Computing Energy Efficiency Maximization Strategy of Wireless Powered Mobile Edge Computing Systems
In order to solve the computing energy efficiency optimization problem of the wireless powered mobile edge computing(MEC) system,a computing resource allocation strategy of wireless powered MEC system based on non-orthogonal multiple access(NOMA) was proposed,which applied a nonlinear energy harvesting model to mo-bile devices. By jointly optimizing the calculation frequency,execution time,base station transmission power,equipment transmission power,offloading time and energy collection time of MEC server and mobile equipment,this strategy could fully utilize the available computing resources of mobile devices and MEC servers,improve de-vice throughput and computing bits,and thus maximize system computing energy efficiency. Then the joint optimi-zation problem was transformed into a non-convex fractional programming problem,and an iterative algorithm based on Dinkelbach was designed to obtain the optimal resource allocation scheme. The comparative simulation results showed that the resource allocation strategy could achieve higher computing energy efficiency and better performance gains.
wireless powered mobile edge computing(MEC) systemnon-orthogonal multiple access(NOMA)computing energy efficiencyenergy harvestingresource allocationcomputing offload
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维普
