研究目的
To develop a generalized likelihood block detection (GLBD) receiver for practical SPAD-based underwater VLC systems to detect data sequences without prior knowledge of the channel and background radiation, and to propose a fast search algorithm to reduce computational complexity.
研究成果
The GLBD receiver outperforms the existing MSD receiver in robustness and efficiency, achieving BER performance closer to the low bound with sufficient sequence length. The fast search algorithm reduces computational complexity without performance loss. Block coding schemes effectively eliminate the error floor. Future work will explore MIMO SPAD-based systems.
研究不足
The study is based on simulations and may not account for all real-world variations. The GLBD receiver requires at least one symbol in the transmitted data sequence and cannot distinguish all-zero or all-one sequences, leading to an error floor that is mitigated by block coding. Computational complexity, though reduced by the fast algorithm, may still be high for very long sequences.
1：Experimental Design and Method Selection:
The study uses Monte-Carlo simulations to evaluate the BER performance of the proposed GLBD receiver under various turbulence conditions. The system model includes an underwater VLC system with SPAD detectors, OOK modulation, and log-normal fading channels. Theoretical models for photon counting with dead time and generalized likelihood ratio detection are employed.
2：Sample Selection and Data Sources:
Simulations are conducted with parameters such as wavelength, dead time, dark count, light speed in water, and photon detection efficiency as specified in Table I. Data is generated synthetically based on these parameters.
3：List of Experimental Equipment and Materials:
No specific physical equipment is mentioned; the study is simulation-based using computational tools.
4：Experimental Procedures and Operational Workflow:
The simulation involves generating signal sequences, applying turbulence effects, implementing the GLBD and MSD receivers, and calculating BER. The fast search algorithm is applied to reduce complexity.
5：Data Analysis Methods:
BER is calculated and compared across different receivers and conditions. The analysis includes performance under varying sequence lengths, turbulence strengths, and symbol rates.
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