Channel Estimation for RIS-aided mmWave Massive MIMO System Using Few-bit ADCs
Ruizhe Wang, Hong Ren, Cunhua Pan, Jun Fang, Mianxiong Dong and, Octavia A. Dobre

TL;DR
This paper proposes a Bayesian low-rank matrix completion method using BiG-AMP for accurate channel estimation in RIS-aided mmWave massive MIMO systems with few-bit ADCs, reducing hardware costs.
Contribution
It introduces a novel Bayesian estimation framework combined with BiG-AMP for cascaded channel estimation under low-resolution quantization in RIS-assisted systems.
Findings
Accurately estimates cascaded channels with low-resolution ADCs.
Demonstrates robustness of the method through extensive simulations.
Reduces hardware costs by enabling effective channel estimation with few-bit ADCs.
Abstract
Millimeter wave (mmWave) massive multiple-input multiple-output (massive MIMO) is one of the most promising technologies for the fifth generation and beyond wireless communication system. However, a large number of antennas incur high power consumption and hardware costs, and high-frequency communications place a heavy burden on the analog-to-digital converters (ADCs) at the base station (BS). Furthermore, it is too costly to equipping each antenna with a high-precision ADC in a large antenna array system. It is promising to adopt low-resolution ADCs to address this problem. In this paper, we investigate the cascaded channel estimation for a mmWave massive MIMO system aided by a reconfigurable intelligent surface (RIS) with the BS equipped with few-bit ADCs. Due to the low-rank property of the cascaded channel, the estimation of the cascaded channel can be formulated as a low-rank…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Advanced Antenna and Metasurface Technologies · Satellite Communication Systems
