本论文开发出了一个全新的理论和算法框架用於无线网络的分布式功率控制。我们提出两种快速分布式功率控制算法，并对此作了深入的研究。 此种算法相当普适，比如适用于目前热门的LTE和认知无线电网络。 它在解的最优性以及收敛速度等方面击败了著名的高通公司的"荷载溢出型分布式功率控制算法" (收录于重要论文[HandeRanganChiangWu08] )以及"分布式加权比例型信干噪比均衡算法" (收录于重要论文[TanChiangSrikant 11)。 / 作为一个重要而富有挑战性的研究课题，通过分布式功率控制达至无线网络效用的最大化一直受到业界的普遍关注。 这方面的研究通常把问题表述为一个最优化问题，即在某些功率约束条件下，优化整体系统的效用函数。 (其中，系统的效用函数通常是各无线收发链路的信干噪比的增函数。 )此问题已经有了不错的集中式解决方案，但成本更低廉、更易于布置、更为实用的分布式解决方案则欠奉，尤其是经严格证明可行的分布式解决方案。 这是因为分布式算法一般只适用于相对简单或者有特殊结构的优化问题。 而无线设备之间的相互干扰和各自信号功率之间的复杂关系使得分布式求解极其困难。 在算法设计上，很小的疏漏就可能导致解决方案无效或者不收敛。 例如，尽管论文[HandeRanganChiangWu08] 和[TanChiangSrikant 11] 都声称各自的分布式算法提供了问题的最优解，但我们通过大量的仿真实验以及理论研究发现并非如此。 我们发现"荷载溢出型分布式功率控制算法"时常要么无法收敛，要么收敛得极其慢。而"分布式加权比例型信干噪比均衡算法"则经常在几次迭代之後就已经发散。 / 我们开发出了全新的分析和算法框架，并将其推广到适用于一般线性功率约束的情况。(前述论文的分析框架是基于某些非常特殊的线性功率约束。)在此基础上，我们逐一找出了前述算法中的错漏之处，并设计出我们的分布式梯度投影功率控制算法，以及与之相匹配的步长规则。 我们严格证明了该步长规则的有效性和算法的收敛性、最优性，并给出了算法复杂度的分析。(相较之下， [HandeRanganChiangWu08] 在算法收敛性证明上语焉不详，在其它方面则付之阙如;而[TanChiangSrikant 11] 的算法收敛性证明存在明显错误，在其它方面同样付之阙如。 )在某些情况下，我们的算法可以进一步提速并提升运行性能。 大量的仿真实验证实我们的算法在解的最优性和运行速度两方面都较前述算法优越。在某些情况下，我们算法的收敛速度上百倍快于前述算法。 / 总而言之，本论文成功解决了重要的效用优化问题并取得比前述论文更好的结果。它开发出全新的理论和算法框架，完全解决了步长规则和收敛性、最优性这些难题。展望未来，我们相信，本论文为快速功率控制在无线和移动解决方案中的应用打下了坚实的理论基础。 我们期待该理论框架能够提供更多問題的解決方案。 / This thesis develops a new theoretical and algorithmic framework for practical distributed power control in wireless networks. It proposes and investigates fast optimal distributed power control algorithms applicable to LTE as well as cognitive radio. The proposed algorithms beat the well-known Qualcomm's load-spillage distributed power control algorithm in [HandeRan-ganChiangWu08] and the distributed weighted proportional SINR algorithm in [TanChiangSrikant11] in terms of both the optimality of the solution and the convergence speed. / Wireless network utility maximization via distributed power control is a classical and challenging issue that has attracted much research attention. The problem is often formulated as a system utility optimization problem under some transmit power constraints, where the system utility function is typically an increasing function of link signal-to-interference-plus-noise-ratio (SINR). This problem is complicated by the fact that these wireless devices may interfere with each other. In particular, the wireless devices are affected by each other's transmit power, and the transmit powers and interferences experienced by the devices are interwoven in a complex manner. / Despite that, there have been good centralized algorithms for solving the problem. "Decentralized" solutions, on the other hand, are a different story. In practice, decentralized algorithms in which the devices interact with each other in a loosely coupled manner to improve the network utility, are easier to deploy than centralized algorithms. However, the design of workable (and provably workable in the mathematical sense) solution is very challenging. Small neglects can lead to solutions that are invalid or non-convergent. For example, although both papers [HandeRanganChiangWu08] and [TanChiangSrikant11] claim their distributed algorithms to be optimal, we discover some experimental evidence suggesting that certain parts of these algorithms are not quite right. Oftentimes, the former fails to converge or converges extremely slowly, while the latter could diverge in the first few iterations. / To fix these glitches and to broaden the scope of the problem, we develop a new analytical and algorithmic framework with a more general formulation. With this framework, we can identify the sources of the defects and shortcomings of prior algorithms. We further construct an optimal distributed (sub)gradient projection algorithm with provably valid step size rules. Rigorous convergence proof and complexity analysis for our algorithm are given (note: convergence proof and complexity analysis were missing in [HandeRanganChiangWu08] and incorrect in [TanChiangSrikant11]). In some scenarios, our algorithm can be further accelerated to yield even better performance. Extensive simulation experiments confirm that our algorithms always outperform the prior algorithms, in terms of both optimality and efficiency. Specifically, simulation demonstrates at least 100 times faster convergence than the prior algorithms under certain scenarios. / In summary, this thesis solves the important SINR-based utility maximization problem and achieves significantly better results than existing work. It develops a new theoretical an dalgorithmic framework which completely addresses the difficult convergence and step-size issues. Going forward, we believe the foundation established in this work will open doors to other fast distributed wireless and mobile solutions to problems beyond the power control problem addressed here. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Zhang, Jialiang. