Development of the Wi-Fi Offloading Business Concept within the African Market Context

Beneyam B. Haile, Edward Mutafungwa, and Henna Warma

Department of Communications and Networking

Aalto University, COMNET Espoo, Finland

{beneyam.haile, edward.mutafungwa, henna.warma}@aalto.fi

Abstract—Offloading traffic to Wi-Fi networks is now becoming an attractive way of alleviating congestion and extending coverage without the need for significant additional investments for increased mobile network coverage and capacity. While Wi-Fi offloading technology standards are maturing and various vendor solutions being adopted by operators in developed economies, the offloading business models need to be re-evaluated for Africa where the Wi-Fi adoption patterns and regulations are a rather different. In this study, we aim to analyze the Wi-Fi offloading business model for the African market context in a holistic manner by identifying plausible offloading scenarios, noting the critical success factors (or barriers) and evaluating the emerging value network configurations. Finally, we present an exemplary business model for an Offloading Service Provider based on an existing offloading vendor solution and using the STOF model as the theoretical framework.

Keywords-Wi-Fi Offloading; Value Networks; Business Models

I. INTRODUCTION Mobile networks are now enabling Internet access for

millions of previously unconnected users in most emerging markets of Africa [1, 2]. Various indicators provide empirical evidence that clearly suggest very rapid mobile Internet growth trends, both in terms of unique user numbers and traffic generated. For instance, Ethiopia has seen a significant growth in mobile subscription with a penetration of 8.15% in 2010; and there is a forecast of huge increment such that the government has planned itself for 50% penetration in 2015 [3]. The mobile web statistics provided by Opera Software (a mobile browser maker) notes that the number of web page-views and data transferred on mobile handsets in Tanzania grew by 335% and 288%, respectively, in the one year period from December 2009 to December 2010 [4]. Furthermore, statistics from Kenya’s regulator also note that the Internet penetration increased from 10% in September 2009 to 22% in September 2010, with mobile Internet access accounting for 99% of the total Internet subscriptions for that period [5]. Cisco has also recently made a forecast that Africa and Middle East will have the strongest mobile data traffic growth than any other region [6].

However, the sustainability of such rapid mobile Internet users and traffic volume growth trends is becoming more of a challenge for mobile operators in Africa, as it demands denser base station deployments to provide additional capacity and coverage. This challenge is attributed to the fact that each new cell site contributes to operator’s capital and operating expenditures [7], costs which are further exacerbated by factors, such as, lack of reliable power supply from the grid. Furthermore, following the initial wave of early adaptors of mobile Internet services, the majority of the next wave of new subscribers in Africa will be from the bottom half of the economic pyramid. This will result in reductions in the average revenue per user (ARPU) that operator can expect from their expanding subscriber base. Alternatively, mobile network upgrades to emerging high-capacity 4G radio access technologies, such as, Long Term Evolution (LTE), is an attractive option, but can only be considered as a long-term solution due to lack of affordable user devices and strategy by operators to first recover their 3G network investments [8].

Therefore, mobile operators are always looking for ways to

alleviate the capacity crunch problem without having to always resort to costly deployments or upgrades to the radio access and core networks. To that end, operators have multiple strategies (e.g. data compression [9], tiered or usage-based pricing [10], etc.) to alleviate the capacity crunch problem. Of the strategies considered, offloading is increasingly being viewed as one of the most effective approaches [10]. In the context of this paper, offloading is considered as transferring traffics from a congested 2G, 3G, or 4G cellular mobile networks to another network.

Currently, mobile offloading can be achieved using two

possible mechanisms, that is, offloading traffic from macro to 3G or 4G femtocells [11], or alternatively offloading to IEEE 802.11x Wi-Fi networks 1 via Wi-Fi access points [12],[13],[14],[15]. Femtocells are gaining considerable interest as a means to alleviate indoor coverage and capacity problems associated with legacy macrocellular mobile networks; however they are yet to achieve mass adoption due

1 Wi-Fi network also referred to as Wireless Local Area Network

(WLAN). In this paper, the terms Wi-Fi and WLAN will be used interchangeably.

to need for standards to mature and femto-macro interference issues to be addressed comprehensively [16]. By contrast, Wi-Fi has had considerable success in terms of user adoption due to operation in 2.4 GHz and 5 GHz unlicensed bands and economies of scale, which have made Wi-Fi products relatively affordable [17].

