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Activity Detection for Massive Random Access using Covariance-based Matching Pursuit
The Internet of Things paradigm heavily relies on a network of a massive number of machine-type devices (MTDs) that monitor changes in various phenomena.
Joint Activity Detection and Channel Estimation for Clustered Massive Machine Type Communications
Compressed sensing multi-user detection (CS-MUD) algorithms play a key role in optimizing grant-free (GF) non-orthogonal multiple access (NOMA) for massive machine-type communications (mMTC).
Joint Coherent and Non-Coherent Detection and Decoding Techniques for Heterogeneous Networks
Cellular networks that are traditionally designed for human-type communication (HTC) have the potential to provide cost effective connectivity to machine-type communication (MTC).
User Activity Detection and Channel Estimation of Spatially Correlated Channels via AMP in Massive MTC
This paper addresses the problem of joint user identification and channel estimation (JUICE) for grant-free access in massive machine-type communications (mMTC).
Joint Channel Estimation and Device Activity Detection in Heterogeneous Networks
Internet of Things (IoT) has triggered a rapid increase in the number of connected devices and new use cases of wireless communications.
