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Save 14million-through-wifi-offload

  1. 1. Ye arly M illion $14 ave ding Offloading an Sffloa Data o rs C ta O on on erat h Da alculatiOp ug C hro Study &T O A TC WHITEPAPER
  2. 2. By Jonathan Ang | July 2010AbstractOf late, network congestion is one of the most talked about topic in the telecoms industry has isattributed to the overwhelming growth in data consumption. According to Cisco, all around theworld, mobile data traffic is expected to double every year through 2014. With such massivedemands for data, industry stakeholders are looking at various measures to cope with the increaseand mitigate congestion issues.There is an assortment of solutions to combat congestion, ranging from high investment tocost-effective and short-term to long-term. In this paper, Greenpacket puts forth a cost-effective,immediate and long-term solution to network congestion – data offloading. We examine a typicalcellular operator’s network structure, congestion points and total cost of ownership (TCO) and next,outline a calculation model (based on an Asia Pacific cellular operator) to demonstrate how muchoperators can save by offloading data to a secondary network such as WiFi. Data offloading directlyimpacts 36.5% of a network’s TCO. As such, operators can potentially* save USD 14.4 million/yearor USD 72 million over 5 years through data offloading.*Cost savings suggested in this paper are based on a network of 7,000 Node B’s.WHITEPAPER
  3. 3. ContentsCan Somebody Define Network Congestion? 01Where Network Congestion Occurs? 04Network Upgrade: Total Cost of Ownership (TCO) Breakdown 11Data Offloading: TCO Study and Calculation 13Cost (OPEX) Savings 20Find Out How Much You Can Save Through Data Offloading! 22WHITEPAPER
  4. 4. Can Somebody Define Network Congestion?Network congestion is at the top of everyone’s mind in the telecommunications industry as it impacts stakeholders indifferent ways. Operators fear it, users complain about it, governing bodies hold meetings over it, while telecom vendorsintroduce new solutions to deal with it. On the contrary, infrastructure vendors cannot get any happier as networkcongestion provides the dais for increasing revenue.With so much drones over this issue, can anyone define network congestion? How does one benchmark a network tobe congested Industry experts relate network congestion to the increase in global data consumption which will rise100-fold over the next four years! Meanwhile, some industry groups blame the proliferation of mobile broadband devicessuch as smartphones and embedded devices, while some say that unlimited data business models are the cause.While data consumption increases exponentially, it is also fair to relate this increase to the tremendous adoption ofbroadband among users over the past three years. In simple math, more users lead to more data usage. Of course thereis no doubt that users use more data today also thanks to buffet pricing plans and mobile devices that enable access todata anytime, anywhere. However, this does not give a clear picture of network congestion. Can it be attributed to thenumber of subscribers operators have?Probably not, instead, it drills down to the efficiency of network planning. For example, Operator X with 100,000subscribers running on a 21.1 HSPA+ network built from 10,000 base stations may not face network congestion asopposed to Operator Y with 50,000 subscribers on a 3.6Mbps HSDPA network built from 10,000 base stations.Aside from network planning, user profiles play a vital role as well. How much data traffic deteriorates the network qualityand upsets a user? Does a user on 256kbps speed have the case to declare a network as congested just because videostreaming is slow? Would complaints be justified when the user’s neighbor, also a subscriber to the same network,enjoys uninterrupted instant messaging sessions with his girlfriend overseas?While network congestion is very much related to a network with high traffic loads but limited bandwidth capacity, itultimately boils down to user expectations. One user might define minimum broadband speeds to be at 256Kbps whileanother sets it at 2Mbps.Network Planning – When Coverage Compensates CapacityThe task of network planning can never be too precise or complete. For a Greenfield operator, network planning can beas simple as focusing on coverage and establishing network sites in areas with large population – the number of cellsand base stations required for the area can be easily defined just by considering the propagation model and path loss.However, it gets complicated when the network matures and capacity becomes an issue rather than coverage. At thispoint, the network load exceeds capacity level thus requiring additional cells and network sites to be added. There aremany factors that can affect a network’s stability and this phenomenon cannot be forecasted for preventive action.Network deployments in areas with ongoing development can suddenly face congestion. For example, a new highdensity residential project or university can cause a radical change in population, leading to higher consumptionof bandwidth and result in congested networks. 01WHITEPAPER
