Proof of Theorem 3.2.1 when n≠ m --- p.36 / Chapter 3.4.1 --- Proof of Theorem 3.2.1 when m <n --- p.36 / Chapter 3.4.2 --- Proof of Theorem 3.2.1 when m > n --- p.37 / Chapter 3.5 --- Applying network coding into multi-radio multichannel networks --- p.37 / Chapter 3.6 --- Some simulation results --- p.40 / Chapter 3.6.1 --- String Topology --- p.40 / Chapter 3.6.2 --- Grid Topology --- p.41 / Chapter 3.6.3 --- Random Topology --- p.42 / Chapter 4 --- Interface Reduction in Wireless Mesh Networks --- p.43 / Chapter 4.1 --- Introduction --- p.43 / Chapter 4.2 --- Preliminaries --- p.44 / Chapter 4.2.1 --- Assumptions and Objectives of the Algorithm --- p.44 / Chapter 4.2.2 --- Definitions --- p.45 / Chapter 4.3 --- Steps of the Algorithm and an Example --- p.49 / Chapter 4.4 --- Simulation Results and Discussions --- p.53 / Chapter 4.5 --- Generalization --- p.54 / Chapter 5 --- Conclusion --- p.66 / Bibliography --- p.68