Ph.D. Theses
Permanent URI for this collection
Browse
Browsing Ph.D. Theses by Author "Akar, Mehmet."
Now showing 1 - 4 of 4
Results Per Page
Sort Options
Item Consensus based power control algorithms for heterogenous networks(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2016., 2016.) Şenel, Kamil.; Akar, Mehmet.The resource allocation problem is crucial for unveiling the potential of heterogeneous networks. The demand for higher data rates from an increasing number of devices compels the operators to look for solutions beyond the traditional network architecture. Heterogeneous network architecture is a promising solution to provide data rates required by the emerging applications and high-speed multimedia services. In this dissertation, we focus on the interference management for heterogeneous networks which is a major problem to be resolved and propose solutions based on power control techniques. We utilize the inherent advantages of consensus algorithms such as non-essentially of objective functions and fairness to design power control algorithms suitable for the task of resource allocation in heterogeneous networks. In this dissertation, several novel, distributed and self optimized power adjustment algorithms are proposed. Contrary to the approaches in the literature, the instantaneous or statistical measurements on channel gains are not required during the power adjustment process. The convergence analyses reveal that the proposed algorithms achieve optimum solution for the power allocation problem with fairness constraints, even under a setup with imperfect communication links. Furthermore, the theoretical analyses show that the convergence properties of the proposed algorithms are preserved under di erent spectrum allocation schemes. The numerical analyses are in agreement with the theoretical analyses and demonstrate signi cant improvement in terms of overall network performance.Item Convergence rate analysis and optimization of distributed consensus algorithms(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2014., 2014.) Cihan, Onur.; Akar, Mehmet.The problem of achieving a common value in a distributed information sharing context, referred to as distributed consensus or agreement, is an important topic that has drawn significant research attention of late. Consensus algorithms find applications in many areas including network clock synchronization, sensor fusion and load balancing where achieving consensus as fast as possible is important. In this dissertation, we study the analysis and optimization of convergence rate of averaging based distributed consensus algorithms evolving on graphs. By relating the convergence speed of the algorithm to the mixing rate of a Markov chain, we propose two semi–definite programming (SDP) methods of assigning transition probabilities to a Markov chain in order to optimize its mixing rate. In the first SDP formulation, there is a single transition probability parameter to be optimized (the holding probability of vertices) which leads to easier and faster computation as opposed to the more general reversible Markov chain formulation corresponding to a stationary distribution that is proportional to the degree of vertices. By deriving exact analytical results, it is shown that both the single parameter and the degree proportional reversible fastest mixing Markov chain formulations yield better results than the symmetric SDP formulation for a path and some well–known edge–transitive and orbit graphs. The convergence rate of the averaging based distributed consensus algorithm is also analyzed for networks where delay exists in data receptions, which is unavoidable in practice. After introducing the delayed version of the consensus algorithm, it is analytically shown that bounded non–uniform delay does not adversely affect its convergence rate for directed acyclic graphs.Item Distributed group consensus in multi - agent networks(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2017., 2017.) Erkan, Özlem Feyza.; Akar, Mehmet.Recent advances in computing and communication technologies have led to considerable progress in multi-agent networks. A variety of applications ranging from social networks to intelligent transportation systems makes the area promising in the sense that it seeks solutions to crucial questions in all realms of life. Among various issues studied in the context of multi-agent networks, the distributed consensus problem where a group of agents working collectively to achieve a common objective, has been one of the most popular. A multi-agent network utilizing a distributed linear consensus protocol may converge to different final values depending on the structure of the communication topology. The focus of this dissertation is to analyze the convergence properties of such networks where multi-equilibria consensus emerge. The problem is first examined for undirected networks represented by static or time-varying graphs. Joint connectivity and integral/sum connectivity conditions are presented that can be utilized to determine the number of equilibria as the interactions among the agents evolve over time. Subsequently, the analysis is extended to the study of multi-equilibria consensus in directed networks for which novel concepts of primary and secondary layer subgraphs are introduced. It is theoretically shown that the number of consensus equilibria of a network can be expressed as the total number of these subgraphs which can automatically be determined by a computer program. The convergence properties of multi-equilibria consensus in directed networks with bounded time-delays are also investigated and it is shown that communication time-delays do not affect the number of equilibria of a given network.Item Resource allocation methods for next-generation networks(Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2023., 2023) Altın, İlke.; Akar, Mehmet.In 5G and beyond systems, the number of connections and data traffic is expected to grow significantly. To support the ever- increasing requirements, new solutions such as Mobile Edge Computing (MEC), Non-Orthogonal Multiple Access (NOMA), and Heterogeneous Networks (HetNets) are studied extensively. This thesis focuses on the resource allocation methods for uplink Hybrid NOMA for MEC offloading, downlink Hybrid NOMA, and downlink HetNets. First, a joint resource allocation that minimizes the total energy consumption of users for uplink Hybrid NOMA MEC Offloading is proposed. By solving the joint optimization problem, we propose a novel optimal Hybrid NOMA scheme referred to as Switched Hybrid NOMA for power and time allocation. Subsequently, we propose an algorithm to solve the sub-channel allocation (SCA) problem. We demonstrate that the proposed methods outperform the results in the literature analytically and by simulations. Then, we switch to the downlink communication, and study a resource allocation scheme that minimizes the total weighted energy consumption in the network. We propose a novel optimal Hybrid NOMA scheme for two users and then extend this idea to multiple users. Via simulations, we demonstrate that the Hybrid NOMA method outperforms Orthogonal Multiple Access (OMA) and NOMA methods. Afterward, we investigate novel distributed sub-channel and power allocation algorithms for HetNets. We introduce an SCA algorithm that minimizes the effective interference experienced by users in the network. Then, a distributed algorithm for power allocation is proposed, and a joint resource allocation method is constructed by combining the proposed algorithms, which outperforms the existing methods in the literature.