  5. 5. As such, Operators need to continuously re-design and optimize their infrastructure to handle different traffic patterns –for example a college area would generate high traffic as gaming, video streaming and social networking are associatedwith students’ lifestyle. On the contrary, an industrial area demands less traffic as the internet would be used primarily foremail correspondence and web browsing.Network Planning – Reverse EngineeringNetwork planning is not as easy as building one site for every 1km radius. A rural area of 10km2 may only require threesites, but on the contrary, a dense urban area might demand 30 sites. Meanwhile, the site requirements can differ evenfor urban areas with similar number of users.Let’s assume that there are two different sites – one a university and the other a residential area, both 3km apart and have100 active subscribers. The traffic in the university area could be higher by 10-fold as compared to the residential areadue to different types of internet activities that contribute to the levels of network congestion. To overcome this problem,an operator might try to increase the number of sites surrounding the university. Yet, bandwidth will be consumedthoroughly and subscribers will remain unsatisfied. Hence, how many sites would be enough? There is never a perfectsolution in network planning. What matters is to deliver a throughput level justifiable to subscribers and a data rate whichis sufficient to satisfy subscriber usage.To conduct network planning through reverse engineering, an operator would need to embark on the following:1. Understand the population demographics and internet usage patterns.2. Decide on the intended throughput per user.3. Based on projected subscriber base and intended throughput per user, the operator has to work backwards to determine the number of sites and infrastructure capacity required.Intended throughput per user is not a straight-forward figure and is subject to environmental conditions and interference.The following table outlines the average throughput a user would gain (intended throughput) according to differentnetwork capacities. Theoretical Speed Actual Speed* Maximum Average Throughput/User per cell per cell Users/cell (Intended Speed) HSDPA 3.6Mbps 2.16Mbps 60** 36Mbps 7.2Mbps 4.32Mbps 72Mbps 14.4Mbps 8.64Mbps 144Mbps HSPA+ 21.1Mbps 12.66Mbps 211Mbps 28.8Mbps 17.28Mbps 288Mbps*Estimated to be about 60% of theoretical speed in view of environmental conditions and interference that affects network speed.**Infrastructure vendors define a range of 48-64 users/cell as bottleneck of an HSxPA base station. 02WHITEPAPER
  6. 6. Hence, depending on the intended bandwidth operators wish to extend to their subscribers, the network deploymenthas to be planned accordingly. For example, if an operator intends to offer a bandwidth of 256Kbps/user, a HSPA+21.1Mbps site has to be deployed (on assumption that the cell hosts a maximum capacity of 60 users). Alternatively,i. Operators can reduce the forecast of intended active users/cell to 30 andii. Double the number of cells to cater for that traffic oriii. Increase the number of sectors per base station for similar throughput. Theoretically, this means that the operator can deploy either method: a. HSPA+ 21.1Mbps via S1/1/1 b. HSPA 14.4Mbps via S2/2/2 c. HSDPA 7.2Mbps via S2/2/2/2/2/2 03WHITEPAPER
  7. 7. Where Network Congestion Occurs?To help understand where network congestion occurs, let’s examine a typical HSxPA network as shown in Figure 1. AHSPA network is often divided into two parts– Radio Access Network (RAN) and Core Network (CN) and each levelwithin has varying bandwidth capabilities.Congestion can occur at anywhere from RAN (RNC, Node B) to CN (from SGSN to GGSN), as well as at all transmissionpoints connecting each access point. Today’s CN is able to support high capacities of between 10-40Gbps while RNCis able to take up 2-8Gbps (depending on infrastructure vendors) and Node B (30-50Mbps). In saying this, anythroughput will never be enough to cater to the demands of users. Bottleneck can occur anywhere within the network,but more often happens at the RAN (specifically on the Node B) level. Transmission is another congestion prone area andthis is a concern as approximately 25-30% of base stations in the world are using E1/T1 (this is further explained in thesection below, Transmission (Backhaul) Congestion).Hence this paper focuses on congestion at RAN, particularly Transmission (Backhaul) and Node B, and how to easecongestion at this level. RAN CN E1 Node B PSTN ISDN E1 Node B E1 MSC/VLR GMSC Node B E1 Node B HLR/AUC E1 Node B RNC SS7 SCE E1 SCP Node B SMS E1 Node B Internet, Intranet E1 RNC GPRS Node B backbone E1 SGSN GGSN E1 Node B Node B CG BG E1 Other Node B PLMN E1 Node BSource: GreenpacketFigure 1: A typical HSxPA network diagram 04WHITEPAPER
