2021/10/31 by Zhaorui Wang, Ya-Feng Liu, Ya‐Feng Liu +1
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Algorithm #Asynchronous communication #Base station #Channel (broadcasting) #Computer science #Coordinate descent #Covariance #Covariance intersection #Covariance matrix #Energy Harvesting in Wireless Networks #Engineering #Estimation of covariance matrices #IoT Networks and Protocols #Joint (building) #Mathematical optimization #Mathematics #Preamble #Real-time computing #Statistics #Telecommunications #cs.IT #eess.SP #math.IT
paper · pdf · doi:10.1109/lsp.2022.3144853
Accepted by IEEE SPL
openalex created_date 2021/10/25 · openalex publication_date 2022/01/01 · arxiv created 2022/01/14 · arxiv updated 2022/03/02 · openalex updated_date 2026/08/05
In this letter, we study the joint device activity and delay detection problem in asynchronous massive machine-type communications (mMTC), where all active devices asynchronously transmit their preassigned preamble sequences to the base station (BS) for device identification and delay detection. We first formulate this joint detection problem as a maximum likelihood estimation problem, which depends on the received signal only through its sample covariance, and then propose efficient coordinate descent type of algorithms to solve the formulated problem. Our proposed covariance-based approach is sharply different from the existing compressed sensing (CS) approach for the same problem. Numerical results show that our proposed covariance-based approach significantly outperforms the CS approach in terms of the detection performance since our proposed approach can make better use of the BS antennas than the CS approach.