With the development of 5G/6G communication technology, an increasing number of communication protocols for data transmission are created and implemented. At the same time, the redundancy of packet headers has become a matter to be optimized when transferring packets across different protocol layers, which causes high resource occupancy, low transmission efficiency and high latency, especially for real-time communications like Voice over IP (VoIP).

The currently standardized Robust Header Compression (RoHC) Algorithm seeks to provide an approach to compressing the protocol headers inscribed in data packets to decrease the amount of data transmission without reducing the communication quality. However, the existing RoHC algorithm is not efficient enough for the requirements of present header compression, as it's initially designed for specific headers like RTP, UDP, and IP. The packet headers must be optimized over the protocol stack for the real-time data stream and the GPRS Tunneling Protocol (GTP) tunnel sections in the 5G network.

An Optimized Header (OH) Compression Algorithm based on the existing RoHC algorithm is proposed in this thesis to compress the headers over the 5G protocol stack in a coordinated fashion for real-time transmission and GTP tunnels. Besides, further development of the OH algorithm is done to optimize protocol headers by merging duplicate header fields for both multiple QoS flows and multi-layer Protocol Data Unit (PDU) flows in the same PDU session. The overall optimization is conducted in the 5G System (5GS) over F1-U and N3 reference points.

The simulation results indicate that the OH algorithm improves the average header compression rate by 45% compared with the RoHC algorithm, as demonstrated via scenario-based 5GS simulations. The average number of transported bits is decreased by 30%, 15% and 26% for Opus coding audio stream, H.264-Opus coding video-audio stream and BLE Version 4.2 triple packets for smartwatch telemedicine stream, respectively, compared with the RoHC algorithm. Besides, the average algorithm execution latency is decreased by 2 μs compared with the RoHC algorithm. Moreover, the multi-stream and multi-layer optimization for the OH algorithm brings about a higher header compression rate and lower execution time in specific scenarios. The overall results indicate that the OH algorithm is capable of compressing the packet size effectively, decreasing the number of transported bits, and shortening the execution time, resulting in higher transmission efficiency and lower latency for VoIP services.

Since the first introduction of 4G in the early 2010s, mobile data traffic has increased significantly, mainly because 4G networks can support more devices, services and applications, as well as greater cellular network coverage. With the advent of the 5G era, the mobile communication system will be further developed. Today, most countries and regions are already implementing their own 5G plans. Compared with China, South Korea and the United States, the three leading countries in the 5G market, the EU’s 5G plans are relatively slow.

The focus of this thesis is to explore various 5G deployment and migration options, as well as the current 5G status in different countries and regions. We start with current network technologies, compare and analyze various 5G deployment and migration options. Then we compare the 5G status of the EU with China, South Korea and the United States, and analyze the internal and external factors faced by the EU in the development of 5G. In these two analysis, we will consider several communication services that are currently used in the mobile network, including, but not limited to, voice/video calling and messaging, for both home usage and roaming usage. Finally, based on the above two analysis, suggestions for EU operators in 5G deployment and development are provided, along with recommendations for future research.

With the proliferating networks, resource allocation based on Quality of Service (QoS) constraints mapping has been one of the difficulties faced by Internet Service Providers (ISP). The advent of new technologies such as virtualization and cloud computing have enabled the users to access content from anywhere around the world. This results in a need for an efficient and fast resource allocation method based on demand acting on the network. Many researchers have developed various algorithms to address this issue. However, they have considered only flow-based network properties, while the contemporary networks communicate mostly through path-based communication using the shortest paths. Inverse shortest path algorithm (ISPA) is a graph-theory based heuristic developed to solve this network resource allocation problem which considers both flow-based communication properties through Effective resistance matrix and path-based communication properties through shortest path matrix. Nevertheless, ISPA is so far implemented only for unweighted graphs. This study aims at assessing the feasibility of ISPA for weighted graphs by understanding the nature of Inverse shortest path problem (ISPP) bounds in weighted random graphs and implementing ISPA for weighted graphs. ISPP bounds behaviour is studied for weighted graphs by analyses of Q-norm distributions, probability of failure distributions and hopcount distributions. A feasibility condition verifying ISPP bounds is derived in relation with the input parameters of the weighted random graph. The solutions obtained through hop count distribution analysis are observed to be Poissonian in nature. Finally, ISPA is implemented for weighted graphs such that demand matrix can be resolved into a simple distance matrix to obtain solution which is a non-negative weighted Adjacency matrix and feasibility conditions are verified for the solutions obtained through ISPA.

Links play a significant role in the functioning of a complex network. The aim of this thesis is to study the links in a weighted network by introducing two new concepts. The link betweenness centrality of a link is defined as the fraction of shortest paths between all pairs of nodes in a graph that traverses that link. Although link betweenness is a widely known measure that characterizes the link, we introduce the concept, link weight tolerance, to understand the extent to which the weight of the link can be increased or decreased such that the shortest paths in the graph are unaffected, therefore the link betweenness of the links remain the same. We develop a method to generate the positive and negative tolerance of a link. We use examples to illustrate the algorithm and discuss the results. Prior to introducing this concept, in addition to surveying existing network theory measures, we also analyse the metric, betweenness centrality and describe the methods used to generate weighted and unweighted random graphs. To extend the concept of link betweenness, we introduce the second concept, link tension. Link tension provides the information related to the ability of the link to handle transmission of data and shows us the links that are important in a network.

