Antenna Array Diagnosis for Millimeter-Wave MIMO Systems

Ma, Siqi; Shen, Wenqian; An, Jianping; Hanzo, Lajos

doi:10.1109/tvt.2020.2977733

Cited by 14 publications

(18 citation statements)

References 19 publications

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“…• (ii) Since a lot data are needed to deal with during continuously monitoring the RIS, it can induce a huge computational complexity and memory cost. According to reference [26], [27], we make some assumptions as follow:…”

Section: System Model a Transmission With Ris Blockagementioning

confidence: 99%

“…Therefore, compressed sensing (CS) has recently been proposed in [23]- [25] for diagnosing large antenna arrays using reduced number of samples. The group CS approach in [26], [27] was proposed to estimate the locations of the blocked antennas and the induced the complex blockage coefficients including attenuation and phase shifts jointly.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, to the best of our knowledge, no literature has been proposed to study the array diagnosis for RIS. Meanwhile, the conventional array diagnosis techniques, such as [26], [27], which have to work in the array under test (AUT) model, can not be applied to the RIS. The AUT model requirs that the BS transmits a sequence of pilot to a reference array for array diagnosis, where the perfect CSI between them is assumed.…”

Section: Introductionmentioning

confidence: 99%

“…However, in practice, the CSI acquisition for the BS-RIS-UE cascaded channel is still a open and difficult issue, due to no signal processing capability for RIS. Therefore, motivated by these reasons, in this paper, comparing to existing works [26], [27], we propose a new algorithm to avoid the AUT model and complete the array diagnosis and channel estimation jointly.…”

Section: Introductionmentioning

confidence: 99%

“…For channel estimation problem in the system, we formulate it as joint antenna diagnosis and channel estimation. The new formulation, which is a two-timescale non-convex optimization formulation, can eliminate the dependence of traditional antenna diagnosis algorithms proposed in [26], [27] on AUT model. • We propose the batch algorithm (BA) to solve the challenging two-timescale non-convex optimization problem, which can identify the locations and the induced attenuation and phase shifts caused by blockages and simultaneously implement channel estimation.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Joint Array Diagnosis and Channel Estimation for RIS-Aided mmWave MIMO System

Zhang

et al. 2020

IEEE Access

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In this paper, we consider a reconfigurable intelligent surface (RIS) aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) system. The system can obtain the huge gain via joint active beamforming at the base station (BS) and passive beamforming at the RIS. However, due to weather and atmospheric effects, outdoor RIS antenna elements are subject to full or partial blockages from a plethora of particles like dirt, salt, ice, and water droplets. These blockages can cause an approximate squared power/SNR loss for the system. Different from the conventional array diagnosis, the RIS has no signal processing capability. Thus, we propose the joint array diagnosis and channel estimation techniques containing two stages to solve the problem. At the first stage the channel parameters at user equipment (UE) and BS are estimated using an iterative reweighted (IR) method. At the second stage, the array blockage coefficient vector and the effective sparse channel parameters at RIS are jointly estimated via solving a two-timescale non-convex optimization problem. We propose two algorithms, i.e., a batch algorithm (BA) and a two-timescale online joint array diagnosis and channel estimation (TOJADCE) algorithm to solve the problem and compare the performance of these two algorithms. Finally, to speed up the convergence of long-term variable and improve estimation performance, we propose a noise reduction (NR) algorithm. The simulations verify the effectiveness of our proposed algorithms. INDEX TERMS mmWave MIMO system, reconfigurable intelligent surface, joint array diagnosis and channel estimation, two-timescale non-convex optimization

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Section: System Model a Transmission With Ris Blockagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Joint Array Diagnosis and Channel Estimation for RIS-Aided mmWave MIMO System

Zhang

et al. 2020

IEEE Access

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Channel estimation for reconfigurable intelligent surface‐assisted multiuser mmWave MIMO system in the presence of array blockage

Zhang

2021

Trans Emerging Tel Tech

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In this article, we focus on the channel estimation problem for reconfigurable intelligent surface (RIS)-assisted multiuser mmWave MIMO system. The main challenge for channel estimation of this system lies in that all elements of the RIS are passive reflecting antennas incapable of processing signals, which are designed to reflect the incident signals by a certain phase shift. Meanwhile, considering that array blockage is often present at the RIS working in mmWave band, the channel estimation problem becomes more challenging. By introducing the effective channel model derived from the cascaded channel model among the base station (BS), the RIS, and the user equipment, we formulate the original problem to estimate the effective channel and array blockage matrix jointly. For the single-user scenario, we propose the orthogonal matching pursuit-array blockage calibration (OMPABC) algorithm to complete this estimation problem. In the multiuser scenario, with the aid of channel estimation scheme based on feedback, all the channel matrices of UEs and array blockage matrix are estimated at the BS jointly. Furthermore, in the small number of UEs case, we introduce the common support among the different UEs and extend this property to the effective channel. Utilizing the property, we propose the joint OMPABC algorithm to estimate the effective channel of all UEs and array blockage matrix jointly. Finally, in the large number of UEs case, we propose the two-space-scale OMPABC algorithm with a low computational complexity. The simulation results illustrate our proposed algorithms can effectively improve the estimation performance.

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Array antenna failure robust compensation via tensor Hankelization in MIMO radar for DOA estimation

Chen

Jiang

et al. 2022

AEU - International Journal of Electronics and Communications

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Antenna Array Diagnosis for Millimeter-Wave MIMO Systems

Cited by 14 publications

References 19 publications

Joint Array Diagnosis and Channel Estimation for RIS-Aided mmWave MIMO System

Joint Array Diagnosis and Channel Estimation for RIS-Aided mmWave MIMO System

Channel estimation for reconfigurable intelligent surface‐assisted multiuser mmWave MIMO system in the presence of array blockage

Array antenna failure robust compensation via tensor Hankelization in MIMO radar for DOA estimation

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