Energy consumption modeling and analysis for short-reach optical transmissions using irregular LDPC codes.

Area of Science:

• Optical Communications
• Error Correction Coding
• Energy Efficiency in Data Centers

Background:

• Increasing data rates in data centers necessitate advanced Forward Error Correction (FEC) for short-reach optical transmissions.
• Energy consumption of short-reach optical links is a growing concern due to the expansion of data centers.
• Quasi-Cyclic LDPC (QC-LDPC) codes offer a balance of error correction capability and hardware simplicity for these systems.

Purpose of the Study:

• To develop a comprehensive energy consumption model for short-reach optical transmission systems incorporating FEC.
• To analyze the energy efficiency of different QC-LDPC coding strategies against uncoded transmissions.
• To investigate the impact of optical transmitter power and channel characteristics on overall system energy consumption.

Main Methods:

• Analytical derivation of probability distributions for bit errors and flipping operations during irregular QC-LDPC decoding using density evolution.
• Integration of optical transmitter energy consumption and short-reach optical channel characteristics into existing LDPC decoding energy models.
• Post-layout circuit simulations to evaluate total system power for various QC-LDPC codes and decoders under different transmission scenarios.

Main Results:

• In short-range, slightly bandwidth-limited scenarios (e.g., 50Gbaud OOK, 25Gbaud PAM4), uncoded strategies are more energy-efficient than LDPC-coded ones.
• In severely band-limited cases requiring FEC (e.g., 70Gbaud OOK, 35Gbaud PAM4), a trade-off exists between transmitter and decoder energy consumption.
• Longer LDPC codes at similar rates consume less power due to superior error correction; a (19200, 15872) LDPC code with Gallager B decoder showed minimum power consumption overall.

Conclusions:

• The choice between coded and uncoded strategies for energy efficiency depends heavily on bandwidth limitations and transmission rates.
• Energy consumption modeling is critical for optimizing system design, as the optimal decoding algorithm varies with pre-BER.
• The study highlights the significant influence of the error correction threshold on LDPC decoder energy consumption, particularly in long-range scenarios.