Linear Complexity ZF-based linear precoder for massive-MIMO Systems

Shafivulla, Sayyed and Patel, Aaqib (2021) Linear Complexity ZF-based linear precoder for massive-MIMO Systems. In: 26th IEEE International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2021, 25 October 2021 through 27 October 2021, Porto.

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The precoding of the downlink-transmit symbol vector in a massive multiple input multiple output (m-MIMO) system has seen numerous linear precoding schemes. When the base station (BS) has ideal channel state information (CSI), techniques such as maximum ratio transmission (MRT) and zero-forcing (ZF) are used. For Rayleigh fading, the sumrate of the ZF precoding scheme is significantly higher than that of the MRT precoding technique due to interference mitigation. However, the ZF precoding scheme requires computing the inverse of the transpose of the channel's Gram matrix, which has significant complexity compared to the MRT precoding scheme. To reduce this complexity and simultaneously achieve the best sumrate, we propose a novel technique that modifies the ZF precoding using Decentralized pre-processing and recently proposed Cayley-Hamilton Theorem with Unit Eigenvalue (CHTUE) and Cayley-Hamilton Theorem with maximum Eigenvalue (CHTME) based inverse approximation. Simulations show that the proposed method's sumrate is much better than the MRT precoder and near ZF precoder, while the computational complexity is significantly low. © 2021 IEEE.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Conference or Workshop Item (Paper)
Additional Information: This publication is an outcome of the R&D work under the DST INSPIRE faculty fellowship, DST, Government of India.
Uncontrolled Keywords: Complexity; massive Multiple-Input Multiple-Output (m-MIMO); maximum ratio transmission (MRT); Zero-Forcing(ZF)
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 03 Sep 2022 10:18
Last Modified: 03 Sep 2022 10:18
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