  8. 8. Transmission (Backhaul) CongestionTranmission (Point B as shown in Figure 1) or sometimes referred to as backhaul plays an important role in transportingdata packets from one point to another. However, it is limited in terms of total bandwidth it can support and is often thearea of worry for telecoms network specialists. In a study conducted by Ovum, respondents said that transmission(backhaul) poses a pressing concern and places a restraint on mobile services (Figure 2). Do you think backhaul capacity is... 17% Currently a restraint on mobile services 33% Will be a restraint on mobile services in the next 12 months 16% Wont be a restraint on mobile services for the foreseeable future Dont know 34%Source: Ovum, South East Asia COM Conference, July 2010Figure 2: Respondents’ thoughts on backhaul capacity Core Network SGSN MSC Iu-PS Iu-CS RNS RNS Iur RNC RNC Iub Iub Iub Iub Node B Node B Node B Node BFigure 3: Simplified network diagram of a HSxPA network with emphasis on TransmissionFigure 3 depicts a simplified HSxPA network diagram emphasizing transmission paths. A typical transmission can appearmore complicated than shown here (possible looping from one Node B to another in a star, tree or ring topology,conversion from TDM to IP, going through aggregation points or hub base station). However, for the purpose ofexamining congestion at transmission level, we will consider transmission from an interface point of view,encompassing Iub, Iur, Iu-CS and Iu-PS. 05WHITEPAPER
  9. 9. The routing of voice using Adaptive Multi-Rate (AMR) flows from Iub to Iu-CS, accessing the Media Gateway (MGW/MSC)and possibly terminates at a PSTN or another mobile network. Since voice service is measured at 12.2kbps and does notconsume much bandwidth (in comparison to data), we can easily discard the routing of lu-CS in this TCO calculation.The primary concern is focused on data that routes from Iub, Iu-PS and possibly Iur. While data travels predominantly onthe Iu-PS interface, most Iu-PS channels today are equipped with STM-1, STM-4 or FE/GE which are well able to supportthe capacity of hundreds of Mbps. Unfortunately, this is not the case with Iub as a significant number of Node B’s todaystill uses E1 or T1 (in US) and STM-1, whereas less than 5% of operators have migrated to a full FE configuration. E1/T1channels emerge as bottlenecks when the HSPA network grows from 3.6Mbps to 14.4Mbps onwards, resulting incongestion issues.Transmission CostIt is common for a HSxPA operator to initially embark deployment using E1/T1 with a 2Mbps/line. In rural areas, two tothree E1s are needed in a 3.6Mbps per cell, three cell configuration site. On the other hand, an urban location with asimilar cell setup would require four to five E1s per site. As the network matures with more active users, operators arerequired to add more E1/T1 of their own or rent them. Transmission rental differs significantly from one country to anotherand normally can consume as much as 20-30% of total cost of ownership.Today, base stations support a maximum of 8E1 IMA, which has a capacity of 16Mbps. If this is insufficient, an upgradeto fiber transmission (STM-1) is necessary. As the network gets upgraded to HSPA+ network using IP, operators maythen need to convert their Iub transmission to Ethernet (FE/GE) as similar approach done by operators such as Etisalat,E-Mobile and Starhub.Node B (RAN) CongestionIn the same research conducted by Ovum on radio access network (RAN) capacity, respondents also believe that RANis also a roadblock. 64% believe that RAN is currently or will put a constraint on mobile services over the next 12 months,as shown in Figure 4 below. Do you think radio access network capacity is... 15% 28% Currently a restraint on mobile services Will be a restraint on mobile services in the next 12 months 21% Wont be a restraint on mobile services for the foreseeable future Dont know 36% 06Source: Ovum, South East Asia COM Conference, July 2010Figure 4: Respondents’ thoughts on RAN capacityWHITEPAPER
  10. 10. During the early stages of network planning, the task of forecasting CAPEX on Node B based on the number of sites isstraightforward. However, the actual cost of Node B does not end here, instead it will undergo constant upgrades andover the next 5 years, the cost spent on upgrades might exceed the cost of purchasing the Node B itself. The primereasons for these upgrades are contributed by an increase in capacity requirements and in some extreme situations,congestion.When does a Node B experience congestion and demand an upgrade?Network upgrades can be conducted using two methods:i. Base station capacity upgrade (involves channel element, power transmit, multi-carrier and HSPA codes)ii. Network upgrade (by increasing sites)Method #1 - Base Station Capacity UpgradeWhen it comes to network improvement, a more cost-effective alternative for operators is to upgrade their existing basestations in terms of throughput per cell, for example from 3.6Mbps to 7.2Mbps or 14.4Mbps.How does this work? Let’s assume that Operator A launches a HSPA network with three cells, each with a throughputof 3.6Mbps as shown in Figure 5. Due to environmental constraints and inteference between users, Greenpacketestimates that the average throughput per cell is at 60% of the theoretical value i.e. 2.16Mbps. During peak hours with10 active users, each user gets approximately 220kbps speed.However, as subscribers grow to 20 active users, each user will only obtain a mean speed of 100kbps. It is important tonote that a HSPA network can support 48-64 users per cell – as the number of users per cell increase, average speedper user decreases and this calls for an upgrade. 