2. Background
Studies indicate that developing countries’ settlement patterns present infrastructure development challenges for the deployment of services [
8]. Settlements have close and scattered proximity and lower population densities and incomes, affecting resource mobilisation and the fair distribution of infrastructure development and business viability. Furthermore, low population densities, low rural income, and lack of local application content affect the expansion and adoption of broadband services, including internet use. Challenges include the lack of institutional capacity, the void created by high prices charged by MNOs, and the lack of primary network access to provide an alternative connectivity network. Governments across developed and developing countries have introduced wireless fidelity (Wi-Fi hotspot) networks to address the lack of affordable services and internet access, and for improved public service efficiency.
Despite the successful government deployment of a substantive fibre infrastructure development and other frameworks, many users complain about high broadband services, poor network services, and a lack of e-government services. Communities in developing countries often settle in sparse-location patterns approximately less than 10 to 40 km apart, which demand MNOs, ISPs, and other service providers to install more infrastructure development, and require added resources [
9]. For example, although Tlhareseleele, Rakhuna, and other villages are less than 10 to 40 km from Pitsane/Goodhope, which have an adequate ICT infrastructure, they experience limited network services. Most of the time, these cluster villages access roaming broadband services across from South Africa’s MNOs [
10].
Therefore, this study noted that many deployments in developing countries, including Botswana, predominately rely on LTE, notwithstanding the many successful deployments of the WiMAX IEEE 802.16 Standard reluctant to adopt the technology. Many studies have point out that WiMAX IEEE 802.16 addresses developing countries’ lack of infrastructure development and significantly reduces the cost of infrastructure deployments. Therefore, this study adopted experimental and simulated WiMAX IEEE 802.16 for access at the last-mile level.
Notwithstanding the gains from the Wi-Fi hotspot initiative, public Wi-Fi services have eased congestion and enhanced service delivery, particularly in the banking sector. As a result, many people access statements, transfer funds, and use other online services outside banking halls. In addition, the introduced metro-based Wi-Fi hotspot initiatives provide service end-users with alternative access away from the high tariffs charged by MNOs and ISPs. However, despite the Wi-Fi hotspot advantages, the initiative has limited coverage, requires extensive network infrastructure deployment, and may not work for rural areas. The expansion of Wi-Fi hotspots requires a series of added infrastructure and network installations, including institutional and regulatory frameworks, to address management, maintenance, and regulatory issues.
Nevertheless, developing countries could adopt more advanced wireless technologies to address the prevalent lack of infrastructure development, high infrastructure deployment costs, and lack of business viability in rural areas. Among the wireless technologies available, Worldwide Interoperability for Microwave Access (WiMAX IEEE 802.11) stands out as a possible solution for developing countries’ rampant lack of infrastructure development and dream of addressing the digital divide and rolling out e-government services. Furthermore, WiMAX IEEE 802.16e has demonstrated the capacity to provide connectivity and access for rural areas beyond other wireless technologies. Therefore, we simulated a testbed to determine the appropriateness of WiMAX IEEE 802.16e as an access technology for rural areas at the last-mile level.
Therefore, this study looks at various alternative options to address connectivity and access for rural areas. The study presents three scenarios, urban and peri-urban, main villages, and rural areas, and measures network efficiency based on distance from base stations, cost of deployment, and access to both LTE and WiMAX infrastructure installations.
In Botswana, urban and peri-urban areas have high population densities and generally have adequate and proportionate infrastructure installations. The situation ensures that service providers experience relatively lower infrastructure deployment costs and service end-users access network services, and are less likely to experience digital divide challenges.
Main villages and rural areas: These villages have populations of over 100,000 and have settlements and smaller villages about 10 km to 30 km away. Despite main villages having adequate infrastructure installations and connectivity, smaller villages close by experience a lack of broadband connectivity and access. In some of the worst situations, some villages situated along the installed fibre infrastructure not connected. The situation adversely affects social movements and businesses, as service end-users experience network service disparities and high service rates.
Involves clusters of smaller villages 10 km to 30 km apart, and one village has infrastructure installations and is connected and others are not connected and are without access to broadband services.
The situations of Scenarios 2 and 3 indicate that the government and MNOs require added costs to provide services, for example for e-education, e-health, e-commerce, and other e-services, due to lack of business viability, high cost, and lack of infrastructure to support connectivity and access. Therefore, we determined whether a testbed using WiMAX 82.16e technology could address connectivity and access for cluster villages and villages on the peripheries of urban areas and main villages.
3. Literature Review
Kaur et al. [
11] used the Opnet 14.5 simulator to evaluate the quality of service over WiMAX IEEE802.16 standard and obtained satisfactory results. In addition, Carrillo and Seki [
12] found that, despite WiMAX 802.16 being used as access technology for the Internet of Things in metro areas, it could drive agribusiness applications such as UAV operation over 45 km and two times 50 m high. The findings indicate that although the WiMAX standard is used commonly in metro areas, it is suited for rural areas. Also, Abdulrazzaq et al. [
13] evaluated WiMAX 802.16 standard and found that the light (standard) VOIP service over WiMAX has no delay and throughput than voice with heavy video. This measurement indicates that using WiMAX-based networks to drive agribusiness in rural areas equally has advantages as other technologies at the last-mile level. Conclusively, Nafea and Hamza [
14] found that 18 to 24 WiMAX 802.16e base stations could service a 467.34 km
2 area, suggesting that the WiMAX EEE 802.16e network could address connectivity and access of clustered small villages within 10 km and 30 km apart.
The lack of relevant technology, infrastructure development, low population, and inadequate local application content in developing countries has limited internet penetration [
15]. As a result, governments face the daunting task of providing connectivity and access, ensuring that end-users access e-government and other broadband services. The government should meet various obligations, such as national development programmes, millennium development goals (MDGs), and international telecommunication union treaties (ITU). However, connectivity and access challenges present opportunities for the government and other broadband stakeholders to explore technologies to address the challenges. Failure to provide citizens with connectivity and access, regardless of location, could create two types of citizens, one with access and the other not benefiting. Another challenge facing developing countries, including Botswana, is the rampant lack of support for infrastructure development, such as the lack of household power (electricity) connectivity, inadequate road networks, and equipment security.
Despite limited WiMAX installations and LTE dominance in Botswana, MNOs, ISPs, and BoFiNET have deployed the technology on some sites. According to the Research ICT Africa report, Angola, Mozambique, Nigeria, Namibia, Ghana, and other countries adopted WiMAX as an access technology in the region, and have improved their internet penetration, affordability, and mitigated connectivity challenges [
16]. Although the WiMAX standard body withdrew the WiMAX 802.16a/b/c, currently 802.16d/e/m is available and provides around 50 km for the Line of Sight or fixed stations, and 5–15 km for non-Line of Sight or mobile stations [
17]. The WiMAX IEEE 802.16d could provide 70 Mbps, 802.16e—15 Mbps, and 802.16m—100 Mbps when installed. In addition, the WiMAX standard provides three alternate topologies: fixed point to point (P2P), fixed point to multipoint (P2MP), and mobile WiMAX [
17]. A mobile WiMAX topology relies on the collaborations of base stations to relay communication to subscriber stations and mobile devices that support a series of overlapping cells, which relay a signal to another base station cell and provide access [
17].
Liang emphasises that only wireless access technologies can address the rural broadband connectivity challenge by deploying wireless access technologies, especially WiMAX technology [
18]. Liang et al. point out that wired technologies require infrastructure installations often incompatible with developing countries’ settlement patterns, which leads to higher deployment costs than for wireless technologies. The reliance on wired technologies has led developing countries to fail to deliver on several connectivity commitments from the government, such as Commonwealth Telecommunication Organization (CTO) 2015 and International Telecommunication Union (ITU) 2016. Despite the positive institutional and regulatory milestones, the RIA Botswana ICT report [
19] found that Botswana’s ICT readiness ranking deteriorated to the worst levels. The ICT report attributes the national broadband project’s deterioration to the universal service obligations (USO), weak tariff regulations, poor quality of service (QoS) and other value-added network services, dimensions to high termination costs, and skewed market [
19]. In addition, the ICT report found that only 9% of their study respondents used the internet and resided in urban areas, while the rest of the country experienced a lack of internet connectivity access [
19].
