The Role of Sigma-Delta ADCs and Zero-Forcing Estimator in Massive MIMO Channel Estimation | ||||
| Journal of Advanced Engineering Trends | ||||
| Articles in Press, Accepted Manuscript, Available Online from 22 January 2024 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/jaet.2024.243344.1262 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Gerges M. Salama 1; Y. S.Mohamad2; Maha Tharwat Saif  3
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| 1Electric Engineering Dep., Faculty of Engineering, Minia University | ||||
| 2Electrical Engineering Dept., Faculty of Engineering,Minia University, Egypt | ||||
| 3Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia, Egypt | ||||
| Abstract | ||||
| In the presented work, we delve into the complexities of improving channel estimates for an uplink large multiple-input multiple-output (MIMO) system. In order to enhance the system's overall accuracy and effective resolution, the base station (BS) is fitted with 1-bit spatial sigma-delta (Σ∆) analog-to-digital converters (ADCs). Our study presents two proposed algorithms to estimate the channel. For the first algorithm, we compute a multipath channel that is specified by angle steering, specifically angles of arrival (AoAs), and path gains. This is accomplished by uplink pilots that can aid in lessening interference that occurs caused by multipath channels when users transmit a signal to the BS. We believe that appropriately setting the quantization voltage level of the (Σ∆) quantizer is critical for this approach to produce the best results. We present a technique for optimizing channel estimation performance when using a zero-forcing (ZF) estimator with the quantized signal from (Σ∆) ADC in the second procedure. According to the results of numerical simulations, the suggested channel estimation algorithms outperform existing standard methods. The first algorithm demonstrates significant improvements in channel estimation accuracy over existing techniques, with a notable increment in the signal-to-noise ratio (SNR) and a decrease in the normalized mean square error (NMSE) rate. where the second algorithm shows the ideal result, which is zero error for different values of SNR. | ||||
| Keywords | ||||
| Massive MIMO, channel estimation, sigma-delta ADC (Σ ∆), Zero Forcing (ZF), Angle of Arrival (AoA) | ||||
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