Does effective spectrum management make a real difference when it comes to more pervasive and affordable access to communication? In this post I look at the spectrum management regimes in four African countries: Kenya, Nigeria, Senegal, and South Africa, and try to draw some conclusions. One of the challenges in comparing access in these countries is simply recognising how different they are from each other. Nigeria is three times more populous than South Africa but with a smaller land mass. Senegal has roughly the same income per capita as Kenya but its wealth is more evenly distributed. Its significantly smaller population and land mass have implications both for ease of coverage but also for the size of the telecommunications market. All of these factors make it challenging to do head-to-head comparisons of telecom sectors, let alone spectrum management alone. Things like population density, robustness of the electrical grid, crime levels, etc., all are factors in the cost of building and maintaining wireless networks.
General country statistics
Country | GDP per capita | Population | Gini Coefficient | Land Mass |
(PPP$) | (millions) | (%) | (sq km) | |
Kenya | 1,781 | 42 | 47.7 | 582,650 |
Nigeria | 2,697 | 164 | 48.8 | 923,768 |
Senegal | 2,005 | 13 | 39.2 | 196,190 |
South Africa | 11,281 | 51 | 63.1 | 1,219,912 |
But that hasn’t stopped anyone trying. Below you can see some indicators that rank countries on ICTs. Actually, the first, the World Bank’s Doing Business Report, is not ICT-specific but rather tries to capture the general ease of doing business in a given country. Next we have the ITU’s Measuring the Information Society (MIS) report which ranks countries’ performance with regard to ICT infrastructure and uptake. Then there is the Alliance for Affordable Internet Access (A4AI) Affordability Report which looks at affordability in the overall context of the regulatory and infrastructure environment. And in the realm of specific indicators, we have the Ookla Net Index which directly measures broadband speeds across countries. Finally Research ICT Africa’s Fair Mobile index looks at prepaid mobile costs.
ICT rankings
Country | World Bank | ITU | A4AI | Ookla | Research ICT Africa |
Doing Business | Measuring the Information Society | Affordability Report | Net Index | Cheapest Prepaid | |
(rank) | (rank) | (rank) | (Mbps) | ($US) | |
Kenya | 129 | 116 | 18 | 6.56 | 4.3 |
Nigeria | 147 | 122 | 19 | 4.43 | 7.36 |
Senegal | 178 | 124 | 24 | 6.71 | 13.32 |
South Africa | 41 | 84 | 12 | 4.92 | 12.06 |
So what can we interpret from the above? Aggregate scores can be difficult to interpret and inevitably reflect the bias of the designers. However across the Doing Business, MIS, and A4AI ranks, we can see South Africa as clearly the front-runner when it comes to the overall ICT and business environment. What then accounts for the extremely high pre-paid costs? Perhaps it is South Africa’s overall GDP per capita and the fact that the market will charge whatever it can. Senegal comes out last of the four countries in all composite indexes and the prepaid costs are consistent with those rankings. Curiously though Senegal appears to have the fastest broadband speed among the four. Nigeria, with five undersea fibre optic cables landing on its shores, more undersea cables than any other country in sub-Saharan Africa, still has the slowest broadband of the four countries according to the NetIndex. Clearly broadband is struggling to make its way in from the coast. What we can interpret from the above is that there are many necessary but not sufficient conditions for competition to occur and even when all the necessary conditions exist, sometimes it take a moment of punctuated equilibrium to get things moving.
Spectrum Assignments
In the rest of this article, you’ll see detailed breakdowns on spectrum assignments in a number of the popular and emerging spectrum bands for mobile services. You’ll see things like MTN 2 x 11 FDD. This means that MTN has 22 MHz of spectrum broken up into two chunks. FDD stands for Frequency Division Duplexing and it means that the uplink and downlink for the spectrum are on two different frequencies, typically at either end of the spectrum band. Historically all mobile spectrum has been allocated this way. This works best when there is relative symmetry in the upload and download traffic such as is found on voice networks. It is less efficient for digital networks where there is a much bigger bias towards download than upload.
