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您的检索式：作者名="Jiang Linling"
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| 1 | Low-Complexity Joint Channel Estimation and Symbol Detection for OFDMA Systems显示文摘In this paper,we propose a joint channel estimation and symbol detection(JCESD)algorithm relying on message-passing algorithms(MPA)for orthogonal frequency division multiple access(OFDMA)systems.The channel estimation and symbol detection leverage the framework of expectation propagation(EP)and belief propagation(BP)with the aid of Gaussian approximation,respectively.Furthermore,to reduce the computation complexity involved in channel estimation,the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula.Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%,compared with the traditional linear minimum mean square error(LMMSE)algorithm,and can approach to the bit error rate(BER)performance bound of perfectly known channel state information within 0.1 dB. | Rui Xin Zuyao Ni Sheng Wu Linling Kuang Chunxiao Jiang | 2019 | China Communications2019，16，7： | 4 |
| 2 | Twisted intra-molecular electron transfer phenomenon of dansyl immobilized on chitosan film and its sensing property to the composition of ethanol-water mixtures显示文摘 | Ding Liping Fang Yu Jiang Linling | 2005 | Thin Solid Films2005，478，12： | 1 |
| 3 | Beam Scheduling with Various Mission Demands in Data Relay Satellite Systems显示文摘Beam scheduling is one of the most important issues regarding data relay satellite systems,which can improve the utilization efficiency of limited system resources by programming beam allocation for relay missions.The ever-increasing relay missions create a substantial challenge for beam scheduling due to an increase in different mission demands.The cooperative usage of different beams further increases the complexity of this problem.Therefore,we develop a novel optimization method to solve the beam scheduling problem for the scenario of various mission demands in the data relay satellite system(DRSS).Based on the analysis of mission demands and resource features,we first construct a heterogeneous parallel machines scheduling model to formulate the beam scheduling problem in the DRSS.To solve this complicated model,we investigate the matching method between mission demands and beam resources,and introduce two concepts,the loose duration and the number of available beams,to make the matching process more effective.Then,the following three algorithms are proposed.Our first approach,the maximized completion probability algorithm(MCPA),applies a greedy strategy based on the new concepts to allocate beams for missions;and two improved versions of this algorithm are also presented,which employ the strategies of mission insertion optimization and mission sequence optimization,respectively.Our simulation results show that the proposed algorithms are superior to the existing algorithms in terms of the scheduled missions,the weight of scheduled missions,and the processing time,which significantly improves the performance of beam scheduling in the DRSS. | Boyu Deng Chunxiao Jiang Jingchao Wang Linling Kuang | 2021 | Journal of Communications and Information Networks2021，6，4： | 0 |
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