Revenue Analytics for Long Term Evolution (LTE)

Transcription

1 Revenue Analytics for Long Term Evolution (LTE) Technical White Paper October, 2012

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3 cvidya Confidential Proprietary This document and the information contained in it is CONFIDENTIAL INFORMATION of cvidya, and shall not be used, published, disclosed, or disseminated outside cvidya in whole or in part without cvidya's consent. This document contains trade secrets of cvidya. Reverse engineering of any or all of the information in this document is prohibited. The copyright notice does not imply publication of the document. Documented Releases Revision Number Revision Description Revision Date 1.0 Initial release Date month year

4 Contents 1 Revenue Management challenges Service Configuration Usage Billing Revenue management solution Revenue Assurance Fraud Management Revenue Management Control Points About cvidya Table of Figures Figure 1 LTE Phase Figure 2 LTE Phase 2 & Figure 3 LTE Charging... 8 Figure 4 LTE Control Points... 12

5 The introduction of LTE The access technology called LTE (Long Term Evolution) is quickly becoming the network technology of choice for 4G deployments around the world as the consumer demand for higher capacity mobile broad band services continues to rise. LTE is becoming the technology of choice because it provides cost effective, highly responsive and very fast mobile data services. The 4G LTE technology revolutionizes mobile network architecture and the services offered for mobile users. LTE lays the foundations for an all IP environment enabling unified internet based interactions of User s Equipment (UE) with a growing number of high bandwidth offerings. Traditional circuit based voice services can be fully assimilated with the packet data infrastructure thus simplifying access technologies and providing richer integrated voice and data services. LTE technology brings changes to the Radio Access Network (RAN) as well as to the network core, moving it from the dual circuit and packet cores architecture, to a unified Evolved Packet Core (CPE) that serves voice, media and data. LTE provides access to emerging IP Multimedia Subsystem (IMS) networks, which will eventually replace the traditional circuit based mobile voice networks of today with rich multimedia services. In most cases, 3G operators are deploying LTE in a phased process (see figures below): Phase 1 Deploy LTE along with the existing 3.xG network; gradually move the traditional 3G data core (BSC, SGSN, GGSN) to the Evolved Packet Core (EPC) Phase 2 Deploy IP Multimedia Subsystem (IMS) along with the existing 3.xG circuit based voice network; gradually move the traditional 3G Voice core (BSC, MSC, HLR) to IMS with EPC Phase 3 Full EPC + IMS network and service environments

6 3.x G Network Circuit Core MSC SMSC SMSC Voice & Messaging BTS NodeB BSC/ RNC Intelligent Network HLR Radio Access Network SGSN GGSN Packet Core Internet 4G LTE Network MME HSS e NodeB S GW P GW Radio Access Network Evolved Packet Core RCRF SPR Figure 1 LTE Phase 1 4G LTE Network IP Multimedia Subsystem HSS CSCF Application Servers Voice & Messaging MME MGW e NodeB Radio Access Network S GW P GW Evolved Packet Core RCRF SPR Internet Figure 2 LTE Phase 2 & 3

7 1 Revenue Management challenges The transition to LTE affects service types, utilization patterns, and also alters the services and customers information. Furthermore, traffic patterns, especially for data, are changed significantly. LTE enables operators to move from traditional flat charge based data usage to more advanced group bundled & quality dependant charges, thus increasing revenues and differentiation. On the other hand, as with the internet, the all IP LTE technology increases the level of vulnerability to fraudsters and hackers. cvidya s and FraudView solutions address the challenges arising from the introduction of LTE and IMS in two ways. Firstly, from the overall perspective of Revenue Assurance and Fraud management, they address the new configuration, usage patterns and vulnerabilities which LTE brings with it, and secondly, they continue to address the relevant traditional RA and Fraud issues from the pre LTE era. The following paragraphs outline some of the major Revenue Assurance and Fraud Management challenges that LTE raises. 1.1 Service Configuration Customers and Service information in 3G networks is usually stored by and managed across the Home Location Register (HLR) and the Prepaid Intelligent Network platforms. Some aspects of 3G data usage are managed by Radius/AAA platforms. In LTE networks the HLR that manages customers service information, is replaced by the Home Subscribers System (HSS), which is a combination of the HLR and AAA, and responsible for managing the overall data services for the customers. Furthermore, LTE supports Quality of Service (QoS) dependent charging, thus the level of quality of service (bandwidth, guarantied bit rate, etc.) depends on parameters provisioned for each customer. The LTE QoS parameters per customers are stored by the Service Profile Register (SPR) platform. The QoS is actually managed by the Policy Charge Rules Function (PCRF) and the Policy Charge Enforcement Function (PCEF) controlling the Packet Data Network Gateway (P GW). It is imperative that the SPR be synchronized with the HLR and HSS (see figure 3). During phase 1 of the LTE deployment, the operators are managing customers information concurrently across the HLR, HSS and SPR. Customers having 3G data are managed on the HLR while those moved to LTE reside on the HSS and SPR, while their voice services are still managed by the HLR. It is of the utmost importance that the data integrity across the HLR, HSS and SPR for all the registered customers and their services, be maintained. To maintain data integrity, it is essential that duplications and discrepancies be resolved during the overall transit period from phase 1 to 3. It is important to note that LTE service and topology attributes, as well as customers information, impact the information handled by the CRM, Billing and ERP (accounting & logistics) systems. Prepaid customers on 3G networks are also managed by a Prepaid Intelligent Network (IN) platform. Revenue management for 3G maintains integrity by avoiding duplications and discrepancies between the HLR and the IN platforms. The transition to LTE introduces the On Line Charging (OCG) platform which receives usage information, coupled with utilized QoS from the PCEF. For data usage, the OCG initially interacts with the Prepaid IN platform, to determine available credit and report utilized credit. Eventually (phase 3), the Prepaid IN

