The Compatible Partial Response Maximum Likelihood Detection Schemes for Blu-ray Discs

The global datasphere is experiencing significant expansion, largely driven by the relentless advancement of artificial intelligence technology. Cold data, in particular, is garnering increasing attention and is now considered a vital asset, constituting a substantial portion of data capacity. Optical discs stand out as a highly promising solution for cold data archiving due to their robust data security, longevity, durability, and non-volatile nature. Additionally, their total cost of operation (TCO) further enhances their appeal. To increase the recording density, signal processing techniques must evolve along with the degradation of signal quality. In this paper, we conduct a comprehensive study of partial response maximum likelihood (PRML) detection based on simulation and real signal testing and compare an adaptive equalized detection scheme with a neural network equalized detection method for BD-ROM and BDXL systems. Results show the effectiveness of PRML method for both BD-ROM and BDXL. The neural network equalized detection method can also improve the detection performance of BD-ROM and BDXL at lower signal-to-noise ratio (SNR) levels.