Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMO

By Zhen-Qing He, Xiaojun Yuan. IEEE Wireless Communications Letters, 2019

721 citations recorded by the source corpus.

In this letter, we consider the problem of channel estimation for large intelligent metasurface (LIM) assisted massive multiple-input multiple-output (MIMO) systems. The main challenge of this problem is that the LIM integrated with a large number of low-cost metamaterial antennas can only passively reflect the incident signals by certain phase shifts, and does not have any signal processing capability. To deal with this, we introduce a general framework for the estimation of the transmitter-LIM and LIM-receiver cascaded channel, and propose a two-stage algorithm that includes a sparse matrix factorization stage and a matrix completion stage. Simulation results illustrate that the proposed method can achieve accurate channel estimation for LIM-assisted massive MIMO systems.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/603923515ccf3e9f3ff0ff6c397c291ab05e8397

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Citations in the corpus

Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis (2019, methodology): “Last, [28] formulated the single-user channel estimation problem as a combined sparse matrix factorization and matrix completion problem and proposed to apply the compressed sensing technique to solve the problem.”
Active Reconfigurable Intelligent Surface-Aided Wireless Communications (2021, background): “Nevertheless, such a passive RIS-aided system is specifically constrained by the double-fading attenuation, since the reflected signals have to go through a cascaded channel, composed of the transmitter-RIS and the RIS-receiver sub-channels [20].”
An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, neutral): “Interested readers can refer to [42]–[48] for more details.”
Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities (2020, background): “individually or isolating the effect of the RIS is much more challenging [60].”
An Optimal Channel Estimation Scheme for Intelligent Reflecting Surfaces Based on a Minimum Variance Unbiased Estimator (2019, methodology): “Some IRS channel estimation methods, such as [4], attempts to estimate G, h separately, but since this is only possible with this signal model up to a complex scaling ambiguity, and since the cascaded channel V = G diag(h) is sufficient information for many methods and application, we do not pursue ”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, background): “In [108], the authors introduce a general framework for the estimation of the transmitter-RIS and RIS-receiver cascaded”
Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization (2019, methodology): “In [26], the low-rank structure of the massive MIMO channel was exploited and the cascaded channel estimation problem for IRS was addressed by leveraging the combined bilinear factorization and matrix completion.”
Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks (2019, methodology): “• Compressive-Sensing Method: In [39], a compressivesensing based method is proposed by exploiting the lowrank property of the RIS-aided link to further reduce the training overhead.”
Deep Denoising Neural Network Assisted Compressive Channel Estimation for mmWave Intelligent Reflecting Surfaces (2020, methodology): “Nevertheless, solutions in [7], [8] and [9] mainly consider a frequency-flat communication system by assuming narrow-band channels.”
A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications (2021, methodology): “In [65], [77], [78], matrix factorization/decomposition was exploited”
Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications (2020, methodology): “In [25], a general framework for cascaded CE in RIS-assisted Multiple Input Multiple Output (MIMO) systems was introduced by leveraging combined bilinear sparse matrix factorization and matrix completion.”
Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface: Discrete Phase Shift and Progressive Refinement (2019, background): “Instead, only the cascaded user-IRS-AP channels can be estimated at the AP (or user) based on the pilot symbols sent by the user (or AP), by adjusting IRS reflection coefficients over time [28]–[30].”
Massive MIMO is a Reality - What is Next? Five Promising Research Directions for Antenna Arrays (2019, background): “ed to behave as an arbitrarily shaped mirror in the given frequency band. Metasurfaces are also known as intelligent reﬂecting surfaces [65], [87] and there are several variations on these names [88]–[91]. Note that the key difference from the second approach, described in the previous paragraph, is”
Wireless Communications With Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement (2019, methodology): “Channel estimation for RIS-assisted systems was discussed in [35]–[37].”
Intelligent Reflecting Surface-Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design (2020, background): “We stress that MMSE estimates yield convenient analytical expressions unlike the algorithms in [29], [30] and can be extended under future channel estimation protocols that reduce training overhead.”
Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applications (2021, background): “…among all edge devices [281], quasi-static property between RIS and edge server channel links [282], [283], spatial features of noisy channels and additive nature of noises [284], as well as channel sparsity [285] and device activity sparsity [185], were exploited to reduce the training overhead.”
Two-Timescale Channel Estimation for Reconfigurable Intelligent Surface Aided Wireless Communications (2019, methodology): “Most cascaded channel estimation methods in the literature are based on the uplink pilot transmission [5], [14], [15], [18].”