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https://dspace.iiti.ac.in/handle/123456789/5098
Title: | Performance Analysis of a SWIPT enabled Cognitive Radio Sensor Network using TS protocol |
Authors: | Kumar, Deepak |
Keywords: | Cognitive radio;Energy harvesting;Energy transfer;Monte Carlo methods;Outages;Signal processing;Wireless power transfer;Decode - and - forwards;Information and power transfers;Information transmission;Mathematical analysis;Mathematical expressions;Performance analysis;Secondary networks;Wireless sensor network (WSNs);Sensor nodes |
Issue Date: | 2020 |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Citation: | Talukdar, B., Kumar, D., & Arif, W. (2020). Performance analysis of a SWIPT enabled cognitive radio sensor network using TS protocol. Paper presented at the International Conference on Advanced Communication Technologies and Signal Processing, ACTS 2020, doi:10.1109/ACTS49415.2020.9350522 |
Abstract: | In this work, we analyze the performance of a simultaneous wireless information and power transfer (SWIPT) enabled Cognitive radio sensor network (CRSN) using time switching (TS) technique at the sensor node. We consider a secondary sensor node that conducts information transmission based on decode and forward approach. A CRSN is a new approach and is capable of solving the issues of spectrum crunch and power limited wireless sensor networks (WSNs). Energy harvesting is incorporated to ensure longer lifetime of the cognitive sensor nodes. The system performance is investigated with respect to the outage probability (OP) and overall network throughput of the CRSN. We extract the exact mathematical expression for the outage probability of both the primary as well as secondary networks. The effect of distinct system and channel parameters on the OP and the overall network throughput is evaluated. Monte Carlo simulations are performed and it verifies the accuracy of the mathematical analysis presented. © 2020 IEEE. |
URI: | https://doi.org/10.1109/ACTS49415.2020.9350522 https://dspace.iiti.ac.in/handle/123456789/5098 |
ISBN: | 9781728170978 |
Type of Material: | Conference Paper |
Appears in Collections: | Department of Electrical Engineering |
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