Mobile users has moved from second generation satisfying their” voice” communication needs to the third generation networks for their voice and data communication needs. Now, with the next generation networks(NGN) like LTE promising to offer a plethora of services at  significant speeds to satisfy the users completely, right from voice to streaming multimedia to social networking to online gaming to web surfing on the go. Though these NGNs, promises to open new revenue vistas but the costs associated in deploying and managing these networks will dictate the profitability equation and the confidence from the operator’s end to go ahead with the deployment.

OPEX   is estimated to contribute to almost 30% of the total costs associated with the network over an average network lifecycle. Thus, in an effort to decrease these infrastructure configuration and O&M associated OPEX costs, Next Generation Mobile Networks (NGMN) Alliance and 3rd Generation Partnership Project (3GPP) have standardized a set of capabilities known as Self-Organizing Networks (SON) in Releases 8 and 9. SON brings in the level of automation in operations and maintenance to minimize the lifecycle cost of running a network by eliminating manual configuration of equipment at the time of deployment, right through to dynamically optimizing radio network performance during operation. SON simplifies network operation and extends the management to the rapidly increasing number of base stations’ configuration and management with least possible human interaction.

HISTORY

NGMN (Next Generation Mobile Networks) laid the foundations for the initial requirements on Self-Organizing Networks in 2006, and since then several use cases have been defined to cover multiple aspects of the network operations.

The generation of SON-specific requirements by the NGMN contributed to the adoption of the SON concept by the 3GPP in TR 36.902 and TR 32.500.

DRIVERS OF SON

Reduction of CAPEX and OPEX

No. of parameters to be set in a network increasing from one technology generation to next

Coordinated and parallel operation of 2G, 3G, LTE and even Wi-Fi.

Configuring and optimizing parameters in HetNets.

(Increasing part of traffic will be on small cells such as microcells, picocells and femto cells. Densifying the networks will be necessary to meet the ever increasing demand for capacity since the amount of spectrum available for mobile services is limited. Hence, networks will consist of cells with very variable size from several kilometres for macrocells down to some few tens of meters for femtocells. Such networks of cells with widely varying cell sizes, and possibly also different radio technologies, are denoted HetNets (feterogeneous networks). Compared to the networks today, which mainly consist of macrocells, the number of network elements will increase dramatically with the development towards HetNets. Configuring and optimizing the parameters in all these network elements represent a complexity that just cannot be handled the same way they have been, and new automatic solutions are clearly needed.)

To be more specific, the MAIN BENEFITS of introducing SON functions in cellular networks

are as follows.

Reduced installation time and costs. Reduced OPEX due to reductions in manual efforts in connection with monitoring, optimizing,

diagnosing, and healing of the network. Reduced CAPEX due to more optimized use of network elements and spectrum. Simplified operations of multi-vendor based system

Improved user experience. Improved network performance Protecting revenue by reducing amount of errors introduced by humans

INTRODUCTION TO LTE ARCHITECTURE

An LTE Network with and without SON

The main FUNCTIONALITY OF SON includes: self-configuration, self-optimization and self-healing.

SELF CONFIGURATION This is the dynamic plug-and-play configuration of newly deployed eNBs. The eNB will by itself configure the Physical Cell Identity, transmission frequency and

power, leading to faster cell planning and rollout. The interfaces S1 and X2 are dynamically configured, as well as the IP address and

connection to IP backhaul. To reduce manual work ANR (Automatic neighbour relations) is used. ANR

configures the neighbouring list in newly deployed eNBs and is optimizing the list configuration during operation.

Dynamic configuration includes the configuration of the Layer 1 identifier, Physical cell identity (PCI) and Cell global ID (CGID).

There are 504 different PCIs available in LTE, the PCI mapping shall fulfill the collision free condition as well as the confusion free. The PCI can be assigned either in a centralized or distributed way.

When centralised assignment is used the OAM system will have a complete knowledge and control of the PCIs. When the distributed solution is used the OAM system assigns a list of possible PCIs to the newly deployed eNB, but the adoption of the PCI is in control of the eNB.

