Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/144819
Title: | Wireless energy harvesting-based relaying : a finite-SNR diversity-multiplexing tradeoff perspective | Authors: | Rao, Yepuri Sudhakara Madhukumar, A. S. Sirigina, Rajendra Prasad |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2019 | Source: | Rao, Y. S., Madhukumar, A. S., & Sirigina, R. P. (2020). Wireless energy harvesting-based relaying : a finite-SNR diversity-multiplexing tradeoff perspective. IEEE Transactions on Green Communications and Networking, 4(1), 277-288. doi:10.1109/TGCN.2019.2948947 | Journal: | IEEE Transactions on Green Communications and Networking | Abstract: | This paper presents an analytical framework to derive the closed-form expressions for diversity-multiplexing tradeoff (DMT) for wireless energy harvesting (WEH) based amplify-and-forward (AF) and decode-and-forward (DF) protocols in finite signal-to-noise (SNR) regime. The results of this investigation suggest that both AF and DF offer similar performance except for few nuances. At low multiplexing gains, DF offers marginally better performance in the low SNR regime, whereas AF performs better in the high SNR scenarios. However, in the higher multiplexing gain regime, though subtle, DF uniformly dominates AF across all SNRs. Furthermore, an analytical study is presented to evaluate the effect of the fraction of time devoted to WEH (time-sharing parameter, ε) on the finite SNR DMT (f-DMT). In addition, the impact of relay position on the outage performance is also presented. A distinguishing feature of the proposed work is the characterization of WEH-based fDMT which reveals the complete interplay between the operating SNR and the time-sharing parameter (ε), which is of fundamental importance to system designers. Finally, Monte-Carlo simulations are provided to confirm the veracity of analytical solutions. | URI: | https://hdl.handle.net/10356/144819 | ISSN: | 2473-2400 | DOI: | 10.1109/TGCN.2019.2948947 | Schools: | School of Computer Science and Engineering | Rights: | © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TGCN.2019.2948947 | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
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