Paper Info
Title
Aggregation transmission scheme for machine type communications.
Abstract
Massive amount of small data generated by machine type communications (MTC) will pose a challenge to the future fifth generation (5G) wireless network. Since the information from or to the machine type users aggregating closely are highly correlated, the relevance of data can be excavated by big data analysis to help improve the spectral efficiency. In this paper we proposed an aggregation transmission scheme (ATS) for MTC downlink transmissions in which the transmission order of users’ data packets can be adjusted according to their relevance under the delay constraints. The users having relevance will temporally share the time slots and their data are transmitted in a multicast way so that much less timeslots are needed. We propose three different algorithms, conditional random search (CRS), standard-row algorithm (SRA), and genetic algorithm (GA) to tackle the problem of transmission order adjustment. Simulation results validate the good performance of ATS and demonstrate that SRA has the lowest complexity while GA may achieve a better performance. We also analyze the impact of different delay requirements. Our work sheds light on dealing with massive MTC data traffic for future wireless communications.
Year
DOI
Venue
2017
10.1007/s11432-017-9196-0
SCIENCE CHINA Information Sciences
Keywords
Field
DocType
machine type communications, aggregation transmission scheme, delay tolerance, genetic algorithm, big data
Wireless network,Wireless,Small data,Network packet,Real-time computing,Spectral efficiency,Multicast,Mathematics,Genetic algorithm,Telecommunications link
Journal
Volume
Issue
ISSN
60
10
1674-733X
Citations 
PageRank 
References 
1
0.34
11
Authors
6
Name
Order
Citations
PageRank
Yanhuan Sun111.02
Ming Zhao2469.53
Sihai Zhang36319.50
Jinkang Zhu413.05
Wuyang Zhou522647.51
Shengli Zhou63909262.81