RDN assisted signal detection for adaptively biased optical OTFS system

Area of Science:

• Optical Communications
• Signal Processing
• Atmospheric Physics

Background:

• Atmospheric turbulence severely impacts free-space optical (FSO) communication systems.
• Existing modulation schemes struggle to maintain reliable performance under these conditions.

Purpose of the Study:

• To introduce and evaluate an adaptively biased optical orthogonal time frequency space (ABO-OTFS) modulation scheme.
• To develop and assess a novel signal detection method for ABO-OTFS in turbulent FSO channels.

Main Methods:

• Theoretical derivation of closed-form average bit error rate (BER) expressions for ABO-OTFS under Málaga turbulence.
• Proposal and evaluation of a residual dense network (RDN) for signal detection.
• Comparison of RDN with maximum likelihood detection without channel state information.

Main Results:

• ABO-OTFS demonstrates superior BER performance compared to direct current biased optical OTFS.
• RDN-assisted detection achieves better BER performance than maximum likelihood at high signal-to-noise ratios under Málaga turbulence.
• The offline-trained RDN model shows feasibility and generalization in realistic FSO scenarios.

Conclusions:

• The proposed ABO-OTFS modulation scheme effectively mitigates atmospheric turbulence effects in FSO systems.
• RDN-based signal detection offers a promising approach for enhancing FSO communication reliability.
• The developed techniques are suitable for practical deployment in challenging atmospheric conditions.