Abstract

Energy harvesting tags with cooperative communication capabilities are recently emerging as a viable infrastructure for internet of things (IoT) applications. This letter studies the cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of tags to communicate with the reader either directly or by cooperating with neighboring tags. We formulate the problem as a Markov decision process (MDP). The simulation results are provided to show the performance of the cooperative transmission policy under various energy harvesting scenarios.

Highlights

  • Cooperative communication and energy harvesting are practical solutions to overcome the battery and communication reliability problems in wireless devices

  • Energy-harvesting active networked tags (EnHANTs) are recently proposed as tiny devices that can be attached to common place objects [1], [2]

  • We evaluate the performance of the optimal cooperative transmission policy by considering various energy harvesting scenarios

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Summary

Introduction

Cooperative communication and energy harvesting are practical solutions to overcome the battery and communication reliability problems in wireless devices. An EnHANT-equipped object might lack sufficient energy to respond directly to the reader when the reader is outside the communication range In such a case, to sustain communication, the object can link its information to a neighboring object, in which the neighboring object forwards the information to the reader by using the concept of a relay [4] -- [6]. In [8], the authors studied energy efficient scheduling strategies for wireless sensor networks with energy-harvesting. They considered a case where a node may use either direct transmission or a cooperative relay transmission and formulated the problem using Markov decision process (MDP). We consider a cooperative transmission strategy that optimizes the long-term average throughput by taking into account both the identification request state and energy constrains

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