3.6Mbps Assuming this is a HSDPA S1/1/1 network site Bandwidth capacity = 3.6 Mbps (practically, ~ 2 Mbps/sector) Planned subscribers/sector = 10 Node B 3.6Mbps Actual subscribers/sector = 20 Result = Congestion 3.6MbpsFigure 5: HSDPA S/1/1/1 Network Site 07WHITEPAPER
  11. 11. A base station upgrade generally involves several areas – channel element, code, power, and multi carrier as shown inFigure 6. NODE B New Site Code Carrier Power Channel Element (CE) Iub Congestion TransmissionFigure 6: RAN upgrade involving Node BTransmission CodeFigure 7 shows the Orthogonal Variable Spreading Factor (OVSF) code tree. At SF=16, 15 HS=PDSCH codes can beused for HSDPA purposes. As HS-PDSCH codes can range from 1 to 15, the remaining codes will be utilized by R99and AMR. Different applications will accept different spreading, for example for voice AMR, the codes can be furtherspread to SF=256. SF = 1 SF = 2 SF = 4 SF = 8 SF = 16 15 HS-PDSCH Codes SF = 32 SF = 64 SF = 128 AMR SF = 256 12.2kbps X - blocked by lower code in treeFigure 7: Orthogonal Variable Spreading Factor (OVSR) code tree 08WHITEPAPER
  12. 12. When code congestion occurs, a typical HSDPA solution is to increase the speed from 3.6Mbps to 7.2Mbps or14.4Mbps (or in other words increase the HSDPA codes). Table below shows the corresponding code to speed.*Today, all HSPA Node B’s support 16QAM modulation. HSPA+ requires 64QAM modulation. Modulation Throughput with 5 codes Throughput with 10 codes Throughput with 15 codes QPSK 1.8Mbps 3.6Mbps 5.4Mbps 16QAM 3.6Mbps 7.2Mbps 14.4Mbps (Based on coding rate of 4/4)Table 1: Correspoding code rates to speedNote: Adding codes come at a price as a trade off of lesser codes occurs for R99 and AMR. This will create a problemin locations where voice and R99 are still dominant, leading to other congestion issues.Code upgrades are purely done via software licenses from infrastructure vendors, with typical license prices based onfive codes per base station.Multi CarrierSolving code congestion may lead to congestion on the carrier level. With more codes dedicated to HSDPA, there will belesser codes available for R99. Instead of allowing the trade off, a popular strategy for operators is to add an additionalcarrier per cell (from S1/1/1 to S2/2/2 of S3/3/3). This carrier overlaying strategy means that technically each cell can haveup to 15 + 15 codes for HSDPA and R99. Depending on the operator’s deployment strategy, they may use both cells forHSPA (each with 10 codes) or employ 15 codes on the first carrier, while the second carrier is used solely for R99.Carrier upgrading mainly involves software, however sometimes hardware changes are required depending on limitationson the base station. Older versions of base stations support transmit receive unit (TRU) modules, where each TRU onlyholds a single carrier. Today’s technology allows multiple TRUs to be embedded within a single module, which is also knownas multi radio unit (MRU). Each MRU consists of multiple power amplifiers (PA) that can support up to two or sometimeseven four or six carriers per hardware module.PowerOnce code and carrier congestion are resolved, operators might face insufficient power problems. As more users areallowed to to connect to a single cell, each cell would then need more power to transmit and overcome interference. Ascoverage and capacity are co-related and often compensates one another, the natural outcome will be a shrinking cellcoverage. Users at the cell edge will need more power, leading to insufficient power at the base station. Depending onthe MRU power transmit capacity, operators may choose to use the power allocation differently.For example, with a MRU of 2 PA capability and maximum power of 40W per MRU, an operator may opt to transmit at20W + 20W to cater for two carriers per cell. This may not be applicable to another operator who prefers to transmit at40W per cell to achieve a further cell edge. Therefore, two MRU modules are required. Infrastructure vendors 09charge for upgrades in terms of MRU boards and a possible license fee to operate the carrier splitting.WHITEPAPER
