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Cross-layer design for OFDMA wireless networks with finite queue length based on game theory
This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.In next generation wireless networks such as 4G- LTE and WiMax, the demand for high data rates, the scarcity of wireless resources and the time varying channel conditions has led to the adoption of more sophisticated and robust techniques in PHY such as orthogonal frequency division multiplexing (OFDM) and the corresponding access technique known as orthogonal frequency division multiplexing access (OFDMA). Cross-layer schedulers have been developed in order to describe the procedure of resource allocation in OFDMA wireless networks. The resource allocation in OFDMA wireless networks has received great attention in research, by proposing many different ways for frequency diversity exploitation and system’s optimization. Many cross-layer proposals for dynamic resource allocation have been investigated in literature approaching the optimization problem from different viewpoints i.e. maximizing total data rate, minimizing total transmit power, satisfying minimum users’ requirements or providing fairness amongst users. The design of a cross-layer scheduler for OFDMA wireless networks is the topic of this research. The scheduler utilizes game theory in order to make decisions for subcarrier and power allocation to the users with the main concern being to maintain fairness as well as to maximize overall system’s performance. A very well known theorem in cooperative game theory, the Nash Bargaining Solution (NBS), is employed and solved in a close form way, resulting in a Pareto optimal solution. Two different cases are proposed. The first one is the symmetric NBS (S-NBS) where all users have the same weight and therefore all users have the same opportunity for resources and the second one, is the asymmetric NBS (A-NBS), where users have different weights, hence different priorities where the scheduler favours users with higher priorities at expense of lower priority users. As MAC layer is vital for cross-layer, the scheduler is combined with a queuing model based on Markov chain in order to describe more realistically the incoming procedure from the higher layers
Non-convex resource allocation in communication networks
The continuously growing number of applications competing for resources
in current communication networks highlights the necessity for efficient resource allocation mechanisms to maximize user satisfaction. Optimization
Theory can provide the necessary tools to develop such mechanisms that will
allocate network resources optimally and fairly among users. However, the
resource allocation problem in current networks has characteristics that turn
the respective optimization problem into a non-convex one. First, current
networks very often consist of a number of wireless links, whose capacity is
not constant but follows Shannon capacity formula, which is a non-convex
function. Second, the majority of the traffic in current networks is generated
by multimedia applications, which are non-concave functions of rate. Third,
current resource allocation methods follow the (bandwidth) proportional
fairness policy, which when applied to networks shared by both concave
and non-concave utilities leads to unfair resource allocations. These characteristics make current convex optimization frameworks inefficient in several
aspects. This work aims to develop a non-convex optimization framework
that will be able to allocate resources efficiently for non-convex resource allocation formulations. Towards this goal, a necessary and sufficient condition
for the convergence of any primal-dual optimization algorithm to the optimal solution is proven. The wide applicability of this condition makes this a fundamental contribution for Optimization Theory in general. A number
of optimization formulations are proposed, cases where this condition is not
met are analysed and efficient alternative heuristics are provided to handle
these cases. Furthermore, a novel multi-sigmoidal utility shape is proposed
to model user satisfaction for multi-tiered multimedia applications more accurately. The advantages of such non-convex utilities and their effect in the
optimization process are thoroughly examined. Alternative allocation policies are also investigated with respect to their ability to allocate resources
fairly and deal with the non-convexity of the resource allocation problem. Specifically, the advantages of using Utility Proportional Fairness as an allocation policy are examined with respect to the development of distributed
algorithms, their convergence to the optimal solution and their ability to
adapt to the Quality of Service requirements of each application
Weighted-DESYNC and Its Application to End-to-End Throughput Fairness in Wireless Multihop Network
The end-to-end throughput of a routing path in wireless multihop network is restricted by a bottleneck node that has the smallest bandwidth among the nodes on the routing path. In this study, we propose a method for resolving the bottleneck-node problem in multihop networks, which is based on multihop DESYNC (MH-DESYNC) algorithm that is a bioinspired resource allocation method developed for use in multihop environments and enables fair resource allocation among nearby (up to two hops) neighbors. Based on MH-DESYNC, we newly propose weighted-DESYNC (W-DESYNC) as a tool artificially to control the amount of resource allocated to the specific user and thus to achieve throughput fairness over a routing path. Proposed W-DESYNC employs the weight factor of a link to determine the amount of bandwidth allocated to a node. By letting the weight factor be the link quality of a routing path and making it the same across a routing path via Cucker-Smale flocking model, we can obtain throughput fairness over a routing path. The simulation results show that the proposed algorithm achieves throughput fairness over a routing path and can increase total end-to-end throughput in wireless multihop networks
Joint Dynamic Radio Resource Allocation and Mobility Load Balancing in 3GPP LTE Multi-Cell Network
Load imbalance, together with inefficient utilization of system resource, constitute major factors responsible for poor overall performance in Long Term Evolution (LTE) network. In this paper, a novel scheme of joint dynamic resource allocation and load balancing is proposed to achieve a balanced performance improvement in 3rd Generation Partnership Project (3GPP) LTE Self-Organizing Networks (SON). The new method which aims at maximizing network resource efficiency subject to inter-cell interference and intra-cell resource constraints is implemented in two steps. In the first step, an efficient resource allocation, including user scheduling and power assignment, is conducted in a distributed manner to serve as many users in the whole network as possible. In the second step, based on the resource allocation scheme, the optimization objective namely network resource efficiency can be calculated and load balancing is implemented by switching the user that can maximize the objective function. Lagrange Multipliers method and heuristic algorithm are used to resolve the formulated optimization problem. Simulation results show that our algorithm achieves better performance in terms of user throughput, fairness, load balancing index and unsatisfied user number compared with the traditional approach which takes resource allocation and load balancing into account, respectively
Improvement of indoor VLC network downlink scheduling and resource allocation
Indoor visible light communications (VLC) combines illumination and communication by utilizing the high-modulation-speed of LEDs. VLC is anticipated to be complementary to radio frequency communications and an important part of next generation heterogeneous networks. In order to make the maximum use of VLC technology in a networking environment, we need to expand existing research from studies of traditional point-to-point links to encompass scheduling and resource allocation related to multi-user scenarios. This work aims to maximize the downlink throughput of an indoor VLC network, while taking both user fairness and time latency into consideration. Inter-user interference is eliminated by appropriately allocating LEDs to users with the aid of graph theory. A three-term priority factor model is derived and is shown to improve the throughput performance of the network scheduling scheme over those previously reported. Simulations of VLC downlink scheduling have been performed under proportional fairness scheduling principles where our newly formulated priority factor model has been applied. The downlink throughput is improved by 19.6% compared to previous two-term priority models, while achieving similar fairness and latency performance. When the number of users grows larger, the three-term priority model indicates an improvement in Fairness performance compared to two-term priority model scheduling
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