Long-term Evolution-advanced Cellular Networks Research Articles

Sharing It My Way: Efficient M2M Access in LTE/LTE-A Networks

When a large number of machine-to-machine (M2M) terminals attempt to access the Long-Term Evolution (LTE)/LTE Advanced (LTE-A) cellular network using the physical random access channel (PRACH), congestion and overload may result, which can lead to serious degradation of performance for both M2M and human-to-human (H2H) terminals. The main cause for this is the inherent complexity of the four-way handshake used for random access, which is well suited for H2H terminal access but unsuitable for massive M2M access. In this paper, we describe an efficient scheme for concurrent M2M and H2H access on the PRACH, which separates the resources for M2M and H2H access at the level of preamble codes and avoids the use of the four-step handshake for M2M terminals by implementing a carrier sense multiple access with collision avoidance (CSMA/CA) overlay network using the designated preamble codes. We analyze the performance of the scheme for both H2H and M2M traffic and show the values of the most important design parameters that enable this scheme to support concurrent access by H2H and M2M terminals with little performance degradation.

Analytical modelling and performance evaluation of realistic time‐controlled M2M scheduling over LTE cellular networks

ABSTRACTSupporting emerging machine‐to‐machine (M2M) communications over Long‐term Evolution (LTE)/LTE Advanced cellular networks in an efficient way will be beneficial for both telecommunication communities. The first step to migrate to an M2M‐enabled cellular standard is to provide these new services through the existing architectures and protocols, while maintaining seamless backward compatibility. To this end, we thoroughly examined a key LTE Medium Access Control entity, which is the packet scheduler, and proposed solutions based on the time‐controlled M2M feature, to deal with the diverse M2M traffic characteristics and quality‐of‐service requirements. Starting from the single M2M class case, we extended our study to more realistic scenarios, involving more M2M classes with diverse quality‐of‐service requirements. We defined analytical models for predicting the system performance on the basis of queueing theory concepts and considered the interaction between classes with different priorities. The proposed analytical models are validated through extensive system‐level simulations. On the basis of the insight obtained from our analytical approach, we modified an existing scheduling algorithm to improve the performance of low‐priority M2M device groups, and we demonstrated its superior performance both experimentally and analytically. Copyright © 2013 John Wiley & Sons, Ltd.