Channel Coding Scheme for 5G Mobile Communication System for Short Length Message Transmission

被引:26
作者
Hajiyat, Zahraa Raad Mayoof [1 ]
Sali, Aduwati [2 ]
Mokhtar, Makhfudzah [2 ]
Hashim, Fazirulhisyam [2 ]
机构
[1] Univ Putra Malaysia, Wireless Commun & Networks Engn, Fac Engn, Serdang 43400, Selangor, Malaysia
[2] Univ Putra Malaysia, Wireless & Photon Network Res Ctr WiPNET, Dept Comp & Commun Syst Engn, Fac Engn, Serdang 43400, Selangor, Malaysia
关键词
Channel coding scheme; 5G short length message; Convolutional; LDPC; Turbo; Polar; Machine-type communication; MACHINE-TYPE COMMUNICATIONS; CONVOLUTIONAL-CODES;
D O I
10.1007/s11277-019-06167-7
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Some channel coding schemes for 5G mobile communication system is facing difficulty in satisfying the user requirements in machine-type communication. This paper evaluates different channel coding schemes (LDPC, turbo, polar, systematic convolutional, and non-systematic convolutional codes) on an AWGN channel with BPSK modulation of code rate 1/2, in order to suggest the optimum channel coding scheme for the 5G mobile communication system for short length message transmission in machine-type communication. The analysis of the different channel coding schemes is based on flexibility, complexity, latency, and reliability according to the user requirements in machine-type communication. The main user requirements of machine-type communication for 5G channel coding scheme are better flexibility, low complexity, low latency, and high reliability in communication. Hence, the evaluation of different channel coding schemes is mainly based on satisfying user requirements in machine-type communication. The evaluation of the results shows that the systematic convolutional code is the optimum channel coding scheme in terms of better flexibility, low encoding computationallatency, and higher reliability for the 5G mobile communication system for short length message transmission (k1024 bits) in machine-type communication. Whereas, the polar code has the lowest decodingcomputational complexity.
引用
收藏
页码:377 / 400
页数:24
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