The last decade has witnessed the convergence of three giant worlds:electronics,computer science and telecommunications.The next decade should follow this convergence in most of our activities with the generalization of sensor networks.In particular with the progress in medicine,people live longer and the aging of population will push the development of wireless person- 相似文献
In this paper,we investigate the matched filter based spectrum sensing in a more reasonable cognitive radio(CR) scenario when the primary user(PU) has more than one transmit power levels,as regulated in most standards,i.e.,IEEE 802.11 Series,GSM,LTE,LTE-A,etc.This new multiple primary transmit power(MPTP) scenario is specialized by two different targets:detecting the presence of PU and identifying the power level.Compared to the traditional binary sensing where only the presence of PU is checked,SU may attain more information about the primary network(making CR more "intelligent") and design the subsequent optimization strategy.The key technology is the multiple hypothesis testing as opposed to the traditional binary hypothesis testing.We discuss two situations under whether the channel phase is known or not,and we derive the closed form solutions for decision regions and several performance metrics,from which some interesting phenomenons are observed and the related discussions are presented.Numerical examples are provided to corroborate the proposed studies. 相似文献
A 25 Gbit/s clock and data recovery(CDR) circuit with 1:2 demultiplexer for 100 Gbit/s Ethernet(100 Gb E) optical interconnects has been designed and fabricated in Taiwan Semiconductor Manufacture Company(TSMC) 65 nm complementary metal-oxide-semiconductor(CMOS) technology. A novel quadrature voltage-controlled-oscillator(QVCO) structure adopts two pairs of transconductance cell and inverters to acquire rail-to-rail output swing. A half-rate bang-bang phase detector adopts four flip-flops array to sample the 25 Gbit/s input data and align the data phase, so the 25 Gbit/s data are retimed and demultiplexed into two paths 12.5 Gbit/s output data. Experimental results show that the recovered clock exhibits a peak-to-peak jitter of 7.39 ps and the recovered data presents a peak-to-peak jitter of 7.56 ps, in response to 312-1 pseudorandom bit sequence(PRBS) input. For 1.2 V voltage supply, the CDR circuit consumes 92 m W(excluding output buffers). 相似文献
This article addresses a new pattern mining problem in time series sensor data, which we call correlated attribute pattern mining. The correlated attribute patterns (CAPs for short) are the sets of attributes (e.g., temperature and traffic volume) on sensors that are spatially close to each other and temporally correlated in their measurements. Although the CAPs are useful to accurately analyze and understand spatio-temporal correlation between attributes, the existing mining methods are inefficient to discover CAPs because they extract unnecessary patterns. Therefore, we propose a mining method Miscela to efficiently discover CAPs. Miscela can discover not only simultaneous correlated patterns but also time delayed correlated patterns. Furthermore, we extend Miscela to automatically search for correlated patterns with any time delays. Through our experiments using three real sensor datasets, we show that the response time of Miscela is up to 20.84 times faster compared with the state-of-the-art method. We show that Miscela discovers meaningful patterns for urban managements and environmental studies.
