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—In a cooperative broadcast scenario, a group of nodes in a network aims to reconstruct a common message. In this paper, we present a new algorithm for distributed consensus-based estimation in such scenarios. Possible applications comprise mobile communication systems and sensor networks. Starting with a least squares estimation problem, the algorithm is(More)
—A possible future application in communications is the wireless uplink transmission in sensor networks. This application is mainly characterized by sporadic transmission over a random access channel. Since each sensor has a low activity probability, the signal for MultiUser Detection (MUD) is sparse. Compressive Sensing (CS) theory introduces detectors(More)
With the expected growth of Machine-to-Machine (M2M) communication, new requirements for future communication systems have to be considered. More specifically, the sporadic nature of M2M communication, low data rates, small packets and a large number of nodes necessitate low overhead communication schemes that do not require extended control signaling for(More)
—One challenging future application in digital communications is the wireless uplink transmission in sensor networks. This application is characterized by sporadic transmissions by a large number of sensors over a random multiple access channel. To reduce control signaling overhead, we propose that sensors do not transmit their activity states; instead(More)
—The growing field of Machine-to-Machine communication requires new physical layer concepts to meet future requirements. In previous works it has been shown for a synchronous CDMA transmission that Compressive Sensing (CS) detectors are capable of jointly detecting both activity and data in multiuser detection (MUD). However, many practical applications(More)
—In dense mobile network deployments, the cooperation of base stations in the uplink promises performance gains w.r.t. area throughput and power efficiency. In this paper, we propose the use of a distributed consensus-based estimation algorithm for the linear equalization of multiple user signals occupying the same resources. We will show that using an(More)
—The application of Compresses Sensing is a promising physical layer technology for the joint activity and data detection of signals. Detecting the activity pattern correctly has severe impact on the system performance and is therefore of major concern. In contrast to previous work, in this paper we optimize joint activity and data detection in(More)