Double Intelligent Reflecting Surface-Assisted Multi-User MIMO Mmwave Systems with Hybrid Precoding

Hehao Niu, Zheng Chu, Fuhui Zhou, Cunhua Pan, Derrick Wing Kwan Ng, Huan X. Nguyen

Research output: Journal PublicationArticlepeer-review

22 Citations (Scopus)


This work investigates the effect of double intelligent reflecting surface (IRS) in improving the spectrum efficient of multi-user multiple-input multiple-output (MIMO) network operating in the millimeter wave (mmWave) band. Specifically, we aim to solve a weighted sum rate maximization problem by jointly optimizing the digital precoding at the transmitter and the analog phase shifters at the IRS, subject to the minimum achievable rate constraint. To facilitate the design of an efficient solution, we first reformulate the original problem into a tractable one by exploiting the majorization-minimization (MM) method. Then, a block coordinate descent (BCD) method is proposed to obtain a suboptimal solution, where the precoding matrices and the phase shifters are alternately optimized. Specifically, the digital precoding matrix design problem is solved by the quadratically constrained quadratic programming (QCQP), while the analog phase shift optimization is solved by the Riemannian manifold optimization (RMO). The convergence and computational complexity are analyzed. Finally, simulation results are provided to verify the performance of the proposed design, as well as the effectiveness of double-IRS in improving the spectral efficiency.

Original languageEnglish
Pages (from-to)1575-1587
Number of pages13
JournalIEEE Transactions on Vehicular Technology
Issue number2
Publication statusPublished - 1 Feb 2022
Externally publishedYes


  • hybrid precoding
  • Intelligent reflecting surface
  • majorization-minimization
  • mmWave communications
  • Riemannian manifold optimization

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics


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