Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2005. / Includes bibliographical references (leaves 94-99). Also available in electronic version.

Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2006. / Dr. Stevenson J. Kenney, Committee Member ; Dr. Paul G. Steffes, Committee Chair ; Dr. Gregory D. Durgin, Committee Member ; Dr. Aaron D. Lanterman, Committee Member ; Dr. Robert G. Roper, Committee Member.

M.Sc. (Information Technology) / A new particle swarm optimisation (PSO) algorithm that produces solutions to the xed spectrum frequency assignment problem (FS-FAP) is presented. Solutions to the FS-FAP are used to allocate frequencies in a mobile telecommunications network and must have low interference. The standard PSO algorithm's velocity method and global selection is ill suited for the frequency assignment problem (FAP). Therefore using the standard PSO algorithm as base, new techniques are developed to allow it to operate on the FAP. The new techniques include two velocity methods and three global selection schemes. This study presents the results of the algorithm operating on the Siemens set of COST 259 problems and shows that it is viable applying the PSO to the FAP.

Natural and manmade noise signals tend to exhibit impulsive behaviors. Therefore modeling those signals as α-stable processes is better suited towards the development of a practical spectrum sensing scheme. However, the performances of detectors operating in an α-stable noise environment are difficult to evaluate. This is because an α-stable random variable can usually only be modeled by the characteristic function since closed-form expressions are usually not available except for the special values of the characteristic exponent that correspond to the Cauchy and Gaussian noise distributions. In this thesis, we derive a general closed-form expression for the probability density function (PDF) of symmetric alpha stable processes having rational characteristic exponent (0<α≤2). Consequently, we obtain analytical expressions for the PDF and corresponding complementary cumulative distribution function (CCDF) of the proposed fractional lower order moment (FLOM) detector. Utilizing false alarm and detection probabilities, the performance analysis of the proposed spectrum sensing scheme is conducted with the assumption that the cognitive radio (CR) users are operating in non-fading channels. We validate the analytical results with Monte Carlo simulations. The effect of the distribution parameters on the receiver operating characteristic (ROC) curves is verified. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

