Browsing by Author "Gamgam, Onur Berkay"
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Item Open Access Regenerator placement in elastic optical networks with adaptive modulation and coding(Bilkent University, 2016-09) Gamgam, Onur BerkayDue to the rapid and diverse increase in the tra c load on the optical networks, e cient utilization of the network resources becomes an important issue. Using di erent modulation formats and coding rates in optical signal transmission, it is possible to assign di erent spectral e ciency and optical reach for each tra c requests. To satisfy the quality of transmission (QoT) for the distances beyond optical reach, optical - electronic - optical (O/E/O) 3R regeneration of the optical signal is required. During the regeneration process, the spectral e ciency and thus optical reach of the resultant signal can also be set. In these circumstances, by selecting speci c regenerator node locations and assigning di erent line rates for each tra c request, the network utilization can be optimized. Joint selection of regenerator placement (RP), routing and adaptive modulation and coding (AMC) pro le in elastic optical networks (EON) is studied to propose an o ine RP algorithm for a given network topology with link length and link capacity constraints. For a given RP, an Integer Linear Programming (ILP) model is formulated to perform routing and AMC pro le assignment for each tra c demand. We use two di erent approaches for determining candidate paths for routing: In the rst set, k shortest paths (KSP) are utilized for all cases. In the second set, namely regenerator location dependent path selection (RLDPS), the candidate paths are determined according to the given RP. To nd the minimum cost RP among all possibilities, Tabu Search based regenerator placement algorithm (TSRPA) is proposed. Results show that adaptively selecting the candidate paths based on the regenerator locations reduces network utilization either by decreasing the number of regenerator nodes by up to 66.6% or decreasing link capacity utilization by up to 5.09% as compared to selecting candidate paths as xed k shortest paths. The regenerator node location distribution obtained with RLDPS concentrated on smaller number of nodes compared to the results obtained with KSP. By placing regenerators at a signi cantly less number of nodes, capital expenditures (CAPEX) are reduced by RLDPS.Item Open Access Satisfying strict deadlines for cellular internet of things through hybrid multiple access(John Wiley and Sons Inc, 2023-08) Gamgam, Onur Berkay; Karasan, EzhanLatency-constrained aspects of cellular Internet of Things (IoT) applications rely on Ultra-Reliable and Low Latency Communications (URLLC), which highlight research on satisfying strict deadlines. In this study, we address the problem of latency-constrained communications with strict deadlines under average power constraint using Hybrid Multiple Access (MA), which consists of both Orthogonal MA (OMA) and power domain Non-Orthogonal MA (NOMA) as transmission scheme options. We aim to maximize the timely throughput, which represents the average number of successfully transmitted packets before deadline expiration, where expired packets are dropped from the buffer. We use Lyapunov stochastic optimization methods to develop a dynamic power assignment algorithm for minimizing the packet drop rate while satisfying time average power constraints. Moreover, we propose a flexible packet dropping mechanism called Early Packet Dropping (EPD) to detect likely to become expired packets and drop them immediately. Numerical results show that Hybrid MA improves the timely throughput compared to conventional OMA by up to (Figure presented.) and on average by more than (Figure presented.). With EPD, these timely throughput gains improve to (Figure presented.) and (Figure presented.), respectively.Item Open Access Timely throughput maximization using multiple access channel(Bilkent University, 2023-10) Gamgam, Onur BerkayLatency and reliability capabilities of currently available fourth-generation (4G) wireless networks paved the path towards massively connected devices requiring much lower latency and much higher reliability. In the fifth-generation (5G) wireless networks, the concept of ultra-reliable and low-latency communications (URLLC) is introduced to fulfill these demands. URLLC aims to deliver short packets with 1 ms latency with a reliability rate of 99.999%. The cellular Internet of Things (IoT) is a framework for conceptualizing such massive connectivity while addressing fundamental challenges such as the ever-increasing number of interconnected devices, latency constraints, and high-throughput demands. One of the challenging tasks for cellular IoT applications is the delivery of deadline-constrained information to densely deployed IoT devices. Increasing demand for delivering timing-critical information in cellular IoT networks poses a URLLC-oriented challenge for both academia and industry. With this motivation, this thesis aims to develop techniques for reliably transferring short packets to densely deployed devices within a given deadline. In this thesis, we address the problem of latency-constrained communications with strict deadlines under average power constraint using Multiple Access (MA) schemes. The first MA scheme considered in the thesis is Hybrid MA, which consists of both Orthogonal MA (OMA) and power domain Non-Orthogonal MA (NOMA) as transmission scheme options. The second MA scheme studied in the thesis is Rate-Splitting Multiple Access (RSMA), which generalizes OMA, NOMA and Space-Division MA (SDMA) schemes. We maximize the timely throughput, which represents the average number of successfully transmitted packets before deadline expiration, where expired packets are dropped from the buffer. We use Lyapunov stochastic optimization methods to develop a dynamic power assignment algorithm for minimizing the packet drop rate while satisfying time average power constraints. Moreover, we propose a flexible packet dropping mechanism called Early Packet Dropping (EPD) to detect likely to become expired packets and drop them proactively. Finally, we propose a simple heuristic to reduce the computational load of the proposed algorithm. Numerical results show that Hybrid MA improves the timely throughput compared to conventional OMA by up to 46% and on average by more than 21%. With EPD, these timely throughput gains improve to 53% and 24.5%, respectively. Utilization of RSMA with EPD further improves timely throughput by up to 5.95% and on the average by about 3.12% compared to Hybrid MA with EPD. Simulation results indicate that the proposed heuristic significantly reduces the computational load at the cost of a small loss in the timely throughput performance.