The newly deployed eNB will request a report, sent either by User Equipment (UEs) over the air interface or by other eNBs over the X2 interface, including already in-use PCIs, see figure 1. - The eNB will randomly select its PCI from the remaining values.

o Figure 1, PCI reporting ANR is used to minimize the work required for configuration in newly deployed eNBs

as well as to optimize configuration during operation. Correct and up-to-date neighbouring lists will increase the number of successful

handovers and minimize the number of dropped calls. Before a handover can be executed the source eNB requires the neighbouring

information: PCI and CGID of the target eNB. The PCI is included in every normal measurement report. The mapping between the PCI and CGID parameters can be done by using

information from the OAM or reported by UEs decoding the target cell CGID on the broadcast channel in the target cell, see figure 2. The capability of decoding CGID is an optional UE feature.

o Figure 2, UE supported reporting of CGID

A network operator can put a cell on a ANR black list, to block certain handover candidates, for example from indoor to outdoor cells.

3GPP has also specified LTE Inter-Frequency and Inter-RAT (Radio Access Technology) ANR.

The functions described above are mainly included in Release 8.

SELF OPTIMISATION Functions for self-optimisation are mainly included in Release 9. It includes

optimisation of coverage, capacity, handover and interference. Mobility load balancing (MLB) is a function where cells suffering congestion can

transfer load to other cells, which have spare resources. MLB includes load reporting between eNBs to exchange information about load level and available capacity.

The periodicity of the reporting can be requested in the range of 1 to 10 s. The report can contain, hardware load, S1 transport network load and Radio resource status.

The Radio resource status reports are separated in Up Link and Down Link reports, including the total allocation guaranteed and non-guaranteed bit rate traffic, the percentage of allocated Physical Resource Block (PRB) and the percentage of PRBs available for load balancing.

MLB can also be used between different Radio Technologies. In case of inter-RAT the load reporting RAN Information Management (RIM) protocol will be used to transfer the information via the core between the base stations of different radio technologies.

A cell capacity class value, set by the OAM-system, will be used to compare and weigh the different technologies radio capacities against each other.

A handover due to load balancing is carried out as a regular handover, but it may be necessary to amend parameters so that the User Equipment (UE) does not return to the congested cell.

The amendment must take place in both cells, so that the handover settings remain coherent in both.

The eNBs need to estimate how much the cell border needs to be shifted, expressed in dB, to avoid a quick return of the UE.

Mobility robustness optimization (MRO) is a solution for automatic detection and correction of errors in the mobility configuration. In Release 9 the focus is on errors causing Radio link failure (RLF) due to too late or early handover, or handover to an incorrect cell.

o Figure 3, Late Handover, the UE does not receive the RRC Handover

command, due to weak signal In case of late handover, see figure 3, the handover procedure in the source cell is

initialized too late, since the UE is moving faster than the Handover (HO) parameter settings allow.

Hence when the RRC HO command from the serving cell is transmitted the signal strength is too weak to reach the UE, now located in the target cell, connection is lost.

The UE attempts a connection re-establishment, containing PCID and C-RNTI belonging to the source cell, but received by the target cell. The target eNB will then inform the source cell about RLF to adjust Handover parameters.

o Figure 4, Handover too early, the signal strength in the target cell is too weak,

and the connection is lost almost immediately It is a bit more complicated to detect a too early handover, see figure 4. The UE has successfully been handed over from source cell A to target cell B, but

since it was triggered too early the connection will drop almost immediately due to too poor radio conditions in the target cell B.

The UE will then try to re-establish the connection, which will now take place in the original source cell, cell A, since this cell is the strongest one.

The UE will use the PCID and RNTI from the target cell B and the source cell A will then consider this as a Radio Link Failure due to too late handover and send an indication to the target cell B.

But the target cell B will now recognize the parameters in the indication, as given to a mobile that had just completed a handover to cell B from cell A now indicating failure.

The target cell B will send back a report about too early Handover to adjust Handover parameters, to the source cell A.

In order to save energy some cells can be switched off when capacity is not needed. The power consumption in a base station is not only related to load, a number of

functions requires power even if there are no users to serve. But, if a cell is switched off, in the legal operator license there are still requirements

on coverage, the coverage must be maintained at all times! The suspension of the cell may occur when the last user leaves the cell, all incoming

handovers during this period of time will then be rejected. The cells that remain on, providing coverage, can wake up a suspended cell when

traffic load increase. This can be done with a wake-up call to the sleeping cell.

