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https://dspace.iiti.ac.in/handle/123456789/5952
Title: | Error Recovery Based Low-Complexity Detection for Uplink Massive MIMO Systems |
Authors: | Bhatia, Vimal |
Keywords: | Bit error rate;Computational complexity;Computer system recovery;Errors;MIMO systems;Recovery;Vectors;Estimated error;Initial estimate;Initial solution;Low-complexity detections;Massive multiple-input- multiple-output system (MIMO);Matrix inversions;Multiple iterations;New approaches;Error detection |
Issue Date: | 2017 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Citation: | Mandloi, M., & Bhatia, V. (2017). Error recovery based low-complexity detection for uplink massive MIMO systems. IEEE Wireless Communications Letters, 6(3), 302-305. doi:10.1109/LWC.2017.2677905 |
Abstract: | In this letter, we introduce a new approach based on error recovery for detection in uplink massive multiple-input multiple-output (MIMO) systems. In the proposed work, first, the non-sparse massive MIMO system is converted into a quasi-sparse error (i.e., error vector consists of a small fraction of significant elements) system by using a rough initial estimate of the transmitted symbol vector. Next, the error is estimated by a low-complexity error recovery technique which detects the error elements in an ordered pattern. Finally, to obtain the output symbol vector, the estimated error vector is combined with the initial solution vector. Furthermore, in order to enhance performance of the algorithm, multiple iterations of error recovery technique are performed. Simulation results reveal that the proposed algorithm outperforms the recently reported methods with approximately equal complexity. © 2012 IEEE. |
URI: | https://doi.org/10.1109/LWC.2017.2677905 https://dspace.iiti.ac.in/handle/123456789/5952 |
ISSN: | 2162-2337 |
Type of Material: | Journal Article |
Appears in Collections: | Department of Electrical Engineering |
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