This paper formulates and solves a joint-optimization problem whose objective is to maximize both the sum-throughput and fairness of a wireless powered communication network (WPCN) with radio frequency (RF) energy harvesting. An algorithm based on the multi-source blind adaptive beamforming with hybrid protocol that maximizes the sum-throughput and fairness (MS-BABF/Hybrid-STF) is proposed and analyzed. Numerical results show that the jointly optimized MS-BABF/Hybrid-STF protocol achieves a 36.7% increase in fairness compared to a single input, single output configuration in a dynamic environment. The MS-BABF/Hybrid-STF protocol also delivers an average of 19.1% fairness gain when the number of sensors is varied from 2 to 8 compared to a similar protocol that optimizes only the sum-throughput of a WPCN instead. The findings are significant for future widespread adoption of WPCN systems powered by RF energy sources in the real world by allowing fairer throughputs between sensors. In turn, the transmission of sensors' sensed data with the required quality can be supported even when there are ongoing changes in channel quality.


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    Title :

    Sum-Throughput and Fairness Optimization of a Wireless Energy Harvesting Sensor Network


    Contributors:


    Publication date :

    2019-09-01


    Size :

    626033 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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