With the emergence of the Internet-of-Things (IoT), communication networks have evolved toward autonomous networks of intelligent devices capable of communicating without direct human intervention. This is known as Machine-to-Machine (M2M) communications. Cellular networks are considered one of the main technologies to support the deployment of M2M communications as they provide extended wireless connectivity and reliable communication links. However, the characteristics and Quality-of-Service (QoS) requirements of M2M communications are distinct from those of conventional cellular communications, also known as Human-to-Human (H2H) communications, that cellular networks were originally designed for. Thus, enabling M2M communications poses many challenges in terms of interference, congestion, spectrum scarcity and energy efficiency. The primary focus is on the problem of resource allocation that has been the interest of extensive research effort due to the fact that both M2M and H2H communications coexist in the cellular network. This requires that radio resources be allocated such that the QoS requirements of both groups are satisfied. In this work, we propose three models to address this problem.
In the first model, a two-phase resource allocation algorithm for H2H/M2M coexistence in cellular networks is proposed. The goal is to meet the QoS requirements of H2H traffic and delay-sensitive M2M traffic while ensuring fairness for the delay-tolerant M2M traffic. Simulation results are presented which show that the proposed algorithm is able to balance the demands of M2M and H2H traffic, meet their diverse QoS requirements, and ensure fairness for delay-tolerant M2M traffic.
With the growing number of Machine-Type Communication Devices (MTCDs) the problem of spectrum scarcity arises. Hence, Cognitive Radio (CR) is the focus of the second model where clustered Cognitive M2M (CM2M) communications underlaying cellular networks is proposed. In this model, MTCDs are grouped in clusters based on their spatial location and communicate with the Base Station (BS) via Machine-Type Communication Gateways (MTCGs). An underlay CR scheme is implemented where the MTCDs within a cluster share the spectrum of the neighbouring Cellular User Equipment (CUE). A joint resource-power allocation problem is formulated to maximize the sum-rate of the CUE and clustered MTCDs while adhering to MTCD minimum data rate requirements, MTCD transmit power limits, and CUE interference constraints. Simulation results are presented which show that the proposed scheme significantly improves the sum-rate of the network compared to other schemes while satisfying the constraints.
Due to the limited battery capacity of MTCDs and diverse QoS requirements of both MTCDs and CUE, Energy Efficiency (EE) is critical to prolonging network lifetime to ensure uninterrupted and reliable data transmission. The third model investigates the power allocation problem for energy-efficient CM2M communications underlaying cellular networks. Underlay CR is employed to manage the coexistence of MTCDs and CUE and exploit spatial spectrum opportunities. Two power allocation problems are proposed where the first targets MTCD power consumption minimization while the second considers MTCD EE maximization subject to MTCD transmit power constraints, MTCD minimum data rate requirements, and CUE interference limits. Simulation results are presented which indicate that the proposed algorithms provide MTCD power allocation with lower power consumption and higher EE than the (Equal Power Allocation) EPA scheme while satisfying the constraints. / Graduate
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/13567 |
| Date | 06 December 2021 |
| Creators | Alhussien, Nedaa |
| Contributors | Gulliver, T. Aaron |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
| Rights | Available to the World Wide Web |
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