K-means non-uniform quantization algorithm for filter bank multi-carrier modulation optical communication system

Abstract

The invention provides a K-means non-uniform quantization algorithm for filter bank multi-carrier modulation optical communication system. The K-means non-uniform quantization algorithm comprises thefollowing steps: step 1, inputting a data sequence sent by a filter bank multi-carrier modulation transmitter into a data preprocessing module, and taking a generated vector as the input of a K-meansquantization module; 2, selecting K vectors as an initial quantization order, calculating the distance between each vector and a quantization order vector, clustering each vector into a set of quantization order vectors with the minimum distance according to the distance, and calculating a quantization interval and a central vector of each quantization interval; step 3, taking the center vector generated in the step 2 as an initial quantization order of distance calculation, and iterating the step 2 until convergence to obtain K quantization intervals and center vectors; and 4, outputting thequantization interval and the central vector obtained in the step 3 to obtain a quantization result. The K-means non-uniform quantization algorithm reduces the quantization error of the system, improves the bit error rate performance of the system, and saves the cost.

Description

technical field [0001] The invention relates to a K-means non-uniform quantization algorithm used in a filter bank multi-carrier modulation optical communication system. Background technique [0002] In recent years, with the emergence of emerging technologies such as machine learning, social networking, and cloud computing, the demand for traffic throughput and bandwidth is also growing rapidly, which puts forward higher requirements for optical transmission networks with high spectral efficiency and low cost. Intensity modulation direct detection technology based on multi-carrier modulation technology is favored in short-distance optical fiber links due to its simple implementation and low complexity. However, compared to traditional multicarrier modulation techniques such as Orthogonal Frequency Division Multiplexing (OFDM), filter bank based multicarrier modulation signals include filter bank based multicarrier (FBMC), universal filter multicarrier (UFMC ), etc., have b...

AI Technical Summary

Problems solved by technology

However, the non-parametric estimation histogram method requires a large number of samples, and the computational complexity and storage complexity are relatively large, and it is only suitable for low-dimensional data. When the dimension increases, the space required for the histogram will increase as the dimension increases. Exponential increase

Therefore, there is still room for improvement in the quantization order optimization determination algorithm.

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