無處不在的無線業務以其不斷增長的需求促進了對稀缺無線資源的高效利用。多年來，優化技術被廣泛地運用在無線資源分配的方案設計上，從而達到改善系統性能之目的。在此領域的大部分工作中，用於定義優化問題的系統參數被假設為精確可知。然而，實際的系統參數往往是時變且隨機的。忽略系統參數的不確定性極易導致資源分配決策偏離最優狀態，或者甚至違反系統運行約束而使分配決策不可行。 / 本論文提出了一套用於無線通信的動態資源分配的隨機優化框架。具體而言，本文抓住了不確定系統參數的隨機本質，從而建立結合實際的問題模型，並且開發了高效的算法，以獲得最佳的分配決策。本文將提出的框架成功地應用於三個很有前景的無線通信系統中：自適應正交頻分多址接入（OFDMA）系統，多輸入多輸出（MIMO）天線系統，以及位置感知網絡。每一個應用系統中都存在與實踐相關的挑戰，而這些挑戰則源自於傳統基於靜態優化的設計在提供滿意的服務質量（QoS）中遇到的困難。結果表明，使用隨機優化的動態資源分配，可達到了更加穩健的QoS性能，並且顯著增強系統的實用性。 / 在自適應OFDMA系統中，本文提出了一套“慢適應“的最優子載波分配方案。該方案通過採用更新遠慢於無線信道波動的資源分配策略，從而使計算複雜度和控制信令大大降低。本文根據不同的應用背景，將慢適應子載波分配問題描述成為幾個不同的隨機規劃問題。其中，我們設計了一個高效的算法專門用以求解機會約束規劃類型的子載波分配問題。 / 在MIMO天線系統中，本文提出了一套天線和發射功率聯合分配的方案，使利用多天線支持單一移動終端上的多個無線電模塊同時運行成為可能。該方案最大化了長期系統吞吐量，同時以容許偶爾違反系統約束的方式滿足每個無線模塊的短期傳輸速率需求。結果表明，最優天線和發射功率分配顯著提高系統的吞吐量和滿足QoS的成功概率；而最優天線分配與最優功率分配相比，對提高系統吞吐量有更大的貢獻。 / 在位置感知網絡中，本文提出了一套魯棒功率分配方案，用以抵抗網絡參數的不確定性，這些參數包括用戶位置以及信道狀態。本文提出了一種新的魯棒優化方法，用以獲得最優功率分配，從而提高定位精度和網絡能效。結果表明，魯棒方案顯著優於非魯棒的功率分配和平均分配方案。 / 本論文著眼於縮短傳統基於靜態優化的設計與其現實針對性之間的差距。鑒於許多無線系統的參數在本質上都具有隨機性，本文所提出的採用隨機優化的資源分配方法，有望在未來無線通信中得到更多的應用。 / The growing demand of ubiquitous wireless services has prompted the efficient utilization of scarce radio resources. Over the years, optimization techniques have been widely employed to design optimal resource allocation schemes to achieve performance improvement. Most work in this area assumes that the system parameters defining the optimization problem are precisely known. In practical systems, however, these parameters are often time varying and random. Ignoring the parameter uncertainties would easily lead to suboptimality or even infeasible solutions that violate system operation constraints. / This thesis presents a stochastic optimization framework for the dynamic resource allocation in wireless communications. In particular, practice-relevant problem formulations are proposed to capture the stochastic nature of the uncertain system parameters, and efficient algorithms are developed to obtain the optimal allocation decisions. The proposed framework has been successfully applied in three promising wireless systems: adaptive orthogonal frequency division multiple access (OFDMA) systems, multiple-input and multiple-output (MIMO) antenna systems, and location-aware networks. Each application contains practice-relevant challenges, where the conventional designs using deterministic optimization fail to provide satisfactory quality of service (QoS). The results demonstrate that the dynamic resource allocation using stochastic optimization achieves more robust QoS performance and remarkably enhances the system practicality. / In adaptive OFDMA systems, a slow adaptation scheme is proposed for optimal subcarrier allocation. The proposed scheme updates the resource allocation decisions on a much slower timescale than that of channel fluctuation, which drastically reduces the computational complexity and control signaling overhead. The problems are formulated into several stochastic programs based on different application scenarios. An efficient algorithm is developed for solving the chance constrained subcarrier allocation problem. / In MIMO antenna systems, an antenna-and-power allocation scheme is proposed to enable the use of multiple antennas to support multiple radios co-operating on the same mobile device. The proposed scheme maximizes the long-term system throughput while satisfying the short-term data rate requirement of each radio transmission with occasional outage. The results show that both system throughput and success probability of QoS satisfaction are improved, and the optimal antenna allocation contributes to a larger portion of throughput increase comparing with the optimal power allocation. / In location-aware networks, robust power allocation schemes are proposed to combat the uncertainties in network parameters including user positions and channel conditions. A novel robust optimization method is developed to obtain the optimal power allocation, which improves both localization accuracy and network energy efficiency. The results show that the robust schemes remarkably outperform both non-robust power allocation and uniform allocation. / The goal of this thesis is to bridge the gap between the current designs under the deterministic optimization framework and their practical relevance. Given the fact that many wireless system parameters are stochastic in nature, the proposed resource allocation methods using stochastic optimization are expected to find further applications in wireless communications. / 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. / Detailed summary in vernacular field only. / Li, Weiliang. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 157-175). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese. / 摘要 / Abstract --- p.iii / Acknowledgement --- p.vi / Contents --- p.ix / List of Figures --- p.xiii / List of Tables --- p.xvii / List of Acronyms --- p.xviii / List of Notations --- p.xxi / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Resource Allocation in Wireless Communications --- p.2 / Chapter 1.2 --- Stochastic Optimization and Its Applications --- p.4 / Chapter 1.2.1 --- Robust Optimization --- p.5 / Chapter 1.2.2 --- Chance Constrained Optimization --- p.8 / Chapter 1.3 --- Motivation and Research Focus --- p.10 / Chapter 1.3.1 --- Motivation --- p.10 / Chapter 1.3.2 --- OFDM and OFDMA Systems --- p.14 / Chapter 1.3.3 --- MIMO Antenna Systems --- p.16 / Chapter 1.3.4 --- Location-Aware Networks --- p.18 / Chapter 1.4 --- Contributions --- p.20 / Chapter 1.5 --- Organization --- p.23 / Chapter 2 --- Slow Subcarrier Allocation in Adaptive OFDMA Systems --- p.25 / Chapter 2.1 --- System and Channel Model --- p.29 / Chapter 2.1.1 --- Channel Model --- p.29 / Chapter 2.1.2 --- Slow Adaptive OFDMA --- p.30 / Chapter 2.2 --- Slow Adaptive OFDMA with Average Rate Constraints for Elastic Traffics --- p.32 / Chapter 2.2.1 --- Problem Formulation --- p.33 / Chapter 2.2.2 --- Computation of Expected Average Data Rate --- p.34 / Chapter 2.2.3 --- Numerical Results --- p.37 / Chapter 2.3 --- Slow Adaptive OFDMA with Average Rate Constraints for Inelastic Traffics --- p.40 / Chapter 2.3.1 --- Problem Formulation --- p.40 / Chapter 2.3.2 --- Numerical Results --- p.43 / Chapter 2.4 --- Slow Adaptive OFDMA with Probabilistic Rate Constraints --- p.46 / Chapter 2.4.1 --- Problem Formulation --- p.47 / Chapter 2.4.2 --- Safe Tractable Constraints --- p.48 / Chapter 2.4.3 --- Algorithm Design --- p.51 / Chapter 2.4.4 --- Problem Size Reduction --- p.59 / Chapter 2.4.5 --- Numerical Results --- p.61 / Chapter 2.5 --- Summary --- p.70 / Chapter 3 --- Dynamic Antenna-and-Power Allocation in Composite Radio MIMO Networks --- p.72 / Chapter 3.1 --- System Model --- p.76 / Chapter 3.1.1 --- Composite Radio System --- p.76 / Chapter 3.1.2 --- Channel Model --- p.77 / Chapter 3.1.3 --- Dynamic Antenna-and-Power Allocation --- p.78 / Chapter 3.2 --- Problem Formulation --- p.80 / Chapter 3.2.1 --- MIMO Channel Capacity --- p.80 / Chapter 3.2.2 --- Chance Constrained Formulation --- p.81 / Chapter 3.2.3 --- Safe Tractable Formulation --- p.82 / Chapter 3.3 --- Search for Feasible Solutions --- p.85 / Chapter 3.3.1 --- Algorithm Design --- p.87 / Chapter 3.4 --- Approach to Optimal Solution --- p.89 / Chapter 3.4.1 --- Cutting-Plane-Based Algorithm --- p.91 / Chapter 3.4.2 --- Optimal Antenna-and-Power Allocation --- p.95 / Chapter 3.5 --- Simulation Results --- p.96 / Chapter 3.6 --- Summary --- p.106 / Chapter 4 --- Robust Power Allocation for Energy-Efficient Location-Aware Networks --- p.107 / Chapter 4.1 --- System Model --- p.110 / Chapter 4.1.1 --- Network Settings --- p.110 / Chapter 4.1.2 --- Position Error Bound --- p.111 / Chapter 4.1.3 --- Directional Decoupling of SPEB --- p.113 / Chapter 4.2 --- Optimal Power Allocation via Conic Programming --- p.115 / Chapter 4.2.1 --- Problem Formulation Based on SPEB --- p.115 / Chapter 4.2.2 --- Problem Formulation Based on mDPEB --- p.117 / Chapter 4.2.3 --- Formulations with QoS Guarantee --- p.120 / Chapter 4.3 --- Robust Power Allocation under Imperfect Network Topology Parameters --- p.122 / Chapter 4.3.1 --- Robust Counterpart of SPEB Minimization --- p.123 / Chapter 4.3.2 --- Robust Counterpart of mDPEB Minimization --- p.131 / Chapter 4.4 --- Efficient Robust Algorithm Using Distributed Computations --- p.132 / Chapter 4.4.1 --- Algorithm for SPEB Minimization --- p.132 / Chapter 4.4.2 --- Algorithm for mDPEB Minimization --- p.136 / Chapter 4.5 --- Simulation Results --- p.137 / Chapter 4.5.1 --- Power Allocation with Perfect Network Topology Parameters --- p.137 / Chapter 4.5.2 --- Robust Power Allocation with Imperfect Network Topology Parameters --- p.140 / Chapter 4.6 --- Summary --- p.144 / Chapter 5 --- Conclusions and Future Work --- p.145 / Chapter 5.1 --- Conclusions --- p.145 / Chapter 5.1.1 --- Slow Adaptive OFDMA Systems --- p.146 / Chapter 5.1.2 --- Composite Radio MIMO Networks --- p.147 / Chapter 5.1.3 --- Energy-Efficient Location-Aware Networks --- p.148 / Chapter 5.2 --- Future Work --- p.150 / Chapter A --- Bernstein Approximation Theorem --- p.153 / Chapter B --- Ergodic MIMO Capacity and Moment Generating Function --- p.155 / Bibliography --- p.157

Submitted in fulfilment of the academic requirements for the degree of Doctor of Philosophy (Ph.D.) in Engineering, in the School of Electrical and Information Engineering, Faculty of Engineering and the Built Environment, at the University of the Witwatersrand, Johannesburg, South Africa, 2017 / The continuous evolution of wireless communications technologies has increasingly imposed a burden on the use of radio spectrum. Due to the proliferation of new wireless networks applications and services, the radio spectrum is getting saturated and becoming a limited resource. To a large extent, spectrum scarcity may be a result of deficient spectrum allocation and management policies, rather than of the physical shortage of radio frequencies. The conventional static spectrum allocation has been found to be ineffective, leading to overcrowding and inefficient use. Cognitive radio (CR) has therefore emerged as an enabling technology that facilitates dynamic spectrum access (DSA), with a great potential to address the issue of spectrum scarcity and inefficient use. However, provisioning of reliable and robust communication with seamless operation in cognitive radio networks (CRNs) is a challenging task. The underlying challenges include development of non-intrusive dynamic resource allocation (DRA) and optimization techniques. The main focus of this thesis is development of adaptive channel assembling (ChA) and DRA schemes, with the aim to maximize performance of secondary user (SU) nodes in CRNs, without degrading performance of primary user (PU) nodes in a primary network (PN). The key objectives are therefore four-fold. Firstly, to optimize ChA and DRA schemes in overlay CRNs. Secondly, to develop analytical models for quantifying performance of ChA schemes over fading channels in overlay CRNs. Thirdly, to extend the overlay ChA schemes into hybrid overlay and underlay architectures, subject to power control and interference mitigation; and finally, to extend the adaptive ChA and DRA schemes for multiuser multichannel access CRNs. Performance analysis and evaluation of the developed ChA and DRA is presented, mainly through extensive simulations and analytical models. Further, the cross validation has been performed between simulations and analytical results to confirm the accuracy and preciseness of the novel analytical models developed in this thesis. In general, the presented results demonstrate improved performance of SU nodes in terms of capacity, collision probability, outage probability and forced termination probability when employing the adaptive ChA and DRA in CRNs. / CK2018