Historically digital communication technologies tend to use a single frequency for upload and download. This approach is known as TDD or Time Division Duplexing, is expressed in the tables below in the form 1 x 10 TDD which refers to a single 10 MHz block. Both TDD and FDD have their strengths and weaknesses and LTE represents the frontier of the debate on FDD vs TDD because manufacturers are producing LTE technologies for both FDD and TDD deployments. My personal opinion is that the future is with TDD technologies, partly because they are better suited to digital usage but also because they make assigning individual blocks of spectrum less complex. FDD is not going away soon though as existing spectrum assignments will be slow to change. For more information on this, Huawei has an interesting paper on the potential for TDD LTE in Africa.
The first major blocks of spectrum to look at are the 900MHz and 1800MHz bands, the bread and butter of GSM networks in Africa and Europe. 900MHz is great for rural networks because of its greater propagation characteristics than 1800MHz while 1800MHz is great for urban deployments because there is more capacity for densely populated areas. You will note that countries make different choices about what size of spectrum to assign an individual operator. In the 900MHz band, most regulators chose to assign spectrum in roughly 10 MHz chunks but the Nigerian regulator chose to assign spectrum in 5MHz chunks. What is the impact of this? Obviously it allows the regulator to open up the field to more competition as we can see five mobile operators with mobile spectrum in Nigeria as opposed to typically three in other countries. The downside to this approach is the capacity that is afforded each operator. The amount of spectrum assigned to each operator has a direct impact on the number of users that can be supported at full capacity on a given cell.
Of course that is not the only factor. Backhaul capacity also is a significant factor. For rural deployments 5MHz may be sufficient but it is likely to be problematic for densely populated urban areas. There is a general assumption that all of the GSM spectrum in Africa has been assigned and is in use but a look at the 1800 MHz table reveals that both Senegal and Kenya have a substantial amount of spectrum in the 1800 MHz band that is unassigned. As 1800 MHz transitions to more LTE use, perhaps that represent an opportunity or at least presents some flexibility in re-farming the band. As we have seen, 1800 MHz is currently the most popular choice for LTE deployments in Africa.
900 MHz
Spectrum range: 880-960MHz (80MHz)
South Africa | Kenya | Nigeria | Senegal | ||||
MTN | 2 x 11 FDD | Safaricom | 2 x10 FDD | Etilisat | 2 x 5 FDD | Orange (Sonatel) | 2 x 12,4 FDD |
Vodacom | 2 x 11 FDD | Celtel (Airtel) | 2 x10 FDD | Glo | 2 x 5 FDD | Tigo (Sentel) | 2 x 10 FDD |
Cell C | 2 x 11 FDD | Telkom Kenya | 2 x 7.5 FDD | Mtel | 2 x 5 FDD | Expresso (Sudatel) | 2 x 12 FDD |
Essar (yuMobile) | 2 x 7.5 FDD | MTN | 2 x 5 FDD | ||||
Zain (Airtel) | 2 x 5 FDD | ||||||
Total: 66 MHz | Total: 70 MHz | Total: 50 MHz | Total: 68.4 MHz |
1800 MHz
Spectrum range: 1710–1785 and 1805–1880 MHz (150 MHz)
South Africa | Kenya | Nigeria | Senegal | ||||
MTN | 2 x 12 FDD | Safaricom | 2 x 10 FDD | Etilisat | 2 x 15 FDD | Orange (Sonatel) | 2 x 16 FDD |
Vodacom | 2 x 12 FDD | Celtel (Airtel) | 2 x 10 FDD | Glo | 2 x 15 FDD | Tigo (Sentel) | 2 x 09 FDD |
Cell C | 2 x 12 FDD | Telkom Kenya | 2 x 10 FDD | Mtel | 2 x 15 FDD | Expresso (Sudatel) | 2 x 16 FDD |
Neotel | 2 x 12 FDD | Essar (yuMobile) | 2 x 10 FDD | MTN | 2 x 15 FDD | ||
Telkom | 2 x 12 FDD | Zain (Airtel) | 2 x 15 FDD | ||||
WBS | 2 x 12 FDD | ||||||
WBS | 1 x 10 TDD | ||||||
Total: 154 MHz | Total: 80 MHz | Total: 150 MHz | Total: 82 MHz |
Next, in the table below, is the 2100 MHz band or what is typically know as 3G spectrum. Once again, Kenya and Senegal appear to have roughly 50% of the spectrum still unassigned. I was unable to obtain data on Nigeria in spite of the regulator’s excellent information on other bands. Can we draw any conclusions so far on the impact of spectrum occupancy? Not a lot at the moment. Kenya leads in cost of mobile access and Senegal lags. Would things be different if they had assigned more spectrum? It seems likely that there are other more significant factors at play.
2100 MHz
Spectrum range: 1920-1980 and 2110–2170 MHz (120 MHz)
South Africa | Kenya | Nigeria | Senegal | ||||
Vodacom | 2 x 15 FDD | Safaricom | 2 x 10 FDD | Glo | ? | Orange (Sonatel) | 2 x 15 FDD |
Vodacom | 1 x 5 TDD | Celtel (Airtel) | 2 x 10 FDD | MTN | ? | Tigo (Sentel) | 2 x 10 FDD |
MTN | 2 x 15 FDD | Telkom Kenya | 2 x 10 FDD | Airtel | ? | Expresso (Sudatel) | 2 x 15 FDD |
MTN | 1 x 5 TDD | Expresso (Sudatel) | 1 x 5 TDD | ||||
Cell C | 2 x 15 FDD | ||||||
Cell C | 1 x 5 TDD | ||||||
Telkom | 2 x 10 FDD | ||||||
Spare | 2 x 10 FDD | ||||||
Total: 125 MHz | Total: 60 MHz | Total: | Total: 70 MHz |
The 800 MHz band has typically been used for CDMA2000 networks in Africa. Once a big contender to GSM as a standard for mobile networks, GSM has largely won out in spite of not being as efficient a technology as CDMA. While many CDMA2000 network operators have incurred losses, the emergence of the 800 MHz band for LTE may offer them new possibilities. However, the organisation of the band for LTE is different and it is likely that it will take years for the re-farming of this spectrum to take place. One exception to this is Smile Telecom who have a 15 MHz TDD license in Nigeria. This has allowed them to launch an LTE data network focused on Internet users. Having a relatively large chunk of spectrum in the sub-1GHz range for LTE arguably puts Smile in a very attractive positive. The question remains how fast regulators will be able to make this spectrum band available.
800 MHz
South Africa | Kenya | Nigeria | Senegal | ||||
Neotel | 2 x 5 FDD | Telkom Kenya | 2 x 5 FDD | Smile | 1 x 15 TDD | Expresso (Sudatel) | 2 x 6,25 FDD |
GiCell Wireless | 2 x 3.75 FDD | ||||||
TC Africa Telecoms Network | 2 x 3.75 FDD | ||||||
Multilinks | 2 x 3.75 FDD | ||||||
Visafone Communications | 2 x 3.75 FDD | ||||||
Total: 10 MHz | Total: 10 MHz | Total: 45 MHz | Total: 12.5 MHz |
Moving on to what are green pastures for mobile operators, the 2300 MHz band has recently risen to prominence. In South Africa, the incumbent Telkom have been able to take advantage of an existing spectrum assignment in the 2300 MHz band designed for point-to-point links and re-purpose it for LTE data. With 60 MHz of spectrum and the wide availability of low-cost data dongles, Telkom has quickly risen to be a serious contender for mobile broadband. Nigeria has very recently made spectrum available in this band with an auction last month that saw Bitflux Communications with 30 MHz of spectrum. Senegal apparently has a universal service consortium operating in this band but more information than that was not available.
2300 MHz
Spectrum range: 2300-2400 MHz (100 MHz)
South Africa | Kenya | Nigeria | Senegal | ||||
Telkom | 3 x 20 TDD | Bitflux Communications | 1 x 30 TDD | CSU SA (Opérateur de Service Universel) | 1 x 10 TDD | ||
Total: 60 MHz | Total: | Total: 30 MHz | Total: 10 MHz |
2600 MHz is another emerging band for LTE services but none of the four countries have assigned spectrum for LTE in this band. South Africa has had plans in the works to auction the 2600 MHz band since 2009 but has failed to date to make this spectrum available. One of the obstacles has been the fact that roughly 1/3 of the band was occupied by two existing operators. The debate over whether and how the spectrum incumbents should re-farmed was a significant obstacle to be overcome. It also highlighted the challenge of trying to satisfy demand for both TDD and FDD spectrum. The reason the incumbents needed to be moved is that their TDD spectrum was low down in the spectrum band which made it impossible to assign any FDD bands. A spectrum neutral approach would see a spectrum framework that accommodates both types of assignments. While I was unable to find specific assignments for Nigeria in this band, the regulator recently announced that they would be auctioning this band as soon as the spectrum was freed up from the national broadcaster in the context of the digital switchover.
2600 MHz
Spectrum range: 2500-2690 MHz (190 MHz)
South Africa | Kenya | Nigeria | Senegal | ||||
Sentech | 1 x 50 TDD | NBC | |||||
WBS (iBurst) | 1 x 15 TDD | ||||||
Total: 65 MHz | Total: | Total: | Total: |
3500 MHz
Spectrum range: 3400-3600 MHz (200 MHz)
South Africa | Kenya | Nigeria | Senegal | ||||
Sentech | 2 x 14 FDD | Telkom Kenya | 2 x 11 FDD | Glo | ? | ||
Neotel | 2 x 28 FDD | KDN | 2 x 28 FDD | MTN | ? | ||
Telkom | 2 x 28 FDD | Open Systems Tech. | 2 x 7 FDD | Airtel | ? | ||
Airwaves Comms | 2 x 7 TDD | Etilisat | ? | ||||
Comtec Group | 2 x 7 FDD | ||||||
IGO Wireless | 2 x 7 FDD | ||||||
SimbaNET | 2 x 7 FDD | ||||||
PacketStream Data | 2 x 8 FDD | ||||||
UUNet Comms | 2 x 7 FDD | ||||||
Total: 140 MHz | Total: 178 MHz | Total: ? | Total: |
700 MHz
So far, no African countries have assigned spectrum for broadband in the 700MHz band. In all four countries, it is still a part of the spectrum allocated for terrestrial television broadcast. Yet it is perhaps one of the most interesting spectrum bands for Africa as its excellent propagation characteristics make it an ideal technology for rural broadband both in terms of reach and in terms of cost of roll-out. Also, the fact that 700 MHz is emerging as a global mobile spectrum band means that end-user devices from handsets to dongles will be cheap. The challenge will be how to make the spectrum available in a manner that promotes competition and encourages rapid deployment. Spectrum auctions are almost unknown in sub-Saharan Africa with Nigeria being the only country to have carried out spectrum auctions. While this has generated revenue for the Nigerian government, it is hard to say whether auctions have had a significant impact on either access or affordability there. It is likely that an auction in the 700 MHz band in most African countries would see spectrum going to the incumbents. This is exactly what happened in the recent 700MHz auction in Canada. Another approach would be to follow the model that Mexico has taken and assign the 700 MHz band to a carrier of carriers that would offer wireless infrastructure to any competitor. There are indications that both South Africa and Kenya may be considering an approach like this.
WiFi
WiFi connectivity is now a serious factor in “mobile” access. Across Africa WiFi hotspots proliferate in cafes, hotels, and airports. Mobile users actively seek out WiFi for cheaper and faster access. However, an aspect of WiFi that is under-reported is its use for point-to-point links. Companies like Ubiquiti and Mikrotik make very low-cost WiFi equipment that can extended connectivity in hundreds of megabits over hundreds of kilometres. Unfortunately not all WiFi regulation in Africa supports this. In Zimbabwe, for instance, a license is required for WiFi point-to-point links and the regulator (POTRAZ) does not give out any licenses. Among the countries in this overview, South Africa is the clear front-runner. Not only does it have very progressive regulation regarding the use of WiFi for point-to-point and point-to-multipoint communication but it is the only country in sub-Saharan Africa to have an industry association, the Wireless Access Providers Association (WAPA), that represents the industry and promotes standards and good conduct. With roughly 150 active members, this is a model that other countries would be well-served by emulating. In Kenya, by contrast, point-to-point WiFi is unlicensed as long as it does not cross a property boundary. Use of WiFi beyond that requires registration and attracts an annual frequency fee of approximately $110 per terminal per year. Given that the WiFi devices themselves will often cost less than $100, this is a significant drag on the innovation that could be happening for low-cost backhaul in both the 2.4GHz and 5GHz unlicensed bands. In Nigeria, WiFi is free for private use but a license is required for commercial use. Senegal similarly requires users to apply for a license for point-to-point WiFi links. As WiFi equipment continues to improve in capacity and affordability, restricting innovation in infrastructure deployment via WiFi represents and increasing missed opportunity.
Dynamic Spectrum
Dynamic allocation of spectrum is steadily gaining traction as a regulatory option, with the the VHF and UHF television spectrum bands being the first likely candidates for “white spaces” spectrum deployments. It is a particularly appealing option in Africa where the UHF band is largely unoccupied and spectrum range in question of 450-700 MHz is particular well-suited to rural deployments. Kenya and South Africa are both leaders in the deployment of this technology with each country having “white spaces” pilots deployed in 2013. Nigeria is not far behind. To date, Senegal has not announced intentions of exploring dynamic spectrum regulation.
Digital Migration
The transition from analogue to digital terrestrial television broadcasting has been in the works since 2006. With just over a year to go, few countries in Africa seem likely to meet the deadline. In South Africa, debates have ranged from which standard to adopt to whether signals should be encrypted to how set-top-boxes should be designed. Kenya is probably the most advanced country in sub-Saharan African in terms of the digital switchover but even there the process is now mired in the courts. In Nigeria, there is steady progress but concerns remain regarding the 2015 deadline. Delays in the switchover could have negative implications not just for television broadcasting but also for the emerging 700 MHz IMT band which is currently allocated to television broadcasting. Dynamic spectrum allocation could also suffer. Although there is no reason for dynamic spectrum allocation to be delayed as it is a secondary use of spectrum, some regulators are reluctant to take any action regarding television spectrum before the switchover is complete.
Conclusion
Wireless technology is evolving rapidly and the challenge in spectrum management is both to keep pace with technological change but also to make decisions that allow for the future to surprise us as it always does. The move to unified licensing by most regulators and to technological neutrality in spectrum licensing are great trends. Nigeria is interesting from the point of view of spectrum auctions. While it is not obvious that auctions have directly led to more effective competition or lower prices than the other countries in this overview, the fact that the Nigerian regulator now has extensive experience in conducting auctions means that they can probably make new spectrum available faster and more efficiently than their peers. One of the keys to successful spectrum auctions is having a well-understood and documented process. Nigeria’s experience with auctions might allow them to move faster than other countries now that they have a clear framework for spectrum assignment.
Progress in roll-out and competitive pricing does not appear to be directly linked to spectrum assignment. It could be argued that Senegal’s small number of operators and modest amount of spectrum assigned are a factor in the relatively high cost of access and low ICT index ranking but it seems more likely that is a side-effect of other processes such as a lack of government prioritisation of ICT infrastructure. Kenya, by contrast, appears to have excelled in competitive pricing but without significantly more spectrum assigned than Senegal. If we are to judge by transparency and public availability of information, the Kenyan regulator tops the list, a model for other countries. Nigeria is a close second. On the other hand, South Africa and Senegal‘s regulatory web resources could use some work both in organisation and content around spectrum.
This comparison of spectrum regimes across these four countries is an attempt to look for strengths, weakness, commonalities, and opportunities in spectrum management in sub-Saharan Africa. Yet it is really just scratching the surface of the issue and would benefit greatly from feedback. I have deliberately chosen a subset of spectrum bands that I think are relevant to the development of wireless broadband. If there are key bands you think I should have included, please let me know. In general, I would be grateful to anyone who could point out mistakes, key omissions, or new insights from this overview.
This entry is part 6 of 6 in the series Africa and Spectrum 2.0.