8 platform will be completely assimilated into the OCG. The PCEF also reports usage of postpaid customers (and visitors) to the Off Line Charging system (retail billing). During phase 1, the OCG functionality can be carried out by the existing prepaid platforms (IN and Prepaid charging gateway). On the other hand, the new OCG can interact with the existing prepaid platforms. Eventually, all related prepaid charging should be assimilated in the OCG. Revenue Management should check the integrity of the OCG vs. the IN Prepaid platform, including prepaid customers information and credit balances. The information residing in the OCG should be checked against that in the HSS. It is essential to maintain data integrity and avoid duplications and discrepancies during the overall transit period from phase 1 to 3. 4G LTE Network MME HSS On Line Charging Off Line Charging e NodeB Radio Access Network S GW P GW RCEF Evolved Packet Core RCRF SPR Figure 3 LTE Charging During phases 2 & 3, the customer information residing in the HLR should be transferred and assimilated in the HSS. The transit period should be monitored by Revenue Management in order to maintain data integrity and avoid duplicates and discrepant configuration records. The customers service information residing in the HSS, SPR and OCG should also be checked on a periodic basis in order to detect Policy Violating service attributes (e.g. customers having service attributes they are not entitled to), and service provisioning misprocesses and latencies. The SPR may be co located with the HSS or separately deployed by other parties (i.e. MVNOs, Wholesale operators). Data residing in the HSS, SPR and OCG may also be exposed to either internal or external (hacking/backdoor) fraudulent activities, aimed at affecting charging or damaging operations. Data integrity controls are therefore necessary on a periodic basis, including strict monitoring of any illegal or policy violating activity (e.g. fraudulent data manipulation) performed on the above service platforms. 1.2 Usage Moving from flat based data usage to QoS/bundled data usage increases the significance of usage data records generated by the LTE network elements (S GW, P GW, PCEF and PCRF). Most of these usage records are partial in nature, requiring the Revenue Management systems (RA and Fraud Management) to process/aggregate them into completed usage

9 records (e.g. a record addressing an overall data session). The sheer number of those partial records requires a capable platform having the ability to collect and process all records. As with 3G networks and services, Revenue Management should check the completeness and integrity of usage records generation (by the relevant network elements), collection (by the data collectors) and processing, in order to detect lost or misprocessed billable events. The Fraud Management solution should detect suspicious traffic patterns, risky services, contract/registration violating usage and more. LTE is an emerging service and in order to manage the technical and service environments and be able to plan ahead, it is important to generate and track usage figures and patterns. The Revenue Management solution should provide the means for traffic and utilizations trends analysis and reports, providing the relevant indications as to suspicious/important deviations. 1.3 Billing LTE facilitates offerings of an increased number of data service types and service derivatives. Furthermore, LTE supports QoS/data bundling dependent charging instead of the flat based charging common to 3G data services. QoS offerings may change dynamically between, and even during, data or media sessions, making the charging process more complex. The increase in the number of service attributes associated with registered customers (post and pre paid), enhances the complexity posed on either prepaid (on line charging) or postpaid (off line charging). Enhanced service offerings may enable a customer to choose which services are prepaid and which are postpaid. It is therefore clear that we must validate the integrity of customers information (static and dynamic) in both on line and off line charging systems. From a charging integrity perspective, the handling of dynamically allocated QoS/data bundled service parameters extends the complexity of both on line and off line charging, thus increasing the probability of errors and misprocessing. It is essential to impose charging integrity controls to check for undercharges, overcharges and miss rates. These integrity checks should be carried out for both on line and off line charging (note: the solution can be implemented across chosen traffic/service samples). As with 3G networks, a Revenue Management system should check that all billable usage events are processed and that all the invoices are handled and delivered in the right manner. The bills generated should be examined periodically in order to detect Policy Violating charges. Data residing in the on line and off line charging platform may also be exposed to either internal or external (hacking/backdoor) fraudulent activities that are aimed at affecting charging or damaging operations. Data integrity controls are therefore necessary on a periodic basis, including strict monitoring of any illegal or policy violating data modification to either of these platforms.