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 83-87). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Thesis Organization --- p.6 / Chapter 1.3 --- Notations --- p.7 / Chapter 2 --- System Model and Problem Formulation --- p.8 / Chapter 2.1 --- System Model --- p.8 / Chapter 2.2 --- Nonnegative Linear Power Constraints --- p.9 / Chapter 2.3 --- Network Utility --- p.10 / Chapter 2.4 --- Problem Formulation --- p.11 / Chapter 2.5 --- Characterization of T[subscript c] --- p.13 / Chapter 2.6 --- Multiple Constraints --- p.16 / Chapter 3 --- Nice Properties of SINR Constraints --- p.18 / Chapter 3.1 --- Convexity, Differentiability and Monotonicity --- p.19 / Chapter 3.2 --- Fast Distributed Gradient Computation --- p.20 / Chapter 3.2.1 --- Distributed SINR-Driven Single-Constrained Power Control --- p.21 / Chapter 3.2.2 --- Network Duality --- p.23 / Chapter 3.3 --- The Case of Multiple Constraints --- p.27 / Chapter 4 --- Network Utility Maximization in Log-SINR Domain --- p.32 / Chapter 4.1 --- Single Active Constraint and Ascent Directions --- p.34 / Chapter 4.2 --- Multiple Constraints and Subgradient Projection --- p.39 / Chapter 4.3 --- Unconstrained Equivalence and Complexity results of M = 1 --- p.46 / Chapter 4.4 --- Simulation Experiments --- p.52 / Chapter 4.4.1 --- Simulation Settings --- p.52 / Chapter 4.4.2 --- Negative results of algorithm 6 in [7] --- p.54 / Chapter 4.4.3 --- Negative results of Qualcomm’s load-spillage algorithm in [25] --- p.56 / Chapter 4.4.4 --- More results of our algorithms --- p.62 / Chapter 5 --- Related Work --- p.64 / Chapter 6 --- Conclusion --- p.68 / Chapter 7 --- Appendix --- p.72

本論文研究非同步物理層網絡編碼(PNC) 系統。本文由兩部分構成。在第一部分中，我們提出了一個物理層網絡編碼整體框架，來處理碼元和載波相位異步問題。基於上述框架，本文證明了非同步的物理層網絡編碼可以提高系統性能。本文的第一個重要貢獻在於，不同於以往的主要理解，我們發現在採取適當的解碼方案後，非同步問題並不會降低系統性能。在第二部分中，我們通過理論和實際系統展示了物理層網絡編碼的原型機。特別是，我們採用正交頻分複用(OFDM) 系統，來解決時域的碼元非同步問題。本文的第二個重要貢獻在於，該工作是自五年前物理層網絡編碼理論提出之後，第一個真正的應用系統。 / 第一部分:在本文的第一部分里， 我們研究物理層網絡編碼系統中存在的碼元和載波相位異步問題。在物理層網絡編碼系統中，一個關鍵的問題是，接收機如何處理不同發射機發送的信號之間存在的不同步問題。也就是說，不同的發射機發送的信號達到接收機的時候，存在碼元移位的相位相對偏差。另一個關鍵的問題是，如何將信道編碼投衛和物理層網絡編碼相結合，來實現可靠的信息傳輸。本文研究上迷兩個重要問題，並且有如下四個主要貢獻1)我們提出並且分析了一個基於置信度傳遞(BP) 的物理層網絡編碼整體框架。該框架可以高效地解決碼元和相位異步問題，並且適用於有信道編碼的系統。2) 對於未經信道編碼的物理層網絡編碼系統， 在BPSK 和QPSK 調製下，我們的BP 算法可以顯著地降低非同步帶來的系統性能損失。3) 對於未經信道編碼的物理層網絡編碼系統，在相對碼元偏移為半碼元長度時，我們的BP 算法可以有效地將相位異步帶來的系統性能損失從6dB 降低到不足1dB。4) 對於經過信道編碼的物理層網絡編碼系統，在應用BP 算法後，異步系統性能優於同步系統。最後，在經過信道編碼的物理層網絡編碼系統中， 我們發現由各種碼元和相位異步組合產生的性能損失不超過ldB。上述貢獻3) 說明，如果我們可以精確地控制信號接收時間，那麼人為產生半個碼元偏移會給未經信道編碼的物理層網絡編碼系統帶來好處。上述貢獻4）說明，在採用了信道編碼後，碼元和相位非同步， 將不再是物理層網絡編碼一個主要擔憂的問題。 / 第二部分:在本文的第二部分里，我們展示了第一個物理層網絡編碼原型機的實現過程，這個原型機可以應用於雙向中繼網絡(TWRC) 。截至目前，僅有簡化的物理層網絡編碼系統，稱作模擬網絡編碼(ANC) 投街，被成功實現。模擬網絡編碼的好處在於它的簡單和容易實現;而它的缺點則是，中繼節點在放大信號的同時也放大了噪聲，因而帶來系統性能損失。在物理層網絡編碼系統中，中繼節點只有實現異或(XOR) 運算或者是去噪聲(denoising) PNC 映射，才能能顯著地提高系統性能。但是，要實現上途的XOR PNC 系統我們需要面對很多挑戰。比如， 中繼節點必須能夠處理接收信號的碼元和相位的異步問題，並且可以在解碼前實現信道估計。本文研究頻域物理曾網絡編碼實現，命名為FPNC，來解決上述問題。FPNC 基於OFDM 調製方式實現。在FPNC 系統中， XOR 映射發生在每一個OFDM 碼元的各個子載波上，而不是在時域的採樣點上。我們在通用軟件無線電設備(USRP) 平臺上實現了上述FPNC 系統。需要強調的是，我們的FPNC 實現僅需稍微修改現有的802. lla/g OFDM系統物理層前導序列。在循環前綴(CP) 的幫助下，碼元異步和多經效應都可以被相應地去除。實驗結果顯示，對於經過信道編碼的和未經信道編碼的FPNC 系統，碼元同步系統和碼元異步系統性能沒有區別。 / This thesis investigates asynchronous physical-layer network coding (PNC) systems. It consists of two parts, each part contains a major contribution within the domain of PNC research. The first part presents a theoretical framework for dealing with phase and symbol asynchronies in PNC. We show how this framework can turn asynchronies to an advantage to boost system performance. The major contribution here is the insight that, contrary to the prior belief, asynchrony is not detrimental to the performance of PNC systems with the right methods to deal with it. The second part reports the first PNC implementation prototype. In particular, we demonstrate both in theory and practice that using OFDM in the PNC system can remove the symbol asynchrony in the time domain. The major contribution here is that this is the first experimental feasibility demonstration of the PNC concept since it was conceived theoretically five years ago. / Part I: In the first part of this thesis, we study the phase and symbol asynchrony problems in PNC. A key issue in physical-layer network coding (PNC) is how to deal with the asynchrony between signals transmitted by multiple transmitters. That is, symbols transmitted by different transmitters could arrive at the receiver with symbol misalignment as well as relative carrier-phase offset. A second important issue is how to integrate channel coding with PNC to achieve reliable communication. This thesis investigates these two issues and makes the following contributions: 1) We propose and investigate a general framework for decoding at the receiver based on belief propagation (BP). The framework can effectively deal with symbol and phase asynchronies while incorporating channel coding at the same time. 2) For non-channelcoded PNC, we show that for BPSK and QPSK modulations, our BP method can significantly reduce the asynchrony penalties compared with prior methods. 