Online Control of Preamble Groups with Priority in Cellular IoT Networks

Internet of Things (IoT) is the ongoing revolution that offers a truly connected society by integrating several heterogeneous services and applications. A major transformation is urgently needed when the volume of connected devices far exceeds people oriented connections. Due to diversity in applications and requirements, one important trend is that the connected devices could manifest different priorities. With the variety of requirements accordingly, in terms of latency, payload size, number of connections, update frequency, reliability, the Random access process (RAP) as the first step to establish connection between most devices and the base station would also require modification in cellular IoT. In order to prioritize the IoT devices in RAP, we propose a novel online control algorithm with dynamic preamble distribution over multiple priorities. The proposed algorithm recursively estimates the number of active devices in each priority based on Bayesian rule and controls the number of preambles for each priority accordingly. Subsequently, we extend our proposal to incorporate access class baring (ACB) to optimize the algorithm. Extensive simulations show the effectiveness of proposed algorithm over multiple priorities.

[1]  Jun-Bae Seo,et al.  Recursive Pseudo-Bayesian Access Class Barring for M2M Communications in LTE Systems , 2017, IEEE Transactions on Vehicular Technology.

[2]  Mohamed Othman,et al.  A Survey of Random Access Control Techniques for Machine-to-Machine Communications in LTE/LTE-A Networks , 2018, IEEE Access.

[3]  Alexandros Kaloxylos,et al.  5G Radio Access Network Architecture: Design Guidelines and Key Considerations , 2016, IEEE Communications Magazine.

[4]  Jeongho Park,et al.  Random access in millimeter-wave beamforming cellular networks: issues and approaches , 2015, IEEE Communications Magazine.

[5]  Young-June Choi,et al.  Random Access Channel Management for Handling Massive Numbers of Machine-to-Machine Communication Devices , 2018, 2018 International Conference on Information and Communication Technology Convergence (ICTC).

[6]  Nelson Luis Saldanha da Fonseca,et al.  Allocation of control resources with preamble priority awareness for human and machine type communications in LTE-Advanced networks , 2017, 2017 IEEE International Conference on Communications (ICC).

[7]  Xiaofeng Tao,et al.  QoS-based Dynamic Allocation and Adaptive ACB Mechanism for RAN Overload Avoidance in MTC , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[8]  Jin Liu,et al.  Initial Access, Mobility, and User-Centric Multi-Beam Operation in 5G New Radio , 2018, IEEE Communications Magazine.

[9]  Jianlong Liu,et al.  A Novel Congestion Reduction Scheme for Massive Machine-to-Machine Communication , 2017, IEEE Access.

[10]  Stefan Parkvall,et al.  NR - The New 5G Radio-Access Technology , 2017, 2018 IEEE 87th Vehicular Technology Conference (VTC Spring).

[11]  Mariyam Ouaissa,et al.  Performance analysis of random access mechanisms for machine type communications in LTE networks , 2016, 2016 International Conference on Advanced Communication Systems and Information Security (ACOSIS).

[12]  Rahim Tafazolli,et al.  Dynamic Preamble Subset Allocation for RAN Slicing in 5G Networks , 2018, IEEE Access.

[13]  Jin Young Lee,et al.  Compressive random access using distance based resource block selection scheme for machine type communications , 2017, 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[14]  Dong In Kim,et al.  LTE/LTE-A Random Access for Massive Machine-Type Communications in Smart Cities , 2016, IEEE Communications Magazine.

[15]  Wolfgang Kellerer,et al.  LATMAPA: Load-Adaptive Throughput- MAximizing Preamble Allocation for Prioritization in 5G Random Access , 2017, IEEE Access.

[16]  Cong Wang,et al.  Dynamic Resource Allocation and Access Class Barring Scheme for Delay-Sensitive Devices in Machine to Machine (M2M) Communications , 2017, Sensors.