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- W2794861931 abstract "Massive machine-to-machine (M2M) is an important application for Internet of Things in 5G. In this letter, we focus on solving the multiuser detection problem supported by low-activity code division multiple access for M2M communications. To address the user activity factor unknown issue in the optimal maximum a posterior probability and improve the signal reconstruction ability, we propose iterative reweighed and minimum mean-square-error iterative reweighed algorithms based on compressive sensing theory. The simulation results demonstrate that the proposed algorithms achieve substantial performance gain over traditional detectors." @default.
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- W2794861931 date "2018-10-01" @default.
- W2794861931 modified "2023-10-16" @default.
- W2794861931 title "Compressive Sensing-Based Multiuser Detection via Iterative Reweighed Approach in M2M Communications" @default.
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- W2794861931 doi "https://doi.org/10.1109/lwc.2018.2820704" @default.
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