Low-Complexity Joint Channel Estimation for Multi-User mmWave Massive MIMO Systems

For multi-user millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, the precise acquisition of channel state information (CSI) is a huge challenge. With the increase of the number of antennas at the base station (BS), the traditional channel estimation techniques encounter the problems of pilot training overhead and computational complexity increasing dramatically. In this paper, we develop a step-length optimization-based joint iterative scheme for multi-user mmWave massive MIMO systems to improve channel estimation performance. The proposed estimation algorithm provides the BS with full knowledge of all channel parameters involved in up- and down-links. Compared with existing algorithms, the proposed algorithm has higher channel estimation accuracy with low complexity. Moreover, the proposed scheme performs well even with a small number of training sequences and a large number of users. Simulation results are shown to demonstrate the performance of the proposed channel estimation algorithm

Detecting the significant nodes in two-layer flow networks: an interlayer non-failure cascading effect perspective

Detecting the significant nodes in multilayer networks is crucial for preventing the large-scale spread of disaster events. However, the existing model can hardly simulate the ubiquitous non-failure cascading effect process in social and economic systems. To solve this problem, first, we propose a mathematical method of constructing a two-layer network model. Then we define the non-failure cascading effect process in the two-layer network. Based on the model and spreading process, we propose a non-failure cascading effect index by using each node's non-failure cascading affecting in uential degree on the two-layer network. We then applied the detecting model in theoretical two-layer networks. We find there exist significant nodes, and also exist several in uential factors of the interlayer cascading effect process. The detecting model is applied in the two-layer industrial input{ output networks between the U.S. and China for testing the validity of the theoretical model. The hybrid network combination is relatively more sensitive to in uential factors; the significant nodes are more prominent in scale-free networks. Our research provides a solution for finding the significant nodes in two-layer social or economic networks based on the non-failure cascading effect process

Posttranslational modification of serine to formylglycine in bacterial sulfatases - Recognition of the modification motif by the iron-sulfur protein AtsB

Marquordt C, Fang QH, Will E, Peng JH, Figura von K, Dierks T. Posttranslational modification of serine to formylglycine in bacterial sulfatases - Recognition of the modification motif by the iron-sulfur protein AtsB. JOURNAL OF BIOLOGICAL CHEMISTRY. 2003;278(4):2212-2218.Calpha-formylglycine is the catalytic residue of sulfatases. Formylglycine is generated by posttranslational modification of a cysteine (pro- and eukaryotes) or serine (pro-karyotes) located in a conserved (C/S)XPXR motif. The modifying enzymes are unknown. AtsB, an iron-sulfur protein, is strictly required for modification of Se-72 in the periplasmic sulfatase AtsA of Klebsiella pneumoniae. Here we show W that AtsB is a cytosolic protein acting on newly synthesized serine-type sulfatases, (ii) that AtsB-mediated FGly formation is dependent on AtsA's signal peptide, and (iii) that the cytosolic cysteine-type sulfatase of Pseudomonas aeruginosa can be converted into a substrate of AtsB if the cysteine is substituted by serine and a signal peptide is added. Thus, formylglycine formation in serine-type sulfatases depends both on AtsB and on the presence of a signal peptide, and AtsB can act on sulfatases of other species. AtsB physically interacts with AtsA in a Ser(72)-dependent manner, as shown in yeast two-hybrid and GST pulldown experiments. This strongly suggests that AtsB is the serine-modifying enzyme and that AtsB relies on a cytosolic function of the sulfatase's signal peptide