Search arXivSearch

arXiv · 1811.07637

Mismatch error correction for time interleaved analog-to-digital converter over a wide frequency range

Abstract

High-speed high-resolution Analog-to-Digital Conversion is the key part for waveform digitization in physics experiments and many other domains. This paper presents a new fully digital correction of mismatch errors among the channels in Time Interleaved Analog-to-Digital Converter (TIADC) systems. We focus on correction with wide-band input signal, which means that we can correct the mismatch errors for any frequency point in a broad band with only one set of filter coefficients. Studies were also made to show how to apply the correction algorithm beyond the base band, i.e. other Nyquist zones in the under-sampling situation. Structure of the correction algorithm is presented in this paper, as well as simulation results. To evaluate the correction performance, we actually conducted a series of tests with two TIADC systems. The results indicate that the performance of both two TIADC systems can be greatly improved by correction, and the Effective Number Of Bits (ENOB) is successfully improved to be better than 9.5 bits and 5.5 bits for an input signal up to the bandwidth (-3dB) range in the 1.6-Gsps 14-bit and the 10-Gsps 8-bit TIADC systems, respectively. Tests were also conducted for input signal frequencies in the second Nyquist zone, which shows that the correction algorithms also work well as expected.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zouyi Jiang, Lei Zhao, Xingshun Gao, Ruoshi Dong, Jinxin Liu, Qi An. 2018-11-19. Mismatch error correction for time interleaved analog-to-digital converter over a wide frequency range. https://doi.org/10.1063/1.5030782

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Multi-Carrier Rydberg Atomic Quantum Receivers with Enhanced Bandwidth Feature for Communication and Sensing

Rydberg atomic quantum receivers (RAQRs) have attracted significant attention in recent years due to their ultra-high sensitivity. Although capable of precisely detecting the amplitude and phase of weak signals, conventional RAQRs face inherent limitations in accurately receiving wideband RF signals, due to the discrete nature of atomic energy levels and their intrinsic instantaneous bandwidth constraints. These limitations hinder their direct application to multi-carrier communication and sensing. To address this issue, this paper proposes a multi-carrier Rydberg atomic quantum receiver (MC-RAQR) structure with five energy levels. We derive the amplitude and phase of the MC-RAQR and extract the baseband electrical signal for signal processing. In terms of multi-carrier communication and sensing, we analyze the channel capacity and accuracy of angle of arrival (AoA) and distance parameters, respectively. Numerical results validate our proposed model, showing that the MC-RAQR can achieve up to a bandwidth of 11.7 MHz, which is 17-fold larger than the conventional RAQRs. As a result, the channel capacity and the resolution for multi-target sensing are improved significantly. Specifically, the channel capacity of MC-RAQR is 110-fold and 2.8-fold larger than the classical RF receivers and RAQRs, respectively. For sensing performance, the RMSE of AoA estimation for MC-RAQR exhibits 7.6-fold reduction, compared with the conventional RAQRs. Furthermore, the RMSE of distance estimation is $634$-fold smaller than that of the root-CRB of classical RF receivers, showing the superior performance of the MC-RAQR. This demonstrates its compatibility with waveforms such as orthogonal frequency-division multiplexing (OFDM) and its significant advantages for multi-carrier signal reception.

eess.SP

Channel Estimation in MIMO Systems Aided by Microwave Linear Analog Computers (MiLACs)

Microwave linear analog computers (MiLACs) have recently emerged as a promising solution for future gigantic multiple-input multiple-output (MIMO) systems, enabling beamforming with greatly reduced hardware and computational cost. However, channel estimation for MiLAC-aided systems remains an open problem. Conventional least squares (LS) and minimum mean square error (MMSE) estimation rely on intensive digital computation, which undermines the computational advantage offered by MiLACs. In this letter, we propose efficient LS and MMSE channel estimation schemes for MiLAC-aided MIMO systems. By designing the training precoder and combiner implemented by lossless and reciprocal MiLACs, the proposed schemes perform LS and MMSE estimation in the analog domain, leaving only simple digital scaling. They achieve identical estimation performance to their digital counterparts while significantly reducing computational complexity. Numerical results verify the effectiveness of the proposed schemes.

eess.SP

Joint Subcarrier Phase Recovery for Nonlinearity Mitigation

We propose a low-complexity phase recovery scheme that simultaneously mitigates laser phase noise and fiber nonlinearity across several subcarriers. In a long single-span link with Raman amplification, the scheme achieves 0.9 dB gain with 99 real multiplications per complex symbol.

eess.SP