Thesis (M. Sc.)--University of Alberta, 2009. / Title from PDF file main screen (viewed on Oct. 2, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science in Communications, Department of Electrical and Computer Engineering, University of Alberta." Includes bibliographical references.

With the development of mobile networks, customer needs and behaviourshave changed. Mobile communications means so much more than simplevoice communication; there is now mobile Internet with web surfing, videophone,streaming media, and micro blogging. The objective of network optimizationhas gradually shifted from enhancing network performance to improvequality of experience (QoE). Therefore, assessing and optimizing QoEis the trend for optimizing future mobile networks. Today, users want reliable access for their content, wherever they go inthe network. To deliver the best possible experience to mobile broadbandsubscribers, operators need new ways to assess performance that will enablethem to build and manage their networks in the most efficient way. The newparadigmatic eco system (user-interface-network-content) requires novel anddisruptive end-to-end considerations in order to enable and sustain the nextgeneration of services and user experience. Thus, the extraordinary adoptionof mobile connectivity by end users, and the need for optimized bandwidthmanagement network resource, on the one hand, and the growing interest forgood quality content delivery/consumption, is boosting the creation of newnetwork solutions. We consider that by taking advantage of the capacity to support multimedia platforms and applications of mobile devices (e.g. smartphones, tablets,etc.) is possible to incorporate and provide awareness to the wireless infrastructuresin the context of cross-layer systems to manage the resource allocationaccording to expected QoE levels. In this thesis, we address the questionon how to implement QoE-aware mobile networks and evaluate differentschedulers oriented to take advantage of the proposed architecture. We showthat by providing QoE-awareness to the network infrastructure is possible toimprove user’s QoE and generate impacts in the utilization of the networkresources. With this study, we provide insights into the broader question ofwhether future mobile infrastructures can be deployed considering QoE besidesthe classical QoS considerations. / <p>QC 20140521</p>

The objective of the proposed research is to develop interference-aware resource management techniques for CR networks that opportunistically operate within the licensed primary networks spectrum and to investigate the application of such CR techniques to emerging wireless networks. In this thesis, we report on a set of laboratory experiments that we undertook to analyze the interference between the CR-based wireless regional-area network (WRAN) standard and the digital television (DTV) broadcasting system. We determined the tolerable levels of WRAN interference into DTV receivers and studied the effect of these interference levels on WRAN deployment. Based on the need for efficient utilization of the primary network spectrum, we propose efficient interference-aware radio resource allocation (RRA) techniques for orthogonal frequency-division multiple access (OFDMA) CR networks. These RRA techniques aim to maximize the CR network throughput and to keep the CR interference to the primary network at or below a predefined threshold, known as the "interference temperature" limit. Moreover, we propose a joint spectrum-sensing design and power control algorithm that lead to increased CR network throughput and efficient protection of the PUs from undue interference. Interference coordination (IC) is considered a key technique for capacity maximization in emerging heterogeneous wireless networks. We propose a CR-based IC and RRA algorithm for OFDMA femtocell deployments to achieve efficient spectrum utilization and maximum network throughput. CR is envisioned as a key enabling technology for future wireless networks; our novel CR techniques will provide other researchers useful tools to design such networks.

