AI Article Synopsis
- The electromagnetic spectrum is critical for wireless communication, but existing systems are using most of it, necessitating innovative solutions like the Reflective In-Band Full-Duplex (R-IBFD) scheme, which combines Full-Duplex and Non-Orthogonal Multiple Access technologies.
- R-IBFD enhances spectrum utilization and improves system parameters such as Secrecy Outage Probability, throughput, and data rates, supporting the advanced needs of 6th Generation (6G) smart city networks.
- The system addresses co-channel interference and security issues, using mathematical derivations and simulations to demonstrate its effectiveness, with machine learning genetic algorithms employed to optimize secrecy capacity.
Article Abstract
The electromagnetic spectrum is used as a medium for modern wireless communication. Most of the spectrum is being utilized by the existing communication system. For technological breakthroughs and fulfilling the demands of better utilization of such natural resources, a novel Reflective In-Band Full-Duplex (R-IBFD) cooperative communication scheme is proposed in this article that involves Full-Duplex (FD) and Non-Orthogonal Multiple Access (NOMA) technologies. The proposed R-IBFD provides efficient use of spectrum with better system parameters including Secrecy Outage Probability (SOP), throughput, data rate and secrecy capacity to fulfil the requirements of a smart city for 6th Generation (6thG or 6G). The proposed system targets the requirement of new algorithms that contribute towards better change and bring the technological revolution in the requirements of 6G. In this article, the proposed R-IBFD mainly contributes towards co-channel interference and security problem. The In-Band Full-Duplex mode devices face higher co-channel interference in between their own transmission and receiving antenna. R-IBFD minimizes the effect of such interference and assists in the security of a required wireless communication system. For a better understanding of the system contribution, the improvement of secrecy capacity and interference with R-IBFD is discussed with the help of SOP derivation, equations and simulation results. A machine learning genetic algorithm is one of the optimization tools which is being used to maximize the secrecy capacity.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9002557 | PMC |
| http://dx.doi.org/10.3390/s22072508 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Exploiting full-duplex opportunities in WLANs via a reinforcement learning-based medium access control protocol.
Sci Rep
December 2024
National University of Defense Technology, Changsha, Hunan, China.
In-band full-duplex communication has the potential to double the wireless channel capacity. However, how to efficiently transform the full-duplex gain at the physical layer into network throughput improvement is still a challenge, especially in dynamic communication environments. This paper presents a reinforcement learning-based full-duplex (RLFD) medium access control (MAC) protocol for wireless local-area networks (WLANs) with full-duplex access points.
View Article and Find Full Text PDFIn-band full-duplex (IBFD) operation is essential for both sensing-centric and communication-centric integrated sensing and communications (ISAC) systems. Both types require the monostatic transceiver to overcome the technical challenge of self-interference (SI). To address this challenge, a photonics-assisted self-interference cancellation (SIC) scheme for an IBFD ISAC transceiver is proposed and experimentally demonstrated.
View Article and Find Full Text PDFIn this paper, we propose a dual-polarization Mach-Zehnder modulator-based photonic nonlinear analog self-interference cancellation (SIC) technique for in-band full duplex (IBFD) systems. By using the proposed technique, an arbitrary 4th order nonlinear transfer function can be generated, meaning the performance limitation caused by the nonlinearity of the analog SIC circuit can be overcome by imitating the nonlinear transfer function of the analog SIC circuit before cancellation. This paper also presents a performance analysis through simulations and the results of a proof-of-concept demonstration.
View Article and Find Full Text PDFA Microwave Photonic 2 × 2 IBFD-MIMO Communication System with Narrowband Self-Interference Cancellation.
Micromachines (Basel)
April 2024
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710129, China.
Combined in-band full duplex-multiple input multiple output (IBFD-MIMO) technology can significantly improve spectrum efficiency and data throughput, and has broad application prospects in communications, radar, the Internet of Things (IoT), and other fields. Targeting the self-interference (SI) issue in microwave photonic-based IBFD-MIMO communication systems, a microwave photonic self-interference cancellation (SIC) method applied to the narrowband 2 × 2 IBFD-MIMO communication system was proposed, simulated, and analyzed. An interleaver was used to construct a polarization multiplexing dual optical frequency comb with a frequency shifting effect, generating a dual-channel reference interference signal.
View Article and Find Full Text PDFAn in-band full-duplex multiband mobile fronthaul network is proposed based on analog radio-over-fiber and tandem single-sideband (TSSB) modulation. Two optical carriers with a wavelength spacing of 50 GHz in accordance with international telecommunication union dense wavelength division multiplexing (DWDM) standards are employed in each distributed unit (DU): one is used to carry two different radio frequency (RF) vector signals at 3 and 10 GHz, while the other is used to carry a vector signal at 15 GHz and a single-tone signal at 15 GHz. At the DU, a parallel TSSB modulation is applied, which eliminates the cross talk of TSSB modulation through two dual-polarization binary phase-shift keying (DP-BPSK) modulators.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!