DocumentCode
3535420
Title
Sparsity Aware Multiuser detection for Machine to Machine communication
Author
Monsees, F. ; Bockelmann, C. ; Wubben, Dirk ; Dekorsy, Armin
Author_Institution
Dept. of Commun. Eng., Univ. of Bremen, Bremen, Germany
fYear
2012
fDate
3-7 Dec. 2012
Firstpage
1706
Lastpage
1711
Abstract
With the expected growth of Machine-to-Machine (M2M) communication, new requirements for future communication systems have to be considered. Traffic patterns in M2M communication fundamentally differ from human based communication. Especially packets in M2M are rather small and transmitted sporadically only. Moreover, nodes for M2M communication are often of reduced functionality which makes complex control overhead or resource management infeasible for such devices. Assuming a star-topology with a central aggregation node that processes all node information one possibility to reduce control signaling is to shift the activity detection fully to the central aggregation node. The methodology of a joint activity and data detection differs strongly from common communication scenarios since errors during the activity detection are fundamentally different from errors made at data detection. In this paper we introduce a non-linear joint activity and data detector for M2M communication. The performance regarding data and activity errors is assessed and compared to a scenario where node activity is known by the aggregation node.
Keywords
multiuser detection; telecommunication network management; telecommunication network topology; M2M communication; activity detection; central aggregation node; complex control overhead; control signaling; data detection; human based communication; machine to machine communication; node activity; nonlinear joint activity; resource management; sparsity aware multiuser detection; star topology; Covariance matrix; Detectors; Joints; Multiaccess communication; Signal to noise ratio; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Globecom Workshops (GC Wkshps), 2012 IEEE
Conference_Location
Anaheim, CA
Print_ISBN
978-1-4673-4942-0
Electronic_ISBN
978-1-4673-4940-6
Type
conf
DOI
10.1109/GLOCOMW.2012.6477842
Filename
6477842
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