Orange Botswana reported that the deployment of WiMAX IEEE 802.16e significantly improved the QoS and affordability of the internet connections in Francistown and Gaborone [
20]. Although the WiMAX standard body initially developed technology for metro and high-density areas access, it has successfully demonstrated connectivity and access for rural areas with less infrastructure deployment [
17].
5. Results and Discussion
Another observation about developing countries is the sparse settlement pattern and the heightened demand for ICT infrastructure development with the capacity to cover more areas with less deployment. Most settlements are 10 to 40 km away from urban areas, so whether sparse settlement patterns connectivity and access are addressed by the deployment of WiMAX 802.16e was analyzed.
The simulation results depended on the simulation model, which evaluated the performance of WiMAX involving subscriber stations placed at various distances from the base station, at 10 km, 20 km, and 30 km.
Figure 3 shows Subscriber Station 1, at 10 km; Subscriber Station 8, at 20 km; and Subscriber Station 11, at 30 km. Again, the same amount of
Y-axis packets sent across the network and the simulation time (
X-axis) was equal for the three scenarios.
Figure 4 shows traffic received, with slight variations for the three subscriber stations. For example, packets received at 10 km and 20 km had very slight variations, while packets received at 30 km were significantly different. For 20 km, the rate of packets received widened, implying that distance affects the quality of the packets received and the variations caused by a signal blockage—trees or anything else that blocked the Line of Sight. In the rural area transmission had an increased use of nodes and lower traffic to manage variations—the latter is a common feature in rural areas.
Figure 5 presents the average time delay of traffic from the base station to the three subscriber stations. The delay for the different subscriber stations varied: the subscriber station at 10 km experienced a more negligible time delay, while the subscriber station at 20 km experienced an average delay. In comparison, the subscriber station at 30 km experienced the most significant time delay.
In
Figure 6, the average time jitter for traffic over the network upon reaching the three subscriber stations shows that the subscriber station at 30 km experienced jitter, even though it was low. In addition, the subscriber stations at 10 km and 20 km also experienced jitter, although less than the subscriber station at 30 km. Inevitably, except for the jitter at the subscriber station at 30 km, the amount of jitter dropped significantly at the other intervals.
Figure 7 presents the traffic that dropped over the network to the three different subscriber stations. The further the subscriber station from the base station, the more traffic the network would drop. However, the network consistently retained the packets, which could be attributed to the wireless MAN-FDMA (orthogonal frequency division multiple access) abilities and the TCP/UDP at the transport layer level. Using TCP/UDP ensures that the network loses or drops packets.
The simulation results show that metrics balance network deficit with the traffic load to optimize efficiency. For example, the continued simulation showed that the further the subscriber station, the more the jitter was reduced.
The consistency of the expected performance metric levels from the three subscriber station distance points suggests that the overall performance was better than expected. The study observed a delay over longer distances and added more nodes to boost the signal. In addition, an apparent characteristic of rural areas, namely, a low population density, means the network may optimize efficiency due to low traffic.
Author Contributions
Conceptualization, B.M.E. and M.M.; methodology, B.M.E.; software, M.M.; validation, B.M.E. and M.M.; formal analysis, B.M.E.; investigation, M.M.; resources, M.M.; data curation, B.M.E.; writing—original draft preparation, M.M.; writing—review and editing, B.M.E.; visualization, B.M.E. and M.M.; supervision, B.M.E.; project administration, B.M.E.; funding acquisition, B.M.E. and M.M. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
The data used in the simulation are contained in this article.
Acknowledgments
We would like to thank the Sol Plaatje University for assistance, as well as the Botswana Ministry of Transport and Communications (MTC), Botswana Fabre Network (BoFiNET), and Botswana Communication Regulatory Authority (BOCRA) for assisting with information on communication infrastructure about Botswana. We are also thankful to MaSIM and FNAS of the North-West University.
Conflicts of Interest
The authors of this article declare no conflict of interest.
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