Cognitive radio (CR) technology allows devices to share the wireless spectrum with other users that have a license for operation in these spectrum bands. This area of research promises to solve the problem of spectrum scarcity in the unlicensed bands, and improve the inefficient spectrum utilization in the bands reserved for the licensed users. However, the opportunistic use of the available spectrum by the CR users must not affect the licensed users. This raises several concerns regarding spectrum sensing, sharing and reliable end-to-end communication in CR networks. This thesis is concerned with the design and implementation of communication protocols for the multi-hop infrastructure-less CR ad-hoc networks (CRAHNs). In addition, it also addresses the critical issue of interference-free spectrum usage in specific ad-hoc architectures, such as, resource-constrained wireless sensor networks and wireless mesh networks that have high traffic volumes. The problems of spectrum management that are unique to CR networks are first identified in this thesis. These issues are then addressed at each layer of the network protocol stack while considering the distributed operation in CRAHNs. At the physical layer an algorithmic suite is proposed that allows the CR devices to detect and adapt to the presence of wireless LANs and commercial microwave ovens. A common control channel is designed that allows sharing of the spectrum information between the CR users, even when the available spectrum varies dynamically. A spectrum sharing scheme for mesh networks is proposed at the link layer that allows cooperative detection of the licensed users and fair utilization of the available spectrum among the mesh devices. The spectrum availability and route formation are then considered jointly at the network layer, so that the licensed users are protected as well as the CRAHN performance is maximized. Finally, we extend the classical TCP at the transport layer to ensure end-to-end reliability in a multi-hop CR environment.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Electrical and Computer Engineering." Includes bibliographical references (p. 109-111).

Thesis (Ph. D.)--University of Notre Dame, 2005. / Thesis directed by Philip E. Mirowski for the Department of Economics. "December 2005." Includes bibliographical references (leaves 152-165).

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy