Channel parameter estimation for millimeter-wave cellular systems with hybrid beamforming

Fazal-E-Asim,; Antreich, Felix; Cavalcante, Charles C.; Almeida, André L. F. de; Nossek, Josef A.

doi:10.1016/j.sigpro.2020.107715

Cited by 12 publications

(2 citation statements)

References 22 publications

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“…But the CSI is challenging to estimate due to the high dimensionality of the RIS. The similar issue also occurs in the mmWave phase shifter network (PSN) based hybrid massive MIMO scenario [8], [9]. In [10], Mishra et al proposed a least square (LS) based channel estimation method for RIS-aided MIMO.…”

Section: Introductionmentioning

confidence: 90%

Efficient RIS Channel Estimation and Projection Using Zadoff-Chu Sequences

Zhou

Yang

Jiang

2021

2021 IEEE/CIC International Conference on Communications in China (ICCC)

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The reconfigurable intelligent surface (RIS) technology is a promising enabler for millimeter wave (mmWave) wireless communications, as it can potentially provide spectral efficiency comparable to the conventional massive multipleinput multiple-output (MIMO) but with significantly lower hardware complexity. In this paper, we focus on the estimation and projection of the uplink RIS-aided massive MIMO channel, which can be time-varying. We propose to let the user equipments (UE) transmit Zadoff-Chu (ZC) sequences and let the base station (BS) conduct maximum likelihood (ML) estimation of the uplink channel. The proposed scheme is computationally efficient: it uses ZC sequences to decouple the estimation of the frequency and time offsets; it uses the space-alternating generalized expectation-maximization (SAGE) method to reduce the high-dimensional problem due to the multipaths to multiple lower-dimensional ones per path. Owing to the estimation of the Doppler frequency offsets, the time-varying channel state can be projected, which can significantly lower the overhead of the pilots for channel estimation. The numerical simulations verify the effectiveness of the proposed scheme.

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Section: Introductionmentioning

confidence: 90%

Efficient RIS Channel Estimation and Projection Using Zadoff-Chu Sequences

Zhou

Yang

Jiang

2021

2021 IEEE/CIC International Conference on Communications in China (ICCC)

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“…However, the ML approach use knowledge to improve channel estimation when the noise is not white, and its covariance matrix is known. Authors in [46], [47] developed a channel estimation approach based on maximum a posteriori (MAP) that treats the channel coefficients as random variables and maximized the likelihood of the channel coefficients given the received data.…”

Section: A Related Workmentioning

confidence: 99%

Robust Channel Estimation in Multiuser Downlink 5G Systems Under Channel Uncertainties

Pourkabirian

Anisi

2022

IEEE Trans. on Mobile Comput.

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In wireless communication, the performance of the network highly relies on the accuracy of channel state information (CSI). On the other hand, the channel statistics are usually unknown, and the measurement information is lost due to the fading phenomenon. Therefore, we propose a channel estimation approach for downlink communication under channel uncertainty. We apply the Tobit Kalman filter (TKF) method to estimate the hidden state vectors of wireless channels. To minimize the maximum estimation error, a robust minimax minimum estimation error (MSE) estimation approach is developed while the QoS requirements of wireless users is taken into account. We then formulate the minimax problem as a non-cooperative game to find an optimal filter and adjust the best behavior for the worst-case channel uncertainty. We also investigate a scenario in which the actual operating point is not exactly known under model uncertainty. Finally, we investigate the existence and characterization of a saddle point as the solution of the game. Theoretical analysis verifies that our work is robust against the uncertainty of the channel statistics and able to track the true values of the channel states. Additionally, simulation results demonstrate the superiority of the model in terms of MSE value over related techniques.

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An optimization-driven model for a hybrid beam forming for massive multiple-input multiple-output

Pawar

Patil²

2023

Wireless Netw

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Channel parameter estimation for millimeter-wave cellular systems with hybrid beamforming

Cited by 12 publications

References 22 publications

Efficient RIS Channel Estimation and Projection Using Zadoff-Chu Sequences

Efficient RIS Channel Estimation and Projection Using Zadoff-Chu Sequences

Robust Channel Estimation in Multiuser Downlink 5G Systems Under Channel Uncertainties

An optimization-driven model for a hybrid beam forming for massive multiple-input multiple-output

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