The success of Wi-Fi is also reflected in current industry

choice offloading mechanisms, with Wi-Fi offloading being the current market leader in developed economies. To that end, the analysis of the opportunity presented by Wi-Fi offloading in emerging markets of Africa is both timely and issue. The objective of this study is to contribute to increased understanding of the Wi-Fi offloading business within the context of African emerging markets. Specifically, we analyze the potential offloading services and clarify the evolution paths for the Wi-Fi offloading market. First, we carry out a scenario analysis on how the Wi-Fi offloading can be provided to the mobile data users and evaluate the alternative value networks which could enable offloading services in the future. In addition, we present a potential business model for a new stakeholder who could start providing offloading services for the mobile operators. The rest of the paper is structured as follows. In Section II, the state of the art in Wi-Fi offloading technologies is presented and Section III discusses the offloading market analysis. Section IV presents an exemplary business model while Section V provides the conclusions of the study.

II. TECHNOLOGY OVERVIEW Wi-Fi offloading can be implemented using a number of

different approaches, based on legacy or novel technologies. The most common and simplest approach is to utilize the user-controlled connection manager feature that is included in the operating systems of most Wi-Fi-enabled mobile. The device’s connection manager enables the end-users to seamlessly or manually connect (or disconnect) data connections from Wi-Fi networks, depending on device settings and stored configurations. Alternatively, there are a number of standardized and proprietary Wi-Fi offloading technologies that provide advanced carrier-grade features, such as, offloading control functionality for the mobile operator.

The Third Generation Partnership Project (3GPP) has

specified three different technologies that enable offloading from 3GPP standardized mobile data networks (Global System for Mobile Communications (GSM)/ General packet radio service (GPRS), Wideband Code Division Multiple Access (WCDMA), High Speed Packet Access (HSPA) etc.) to Wi-Fi for multimode terminals (with both 3GPP and Wi-Fi interfaces). These technologies are described briefly below.

i. Generic Access Network (GAN) which is also referred to as Unlicensed Mobile Access (UMA), whereby a GAN Controller (GANC) is deployed in a mobile core network (emulating an Radio Network Controller) to enable 3GPP-WLAN vertical handovers for UMA-enabled terminals [12].

ii. Inter-working Wireless LAN (I-WLAN) which specifies interfaces for common control mechanisms (e.g. authentication) for 3GPP and WLAN inter-working, and the Packet Data Gateway (PDG) to provide gateway functionality for WLAN access towards the 3GPP core network [13].

iii. Access Network Discovery and Selection Function (ANDSF), an entity within the 3GPP Evolved Packet Core (EPC) which provides means for the mobile operator to define policies which dictate how ANDSF-enabled terminals could connect to non-3GPP access (WLAN, Worldwide Interoperability for Microwave Access (WIMAX), etc.)[14].

The Third Generation Partnership Project 2 (3GPP2) has

also standardized CDMA 2000 networks and WLAN inter-working, where Packet Data Interworking Function (PDIF) is included as a security gateway so that the operator network will be guarded against unauthorized access and inbounds threats [18]. This inter-working is very important in a country like Ethiopia where almost 90% the country is covered by CDMA network [3].

Various vendors (Kineto Wireless, Greenpacket, WeFi

etc.) have ventured into the offloading market with proprietary Wi-Fi offloading solutions based on customized versions of the aforementioned standardized technologies. Typically, these solutions are proprietary based on their client applications which provide implementations of the respective standards within the terminal devices. Furthermore, the market also includes fully proprietary technologies that fall outside the scope of the aforementioned standardized offloading technologies. This includes the Wi-Fi offloading solution from Notava [15], which will be presented in more detail in the exemplary offloading business model of Section IV.

III. WI-FI OFFLOADING MARKET ANALYSIS This Section analyzes Wi-Fi offloading within the context

of the African market. To that end, a scenario analysis for adoption of Wi-Fi offloading is carried out and alternative value-network configurations are evaluated.

A. Scenario Analysis In order to clarify the big picture and the possible evolution

of the offloading market, we construct scenarios to address the question on how Wi-Fi offloading could be provided for end users in the African market context. Scenario analysis methodology previously proposed by Schoemaker [19], has recently gained popularity as a tool for managing the uncertainty, complexity and disruptiveness of new technologies, such as, broadband local wireless access [20].

Several offloading solutions exist in the market as noted previously in Section II, each employing differing mechanisms from the perspective of the end-users and the mobile operators. Following some carefully targeted literature and market survey, as well as expert interviews, we identified some notable macro-environmental trends that influence the Wi-Fi offloading market, particularly in the African-context. These trends were then compiled using a PEST (Political, Economical, Social and Technological) analysis, with the findings being summarized in Fig. 1.

Figure 1. Key macro-environmental trends in Wi-Fi offloading market

From the PEST analysis, several uncertainty factors were noted for the Wi-Fi offloading market. Of those factors, the two that had the most significant impact on the market were then considered key for the scenario analysis, namely:

i. End-user willingness (and/or capability) to install the offloading client application. Some of the offloading solutions are enabled on the user-side by downloading and installation of a client application on the terminal devices. Therefore, the adoption of the offloading service will be highly dependent on the end-users attitude (and/or technical proficiency) in regards to the installation of the client application. To that end, the user could be reluctant/unable or willing/able.

ii. Actor who triggers and control the offloading. The triggering and controlling role could vary from fully operator-controlled offloading to full end-user control. Typically, mobile operators gravitate towards solutions that give them a capability to control the overall decision-making (who, when, how) for offloading process due to sensitivity on issues of churn and revenue erosion, as well as, means for increasing ARPU (e.g. through onDemand Wi-Fi).

The Wi-Fi offloading market scenarios were then

developed by taking into account the two uncertainty factors. The resulting four scenarios, namely: spontaneous, value added, managed and idealistic offloading, are described and

existing solutions are mapped into them in the scenario matrix of Fig. 2. Considering the commercially-available offloading solutions, increased competition in mobile Internet access, limited number of end-user owned Wi-Fi access points, and the low/moderate technical proficiency of majority of the end-users [21], the most feasible offloading scenarios for African operators are value-added and managed offloading.

Figure 2. Scenario matrix

B. Value Network Analysis

Value network analysis enables the definition of actors (stakeholders), their roles and business interactions amongst them, and has previously been utilized to evaluate value network configurations (VNCs) for local broadband wireless access (3GPP and Wi-Fi access) [22]. In addition to the actors and roles introduced in [22], this paper defines two additional new roles relevant for the Wi-Fi offloading business: offloading equipment provisioning and offloading operation. The former is a straightforward role whose business actors are usually the offloading solution vendors (Notava, WeFi, Greenpacket, etc.). However, the latter offloading operation role may be played by various actors, such as, the end-user, fixed broadband operator, mobile operator, or a new business actor defined here as the offloading service provider (OSP). As a result, different VNCs could emerge depending on the identity of the business actor responsible for the offloading operation.

Since the value-added and managed offloading scenarios

are the most likely for the African market (as noted in situation analysis of Section III.A), then the business cases that put mobile operators and OSPs in the offloading operation role are selected for further value network analysis. The resulting VNCs are referred to as mobile operator driven and OSP driven offloading, respectively. The VNC are illustrated using actor block and interface connector notations adapted from [22], and shown in Fig. 3.

Figure 3. Notation for illustrating value network configurations

The mobile operator driven offloading configuration is depicted in Fig. 4, whereby the mobile operator typically rolls out the offloading infrastructure and may own the Wi-Fi access points. In that case, the mobile operator negotiates with venue owners (e.g. hospitals) for deployment of Wi-Fi access points and the fixed broadband operator for access point backhaul. A few variations to the configuration are possible. For instance, if the mobile operator is also a fixed broadband operator, the configuration is slightly modified by merging the Mobile Operator and Fixed Broadband Access Operator blocks and absorbing the business interfaces between them. Uganda Telecoms is an example of an incumbent fixed operator, with both mobile broadband and Wi-Fi networks [23]. Alternatively, the mobile operators may also have agreements with the venue owners (hotels, airports, etc.) who already operate their own Wi-Fi access points to obtain Wi-Fi capacity for the offloading service. In this case, the configuration is slightly changed by moving the Wi-Fi

Network Operation role from the mobile operator to the venue owner and adding business and technical interface between venue owner and fixed broadband operator. However, this approach may be tedious for mobile operators due to the need to negotiate and maintain contractual agreements with multiple venue owners that operate access points.