  13. 13. Channel Element (CE)While code, power and carrier are similar among infrastructure vendors, channel element (CE) deployment differssignificantly. In general, one CE is used for one AMR 12.2kbps user. However, this may not be applicable for R99 andHSPA usage. Due to CE’s proprietary technology, some vendors may require eight and 16 CEs for PS144 and PS384,while another may need four to eight CEs.This applies to HSDPA and HSUPA where some vendors may need CE forevery user while others may not. Because of this, the price of CE may vary between vendors to offset differences in thenumber of CEs supplied. When subscriber base increases in an area, voice and R99 may increase as well, leading tohigher demand for CE from operators as well as CE congestion if not handled properly.Channel element is software supported by the base stations baseband and it can be upgraded up to the maximum levelallowed by the hardware.The vicious cycle of network congestion may not take place in the above-mentioned order as subscriber usage habitsdiffer. An example situation iswhereby power insufficiency due to cell edge may be resolved by adding more MRU,without increasing codes or CE. Similarly, additional five to 10 codes may be sufficient without adding carriers.Though most operators would prefer to upgrade the base station as it is fast, the cost of upgrading may not be justifiedwhen compared to the TCO. It could be cheaper to purchase a base station with higher capacity and more advancedconfiguration. Network planning is not easy,but done as accurately as possible, it could save an operator millions.Method #2 – Network Upgrade (By Increasing Sites)While base station upgrade remains the quickest option in terms of deployment, there is a limitation to the amount ofupgrades. Sometimes a base station can only hold a maximum of six carriers and subsequently any additional carrierrequires a new base station. Similarly, in situations where CE demands exceed the base station’s basebandconfiguration, an additional base station is required.Another advantage of upgrading sites is its long-term positive impact on the network. For example, adding more powerto support cell edge users will not yield similar performanceas opposed to adding a new site at the cell edge or withinthe vicinity.Apart from better performance, operators need to compare the cost of upgrading versus the cost of adding a new basestation. Though both their effect on the network may be similar, a newer base station requires lower maintenance andprovides a full range warranty period. The disadvantage to a new base station,however, is that new site acquisition isneeded and this could be a long process. 10WHITEPAPER
  14. 14. Network Upgrade: Total Cost of Ownership (TCO)BreakdownThe earlier section explored network improvement mechanisms such as base station upgrades and the addition of newsites which were not considered during the initial network planning stage. How much do network improvementscontribute to the total network cost over a long period of time, say five years? First, a network’s total cost or TCO has tobe understood.A network’s total cost comprises of both the capital expenditure (CAPEX) and operation expenditure (OPEX). The cost ofa network does not stop just after it is rolled out. Instead, it is actually the beginning of many reoccurring costs such asmaintenance cost, upgrade cost, site and bandwidth rental, manpower, power supply and others which fall underoperations cost (OPEX).Most operators are concerned about CAPEX but fail to realize that in the long run (for example, five years), more is spenton OPEX. Moreover, OPEX costs such as manpower and electricity are always increasing , but CAPEX costs decreasesas prices of infrastructure equipment usually declines as its technology matures.Figure 8 gives an overview of network TCO according to In-Stat, where 27% is spent on CAPEX and 73% on OPEX.While the TCO shows a CAPEX to OPEX ratio (percentage) of 73:27, Greenpacket believes that the ratio will eventuallychange to approximately 80:20 due to the reasons mentioned earlier.Network TCO – The ComponentsFor operators, CAPEX constitutes the purchase of infrastructure and transmission equipment, as well as antenna andother supporting accessories, while deployment cost involves site acquisition, equipment installation and civil works.On the other hand, OPEX encompasses site rental, power consumption, leased line rental as well as software andhardware costs. Meanwhile, maintenance costs cover the network’s upkeep and manpower.It is interesting to note that leased line and site rental forms the largest chunk of network TCO with a combined total of43.8%. Leased line refers to the rental of E1 (though some operators may opt to construct their own backhaul, makingit a cost that falls under CAPEX) and site rental refers to the rental operators have to pay for all their sites. Both leasedline and site rental expenditures are closely related to network congestion that requires upgrades. Operators usually fretabout millions being spent on equipment, but in actual fact, this component is only 5.4% of the total network cost. 11WHITEPAPER
