Joint PHY and MAC Layer Perspective for Compressed Sensing in Wireless Communications

In the massive Machine Type Communications service of 5G, low control signalling and overhead is more preferred to support the communication between an aggregation center and massive number of Machine Type Devices. To this end, direct random access has become one of many promising approaches in this field, which can be enabled by the Physical layer technique, Compressed Sensing based Multi-User Detection. Based on the state-of-the-art analysis of Compressed Sensing based Multi-User Detection, this thesis focuses on the requirements and characteristics of massive Machine Type Communications and try to further study the applicability of Compressed Sensing based Multi-User Detection in massive Machine Type Communications such as different traffic models, channel estimation perspective, in combination with MAC layer protocols and performance abstraction of Compressed Sensing based Multi-User Detection based PHY layer processing.