TY - GEN
T1 - Coverage and capacity self-optimisation in LTE-Advanced using active antenna systems
AU - Sharsheer, Mohammad
AU - Barakat, Basel
AU - Arshad, Kamran
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016
Y1 - 2016
N2 - In order to enhance the Long Term Evolution (LTE) network performance, the Third Generation Partnership Project (3GPP) introduced Coverage and Capacity Optimisation (CCO) in the context of Self Organising Network (SON). Antenna parameters (i.e. azimuth, electrical tilt etc.) play a key role in CCO and have a significant impact on the users' Quality of Service (QoS). In this paper, a novel metric, to evaluate the cells performance, that consider several performance indicators, is introduced. Furthermore, a distributed CCO algorithm is proposed which has three distinct phases. The first phase is to determine the target cell, the second phase adjust the antenna parameters for the target and neighbouring cells and in the last phase the optimum antenna parameters for the target and neighbouring cells is determined. The simulation results show significant improvement in the overall network performance with the proposed CCO algorithm. In particular, the target cell average performance can be improved by 16.75%.
AB - In order to enhance the Long Term Evolution (LTE) network performance, the Third Generation Partnership Project (3GPP) introduced Coverage and Capacity Optimisation (CCO) in the context of Self Organising Network (SON). Antenna parameters (i.e. azimuth, electrical tilt etc.) play a key role in CCO and have a significant impact on the users' Quality of Service (QoS). In this paper, a novel metric, to evaluate the cells performance, that consider several performance indicators, is introduced. Furthermore, a distributed CCO algorithm is proposed which has three distinct phases. The first phase is to determine the target cell, the second phase adjust the antenna parameters for the target and neighbouring cells and in the last phase the optimum antenna parameters for the target and neighbouring cells is determined. The simulation results show significant improvement in the overall network performance with the proposed CCO algorithm. In particular, the target cell average performance can be improved by 16.75%.
KW - Coverage and Capacity Optimisation
KW - Long Term Evolution Advanced
KW - Performance Evaluating Metric
KW - Self-Organising Network
UR - https://www.scopus.com/pages/publications/84989835866
U2 - 10.1109/WCNC.2016.7564650
DO - 10.1109/WCNC.2016.7564650
M3 - Conference contribution
AN - SCOPUS:84989835866
T3 - IEEE Wireless Communications and Networking Conference, WCNC
BT - 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016
Y2 - 3 April 2016 through 7 April 2016
ER -