Performance analysis of an enhanced delay sensitive LTE uplink scheduler for M2M traffic

Abstract

The Long Term Evolution (LTE) standard is one of the most promising wireless access technologies for Machine to Machine (M2M) communications because of its high data rates, low latency and economies of scale. M2M communications typically involves a large number of autonomous devices sending traffic in a coordinated manner (and possibly even simultaneously), therefore creating an uplink-heavy trend which needs an efficient radio resource management scheme. The conventional scheduling algorithms and performance metrics are not suitable for M2M systems because of the different characteristics and service requirements of M2M traffic. In this paper, we analyze the performance of an enhanced delay sensitive uplink scheduler in context of LTE TDD configurations 0 and 1 for delay sensitive event based M2M traffic. We show that unlike an ordinary equal capacity fair scheduler, our proposed delay sensitive scheduler can make utmost use of the maximally uplink-biased TDD configuration 0, attaining higher capacity and maximizing the chance of satisfying packet delay budget of M2M traffic. We also introduce a new performance metric called "Effective Allocated Bits/RB pair" to measure the allocation efficiency of a scheduler, evaluate the performance of the proposed scheduler in terms of this metric and identify the scope of possible improvements.

BAT: A Balanced Alternating Technique for M2M Uplink Scheduling over LTE

“…We now conduct a simulation-based comparison among some basic algorithms (Round-Robin and SNR based), algorithm from literature (Enhanced Delay [14]) and the proposed algorithm (BAT at q% = 50%, 90%). Fig.…”

“…In [14], the authors present the "Enhanced Delay Sensitive Scheduler" that uses a newly defined metric called urgency. Urgency is a function of packet deadline and buffer size.…”

“…This algorithm is application-specific for Wireless Sensor Networks (WSN) or cascaded alarming systems. Delay has more priority than channel [8] QoS Dedicated QoS class is defined by delay and bit rate [9] Delay Hybrid Classes based on delay [10] Channel, Utlity Hybrid Utility is based on required bit rate [11] Fairness, QoS, Channel Hybrid QoS class is defined by delay and bit rate [12] Packet Arrival N/A* Groups based on packet arrival and jitter [13] Packet Arrival, Data Size Dedicated Groups based on packet arrival and data size [14] Delay …”

Comparative performance study of LTE uplink schedulers for M2M communication

“…In [9], the authors propose a scheduler to satisfy the QoS requirements. This scheduler prioritizes the devices that have a critical deadline and more data do transmit.…”

“…The solution proposed in [10] uses a group-based scheduling to satisfy the QoS requirements. In this approach, the devices are grouped into classes according with their deadline and calculated similarly as shown in [9]. Furthermore, to control the impact of M2M on H2H, in the scheduling it is given higher priority to the H2H devices than to the M2M devices in the same class.…”