Analyzing Novel Grant-Based and Grant-Free Access Schemes for Small Data Transmission

The Fifth Generation (5G) New Radio (NR) does not support data transmission during the random access (RA) procedures, which results in unnecessary control signalling overhead and power consumption, especially for small data transmission. Motivated by this, we propose two new RA schemes based on the existing grant-based (4-step) and grant-free (2-step B) RA schemes, which are NR Early Data Transmission (NR EDT) and 2-step A RA schemes, with the aim to enable data transmission during RA procedures in Radio Resource Control (RRC) Inactive state. To compare our proposed schemes with the benchmark schemes, we provide a spatio-temporal analytical framework to evaluate the RA schemes, which jointly models the preamble detection, Physical Uplink Shared Channel (PUSCH) decoding, and data transmission procedures. Based on this analytical model, we derive the analytical expressions for the overall packet transmission success probability of four RA schemes in each time slot. We also derive the throughput and the average energy consumption for a successful packet transmission of each scheme. Our results show that the 2-step A and 2-step B RA schemes provide the highest overall packet transmission success probability, the 2-step A RA scheme provides the lowest average energy consumption in low device intensity scenario, and 2-step B RA provides the lowest average energy consumption in high device intensity scenario.

[1]  Zhensheng Zhang,et al.  Comments on 'The effect of capture on performance of multichannel slotted ALOHA systems' , 1993, IEEE Trans. Commun..

[2]  Xingqin Lin,et al.  Random Access Preamble Design and Detection for 3GPP Narrowband IoT Systems , 2016, IEEE Wireless Communications Letters.

[3]  Erik Dahlman,et al.  4G: LTE/LTE-Advanced for Mobile Broadband , 2011 .

[4]  Martin Haenggi,et al.  Stochastic Geometry for Wireless Networks , 2012 .

[5]  Olav Tirkkonen,et al.  RRC State Handling for 5G , 2019, IEEE Communications Magazine.

[6]  George K. Karagiannidis,et al.  Analyzing Grant-Free Access for URLLC Service , 2020, ArXiv.

[7]  Sarah J. Johnson,et al.  Massive Multiple Access Based on Superposition Raptor Codes for Cellular M2M Communications , 2017, IEEE Transactions on Wireless Communications.

[8]  Sandra Lagen,et al.  The Impact of NR Scheduling Timings on End-to-End Delay for Uplink Traffic , 2019, 2019 IEEE Global Communications Conference (GLOBECOM).

[9]  Xu Li,et al.  Non-Orthogonal Random Access for 5G Networks , 2017, IEEE Transactions on Wireless Communications.

[10]  Jaiyong Lee,et al.  Exploiting the Capture Effect to Enhance RACH Performance in Cellular-Based M2M Communications , 2017, Sensors.

[11]  Tuomas Tirronen,et al.  3GPP Release 15 Early Data Transmission , 2018, IEEE Communications Standards Magazine.

[12]  H. Vincent Poor,et al.  Secure Short-Packet Communications for Mission-Critical IoT Applications , 2019, IEEE Transactions on Wireless Communications.

[13]  Mischa Dohler,et al.  Machine-to-Machine (M2M) Communications: Architecture, Performance and Applications , 2015 .

[14]  Sunghyun Choi,et al.  Low Latency Random Access for Small Cell Toward Future Cellular Networks , 2019, IEEE Access.

[15]  Adnan Aijaz,et al.  On Performance Evaluation of Random Access Enhancements for 5G uRLLC , 2019, 2019 IEEE Wireless Communications and Networking Conference (WCNC).

[16]  Stefan Parkvall,et al.  5G New Radio: Unveiling the Essentials of the Next Generation Wireless Access Technology , 2018, IEEE Communications Standards Magazine.

[17]  Vincent W. S. Wong,et al.  Optimal Access Class Barring for Stationary Machine Type Communication Devices With Timing Advance Information , 2015, IEEE Transactions on Wireless Communications.

[18]  Antonino Masaracchia,et al.  Robust Adaptive Modulation and Coding (AMC) Selection in LTE Systems Using Reinforcement Learning , 2014, 2014 IEEE 80th Vehicular Technology Conference (VTC2014-Fall).

[19]  Petar Popovski,et al.  Towards Massive, Ultra-Reliable, and Low-Latency Wireless Communication with Short Packets , 2015 .

[20]  Arumugam Nallanathan,et al.  RACH Preamble Repetition in NB-IoT Network , 2018, IEEE Communications Letters.

[21]  Andrea Zanella,et al.  Theoretical Analysis of the Capture Probability in Wireless Systems with Multiple Packet Reception Capabilities , 2012, IEEE Transactions on Communications.

[22]  Mohamed-Slim Alouini,et al.  Spatiotemporal Model for Uplink IoT Traffic: Scheduling and Random Access Paradox , 2018, IEEE Transactions on Wireless Communications.

[23]  Dan Keun Sung,et al.  An Early Preamble Collision Detection Scheme Based on Tagged Preambles for Cellular M2M Random Access , 2017, IEEE Transactions on Vehicular Technology.

[24]  Ahlem Khlass,et al.  Efficient Handling of Small Data Transmission for RRC Inactive UEs in 5G Networks , 2021, 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring).

[25]  Arumugam Nallanathan,et al.  Random Access Analysis for Massive IoT Networks Under a New Spatio-Temporal Model: A Stochastic Geometry Approach , 2017, IEEE Transactions on Communications.

[26]  Tony Q. S. Quek,et al.  Analyzing Random Access Collisions in Massive IoT Networks , 2018, IEEE Transactions on Wireless Communications.

[27]  Klaus Moessner,et al.  Energy-Efficient Short Packet Communications for Uplink NOMA-Based Massive MTC Networks , 2019, IEEE Transactions on Vehicular Technology.

[28]  Stefania Sesia,et al.  LTE - The UMTS Long Term Evolution, Second Edition , 2011 .

[29]  Petar Popovski,et al.  Preamble Detection in NB-IoT Random Access with Limited-Capacity Backhaul , 2019, ICC 2019 - 2019 IEEE International Conference on Communications (ICC).

[30]  Yuan Wu,et al.  Uplink Scheduling and Link Adaptation for Narrowband Internet of Things Systems , 2017, IEEE Access.

[31]  Mohamed-Slim Alouini,et al.  Spatiotemporal Stochastic Modeling of IoT Enabled Cellular Networks: Scalability and Stability Analysis , 2016, IEEE Transactions on Communications.