Machine type communications is seen as a form of data communication, among devices and/or from devices to a set of servers, that do not necessarily require human interaction. It provides ubiquitous connectivity between machines, enabling creation of the so-called Internet-of-Things. However, it is challenging to accommodate MTC in LTE as a result of its specific characteristics and requirements such as: massive number of connected devices, small and sporadic payload transmissions, power constraint, and various quality-of-service requirements.
The aim of this thesis is to propose mechanisms and optimize the access layer techniques for MTC in LTE. In particular, our research deal with the uplink channel access and downlink reception. For uplink access, we propose two methods to improve the performance of random access in terms of latency: a packet aggregation method and a Transmission Time Interval bundling scheme. To further reduce the uplink latency and enable massive number of connected device, we propose a new contention based access method (CBA) to bypass both the redundant signaling in the random access procedure and also the latency of regular scheduling. We also present a resource allocation method for CBA to guarantee the delay constraint under minimal allocation. For downlink reception, we propose two methods to analyze the performance of discontinuous reception DRX mode for MTC applications: the first with the Poisson distribution and the second with the Pareto distribution for sporadic traffic. With the proposed models, the power saving factor and wake up latency can be accurately estimated for a given choice of DRX parameters, thus allowing to select the ones presenting the optimal tradeoff.