Abdullahi Kutiriko Abubakar

Low Power Wide Area Networks (LPWANs) are a subset of IoT transmission technologies that have gained traction in recent years with the number of such devices exceeding 200 million. This paper considers the scalability of one such LPWAN, LoRaWAN, as the number of devices in a network increases. Various existing optimisation techniques target LoRa characteristics such as collision rate, fairness, and power consumption. This paper proposes a machine learning ensemble to reduce the total distance between devices and improve the average received signal strength, resulting in improved network throughput, the scalability of LoRaWAN, and the cost of networks. The ensemble consists of a constrained K-Means clustering algorithm, a regression model to validate new gateway locations and a Neural network to estimate signal strength based on the location of the devices. Results show a mean distance reduction of 51% with an RSSI improvement of 3% when maintaining the number of gateways, also achieving a distance reduction of 27% and predicting an RSSI increase of 1% after clustering with 50% of the number of gateways.

The specialness of New Year eve traffic is a telecoms industry fable. But how true is it, and what's the impact on user experience? We investigate this on the four UK cellular networks, in London, on New Year eve in 2016/17, 2017/18, 2018/19 and 2019/20 (covid cancelled 2020/21 & 2021/22). Overall, we captured 544,560 readings across 14 categories using 3G/4G/5G devices. This paper summarises our longitudinal readings into 10 observations on the nature of network performance, from a user's perspective, on special days such as New Year eve. Based on these, we confirm that mature 3G/4G networks are unable to deliver a consistent user experience, especially on atypical days. For example, on 4G, a user had a 60% chance to get a latency below 50 ms and 90% chance for 500ms. If repeated in mature 5G networks, it suggests that it is inadequate to support safety-critical 5G use cases.

As adoption of connected cars (CCs) grows, the expectation is that 5G will better support safety-critical vehicle-to-everything (V2X) use cases. Operationally, most relationships between cellular network providers and car manufacturers or users are exclusive, providing a single network connectivity, with at best an occasional option of a back-up plan if the single network is unavailable. We question if this setup can provide QoS assurance for V2X use cases. Accordingly, in this paper, we investigate the role of redundancy in providing QoS assurance for cellular connectivity for CCs. Using our bespoke Android measurement app, we did a drive-through test on 380 kilometers of major and minor roads in South East England. We measured round trip times, jitter, page load times, packet loss, network type, uplink speed and downlink speeds on the four UK networks for 14 UK-centric websites every five minutes. In addition, we did the same measurement using a much more expensive universal SIM card provider that promises to fall back on any of the four UK networks to assure reliability. By comparing actual performance on the best performing network versus the universal SIM, and then projected performance of a two/three/four multi-operator setup, we make three major contributions. First, the use of redundant multi-connectivity, especially if managed by the demand-side, can deliver superior performance (up to 28 percentage points in some cases). Second, despite costing 95x more per GB of data, the universal SIM performed worse than the best performing network except for uplink speed, highlighting how the choice of parameter to monitor can influence operational decisions. Third, any assessment of CC connectivity reliability based on availability is sub-optimal as it can hide significant under-performance.