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RESEARCH PRODUCT
Energy-Efficient Resource Allocation and User Scheduling for Collaborative Mobile Clouds With Hybrid Receivers
Zheng ChangTapani RistaniemiJie GongZhisheng Niusubject
Optimization problemComputer Networks and CommunicationsComputer scienceDistributed computingresource allocationAerospace EngineeringCloud computing02 engineering and technology7. Clean energyScheduling (computing)Frequency allocation0203 mechanical engineeringTelecommunications link0202 electrical engineering electronic engineering information engineeringWirelessElectrical and Electronic Engineeringta113collaborative mobile cloudscontent distributionbusiness.industryuser scheduling020302 automobile design & engineering020206 networking & telecommunicationsEnergy consumptionpower allocationuser cooperationgreen communicationsAutomotive EngineeringConvex optimizationResource allocationsubchannel allocationbusinessEfficient energy usedescription
In this paper, we study the resource allocation and user scheduling algorithm for minimizing the energy cost of data transmission in the context of OFDMA collaborative mobile cloud (CMC) with simultaneous wireless information and power transfer (SWIPT) receivers. The CMC, which consists of several collaborating MTs offers one potential solution for downlink con- tent distribution and for the energy consumption reduction at the terminal side. Meanwhile, as RF signal can carry both informa- tion and energy simultaneously, the induced SWIPT has gained much attention for energy efficiency design of mobile nodes. Previous work on the design of CMC system mainly focused on the cloud formulation or energy efficiency investigation, while how to allocate the radio resource and schedule user transmission lacks attention. With the objective to minimize the system energy consumption, an optimization problem which jointly considers subchannel assignment, power allocation and user scheduling for a group of SWIPT receivers has been presented. The formulated problem is addressed through the convex optimization technique. Simulation results demonstrate that the proposed user scheduling and resource allocation algorithms can achieve significant energy saving performance.
year | journal | country | edition | language |
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2016-12-01 | IEEE Transactions on Vehicular Technology |