Energy Efficient Resource Allocation and User Scheduling for Collaborative Mobile Clouds with Hybrid Receivers
Chang, Z., Gong, J., Ristaniemi, T., & Niu, Z. (2016). Energy Efficient Resource Allocation and User Scheduling for Collaborative Mobile Clouds with Hybrid Receivers. IEEE transactions on vehicular technology, 65(12), 9834-9846. https://doi.org/10.1109/TVT.2016.2525821
Published inIEEE transactions on vehicular technology
© 2016 IEEE. This is a final draft version of an article whose final and definitive form has been published by IEEE. Published in this repository with the kind permission of the publisher.
In this paper, we study the resource allocation and user scheduling algorithm for minimizing the energy cost of data transmission in the context of orthogonal frequency-division multiple-access (OFDMA) collaborative mobile clouds (CMCs) with simultaneous wireless information and power transfer receivers. The CMC, which consists of several collaborating mobile terminals, offers one potential solution for downlink content distribution and for energy consumption (EC) reduction. Previous work on the design of the CMC system mainly focused on cloud formulation or energy efficiency (EE) investigation, whereas how to allocate the radio resource and schedule user transmission has not gotten much attention. With the objective of minimizing system EC, an optimization problem that jointly considers subchannel assignment, power allocation, and user scheduling has been presented. We propose different algorithms to address the formulated problem based on the convex optimization technique. Simulation results demonstrate that the proposed user scheduling and resource allocation algorithms can achieve significant EE performance. ...
PublisherInstitute of Electrical and Electronics Engineers
Publication in research information system
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Related funder(s)Academy of Finland
Funding program(s)Joint International Project, AoF
Additional information about funding10.13039/501100002341-Academy of Finland; National Basic Research Program of China (973 Program); 10.13039/501100001809-National Science Foundation of China (NSFC).
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