Next generation wireless communication networks are expected to provide ubiquitous high data rate coverage and support heterogeneous wireless services with diverse quality-of-service (QoS) requirements. This translates into a heavy demand for the spectral resources. In order to meet these requirements, Orthogonal Frequency Division Multiple Access (OFDMA) has been regarded as a promising air-interface for the emerging fourth generation (4G) networks due to its capability to combat the channel impairments and support high data rate. In addition, OFDMA offers flexibility in radio resource allocation and provides multiuser diversity by allowing subcarriers to be shared among multiple users. One of the main challenges for the 4G networks is to achieve high throughput throughout the entire cell. Cooperative relaying is a very promising solution to tackle this problem as it provides throughput gains as well as coverage extension. The combination of OFDMA and cooperative relaying assures high throughput requirements, particularly for users at the cell edge. However, to fully exploit the benefits of relaying, efficient relay selection as well as resource allocation are critical in such kind of network when multiple users and multiple relays are considered. Moreover, the consideration of heterogeneous QoS requirements further complicate the optimal allocation of resources in a relay enhanced OFDMA network. Furthermore, the computational complexity and signalling overhead are also needed to be considered in the design of practical resource allocation schemes. In this dissertation, we conduct a comprehensive research study on the topic of radio resource management for relay-based cooperative OFDMA networks supporting heterogeneous QoS requirements. Specifically, this dissertation investigates how to effectively and efficiently allocate resources to satisfy QoS requirements of 4G users, improve spectrum utilization and reduce computational complexity at the base station. The problems and our research achievements are briefly outlined as follows. Firstly, a QoS aware optimal joint relay selection, power allocation and subcarrier assignment scheme for uplink OFDMA system considering heterogeneous services under a total power constraint is proposed. The relay selection, power allocation and subcarrier assignment problem is formulated as a joint optimization problem with the objective of maximizing the system throughput, which is solved by means of a two level dual decomposition and subgradient method. The computational complexity is finally reduced via the introduction of two suboptimal schemes. The performance of the proposed schemes is demonstrated through computer simulations based on OFDMA network. Numerical results show that our schemes support heterogeneous services while guaranteeing each user's QoS requirements with slight total system throughput degradation. Secondly, we investigate the resource allocation problem subject to the satisfaction of user QoS requirements and individual total power constraints of the users and relays. The throughput of each end-to-end link is modeled considering both the direct and relay links. Due to non-convex nature of the original resource allocation problem, the optimal solution is obtained by solving a relaxed problem via two level dual decomposition. Numerical results reveal that the proposed scheme is effective in provisioning QoS of each user's over the conventional resource allocation counterpart under individual total power constraints of the users and relays . Lastly, decentralized resource allocation schemes are proposed to reduce the computational complexity and CSI feedback overhead at the BS. A user centric distributed (UCD) scheme and a relay centric distributed (RCD) scheme are proposed, where the computation of the centralized scheme is distributed among the users and relays, respectively. We also proposed suboptimal schemes based on simplified relay selection. The suboptimal schemes can be combined with the distributed schemes to further reduce of signalling overhead and computational complexity. Numerical results show that our schemes guarantee user's satisfaction with low computational complexity and signalling overhead, leading to preferred candidates for practical implementation. The research results obtained in this dissertation can improve the resource utilization and QoS assurance of the emerging OFDMA networks.

Cognitive radio (CR) is a promising technique to improve spectrum efficiency for wireless communications. This thesis focuses on the resource allocation in two kinds of CR networks (CRNs), traditional CRNs (TCRNs) and cooperative CRNs (CCRNs). In TCRNs, CR sources and destinations communicate directly. By exploring the heterogeneity among CRs, a prioritized CSMA/CA is proposed for demand-matching spectrum allocation. A distributed game is formulated and no-regret learning is adopted to solve the game. Simulation results indicate increase on the number of satisfied CRs. In CCRNs, some nodes are selected as relays to assist the communication. A two-layer auction game is proposed with the first layer performing spectrum allocation and relay formation, and the second layer performing relay allocation. These two layers interact and jointly solve the resource allocation problem. Simulation results show that, compared to counterparts, both the network throughput and convergence time can be improved.

