Noise Shaping Enhanced DMT Signal Transmission Utilizing Low-Resolution DAC

Abstract

In order to reduce the quantization noise of lowresolution DAC, we study a noise shaping technique that can reshape the white quantization noise to an irregular spectrum, in which the noise in the data subcarrier band is almost transformed into the null subcarrier band. Both in simulation and experiment, we verify the effectiveness of the investigated scheme in 25 GHz 16-QAM/32-QAM/64-QAM DMT transmission systems. The experimental results show that the noise shaping technique can enhance the receiver sensitivity of 4-bit quantized 16-QAM DMT and 5-bit quantized 32-QAM DMT by 4.3 dB and 2.5 dB respectively, at BER of hard decision forward error correction (HD-FEC) threshold (3.8×10 -3 ). In addition, with the aid of noise shaping, the performance of 4-bit quantization 16-QAM DMT system is the same as the 8-bit quantization 16-QAM DMT system at the HD-FEC threshold. The experimental results reveal that the proposed noise shaping scheme is a good solution for high-speed, low-cost short reach intra-DCI with low-resolution DAC in future 6G networks evolved from 5G mobile networks.

Deep graph neural network optimized with fertile field algorithm based detection model for uplink multiuser massive multiple‐input and multiple‐output system

“…The input parameters are generated randomly after the initialization process. The input parameters, like BER, spectral proficiency, computational complexity, sum rate, and energy efficiency are considered as the input that are generated randomly utilizing matrix (Z) that is given in Equation (10),…”

“…Nowadays, massive multiple input multiple output schemes include binary phase shift keying and 4‐quadrature amplitude modulation signals for low‐order modulation signals, several detection approaches determined the approximate optimal performance of bit error rate utilizing the maximal likelihood algorithm along polynomial computational complexity, contains the likelihood ascents search (LAS), mixed Gibbs sampling (MGS), and ant colony optimization detection algorithm 7‐9 . These models have inefficient for detecting high‐order modulation signals owing to worst performance of bit error rate, 16‐quadrature amplitude modulation, 64‐quadrature amplitude modulation signals 10‐14 . In lesser or medium scale MIMO systems, semi definite relaxation decoder, LLLSDR detection, MGS‐MR detection, hybrid RTS‐BP detection gives results of high order modulation signals.…”

“…[7][8][9] These models have inefficient for detecting high-order modulation signals owing to worst performance of bit error rate, 16-quadrature amplitude modulation, 64-quadrature amplitude modulation signals. [10][11][12][13][14] In lesser or medium scale MIMO systems, semi definite relaxation decoder, LLLSDR detection, MGS-MR detection, hybrid RTS-BP detection gives results of high order modulation signals.…”

High-Speed Optical Fiber Communication in China

“…However, large quantization noise will be introduced if low-resolution DAC is used. The noise shaping technique is proposed to reshape the quantization noise and thus improve the in-band signal to quantization noise ratio (SQNR). − In ref , the transmission of the DMT signal generated by 4/5/6-bit resolution DAC with noise shaping in beyond 100 Gb/s intra-DCI is demonstrated, and the receiver sensitivity of 4-bit quantization 16QAM DMR at the HD-FEC threshold can be improved by 4.3 dB. Besides, the transmission of a 100 Gb/s PAM4 signal over 40/80 km SMF in the O-band utilizing a 4-bit DAC is experimentally achieved, and the BER performance of the signal generated by 4-bit DAC with noise shaping can approach that of the signal generated by 8-bit DAC .…”

Simplified coherent optical transmissions utilizing noise shaping and non-integer-oversampling clock data recovery

“…9 On the other hand, reducing the requirement of high-bit resolution digital-to-analog converters (DACs) is beneficial to simplify the optical communication systems, but it scarifies with the large quantization noise which affects the transmission performance. 10 To address the issue, quantization noise suppression techniques including delta-sigma modulator (DSM), digital resolution enhancer (DRE), and noise shaping (NS) technique have been proposed. [11][12][13] NS can effectively overcome the obstacles of high oversampling rate in DSM and computational complexity of DRE, making it more feasible to use cheap DACs with low resolutions for the purpose of simplifying the coherent optical systems.…”