Self-organizing network (SON) functions can be characterized by their required cooperation between the network elements (NEs). The cooperation among the NEs can include a multitude of possible actions, such as reporting of alarms or coordination of joint parameter modifications at multiple NEs. However, the question for the advantage of cooperation among the NEs in SONs is still an open research topic. By limiting the cooperation between the NEs, the required architectures for utilizing the SON function at hand can be simplified, which in turn can lead to cost savings. In this paper, we investigate the impact of degraded cooperation among the NEs on the SON architecture required and on the performance in a joint capacity and coverage optimization (CCO) use case. For the scenario investigated, we observe that the performance decreases dramatically when decreasing the cooperation among the NEs. However, we can also show that the exchange of information, such as the values of considered key performance indicators (KPIs), among the NEs is more important for an efficient operation than the coordination of the NE's actions. Our results show that, a centralized approach outperforms distributed and localized approaches for the CCO use case investigated.
[1]
Ingo Viering,et al.
A Mathematical Perspective of Self-Optimizing Wireless Networks
,
2009,
2009 IEEE International Conference on Communications.
[2]
Limin Xiao,et al.
A mathematical model for joint optimization of coverage and capacity in Self-Organizing Network in centralized manner
,
2012,
7th International Conference on Communications and Networking in China.
[3]
Xue-song Qiu,et al.
Achieving distributed load balancing in self-organizing LTE radio access network with autonomic network management
,
2010,
2010 IEEE Globecom Workshops.
[4]
Nachum Shacham,et al.
Self-organizing networks
,
1988,
Future Gener. Comput. Syst..
[5]
3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (e-utra); Further Advancements for E-utra Physical Layer Aspects (release 9)
,
2022
.
[6]
Gerhard Fettweis,et al.
Force field based joint optimization of strictly monotonic KPIs in wireless networks
,
2012,
2012 IFIP Wireless Days.
[7]
Andreas Mitschele-Thiel,et al.
Cooperative Fuzzy Q-Learning for self-organized coverage and capacity optimization
,
2012,
2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).
[8]
Henning Sanneck,et al.
LTE Self-Organising Networks (SON): Network Management Automation for Operational Efficiency
,
2012
.