Abstract

Recent developments in mobile networks towards the fifth generation (5G) communication technology have been mainly driven by an explosive increase in mobile traffic demand and emerging vertical applications with their diverse Quality–of–Service (QoS) requirements, which current mobile networks are likely to fall short of satisfying. New technological cost–efficient solutions are, therefore, required to boost the network capacity and advance its capabilities in order to support the QoS requirements of, for example, enhanced mobile broadband services and the ones requiring ultra–reliable low latency communication. Network densification is known to be as one of the promising approaches aiming to increase the network capacity. This is achieved thanks to aggressive frequency reuse at small cells. Nonetheless, this entails performance degradation especially for cell–edge users due to a high Inter–cell Interference (ICI) level. Cloud Radio Access Network (C–RAN) architecture has been proposed as an efficient way to address the aforementioned challenges, tackle some of the problems persistent in the present–day mobile networks (e.g., inefficient use of frequency bands, high power consumption) and, by employing virtualization techniques, facilitate the network management while paving a way for new business opportunities for mobile virtual network operators. The main idea behind C–RAN is to decouple the radio unit of a base station, referred as a Decentralized Unit (DU) from the baseband processing unit, referred as a Centralized Unit (CU) and virtualize the latter in a centralized location, referred as a CU pool. Then, by executing so–called "functional split" in the RAN protocol stack between the CU and the DU, identify the RAN functionalities that are to be performed at the DU and the CU pool. Depending on the selected functional split (i.e., the resource centralization level), the bandwidth and latency requirements vary in the fronthaul network, which is the one interconnecting the DU with the CU pool. This results in a different level of resource centralization benefits. Thus, an inherent trade–off exists between resource centralization benefits and fronthaul requirements in the C–RAN architecture. C–RAN, although provides numerous advantages, raises a series of challenges one of which, depending on the functional split option, is a huge fronthaul bandwidth requirement. Optical fiber, thanks to its high bandwidth and low latency characteristics, is perceived to be the most capable fronthauling option; nevertheless, it requires a huge investment. Fortunately, recent advancement in the MillimeterWave (mmWave) wireless technology allows for multi–Gbps transmission over the distance of one kilometer, therefore, making it a good candidate for the fronthaul network in an ultra–dense small cell deployment scenario. In this doctoral dissertation, we first study the trade–offs between different functional splits, considering the mmWave technology in the fronthaul network. Specifically, we formulate and solve a Virtual Network Embedding (VNE) problem that aims at minimizing the fronthaul bandwidth utilization along with the number of active mmWave interfaces, and therefore, also minimizing the power consumption in the fronthaul network for different functional split scenarios. We then carry out a relative comparison between themmWave and optical fiber fronthauling technologies in terms of their deployment cost in order to ascertain when it would be economically more efficient to employ mmWave fronthaul instead of optical fiber. Different functional splits enable theMobile Network Operators (MNOs) to harvest different level of resource centralization benefits and pose diverse fronthaul requirements. There is no one–fits–all functional split that can be adopted in C–RAN to cope with all of its challenges since each split is more appropriate to be employed in a specific scenario in comparison with the others. Thus, another problem is to select the optimal functional split for each small cell in the network. This is a non–trivial task since there are a number of parameters to be taken into account in order to make such a choice. To this end, we developed a set of algorithms that dynamically select an optimal split option for each small cell considering ICI level as the main criterion. The dynamic functional selection approach is motivated by the argument that a single static functional split is not a viable option especially in the long run. The proposed algorithms provide MNOs with various options to select between promptness, solution optimality, and scalability. After having thoroughly analyzed the C–RAN architecture along with the pros and cons of different functional split options, the main objective for MNOs, who already own mobile network infrastructures and want to migrate to the C–RAN architecture, would be to accomplish such a migration with minimal investments. We developed an algorithm that aims at reducing the required investments by reusing the available infrastructure in the most efficient way. To quantify the economic benefit in terms of Total Cost of Ownership (TCO) savings, a case study is carried out considering a small cluster of an operational Long Term Evolution Advanced (LTE–A) network in the simulation and the proposed infrastructure–aware C–RAN migration algorithm is compared with its infrastructure–unaware counterpart. We also evaluate the multiplexing gain provided by the C–RAN in a specific functional split case and draw a comparison with the one achievable in traditional LTE networks.