RACH optimisation aims to minimise the number of attempts on the RACH channel, causing interference.

The UE can be polled by the eNB for RACH statistics after connection. The number of preambles sent until successful RACH completion, and the number of

contention resolution failure are in the statistics. But PRACH configuration parameters can also be distributed amongst eNBs, like

zero correlation configuration, root sequence, high speed flag and PRACH frequency offset.

SELF-HEALING Features for automatic detection and removal of failures and automatic adjustment of

parameters are mainly specified in Release 10. Coverage and Capacity Optimization enables automatic correction of capacity

problems depending on slowly changing environment, like seasonal variations.Minimization of drive tests (MDT), is enabling normal UEs to provide the same type of information as those collected in drive test. A great advantage is that UEs can retrieve and report parameters from indoor environments.

The ARCHITECTURES OF SON are hybrid, distributed and centralised. There are three main alternatives regarding the architecture of SON functions in cellular

networks Centralized SON Distributed SON Hybrid SON

Centralized SON Algorithms are executed at the network management level. Commands, requests and parameter settings data flow from the network management level

to the network elements, while measurement data and reports flow in the opposite direction. Advantages

SON algorithms can take information from all parts of the network into consideration. It is more robust against network instabilities caused by the simultaneous operation of SON

functions having conflicting goals. Multivendor and third party SON solutions are possible. Centralized SON solutions give the operator more control over the network as all information

and control are available at the network management level. Disadvantages

Longer response times. Increased backbone traffic. A single point of failure and

Centralized processing power needed will be large

Distributed SON

SON algorithms are run in the network nodes and the nodes exchange SON related messages directly with each other.

Advantages This architecture can make the SON functions much more dynamic than centralized SON

solutions, so that the network can adapt to changes much more quickly. Distributed SON solutions do not have the scalability and single point of failure problem. Multivendor and third party SON solutions are possible.

Disadvantages Optimizations done at cell level do not necessarily result in optimum operation for the network

as a whole.

implementation of the SON algorithm in the network elements will be vendor specific, so third party solutions will be difficult.

Coordination of different SON functions, possibly having conflicting goals and operating on different time scales, is more challenging than in the centralized case.

Hybrid SON

In this, part of the SON algorithm is run on the network management level and part is run in the network elements.

Advantages Centralized coordination of SON functions. Ability to respond quickly to changes at the network element level.

Disadvantages Scalability problem Third party solutions will be difficult. Also, single point of failure problem is unavoidable in hybrid SON architecture.

USE CASES:

A use case a list of steps, typically defining interactions between a role and a system, to achieve a goal. SON functionalities have been developed in the different releases of the 3GPP specification staring with Release 8. These are shown below:

3GPP Release 8

1. Self-Establishment of eNBs.

This includes:

Automated establishment of IP connectivity between the eNB and the element manager Automated download of software and an automated download of radio and transport

configuration data. Automatic setup of X2 and S1 interfaces. Newly established eNBs might also perform self-test and send out reports about the results.

2. Automatic Neighbour Relation

In the context of LTE, it is necessary to set up the neighbour relation automatically as much as possible. Because the next generation mobile network is growing more and more complex, it will cause a lot of efforts to configure the neighbour relation relying on traditional configuration methods. ANR function aims at automatic setting of neighbour relation. ANR function relies on UE to report the cells that it has detected but not in the neighbour list. According to the standards, the UE measures and reports the following types of cells:

The serving cell. Listed cells, i.e. cells that are indicated by the E-UTRAN as part of the list of neighbouring cells

(i.e. as measurement object). Detected cells, i.e. cells that are not indicated by the E-UTRAN but detected by the UE. However,

E-UTRAN does indicate the carrier frequency.

So the detected cell can be a LTE cell within the same frequency or a LTE cell with a different frequency or even a cell belonging to another RAT. To detect inter-frequency cells or inter-RAT cells, eNB needs to instruct UE to do the measurement on that frequency.

