Zhao, Y., Xu, J., Xu, W., Wang, K., Ye, X., Yuen, C., & You, X. (2024). Joint MIMO Transceiver and Reflector Design for Reconfigurable Intelligent Surface-Assisted Communication. IEEE Transactions on Vehicular Technology, 73(10), 15061–15075. https://doi.org/10.1109/tvt.2024.3406199
Abstract:
In this paper, we consider a reconfigurable intelligent
surface (RIS)-assisted multiple-input multiple-output communication
system with multiple antennas at both the base station (BS) and
the user. We plan to maximize the achievable rate through jointly
optimizing the transmit precoding matrix, the receive combining
matrix, and the RIS reflection matrix under the constraints of the
transmit power at theBS and the unit-modulus reflection at the RIS.
Regarding the non-trivial problem form, we initially reformulate
it into an considerable problem to make it tractable by utilizing
the relationship between the achievable rate and the weightedminimum
mean squared error. Next, the transmit precoding matrix,
the receive combining matrix, and the RIS reflection matrix are
alternately optimized. In particular, the optimal transmit precoding
matrix and receive combining matrix are obtained in closed
forms. Furthermore, a pair of computationally efficient methods
are proposed for theRIS reflectionmatrix, namely the semi-definite
relaxation (SDR) method and the successive closed form (SCF)
method. We theoretically prove that both methods are ensured to
converge, and the SCF-based algorithm is able to converges to a
Karush-Kuhn-Tucker point of the problem.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the National Key Research and Development Program - NA
Grant Reference no. : 2020YFB1806608
This research / project is supported by the Fundamental Research Funds for the Central Universities - NA
Grant Reference no. : 2242022k60002, 2242023K5003
This research / project is supported by the Research Fund of National Mobile Communications Research Laboratory, Southeast University - NA
Grant Reference no. : 2024A03
This research / project is supported by the ZTE Industry-University-Institute Cooperation Funds - NA
Grant Reference no. : IA20240319003
This research / project is supported by the Ministry of Education, Singapore - Academic Research Fund Tier 2
Grant Reference no. : MOE-T2EP50220-0019
This research / project is supported by the Science and Engineering Research Council of A*STAR (Agency for Science, Technology and Research) Singapore - Manufacturing, Trade, and Connectivity Programmatic Fund
Grant Reference no. : M22L1b0110