K-means Cluster Algorithm Applied for Geometric Shaping Based on Iterative Polar Modulation in Inter-Data Centers Optical Interconnection

The demand of delivering various services is driving inter-data centers optical interconnection towards 400 G/800 G, which calls for increasing capacity and spectrum efficiency. The aim of this study is to effectively increase capacity while also improving nonlinear noise anti-interference. Hence, this paper presents a state-of-the-art scheme that applies the K-means cluster algorithm in geometric shaping based on iterative polar modulation (IPM). A coherent optical communication simulation system was established to demonstrate the performance of our proposal. The investigation reveals that the gap between IPM and Shannon limit has significantly narrowed in terms of mutual information. Moreover, when compared with IPM and QAM using the blind phase searching under the same order at HD-FEC threshold, the IPM-16 using the K-means algorithm achieves 0.9 dB and 1.7 dB gain; the IPM-64 achieves 0.3 dB and 1.1 dB gain, and the IPM-256 achieves 0.4 dB and 0.8 dB gain. The robustness of nonlinear noise and high capacity enable this state-of-the-art scheme to be used as an optional modulation format not only for inter-data centers optical interconnection but also for any high speed, long distance optical fiber communication system.

Nonlinear Noise Reduction for the Airborne Transient Electromagnetic Method based on Kernel Minimum Noise Fraction

The airborne transient electromagnetic method has become a powerful tool to explore deep resource and tectonic structures. However, aircraft vibrations and flight environments produce very strong and complex nonlinear noise and result in poor data quality compared to ground transient electromagnetic methods. Consequently, the reduction of airborne electromagnetic noises is of vital importance to data inversion and imaging. To suppress and remove the nonlinear noise, we propose using kernel minimum noise fraction (KMNF), which is a nonlinear generalized method of minimum noise fraction. First, an adaptive variable window-width filtering algorithm is used to evaluate the noises and perform the preliminary denoising. Then, we adopt the two filter methods, which are minimum noise fraction (MNF) and KMNF to suppress the noise. The results show that these two methods can both suppress noise and make the decay curves smooth, but kernel MNF is more effective for the nonlinear characteristics of noise and it does not weaken the anomaly. Finally, field data from the Qinling mine area is processed, using the MNF and KMNF methods. The results show that nonlinear noise is suppressed by both methods but the results of KMNF are better than those of the linear MNF method.

Noise analysis of translinear circuits

This thesis presents noise analysis of translinear circuits, or in general, log-domain filters. Due to the inherit companding [sic] behaviour and nonstationary nature of the translinear noise sources, a nonlinear noise analysis method is proposed.

Noise analysis of translinear circuits

This thesis presents noise analysis of translinear circuits, or in general, log-domain filters. Due to the inherit companding [sic] behaviour and nonstationary nature of the translinear noise sources, a nonlinear noise analysis method is proposed.