TY - GEN
T1 - Error Rate Analysis for Grant-free Massive Random Access with Short-Packet Transmission
AU - Bian, Xinyu
AU - Mao, Yuyi
AU - Zhang, Jun
N1 - Funding Information:
This work is supported by the Hong Kong Research Grants Council under Grant No. 15207220.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Grant-free massive random access (RA) is a promising protocol to support the massive machine-type communications (mMTC) scenario in 5G and beyond networks. In this paper, we focus on the error rate analysis in grant-free massive RA, which is critical for practical deployment but has not been well studied. We consider a two-phase frame structure, with a pilot transmission phase for activity detection and channel estimation, followed by a data transmission phase with coded data symbols. Considering the characteristics of short-packet transmission, we analyze the block error rate (BLER) in the finite blocklength regime to characterize the data transmission performance. The analysis involves characterizing the activity detection and channel estimation errors as well as applying the random matrix theory (RMT) to analyze the distribution of the post-processing signal-to-noise ratio (SNR). As a case study, the derived BLER expression is further simplified to optimize the pilot length. Simulation results verify our analysis and demonstrate its effectiveness in pilot length optimization.
AB - Grant-free massive random access (RA) is a promising protocol to support the massive machine-type communications (mMTC) scenario in 5G and beyond networks. In this paper, we focus on the error rate analysis in grant-free massive RA, which is critical for practical deployment but has not been well studied. We consider a two-phase frame structure, with a pilot transmission phase for activity detection and channel estimation, followed by a data transmission phase with coded data symbols. Considering the characteristics of short-packet transmission, we analyze the block error rate (BLER) in the finite blocklength regime to characterize the data transmission performance. The analysis involves characterizing the activity detection and channel estimation errors as well as applying the random matrix theory (RMT) to analyze the distribution of the post-processing signal-to-noise ratio (SNR). As a case study, the derived BLER expression is further simplified to optimize the pilot length. Simulation results verify our analysis and demonstrate its effectiveness in pilot length optimization.
KW - approximate message passing (AMP)
KW - block error rate (BLER)
KW - Grant-free massive random access
KW - pilot length optimization
KW - random matrix theory (RMT)
KW - short-packet transmission
UR - http://www.scopus.com/inward/record.url?scp=85146935419&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM48099.2022.10001105
DO - 10.1109/GLOBECOM48099.2022.10001105
M3 - Conference article published in proceeding or book
AN - SCOPUS:85146935419
T3 - 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings
SP - 4752
EP - 4757
BT - 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE Global Communications Conference, GLOBECOM 2022
Y2 - 4 December 2022 through 8 December 2022
ER -