10 2 Revenue management solution The tables below map the relevant Revenue Management process required to address major revenue leakages and fraudulent activities associated with LTE. The tables address only the threats posed by LTE. Classical 3G revenue threats are still relevant, but are not addressed below. The following Revenue Affecting Threats are divided into Revenue Assurance and Fraud Management threats. 2.1 Revenue Assurance Threat Control Solution Platform Integrity of HSS configuration Integrity of SPR configuration Integrity of OCG configuration Completeness of HSS configuration Compare CRM/Billing vs. HSS Compare HSS vs. HLR Compare HSS vs. IN prepaid Compare CRM/Billing vs. SPR Compare SPR vs. HLR Compare SPR vs. IN prepaid Compare CRM/Billing vs. OCG Compare OCG vs. IN prepaid (incl. remaining credit) Latencies in CRM/Billing vs. HSS Completeness of SPR configuration Completeness of OCG configuration Latencies in CRM/Billing vs. HSS Latencies in CRM/Billing vs. HSS Service Policies HSS/SPR/OCG Assure CRM/Billing vs. Service Policies Generated integrity Usage deviations Count & aggregated payloads of PCEF vs. OCG Count & aggregated payloads of PCEF vs. Off line Billing Trend analysis of OCG Trend analysis of Off line Billing On line rating integrity Accuracy of OCG processing (sample) /RBV Off line rating integrity Accuracy of Off Line Billing (sample) /RBV Invoice integrity Accuracy of invoices for LTE customers /RBV LTE billing integrity Billing Service Policies by customer type Completeness of inputs to Off Line billing vs. rated OCG rated records vs. Service Policies Off Line rated records vs. Service Policies

11 2.2 Fraud Management Threat Control Solution Platform Manipulation of HSS data Manipulation of SPR data Manipulation of OCG data Look for fraud characteristics: HSS vs. CRM/Bill HSS vs. Service Policies Look for fraud characteristics: SPR vs. CRM/Bill SPR vs. Service Policies Look for fraud characteristics: OCG vs. CRM/Bill OCG vs. Service Policies OCG vs. IN + FraudView + FraudView + FraudView Unauthorized usage Usage by blocked/non registered users FraudView Illegal usage Usage for non authorized services FraudView Illegal bandwidth utilization Usage with QoS exceeding registered services FraudView Large utilized bandwidth (risk of piggybacking) + FraudView Service Policies violating usage Usage superseding service policies FraudView Suspicious usage Suspicious service configuration (CRM/Billing/HSS/SPR/OCG) Service violating configuration (CRM/Billing/HSS/SPR/OCG) Large usage counts Large usage payloads Large usage during irregular hours/time bands Hot Listed usage Behavior violating usage (large deviations from average usage) Look for non authorized /suspicious access or service configuration Look for non authorized /suspicious access or service configuration FraudView FraudView/Internal fraud FraudView / Internal fraud

12 2.3 Revenue Management Control Points Figure 4 below, outlines the major data sources (or control points) required for both Revenue Assurance and Fraud Management Service Configuration Portal Business Support Systems CRM Billing System Peering & Interconnect Billing IP Multimedia Subsystem Application Servers CSCF MME HSS MGW e NodeB S GW P GW On Line Charging Off Line Charging Radio Access Network RCEF Evolved Packet Core PCRF Represents Subscriber or Service information Represents Usage Records SPR Figure 4 LTE Control Points

13 3 About cvidya cvidya Networks is a global leader of Revenue Analytics solutions for telecom, media and entertainment service providers. Innovative cvidya solutions serve to maximize margins, improve customer experience and optimize ecosystem relationships by encompassing Revenue Assurance, Fraud Management, Operational Risk Management & Compliance, Sales Performance Management and Pricing Analytics. The cvidya experts and consultants have established a stellar track record by achieving rapid ROI and lower TCO for over 150 customers. Operating regional offices worldwide, cvidya has partnered with leading vendors to implement an impressive base of operational solutions. cvidya s customers include British Telecom, Telefonica Group, Vodafone Group, AT&T, O2, MTN and Swisscom. Follow us on Facebook, Linkedin, Twitter or visit us at and YouTube.