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Articles by Jinkuan Wang
Total Records ( 4 ) for Jinkuan Wang
  Liqun Shan , Jinkuan Wang , Yanchao Zhao and Yanchang Liu
  This study has addressed the problem of data aggregation scheduling problem to minimize the latency in wireless sensor networks (WSNs). An efficient distributed synchronous aggregation scheduling method is proposed to structure a collision-free schedule for data aggregation in WSNs. By using a Connected Dominating Set (CDS) as an aggregation tree we implement the synchronous aggregation scheduling. We prove that the latency of the aggregation schedule generated by our algorithm is at most 4δ+15R-16 time-slots where R is the network radius and δ is the maximum node degree in the communication graph of the original network. Analysis and simulation results show the validity and superiority of the algorithm.
  Ruiyan Du , Jinkuan Wang , Yanli Bo and Liang Cui
  Compressive sensing is an emerging area which uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compressible signals. This study considered the carrier frequency offset estimation problem for interleaved orthogonal frequency-division multiple-access uplink systems. A new carrier frequency offset estimation method based on the compressive sensing theory is proposed to estimate the carrier frequency offsets in interleaved OFDMA uplink systems. The presented method can effectively estimate all carrier frequency offsets of the active users by finding the sparest coefficients. Simulation results are presented to verify the efficiency of the proposed approach.
  Liqun Shan , Jinkuan Wang and Wei Wei
  In Wireless Sensor Networks (WSNs), each sensor obtains data and have to communicate these data to a central node. Because sensors are battery powered they are highly energy constrained. Data aggregation can be used to combine data of several sensors into a single message, thus reducing the data traffic and the power consumption. This study has considered the problem of maximizing the time at which the first node with data aggregation in WSNs drains out of energy. It investigated optimal data aggregation routing for achieving the goal above. The problem is formulated as a linear programming problem. By solving the network lifetime optimization problem, the optimal solutions and the distributed implementation can be obtained that are based on the primal-dual decomposition. Simulation results indicate that the algorithm is superior to the existing methods.
  Peng Han , Jinkuan Wang , Yan Li and Yinghua Han
  The large adoption of hybrid renewable energy systems and the increasing power requirements of residential loads brings significant challenges to the construction and operation of the micro-grid systems. In this study, the agent-based modelling methodology is proposed to proper model and assess the discarded energy in the micro-grid. With the integration of the agent-based modelling and the system dynamic approach, the proposed approach contributes to a micro-grid model that is hierarchically constituted by micro-grid management layer and component layer. The system dynamics modelling is adopted in the management layer to model the energy consumption in the micro-grid while the object-oriented agent-based modelling is adopted to generate the main components. Furthermore, this study also proposed a comprehensive micro-grid operation simulation system, through which the observation and assessment of the proposed model can be achieved. Monte Carlo simulations show that the model and system can comprehensively reflect the energy consumption and generation in the micro-grid, providing preferred quantitate assessment for the micro-grid operation economical-efficiency and security with various HRES penetrations and time scales. The proposed methodology of this study will be beneficial for the study of the micro-grid discarded energy assessment and can be further utilized to the energy management policy evaluation, electricity consumption prediction and HRES deployment optimization.
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