Resource management strategies for cellular and non-cellular IOT applications

Abstract

The number of IoT connected devices and applications are increasing day-by-day. Ever-increasing applications of IoT in various sectors necessitate the management of available resources for their effective operations. Different IoT applications have different requirements in terms of data-rate, coverage, latency, power consumption, mobility, cost, etc. However, due to the trade-off between different parameters i.e., power consumption, coverage, and data-rate, a single technology cannot meet these requirements of different IoT applications. This, in turn, forces to adopt different IoT technologies based on intended application requirements. For instance, some applications such as remote patient monitoring, security cameras, smart-phones, etc., require medium to high data-rate, low-latency and wider coverage. Cellular IoT framework best fits for such applications, thereby these applications fall under cellular IoT applications. On the other hand, number of applications such as traffic congestion control, water metering, smart parking, smart lighting, waste management, pollution monitoring, animal tracking, etc., work well at low data-rates, but require extensive coverage at low power consumption. Such applications can work well over non-cellular IoT framework, and thereby these applications fall under non-cellular IoT applications. In this thesis, we emphasis on both the cellular and non-cellular IoT applications. Non-cellular IoT technologies mainly include Bluetooth, wireless-fidelity (Wi-Fi), Sigfox, and Long Range Wide Area Network (LoRaWAN). Over the past few years, we have witnessed an explosive increase in the number of LoRaWAN devices to serve the non-cellular IoT applications, primarily because LoRaWAN offers attractive features such as long-range, low-power, and low-cost. Moreover, its open standards that allow an individual to build an autonomous network. However, the scalability of LoRaWAN is a major concern, which in particular depends on spreading factor (SF) allocation schemes. In Chapter 2 and Chapter 3 of this thesis, we propose two novel SF allocation schemes to improve the scalability of LoRaWAN. Cellular IoT technologies mainly include legacy wireless technologies, (i.e., 2G, 3G, 4G, and 5G), and narrow-band IoT (NB-IoT). Providing massive connectivity at high data-rates to cellular IoT devices is foremost challenge for cellular IoT technologies. Network densification is one of the promising solution to meet this requirement of cellular IoT networks. However, due to scarcity of spectrum, increase in cellular IoT devices lead to an inter-cell-interference (ICI) on already existing cellular devices and users. This impact of ICI on user or device is more severe when interference comes from the LoS link. In Chapter 4 of this thesis, we addressed the issue of ICI on user or device in an aerial-terrestrial based non-cellular IoT networks by efficiently allocating the available spectrum. Another possible solution to reduce ICI in cellular-based IoT networks is to use both mmWave and microwave RAT. In Chapter 5 of this thesis, we model an integrated mmWave and microwave network and proposes a novel RAT selection rule to take the additional benefits from mmWave RAT in terms of data-rate and reduced interference.