4 Concepts and background

32.5213GPPRelease 11RequirementsSelf-Organizing Networks (SON) Policy Network Resource Model (NRM) Integration Reference Point (IRP)Telecommunication managementTS

4.1 Overview

A self-optimization functionality will monitor input data such as performance measurements, fault alarms, notifications etc. After analyzing the input data, optimization decisions will be made according to the optimization algorithms. Finally, corrective actions on the affected network node(s) will be triggered automatically or manually when necessary.

IRPManager should be able to control the self-optimization procedures according to the operator’s objectives and targets.

The following diagram is illustrated how the self-optimization functionality works:

Loop: Keep Monitoring

Is system status better after the corrective actions’ execution?

Analyse input data with Optimization Algorithms

Execute corrective actions

Monitor input data

One time Self-optimization procedure ends

Fallback may be needed to reverse the system to the previous status, which is before the corrective actions executed.

Yes

No

Meet the targets?

Yes

No

Figure 4-1 Logical view of self-optimization procedure

The self-optimization functionality working procedure could be interpreted logically as following:

1. The self-optimization functionality keeps monitoring input data according to the operator’s objectives and targets.

2. Whenever the objectives and targets are not met, optimization algorithms will be triggered.

3. Corrective actions are provided and executed.

4. Then the self-optimization functionality evaluates the result of the executed corrective actions.

    1. If the system status is not satisfactory after the corrective actions’ execution, fallback may be needed to reverse the system configuration to the previous status, which is before the corrective actions executed.
    2. If the system status is satisfactory after the corrective actions’ execution, the one time self-optimization procedure ends.

5. Self-optimization functionality returns to monitoring the input data.

4.2 Self-Optimization Concept

4.2.1 Logical Function Blocks

4.2.1.1 Self-Optimization Input Monitoring Function (SO_MON_F)

This functional bloc supports the following functions: [SO1].

4.2.1.2 Triggering Optimization Function (TG_F)

This functional bloc supports the following functions: [SO2], [SO3].

4.2.1.3 Optimization Fallback Function (O_FB_F)

This functional bloc supports the following functions: [SO7], [SO9], [SO10].

4.2.1.4 Self-Optimization Progress Update Function (SO_PGS_UF)

This function updates the self-optimization progress and important events to the operator: [SO11]

4.2.1.5 NRM IRP Update Function (NRM_UF)

This function updates the E-UTRAN and EPC NRM IRP with the optimization modification if needed.

4.2.1.6 Self-Optimization Monitoring and Management Function (SO_MMF)

This function monitors the self-optimization process and provides the operator with this information. This function must be able to get information about all other functional blocs. In addition to this it allows the operator to control the execution of the self-optimization process.

This function also resolves conflicts of different SON functions trying to change or actually changing parameter values in different directions or reports such conflicts, if they cannot be solved.

4.2.1.6.1 Self-Optimization Monitoring and Management Function (SO_MMF_NM)

SO_MMF_NM (IRP Manager): representing the NM portion of SO_MMF (necessary monitoring and limited interaction capabilities to support an automated optimization), as well as related IRPManager functionality

In a centralized conflict resolution approach SO_MMF_NM identifies and resolves conflicts.

In distributed and hybrid conflict resolution approach SO_MMF_NM sends policy directions towards the SO_MMF_EM.

4.2.1.6.2 Self-Optimization Monitoring and Management Function (SO_MMF_EM)

SO_MMF_EM (IRP Agent): representing the portion of SO_MMF operating below Itf-N, as well as related IRPAgent functionality

In distributed and hybrid conflict resolution approach SO_MMF_EM identifies, resolves and/or reports conflicts, according to the policy directions received by SO_MMF_NM.

In case SO_MMF_EM is not able to solve a conflict, it will request the SO_MMF_NM to resolve the conflict.

4.2.1.7 Load Balancing Function (LB_F)

This function handles the load balancing optimization.

4.2.1.8 Interference Control Function (IC_F)

This function handles the interference control optimization.

4.2.1.9 Coverage and Capacity Function (CC_F)

This function handles the coverage and capacity optimization.

4.2.1.10 RACH Optimization Function (RACH_F)

This function handles the RACH optimization.

4.2.1.11 HandOver Optimization Function (HO_F)

This function handles the handover optimization.

4.3 SON Coordination Concepts

When multiple SON functions attempt to change some (same or associated) network configuration parameters of some (same or associated) nodes, one or more of these SON functions may not be able to achieve the operator’s specified SON target(s) (for individual SON function) since they may have conflicting demands on network resources. This situation is considered as “SON functions in conflict” and requires conflict prevention or resolution. Detection of “SON functions in conflict” can be Use Case specific (for example, two SON functions make change at the same time or during the impact time interval).

The associated network configuration parameters include parameters within the same network element or parameters of different network elements with impact between each other. For example, the associated parameters of one cell are the parameters of its neighbour cells. Another typical association example is the TX power, antenna azimuth and tilt of one cell are associated with each other.

Different SON functions may have dependancies with each other. The behaviour of one SON function may have influence on other SON functions. For example, CCO function may adjust the Neighbour Relation due to coverage optimization, and then the changed NR will have an influence on Handover Parameter Optimization function.

SON coordination is to detect, prevent or resolve conflicts or negative influences between SON functions to make SON functions comply with operator’s policy.