Server Based Solutions for Self-Organizing Networks

February 1, 2017 | 11:07
Server Based Solutions for Self-Organizing Networks
Server Based Solutions for Self-Organizing Networks
The evolution of networks across generations of evolving protocols has led to a complex mixture of deployed wireless systems. Development towards 5G and the increasing use of heterogeneous networks (HetNets) to improve coverage with fill-in solutions has created an environment of growing complexity, whose management and resource allocation has become a key issue for network operators.

This article aims to present the ideas and initiatives driving self-organizing networks (SONs), a key enabler for effective 5G deployment. The authors look closely at the challenge of a data center-based eNodeB pool in a Cloud RAN (C-RAN) context and present a possible solution based on open standard technologies.
                   
Optimized spectral efficiency
In addition to growing network complexity, there is also an alarming shortage of bandwidth in the radio spectrum. The ability to optimize the networks to maximize the spectral efficiency of wireless coverage is key to the future of user bandwidth delivery. Invariably this means rationing spectrum by providing just enough resource for the type of device connected. Developments such as Narrow-band LTE (NB-LTE), for example, will be a key enabling technology for the Internet of Things (IoT). The management and coordination of networks with a mix of these 200-kHz bands alongside conventional 1.5-MHz to 20-MHz bands will soon be the norm.
 
Adaptation
And it’s not just spectral efficiency of mobile communications. As the airwaves become more congested, blocking signals from other sources becomes a prime obstacle to attaining maximum data bandwidth. The ability for a network to adapt to the spectral environment in a coordinated fashion provides a great advantage to maintaining the best service. LTE already includes Channel Quality Indicators (CQIs) for channel allocation within a band, and if a network can be devised which spans multiple bands then these same CQIs could be use at a high level of abstraction to favor the operation of different bands within different locations.
 
Dynamic geographic allocation
Lastly, geographic network demand is seldom static over time. The peak demand during the working day is likely to be concentrated in the commercial districts while an evening profile may be skewed by a sports event in one area or a concert event in another. The network needs to address this temporal shift in demand. Activation of fill-in cells and the direction of network processing resources to the cells experiencing heavy user registration are key for network bandwidth management.
 
Self-organizing networks
Software Defined Networking (SDN) and Network Functions Virtualization (NFV) are initiatives which promise to free the network from the rigid framework of one-off network provision, and which are key enablers for Self-organizing Networks (SONs). This requires the challenging re-imagining of network components and architectures around a central point of intelligence and coordination.

This central point of a Co-operative MultiPoint (CoMP) network finds a natural home in the data center. It is already home to the Evolved Packet Core (EPC) in large networks and is the center for routing and policy management. Adding network management capabilities enables the support of hosting multi-tenant Mobile Virtual Networks (MVNs) and the ability to time-share network resources as part of service contracts.

Co-locating the higher layers of the LTE protocol stack here also provides a much richer source of network management data. This can be used to fuel the intelligence of network organization, for example by providing access to data mining tools and facilitating more predictive network analysis. It’s conceivable that using the GPS component of mobile data to anonymously track users would support resource allocation before it is required, such as turning on a fill-in cell as a crowd gathers at a rock concert.

A side benefit is that the data center offers a less challenging environment than most base station locations, reducing the CapEx cost of equipment ruggedisation. Advanced cooling and power management technologies in this environment save energy; and providing a single point-of-service access reduces OpEx.
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