Channel Estimation and Performance Analysis of One-Bit Massive MIMO Systems
By Yongzhi Li, Cheng Tao, Gonzalo Seco-Granados, Amine Mezghani, A. L. Swindlehurst, Liu Liu. IEEE Transactions on Signal Processing, 2016
531 citations recorded by the source corpus.
This paper considers channel estimation and system performance for the uplink of a single-cell massive multiple-input multiple-output system. Each receiver antenna of the base station is assumed to be equipped with a pair of one-bit analog-to-digital converters to quantize the real and imaginary part of the received signal. We first propose an approach for channel estimation that is applicable for both flat and frequency-selective fading, based on the Bussgang decomposition that reformulates the nonlinear quantizer as a linear function with identical first- and second-order statistics. The resulting channel estimator outperforms previously proposed approaches across all SNRs. We then derive closed-form expressions for the achievable rate in flat fading channels assuming low SNR and a large number of users for the maximal ratio and zero forcing receivers that takes channel estimation error due to both noise and one-bit quantization into account. The closed-form expressions, in turn, allow us to obtain insight into important system design issues such as optimal resource allocation, maximal sum spectral efficiency, overall energy efficiency, and number of antennas. Numerical results are presented to verify our analytical results and demonstrate the benefit of optimizing system performance accordingly.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/5d5ce05c6a9cb389d643069006ba07b1071bad44
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Electrical and Electronic Engineering
- Robert W. Heath
- Philip Schniter
- Jianhua Mo
- Giuseppe Durisi
- Christoph Studer
- Tom Goldstein
- Mikael Coldrey
- Sven Jacobsson
Citations in the corpus
- Quantized Precoding for Massive MU-MIMO (2016, background): “We further note that, analogously to the uplink scenario [23], [24], high sum-rate throughputs can be achieved despite having low-resolution DACs at the BS.”
- Channel Estimation in Broadband Millimeter Wave MIMO Systems With Few-Bit ADCs (2016, methodology): “Assuming E [ xx ∗ ] = σ 2 x I (as above) and leveraging the result (38) that E [ (cid:98) w (cid:98) w ∗ ] ≈ σ 2 (cid:98) w I , one can straightforwardly derive the linear MMSE (LMMSE) estimator of x from y in (35).”