TY - GEN
T1 - Throughput Maximization and IR-HARQ Optimization for URLLC Traffic in 5G Systems
AU - Avranas, Apostolos
AU - Kountouris, Marios
AU - Ciblat, Philippe
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/5/1
Y1 - 2019/5/1
N2 - Emerging 5G networks will need to efficiently support ultra-reliable, low-latency communications (URLLC) services, which require extremely low latency (msec order) with very high reliability (99.999%). We consider a URLLC system with short packets and incremental redundancy hybrid automatic repeat request (IR-HARQ). We aim at maximizing the throughput by optimally tuning the IR-HARQ mechanism subject to URLLC constraints and a fixed energy budget. We propose a dynamic programming algorithm for solving the throughput maximization problem in the finite blocklength regime and assess its performance numerically.
AB - Emerging 5G networks will need to efficiently support ultra-reliable, low-latency communications (URLLC) services, which require extremely low latency (msec order) with very high reliability (99.999%). We consider a URLLC system with short packets and incremental redundancy hybrid automatic repeat request (IR-HARQ). We aim at maximizing the throughput by optimally tuning the IR-HARQ mechanism subject to URLLC constraints and a fixed energy budget. We propose a dynamic programming algorithm for solving the throughput maximization problem in the finite blocklength regime and assess its performance numerically.
UR - https://www.scopus.com/pages/publications/85070200601
U2 - 10.1109/ICC.2019.8761154
DO - 10.1109/ICC.2019.8761154
M3 - Conference contribution
AN - SCOPUS:85070200601
T3 - IEEE International Conference on Communications
BT - 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Conference on Communications, ICC 2019
Y2 - 20 May 2019 through 24 May 2019
ER -