A Quantum Approximate Optimization Algorithm-based Decoder Architecture for NextG Wireless Channel Codes

• DOI: 10.48550/arxiv.2408.11726
• Publication Date: 2024-08-21
• Authors: Srikar Kasi; James Sud; Kyle Jamieson; Gokul Subramanian...
• Keywords: Quantum Physics; FOS: Physical sciences; Quantum Physics (quant-ph)

Forward Error Correction (FEC) provides reliable data flow in wireless networks despite the presence of noise and interference. However, its processing demands significant fraction a network's resources, due to computationally-expensive decoding process. This forces network designers compromise between performance implementation complexity. In this paper, we investigate novel architecture for FEC decoding, one based on quantum approximate optimization algorithm (QAOA), evaluate potential emerging compute approach resolving performance-complexity tradeoff. We present FDeQ, QAOA-based Decoder design targeting popular NextG Low Density Parity Check (LDPC) Polar codes. To accelerate towards practical utility, FDeQ exploits temporal similarity among tasks. is enabled by fixed structure particular code, which independent any time-varying channel noise, ambient interference, even payload data. at variety system parameter settings both ideal (noiseless) noisy QAOA simulations, show that achieves successful with error par state-of-the-art classical decoders low code block lengths. Furthermore, holistic resource estimation analysis, projecting quantitative targets future devices terms required qubit count gate duration, application networks, highlighting scenarios where may outperform decoders.