3) For non-channel-coded PNC, with half symbol offset between the transmitters, our BP method can drastically reduce the performance penalty due to phase asynchrony, from more than 6 dB to no more than 1 dB. 4) For channel-coded PNC, with our BP method, both symbol and phase asynchronies actually improve the system performance compared with the perfectly synchronous case. Furthermore, the performance spread due to different combinations of symbol and phase offsets between the transmitters in channel-coded PNC is only around 1 dB. The implication of 3) is that if we could control the symbol arrival times at the receiver, it would be advantageous to deliberately introduce a half symbol offset in non-channel-coded PNC. The implication of 4) is that when channel coding is used, symbol and phase asynchronies are not major performance concerns in PNC. / Part II: In the second part of this thesis, we present the first implementaii tion of a two-way relay network based on the principle of physical-layer network coding. To date, only a simplified version of physical-layer network coding (PNC) method, called analog network coding (ANC), has been successfully implemented. The advantage of ANC is that it is simple to implement; the disadvantage, on the other hand, is that the relay amplifies the noise along with the signal before forwarding the signal. PNC systems in which the relay performs XOR or other denoising PNC mappings of the received signal have the potential for significantly better performance. However, the implementation of such PNC systems poses many challenges. For example, the relay must be able to deal with symbol and carrier-phase asynchronies of the simultaneous signals received from the two end nodes, and the relay must perform channel estimation before detecting the signals. We investigate a PNC implementation in the frequency domain, referred to as FPNC, to tackle these challenges. FPNC is based on OFDM. In FPNC, XOR mapping is performed on the OFDM samples in each subcarrier rather than on the samples in the time domain. We implement FPNC on the universal soft radio peripheral (USRP) platform. Our implementation requires only moderate modifications of the packet preamble design of 802.11a/g OFDM PHY. With the help of the cyclic prefix (CP) in OFDM, symbol asynchrony and the multi-path fading effects can be dealt with in a similar fashion. Our experimental results show that symbol-synchronous and symbol-asynchronous FPNC have essentially the same BER performance, for both channel-coded and non-channelcoded FPNC. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Lu, Lu. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 123-128). / 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.viii / Publications --- p.x / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Asynchrony Problems in Physical-Layer Network Coding --- p.3 / Chapter 1.2 --- Implementation of Physical-Layer Network Coding --- p.4 / Chapter 1.3 --- Outline of the Thesis --- p.5 / Chapter 2 --- Asynchronous PNC --- p.7 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Related Work --- p.10 / Chapter 2.2.1 --- Classification --- p.11 / Chapter 2.2.2 --- Non-channel-coded PNC --- p.11 / Chapter 2.2.3 --- Channel-coded PNC --- p.12 / Chapter 2.3 --- System Model --- p.14 / Chapter 2.4 --- Non-channel-coded PNC --- p.19 / Chapter 2.4.1 --- Synchronous Non-channel-coded PNC --- p.19 / Chapter 2.4.2 --- BP-UPNC: A Belief Propagation based Non-channelcoded PNC Scheme --- p.20 / Chapter 2.4.3 --- Numerical Results --- p.27 / Chapter 2.4.4 --- Diversity and Certainty Propagation --- p.29 / Chapter 2.5 --- Channel-coded PNC --- p.33 / Chapter 2.5.1 --- Channel-decoding and Network-Coding (CNC) Process --- p.34 / Chapter 2.5.2 --- Jt-CNC: A Joint Channel-decoding and Network-Coding Scheme --- p.36 / Chapter 2.5.3 --- XOR-CD: A Disjoint Channel-decoding and Network-Coding Scheme --- p.40 / Chapter 2.5.4 --- Numerical Results --- p.43 / Chapter 2.5.5 --- Shannon Limits for Gaussian Channel --- p.48 / Chapter 2.5.6 --- Diversity and Certainty Propagation in Jt-CNC --- p.50 / Chapter 2.6 --- Conclusions --- p.51 / Chapter 3 --- Implementation of Asynchronous PNC --- p.54 / Chapter 3.1 --- Introduction --- p.54 / Chapter 3.1.1 --- Challenges --- p.56 / Chapter 3.2 --- Effect of Delay Asynchrony in Frequency Domain --- p.60 / Chapter 3.2.1 --- Effective Discrete-time Channel Gains --- p.60 / Chapter 3.2.2 --- Delay-Spread-Within-CP Requirement --- p.63 / Chapter 3.3 --- FPNC Frame