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A new wideband LNA using a g_m-boosting technique

Journal of Semiconductors 2014年第1期35卷 84-90页

作者：陈亮李智群曹佳吴晨健张萌 Institute of RF- & OE- ICs Southeast University RFIC and System Engineering Research Center of Ministry of Education of China Southeast University Jiangsu Provincial Key Laboratory of Sensor Network Technology

A new broadband low-noise amplifier （LNA） is proposed. The conventional common gate （CG） LNA exhibits a relatively high noise figure, so active gin-boosting technology is utilized to restrain the noise generated by the input transistors and reduce the noise figure. Theory, simulation and measurement are shown. An implemented prototype using 0.13 μm CMOS technology is evaluated using on-wafer probing. S11 and S22 are below -10 dB across 0.1-5 GHz. Measurements also show a gain of 18.3 dB with a 3 dB bandwidth from 100 MHz to 2.1 GHz and an ⅡP3 of-7 dBm at 2 GHz. The measured noise figure is better than 2.5 dB below 2.1 GHz, is better than 4.5 dB below 5 GHz, and at 500 MHz, it gets its minimum value 1.8 dB. The LNA consumes 9 mA from 1.5 V supply and occupies an area of 0.04 mm^2.

关键词： broadband LNA gm-boosting CMOS

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A fully integrated CMOS IF module for C-band RF transceiver

A fully integrated CMOS IF module for C-band RF transceiver

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IEEE International Wireless Symposium (IWS)

作者： Kai Zhang Zhiqun Li Zengqi Wang Yang Guo Tailun Sun Institute of RF- & OE-ICs Southeast University Nanjing China Jiangsu Provincial key Laboratory of Sensor Network Technology Wuxi China RFIC and System Engineering Research Center Ministry of Education of China Nanjing China

This paper presents a fully integrated IF module which can receive or transmit signal with only one port. The switching time between reception and transmission is less than 3μs. In the state of reception, the IF module can convert differential signal to single-ended signal. Simulation results show 3.2dB power gain and 11.65dBm OP1dB while drawing 45mA from a 3.3V supply. In the state of transmission, the IF module can convert single-ended signal to differential signal. Simulation results show 0~15dB programmable voltage gain and -3.5dBm IP1dB while drawing 16mA from a 3.3V supply. At working frequency of 1.3GHz~1.4GHz, VSWRs can attain high performance in two states, both are less than 1.5* 1. The chip is designed in 0.18μm CMOS technology, the die area is 1.5*1.5 mm2. All the components of the linearization scheme are designed on-chip enabling maintenance of a single chip transceiver solution.

关键词： Impedance matching Radio frequency CMOS integrated circuits Ports (Computers) Transceivers Power amplifiers Electronics packaging

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Design of ultralow power receiver front-ends for 2.4 GHz wireless sensor network applications

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Journal of Semiconductors 2014年第1期35卷 104-111页

作者：张萌李智群王曾祺吴晨健陈亮 Institute of RF- & OE-ICs Southeast University Engineering Research Center of RF-ICs & RF-Systems Ministry of Education Southeast University Jiangsu Provincial Key Laboratory of Sensor Network Technology

This paper presents the design of an ultralow power receiver front-end designed for a wireless sensor network （WSN） in a 0.18 μm CMOS process. The author designs two front-ends working in the saturation region and the subthreshold region respectively. The front-ends contain a two-stage cross-coupling cascaded common-gate （CG） LNA and a quadrature Gilbert IQ mixer. The measured conversion gain is variable with high gain at 24 dB and low gain at 7 dB for the saturation one, and high gain at 22 dB and low gain at 5 dB for the subthreshold one. The noise figure （NF） at high gain mode is 5.1 dB and 6.3 dB for each. The input 1 dB compression point （IPldB） at low gain mode is about -6 dBm and -3 dBm for each. The front-ends consume about 2.1 mA current from 1.8 V power supply for the saturation one and 1.3 mA current for the subthreshold one. The measured results show that, comparing with the power consumption saving, it is worth making sacrifices on the performance for using the subthreshold technology.