Although project portfolio management (PPM) has been an active research area over the past 50 years, budget allocation models that consider competition are sparse. Firms faced with the project portfolio management problem must not only consider their current projections for the returns from their projects’ target markets, but must also anticipate that these returns can depend significantly on the investment decisions made by their competitors. In this thesis, we develop four Competitive PPM (CPPM) models wherein firms allocate resources between multiple projects and project returns are influenced by the actions taken by competitors. In the first two CPPM problems, we assume all-or-nothing project investment decisions where firms fully commit to either a project targeting a mature or an emerging market and the investment amount is fixed (first model) or a decision variable (second model). In the final two CPPM problems, firms have a fixed budget which they allocate in a continuous manner between two markets (third model) or multiple markets (fourth model). The returns each firm obtains from investments into these markets are assumed to follow an s-shaped curve (first model), the Inada (1963) conditions (third model), or are determined based on linear demand functions (second and fourth model). In the first model, two competing firms consider investing into two separate projects targeting a mature and an emerging market. We assume that firms have symmetric investment opportunities for each market and each firm simultaneously decides whether to invest in the mature or the emerging market. The returns from these markets are assumed to follow an s-shaped curve and depend on both firms’ investment decision. We characterize the variety of interactions that may emerge in symmetric environments (e.g., Prisoner’s Dilemma or Game of Chicken). For each game, we outline the CPPM strategy that can offer higher returns by exploiting first-mover advantages, cooperation opportunities and aggressive choices. We also discuss the market conditions that lead to these games. In the second model, a similar CPPM setting is considered where two symmetric firms face two target markets. However, we assume that demand for the emerging market is uncertain and may expand through firms’ market entry (positive diffusion effects), while demand for the mature market is known with certainty and cannot expand. Firms decide when to invest, in which market to invest, and how much to invest into this market. Our analysis reveals that the existence of multiple investment opportunities may induce firms to delay their investment even in the absence of demand uncertainty, and that high diffusion effects coupled with low demand uncertainty can drive firms to invest early even if both firms could increase returns by delaying their investment. We then study the asymmetric case where firms differ with respect to their costs and diffusion effects and show some counter-intuitive results. In the third CPPM problem, we consider continuous budget allocations and prove that while a monopoly firm bases its budget allocation decision solely on the marginal returns of the two markets, duopoly firms also account for their average returns from the two markets. This drives duopoly firms, in particular the firm with the smaller budget, to invest more heavily into the mature market. We show that as a firm’s budget increases, the share of its budget that is invested into the mature market decreases while its competitor’s investment into the mature market increases. This chapter also explores how changes to the market parameters and market uncertainty affect the resource allocation decision of firms under competition. Considering the special case of identical budgets, we prove that as the number of competing firms increases (with a fixed total budget), firms allocate an even greater share of their budget into the mature market. The fourth model considers a general case where a number of budget-constrained firms engage in production decisions for multiple markets under competition. Each firm decides how much to produce for each market, subject to its budget constraint. We prove that firms produce greater quantities for markets with higher than average base demand and that these quantities are increasing in the number of competitors (assuming identical production capacities). With asymmetric production capacities, we numerically illustrate how firms with large production capacities may, instead, increase production into lower than average base demand markets. Furthermore, we characterize the increase in return firms can expect from budget increases and conjecture that if some markets are not served by all firms, the remaining firms reduce their production into those markets where some firms are not producing.

Within the artificial intelligence subfield of multiagent systems, one challenge that arises is determining how to efficiently allocate resources to all agents in a way that maximizes the overall expected utility. In this thesis, we explore a distributed solution to this problem, one in which the agents work together to coordinate their requests for resources and which is considered to be ex-ante rational: in other words, requiring agents to be willing to give up their current resources to those with greater need by reasoning about what is for the common good. Central to our solution is allowing for preemption of tasks that are currently occupying resources; this is achieved by introducing a concept from adjustable autonomy multiagent systems known as a transfer of control (TOC) strategy. In essence a TOC strategy is a plan of an agent to acquire resources at future times, and can be used as a contingency plan that an agent will execute if it loses its current resource. The inclusion of TOC strategies ultimately provides for a greater optimism among agents about their future resource acquisitions, allowing for more generous behaviours, and for agents to more frequently agree to relinquish current resources, resulting in more effective preemption policies. Three central contributions arise. The first is an improved methodology for generating transfer of control strategies efficiently, using a dynamic programming approach, which enables a more effective employment of TOCs in our resource allocation solution. The second is an important clarification of the value of integrating learning techniques in order for agents to acquire improved estimates of the costs of preemption. The last is a validation of the overall multiagent resource allocation (MARA) solution, using simulations which show quantifiable benefits of our novel approach. In particular, we consider in detail the emergency medical application of mass casualty incidents and are able to demonstrate that our approach of integrating transfer of control strategies results in effective allocation of patients to doctors: ones which in simulations re- sult in dramatically fewer patients in a critical healthstate than are produced by competing MARA algorithms. In short, we offer a principled solution to the problem of preemption, allowing the elimination of a source of inefficiencies in fully distributed multiagent resource allocation systems; a faster method for generation of transfer of control strategies; and a convincing application of the system to a real world problem where human lives are at stake.

