QoS performances of heterogeneous networks with multiple radio access technologies

The paper presents a QoS framework for terminals with multi-RAT (multiple radio access technologies) interfaces for heterogeneous network environment. It investigates a QoS provisioning with vertical multi-homing and multistreaming features for 5G heterogeneous networks. The presented enhanced framework for 5G systems leads to better performance opportunities for multimedia services with very high level of QoS provisioning in different radio access network (RAN) conditions. The system framework is user-centric oriented, with ability to simultaneously handle multiple RAN connections, choosing the most appropriate RAN for each used service. This paper evaluates the key QoS parameters for multimedia traffic in heterogeneous mobile and wireless scenarios were multiple RANs coexist in the simulation set up. The simulation scenarios includes 3G, 4G, and 5G radio access networks and use Genetic Algorithm and Linear Programming algorithm to solve the optimization problem. The analysis shows significantly high QoS performance for the achievable aggregated throughput and multimedia access probability ratio in heterogeneous wireless and mobile environment, especially in case of large number of available heterogeneous nodes.

[1]  Valentin Rakovic,et al.  Visions Towards 5G: Technical Requirements and Potential Enablers , 2016, Wirel. Pers. Commun..

[2]  K. Radhika,et al.  Network selection in heterogeneous wireless networks based on Fuzzy Multiple criteria Decision Making , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[3]  Nikos I. Passas,et al.  Network Selection Algorithm for Heterogeneous Wireless Networks: from Design to Implementation , 2009, Netw. Protoc. Algorithms.

[4]  Xiqi Gao,et al.  Cellular architecture and key technologies for 5G wireless communication networks , 2014, IEEE Communications Magazine.

[5]  Junyi Li,et al.  Network densification: the dominant theme for wireless evolution into 5G , 2014, IEEE Communications Magazine.

[6]  Andreas Mitschele-Thiel,et al.  Latency Critical IoT Applications in 5G: Perspective on the Design of Radio Interface and Network Architecture , 2017, IEEE Communications Magazine.

[7]  Toni Janevski.  5G Mobile Phone Concept , 2009, 2009 6th IEEE Consumer Communications and Networking Conference.

[8]  Aleksandr Ometov,et al.  Effects of Heterogeneous Mobility on D2D- and Drone-Assisted Mission-Critical MTC in 5G , 2017, IEEE Communications Magazine.

[9]  Toni Janevski,et al.  5G mobile terminals with advanced QoS-based user-centric aggregation (AQUA) for heterogeneous wireless and mobile networks , 2015, Wireless Networks.

[10]  Oriol Sallent,et al.  A novel joint radio resource management approach with reinforcement learning mechanisms , 2005, PCCC 2005. 24th IEEE International Performance, Computing, and Communications Conference, 2005..

[11]  Aladdin Ayesh,et al.  Access Network Selection Based on Fuzzy Logic and Genetic Algorithms , 2008, Adv. Artif. Intell..

[12]  Josef Noll,et al.  5G: Service Continuity in Heterogeneous Environments , 2011, Wirel. Pers. Commun..

[13]  Toni Janevski,et al.  Radio Network Aggregation for 5G Mobile Terminals in Heterogeneous Wireless and Mobile Networks , 2014, Wirel. Pers. Commun..

[14]  Abdul Jabbar,et al.  Design and Analysis of a 3-D Gauss-Markov Model for Highly Dynamic Airborne Networks , 2010 .

[15]  Robert W. Heath,et al.  Five disruptive technology directions for 5G , 2013, IEEE Communications Magazine.

[16]  B. Bangerter,et al.  Networks and devices for the 5G era , 2014, IEEE Communications Magazine.

[17]  Navrati Saxena,et al.  Efficient IoT Gateway over 5G Wireless: A New Design with Prototype and Implementation Results , 2017, IEEE Communications Magazine.