关键词： receiver front-end wireless sensor network （WSN） VG-LNA IQ-mixer low power subthresholdbiased

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A parallel HEVC encoder scheme based on Multi-core platform

A parallel HEVC encoder scheme based on Multi-core platform

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2015 4th National Conference on Electrical,Electronics and Computer engineering(NCEECE 2015)

作者： Shu Jun Hu Dong Education Ministry’s Key Lab of Broadband Wireless Communication and Sensor Network Technology Education Ministry’s Engineering Research Center of Ubiquitous Network and Health Service System Jiangsu Province’s Key Lab of Image Procession and Image Communications Nanjing University of Post and Telecommunications

ISBN: (纸本)9781510819085

In this paper, we propose a parallel HEVC encoder scheme based on multi-core platform, which provides maximized parallel scalability by exploiting two-level parallelism, namely, the frame level parallelism and the CTB level parallelism. Inspired by the intra-CTB row level parallelism of WPP in HEVC, we investigate the inter-frame CTB prediction dependency to its reference CTBs, and find the inter-CTB correlation. Using this inter-correlation, we divide a frame into CTB units and create CTB-row level coding threads when their corresponding reference CTBs are available. Each thread is bonded to a processing core, therefore, both intra- and inter-CTB rows can be encoded in parallel. Moreover, we introduce a priority scheduling mechanism to control the coding threads. Experiments on Tilera-Gx36 multi-core platform show that, compared with serial execution, the proposed method achieves 3.6 and 4.3 times speedup for 1080 P and 720 P video sequences, respectively.

关键词： HEVC multi-core platform parallel processing frame-level CTB-level

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A feature selection algorithm based on Hoeffding inequality and mutual information

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2015年第11期8卷 433-444页

作者： Yin, Chunyong Feng, Lu Ma, Luyu Yin, Zhichao Wang, Jin School of Computer and Software Jiangsu Key Laboratory of Meteorological Observation and Information Processing Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China Nanjing No.1 Middle School Nanjing China

With the rapid development of the Internet, the application of data mining in the Internet is becoming more and more extensive. However, the data source’s complex feature redundancy leads that data mining process becomes very inefficient and complex. So feature selection research is essential to make data mining more efficient and simple. In this paper, we propose a new way to measure the correlation degree of internal features of dataset which is a mutation of mutual information. Additionally we also introduce Hoeffding inequality as constraint of constructing algorithm. During the experiments, we use C4.5 classification algorithm as test algorithm and compare HSF with BIF(feature selection algorithm based on mutual information). Experiments results show that HSF performances better than BIF[1] in TP and FP rate, what’s more the feature subset obtained by HSF can significantly improve the TP, FP and memory usage of C4.5 classification algorithm. © 2015 SERSC.

关键词： Feature Selection

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OGLE-2015-BLG-1649Lb: A gas giant planet around a low-mass dwarf

