University of Warwick Researchers Target Machine Learning (Machine-learning-based pilot symbol assisted channel prediction)

摘要

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on artificial intelligence are presented in a new report. According to news originating from the University of Warwick by NewsRx correspondents, research stated, “In this paper, machine learning (ML) algorithms are used for channel prediction in wireless communications.” The news correspondents obtained a quote from the research from University of Warwick: “The performances of five ML algorithms are compared in terms of the prediction accuracy and the symbol error rate (SER) of different modulation schemes based on the prediction. The result shows that, for channel prediction, support vector machine (SVM) has the best performance in terms of accuracy and stability. For signal detection, SVM and linear regression (LR) have their own advantages in different ranges of signal to noise ratio (SNR). At high constellation size, ML methods give similar performances to existing scheme. From the numerical examples, the SERs based on SVM and LR can both reach lower than 10-3 in binary phase shift keying and 16-ary quadrature amplitude modulation signalling, and can reach 1.13 × 10-2$ imes 10∧{-2}$ and 4.28 × 10-3$ imes 10∧{-3}$ in 16-ary phase shift keying signalling respectively.”