Differential AR algorithm for packet delay prediction

Different delay prediction algorithms have been applied in multimedia communication, among which linear prediction is attractive because of its low complexity. AR (auto regressive) algorithm is a traditional one with low computation cost, while NLMS (normalize least mean square) algorithm is more precise. In this paper, referring to ARIMA (auto regression integrated with moving averages) model, a differential AR algorithm (DIAR) is proposed based on the analyses of both AR and NLMS algorithms. The prediction precision of the new algorithm is about 5-10 db higher than that of the AR algorithm without increasing the computation complexity.Compared with NLMS algorithm, its precision slightly improves by 0.1 db on average, but the algorithm complexity reduces more than 90%. Our simulation and tests also demonstrate that this method improves the performance of the average end-to-end delay and packet loss ratio significantly.

作 者： JIAO Liangbao ZHANG De BI Houjie   作者單位： JIAO Liangbao,ZHANG De(Institute of Acoustics, State Key Laboratory of Modem Acoustics, Nanjing University, Nanjing 210093, China;Institute of Communication Technique, Nanjing University, Nanjing 210093, China)

BI Houjie(Institute of Communication Technique, Nanjing University, Nanjing 210093, China) 

刊 名： 自然科學(xué)進(jìn)展（英文版）  SCI 英文刊名： PROGRESS IN NATURAL SCIENCE  年，卷(期)： 2006 16(4)  分類號(hào)： O1  關(guān)鍵詞： AR algorithm   NLMS algorithm   differential AR algorithm   ARIMA model  

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