Performance of Battery-Assisted EH Full-Duplex NOMA Network With FBL Driven Mode Switching Under Imperfect CSI and SIC

This paper investigates a cooperative Internet of Things (IoT) non-orthogonal multiple access (NOMA) network comprising of a multi-antenna base station (BS), a near IoT user (NU) with full-duplex capabilities, and multiple far IoT users (FU). The NU utilizes the power-splitting (PS) energy harvesting (EH) protocol and augments the harvested energy with a little energy from its battery to assist the FU. Considering the novel cooperative NOMA/non-cooperative (C-NM/NC) switching, the impact of successive interference cancellation (SIC), channel state information (CSI) errors, and nonlinear EH, closed-form expressions are derived for average blocklength error rates (BLER) of both users in finite blocklength regime. Utilizing the derived BLER expressions, the Goodput, Reliability, Latency, and battery power efficiency are expressed in closed form. We then demonstrate that the CSI errors severely degrades the performance of both the users. Monte Carlo simulations validate the accuracy of the derived analytical expressions. We also establish that a significantly better maximum performance is attained at the FU, given a target NU Goodput by the careful choice of NOMA and EH parameters. C-NM/NC switching offers a higher EE and better self-interference immunity. Results indicate that the choice of blocklength is crucial for efficient system performance.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Communications
Published
2024-11-27
DOI
https://doi.org/10.1109/tcomm.2024.3506919
Citations
1
Primary Topic
Full-Duplex Wireless Communications
Type
article
Field-Weighted Citation Impact
0.21
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance of Battery-Assisted EH Full-Duplex NOMA Network With FBL Driven Mode Switching Under Imperfect CSI and SIC

Shankar Prakriya, M A Ajay, Sandeep Kumar Singh, Kamal Agrawal et al.
1 citations
IEEE Transactions on Communications
Full-Duplex Wireless Communications
0.21
article

Performance of Battery-Assisted EH Full-Duplex NOMA Network With FBL Driven Mode Switching Under Imperfect CSI and SIC

Shankar Prakriya, M A Ajay, Sandeep Kumar Singh, Kamal Agrawal, Keshav Singh, Chih–Peng Li
article en
1 citations

Abstract

This paper investigates a cooperative Internet of Things (IoT) non-orthogonal multiple access (NOMA) network comprising of a multi-antenna base station (BS), a near IoT user (NU) with full-duplex capabilities, and multiple far IoT users (FU). The NU utilizes the power-splitting (PS) energy harvesting (EH) protocol and augments the harvested energy with a little energy from its battery to assist the FU. Considering the novel cooperative NOMA/non-cooperative (C-NM/NC) switching, the impact of successive interference cancellation (SIC), channel state information (CSI) errors, and nonlinear EH, closed-form expressions are derived for average blocklength error rates (BLER) of both users in finite blocklength regime. Utilizing the derived BLER expressions, the Goodput, Reliability, Latency, and battery power efficiency are expressed in closed form. We then demonstrate that the CSI errors severely degrades the performance of both the users. Monte Carlo simulations validate the accuracy of the derived analytical expressions. We also establish that a significantly better maximum performance is attained at the FU, given a target NU Goodput by the careful choice of NOMA and EH parameters. C-NM/NC switching offers a higher EE and better self-interference immunity. Results indicate that the choice of blocklength is crucial for efficient system performance.

IEEE Transactions on CommunicationsVol. 73(6)
National Sun Yat-sen University (TW), Motilal Nehru National Institute of Technology (IN), Shiv Nadar University (IN), Indian Institute of Technology Delhi (IN), Vellore Institute of Technology University (IN)
Affordable and clean energy
Openalex Percentile: Top 46%
Full-Duplex Wireless Communications
0.21
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.