1. UE does the measurement according to the measurement configuration set by EUTRAN. In this example, UE detects an EUTRAN cell with Physical ID 3.2. UE sends the measurement report to the serving cell, using Physical ID to identify different E-UTRAN cells. Here, UE includes the measurements of the cell with Physical ID 3.3. eNB receives the report and instructs the UE to report Global Cell ID for the cell with Physical ID 3.4. UE gets the Global Cell ID by reading the BCCH (Broadcast Control Channel) of the detected cell.5. UE reports the Global Cell ID to the serving cell.6. The serving eNB updates the neighbour cell list.

3. Automatic Physical Cell ID (PCI) assignment

The goal of this use case is to automatically configure the Physical Cell ID of a newly introduced cell. The Physical Cell ID (Ph_ID) is an essential configuration parameter for a cell. It is contained in the SCH (Synchronization Channel) for UE to synchronize with the cell on the downlink. There are 504

unique Ph_IDs in E-UTRAN, so the reuse of Ph_Ids in different cells is unavoidable. When a new eNB is established, it needs to select Ph_IDs for all the cells it supports.

RELEASE 9

1. Coverage & Capacity Optimization

This optimization aims at maximizing the system capacity and ensuring there is an appropriate overlapping area between adjacent cells. The optimal parameter setting is acquired by cooperatively adjusting antenna tilt and pilot power among the related cells. This optimization should operate with some effect even if the measurement reports from UE do not include their data on their own location.

A typical operational task is to optimize the network according to coverage and capacity. The traditional way is to find the problems by drive tests and use planning tools to find possible solutions. This use case aims at discovering the coverage and capacity problems automatically through the measurements at the eNB and those reported by UEs. It minimizes the human intervention and reduces the feedback delay.

2. Mobility robustness optimization –

To eliminate unnecessary handover and to provide appropriate handover timing, this optimization automatically adjusts the thresholds related to cell reselection and handover. The adjustment is triggered by the related KPI degradations and is processed while identifying the root causes of the degradations such as a handover that is too early or too late or the ping-pong effect.

3. RACH Optimization

In LTE, RACH (Random Access Channel) is an uplink unsynchronized channel, used for initial access or uplink synchronization. Random Access procedure performance influences the call setup delay, handover delay, data resuming delay, call setup success rate and handover success rate. Besides, physical resources for RACH are reserved for its special use. So the configuration for RACH influences the capacity of the whole network. If network configurations or load is changed, the performance of Random Access procedure may change greatly, which influences the performance of other procedures, such as call setup, data resuming and handover. Therefore the automatic optimization of RACH would be beneficial.

4. Load Balancing optimization

Self-optimisation of the intra-LTE and inter- RAT mobility parameters to the current load in the cell and in the adjacent cells can improve the system capacity compared to static/non-optimised cell reselection/handover parameters and can minimize human intervention in the network management and optimization tasks.

The load balancing shall not affect the user QoS negatively in addition to what a user would experience at normal mobility without load-balancing.Optimisation of cell reselection/handover parameters to cope with the unequal traffic load and minimize the number of handovers and redirections needed to achieve the load balancing.

5. SON for Home eNodeB

Introducing home eNodeBs (aka femtocells) significantly increases the number of base stations in the network and it also means that the network operator has less control of the nodes. Therefore, there is an immediate need for self-configuration of home eNodeBs.

Release 10

1.

Energy is a significant part of the operation expenses of a cellular network; hence reducing the energy consumption is a valuable optimization. The main savings potential results from variations in load over time, which would allow parts of the resources to be switched off, for example during night. An eNodeB may switch off part of the resources on the basis of local decisions, but, if the whole eNodeB is switched off, other base stations need to make up for the reduction of coverage and capacity. Hence there is a need for coordination between eNodeBs.

2. SON Self-Healing Management

The target of self- Healing (SH) is to recover from or mitigate errors in the network with a minimum of manual intervention from the operator. Self-healing functionality will monitor and analyse relevant data like fault management data, alarms, notifications, and self-test results, and so forth and will automatically trigger or perform corrective actions on the affected network element(s) when necessary. This will significantly reduce manual interventions and replace them with automatically triggered reconfigurations, or software reloads/upgrades thereby helping to reduce operating expense.

