With Fifth Generation (5G) mobile networks, the concept of Bandwidth Part (BWP) was introduced to support flexible Orthogonal Frequency-Division Multiplexing (OFDM) subcarrier spacing, also deemed numerologies to achieve lower latency for delay stringent services. A BWP is a set of contiguous Physical Resource Blocks (PRBs) associated to a numerology which is scanned by the User Equipment (UE) to retrieve or submit its data. Additionally, a UE can be connected to multiple slices or services simultaneously thanks to slicing which was introduced in 5G to ensure isolation among multiple co-existing services on the same network. In this context, a BWP switch is required for such users when their services use different numerologies. In this paper, we propose three innovative methods to optimize the BWP Switching process for users connected to multiple slices where both enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communications (URLLC) services are considered. These mechanisms rely on the modification of the Downlink Control Information (DCI) which carries the BWP indicator for users as well as the BWP Inactivity Timer that triggers a Default BWP switch. The performance evaluation demonstrates the high efficiency of our solutions in terms of latency for URLLC services, throughput for eMBB services and number of DCIs scanned compared to the baseline approach.

Fifth generation mobile networks (i.e, 5G) are not only characterized by higher capacity and throughput, but also by the support of heterogeneous services, characterized by different Quality of Service (QoS) requirements in terms of throughput, delay or energy consumption. Such multi-service networks require the partitioning of the available radio resources into mutliple slices, where each service occupies one slice in an isolated manner. However, a static isolation scheme among slices might have a negative impact on radio resource efficiency. For example, when one slice is highly loaded, while the second is lowly loaded, the resources of the first slice are over-utilized, whereas the resources of the second are under-utilized. Consequently, a Dynamic Radio Access Networks (RAN) slicing algorithm is paramount so as to adapt to the different load conditions of services. In that way, the radio resource utilization efficiency is increased, while the different QoS requirements of services are satisfied. In this paper, we tackle this problem by proposing a Dynamic RAN Slicing algorithm based on a crowding game. The algorithm efficiently allocates the resources among heterogeneous RAN slices in a way to satisfy the different QoS requirements of users belonging to different services while increasing the resource utilization efficiency. The results show that our proposed solution overcomes the Static Scheme in terms of QoS guarantee and utilization efficiency.

Edge Computing in 5G and Beyond is a promising solution for ultra-low latency applications (e.g., Autonomous Vehicle, Augmented Reality, and Remote Surgery), which have an extraordinarily low tolerance for delay and require fast data processing for a very high volume of data. The requirements of delay-sensitive applications (e.g., Low latency, proximity, and Location/Context-awareness) cannot be satisfied by Cloud Computing due to the high latency between User Equipment and Cloud. Nevertheless, Edge Computing in 5G and beyond can promise ultra-high-speed data processing thanks to the placement of computation capabilities closer to endpoint devices, where 5G encourages the speed rate that is 10 times faster than 4G LTE-Advanced. This paper deeply investigates Edge Computing in 5G and characterizes it based on the requirements of ultra-low latency applications. As a contribution, we propose a hybrid architecture that takes advantage of novel and sustainable technologies (e.g., D2D communication, Massive MIMO, SDN, and NFV) and has major features such as scalability, reliability, and ultra-low latency support. The proposed architecture is evaluated based on agent-based simulations demonstrating that our proposal can satisfy requirements and has the ability to respond to high volume demands with low latency.

5G RAN aims to evolve new technologies spanning the Cloud infrastructure, virtualization techniques and Software Defined Network capabilities. Advanced solutions are introduced to split the functions of the Radio Access Network (RAN) between centralized and distributed locations. Such paradigms improve RAN flexibility and reduce the infrastructure deployment cost without impacting the user quality of service. We propose a novel functional split orchestration scheme that aims at minimizing the RAN deployment cost, while considering the requirements of its processing network functions and the capabilities of the Cloud infrastructure. With a fine grained approach on user basis, we show that the proposed solution optimizes both processing and bandwidth resource usage, while minimizing the overall energy consumption compared to i) cell-centric, ii) distributed and iii) centralized Cloud-RAN approaches. Moreover, we evaluate the effectiveness of our proposal in a 5G experimental prototype, based on Open Air Interface (OAI). We show that our solution achieves good performance in terms of total deployment cost and resolution time.

5G radio access networks are expected to leverage the Cloud environment for building a cost effective network infrastructure. Advanced mechanisms with functional split are introduced to split the RAN functionalities into centralized and distributed locations. This novelty has brought more flexibility to RAN deployment but is still conditioned to the radio resource availability. In this paper, we propose a new orchestration framework for joint radio and functional split scheme on user basis. Specifically, we address the orchestration of heterogeneous resources in a multi-sited Cloud-RAN infrastructure. The key idea behind our proposal is to optimize jointly the functional split and End-to-End resource allocation in order to achieve an enhanced throughput satisfaction and a low deployment cost. Results show that our approach E2E-US optimizes the heterogeneous resource usage. Indeed, the appropriate user radio load and functional split are dynamically and jointly selected, which outperforms cell centric functional split approaches.

The next 5G infrastructure is expected to serve a multitude of services with heterogeneous requirements, which might be potentially managed by multiple Mobile Virtual Network Operators (MVNOs) that share the same network infrastructure. The new emerging technologies, such as i) Software Defined Networking (SDN), ii) Network Function Virtualization (NFV) and iii) Network Slicing, where physical resources are partitioned and allocated in an isolated manner to a set of services or to MVNOs according to a specific Service Level Agreement (SLA), are seen as the key enabling approaches to fulfill the diversity of requirements of 5G services in a cost-effective manner. In this paper, we design and prototype a network slicing solution, which we have developed in a Cloud-RAN (C-RAN) infrastructure based on the Open Air Interface (OAI) platform and FlexRAN SDN controller. The aim of our work is to validate the feasibility of the prototype in handling the creation and configuration of network slices on-demand, taking into account some requirements that are elaborated from SDN-based slicing applications. By means of emulations, we show that our prototype reacts well to the inputs coming from the SDN application and is finally capable of providing isolation among multiple slices in a dynamic fashion.

Network slicing is considered a key technology for the upcoming 5G system, enabling operators to efficiently support multiple services with heterogeneous requirements, over a common shared infrastructure. In this demo, we present a prototype for managing network slices in the Cloud Radio Access Network (C-RAN), which is considered the reference network architecture for 5G. Our prototype deals with the spectrum slicing problematic and aims at efficiently sharing the bandwidth resources among different slices, while considering their requirements. The prototype makes use of the Open Air Interface (OAI) platform and a specific Software Defined Network (SDN) controller, known as FlexRAN. By using real smart-phones, we run experiments on stage to validate the feasibility of the prototype in configuring multiple slices on-demand, driven by the input of a northbound application.

The massive adoption of Cloud technology in mobile access networks has driven the operators and vendors to work together in order to make Radio Access Network (RAN) ecosystem more agile. In this context, the virtualization of network functions is the cornerstone of a successful Network Function Virtualization (NFV) environment. However, the stringent requirements of RAN functions make their deployment in a Cloud infrastructure more complex and prone to performance issues. In this respect, this paper puts forward a novel approach that adopts an agile orchestration of fine-grained RAN network functions in order to achieve higher flexibility and improve performances. Specifically, we address the orchestration of baseband processing network functions in a multi-sited Cloud infrastructure. To do so, we propose a user-centric solution, denoted UCS-CRAN, that optimizes the split of the baseband units, while considering both the requirements of its processing network functions and the capabilities of Cloud infrastructure. Based on extensive simulations, the results show that our proposal optimizes both processing and bandwidth usage while minimizing the energy consumption compared to cell-centric, distributed and centralized Cloud-RAN approaches.

The provision of service-oriented network resource virtualization, commonly known as network slicing, is envisioned as an answer to the increasing diversity of application demands in evolving 5G mobile networks. Network slicing is helpful in isolating a specified amount of resources in order to accommodate diverse services having heterogeneous requirements that may be conflicting. In this paper, we propose a service-oriented network resource slicing scheme for a Time Division Duplex (TDD) network that, for a pre-defined time duration, forms service-specific network slices based on traffic prediction. The aim of the proposed slicing scheme is to enhance the services, Quality of Experience (QoE) and system resource utilization efficiency by introducing a new degree of flexibility upon allocating resources to different tenants. System-level simulation analysis shows that the proposed scheme improves the performance of high priority services and boosts resource utilization at negligible performance loss for low-priority traffic.

In this paper, we present a novel framework for virtualizing the Long Term Evolution (LTE) base stations to improve the user performance and lower the downlink interference. Our proposal, referred to as “OpeNB”, is an attempt to utilize the benefits of Software Defined Networking (SDN) and OpenFlow, introducing network virtualization in LTE networks with an adaptable, highly extensible, and less invasive manner. The proposed solution consists of a novel network architecture and a mechanism that allows the virtualization of LTE base stations depending on the network state. Simulation results show that the proposed framework improves the average interference, throughput and packet loss experienced by the end users.