  15. 15. NETWORK TCO CAPEX (27%) OPEX (73%) Purchasing (14%) Deployment (13%) Operations (60%) Maintainance (13%) Equipment 5.4% Site Acquisition 2.7% Site Rental 21.9% Maintenance 11.0% Transmission 1.4% Installation 2.7% Power 7.3% Man Power 3.7% Equipment Consumption Civil Works 8.1% Accessory 5.4% Leased Line 21.9% Antenna 1.4% Hardware & 7.3% SoftwareSource: In-Stat, June 08Figure 8: Network TCO, outlining CAPEX and OPEXIs There A Cheaper Alternative?Though the growth in data usage may seem to be a boon to many operators, its rapid growth can be detrimental to anoperator’s bottomline due to its associated CAPEX and OPEX costs caused by network congestion.Therefore, operators must place together a strategy to combat network congestion. There are various congestionmanagement methods available on the market, and this includes policy control, data traffic offload, infrastructureinvestment and network optimization2. From these methods, data offloading is the most preferred as it presents a moreimmediate and cost-effective approach. This is supported by same study conducted by Ovum and Telecom Asia,whereby respondents were asked what is the most effective solution to deal with traffic growth besides upgradingnetwork infrastructure and 41% favored data offloading, as shown in Figure 9 below. Excluding installing more capacity, what is the most effective solution to deal with traffic growth? 5.7% 12.6% Wi-Fi and offloading traffic of the macro network Other traffic management techniques such as 41.0% throttling and use of policy control 18.9% New charging schemes (QoS, SLA, etc) Femto cells Others 21.8%Source: Ovum/Telecom AsiaFigure 9: Data offloading is the prefered choice for network congestion management2Bridgewater Systems 12WHITEPAPER
  16. 16. Data Offloading: TCO Study and CalculationData Offloading ToolData offloading is done via Greenpacket’s Intouch Connection Management Platform (ICMP), an easy-to-use,single-client connection management solution, innovatively conceptualized from Mobile IP technology. With its Seamless Mobility advantage, ICMP doubles up as a cost-effective, hassle-free and immediate data offloading tool. Based on preset profiles, Operators can determine the priority of network connection corresponding to the surrounding environment. Hence, ICMP intelligently monitors the network environment - if it detects that a user is using data services on a cellular network (such as 3G) and if there is less congested alternative network (such as WiFi, WiMAX, DSL) available in the same vicinity, ICMP transfers the userFigure 10: Greenpacket’s Intouch Connection Management from 3G to WiFi without interruption to connectivity. Platform (ICMP)Components Impacted Through Data OffloadingNetwork deployment to improve coverage is a continuous CAPEX. Greenpacket believes that data offloading has a directimpact on the OPEX (operations cost) which tantamounts to 36.5% of the total TCO. While it is not possible to totallyeliminate this cost, operators can significantly reduce it through data offloading to WiFi networks.Data offloading has a direct impact on the following components of the OPEX TCO:i. Hardware and software upgrade – Since data is being offloaded, there will befewer users accessing the HSPA network. Therefore, network upgrades such as (but not limited to) channel element, power, carrier and codes are reduced.ii. Leased line – Operators often have to upgrade the backhaul especially for the Iub interface to add more E1 channels or migrate to STM-1 and FE/GE. By offloading, existing backhaul can be maintained or requires fewer upgrades.iii. Power consumption – When fewer users group on the HSPA network, lower power is required for tranmission. Eventually, the base station will consume less power.iv. Site rental – In situations where data is offloaded to WiFi networks, the number of sites can be minimized. This contributes to savings on site rental, civil works and CAPEX expenditure related to site acquisition. 13WHITEPAPER
  17. 17. NETWORK TCO CAPEX (27%) OPEX (73%) Purchasing (14%) Deployment (13%) Operations (60%) Maintainance (13%) Equipment 5.4% Site Acquisition 2.7% Site Rental 21.9% Maintenance 11.0% Transmission 1.4% Installation 2.7% Power 7.3% Man Power 3.7% Equipment Consumption Civil Works 8.1% Accessory 5.4% Leased Line 21.9% Antenna 1.4% Hardware & 7.3% Software 100 ~60% ~13% Data offloading directly impacts 36.5% of TCO 80 60 40 20 ~13% ~14% 0 Purchasing Deployment Operation Maintenance TOTALSource: GreenpacketFigure 11: TCO breakdown of an Asia Pacific 3G OperatorNetwork DimensioningIn this study, the following areas are considered for costs calculation. Transmission will have an impact on Iub, Iu-PS andIur, but to simplify the calculation, only Iub transmission savings will be considered. RAN upgrades will have an impact onboth Node B and RNC, but again for handling simpler illustration, we will calculate Node B’s cost only.Our dimensioning tools were used to study an operator in Asia Pacific and these data were obtained:i. The operator’s network scale (migration path from HSPA to HSPA+) over the next 5 yearsii. Traffic profiles such as user habits and peak hoursiii. Total number of Node B’s expected over five yearsiv. Equipment vendor (as equipment dimensioning from one vendor to another differs)*From the dimensioning tools, traffic that will occur during peak hours and its cost over the next five years is generated.Monetary savings are then calculated comparing the traffic and costs against offloading to a WiFi network.*Name and details of infrastructure vendor withheld to protect its interests 14WHITEPAPER
