Step-GRAND: A Low Latency Universal Soft-input Decoder

07/14/2023
by   Syed Mohsin Abbas, et al.
0

GRAND features both soft-input and hard-input variants that are well suited to efficient hardware implementations that can be characterized with achievable average and worst-case decoding latency. This paper introduces step-GRAND, a soft-input variant of GRAND that, in addition to achieving appealing average decoding latency, also reduces the worst-case decoding latency of the corresponding hardware implementation. The hardware implementation results demonstrate that the proposed step-GRAND can decode CA-polar code (128,105+11) with an average information throughput of 47.7 Gbps at the target FER of ≤10^-7. Furthermore, the proposed step-GRAND hardware is 10× more area efficient than the previous soft-input ORBGRAND hardware implementation, and its worst-case latency is 1/6.8× that of the previous ORBGRAND hardware.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro