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Found 10 papers, 0 papers with code
Low-Complexity Near-Field Channel Estimation for Hybrid RIS Assisted Systems
We investigate the channel estimation (CE) problem for hybrid RIS assisted systems and focus on the near-field (NF) regime.
Device Detection and Channel Estimation in MTC with Correlated Activity Pattern
This paper provides a solution for the activity detection and channel estimation problem in grant-free access with correlated device activity patterns.
Hierarchical MTC User Activity Detection and Channel Estimation with Unknown Spatial Covariance
To solve the JUICE problem, we first leverage the concept of strong priors and propose a hierarchical-sparsity-inducing spike-and-slab prior to model the structured sparse activity pattern.
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 Estimation of Clustered User Activity and Correlated Channels with Unknown Covariance in mMTC
This paper considers joint user identification and channel estimation (JUICE) in grant-free access with a \emph{clustered} user activity pattern.
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).
Spatial Correlation Aware Compressed Sensing for User Activity Detection and Channel Estimation in Massive MTC
First, for the case without prior information, we formulate the JUICE as an iterative reweighted $\ell_{2, 1}$-norm minimization problem.
Iterative Reweighted Algorithms for Joint User Identification and Channel Estimation in Spatially Correlated Massive MTC
Joint user identification and channel estimation (JUICE) is a main challenge in grant-free massive machine-type communications (mMTC).
An IoT-Based Framework for Remote Fall Monitoring
Fall detection is a serious healthcare issue that needs to be solved.