  18. 18. Input Iu-CS  UTRAN Output HSPA Evolution  Iu-PS  RNC Network Scale & Node B Distribution  Iur Transmission   Iub  Traffic Profile  CE  Node B   Subscriber Profile Codes WiFi Network  Carrier  Output Price of Upgrade Equipment Vendor  Power  SGSN BG, DNS, GGSN DHCP,  CS CN Assumptions PS Signaling Firewall, CG Router... PS Traffic PS CN CS Signalling MSC Server HLR CS Traffic MGWSource: GreenpacketFigure 12: Network factors considered by Greenpacket for data offloading calculationOperator’s Network DataIn this section, we will examine the following input parameters used to perform the calculation. Input HSPA Evolution Traffic Profile WiFi Network Equipment Vendor Network Scale & Node B Distribution Subscriber Profile Price of Upgrade AssumptionsSource: GreenpacketFigure 13: Input parameters for data offloading calculationHSPA EvolutionThe selected cellular operator has a five year network evolution plan, moving from 3G (3.6Mbps) to HSPA (7.2Mbps) andeventually to HSPA+ as shown in Figure 14. 15WHITEPAPER
  19. 19. Initial Deployment HSPA Stage HSPA+ Stage Phase 1 Node B 3.6Mbps 7.2Mbps on Hotspots, migration to STM-1, Maintain old Node B to support HSPA, with priority on R99 (10 codes) 3.6Mbps on less congested area new Node B deploy on HSPA+ 3G (R99+HSPA) Evolve to 14.4Mbps Dual Carrier 7.2Mbps (R99 + HSPA on single carrier) HSPA+ 21Mbps CPC and CELLFACHFigure 14: Network evolution of the selected operatorNetwork Scale and Node B Distribution 7000 6000 2008 5000 2009 4000 2010 2011 3000 2012 2000 1000 0 Dense Urban Urban Rural Total SitesFigure 15: Distribution of sites by dense urban, urban and rural areasTraffic ProfileSite Configuration Site Configuration 2008 2009 2010 2011 2012 HSDPA 3.6Mbps/cell Single Carrier 100% 60% 20% 0% 0% HSDPA 7.2Mbps/cell Single Carrier 0% 40% 80% 20% 0% HSDPA 14.4Mbps Dual Carrier 0% 0% 0% 30% 0% HSPA+ 21Mbps Dual Carrier 0% 0% 0% 50% 100%Figure 16: Site configuration over 5 years 16WHITEPAPER
  20. 20. Population Breakdown 100% 80% Dense Urban 60% Urban 40% Rural 20% 0% 1 2 3 4 5Figure 17: Breakdown of population in dense urban, urban and rural areasSubscriber ProfileCurrent and Projected 3G Active Subscribers 3,500,000 3,000,000 2008 2,500,000 2009 2,000,000 2010 2011 1,500,000 2012 1,000,000 500,000 0 Dense Urban Urban Rural TotalFigure 18: Number of current and projected 3G active subscribersNetwork Usage Patterns Usage 2008 2009 2010 2011 2012 AMR12.2 75% 60% 50% 40% 30% R99 PS 10% 10% 10% 5% 5% HSDPA 15% 30% 40% 55% 65%Figure 19: Network usage patterns over 5 years 17WHITEPAPER
  21. 21. WiFi Network 12% 53% Dense Urban Urban Rural 35%Figure 20: WiFi networks in dense urban, urban and rural areasPrice of UpgradeTransmission cost in Asia Cost of New Codes, Carriers and Sites $1,600 $1,400 $1,200 30,000 $1,000 25,000 $800 20,000 $600 15,000 $400 10,000 $200 5,000 $0 0 E1 STM-1 GE GE GE 5 codes 1 carrier New Site (2Mbps) (10Mbps) (2Mbps) (4Mbps) (10Mbps)Figure 21: Transmission Cost in Asia (in USD) Figure 22: Costs of new codes, carriers and sitesNetwork AssumptionsFor this TCO study and calculation, the following network assumptions are made:1. Transmission is rented, hence it falls under OPEX.2. Site increment is based on 1,000 sites/year to improve coverage and capacity (90% coverage of 300,000km2 area). 183. Subscriber growthis projected at 50% per year.4. Network is based on UMTS2100.WHITEPAPER
  22. 22. 5. E1 is used to provide 3.6Mbps; STM-1 for 7.2Mbps, FE for 14.4Mbps and 21.1Mbps.6. All Node B’s can support 2 IMA groups (16E1) and capacity is ready.7. All Node B’s comprises 3 sectors.8. 7.2Mbps is single carrier (1 HSPA+ and 1 R99), 14.4Mbps dual carrier (1 HSPA, 1 for R99)9. Maximum deployment of 2 carriers.10. Transmission is calculated based on DL traffic only.11. 20% transmission buffer is allowed for Capacity Planning.12. WiFi offload for HSPA + R99 PS only.13. All Node B’s are upgradable to HSPA 14.4Mbps (15 codes, 64QAM, 2 carrier) but not upgradeable to HSPA+ (which requires Enhanced CELL_FACH, CPC (Continues Packet Connectivity).14. MBMS and HSUPA are not considered within 5 years roadmap (to simplify calculation of CE).15. All Node B’s purchased supports HSPA+ Phase I 21.1Mbps (not HSPA+ Phase II 28.8Mbps).16. HSDPA does not consume CE. 19WHITEPAPER
