TY - GEN
T1 - Precoding Design of Reconfigurable Massive MIMO in the Electromagnetic Domain
AU - Ying, Keke
AU - Gao, Zhen
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Reconfigurable massive multiple-input multiple-output (RmMIMO) is expected to unlock the unexplored degrees of freedom in the electromagnetic (EM) domain, offering more flexibility to the design of communication systems. Specifically, optimizing the delicate EM properties such as radiation pattern depends on detailed domain knowledge. Traditional spatial domain channel state information (sCSI) has obscured the underlying EM domain information of the channel, thereby hindering the base station's efforts in exploring the EM properties of the channel for precoding optimization. This paper exploits the detailed EM domain channel state information (eCSI) for radiation pattern design at the base station. Using the orthogonal decomposition method on the spherical harmonics bases, the radiation pattern is decomposed into the linear combination of these orthogonal bases. We then formulate the pattern design problem as a problem of optimizing projection coefficients on these bases. Specifically, we propose a manifold optimization-based method that can alternatively optimize the radiation pattern design and the digital precoder. Simulation results demonstrate that, in comparison to traditional mMIMO systems with fixed antenna radiation patterns, RmMIMO architecture induces significant throughput gain for downlink transmission.
AB - Reconfigurable massive multiple-input multiple-output (RmMIMO) is expected to unlock the unexplored degrees of freedom in the electromagnetic (EM) domain, offering more flexibility to the design of communication systems. Specifically, optimizing the delicate EM properties such as radiation pattern depends on detailed domain knowledge. Traditional spatial domain channel state information (sCSI) has obscured the underlying EM domain information of the channel, thereby hindering the base station's efforts in exploring the EM properties of the channel for precoding optimization. This paper exploits the detailed EM domain channel state information (eCSI) for radiation pattern design at the base station. Using the orthogonal decomposition method on the spherical harmonics bases, the radiation pattern is decomposed into the linear combination of these orthogonal bases. We then formulate the pattern design problem as a problem of optimizing projection coefficients on these bases. Specifically, we propose a manifold optimization-based method that can alternatively optimize the radiation pattern design and the digital precoder. Simulation results demonstrate that, in comparison to traditional mMIMO systems with fixed antenna radiation patterns, RmMIMO architecture induces significant throughput gain for downlink transmission.
KW - Electromagnetic domain
KW - manifold optimization
KW - precoding
KW - radiation pattern
KW - reconfigurable massive MIMO
UR - http://www.scopus.com/inward/record.url?scp=85187369148&partnerID=8YFLogxK
U2 - 10.1109/GLOBECOM54140.2023.10437841
DO - 10.1109/GLOBECOM54140.2023.10437841
M3 - Conference contribution
AN - SCOPUS:85187369148
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 5769
EP - 5774
BT - GLOBECOM 2023 - 2023 IEEE Global Communications Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE Global Communications Conference, GLOBECOM 2023
Y2 - 4 December 2023 through 8 December 2023
ER -