Aijaz, Adnan

Machine-to-Machine (M2M) communications is an emerging communication paradigm that provides ubiquitous connectivity between devices along with an ability to communicate autonomously without human intervention. M2M communications acts as an enabling technology for the practical realization of Internet-of-Things (IoT). However, M2M communications differs from conventional Human-to-Human (H2H) communications due to its unique features such as massive number of connected devices, small data transmissions, little or no mobility, requirements of high energy efficiency and reliability, etc. These features create various challenges for existing communication networks which are primarily optimized for H2H communications. Therefore, novel solutions are required to meet the key requirements of M2M communications. In addition, enhancements are required at different layers of the protocol stack to support co-existence of M2M devices and H2H users.The main objective of this research is to investigate the challenges of M2M communications in two broad types of M2M networks; capillary M2M and cellular M2M networks. The primary focus is on developing novel solutions, algorithms, and protocol enhancements for successfully enabling M2M communications. Since cognitive radio technology is very promising for M2M communications, special emphasis is on capillary M2M networks with cognitive radio based Physical layer. Besides, the focus is also on exploring new frontiers in M2M communications.This thesis covers different aspects of M2M communications. Considering the motivation for cognitive M2M and service requirements of M2M devices, two cognitive MAC protocols have been proposed. The first protocol is centralized in nature and utilizes a specialized frame structure for co-existence with the primary network as well as handling different Quality-of-Service (QoS) requirements of M2M devices. The second protocol is a distributed cognitive MAC protocol, which is specially designed to provide high energy efficiency and reliability for M2M devices operating in challenging wireless environments. Both protocols explicitly account for the peculiarities of cognitive radio environments. The protocols have been evaluated using analytical modeling and simulation studies.Recently IETF has standardized a specially designed routing protocol for capillary M2M networks, known as RPL (Routing for Low Power and Lossy Networks). RPL is emerging as the de facto routing protocol for many M2M applications including the smart grid. On the other hand, the application of cognitive radio for smart grid communication is under active investigation in the research community. Hence, it is important to investigate the applicability and adaptation of RPL in cognitive radio environments. In this regard, an enhanced RPL based routing protocol has been proposed for cognitive radio enabled smart grid networks. The enhanced protocol provides novel modifications to RPL for protecting the primary users along with meeting the utility requirements of the secondary network.An important challenge in LTE-based cellular networks with M2M communications is the uplink radio resource management as available resources are shared between M2M devices and H2H users, having different and often conflicting QoS requirements. Apart from this, energy efficiency requirements become critically important. Further, the specific constraints of Single Carrier Frequency Division Multiple Access (SC-FDMA) complicate the resource allocation problem. In this respect, an energy efficient resource allocation algorithm for the uplink of LTE networks with M2M/H2H co-existence under statistical QoS guarantees has been developed, that is based on canonical duality theory. The proposed algorithm outperforms classical algorithms in terms of energy efficiency while satisfying the QoS requirements of M2M devices and H2H users.A new frontier in M2M communications is the nano-M2M communications, which is envisioned to create the Internet-of-Nano-Things (IoNT). Molecular communication (MC) is a promising communication technique for nano-M2M communications. In literature, no model for error performance of MC exists. Therefore, an error performance model has been developed that explicitly accounts for noise and interference effects. Since relaying and network coding based solutions are gaining popularity for nano-M2M networks, the error performance of a network coded molecular nano-M2M network has been evaluated as well.Finally, the thesis is concluded based on the overall picture of the research conducted. In addition, some directions for future work are included as well

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Protocol Design for Machine-to-Machine Networks

https://kclpure.kcl.ac.uk/portal/files/33251500/2014_Aijaz_Adnan_1019375_ethesis.pdf

Protocol Design for Machine-to-Machine Networks

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