Format --- p.66 / Chapter 3.3.1 --- FPNC Short Training Symbol --- p.68 / Chapter 3.3.2 --- FPNC Long Training Symbol --- p.69 / Chapter 3.3.3 --- FPNC Pilot --- p.70 / Chapter 3.4 --- Addressing Key Implementation Challenges in FPNC --- p.71 / Chapter 3.4.1 --- FPNC Carrier Frequency Offset (CFO) Compensation --- p.71 / Chapter 3.4.2 --- FPNC Channel Estimation --- p.75 / Chapter 3.4.3 --- FPNC Mapping --- p.76 / Chapter 3.5 --- Experimental Results --- p.80 / Chapter 3.5.1 --- FPNC Implementation over Software Radio Platform --- p.80 / Chapter 3.5.2 --- Experimental Results --- p.81 / Chapter 3.6 --- Conclusions --- p.88 / Chapter 4 --- Conclusions and Future Work --- p.90 / Chapter 4.1 --- Conclusions --- p.90 / Chapter 4.2 --- Future Work --- p.92 / Chapter 4.2.1 --- Asynchronous PNC --- p.93 / Chapter 4.2.2 --- Implementation of PNC --- p.94 / Chapter A --- Message Update Steps of Jt-CNC --- p.97 / Chapter A.1 --- Step 1. Updates of messages below code nodes X: --- p.98 / Chapter A.2 --- Step 2. Updates of upward messages into check nodes C: --- p.98 / Chapter A.3 --- Step 3. Update of upward messages into the source nodes S: --- p.99 / Chapter A.4 --- Step 4. Update of downward messages into the check nodes C: --- p.100 / Chapter A.5 --- Step 5. Updates of downward messages into code nodes X: --- p.100 / Chapter B --- Channel-coded Collision Resolution --- p.101 / Chapter B.1 --- Introduction --- p.101 / Chapter B.2 --- System Model --- p.103 / Chapter B.3 --- C-CRESM --- p.105 / Chapter B.3.1 --- Review of RA code --- p.106 / Chapter B.3.2 --- Virtual Tanner Graph for RA coded CRESM --- p.107 / Chapter B.3.3 --- Definitions --- p.108 / Chapter B.3.4 --- Message Update Rules --- p.109 / Chapter B.4 --- Comparison of Different Methods --- p.115 / Chapter B.4.1 --- Independent Multiuser Detection and Channel Decoding (Independent MU-CD) --- p.116 / Chapter B.4.2 --- Turbo-SIC --- p.117 / Chapter B.4.3 --- Channel-coded CRESM (C-CRESM) --- p.118 / Chapter B.5 --- Simulation Results --- p.119 / Chapter B.6 --- Conclusion --- p.121 / Bibliography --- p.123

這篇論文示主要討論在信息不完全情況下的無線網絡資源分配的兩個問題。傳輸節點不固定和信道狀態的不確定性將影響資源分配的選擇。因為不完整的信息，或在這些情況下可能無法確切獲得準確的信息，將對資源優化配置產生一定的影響。對於不完整信息對無線網路的影響，其中用戶的移動性和信道增益的不確定性，將是本論文中討論的兩個主要問題。 / 本論文的第一部分是關於移動傳輸節點的資源分配問題。我們主要分析上行系統的移動用戶，其中每個用戶會盡量優化他或她自己的功效函數，以達到最佳的性能。此外，我們提出對移動用戶的功率分配優化的方案當所有信道信息可用的時候。此外，我們提出了幫助每個用戶預測信道信息總幹擾來優化功效函數，當信息不完備的時候。這形成了一個不完全信息博弈。我們提出了預測的規則，幫助動態預測總幹擾。我們採用了卡爾曼濾波器來處理測量噪聲 我們也說明了利用預測來優化的功效函數和由完整的信息得出的之間的差異。此外，從動態規劃，我們在預測的基礎上給出一個動態的功率分配方案。 / 第二部分討論了在資源分配時，當有關信道增益是不完整時的不確定規劑。我們主要考慮認知無線電模型。在第二部分中，我們考慮，當二級用戶的干擾不會超過一定限制時，他們能夠使用共享的頻率的情況。我們首先利用約束幹擾的限制進行建模，使得二級用戶的干擾，即使在最壞的情況下，也不會超過限制，這將有助於他或她以避免不可行的解決方案。然後，我們擴展我們的概率約束條件來代表不確定性的干擾限制。由於概率約束一般都是難以解決的，而基於無線信道的衰落效應，有關變量的完整的信息是很難獲得。我們重新將概率約束條件轉化為隨機期望約束條件。利用樣本平均近似法，我們提出了隨機學習算法，以幫助次級用戶從主要用戶那裡獲得反饋信息，最大限度地提高自己的功效函數。此外，我們分析了在認知無線電網絡定價條件的頻譜共享方案。我們展示的聯合優化配置方案，幫助次級用戶從主要用戶購買頻譜和優化功率。當有信道增益的不確定性時，二級用戶希望最大限度地提高功效函數的期望值並且採用相對穩定的採購策略追求最佳平均收益。它是一個有鞍點的隨機優化問題。我們展示一個分佈式的隨機算法，以幫助二級用戶更新資源分配策略。在一些實際的情況下，為了減少計算複雜性和希望實施越來較為容易，我們利用迭代平均來為二級用戶進行資源配置。 / Two main issues of resource allocation in wireless networks with incomplete information are addressed in this thesis. Transmission node is not fixed in the wireless system and uncertainties of the channel states would also affect the choices of resource allocation, since full information cannot be provided or may not be exact under these scenarios. For incomplete information in wireless networks, mobility of the users and uncertainties of channel gains are two main issues that would be considered in this thesis. / The first part of this thesis is concerning the resource allocation problems with mobile trans- mission nodes. We consider mobile users in an up-link system. We analyze the mobile system where each user would try to maximize his or her own utility to achieve the best performance. Besides, we propose a power allocation scheme for the mobile users when all channel information is available. We show that our model can form a game. Moreover, we illustrate that each user would expect to predict the aggregate interference to maximize the utility when channel information is incomplete. It can be shown that this forms a game with incomplete information. We demonstrate the prediction rules which help predict the aggregate interference dynamically. We apply the Kalman filter to tackle measurement noises. We also illustrate the bound on the difference between the utility with prediction and that with complete information. Moreover, applying dynamic programming, we give a dynamic power allocation scheme based on the predictions. / The second part discusses the issue of uncertain programming in resource allocation when information about channel gains is incomplete. We mainly consider the model of cognitive radio networks. We