Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2013, Vol. 36 ›› Issue (6): 45-49.doi: 10.13190/j.jbupt.2013.06.010

• Papers • Previous Articles     Next Articles

A LTE Downlink Scheduling Based on CQI Predicted by Neural Network

WU Bin1, MI Zheng-kun1, WANG Wen-nai1, LU Yuan-chen2, ZHU Ze-wen1   

  1. 1. Key Laboratory of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education, Nanjing 210003, China;
    2. Huawei Software Technologies Company Limited, Nanjing 210012, China
  • Received:2013-06-19 Online:2013-12-31 Published:2013-10-08

Abstract:

Using the available outdated channel quality indicator (CQI), an optimized long term evolution downlink resource allocation method is proposed. The key is a neural network based on CQI prediction model and algorithm, which can predict the current CQI from the outdated CQIs. The scheduler uses the predicted CQI to allocate radio resources and decide on proper modulation and coding scheme. Simulation shows that the proposed prediction model and algorithm have practical effects on solving the degradation of scheduling efficiency due to the outdated CQI.

Key words: 3GPP long term evolution, radio resource scheduling, channel quality indicator prediction, neural network

CLC Number: