Performance of Cell-Free Massive MIMO Under Imperfect Channel State Information and Reciprocity Calibration

Cao, Yi; Liang, Xiaodong; Wang, Xiaoni; Liu, Yuan; Fu, Qiang; Wang, Dongming; You, Xiaohu

doi:10.1109/jsyst.2023.3269145

Cited by 4 publications

(1 citation statement)

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“…In this scenario, the relay performs the functions of normalizing, amplifying, and forwarding the signals to the indoor users. The base station (BS) predicts the comparable uplink channel, and the downlink channel state information (CSI) is derived by leveraging the principle of channel reciprocity [20].…”

Section: Introductionmentioning

confidence: 99%

Outdoor-to-Indoor mmWave Relaying with Massive MIMO: Impact of Imperfect Channel Estimation

Bounouader,

Chafnaji,

Benjillali

2024

Electronics

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Assuming incomplete knowledge of the channel state information (CSI), we investigate two scenarios involving millimeter wave (mmWave) relaying to support outdoor-to-indoor communications. We proceed to derive the average signal-to-noise ratio (SNR) expressions for two relaying scenarios and quantify the asymptotic SNR. The performance of the two relaying scenarios is evaluated using the outage probability—for which we have derived closed-form equations—the end-to-end channel capacity, and the energy efficiency. The obtained results are compared with those derived assuming complete knowledge of the CSI. The effect of the imperfect CSI is therefore assessed in relation to the reference of perfect CSI. In these scenarios, an outside base station (BS) in an urban cellular network serves several indoor users. In the context of a two-hop full-duplex (FD) relaying scheme, we initially suggest a method in which the base station (BS) utilizes zero-forcing (ZF) precoding, and we take into account the overall channel response. Furthermore, we make the assumption that the base station (BS) engages in precoding only depending on the response of the channel in the first hop; in this second design, the relay precodes (using the response of the second-hop channel), amplifies, and sends the signals. Both techniques utilize massive multiple-input–multiple-output (mMIMO) arrays to permit transmission. We also present Monte Carlo simulation results to assess the accuracy of our analytical results. Finally, the two systems are compared in terms of channel estimation and precoding complexity, the number of antennas, as well as the number of users. Practical deployment recommendations are formulated at the end of this work.

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Section: Introductionmentioning

confidence: 99%