introduce a resource allocation scheme for secondary users with spectrum sharing in a cognitive radio network. Secondary users can exploit the spectrum owned by primary links when their interference level does not exceed certain requirements. We first model the interfer- ence constraints as robust constraints such that secondary users would satisfy the interference constraints even under the worst cases, which would help him or her to avoid the unfeasible solutions. We then extend our consideration of the interference constraints as chance constraints to represent uncertainties. Since chance constraints are generally difficult to solve and full in- formation about the uncertain variables is not available due to the fading effects of wireless channels, we reformulate the constraints into stochastic expectation constraints. With sample average approximation method, we propose stochastic distributed learning algorithms to help secondary users satisfy the constraints with the feedback information from primary links when maximizing the utilities. Moreover, we introduce a resource allocation scheme for secondary users to share spectrum and optimize usage of power with pricing. Secondary users need to buy spectrum from primary users. In the process, secondary users also enhance the utilization of the unused bandwidth by primary users. We first demonstrate the resource allocation scheme when full information about channel gains is available. When there are uncertainties of channel gains, secondary users would like to maximize the expected value of the utilities to pursue the best benefits on average with relatively stable buying strategies. It can be shown that it is a stochastic optimization problem with saddle points. We demonstrate a Distributed Stochastic Algorithm to help secondary users update their resource allocation strategies. For some practical scenarios, to reduce computation complexity and make implementation easy, we illustrate an Iterate Average from Distributed Stochastic Algorithm for secondary users. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Zhou, Kenan. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 123-134). / 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.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivations --- p.1 / Chapter 1.2 --- Contributions and Outline of the Thesis --- p.2 / Chapter 2 --- Background Study --- p.5 / Chapter 2.1 --- Slow and Flat Fading Wireless Channel --- p.5 / Chapter 2.2 --- Cognitive Radio Networks --- p.7 / Chapter 2.3 --- Multiple-Access Channel --- p.8 / Chapter 2.4 --- Mobility Model --- p.10 / Chapter 2.5 --- Convex Optimization --- p.12 / Chapter 2.6 --- Uncertain Programming --- p.13 / Chapter 2.7 --- Game Theory --- p.14 / Chapter Part I --- Resource Allocation in Wireless Networks with Mobility --- p.16 / Chapter 3 --- Resource Allocation with Mobile Users in an Up-link System --- p.19 / Chapter 3.1 --- System Model --- p.20 / Chapter 3.2 --- Power Allocation for Mobile Users with Complete Information --- p.22 / Chapter 3.3 --- Power Allocation with Incomplete Information --- p.26 / Chapter 3.3.1 --- Bound on the difference between the utility with prediction and that with complete information --- p.27 / Chapter 3.3.2 --- Prediction Scheme for Incomplete Channel Information --- p.30 / Chapter 3.3.3 --- Power Allocation with Dynamic Programming --- p.32 / Chapter 3.4 --- Numerical results and discussion --- p.35 / Chapter 3.4.1 --- Simulation Model --- p.35 / Chapter 3.4.2 --- Numerical Results --- p.36 / Chapter 3.5 --- Chapter Summary --- p.42 / Chapter 3.6 --- Appendices --- p.44 / Chapter 3.6.1 --- Proof of Theorem 3.1 --- p.44 / Chapter 3.6.2 --- Proof of Theorem 3.2 --- p.47 / Chapter Part II --- Resource Allocation inWireless Networks with Uncertain Programming --- p.48 / Chapter 4 --- Resource Allocation with Robust Optimization --- p.52 / Chapter 4.1 --- System Model --- p.52 / Chapter 4.2 --- Resource Allocation with Robust Optimization Approach --- p.54 / Chapter 4.3 --- Trade-Off Between Robustness and Performance --- p.59 / Chapter 4.4 --- Numerical results and discussion --- p.62 / Chapter 4.4.1 --- Choice of the Penalty Function --- p.62 / Chapter 4.4.2 --- Simulation Model --- p.63 / Chapter 4.4.3 --- Simulation Results --- p.64 / Chapter 4.5 --- Chapter Summary --- p.65 / Chapter 5 --- Resource Allocation with Chance Constraints --- p.67 / Chapter 5.1 --- System Model --- p.68 / Chapter 5.2 --- Power Allocation with Complete Information about Probabilistic Constraints --- p.69 / Chapter 5.3 --- A Stochastic Approximation Approach Based on the Outage Event --- p.72 / Chapter 5.3.1 --- Feasibility of the Stochastic Approximation Method --- p.74 / Chapter 5.3.2 --- Stochastic Distributed Learning Algorithm I (SDLA-I) --- p.76 / Chapter 