PROJECT TITLE :
A Predictive Resource Allocation Algorithm in the LTE Uplink for Event Based M2M Applications
Some M2M applications like event monitoring involve a cluster of devices in a very vicinity that act in a very co-ordinated manner. An LTE network can exploit the correlated traffic characteristics of such devices by proactively assigning resources to devices primarily based upon the activity of neighboring devices in the identical group. This will scale back latency compared to waiting for each device within the group to request resources reactively per the quality LTE protocol. In this paper, we specify a new low complexity predictive resource allocation algorithm, called the one method algorithm, to be used with delay sensitive event primarily based M2M applications in the LTE uplink. This algorithm needs minimal incremental processing power and memory resources at the eNodeB, yet will reduce the mean uplink latency below the minimum potential price for a non-predictive resource allocation algorithm. We have a tendency to develop mathematical models for the chance of a prediction, the chance of a successful prediction, the chance of an unsuccessful prediction, resource usage/wastage possibilities, and mean uplink latency. The validity of these models is demonstrated by comparison with the results from a simulation. The models can be used offline by network operators or on-line in real time by the eNodeB scheduler to optimize performance.
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