QoE-oriented cross-layer downlink scheduling for heterogeneous traffics in LTE networks

With the soaring demands for high speed data communication, as well as transmission of various types of services with different requirements over cellular networks, having a decent radio resource management is considered vital in Long Term Evolution (LTE) system. In particular, satisfying the Quality of Service (QoS) requirements of different applications is one of the key challenges of radio resource management that needs to be dealt by the LTE system. In this paper, we propose a cross-layer design scheme that jointly optimizes three different layers of wireless protocol stack, namely application, Medium Access Control (MAC), and physical layer. The cross-layer optimization framework provides efficient allocation of wireless resources across different types of applications (i.e., real-time and non real-time) run by different users to maximize network resource utilization and user-perceived quality of service, or also known as Quality of Experience (QoE). Here, Mean Opinion Score (MOS) is used as a unified QoE metric that indicates the user-perceived quality for real-time or multimedia services notably video applications. Along with multimedia services, the proposed framework also takes care of non-real-time traffic by ensuring certain level of fairness. Our simulation, applied to scenarios where users simultaneously run different types of applications, confirms that the proposed QoE-oriented cross-layer framework leads to significant improvement in terms of maximizing user-perceived quality as well as maintaining fairness among users

5GAuRA. D3.3: RAN Analytics Mechanisms and Performance Benchmarking of Video, Time Critical, and Social Applications

5GAuRA deliverable D3.3.This is the final deliverable of Work Package 3 (WP3) of the 5GAuRA project, providing a report on the project’s developments on the topics of Radio Access Network (RAN) analytics and application performance benchmarking. The focus of this deliverable is to extend and deepen the methods and results provided in the 5GAuRA deliverable D3.2 in the context of specific use scenarios of video, time critical, and social applications. In this respect, four major topics of WP3 of 5GAuRA – namely edge-cloud enhanced RAN architecture, machine learning assisted Random Access Channel (RACH) approach, Multi-access Edge Computing (MEC) content caching, and active queue management – are put forward. Specifically, this document provides a detailed discussion on the service level agreement between tenant and service provider in the context of network slicing in Fifth Generation (5G) communication networks. Network slicing is considered as a key enabler to 5G communication system. Legacy telecommunication networks have been providing various services to all kinds of customers through a single network infrastructure. In contrast, by deploying network slicing, operators are now able to partition one network into individual slices, each with its own configuration and Quality of Service (QoS) requirements. There are many applications across industry that open new business opportunities with new business models. Every application instance requires an independent slice with its own network functions and features, whereby every single slice needs an individual Service Level Agreement (SLA). In D3.3, we propose a comprehensive end-to-end structure of SLA between the tenant and the service provider of sliced 5G network, which balances the interests of both sides. The proposed SLA defines reliability, availability, and performance of delivered telecommunication services in order to ensure that right information is delivered to the right destination at right time, safely and securely. We also discuss the metrics of slicebased network SLA such as throughput, penalty, cost, revenue, profit, and QoS related metrics, which are, in the view of 5GAuRA, critical features of the agreement.Peer ReviewedPostprint (published version

Quality of experience-oriented cross-layer downlink scheduling for heterogeneous traffic in long term evolution networks

Long Term Evolution (LTE) is a recently evolving technology proposed by Third Generation Partnership Project (3GPP) to provide a smooth migration towards Fourth Generation (4G) of cellular networks. Due to the ever-increasing demands for high speed data communication along with transmission of various types of services over cellular networks, it is of vital importance for the LTE system to has an efficient radio resource management. In particular, satisfying the Quality of Service (QoS) requirements of different applications is one of the key challenges of radio resource management that needs to be dealt by the LTE system. In this thesis, a cross-layer scheduler that interact between three different layers of wireless protocol stack, namely application, the Medium Access Control (MAC) and physical layer is proposed. The cross-layer scheduler provides efficient allocation of the wireless resources across different types of application (i.e., real-time and non real-time) run by different users to maximize network resource utilization and user-perceived quality of service, or also known as Quality of Experience (QoE). Here, Mean Opinion Score (MOS) is used as a unified QoE metric that indicates the user-perceived quality for real-time or multimedia services, notably video applications. Along with multimedia services, the proposed framework also takes care of non-real-time traffic by ensuring a certain level of fairness. In the proposed framework, different modules were employed to handle cross-layer scheduling, including video application, Cross Layer Resource Allocator (CLRA), scheduler and transmitter. Video application module at the application layer buffers the incoming video from backbone and reports video distortion to CLRA module. Next, CLRA exploits the video distortion along with channel distortion from physical layer to estimate MOS value. Finally, based on the obtained MOS value, frame priority weight, QoS delay constraints and channel quality status,in every TTI, the user with the highest weight metric will obtain scheduling opportunity. To appreciate the effectiveness of the proposed framework, two different scenarios of single-cell and multi-cell were taken into considerations. The simulation, applied to scenarios where users simultaneously run different types of applications, confirms that the proposed QoE-oriented cross-layer framework leads to 14.2% and 18% of improvement in terms of user-perceived quality and spectral efficiency respectively

Characterizing energy efficiency for heterogeneous cellular networks

Energy efficiency in wireless networks, especially heterogeneous networks (HetNets) have received a lot of attention due to energy crisis and environmental protection. This emerging trend has motivated the academic and industrial world for new research area, which leads to green networks. In this paper, we provide a brief overview on those studies with an emphasis on introducing some energy efficiency metrics in HetNets such as Energy Consumption Ratio (ECR) and Energy Saving (ES). Since these metrics provide quantified information to compare and assess the efficiency of consumed energy, understanding those metrics can yield insight into the potential energy saving in HetNets. Furthermore, the assessment of potential energy conservation of both energy efficiency metrics will be carried out in different deployment strategies such as macro-micro, macro-relay and micro-relay. The obtained numerical results show that the macro-relay deployment strategy is much energy efficient compared to macro-micro and micro-relay. Therefore, it is concluded that the energy efficiency metrics can be the key measurement for the energy consumption in HetNets

QoE-driven cross-layer downlink scheduling for heterogeneous traffics over 4G networks

With the soaring demands for high speed data communication, as well as transmission of various types of services with different requirements over cellular networks, having a decent radio resource management is considered vital in Long Term Evolution (LTE) system. In particular, satisfying the quality of service (QoS) requirements of different applications is one of the key challenges of radio resource management that needs to be dealt by the LTE system. In this paper, we propose a cross-layer design scheme that jointly optimizes three different layers of wireless protocol stack, namely application, Medium Access Control, and physical layer. The cross-layer optimization framework provides efficient allocation of wireless resources across different types of applications (i.e., real-time and non real-time) run by different users to maximize network resource utilization and user-perceived QoS, or also known as Quality of Experience (QoE). Here, Mean Opinion Score is used as a unified QoE metric that indicates the user-perceived quality for real-time or multimedia services notably video applications. Along with multimedia services, the proposed framework also takes care of non-real-time traffic by ensuring certain level of fairness. Our simulation, applied to scenarios where users simultaneously run different types of applications, confirms that the proposed QoE-oriented cross-layer framework leads to significant improvement in terms of maximizing user-perceived quality as well as maintaining fairness among users