Achieving distributed load balancing in self-organizing LTE radio access network with autonomic network management

Author(s):  
Heng Zhang ◽  
Xue-song Qiu ◽  
Luo-ming Meng ◽  
Xi-dong Zhang
Author(s):  
Ebude Carine Awasume ◽  
Stephen Musyoki ◽  
Vitalice Kalecha Oduol

In order to address the challenges that have come with the exploding demand for higher speed, traffic growth and mobile wireless devices, Mobile network operators have decided to move to the notion of small cells based on cloud radio access network. The merits of cloud based RAN includes the ease of infrastructure deployment and network management as well as the fact that its performance are optimized and it is cost effective the merits of cloud based RAN includes the ease of infrastructure deployment and network management as well as the fact that its performance are optimized and it is cost effective. Notwithstanding, cloud radio access network comes with so many strict requirements to be fulfilled for its fronthaul network. In this paper, we have presented these requirements for a 5G fronthaul network. Particular interest on the time division multiplex passive optical network’s challenge of latency was treated by proposing an optimized version of the round robin dynamic bandwidth allocation algorithm. Results obtained show an improvement in the latency of the original algorithm which meets the fronthaul requirement. Other test parameters like jitter and BER were also improved by our proposed optimized algorithm.


2018 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
Achmad Rizal Danisya ◽  
Rendy Munadi ◽  
Sofia Naning Hertiana

The improvement of Long Term Evolution (LTE) radio access network services is affecting the increased value of traffic load in its network, which is causing traffic unbalance between cells in LTE Radio Access Network (RAN). Users will be served with ineffective resource block allocation which will make the total of gained throughput are not optimal. A method is required to move network load from overloaded cells to underloaded cells in order to balance the resource block allocation optimally. By using NS-3.26 simulation, User Throughput Based (UTB) predictive Mobility Load Balancing (MLB) method is tested with RandomWalkMobilityModel for each user. This method produces an improvement of 2,29 % in average of total throughput of 63,33 % successful optimization.


Sign in / Sign up

Export Citation Format

Share Document