Millimeter-Wave Channel Estimation Based on 2-D Beamspace MUSIC Method

Guo, Ziyu; Wang, Xiaodong; Wei, Heng

doi:10.1109/twc.2017.2710049

Cited by 153 publications

(99 citation statements)

References 33 publications

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“…Note that there is a great difference between the proposed channel estimation methods and that in [11] except the wideband or narrowband channels. Unlike the existing ESPRIT-based or MUSIC-based channel estimation schemes that have to turn off approximately half of the antennas so that the number of active antennas is equal to that of time slots for channel estimation [11], [12], here we turn off only one antenna at each side, which ensures almost the same of transmission power and signal coverage. Note that if each user only has M A = 1 antenna, i.e., the MISO scenario, U users do not need to turn off the single antenna because the AoD is nonexistent in this case.…”

Section: A Aoa Estimationmentioning

confidence: 99%

“…where W is set to be the same as that in (15). Therefore, (14) can be represented as 12 · · · e jπθ u,Lu 2 . .…”

Section: A Aoa Estimationmentioning

confidence: 99%

“…We propose two channel estimation schemes based on ESPRIT [18] for mmWave massive MIMO channels with OFDM transmission. Different from the existing schemes based on the ESPRIT and MUSIC methods [11], [12], our schemes can estimate frequency-selective channels and only need to turn off one antenna, which has little impact on the total transmission power. The contribution of this paper is summarized as follows.…”

Section: Introductionmentioning

confidence: 99%

“…However, since the mmWave massive MIMO system with hybrid precoding and combining is totally different from the radar system, it is difficult to directly use the ESPRIT method. A scheme based on the ESPRIT and a scheme based on multiple signal classification (MUSIC) are proposed in [11] and [12], respectively. In order to eliminate the effect of the hybrid precoding and combining so that the ESPRIT and MUSIC methods can be directly used, these two schemes have to turn off approximately half of the antennas so that the number of active antennas is equal to that of time slots for channel estimation, which reduces the total transmission power and signal coverage.…”

Section: Introductionmentioning

confidence: 99%

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High-Resolution Channel Estimation for Frequency-Selective mmWave Massive MIMO Systems

2020

IEEE Trans. Wireless Commun.

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In this paper, we develop two high-resolution channel estimation schemes based on the estimating signal parameters via the rotational invariance techniques (ESPRIT) method for frequency-selective millimeter wave (mmWave) massive MIMO systems. The first scheme is based on two-dimensional ESPRIT (TDE), which includes three stages of pilot transmission. This scheme first estimates the angles of arrival (AoA) and angles of departure (AoD) and then pairs the AoA and AoD. The other scheme reduces the pilot transmission from three stages to two stages and therefore reduces the pilot overhead. It is based on one-dimensional ESPRIT and minimum searching (EMS). It first estimates the AoD of each channel path and then searches the minimum from the identified mainlobe. To guarantee the robust channel estimation performance, we also develop a hybrid precoding and combining matrices design method so that the received signal power keeps almost the same for any AoA and AoD. Finally, we demonstrate that the proposed two schemes outperform the existing channel estimation schemes in terms of computational complexity and performance.Index Terms-Millimeter wave communications, channel estimation, hybrid precoding, massive MIMO.

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Section: A Aoa Estimationmentioning

confidence: 99%

“…where W is set to be the same as that in (15). Therefore, (14) can be represented as 12 · · · e jπθ u,Lu 2 . .…”

Section: A Aoa Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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High-Resolution Channel Estimation for Frequency-Selective mmWave Massive MIMO Systems

2020

IEEE Trans. Wireless Commun.

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“…Direction-of-arrival (DOA) estimation of multiple narrowband sources is one of the most important issues in signal processing, which has diverse applications ranging from synthetic aperture radar [1], wireless communications [2] to source localization [3]. It is well known that many DOA estimation algorithms are confined to the overdetermined scenario where the number of sources is less than the number of sensors [4]- [8].…”

Section: Introductionmentioning

confidence: 99%

A Block Alternating Optimization Method for Direction-of-Arrival Estimation With Nested Array

et al. 2019

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In this paper, direction-of-arrival estimation using nested array is studied in the framework of sparse signal representation. With the vectorization operator, a new real-valued nonnegative sparse signal recovery model which has a wider virtual array aperture is built. To leverage celebrated compressive sensing algorithms, the continuous parameter space has to be discretized to a number of fixed grid points, which inevitably incurs modeling error caused by off-grid gap. To remedy this issue, a block alternating optimization method is put forth that jointly estimates the sparse signal and refines the locations of grid points. Specifically, inspired by the majorization minimization, the proposed method iteratively minimizes a surrogate function majorizing the given objective function, where only a single block of variables are updated per iteration while the remaining ones are kept fixed. The proposed method features affordable computational complexity, and numerical tests corroborate its superior performance relative to existing alternatives in both overdetermined and underdetermined scenarios.

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An Introduction on Millimeter Wave Communications

Huang

2019

Wiley 5G Ref

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In the past few years, millimeter wave (mmWave) communication has attracted significant attention both from industry and academia, due to the large available spectrum at mmWave frequency bands. With the significantly increased communication bandwidth, mmWave communication is able to achieve tremendous data rate (e.g. on the order of dozens of Gbps) to satisfy the ever‐increasing traffic demand in 5G‐and‐beyond wireless networks. This article aims to give an introductory overview on the fundamentals of mmWave communication, including the general background of mmWave systems, the propagation characteristics of mmWave channels, followed by the design of hybrid antenna architecture to balance the trade‐off between the hardware cost and the system performance. The state of the art for the design of hybrid precoding/combining and channel acquisition for mmWave systems will be highlighted.

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Millimeter-Wave Channel Estimation Based on 2-D Beamspace MUSIC Method

Cited by 153 publications

References 33 publications

High-Resolution Channel Estimation for Frequency-Selective mmWave Massive MIMO Systems

High-Resolution Channel Estimation for Frequency-Selective mmWave Massive MIMO Systems

A Block Alternating Optimization Method for Direction-of-Arrival Estimation With Nested Array

An Introduction on Millimeter Wave Communications

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