A blind detection method for underwater visible light communication system
A visible light communication and blind detection technology, applied in baseband systems, transmission systems, digital transmission systems, etc., can solve problems such as poor detection performance and limited application scenarios, and achieve enhanced interpretability and predictability, and improved spectrum Efficiency, the effect of improving BER performance
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Embodiment 1
[0071] Such as figure 1 As shown, a blind detection method for an underwater visible light communication system includes the following steps:
[0072] S1: Build a UVLC system for OOFDM modulation and communicate through UVLC channels;
[0073] S2: The transmitting end of the UVLC system performs baseband signal modulation and amplitude limiting to obtain time-domain transmitting signals;
[0074] S3: Modeling the channel impulse response CIR of the UVLC system during the transmission of the time-domain transmit signal through the UVLC channel;
[0075] S4: According to the modeling result, establish a frequency domain baseband signal transmission model;
[0076] S5: The receiving end of the UVLC system performs blind detection on the frequency domain baseband signal transmission model based on the neural network BDNet;
[0077] Among them, OOFDM means optical orthogonal frequency division multiplexing; UVLC means underwater visible light communication.
[0078] In the spec...
Embodiment 2
[0125] In order to more fully illustrate the beneficial effects of the present invention, the effectiveness and advancement of the present invention will be further described below in combination with the simulation analysis and results of a specific embodiment.
[0126] First, DCO-OFDM is selected as the OOFDM scheme of this embodiment. In the DCO-OFDM system, one frame contains 100 OOFDM symbols, the number of subcarriers K is 64, the bandwidth is 500MHz, and the modulation method is 16-QAM. In the deep blind channel estimation unit, the number of convolutional layers is set to 12. Table 1 lists the main parameters of the simulation.
[0127] Table 1: Simulation main parameter table
[0128]
[0129] Among them, the literature [7] is D.P.Kingma and J.L.Ba, "Adam: a method for stochastic optimization," in Proceedings of International Conference for Learning Representations (ICLR), San Diego, USA, 7-9May 2015.
[0130] Figure 5 Comparing different detection schemes in ...
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