Fig. 5 shows the alternative OSP driven offloading

configuration. Here, the newly introduced business actor, the OSP, owns the offloading infrastructure and the Authentication, Authorization and Accounting (AAA) elements of the Wi-Fi network. It should be noted that in this case the OSP has access to AAA capabilities, but does not necessarily operate the Wi-Fi network. This scenario may manifest through the increasingly common practice of aggregating Wi-Fi capacity owned by different venue owners. Boingo Wireless [24] and FON [25] are good examples of community and commercial based Wi-Fi aggregators, respectively, who have gained a significant user base across many countries. Although they have utilized different business approaches to aggregate the Wi-Fi capacity successfully in a global scale, so far they yet to have any notable penetration in most African markets [17]. Considering the fast rising intra-Africa travel creating demand for data services away from home networks and the liberalization of the telecom sector across most African countries giving rise innovative cross-border service providers, the time is now feasible to devise a suitable Wi-Fi aggregation approach for Africa.

Figure 4. Mobile operator driven offloading VNC

Figure 5. VNC Offloading service provider driven offloading VNC

An alternative configuration is that of the OSP also having ownership of the Wi-Fi network. In this case the configuration is changed by moving the Wi-Fi Network Operation role from the Venue Operator to the OSP. Emerging Wi-Fi network operators, such as, UhuruOne (Tanzania) [26], may fit this role, although the coverage of these operators maybe limited only to certain areas of the urban centers of Africa (Dar es Salaam, in the case of UhuruOne). The challenge is for the Wi-Fi network-owning OSP to supplement their coverage by aggregating Wi-Fi capacity in locations that coincide with the mobile operators areas of interest traffic offloading. The aggregation strategy could be national, regional (across several African countries) or through Wi-Fi roaming agreements with global players (e.g. Boingo Wireless).

IV. EXEMPLARY BUSINESS MODEL A high-level exemplary business model for the OSP-driven offloading is presented in this chapter. The business model is developed using the STOF model [27], which provides a theoretical framework for design of business models through evaluating four inter-related domains, namely: service, technology, organizational and financial domains. The developed exemplary business model for the OSP is presented below for the different domains within the framework.

Service domain: The service concept is that the mobile operators (customers of the OSP) request offloading service from the OSP for their subscribers. The OSP may also provide Wi-Fi on demand service utilizing the same solution used for the offloading assuming that a suitable legislation exists. The OSP achieves customer retention through proper demonstration of the benefits and uniqueness of its offloading solution. Technology domain: The technical architecture of the Wi-Fi offloading solution considered for the exemplary business model is based Notava’s uAxes solution [15] and illustrated in Fig. 6.

Figure 6. Technical architecture of the offloading solution (Modified from [15])

In the stand-alone version of uAxes, the mobile devices enabled with uAxes SW update the location info (1) to the

uAxes Server provided they have active data bearer. The offloading procedure is initiated by the uAxes server as it compares device location with operator defined policy. An example policy defines offloading to take place in congested cells during the busy hour. Alternatively, if the operator installs a core network integration component the location and other usage related information is obtained from the core network (1b). The server triggers the offloading by sending a response (1a) or sending an SMS to the uAxes enabled device. The receiving of the trigger makes the device to activate Wi-Fi radio and to contact with a uAxes server task specified in the trigger (5). Using the Wi-Fi scan information the server task selects the appropriate Wi-Fi access point to be used for offloading (6) and provides the credentials and the applied authentication scheme for the device (7). Next the uAxes enabled device uses the protocols relevant to the applied authentication scheme (8)–(11).

The architecture is simple, secure and robust, as well as being scalable in terms of subscribers, mobile platforms, and Wi-Fi networks. The Wi-Fi network’s scalability is engineered in a way such that the server task specified in the offloading trigger may reside in any physical or virtual server machine.

Organization domain: The primary business partners for the OSP are offloading solution vendors, mobile operators and Wi-Fi service providers. The business relationships between these business partners and end users are depicted in Fig. 7.

Financial domain: The OSPs capital expenditure derives from establishing brand reorganization among the partners (operators, Wi-Fi providers etc.) and initial deployment of the offloading server infrastructure. Operational costs incurred mainly from leasing the Wi-Fi capacity from the providers and

maintaining the offloading server infrastructure (e.g. rental fees to facilities providers). Mobile operators are charged only for the successful offloads and the charging is based on the volume of offloaded traffic. This type of pricing scheme introduces a low risk solution for the operators, yet potentially significant revenue stream for the OSP.

