The Experts below are selected from a list of 263607 Experts worldwide ranked by ideXlab platform
Yong-hoon Lee - One of the best experts on this subject based on the ideXlab platform.
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VTC Spring - Multiuser Scheduling Based on Reduced Feedback Information in Cooperative Communications
VTC Spring 2009 - IEEE 69th Vehicular Technology Conference, 2009Co-Authors: Yong-up Jang, Won-yong Shin, Yong-hoon LeeAbstract:We introduce a multiuser (MU) scheduling method for amplify-and-forward (AF) relay systems, which opportunis- tically selects both the transmission mode, i.e., either one- or two-hop transmission, and the desired user. A closed-form expression for the average achievable rates is derived under two transmissions with MU scheduling, and its asymptotic solution is also analyzed in the limit of large number N of mobile stations (MSs). Based on the analysis, we perform our two-step scheduling algorithm: the transmission mode selection followed by the user selection that needs partial Feedback for instantaneous signal-to- noise ratios (SNRs) to the base station (BS). We also analyze the average SNR condition where the MU diversity gain is fully exploited. In addition, it is examined how to further reduce a quantity of Feedback under certain conditions. The proposed scheduling algorithm shows the comparable achievable rates to those of optimal one using full Feedback Information, while its required Feedback Information is reduced below half of the optimal one.
He You - One of the best experts on this subject based on the ideXlab platform.
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Composite filtering with Feedback Information
Journal of Systems Engineering and Electronics, 2007Co-Authors: He You, Xiong Wei, Ma QiangAbstract:Abstract The optimal fusion solution with Feedback Information for a hybrid multisensor data fusion system is presented. In this system, a part of sensors process their data locally to produce local tracks, and another part of sensors only provide detection reports These tracks and detection reports are communicated to a central site where track fusion and composite filtering are performed. The comparative results on the simulations suggest the Feedback Information from the center can greatly improve the tracking performance of the local node.
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Relationship between track fusion solutions with and without Feedback Information
Journal of Systems Engineering and Electronics, 2003Co-Authors: He You, Xiong WeiAbstract:In distributed multisensor data fusion systems, there are two types of track fusion approaches. One is sensor track fusion with Feedback Information, the other is without Feedback Information. This paper proves that the solutions of sensor track fusion with and without Feedback Information are both optimal and equal.
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Multisensor Hierarchical Esitimation Algorithms with Feedback Information
2000Co-Authors: He YouAbstract:In order to inprove the tracking performances of some sensors and local nodes,the paper discusses the state estimation techniques in multilevel multisensor surveillance systems with Feedback Information.Based on the single sensor Kalman fitering equations with Feedback Information,this paper presents two level centralized,distributed and hybrid track level fusion methods with Feedback Information in multicoordinate systems.In the different Cartesian coordinates,several kinds of track level fusion methods with Feedback Information for three level multisensor data fusion systems are proposed,in which centralized distributed,distrbuted distributed and hybrid distributed estimation combination problems with Feedback Information are considered,and proves that two kinds of three level estimation solutions with or without Feedback Information are optimal and equivalent in the form of the theorem.The simulation results show that the multilevel multisensor data fusion system can not only increase the global estimation acuracy of target but also greatly improve the tracking perfomances of some sensors and local nodes by using the Feedback Information.
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Sensor track fusion with Feedback Information
1999Co-Authors: He You, P. Ying-ning, L. Da-jinAbstract:In multisensor tracking systems where sensors process their data locally to produce local tracks, these tracks are communicated to a central location where track fusion is performed. This paper addresses the issue of optimal track fusion with Feedback Information for similar and dissimilar synchronous sensors. It is shown that the multisensor data fusion system can not only increase the global estimation accuracy of target but also greatly improve the tracking performance of the local node by using Feedback Information. The proposed track fusion algorithm with Feedback Information is tested, using simulated tracks, and compared to a commonly used track fusion algorithm without Feedback Information.
Chen Qian-bin - One of the best experts on this subject based on the ideXlab platform.
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Multiuser Scheduling Based on Reduced Feedback Information in Relay Networks
Signal Processing, 2011Co-Authors: Chen Qian-binAbstract:This paper proposes a semi-distributed scheduling algorithm to decrease the Feedback of Channel State Information. According to the probability of Feedback interruption and total number of users,the threshold of channel state Information Feedback is set up respectively at base station and relay.In every slot,through the comparison with the threshold,users decide whether to Feedback the corresponding link Information about the signal to noise ratio.The base station,according to the Feedback from users,decide which transmission modes will be selected.In addition,this paper gives detailed theoretical derivation on performance index of the proposed algorithm,such as the number of Feedback users and the average achievable rates etc.Moreover,under the AF protocol,the fianl result shows the performance of system by using this scheme is corresponding to mathematical derivation.Furthermore,the proposed algorithm could greatly reduce(over 90%) the quantity of Feedback Information in the system.
Y. Sasaki - One of the best experts on this subject based on the ideXlab platform.
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Effect Of The Filtered Visual Feedback Information On Postural Control
[1990] Proceedings of the Twelfth Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1Co-Authors: Makoto Yoshizawa, Hiroshi Takeda, M. Ozawa, N. Honma, Y. SasakiAbstract:Effects of the filtered visual Feedback Information on the human postural control characteristics have been analyzed to examine the hypothesis that the visual Feedback Information used to stabilize the posture is processed in a discrete-time fashion by the postural control center in the brain. In the experiments, the test subject stood upright and was watching the image of a vertical line displayed in the three dimensional visor display. The signal of the image was filtered through a personal computer system. The body sway was analyzed when the parameter of each filter was changed. The results could support the hypothesis. It has been concluded that repetitive renewal of the visual Information with sampling period shorter than about 0.3sec to O.5sec is necessary for stabilization of the posture.
Kai-yuan Cai - One of the best experts on this subject based on the ideXlab platform.
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A cost-effective software testing strategy employing online Feedback Information
Information Sciences, 2018Co-Authors: Zhi Quan Zhou, Arnaldo Sinaga, Willy Susilo, Lei Zhao, Kai-yuan CaiAbstract:Abstract An online partitioning strategy is presented, in which test cases are selected based on Feedback Information collected during the testing process. The strategy differs from conventional approaches because the partitioning is performed online rather than off-line and because the partitioning is not based on program code or specifications. It can, therefore, be implemented in the absence of the source code or specification of the program under test. The cost-effectiveness of the proposed strategy has been empirically investigated with a set of subject programs, namely, SPACE, SED, GREP, and the Siemens Suite of Programs. The results demonstrate that the proposed strategy constantly achieves large savings in terms of the total number of test case executions needed to detect all faults.