5.3.3 --- Stochastic Distributed Learning Algorithm II (SDLA-II) --- p.80 / Chapter 5.4 --- Numerical Results and Discussion --- p.82 / Chapter 5.4.1 --- Examples of uk(.) for Simulation --- p.82 / Chapter 5.4.2 --- Simulation Model --- p.83 / Chapter 5.4.3 --- Simulation Results and Discussions --- p.84 / Chapter 5.5 --- Chapter Summary --- p.86 / Chapter 5.6 --- Appendices --- p.88 / Chapter 5.6.1 --- Proof of Lemma 5.3 --- p.88 / Chapter 6 --- Priced Resource Allocation with Stochastic Optimization --- p.90 / Chapter 6.1 --- System Model --- p.91 / Chapter 6.2 --- Price-Based Optimization with Complete Information --- p.94 / Chapter 6.3 --- Price-Based Stochastic Optimization with Uncertainties --- p.96 / Chapter 6.4 --- Distributed Stochastic Algorithms for the Price-Based Stochastic Optimization --- p.100 / Chapter 6.4.1 --- Iterate Averages of DSA --- p.104 / Chapter 6.5 --- Numerical Results and Discussion --- p.106 / Chapter 6.5.1 --- Simulation Model --- p.106 / Chapter 6.5.2 --- Numerical Results --- p.107 / Chapter 6.6 --- Chapter Summary --- p.112 / Chapter 6.7 --- Appendices --- p.113 / Chapter 6.7.1 --- Proof of Lemma 6.1 --- p.113 / Chapter 6.7.2 --- Proof of Proposition 6.1 --- p.114 / Chapter 6.7.3 --- Proof of Lemma 6.3 --- p.114 / Chapter 6.7.4 --- Proof of Lemma 6.4 --- p.115 / Chapter 6.7.5 --- Proof of Proposition 6.2 --- p.116 / Chapter 7 --- Conclusion and Future Work --- p.117 / Chapter 7.1 --- Conclusion --- p.117 / Chapter 7.2 --- Future Work --- p.119 / Chapter 7.2.1 --- Joint Power and Channel Access Scheduling for Mobile Users --- p.119 / Chapter 7.2.2 --- Power Control for Heterogeneous Mobile Users --- p.120 / Chapter 7.2.3 --- More on Uncertain Programming in Cognitive Radios --- p.120 / Chapter 7.2.4 --- Transmissions in Complex Networks with Uncertainties --- p.121 / Chapter 7.2.5 --- Secure Transmissions in Wireless Networks with Uncertainties --- p.122 / Bibliography --- p.123

"In modern wireless communication systems, intersymbol interference (ISI) introduced by frequency selective fading is one of the major impairments to reliable data communication. In ISI channels, the receiver observes the superposition of multiple delayed reflections of the transmitted signal, which will result errors in the decision device. As the data rate increases, the effect of ISI becomes severe. To combat ISI, equalization is usually required for symbol detectors. The optimal maximum-likelihood sequence estimation (MLSE) based on the Viterbi algorithm (VA) may be used to estimate the transmitted sequence in the presence of the ISI. However, the computational complexity of the MLSE increases exponentially with the length of the channel impulse response (CIR). Even in channels which do not exhibit significant time dispersion, the length of the CIR will effectively increase as the sampling rate goes higher. Thus the optimal MLSE is impractical to implement in the majority of practical wireless applications. This dissertation is devoted to exploring practically implementable symbol detectors with near-optimal performance in wireless ISI channels. Particularly, we focus on the design and implementation of an iterative detector based on the belief propagation (BP) algorithm. The advantage of the BP detector is that its complexity is solely dependent on the number of nonzero coefficients in the CIR, instead of the length of the CIR. We also extend the work of BP detector design for various wireless applications. Firstly, we present a partial response BP (PRBP) symbol detector with near-optimal performance for channels which have long spanning durations but sparse multipath structure. We implement the architecture by cascading an adaptive linear equalizer (LE) with a BP detector. The channel is first partially equalized by the LE to a target impulse response (TIR) with only a few nonzero coefficients remaining. The residual ISI is then canceled by a more sophisticated BP detector. With the cascaded LE-BP structure, the symbol detector is capable to achieve a near-optimal error rate performance with acceptable implementation complexity. Moreover, we present a pipeline high-throughput implementation of the detector for channel length 30 with quadrature phase-shift keying (QPSK) modulation. The detector can achieve a maximum throughput of 206 Mb/s with an estimated core area of 3.162 mm^{2} using 90-nm technology node. At a target frequency of 515 MHz, the dynamic power is about 1.096 W. Secondly, we investigate the performance of aforementioned PRBP detector under a more generic 3G channel rather than the sparse channel. Another suboptimal partial response maximum-likelihood (PRML) detector is considered for comparison. Similar to the PRBP detector, the PRML detector also employs a hybrid two-stage scheme, in order to allow a tradeoff between performance and complexity. In simulations, we consider a slow fading environment and use the ITU-R 3G channel models. From the numerical results, it is shown that in frequency-selective fading wireless channels, the PRBP detector provides superior performance over both the traditional minimum mean squared error linear equalizer (MMSE-LE) and the PRML detector. Due to the effect of colored noise, the PRML detector in fading wireless channels is not as effective as it is in magnetic recording applications. Thirdly, we extend our work to accommodate the application of Advanced Television Systems Committee (ATSC) digital television (DTV) systems. In order to reduce error propagation caused by the traditional decision feedback equalizer (DFE) in DTV receiver, we present an adaptive decision feedback sparsening filter BP (DFSF-BP) detector, which is another form of PRBP detector. Different from the aforementioned LE-BP structure, in the DFSF-BP scheme, the BP detector is followed by a nonlinear filter called DFSF as the partial response equalizer. In the first stage, the DFSF employs a modified feedback filter which leaves the strongest post-cursor ISI taps uncorrected. As a result, a long ISI channel is equalized to a sparse channel having only a small number of nonzero taps. In the second stage, the BP detector is applied to mitigate the residual ISI. Since the channel is typically time-varying and suffers from Doppler fading, the DFSF is adapted using the least mean square (LMS) algorithm, such that the amplitude and the locations of the nonzero taps of the equalized sparse channel appear to be fixed. As such, the channel appears to be static during the second stage of equalization which consists of the BP detector. Simulation results demonstrate that the proposed scheme outperforms the traditional DFE in symbol error rate, under both static channels and dynamic ATSC channels. Finally, we study the symbol detector design for cooperative communications, which have attracted a lot of attention recently for its ability to exploit increased spatial diversity available at distributed antennas on other nodes. A system framework employing non-orthogonal amplify-and-forward half-duplex relays through ISI channels is developed. Based on the system model, we first design and implement an optimal maximum-likelihood detector based on the Viterbi algorithm. As the relay period increases, the effective CIR between the source and the destination becomes long and sparse, which makes the optimal detector impractical to implement. In order to achieve a balance between the computational complexity and performance, several sub-optimal detectors are proposed. We first present a multitrellis Viterbi algorithm (MVA) based detector which decomposes the original trellis into multiple parallel irregular sub-trellises by investigating the dependencies between the received symbols. Although MVA provides near-optimal performance, it is not straightforward to decompose the trellis for arbitrary ISI channels. Next, the decision feedback sequence estimation (DFSE) based detector and BP-based detector are proposed for cooperative ISI channels. Traditionally these two detectors are used with fixed, static channels. In our model, however, the effective channel is periodically time-varying, even when the component channels themselves are static. Consequently, we modify these two detector to account for cooperative ISI channels. Through simulations in frequency selective fading channels, we demonstrate the uncoded performance of the DFSE detector and the BP detector when compared to the optimal MLSE detector. In addition to quantifying the performance of these detectors, we also include an analysis of the implementation complexity as well as a discussion on complexity/performance tradeoffs."

This dissertation examines second order network formation on India's large and rapidly expanding mobile phone networks. It does so by examining a particular second order network - the Indian Premier League (IPL) mobile network. Using a case study approach and a mix of ethnographic methods and textual analysis, I explore the history that preceded the IPL mobile network, the intentions of its creators, the processes by which users participate on the network, and the outcomes of network expansion and evolution. I deploy the space of flows concept of Manuel Castells, to draw attention to continuity and change in Indian communication networks, and to highlight the new spatial dynamics at work in mass mobile telephony. This dissertation emphasizes the transformative nature of second order networks and identifies the ways that masses of users can disrupt and alter communication networks, especially in contexts of informal economics and power structures.