V. CONCLUSION The Wi-Fi offloading service in an African-context has the

potential not just to enhance the user experience but also to seamlessly extend operators’ broadband Internet service availability to areas that are under-served or yet to be covered by their 3G networks. Furthermore, the Wi-Fi offloading scenarios and value network configurations presented here highlight significant opportunities for various business actors (e.g. operators, OSPs, venue owners, etc.) to create and/or capture value from this relatively new business concept. To further highlight the feasibility of this opportunity we presented a high-level exemplary business model based on an existing offloading solution from Notava to support to enable an OSP to provide an offloading service to multiple operators. With handset vendors now targeting multimode mobile terminals (with mobile 3G and Wi-Fi interfaces) for low/mid price points and more venue owners in Africa deploying Wi-Fi hotspots to add value to their core activities, the potential for the Wi-Fi offloading is continuously growing, and the derived benefits would be valuable to the end-users as well as operators.

Figure 7. Value network of OSP offloading business

REFERENCES [1] International Telecommunications Union (ITU): Monitoring the WSIS

Targets: A Mid-Term Review.World Telecommunication/ ICT Development Report. (2010)

[2] Lawal, L.S. & Chatwin, C.R. , The future of wireless communications in Africa. (2012)

[3] Federal Democratic Republic of Ethiopia, Growth and Transformation Plan 2010/2011-2014/2015, (2010)

[4] Opera Software ASA: State of the Mobile Web, December 2010. (2011) [5] Communications Commission of Kenya (CCK): Quarterly Sector

Statistics Report. 2nd Quarter October-December 2010/2011. (2011) [6] Cisco White Paper : Cisco Visual Networking Index: Global Mobile

Data Traffic (2011) [7] Nokia Siemens Networks: Mobile Broadband with HSPA and LTE:

Capacity and Costs Aspects. NSN white paper. (2010) [8] Various authors. 4G: From Grey to Crystal Clear. Africa Telecoms

Magazine, Issue 10 (2010) [9] Svoboda, P., Ricciato, F., Keim, W., Rupp, M.: Measured WEB

Performance in GPRS, EDGE, UMTS and HSDPA with and without Caching. In Proceedings of the IEEE International Symposium on World of Wireless, Mobile and Multimedia Networks (WoWMoM), Espoo, (2007)

[10] Brigdewater Systems: Towards a Profitable Mobile Data Business Model: Scenarios for Cost Reduction and Innovative Service Plans. Bridgewater Systems white paper. (2011)

[11] Claussen, H., Calin, D.: Macrocell Offloading Benefits in Joint Macro-and Femtocell Deployments. In Proceedings of the IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications, Tokyo, (2009)

[12] 3GPP TS 43.318: Generic Access Network (GAN). (2011)

[13] 3GPP TS 23.234: 3GPP system to WLAN Interworking. (2011) [14] 3GPP TS 23.402: Architecture Enhancements for Non-3GPP Accesses.

(2011) [15] Suoranta, R., Lappeteläinen, A.: Rethinking the problem. Notava white

paper (2010) [16] Zhang, J., de la Roche, G.: Femtocells: Technologies and Deployment.

1st edn. John Wiley & Sons Ltd, Chichester (2009) [17] Lemstra, W., Hayes, V., Groenewegen, J.: The Innovation Journey of

Wi-Fi: The Road to Global Success. Cambridge University Press, Cambridge (2011)

[18] 3GPP2 X.S0028-200-A: cdma2000 Packet Data Service: Wireless Local Area Network (WLAN) Interworking – Revision A. (2008)

[19] Schoemaker, P.: Scenario Planning: A Tool for Strategic Thinking. Sloan Management Review, (1995).

[20] Smura, T., Sorri, A.: Future Scenarios for Local Area Access: Industry Structure and Access Fragmentation. In: Proceedings of the Eight International Conference on Mobile Business, Washington DC, (2009)

[21] Gitau, S., Marsden, G., Donner, J.: After Access – Challenges Facing Mobile-Only Internet Users in the Developing World. In: Proceedings of the 28th International Conference on Human factors in Computing Systems, Atlanta, (2010)

[22] Casey, T., Smura, T., Sorri, A.: Value Network Configurations in Wireless Local Area Access. In: Proceedings of the 9th Conference of Telecommunication, Media and Internet Techno-Economics (CTTE). Ghent, Belgium (2010)

[23] Uganda Telecom: http://www.utl.co.ug/utl.php?i=17 [24] Boingo: http://www.boingo.com [25] FON: http://corp.fon.com/en/this-is-fon [26] UhuruOne: http://www.uhuruone.com/ [27] Bouwman, H., De Vos, H., Haaker, T. eds.: Mobile Service Innovation

and Business Models. Berlin: Springer (2008) .