Publication | Closed Access
Sparsity Aware Multiuser detection for Machine to Machine communication
29
Citations
12
References
2012
Year
Unknown Venue
Cluster ComputingEngineeringIot CommunicationMachine To MachineM2m CommunicationInternet Of ThingsActivity DetectionData CommunicationComputer ScienceMobile ComputingIot Data ManagementMulti-user DetectionSignal ProcessingJoint ActivityEdge ComputingCloud ComputingMachine-to-machine CommunicationNetwork Traffic MeasurementNetwork MonitoringMachine Communication
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.
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