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Leveraging parallelizability and channel structure in THz-band, Tbps channel-code decoding

Hakim Jemaa, Hadi Sarieddeen, Simon Tarboush, Mohamed-Slim Alouini, Tareq Y. Al-Naffouri

TL;DR

This paper addresses the challenge of achieving Tbps data rates in THz-band communications by focusing on the baseband computation bottleneck by leveraging parallel processing and pseudo-soft information (PSI) across multicarrier THz channels for efficient channel code decoding.

Abstract

As advancements close the gap between current device capabilities and the requirements for terahertz (THz)-band communications, the demand for terabit-per-second (Tbps) circuits is on the rise. This paper addresses the challenge of achieving Tbps data rates in THz-band communications by focusing on the baseband computation bottleneck. We propose leveraging parallel processing and pseudo-soft information (PSI) across multicarrier THz channels for efficient channel code decoding. We map bits to transmission resources using shorter code-words to enhance parallelizability and reduce complexity. Additionally, we integrate channel state information into PSI to alleviate the processing overhead of soft decoding. Results demonstrate that PSI-aided decoding of 64-bit code-words halves the complexity of 128-bit hard decoding under comparable effective rates, while introducing a 4 dB gain at a $10^{-3}$ block error rate. The proposed scheme approximates soft decoding with significant complexity reduction at a graceful performance cost.

Leveraging parallelizability and channel structure in THz-band, Tbps channel-code decoding

TL;DR

This paper addresses the challenge of achieving Tbps data rates in THz-band communications by focusing on the baseband computation bottleneck by leveraging parallel processing and pseudo-soft information (PSI) across multicarrier THz channels for efficient channel code decoding.

Abstract

As advancements close the gap between current device capabilities and the requirements for terahertz (THz)-band communications, the demand for terabit-per-second (Tbps) circuits is on the rise. This paper addresses the challenge of achieving Tbps data rates in THz-band communications by focusing on the baseband computation bottleneck. We propose leveraging parallel processing and pseudo-soft information (PSI) across multicarrier THz channels for efficient channel code decoding. We map bits to transmission resources using shorter code-words to enhance parallelizability and reduce complexity. Additionally, we integrate channel state information into PSI to alleviate the processing overhead of soft decoding. Results demonstrate that PSI-aided decoding of 64-bit code-words halves the complexity of 128-bit hard decoding under comparable effective rates, while introducing a 4 dB gain at a block error rate. The proposed scheme approximates soft decoding with significant complexity reduction at a graceful performance cost.
Paper Structure (10 sections, 9 equations, 2 figures, 1 table, 1 algorithm)

This paper contains 10 sections, 9 equations, 2 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. System and channel models
  3. System model
  4. THz channel model
  5. Soft and pseudo-soft information
  6. Parallelizability and channel-code decoding
  7. Tbps candidate coding and decoding schemes
  8. Parallelism via short codes
  9. Simulation results
  10. Conclusions

Figures (2)

  • Figure 1: BLER versus SNR for hard, PSI-based, and soft decoding - ZF detection - BPSK modulation - SCL ($L=16$) and GRAND decoding of polar codes ($N=128$, $K=116$)/($N=64$, $K=57$) (solid/dotted lines) - frequency-selective THz channels.
  • Figure 2: Hard, PSI-based, and soft decoding - ZF detection - SCL ($L\!=\!16$) and GRAND decoding - polar codes ($N\!=\!64$, $K\!=\!57$) - BPSK and QPSK - frequency-selective indoor SV THz channel tarboush2021teramimo.