TY - GEN
T1 - A Quantum Approximate Optimization Algorithm-Based Decoder Architecture for NextG Wireless Channel Codes
AU - Kasi, Srikar
AU - Sud, James
AU - Jamieson, Kyle
AU - Ravi, Gokul Subramanian
N1 - Publisher Copyright: © 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Forward Error Correction (FEC) provides reliable data flow in wireless networks despite the presence of noise and interference. However, its processing demands significant fraction of a wireless network's resources, due to its computationally-expensive decoding process. This forces network designers to compromise between performance and implementation complexity. In this paper, we investigate a novel processing architecture for FEC decoding, one based on the quantum approximate optimization algorithm (QAOA), to evaluate the potential of this emerging quantum compute approach in resolving the decoding performance-complexity tradeoff. We present FDeQ, a QAOA-based FEC Decoder design targeting the popular NextG wireless Low Density Parity Check (LDPC) and Polar codes. To accelerate QAOA-based decoding towards practical utility, FDeQ exploits temporal similarity among the FEC decoding tasks. This similarity is enabled by the fixed structure of a particular FEC code, which is independent of any time-varying wireless channel noise, ambient interference, and even the payload data. We evaluate FDeQ at a variety of system parameter settings in both ideal (noiseless) and noisy QAOA simulations, and show that FDeQ achieves successful decoding with error performance at par with state-of-the-art classical decoders at low FEC code block lengths. Furthermore, we present a holistic resource estimation analysis, projecting quantitative targets for future quantum devices in terms of the required qubit count and gate duration, for the application of FDeQ in practical wireless networks, highlighting scenarios where FDeQ may outperform state-of-the-art classical FEC decoders.
AB - Forward Error Correction (FEC) provides reliable data flow in wireless networks despite the presence of noise and interference. However, its processing demands significant fraction of a wireless network's resources, due to its computationally-expensive decoding process. This forces network designers to compromise between performance and implementation complexity. In this paper, we investigate a novel processing architecture for FEC decoding, one based on the quantum approximate optimization algorithm (QAOA), to evaluate the potential of this emerging quantum compute approach in resolving the decoding performance-complexity tradeoff. We present FDeQ, a QAOA-based FEC Decoder design targeting the popular NextG wireless Low Density Parity Check (LDPC) and Polar codes. To accelerate QAOA-based decoding towards practical utility, FDeQ exploits temporal similarity among the FEC decoding tasks. This similarity is enabled by the fixed structure of a particular FEC code, which is independent of any time-varying wireless channel noise, ambient interference, and even the payload data. We evaluate FDeQ at a variety of system parameter settings in both ideal (noiseless) and noisy QAOA simulations, and show that FDeQ achieves successful decoding with error performance at par with state-of-the-art classical decoders at low FEC code block lengths. Furthermore, we present a holistic resource estimation analysis, projecting quantitative targets for future quantum devices in terms of the required qubit count and gate duration, for the application of FDeQ in practical wireless networks, highlighting scenarios where FDeQ may outperform state-of-the-art classical FEC decoders.
KW - Decoding
KW - LDPC Codes
KW - Polar Codes
KW - QAOA
UR - http://www.scopus.com/inward/record.url?scp=85217360188&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85217360188&partnerID=8YFLogxK
U2 - 10.1109/QCE60285.2024.00051
DO - 10.1109/QCE60285.2024.00051
M3 - Conference contribution
T3 - Proceedings - IEEE Quantum Week 2024, QCE 2024
SP - 368
EP - 379
BT - Technical Papers Program
A2 - Culhane, Candace
A2 - Byrd, Greg T.
A2 - Muller, Hausi
A2 - Alexeev, Yuri
A2 - Sheldon, Sarah
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE International Conference on Quantum Computing and Engineering, QCE 2024
Y2 - 15 September 2024 through 20 September 2024
ER -