eHealth M2M wireless uplink for LTE cellular networks

eHealth is one of the most rapidly growing facets of the medical industry. Future eHealth appllications will require a great emphasis on remote patient monitoring (RPM). To facilitate this a robust scheduling scheme needs to be in place to accommodate the large number of Machine to Machine (M2M) devices which will require network resources. This project looks at utilising the LTE cellular network framework to facilitate wireless M2M communication in the facet of eHealth applications by introducing a hybrid scheduling scheme. the scheduler emphasises proportional fairness by allocating a specific percentage of the available network resources to both human and machine UE's depending on the time of day. It also borrows concepts from maximum throughput scheduling to assign priorities and uses a unique mathematical approach to calculate the amount of resources allocated to each device. It also identifies the optimal transmission time for a given device to accommodate their delay budget requirements. The proposed scheduling algorithm is not an adaptation of any one specific type of scheduling scheme, but rather a hybrid of several schemes to create a scheduling mechanism which is appropriate for the network. The scheduler was then modelled in the VIENNA LTE MATLAB simulator to look at its performance with regards to throughput, bit error rate (BER), and block error rate (BLER). Its performance was then contrasted with existing scheduling schemes, both primitive and hybrid. For ots specific application it outperformed all the other scheduling types that it was comprised of and is the most appropriate for use within its field. The ultimate outcome of this project is a hybrid LTE scheduler which can Effectively be used to assist RPM related eHealth applications over the current 4G/LTE network.