The thesis focuses on investigating the role of IP Multimedia Subsystem (IMS) in 5G networks. IMS already plays a very important role in enabling a wide range of real-time multimedia communication services such as basic phone calls and messaging in the LTE network. Addition of application servers on top of the IMS core can provide enhanced functionalities like presence, advanced messaging and SIP trunking. IMS guarantees quality, security and reliability of multimedia services when serving users without the installation of any application as well as flexibility over access. This sets IMS apart from other third party applications found on the internet. IMS was created with the idea of being adaptable to the evolving technology. With the implementation of the 5G network underway, a study of the impact of this new architecture on the IMS services is imminent. The thesis focuses on the study of different network elements participating in an IMS service as well as investigating IMS voice and video calls over the 5G network.
The thesis consists of two parts: The first part involves exploring the role of IMS in 5G networks. A brief overview of the evolution of mobile networks will help understand the differences between 1G/2G/3G/4G. Following this, IMS and its role in enabling multimedia services in the LTE network is explored. Next, the 5G System Architecture is explained along with components and their functions.
Next, a comparison between the elements in 4G and 5G provides a clear understanding of the technological evolution and the procedure involved. The next steps would include understanding the IMS call flow in LTE networks. This would provide a good foundation to understand how the IMS services will be provided over the 5G network. The second part of the thesis includes testing the voice and video services over Ericsson’s 5G network at their Rijen office. As a starting step, the voice and video services are tested using WebRTC. Upon succeeding in the peer-to-peer test, the next step is establishing connectivity to Ericsson’s IMS network at Kista, Sweden. This will allow the testing of IMS voice and video services over the 5G network. The results are recorded and analysed. These are in agreement with the theoretical expectations.

Multi-access Edge Computing (MEC) is a concept brought up by ETSI and it places computing, storage, processing and network resources into MEC hosts and places these MEC hosts as close as needed to the telecom network edge in order to reduce service latency and bandwidth usage. For self-driving vehicles, streaming video and real-time gaming, the devices involved (e.g. vehicles, cellphones, etc.) might not have enough capabilities to perform all the computations and might not have sufficient storage capacity; MEC can be used here for offloading data computations and content caching. To enhance service quality and user experience, MEC hosts and MEC applications should be located close(r) to the end-users, which increases the number of handovers between MEC hosts to maintain MEC service continuity for mobile end-users as well as the costs for the telecom operators. Therefore, a balance needs to be found. Consider the fact that mobile UEs need MEC service handovers to maintain service continuity and handovers may cause service interruptions which can cause severe degradation to MEC service qualities and user experience, hence the number of handovers between MEC hosts experienced by end-users should be minimized. To find a suitable deployment of MEC hosts and MEC applications in order to minimize the number of handovers, three greedy algorithms and two heuristic algorithms are introduced, implemented, tested, compared and analyzed in this thesis to see which identifies the deployment mechanism that has the smallest number of handovers. When it is time for a mobile UE to connect to a new MEC host and there are multiple potential choices of the new MEC host, the most suitable one for the UE needs to be determined dynamically according to the real-time condition of each possible MEC host. To achieve this, reinforcement learning is considered. Three different reinforcement learning algorithms based on SARSA learning and Deep Q Network are introduced, implemented, tested, compared and analyzed in this thesis. Furthermore, a decision-making mechanism is designed to cope with exceptional situations where the required service quality cannot be guaranteed.

Web Real-Time communication (WebRTC) is a technology that enables web browsers to establish real-time communication services without the need of specific software or plug-ins. This technology is gaining popularity and is already supported by popular browsers such as Google Chrome, Firefox and Safari. The quality of real-time communication services depends highly on latency. For this reason, real-time flows have different requirements than conventional TCP flows which focus mainly on the transfer of bulk traffic. The IETF created the working group RMCAT (RTP Media Congestion Avoidance Techniques) to define requirements for real-time congestion control algorithms. One of the proposed algorithms is Google Congestion Control (GCC). This is the only real-time congestion control algorithm implemented in commercial browsers such as Google Chrome. Unfortunately, the performance of GCC in wireless networks has not been extensively evaluated. It is not clear yet what limitations a WebRTC communication might encounter in this type of networks, especially when it is competing with other type of flows. This project addressed this issue by evaluating GCC in different technologies, namely in wired, WiFi and 4G networks. Controlled testbeds were used for the evaluation. The experiments followed the evaluation guidelines for real-time congestion control algorithms defined by the IETF. GCC proved to be a compliant RMCAT congestion control algorithm in networks with no contention. However, the results obtained in wireless access technologies revealed that GCC collapses when TCP flows are present in the channel. This issue is not attributed to GCC itself but to channel access methods of this type of networks. It is necessary to implement procedures to assign a different QoS to WebRTC flows in order to overcome this problem.