In this thesis, we investigate several radio resourcemanagement (RRM) techniques and concepts in an indoorenvironment with a dense infrastructure. Future wireless indoorcommunication networks will very likely be implemented atplaces where the user concentration is very high. At these hotspots, the radio resources must be used efficiently. The goalis to identify efficient RRM techniques and concepts that aresuitable for implementation in an indoor environment. Handling the high level of co-channel interference is shownto be of paramount importance. Several investigations in thethesis point this out to be the key problem in an indoorenvironment with a dense infrastructure. We show that a locallycentralized radio resource management concept, the bunchconcept, can give a very high performance compared to othercommonly used RRM concepts. Comparisons are made withdistributed systems and systems using channel selection schemeslike CSMA/CA. The comparisons are primarily made by capacityand throughput analysis which are made by system levelsimulations. Results show that the centralized concept can give85 percent higher capacity and 70 percent higher throughputthan any of the compared systems. We investigate several RRM techniques to deal with thechannel interference problem and show that beamforming cangreatly reduce the interference and improve the systemperformance. Beamforming, especially sector antennas, alsoreduce the transmitter powers and the necessary dynamic range.A comparison is made between the use of TD/CDMA and pure TDMAwhich clearly shows the performance benefits of usingorthogonal channels that separates the users and reduces theco-channel interference. Different channel selection strategiesare studied and evaluated along with various methods to improvethe capability of system co-existence. We also investigate several practical measures to facilitatesystem implementation. Centralized RRM is suitable forguaranteeing QoS but is often considered too complex. With thestudied centralized concept the computational complexity can bereduced by splitting the coverage area into smaller pieces andcover them with one centralized system each. This reduces thecomplexity at the prize of lost capacity due to theuncontrolled interference that the different systems produce.Our investigations show that sector antennas can be used toregain this capacity loss while maintaining high reduction incomplexity. Without capacity loss, the computational complexitycan be reduced by a factor of 40 with sectoring. Theimplementation aspects also include installation sensitivity ofthe indoor architecture and the effect of measurement errors inthe link gains. The robustness against installation errors ishigh but the bunch concept is quite sensitive to largemeasurement errors in the studied indoor environment. Thiseffect can be reduced by additional SIR-margins of the radiolinks. The studied bunch concept is shown to be promising for usein future wireless indoor communication systems. It provideshigh performance and is feasible to implement. Keywords:Radio resource management, indoorcommunication, the bunch concept, centralized RRM, dynamicchannel allocation, channel selection, co-channel interference,power control, feasibility check, capacity, throughput, qualityof service, beamforming, downtilting, sector antennas,co-existence, computational complexity, sensitivity analysis,measurement errors, infrastructure, system implementation,WLAN, HiperLAN/2, IEEE 802.11.

The third generation of mobile communication systems introduce interactive Multicast and Unicast multimedia services at a fast data rate of up to 2 Mbps and is expected to complete the globalization of the mobile telecommunication systems. The implementation of these services on satellite systems, particularly for broadcast and multicast applications to complement terrestrial services is ideal since satellite systems are capable of providing global coverage in areas not served by terrestrial telecommunication services. However, the main bottleneck of such systems is the scarcity of radio resources for supporting multimedia applications which has resulted in the rapid growth in research efforts for deriving efficient radio resource management techniques. This issue is addressed in this thesis, where the main emphasis is to design a dynamic scheduling framework and algorithm that can improve the overall performance of the radio resource management strategy of a UMTS compatible satellite network, taking into account the unique characteristics of wireless channel conditions. This thesis will initially be focused on the design of the network and functional architecture of a UMTS -compatible satellite network. Based on this architecture, an effective scheduling framework is designed, which can provide different types of resource assigning strategies. A functional model of scheduler is defined to describe the behaviours and interactions between different functional entities. An OPNET simulation model with a complete network protocol stack is developed to validate the performance of the scheduling algorithms implemented in the satellite network. Different types of traffic are considered for the OPNET simulation, such as the Poisson Process, ONOFF Source and Self Similar Process, so that the performance of scheduling algorithm can be analyzed for different types of services. A novel scheduling algorithm is proposed to optimise the channel utilisation by considering the characteristics of the wireless channel, which are bursty and location dependent. In order to overcome the channel errors, different code rates are applied for the user under different channel conditions. The proposed scheduling algorithm is designed to give higher priority to users with higher code rate, so that the throughput of network is optimized and at the same time, maintaining the end users' service level agreements. The fairness of the proposed scheduling algorithm is validated using OPNET simulation. The simulation results show that the algorithm can fairly allocate resource to different connections not only among different service classes but also within the same service class depending on their QoS attributes.

