RF Energy Harvesting and Information Transmission in IoT Relay Systems based on Time Switching and NOMA
Chapter, Chapter, Peer reviewed
Accepted version
Date
2018Metadata
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Original version
Rauniyar A, Engelstad P.E., Østerbø O: RF Energy Harvesting and Information Transmission in IoT Relay Systems based on Time Switching and NOMA. In: Gregory. 2018 28th International Telecommunication Networks and Applications Conference (ITNAC), 2018. IEEE conference proceedings p. 168-174 https://dx.doi.org/10.1109/ATNAC.2018.8615403Abstract
A huge expansion of billions of Internet of Things (IoT) sensor and devices is expected over the next few years which will consume more power. Therefore, energy efficiency is a major concern for the development of fifth generation (5G) wireless systems. In wireless communication systems, energy harvesting (EH) is an emerging paradigm that allows the sensor nodes to recharge themselves through radio frequency (RF) signals directed to them from the source node and then relaying or transmitting the information. Although a myriad of works have been carried out in the literature for EH, the absolute vast majority of those works only consider RF EH at relay node and transmission of source node data successfully to its destination node. Those approaches do not consider the data transmission of the relay node that may be an IoT node which needs to transmit its data along with the source node data to their respective destinations. Thus, such approaches are clearly ineffective for energy efficient IoT relay systems. In this paper, we rather focus on RF EH and information transmission based on time switching (TS) relaying and non-orthogonal multiple access (NOMA) for IoT relay systems. A source node information data is relayed through power constrained IoT relay node that first harvests the energy from source node RF signal using TS protocol and then transmits source node information along with its information using NOMA protocol. We have mathematically derived analytical expressions for outage probability, throughput and sum-throughput for our proposed system. We have also formulated an algorithm to find out optimal TS factor that maximizes the sum-throughput for our proposed system. Our proposed system analytical results are validated by the simulation results.