  23. 23. Cost (OPEX) SavingsIUB (Transmission) SavingsIn a five-year period and using Greenpacket’s ICMP to facilitate data offload to WiFi, only USD95 million is spent on IUBtransmission as opposed to USD105.83 million if no data offloading was carried out. Hence, within five years, USD28.22million is saved for 7000 Node B’s. IUB transmission - 5 years TCO USD (mil) Savings $12 $10 With WiFi Offload USD 95 million $8 $6 $4 Without WiFi USD 105.83 million $2 USD (mil) $0 $90 $95 $100 $105 $110 Year 1 Year 2 Year 3 Year 4 Year 5Figure 23: IUB transmission TCO over 5 years Figure 24: IUB transmission savings over 5 years Total Savings of ~28.22mil over 5 years for 7000 Node B’sNode B SavingsFor Node B, Greenpacket calculated the price difference for SF Codes, Transmission Power and Channel Element (CE). Price Difference for Code and Power Upgrade Price Difference for CE USD (mil) Difference USD (mil) $45 $7 $40 $6 $35 $30 $5 $25 $4 $20 $3 $15 $2 $10 $5 $1 $0 $0 Year 1 Year 2 Year 3 Year 4 Year 5 Year 1 Year 2 Year 3 Year 4 Year 5Figure 25: Price difference for code and power upgrade Figure 26: Price difference for channel element Total Savings (Code, Power & CE) of ~43.78 mil over 5 years for 7000 Node B’s 20WHITEPAPER
  24. 24. Total Savings NETWORK TCO CAPEX (27%) OPEX (73%) Purchasing (14%) Deployment (13%) Operations (60%) Maintainance (13%) Equipment 5.4% Site Acquisition 2.7% Site Rental 21.9% Maintenance 11.0% Transmission 1.4% Installation 2.7% Power 7.3% Man Power 3.7% Equipment Consumption Civil Works 8.1% Accessory 5.4% Leased Line 21.9% Antenna 1.4% Hardware & 7.3% Software IUB Transmission Node B (Codes, Power & CE) Savings of 12% (of OPEX) Savings of 4% (of OPEX) or 2.6% (of TCO) or 0.3% (of TCO) Total Savings Savings of 16% (of OPEX) or 2.9% (of TCO) With a operational expenditure of USD 300 million/year, an operator can save USD 8.7 million/year through data offloading 21WHITEPAPER
  25. 25. Find Out How Much You Can Save Through Data Offloading!Greenpacket welcomes you to embark on the offloading journey today and enjoy tremendous cost savings on yournetwork operations. At Greenpacket, we understand the demands placed on Operators like you. That is why oursolutions are designed to give you the capacity to constantly deliver cutting-edge offerings without exhausting yourcapital and operating expenditures.With Greenpacket, limitless freedom begins now!Free ConsultationIf you would like a free consultation on how you can start saving network cost through data offloading, feel free to contactus at kindly quote the reference code, WP0710DL when you contact us. As part of theconsultation, we will be happy to walk-through your network’s TCO and determine how much savings you would gain byoffloading data. 22WHITEPAPER
  26. 26. References1. Telecoms: At the starting line – The race to mobile broadband by Gareth Jenkins and Jussi Uskola, Deutsche Bank.2. Towards a Profitable Mobile Data Business Model by Bridgewater Systems3. Sharing the Load by Bridgewater Systems4. Mobile Broadband: Still Growing But Realism Sinks In by Telecom Asia (January/February 2010)5. Mobile Communications 2008: Green Thinking Beyond TCO Consideration, Kevin Li, In-Stat 23WHITEPAPER
  27. 27. About Green Packet Greenpacket is the international arm of the Green Packet Berhad group of companies which is listed on the Main Board of the Malaysian Bourse. Founded in San Francisco’s Silicon Valley in 2000 and now headquartered in Kuala Lumpur, Malaysia, Greenpacket has a presence in 9 countries and is continuously expanding to be near its customers and in readiness for new markets. We are a leading developer of Next Generation Mobile Broadband and Networking Solutions for Telecommunications Operators across the globe. Our mission is to provide seamless and unified platforms for the delivery of user-centric multimedia communications services regardless of the nature and availability of backbone infrastructures. At Greenpacket, we pride ourselves on being constantly at the forefront of technology. Our leading carrier-grade solutions and award-winning consumer devices help Telecommunications Operators open new avenues, meet new demands, and enrich the lifestyles of their subscribers, while forging new relationships. We see a future of limitless freedom in wireless communications and continuously commit to meeting the needs of our customers with leading edge solutions. With product development centers in USA, Shanghai, and Taiwan, we are on the cutting edge of new developments in 4G (particularly WiMAX and LTE), as well as in software advancement. Our leadership position in the Telco industry is further enhanced by our strategic alliances with leading industry players. Additionally, our award-winning WiMAX modems have successfully completed interoperability tests with major WiMAX players and are being used by the world’s largest WiMAX Operators. We are also the leading carrier solutions provider in APAC catering to both 4G and 3G networks and aim to be No. 1 globally by the end of 2010. For more information, visit: Francisco · Kuala Lumpur · Singapore · Shanghai · Taiwan · Sydney · Bahrain · Bangkok · Hong Kong Associate MemberCopyright © 2001-2010 Green Packet Berhad. All rights reserved. No part of this publication may be reproduced, transmitted, transcribed, stored in a retrieval system, or translated into any language, in any formby any means, without the written permission of Green Packet Berhad. Green Packet Berhad reserves the right to modify or discontinue any product or piece of literature at anytime without prior notice.