3. Minimization of Drive Tests (MDT)

At present, the network optimisation after it is operational is generally done by drive testing. In this an equipment (test mobile) that collects measurements and location information collects all the required information while the equipment is being driven in a car on the roads and this information is used offline to analyse the coverage in different locations and based on that the parameters, power, antenna locations, antenna tilts, etc. are optimised. After the changes to any of the optimisation paramaters, drive test has to be undertaken again to make sure that the impact of these changes are positive.

Goal of MDT in 3GPP Rel.10– Automatic UE measurements collection and data logging used to replace the manual drive testing that the operators have to perform in their networks– Evaluation of network performance per physical location– For both HSPA & LTE

RELEASE 11

1. UTRAN Self-Organizing Networks (SON) management

The SON target is to maintain network quality and performance with minimum manual intervention from the operator. Introducing SON functions into the UTRAN legacy is also very important for operators to minimize OPEX. Even though the automatic neighbour relation (ANR) function and the minimization of drive tests (MDT), specified in the LTE context, were introduced during release 10 in UTRAN as well, most problems that have SON solutions in LTE are not addressed in UTRAN. This has been taken care of in Release 11.

Thus, SON will bring in high level of plug-n-play functionality that will allow the network operators to quickly integrate new network elements and implement configuration changes to the network easily which was not entirely possible in legacy networks. It also means reduced expertise requirement and high-level oversight for the operator . SON in LTE networks will reduce the manual work associated with network operation and maintenance  with an ability to self-configure

and continuously self-optimize in response to network and traffic changes helping operators to reduce the OPEX , increase operating efficiency delivering higher level of performance through such a robust, energy efficient and intelligent network.

SON FOR 2G,3G

There is significant potential in the extension of the scope of the Self-Organizing Networks (SON) paradigm to also cover GSM, GPRS, EDGE, UMTS and HSPA radio access technologies, as well as of course LTE. Such extended concept is referred to as multi-technology SON.

Benefits:

Harmonizing the whole network management approach boosting operational efficiency Reduced CAPEX & OPEX Better QoS through faster reaction to disruptive network incidences

Since GSM and UMTS are legacy radio access technologies, a distributed SON architecture is only feasible through 3GPP standardization or using vendor specific proprietary solutions. Although 3GPP standardization started to specify some SON Use Cases for UTRAN, e.g. Automatic Neighbor Relation (ANR), it is believed that distributed 2G and 3G SON support will be limited to a few Use Cases.

Self Planning

Self-Planning is defined as the automation of the network planning process to reduce the associated cost and operational effort. This can be achieved by utilizing functions and components that are highly automated. The degree of automation depends on the functions and components used in the planning process.

Cross-Technology Constraints

Multi-technology networks need to be planned carefully when they coexist in the same geographical area since they are usually designed to provide combined coverage, quality and capacity for the entire offered traffic and service profiles.

● Antenna sharing: the planning process needs to derive the antenna settings of a new networkelement (e.g. azimuth, mechanical tilt and electrical tilt). If antennas are shared amongdifferent radio access technologies, the planning process has to take into consideration thecoverage, capacity and quality of those technologies that share antennas. The suggestedantenna settings for the new network element should not, for example, cause degradation tothe performance of other technology layers beyond an allowed or acceptable threshold.● Traffic share: when new network elements are planned, assumptions are made on the trafficsplit among the different radio technologies. The planned coverage and capacity of newnetwork layers should be consistent with those of legacy layers, and take into account theforecasted traffic migration between layers (subject, for example, to availability of capableterminals) in order to avoid overinvestment in new infrastructure.

Self Planning for 2G

Automation of the entire frequency planning process is very important especially when the focus of the operator is on new technologies (3G and 4G) but significant traffic is still present in GSM.

● Routinely retune (automatically) only subareas and groups of cells where the KPIs arebelow acceptable levels.● Self-Planning of spectrum for new sites.● Minimize the amount of time required to generate frequency plans as compared to manualplanning.● Allow automatic selection of the frequency planning strategy (segregated versus mixedBCCH/TCH spectra, MAL size, traffic allocation considerations, etc.). Generating multipleplans using different strategies and comparing them allows the selection of the best plan andstrategy.