Addressing inequities in health both within and between countries has attracted considerable global attention in recent years. In theory, equity remains one of the key policy objectives of health systems and underpins the allocation of health sector resources in many countries. In practice, however, current evidence demonstrates that only limited progress has been made in terms of bridging the health inequity gap and improving the health of the least advantaged. The persistence of inequities in health and health outcomes raises concerns about how governments and health authorities distribute limited health resources to improve the health of the poor and most vulnerable and thereby promote equity. This thesis is about equity and allocation of financial resources in the health system of New South Wales, one of the eight states of Australia. It investigated the extent to which there has been a movement towards equity in resource allocation to Area Health Services under the NSW Health Resource Distribution Formula and whether this has been reflected in equitable resource allocation within Area Health Services. It considered only resources allocated through the NSW Department of Health. The study employed a combination of qualitative and quantitative methods to gather and analyse data. The qualitative component analysed data gathered through semi–structured interviews with policy makers, health executives, managers, and other stakeholders to establish the resource allocation processes and the factors upon which the allocation decisions were based. The quantitative component analysed health expenditure and health needs data to assess the extent to which allocation of resources from the State to Area Health Service levels has been equitable in terms of reflecting the level of health needs. Two indices were constructed and used as proxies for health needs. Principal component analysis was used in the construction of one of the indices, using demographic, socio–economic and health-related data. The other index was developed using a combination of premature mortality and morbidity data. The quantitative study spans the two decades 1989/90 to 2006/07, with a more detailed analysis of material for the years 2003/04 to 2006/07. The findings of the study show a considerable degree of inequity in resource allocation with several Area Health Services (AHSs) receiving less than a fair share of funding for the years analysed, although some movements towards equity were evident. This contradicts the general impression that the introduction of the resource distribution formula in NSW has significantly improved equity in resource allocation. In general, funding allocation at the State level correlated significantly with population size but not with health needs of the eight AHSs in NSW. Similarly, within the AHSs, allocation of funds was based on programs and services and not on health needs. Key issues that emerged from the qualitative data as affecting the equity with which health funds are allocated in the NSW health system include limited use of the resource distribution formula at the state level, lack of an effective resource allocation tool to guide the distribution of funds within AHSs, and insufficient emphasis on equity at the AHS level. It is crucial that these and several other issues identifies in the study are addressed if current inequities in funding and in health outcomes generally are to be effectively reduced.

Addressing inequities in health both within and between countries has attracted considerable global attention in recent years. In theory, equity remains one of the key policy objectives of health systems and underpins the allocation of health sector resources in many countries. In practice, however, current evidence demonstrates that only limited progress has been made in terms of bridging the health inequity gap and improving the health of the least advantaged. The persistence of inequities in health and health outcomes raises concerns about how governments and health authorities distribute limited health resources to improve the health of the poor and most vulnerable and thereby promote equity. This thesis is about equity and allocation of financial resources in the health system of New South Wales, one of the eight states of Australia. It investigated the extent to which there has been a movement towards equity in resource allocation to Area Health Services under the NSW Health Resource Distribution Formula and whether this has been reflected in equitable resource allocation within Area Health Services. It considered only resources allocated through the NSW Department of Health. The study employed a combination of qualitative and quantitative methods to gather and analyse data. The qualitative component analysed data gathered through semi–structured interviews with policy makers, health executives, managers, and other stakeholders to establish the resource allocation processes and the factors upon which the allocation decisions were based. The quantitative component analysed health expenditure and health needs data to assess the extent to which allocation of resources from the State to Area Health Service levels has been equitable in terms of reflecting the level of health needs. Two indices were constructed and used as proxies for health needs. Principal component analysis was used in the construction of one of the indices, using demographic, socio–economic and health-related data. The other index was developed using a combination of premature mortality and morbidity data. The quantitative study spans the two decades 1989/90 to 2006/07, with a more detailed analysis of material for the years 2003/04 to 2006/07. The findings of the study show a considerable degree of inequity in resource allocation with several Area Health Services (AHSs) receiving less than a fair share of funding for the years analysed, although some movements towards equity were evident. This contradicts the general impression that the introduction of the resource distribution formula in NSW has significantly improved equity in resource allocation. In general, funding allocation at the State level correlated significantly with population size but not with health needs of the eight AHSs in NSW. Similarly, within the AHSs, allocation of funds was based on programs and services and not on health needs. Key issues that emerged from the qualitative data as affecting the equity with which health funds are allocated in the NSW health system include limited use of the resource distribution formula at the state level, lack of an effective resource allocation tool to guide the distribution of funds within AHSs, and insufficient emphasis on equity at the AHS level. It is crucial that these and several other issues identifies in the study are addressed if current inequities in funding and in health outcomes generally are to be effectively reduced.

Thesis (Ph. D.)--University of Washington, 1989. / Vita. Includes bibliographical references (leaves [183]-197).

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--Ohio University, June, 2000. / Title from PDF t.p.

Thesis (Ph.D.)--Drexel University, 2008. / Includes abstract and vita. Includes bibliographical references (leaves 85-89).