The next generation wireless communication systems require ubiquitous high-throughput mobile connectivity under a range of challenging network settings (urban versus rural, high device density, mobility, etc). To improve the performance of the system, the physical layer design is of great importance. The previous research on improving the physical layer properties includes: a) highly directional transmissions that can enhance the throughput and spatial reuse; b) enhanced MIMO that can eliminate contention, enabling linear increase of capacity with number of antennas; c) mmWave technologies which operate on GHz bandwidth to over substantially higher throughput; d) better cooperative spectrum sharing with cognitive radios; e) better multiple access method which can mitigate multiuser interference and allow more multi-users. This dissertation addresses several techniques in the physical layer design of the next generation wireless communication systems. In chapter two, an orthogonal frequency division with code division multiple access (OFDM-CDMA) systems is proposed and a polyphase code is used to improve multiple access performance and make the OFDM signal satisfy the peak to average ratio (PAPR) constraint. Chapter three studies the I/Q imbalance for direct down converter. For wideband transmitter and receiver that use direct conversion for I/Q sampling, the I/Q imbalance becomes a critical issue. With higher I/Q imbalance, there will be higher degradation in quadrature amplitude modulation, which degrades the throughput tremendously. Chapter four investigate a problem of spectrum sharing for cognitive wideband communication. An energy-efficient sub-Nyquist sampling algorithm is developed for optimal sampling and spectrum sensing. In chapter ve, we study the channel estimation of millimeter wave full-dimensional MIMO communication. The problem is formulated as an atomic-norm minimization problem and algorithms are derived for the channel estimation in different situations. In this thesis, mathematical optimization is applied as the main approach to analyze and solve the problems in the physical layer of wireless communication so that the high-throughput is achieved. The algorithms are derived along with the theoretical analysis, which are validated with numerical results.

Local Oscillator (LO) is an essential building block in modern wireless radios. In modern wireless radios, LO often serves as a reference of the carrier signal to modulate or demod- ulate the outgoing or incoming data. The LO signal should be a clean and stable source, such that the frequency or timing information of the carrier reference can be well-defined. However, as radio architecture evolves, the importance of LO path design has become much more important than before. Of late, many radio architecture innovations have exploited sophisticated LO generation schemes to meet the ever-increasing demands of wireless radio performances. The focus of this thesis is to address challenges in the LO path design for next-generation high performance wireless radios. These challenges include (1) Congested spectrum at low radio frequency (RF) below 5GHz (2) Continuing miniaturization of integrated wireless radio, and (3) Fiber-fast (>10Gb/s) mm-wave wireless communication. The thesis begins with a brief introduction of the aforementioned challenges followed by a discussion of the opportunities projected to overcome these challenges. To address the challenge of congested spectrum at frequency below 5GHz, novel ra- dio architectures such as cognitive radio, software-defined radio, and full-duplex radio have drawn significant research interest. Cognitive radio is a radio architecture that opportunisti- cally utilize the unused spectrum in an environment to maximize spectrum usage efficiency. Energy-efficient spectrum sensing is the key to implementing cognitive radio. To enable energy-efficient spectrum sensing, a fast-hopping frequency synthesizer is an essential build- ing block to swiftly sweep the carrier frequency of the radio across the available spectrum. Chapter 2 of this thesis further highlights the challenges and trade-offs of the current LO gen- eration scheme for possible use in sweeping LO-based spectrum analysis. It follows by intro- duction of the proposed fast-hopping LO architecture, its implementation and measurement results of the validated prototype. Chapter 3 proposes an embedded phase-shifting LO-path design for wideband RF self-interference cancellation for full-duplex radio. It demonstrates a synergistic design between the LO path and signal to perform self-interference cancellation. To address the challenge of continuing miniaturization of integrated wireless radio, ring oscillator-based frequency synthesizer is an attractive candidate due to its compactness. Chapter 4 discussed the difficulty associated with implementing a Phase-Locked Loop (PLL) with ultra-small form-factor. It further proposes the concept sub-sampling PLL with time- based loop filter to address these challenges. A 65nm CMOS prototype and its measurement result are presented for validation of the concept. In shifting from RF to mm-wave frequencies, the performance of wireless communication links is boosted by significant bandwidth and data-rate expansion. However, the demand for data-rate improvement is out-pacing the innovation of radio architectures. A >10Gb/s mm-wave wireless communication at 60GHz is required by emerging applications such as virtual-reality (VR) headsets, inter-rack data transmission at data center, and Ultra-High- Definition (UHD) TV home entertainment systems. Channel-bonding is considered to be a promising technique for achieving >10Gb/s wireless communication at 60GHz. Chapter 5 discusses the fundamental radio implementation challenges associated with channel-bonding for 60GHz wireless communication and the pros and cons of prior arts that attempted to address these challenges. It is followed by a discussion of the proposed 60GHz channel- bonding receiver, which utilizes only a single PLL and enables both contiguous and non- contiguous channel-bonding schemes. Finally, Chapter 6 presents the conclusion of this thesis.

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