Academic Journal

Power Beacon and NOMA-Assisted Cooperative IoT Networks with Co-Channel Interference: Performance Analysis and Deep Learning Evaluation

التفاصيل البيبلوغرافية
العنوان: Power Beacon and NOMA-Assisted Cooperative IoT Networks with Co-Channel Interference: Performance Analysis and Deep Learning Evaluation
المؤلفون: Le, Anh-Tu, TRAN DINH, Hieu, Le, Chi-Bao, Tin, Phu Tran, Nguyen, Tan N., Ding, Zhiguo, Poor, H. Vincent, Voznak, Miroslav
المصدر: IEEE Transactions on Mobile Computing, 23 (6), 7270 - 7283 (2024-06)
بيانات النشر: Institute of Electrical and Electronics Engineers Inc.
سنة النشر: 2024
المجموعة: University of Luxembourg: ORBilu - Open Repository and Bibliography
مصطلحات موضوعية: Co-channel interference, deep neural network, energy harvesting, Internet of Things, non-orthogonal multiple access, power beacon, two-way relay, wireless power transfer, Co-channel interferences, Multiple access, NOMA, Non-orthogonal, Power, Relay, Resource management, Software, Computer Networks and Communications, Electrical and Electronic Engineering, Engineering, computing & technology, Computer science, Ingénierie, informatique & technologie, Sciences informatiques
الوصف: peer reviewed ; This study investigates a two-way relaying non-orthogonal multiple access (TWR-NOMA) enabled Internet-of-Things (IoT) network, in which two NOMA users communicate via an IoT access point (IAP) relay using a decode-and-forward (DF) protocol. A power beacon (PB) is used to power the IAP to address the IAP's limited lifetime due to energy constraints. Since co-channel interference (CCI) is inevitable in IoT systems, this effect is also studied in the proposed system to improve practicality. Based on the proposed system model, the closed-form equations for the exact and asymptotic outage probability (OP) and ergodic data (ED) of the NOMA users' signals are first derived to describe the performance of TWR-NOMA systems. The system's diversity order and throughput are then evaluated according to the derived results. To further improve the system's performance, a low-complexity strategy 2D golden section search (GSS) is performed, subject to power allocation (PA) and time-switching (TS) factors, to optimize the outage performance. Finally, a deep learning design with minimal computing complexity and precision OP prediction is established for a real-time IoT network configuration. The numerical results are discussed and analyzed in terms of the effects of the CCI, the TS ratio, the PA factor, the fading parameter on the OP, system throughput, and ED.
نوع الوثيقة: article in journal/newspaper
اللغة: English
تدمد: 1536-1233
Relation: https://ieeexplore.ieee.org/ielam/7755/10521901/10321692-aam.pdf; urn:issn:1536-1233; https://orbilu.uni.lu/handle/10993/62376; info:hdl:10993/62376; wos:001216462000025
DOI: 10.1109/TMC.2023.3333764
الاتاحة: https://orbilu.uni.lu/handle/10993/62376
https://orbilu.uni.lu/bitstream/10993/62376/1/Power_Beacon_and_NOMA-Assisted_Cooperative_IoT_Networks_With_Co-Channel_Interference_Performance_Analysis_and_Deep_Learning_Evaluation.pdf
https://doi.org/10.1109/TMC.2023.3333764
Rights: open access ; http://purl.org/coar/access_right/c_abf2 ; info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.D06ED6D5
قاعدة البيانات: BASE
الوصف
تدمد:15361233
DOI:10.1109/TMC.2023.3333764