A Research Report submitted to the Faculty of Engineering and the Built Environment, University of Witwatersrand, in the partial fulfilment of the requirements for the degree of Master of Science in Engineering Johannesburg, 2015. / Due to the enormous demand for multimedia services which relies hugely on the availability of spectrum, service providers and technologist are devising a means or method which is able to fully satisfy these growing demands. The availability of spectrum to meet these demands has been a lingering issue for the past couple of years. Many would have it tagged as spectrum scarcity but really the main problem is not how scarce the spectrum is but how efficiently allocated to use is the spectrum. Once such inefficiency is tackled effectively, then we are a step closer in meeting the enormous demands for uninterrupted services. However, to do so, there are techniques or methodologies being developed to aid in the efficient management of spectrum. In this research project, two methodologies were considered and the efficiency of these methodologies in the areas of spectrum management. The Geo-location Spectrum Database (GLSD) which is the most adopted technique and the Cognitive radio spectrum sensing technique are currently the available techniques in place. The TV whitespaces (TVWS) was explored using both techniques and certain comparison based on performances; implementation, practicability, cost and flexibility were used as an evaluation parameter in arriving at a conclusion. After accessing both methodologies, conclusions were deduced on the preferred methodology and how its use would efficiently solve the issues encountered in spectrum management

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

The rapid growth in demand due to the emergence of mobile communication services with variable rates, coupled with the resource scarcity of mobile air interface, has encouraged researchers to find technological solutions to increase spectral efficiency in order to support different levels of Quality of Service (QoS). Radio resource management (RRM) plays a major role in QoS provisioning and congestion control for wireless networks. The main problem with the congestion control mechanisms provided by current RRM schemes is that they are mostly reactive, triggered only when congestion occurs. The common, traditional solution to congestion has been for system planners to over-engineer a network by assigning more resources than are necessary. This approach is very costly because busy periods are usually brief, causing the network to be often under-utilised outside of these periods. Current static, usage-based pricing models also fail to assist in traffic shaping to even out loads. Economic modelling offers a new perspective into current RRM schemes and enables efficient utilisation of scarce resources and congestion prevention based on concepts such as utility, price, Pareto optimality and game theory. Dynamic pricing has been proposed as a mechanism to encourage users to adapt their resource consumption level according to network conditions. A good pricing model can provide the necessary positive incentives to increase users’ arrival rate when the network load is relatively low and negative incentives for users to defer their usage when the load is relatively high. In this dissertation, we propose an economic framework for pricing and RRM for 3G and beyond systems. Our aim is two-fold: to calculate an optimal integrated dynamic pricing and RRM policy; and to allocate scarce network resources in a fair and Pareto-optimal manner. The optimal integrated dynamic pricing and RRM policy is computed based on the stochastic distribution of users’ budget, arrivals, handoffs and departures. Our results show that the integrated policy is superior in terms of average reward improvement and congestion prevention to current schemes that use static pricing models. In interferencebased networks such as WCDMA, we suggest users be charged according to their noise rise factor, i.e. an estimate of the amount of interference generated by the call. This interference-based pricing model improves on the conventional load-based model in by delivering higher revenue and lower call blocking and handoff probabilities. Using the axiomatic bargaining concepts from cooperative game theory, we derive a class of fair and Pareto-optimal bargaining solutions that allocate wireless resources based on users’ minimum and maximum rate requirements. We propose two models: symmetric and asymmetric. In the latter, resource is allocated according to the price paid by the users. An important significance of the asymmetric bargaining model is that this solution is still Pareto-optimal and fair according to the users’ bargaining power. Our approach is also a departure from current works using noncooperative game theory that can only achieve an inefficient outcome, i.e. the Nash equilibrium; or cooperative game theory that focus on only one solution on the Pareto-optimal boundary. By analysing a range of bargaining solutions instead of specific ones, operators can proceed to select the best outcome out of these Pareto-optimal solutions based on criteria like revenue. / Thesis (Ph.D) -- University of Adelaide, School of Electrical and Electronic Engineering, 2007