arXiv

引用

arXiv 2019年

作者： Nagakane, M. Lee, Chien-Hsiu Koshimoto, N. Suzuki, D. Udalski, A. Beaulieu, J.P. Sumi, T. Bennett, D.P. Bond, I.A. Rattenbury, N. Bachelet, E. Dominik, M. Abe, F. Barry, R.K. Bhattacharya, A. Donachie, M. Fujii, H. Fukui, A. Hirao, Y. Itow, Y. Kamei, Y. Kondo, I. Li, M.C.A. Matsubara, Y. Matsuo, T. Miyazaki, S. Muraki, Y. Ranc, C. Shibai, H. Suematsu, H. Sullivan, D.J. Tristram, P.J. Yamakawa, T. Yonehara, A. Mróz, P. Poleski, R. Skowron, J. Szymański, M.K. Soszyński, I. Pietrukowicz, P. Kozlowski, S. Ulaczyk, K. Bramich, D.M. Cassan, A. Figuera Jaimes, R. Horne, K. Hundertmark, M. Mao, S. Menzies, J. Schmidt, R. Snodgrass, C. Steele, I.A. Street, R. Tsapras, Y. Wambsganss, J. Jørgensen, U.G. Bozza, V. Longã, P. Peixinho, N. Skottfelt, J. Southworth, J. Andersen, M.I. Burgdorf, M.J. D’Ago, G. Evans, D.F. Hinse, T.C. Korhonen, H. Rabus, M. Rahvar, S. Department of Earth and Space Science Graduate School of Science Osaka University 1-1 Machikaneyama Toyonaka Osaka560-0043 Japan 650 N Aohoku Pl. HiloHI96720 United States Department of Astronomy Graduate School of Science University of Tokyo 7-3-1 Hongo Bunkyoku Tokyo113-0033 Japan National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo Sagamihara Kanagawa252-5210 Japan Astronomical Observatory University of Warsaw Al. Ujazdowskie 4 Warszawa00-478 Poland Sorbonne Universités CNRS UPMC Univ Paris 06 UMR 7095 Institut d’Astrophysique de Paris ParisF-75014 France Laboratory for Exoplanets and Stellar Astrophysics NASA/Goddard Space Flight Center GreenbeltMD20771 United States Department of Astronomy University of Maryland College ParkMD20742 United States Institute of Information and Mathematical Sciences Massey University North Shore Mail Centre Private Bag 102-904 Auckland New Zealand Department of Physics University of Auckland Private Bag 92019 Auckland New Zealand Las Cumbres Observatory Global Telescope Network 6740 Cortona Drive suite 102 GoletaCA93117 United States Centre for Exoplanet Science SUPA School of Physics & Astronomy University of St Andrews North Haugh St AndrewsKY16 9SS United Kingdom Institute for Space-Earth Environmental Research Nagoya University Nagoya464-8601 Japan Instituto de Astrofísica de Canarias Vía Láctea s/n La Laguna TenerifeE-38205 Spain School of Chemical and Physical Sciences Victoria University Wellington New Zealand University of Canterbury Mt. John Observatory P.O. Box 56 Lake Tekapo8770 New Zealand Department of Physics Faculty of Science Kyoto Sangyo University Kyoto603-8555 Japan Department of Astronomy Ohio State University 140 W. 18th Ave. ColumbusOH43210 United States Department of Physics University of Warwick Gibbet Hill Road CoventryCV

We report the discovery of an exoplanet from the analysis of the gravitational microlensing event OGLE-2015-BLG-1649 that challenges the core accretion model of planet formation and appears to support the disk instability model. The planet/host-star mass ratio is q = 7.2 × 10−3 and the projected separation normalized to the angular Einstein radius is s = 0.9. We conducted high-resolution follow-up observations using the IRCS camera on the Subaru telescope and are able to place an upper limit on the lens flux. From these measurements we are able to exclude all host stars greater than or equal in mass to a G-type dwarf. We conducted a Bayesian analysis with these new flux constraints included as priors resulting in estimates of the masses of the host star and planet. These are ML = 0.34 ± 0.19 M☉ and Mp = 2.5+1−1..54 MJup, respectively. The distance to the system is DL = 4.23+1−1..5164 kpc. The projected star-planet separation is a⊥ = 2.07+0−0..6577 AU. The estimated relative lens-source proper motion, ∼ 7.1 mas/yr, is fairly high and thus the lens can be better constrained if additional follow-up observations are conducted several years after the event. Copyright © 2019, The Authors. All rights reserved.

关键词： Gravitation

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Improved locality-sensitive hashing method for the approximate nearest neighbor problem

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Chinese Physics B 2014年第8期23卷 217-225页

作者：陆颖华马廷淮钟水明曹杰王新 Abdullah Al-Dhelaane Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology School of Computer & Software Nanjing University of Information Science & Technology School of Economic & Management Nanjing University of Information Science & Technology Huafeng Meteorological Media Group Computer Science Department College of Computer and Information Science King Saud University

In recent years, the nearest neighbor search （NNS） problem has been widely used in various interesting applications. Locality-sensitive hashing （LSH）, a popular algorithm for the approximate nearest neighbor problem, is proved to be an efficient method to solve the NNS problem in the high-dimensional and large-scale databases. Based on the scheme of p-stable LSH, this paper introduces a novel improvement algorithm called randomness-based locality-sensitive hashing （RLSH） based on p-stable LSH. Our proposed algorithm modifies the query strategy that it randomly selects a certain hash table to project the query point instead of mapping the query point into all hash tables in the period of the nearest neighbor query and reconstructs the candidate points for finding the nearest neighbors. This improvement strategy ensures that RLSH spends less time searching for the nearest neighbors than the p-stable LSH algorithm to keep a high recall. Besides, this strategy is proved to promote the diversity of the candidate points even with fewer hash tables. Experiments are executed on the synthetic dataset and open dataset. The results show that our method can cost less time consumption and less space requirements than the p-stable LSH while balancing the same recall.

