Low-complexity Block-Based Decoding Algorithms for Short Block Channels
Abstract:
This paper presents low-complexity block-based en-
coding and decoding algorithms for short block length channels.
In terms of the precise use-case, we are primarily concerned
with the baseline 3GPP Short block transmissions in which
payloads are encoded by Reed-Muller codes and paired with
orthogonal DMRS. In contemporary communication systems, the
short block decoding often employs the utilization of DMRS-
based least squares channel estimation, followed by maximum
likelihood decoding. However, this methodology can incur sub-
stantial computational complexity when processing long bit
length codes. We propose an innovative approach to tackle this
challenge by introducing the principle of block/segment encoding
using First-Order RM Codes which is amenable to low-cost
decoding through block-based fast Hadamard transforms. The
Block-based FHT has demonstrated to be cost-efficient with
regards to decoding time, as it evolves from quadric to quasi-
linear complexity with a manageable decline in performance.
Additionally, by incorporating an adaptive DMRS/data power
adjustment technique, we can bridge/reduce the performance gap
and attain high sensitivity, leading to a good trade-off between
performance and complexity to efficiently handle small payloads.
keyword :5G NR, Short block-lengths, ML detection,
Training-based Transmission, Reed Muller codes, Fast Hadamard
Transform, Block-based Encoding and Decoding, Adaptive Power
Adjustment.