Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed

Enabling Hardware Green Internet of Things: A review of Substantial Issues

Between now and the near future, the Internet of Things (IoT) will redesign the socio-ecological morphology of the human terrain. The IoT ecosystem deploys diverse sensor platforms connecting millions of heterogeneous objects through the Internet. Irrespective of sensor functionality, most sensors are low energy consumption devices and are designed to transmit sporadically or continuously. However, when we consider the millions of connected sensors powering various user applications, their energy efficiency (EE) becomes a critical issue. Therefore, the importance of EE in IoT technology, as well as the development of EE solutions for sustainable IoT technology, cannot be overemphasised. Propelled by this need, EE proposals are expected to address the EE issues in the IoT context. Consequently, many developments continue to emerge, and the need to highlight them to provide clear insights to researchers on eco-sustainable and green IoT technologies becomes a crucial task. To pursue a clear vision of green IoT, this study aims to present the current state-of-the art insights into energy saving practices and strategies on green IoT. The major contribution of this study includes reviews and discussions of substantial issues in the enabling of hardware green IoT, such as green machine to machine, green wireless sensor networks, green radio frequency identification, green microcontroller units, integrated circuits and processors. This review will contribute significantly towards the future implementation of green and eco-sustainable IoT

Diversity techniques for signal-strength based indoor location determination

Diversity techniques have been found in the literature to be suitable for compensating channel uncertainties such as multipath fading. In this thesis, we exploit spatial and frequency diversity techniques for improving accuracy in locating stationary and mobile objects in the indoor environment --Abstract, page iv

Resource Allocation in Ad Hoc Networks

Unlike the centralized network, the ad hoc network does not have any central administrations and energy is constrained, e.g. battery, so the resource allocation plays a very important role in efficiently managing the limited energy in ad hoc networks. This thesis focuses on the resource allocation in ad hoc networks and aims to develop novel techniques that will improve the network performance from different network layers, such as the physical layer, Medium Access Control (MAC) layer and network layer. This thesis examines the energy utilization in High Speed Downlink Packet Access (HSDPA) systems at the physical layer. Two resource allocation techniques, known as channel adaptive HSDPA and two-group HSDPA, are developed to improve the performance of an ad hoc radio system through reducing the residual energy, which in turn, should improve the data rate in HSDPA systems. The channel adaptive HSDPA removes the constraint on the number of channels used for transmissions. The two-group allocation minimizes the residual energy in HSDPA systems and therefore enhances the physical data rates in transmissions due to adaptive modulations. These proposed approaches provide better data rate than rates achieved with the current HSDPA type of algorithm. By considering both physical transmission power and data rates for defining the cost function of the routing scheme, an energy-aware routing scheme is proposed in order to find the routing path with the least energy consumption. By focusing on the routing paths with low energy consumption, computational complexity is significantly reduced. The data rate enhancement achieved by two-group resource allocation further reduces the required amount of energy per bit for each path. With a novel load balancing technique, the information bits can be allocated to each path in such that a way the overall amount of energy consumed is minimized. After loading bits to multiple routing paths, an end-to-end delay minimization solution along a routing path is developed through studying MAC distributed coordination function (DCF) service time. Furthermore, the overhead effect and the related throughput reduction are studied. In order to enhance the network throughput at the MAC layer, two MAC DCF-based adaptive payload allocation approaches are developed through introducing Lagrange optimization and studying equal data transmission period

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors