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49,80 €ISBN 978-3-8440-5877-2Softcover214 pages63 figures318 g21 x 14,8 cmEnglishThesis
April 2018
Fabian Monsees
Signal Processing for Compressed Sensing Multiuser Detection
The era of human based communication was longly believed to be the main driver for the development of communication systems. Already nowadays we observe that other types of communication impact the discussions of how future communication system will look like. One emerging technology in this direction is machine to machine (M2M) communication. M2M addresses the communication between autonomous entities without human interaction in mind.
A very challenging aspect is the fact that M2M strongly differ from what communication system were designed for. Compared to human based communication, M2M is often characterized by small and sporadic uplink transmissions with limited data-rate constraints.
Within this thesis physical layer concepts are introduced for a novel medium access technology tailored to the demands of M2M. This concept combines advances from the field of sporadic signal processing and communications. The main idea is to exploit the sporadic structure of the M2M traffic to design physical layer algorithms utilizing this side information. This concept is known as Compressed Sensing Multiuser Detection (CS-MUD).
A very challenging aspect is the fact that M2M strongly differ from what communication system were designed for. Compared to human based communication, M2M is often characterized by small and sporadic uplink transmissions with limited data-rate constraints.
Within this thesis physical layer concepts are introduced for a novel medium access technology tailored to the demands of M2M. This concept combines advances from the field of sporadic signal processing and communications. The main idea is to exploit the sporadic structure of the M2M traffic to design physical layer algorithms utilizing this side information. This concept is known as Compressed Sensing Multiuser Detection (CS-MUD).
Keywords: Signal Processing; Compressed Sensing; Multiuser Detection; Machine to Machine Communication; Machine Type Communication; Bayesian Inference
Dissertationen aus dem Arbeitsbereich Nachrichtentechnik der Universität Bremen
Edited by Prof. Dr.-Ing. Armin Dekorsy, Bremen
Volume 5
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