Active User Detection and Channel Estimation for Spatial-Based Random Access in Crowded Massive MIMO Systems via Blind Super-Resolution
Author:
Affiliation:
1. School of Electrical Engineering, Iran University of Science and Technology, Tehran, Iran
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/97/9686799/09751390.pdf?arnumber=9751390
Reference28 articles.
1. Covariance Based Joint Activity and Data Detection for Massive Random Access with Massive MIMO
2. Phase Transition Analysis for Covariance Based Massive Random Access with Massive MIMO
3. Improved Scaling Law for Activity Detection in Massive MIMO Systems
4. Sparse Signal Processing for Grant-Free Massive Connectivity: A Future Paradigm for Random Access Protocols in the Internet of Things
5. Massive MIMO Has Unlimited Capacity
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1. Uncoordinated Channel Tracking Algorithms and Their Stability in Practical Scenario for High-Rate IoT Devices With Massive MIMO;IEEE Transactions on Vehicular Technology;2024-06
2. Blind Asynchronous Goal-Oriented Detection for Massive Connectivity;2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt);2023-08-24
3. A novel blind spatial-based random access to pilots (BSB-RAP) in overloaded massive MIMO systems;Physical Communication;2023-04
4. Blind Goal-Oriented Massive Access for Future Wireless Networks;IEEE Transactions on Signal Processing;2023
5. Channel Estimation Based on Compressed Sensing for Massive MIMO Systems With Lens Antenna Array;IEEE Access;2023
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