Self Planning for 3G

Scrambling is a process used in UMTS to distinguish and decode signals from differentsources (cells or UEs). It is used on top of channelization in both DL and UL. Without knowingthe exact scrambling sequence applied at the source, the original user data sequence cannot bedecoded at the receiver. Scrambling is used in the DL to uniquely distinguish signals fromdifferent cells (sectors) and, in the UL, to uniquely distinguish signals from different UEs.

UMTS-FDD uses 8192 scrambling codes. Those codes are divided into 512 groups of 16codes each. Each group consists of one primary and 15 secondary codes. The 512 PSCs numberedfrom 0-511 are further divided into 64 groups of eight codes each. Each cell within a UMTS-FDD system is allocated one PSC that identifies that cell in the network, following a

philosophy that is similar to the way in which a BSIC/BCCH combination is used in GSM networks to identify a cell.

PSC planning becomes a challenge since network operators have to continuouslyupdate and optimize current PSC plan, and they also need to derive new PSCs for new sites.

Automated PSC optimization/planning can be implemented as a SON function. This function can be used to optimize the PSC assignment of new sites and existing ones. Typical triggers for PSC optimization include the addition of new site, antenna configuration changes (e.g. electrical tilt, mechanical tilt and azimuth) and changes in transmit power. Such changes will have an impact on neighbour lists, inter-cell interference and overshooting cells.

Self Optimization

Self-Optimization is defined as the utilization of measurements and performance indicatorscollected by the User Equipments (UEs) and the base stations in order to auto-tune the networksettings.

Self Optimization in 2G Networks

There are two main Self-Optimization Use Cases that consistently offer noticeable performance improvement when applied in live, operational 2G networks:

Mobility Load Balance (MLB)

In live networks, traffic is typically distributed among sectors in a non-uniform way, whichresults in suboptimal utilization of the available resources. Whereas some sectors may becongested, therefore blocking traffic and calling for capacity expansions, others may havespare capacity at the same time. By applying MLB, some traffic is shifted from the highestloaded sectors to those with lower resource utilization, taking into account the installedcapacity in each sector (see Figure 5.6). By doing this, the utilization of the resources acrossthe network becomes more equalized, which results in higher trunking efficiency and thereforelower need for capacity expansions and Capital Expenditure (CAPEX).

Figure 5.6 Traffic balance for congestion relief and CAPEX rationalization.

Mobility Robustness Optimization (MRO)

Continuous and autonomous Self-Optimization of several HO parameters in order to improve HO performance and handle network interference. The main objective of this process is quality improvement, materialized in improved HO performance and lower DCR.

Self Optimization in 3G Networks

UMTS performance can be systematically analyzed by structuring performance information in three dimensions: coverage, capacity and quality. Each one of them is characterized by a set of KPI’s. Key optimization parameters are:

Neighbour ListsElectrical Tilt (Moving the antenna)Channel PowerHO Optimization (Soft, hard & iRAT HO)

Self Healing

Self-Healing can be defined as the execution of the routine actions that keep the network operational and/or prevent disruptive problems Upon the detection of a problem, the different elements in 2nd Generation (2G) networks needto be analyzed at different levels, from Transceiver (TRX) to Base Station Controller (BSC).Guided by the nature of the detected symptoms, the analyses will yield a set of probablecauses. These analyses cover three main differentiated areas:

● System alarms. – alarms contain very valuable information about the event that raised the alarm, which represents a crucial input for the analysis● Analysis of configuration parameters- correlation between performance degradation and recent configuration changes● Correlation of performance indicators- Correlation of pairs of KPIs provides valuable information that must be exploited for accurate diagnosis.

●Cure - The following are potential actions to fix performance degradation:● Reversion of parameter settings back to previous configurations.● Assigning a default value for out-of-range parameter.● Activating certain features that were disabled.● Perform complex actions that involve multiple cells such as the generation of a newfrequency plan or the optimization of the antenna settings. That can be taken care of bySelf-Optimization functions.