A Channel Quality Indicator (CQI) Prediction Scheme Using Feed Forward Neural Network (FT-NN) technique for MU-MIMO LTE System

被引：0

作者：

Abdulhasan, Muntadher Qasim ^{[1
]}

Salman, Mustafa Ismael ^{[1
]}

Ng, Chee Kyun ^{[1
,2
]}

Noordin, Nor Kamariah ^{[1
]}

Hashim, Shaiful Jahari ^{[1
]}

Bin Hashim, Fazirulhisham ^{[1
]}

机构：

[1] Univ Putra Malaysia, Fac Engn, Dept Comp & Commun Syst Engn, Upm Serdang 43400, Selangor, Malaysia

[2] Univ Putra Malaysia, Inst Gerontol, Upm Serdang 43400, Selangor, Malaysia

来源：

2014 IEEE 2ND INTERNATIONAL SYMPOSIUM ON TELECOMMUNICATION TECHNOLOGIES (ISTT) | 2014年

关键词：

CQI feedback LTE; Feed Forward Neural; Network techniqe; MU-MIMO;

D O I：

暂无

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

In Multi User-Multiple-in Multiple-Out - Long Term Evolution (MU-MIMO-LTE) networks, Channel Quality indicator (CQI) plays a vital role. CQI is crucial in describing the channel information to assign appropriate modulation and coding scheme (MCS). However, obtaining CQI values for each transmission time interval (TTI) inevitably entails use and can lead to an undesirable degradation in spectral efficiency (SE) as well as increasing the error rate. Therefore, providing an accurate and reliable CQI with low overhead is an intricate task. In this paper, a CQI prediction scheme using Feed Forward Neural Network (FF-NN) algorithm for MU-MIMO-LTE Advanced systems is proposed. Initially, a channel model for MU-MIMO-LTE advanced network is carried out. Through this model, CQI is predicted and the obtained values are compressed using a feedback compression technique. Finally, the proposed technique makes use of FF-NN algorithm to train and achieve enhanced CQI values. Further, an enhanced and accurate CQI values are acquired. Results show that the system SE of single user (SU)-MIMO proportionally increases with the SNR values at the cost of BER. Therefore, a MU-MIMO CQI prediction scheme is recommended to improve the tradeoff between BER and SE.

引用

页码：17 / 22

页数：6