An Adaptive Buffer Based Semi-persistent Scheduling Scheme for Machine-to-Machine Communications over LTE

One of the key characteristics of cellular Machine-to-Machine (M2M) communications is the generation of small data packets by a large number of devices. The excessive control signaling required for dynamic scheduling of such uplink data in the Long Term Evolution (LTE) standard impedes the deployment of LTE networks for M2M communications. Traditional Semi-persistent scheduling (SPS) reduces the load on control channel but it is currently only developed for constant data rate voice packets. For realistic M2M environments, non-deterministic data traffic needs to be served in a resource efficient way. In this paper, we propose a buffer based adaptive SPS scheme for the LTE uplink which does not require the control signaling overhead of dynamic scheduling, but offers the same flexibility of increasing or decreasing the number of allocated radio resource blocks according to the latest buffer status of the device. We examine the influence of SPS periodicity on quality of Service (QoS) satisfaction of delay constrained stochastic M2M traffic and compare the performance of the proposed adaptive SPS scheme with rigid fixed allocation SPS schemes for such traffic. We also demonstrate how the adaptive SPS scheme can be implemented in a resource efficient way to meet the QoS requirements of a large number of machine type nodes through data aggregation.