关键词： approximate nearest neighbor problem locality-sensitive hashing

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MRG-DBSCAN: An improved DBSCAN clustering method based on map reduce and grid

International Journal of Database Theory and Application

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International Journal of Database Theory and Application 2015年第2期8卷 119-128页

作者： Ma, Li Gu, Lei Li, Bo Qiao, Shouyi Wang, Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Key Laboratory of Meteorological Disaster Ministry of Education Nanjing University of Information Science and Technology Nanjing China CMA Research Centre for Strategic Development Beijing China

DBSCAN is a density-based clustering algorithm. This algorithm clusters data of high density. The traditional DBSCAN clustering algorithm in finding the core object, will use this object as the center core, extends outwards continuously. At this point, the core objects growing, unprocessed objects are retained in memory, which will occupy a lot of memory and I/O overhead, algorithm efficiency is not high. In order to ensure the high efficiency of DBSCAN clustering algorithm, and reduce its memory footprint. In this paper, the original DBSCAN algorithm was improved, and the G-DBSCAN algorithm is proposed. G-DBSCAN algorithm reduces the number of query object as a starting point. Put the data into the grid, with the center point of the data in the grid to replace all the grid points as the algorithm input. The query object will be drastically reduced, thus improving the efficiency of the algorithm, reduces the memory footprint. In order to make the G-DBSCAN algorithm can adapt to large data processing, we will parallelize the G-DBSCAN algorithm, and combining it with Map Reduce framework. The results prove that G-DBSCAN and MRG-DBSCAN algorithm are feasible and effective. © 2015 SERSC.

关键词： Cluster analysis

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A new combination prediction model for short-term wind farm output power based on meteorological data collected by WSN

International Journal of Control and Automation

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International Journal of Control and Automation 2014年第1期7卷 171-180页

作者： Ma, Li Li, Bo Yang, Zhen Bin Du, Jie Wang, Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 China Key Laboratory of Meteorological Disaster of Ministry of Education Nanjing University of Information Science and Technology Nanjing 210044 China CMA Public Meteorological Service Centre Beijing 100081 China

The prediction of wind farm output power is considered as an effective way to increase the wind power capacity and improve the safety and economy of power system. It is one of the hot research topics on wind power. The wind farm output power is related to many factors such as wind speed, temperature, etc., which is difficult to be described by some mathematical expression. In this paper, Back Propagation (BP) neural network algorithm is respectively combined with genetic algorithm (GA) and particle swarm optimization (PSO) to establish the combination prediction model of the short-term wind farm output power based on meteorological data collected by Wireless sensor network (WSN). The meteorological data is used to determine the input variables of the BP neural network. Meanwhile, the GA and the PSO is respectively used to adjust the value of BP's connection weight and threshold dynamically. Then the trained GA-BP and PSO-BP neural network are used to predict the wind power by combination method. The experiment results show that our method has better prediction capability compared with that using BP neural network, GA-BP neural network and PSO-BP neural network alone. © 2014 SERSC.

关键词： Wireless sensor networks

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Compact and Tunable Mid-IR Light Source Based on a Dual-Wavelength Fiber Laser

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Chinese Physics Letters 2013年第11期30卷 106-108页

作者： CHANG Jian-Hua WANG Ting-Ting ZHANG Chuang GE Yi-Xian TAO Zai-Hong Jiangsu Key Laboratory of Meteorological Observation and Information Processing Nanjing University of Information Science&TechnologyNanjing 210044 Jiangsu Technology&Engineering Center of Meteorological Sensor Network Nanjing University of Information Science&TechnologyNanjing 210044

A compact,tunable mid-IR difference-frequency generation(DFG)light source based on a dual-wavelength fiber laser and a 5mol%MgO-doped periodically poled lithium niobate(MgO:PPLN)crystal is developed and *** output power of 233μW is achieved with a conversion efficiency of 0.1%/*** mid-IR wavelength can be tuned between 3308 nm and 3314 nm by changing the temperature of a pair of fiber Bragg grating(FBG)taking as cavity mirrors in the dual-wavelength fiber laser from 26.5°C to 106.5°C.

关键词： fiber tunable Dual

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