Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface: Discrete Phase Shift and Progressive Refinement

By Changsheng You, Beixiong Zheng, Rui Zhang. IEEE Journal on Selected Areas in Communications, 2019

371 citations recorded by the source corpus.

Prior studies on intelligent reflecting surface (IRS) have mostly assumed perfect channel state information (CSI) available for designing the IRS passive beamforming as well as the continuously adjustable phase shift at each of its reflecting elements, which, however, have simplified two challenging issues for implementing IRS in practice, namely, its channel estimation and passive beamforming designs both under the constraint of discrete phase shifts. To address them, we consider in this paper an IRS-aided single-user communication system and design the IRS training reflection matrix for channel estimation as well as the passive beamforming for data transmission, both subject to the new constraint of discrete phase shifts. We show that the training reflection matrix design with discrete phase shifts greatly differs from that with continuous phase shifts, and the corresponding passive beamforming design should take into account the correlated IRS channel estimation errors due to discrete phase shifts. Moreover, a novel hierarchical training reflection design is proposed to progressively estimate IRS elements’ channels over multiple time blocks by exploiting the IRS-elements grouping and partition. Based on the resolved IRS channels in each block, we further design the progressive passive beamforming at the IRS with discrete phase shifts to improve the achievable rate for data transmission over the blocks. Extensive numerical results are presented, which demonstrate the significant performance improvement of proposed channel estimation and passive beamforming designs as compared to various benchmark schemes.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/1293ac62d5ca6c395422ab4419d92c1c6ad0c8d6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

1. Rui Zhang
2. Yuanwei Liu
3. Qingqing Wu
4. M. Di Renzo
5. Merouane Debbah
6. Robert Schober
7. Mohamed-Slim Alouini
8. Chau Yuen

In Electrical and Electronic Engineering

1. Rui Zhang
2. Yuanwei Liu
3. Merouane Debbah
4. M. Di Renzo
5. Qingqing Wu
6. Chau Yuen
7. Robert Schober
8. Xidong Mu

In Ocean Engineering

1. Rui Zhang
2. Qingqing Wu
3. Changsheng You
4. Yuanwei Liu
5. Xidong Mu
6. Beixiong Zheng
7. Robert Schober
8. Chau Yuen

Citations in the corpus

• Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, background): “In [104], the authors propose a hierarchical training reflection design for progressively estimating the channels based on an RIS-elements grouping and partition method.”
• Simultaneously Transmitting And Reflecting (STAR) RIS Aided Wireless Communications (2021, methodology): “(2)Based on the TS protocol, the CSI of the T and R users can be consecutively estimated using channel acquisition methods recently proposed for conventional RISs [25, 26].”
• Reconfigurable Intelligent Surfaces for Wireless Communications: Overview of Hardware Designs, Channel Models, and Estimation Techniques (2022, background): “Similarly, a novel hierarchical training reflection design is proposed in [142] to progressively estimate the RIS-empowered channels”
• A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications (2021, methodology): “IRS channel estimation • Near-orthogonal IRS training reflection design subject to the discrete phase-shift constraint in narrowband system [106], [107] • Cascaded channel estimation accounting for discrete phase-shift model in broadband system [112] • ON/OFF training reflection pattern [34], [54] I”
• Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization (2019, background): “In the literature, there are some recent works that studied the channel estimation problem for IRS-aided wireless systems [14], [15], [21], [25], [26].”
• Exploiting Intelligent Reflecting Surfaces in NOMA Networks: Joint Beamforming Optimization (2019, methodology): “1The involved CSI can be efficiently obtained by the recently proposed channel estimation techniques for IRS-aided systems [32], [43].”
• Reconfigurable Intelligent Surfaces: Principles and Opportunities (2020, methodology): “[66] proposed a discrete phase shifts model for a MISO assisted RIS network.”