IEEE Internet of Things Journal · 2018 · 55 citations · 41 references
EngineeringComputer EngineeringElectrical EngineeringComputer NetworksInternet Of ThingsWireless CommunicationsCooperative CommunicationIot NetworkingMassive Multiple-input Multiple-outputNetwork Information TheoryWireless NetworksWireless Sensor NetworksDecode-forward RelayingEnergy Optimization AlgorithmsEnergy-efficient CommunicationEnergy-efficient Data TransmissionEnergy-efficient Iot DesignEnergy-efficient NetworkingEnergy-efficient Resource AllocationPower Allocation In Cooperative Networks
To meet the requirements of high energy efficiency (EE) and large system capacity for the fifth-generation Internet of Things (IoT), the use of massive multiple-input multiple-output technology has been launched in the massive IoT (mIoT) network, where a large number of devices are connected and scheduled simultaneously. This paper considers the energy-efficient design of a multipair decode-and-forward relay-based IoT network, in which multiple sources simultaneously transmit their information to the corresponding destinations via a relay equipped with a large array. In order to obtain an accurate yet tractable expression of the EE, first, a closed-form expression of the EE is derived under an idealized simplifying assumption, in which the location of each device is known by the network. Then, an exact integral-based expression of the EE is derived under the assumption that the devices are randomly scattered following a uniform distribution and transmit power of the relay is equally shared among the destination devices. Furthermore, a simple yet efficient lower bound of the EE is obtained. Based on this, finally, a low-complexity energy-efficient resource allocation strategy of the mIoT network is proposed under the specific quality-of-service constraint. The proposed strategy determines the near-optimal number of relay antennas, the near-optimal transmit power at the relay, and near-optimal density of active mIoT device pairs in a given coverage area. Numerical results demonstrate the accuracy of the performance analysis and the efficiency of the proposed algorithms.
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