12 research outputs found

    Research of TD-SCDMA Channel Estimation Method and GPPSDR-Based Implementation

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    TD-SCDMA是我国自主提出的第三代移动通信标准,采用了很多先进的关键技术如智能天线、联合检测等,它们的性能在很大程度上依赖于信道估计的精确性。因此,研究TD-SCDMA系统中的上行信道估计方法对TD-SCDMA整个系统实现具有重要的意义。 本文在研究TD-SCDMA信道特性的基础上,详细地分析了TD-SCDMA的信道模型,并给出了TD-SCDMA上行链路信道模型。其次,针对TD-SCDMA标准中的信道估计技术,给出了用于信道估计的接收矢量模型,详细地阐述了TD-SCDMA中的信道估计原理,包括单小区信道估计算法与多小区信道估计算法的原理;在充分分析现有经典信道估计算法的基础上,提出了低代...TD-SCDMA standard is a third generation mobile communication standard that proposed independently by our country.It has milestone significance in our country’s communication history , and combines the advantage of the time division duplex (TDD) with CDMA, makes use of many advanced techniques, such as smart antenna, Joint Detection and so on. But, these key technologies performance rely on the acc...学位:工学硕士院系专业:信息科学与技术学院通信工程系_通信与信息系统学号:2332009115281

    Software design and optimization of GPP-SDR based TD-HSDPA physical channels

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    为了改善传统软件无线电开发方式的灵活性,降低开发成本,采用基于通用处理器的软件无线电(gPP-Sdr)平台,研究了Td-HSdPA高速物理信道的实现及优化,包括HArQ功能模块的设计。通过优化接收机代码,极大提高了软件运行效率,对处理时延的测试结果表明,软件设计能够实现Td-HSdPA实时传输,并支持其高速物理信道协议栈在gPP-Sdr平台上的高效运行。给出的HArQ仿真结果验证了系统的吞吐率性能。To improve flexibility of the traditional software defined radio development and reduce the cost,general-purpose processor software defined radio(GPP-SDR) platform is adopted to study software development and optimization of TD-HSDPA high-speed physical channel including HARQ functional module.By optimizing the receiver code,the efficiency of software is greatly improved.Latency measurement results demonstrate that this software implementation can realize real-time TD-HSDPA transfer and support the physical channel protocol stack running on the GPP-SDR platform efficiently.HARQ simulation results for this design are also given to validate its performance

    Micro cutting mechanism of abrasive flow precision machining

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    Prediction of Energy Resolution in the JUNO Experiment

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    International audienceThis paper presents the energy resolution study in the JUNO experiment, incorporating the latest knowledge acquired during the detector construction phase. The determination of neutrino mass ordering in JUNO requires an exceptional energy resolution better than 3% at 1 MeV. To achieve this ambitious goal, significant efforts have been undertaken in the design and production of the key components of the JUNO detector. Various factors affecting the detection of inverse beta decay signals have an impact on the energy resolution, extending beyond the statistical fluctuations of the detected number of photons, such as the properties of liquid scintillator, performance of photomultiplier tubes, and the energy reconstruction algorithm. To account for these effects, a full JUNO simulation and reconstruction approach is employed. This enables the modeling of all relevant effects and the evaluation of associated inputs to accurately estimate the energy resolution. The study reveals an energy resolution of 2.95% at 1 MeV. Furthermore, the study assesses the contribution of major effects to the overall energy resolution budget. This analysis serves as a reference for interpreting future measurements of energy resolution during JUNO data taking. Moreover, it provides a guideline in comprehending the energy resolution characteristics of liquid scintillator-based detectors

    JUNO Sensitivity on Proton Decay pνˉK+p\to \bar\nu K^+ Searches

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    The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in pνˉK+p\to \bar\nu K^+ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via pνˉK+p\to \bar\nu K^+ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is 9.6×10339.6 \times 10^{33} years, competitive with the current best limits on the proton lifetime in this channel

    Measurement of integrated luminosity of data collected at 3.773 GeV by BESIII from 2021 to 2024*

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    Determination of the number of ψ(3686) events taken at BESIII

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    The number of ψ(3686) events collected by the BESIII detector during the 2021 run period is determined to be (2259.3±11.1)×106 by counting inclusive ψ(3686) hadronic events. The uncertainty is systematic and the statistical uncertainty is negligible. Meanwhile, the numbers of ψ(3686) events collected during the 2009 and 2012 run periods are updated to be (107.7±0.6)×106 and (345.4±2.6)×106, respectively. Both numbers are consistent with the previous measurements within one standard deviation. The total number of ψ(3686) events in the three data samples is (2712.4±14.3)×10^

    JUNO sensitivity on proton decay p → ν K + searches*

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    The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the pνˉK+ p\to \bar{\nu} K^+ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via pνˉK+ p\to \bar{\nu} K^+ is 36.9% ± 4.9% with a background level of 0.2±0.05(syst)±0.2\pm 0.05({\rm syst})\pm 0.2(stat) 0.2({\rm stat}) events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is 9.6×1033 9.6 \times 10^{33} years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies
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