14 research outputs found

    Iterative Signal Processing for Integrated Sensing and Communication Systems

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    Integrated sensing and communication (ISAC), with sensing and communication sharing the same wireless resources and hardware, has the advantages of high spectrum efficiency and low hardware cost, which is regarded as one of the key technologies of the fifth generation advanced (5G-A) and sixth generation (6G) mobile communication systems. ISAC has the potential to be applied in the intelligent applications requiring both communication and high accurate sensing capabilities. The fundamental challenges of ISAC system are the ISAC signal design and ISAC signal processing. However, the existing ISAC signal has low anti-noise capability. And the existing ISAC signal processing algorithms have the disadvantages of quantization errors and high complexity, resulting in large energy consumption. In this paper, phase coding is applied in ISAC signal design to improve the anti-noise performance of ISAC signal. Then, the effect of phase coding method on improving the sensing accuracy is analyzed. In order to improve the sensing accuracy with low-complexity algorithm, the iterative ISAC signal processing methods are proposed. The proposed methods improve the sensing accuracy with low computational complexity, realizing energy efficient ISAC signal processing. Taking the scenarios of short distance and long distance sensing into account, the iterative two-dimensional (2D) fast Fourier transform (FFT) and iterative cyclic cross-correlation (CC) methods are proposed, respectively, realizing high sensing accuracy and low computational complexity. Finally, the feasibility of the proposed ISAC signal processing methods are verified by simulation results

    An Unstructured Phylogeographic Pattern with Extensive Gene Flow in an Endemic Bird of South China: Collared Finchbill (Spizixos semitorques)

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    Recent phylogeographical studies indicated that glacial oscillations played a key role on the phylogeographic pattern of extant species. As most studies have previously been carried out on heavily ice-covered regions, such as in European and North American regions, potential effects of climatic oscillations on species that are distributed on ice-free regions are less known. To address this, we investigated the phylogeographic pattern of an avian species endemic to South China, which was not glaciated during the Pleistocene glaciations. By using 2142 bp mitochondrial DNA, we identified 89 haplotypes defined by 39 polymorphic sites. A combination of high haplotype diversity (0.786–1.00) and low nucleotide diversity (0.00132–0.00252) was detected among geographic populations. Explicit genetic divergence was observed between S. s. semitorques and S. s. cinereicapillus but not detected among geographic populations of S. s. semitorques. Divergence time of the two subspecies was dated back to 87 Kyr which is congruent with the interglacial MIS 5. A weak phylogeographic structure due to strong gene flow among geographic populations was identified in this species, suggesting complex topography of South China has not formed barriers for this species

    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Segmented Real-time Dispatch Model and Stochastic Robust Optimization for Power-gas Integrated Systems with Wind Power Uncertainty

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    This paper develops a segmented real-time dispatch model for power-gas integrated systems (PGISs), where power-to-gas (P2G) devices and traditional automatic generation control units are cooperated to manage wind power uncertainty. To improve the economics of the real-time dispatch in regard to the current high operation cost of P2Gs, the wind power uncertainty set is divided into several segments, and a segmented linear decision rule is developed, which assigns adjustment tasks differently when wind power uncertainty falls into different segments. Thus, the P2G operation with high costs can be reduced in real-time adjustment. Besides, a novel segmented stochastic robust optimization is proposed to improve the efficiency and robustness of PGIS dispatch under wind power uncertainty, which minimizes the expected cost under the empirical wind power distribution and builds up the security constraints based on the robust optimization. The expected cost is formulated using a Nataf conversion-based multi-point estimate method, and the optimal number of estimate points is determined through sensitivity analysis. Furthermore, a difference-of-convex optimization with a partial relaxation rule is developed to solve the non-convex dispatch problem in a sequential optimization framework. Numerical simulations in two testing cases validate the effectiveness of the proposed model and solving method
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