Cognitive Wireless Sensor Networks (CWSN) are known to be energy constrained because they are required to perform cognitive functions in addition to sensing, which reduces the lifetime of CWSN. RF Wireless Energy Harvesting (RFWEH) is known to improve network lifetime by compensating energy losses through harvesting gain without any additional hardware. However, the allocation of time slots for energy harvesting results in degradation of network parameters such as latency and throughput. In this paper, we propose an energy harvesting MAC protocol (R-MAC) for CWSN that balances network energy losses with harvested energy gains, thereby resulting in a self sustainable CWSN. This is done such that both latency and throughput remain close to predefined target values. R-MAC employs TDMA and relies on clustering for creation and dissemination of the schedule. We also propose an algorithm to add harvesting slots based on a recursive regression technique to achieve the energy balance. Using simulation we compared its performance with the well known cognitive KoNMAC protocol, after incorporating energy harvesting in it. The simulation results show that the proposed protocol increases the lifetime of the CWSN nodes substantially, resulting in an energy self sufficient network while maintaining throughput and latency within acceptable limits.


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    Title :

    An Energy Harvesting MAC Protocol for Cognitive Wireless Sensor Networks


    Contributors:


    Publication date :

    2021-04-01


    Size :

    2113247 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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