Performance Analysis of URLL Energy-Harvesting Cognitive-Radio IoT Networks With Short Packet and Diversity Transmissions

• Main Authors: Mohammad Reza Amini, Mohammed W. Baidas
• Format: Article
• Language: English
• Published: IEEE 2021-01-01
• Series: IEEE Access
• Subjects: Cognitive-radio; energy-harvesting; finite blocklength; Internet-of-Things; low-latency; ultra-reliability
• Online Access: https://ieeexplore.ieee.org/document/9439472/

The advent of the Internet-of-Things (IoT) and proliferation of wireless devices and systems have put stringent requirements on reliability and latency, in addition to the scarcity of energy and spectrum resources. More importantly, ultra-reliability and low-latency (URLL) combined with concepts of energy-harvesting (EH) and cognitive-radio (CR) make the analysis of IoT networks much more complex. This paper analyzes the performance of uplink EH-CR-IoT networks with URLL requirements. Analytical expressions for IoT network metrics, namely, average packet latency, reliability, and energy-efficiency are derived, while incorporating diversity transmissions under the finite blocklength (FBL) regime. The effect of network parameters, such as number of resource blocks allocated to each IoT user equipment (UE), blocklength, and number of packet replicas is examined on the network metrics, and their tradeoffs are discussed. Finally, the derived expressions are utilized to maximize the energy-efficiency of the IoT UEs subject to energy-causality and URLL constraints.