Software defined radio implementation of adaptive nonlinear digital self-interference cancellation for mobile inband full-duplex radio

Aghababaeetafreshi, Mona; Koskela, Matias; Korpi, Dani; Jääskeläinen, Pekka; Valkama, Mikko; Takala, Jarmo

doi:10.1109/globalsip.2016.7905939

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…In the last decades, much research on PIMD has focused on phenomena, measurement techniques and mechanisms [4,5]. To mitigate PIMD, a method of introducing artificial and adjustable passive nonlinearities was considered [6], while an adaptive algorithm that removes nonlinear interference was proposed for a mobile inband full duplex radio and it was implemented using a software defined radio based on the graphics processing units [7]. Various real-time adaptive algorithms have been proposed to eliminate PIMD in digital satellite communication transceivers [8].…”

Section: Introductionmentioning

confidence: 99%

Third-order passive intermodulation distortion cancellation using a cubic Volterra filter for wireless relay systems

Jang

Kim

et al. 2020

NOLTA

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Passive intermodulation distortion (PIMD) is a phenomenon in which two or more transmission signal frequencies interfere with each other due to non-linearity in passive elements of a wireless communication system and undesired signals are generated. Such intermodulation distortion increases the noise level in the receive frequency band of the wireless communication system, thereby degrading the performance of the receiver. In this paper, a PIMD mitigation scheme based on a modified cubic Volterra filter is proposed to reduce a passive intermodulation distortion level to enhance the uplink signal receive performance. The performance of the proposed approach is evaluated by applying it to the data sampled at a repeater for the long term evolution (LTE) system. The proposed approach demonstrates a notable reduction of PIMD in the receive band. The conventional least mean square (LMS) approach is considered in this study for the purpose of comparison.

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Section: Introductionmentioning

confidence: 99%

Third-order passive intermodulation distortion cancellation using a cubic Volterra filter for wireless relay systems

Jang

Kim

et al. 2020

NOLTA

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“…At low or moderate transmit power levels, the digital domain cancellation is typically performed using linear cancelers, which reconstruct an estimated copy of the SI signal based on techniques such as least-squares (LS) channel estimation [47], [49], [53]. However, at high transmit power levels, such cancellation only becomes insufficient to entirely suppress the SI to the Rx noise floor due to the stringent non-linear behavior of FD transceiver's components, such as the power and low-noise amplifiers (PA and LNA) [47], [49], [52]. Thus, non-linear digital cancellation is applied with the linear cancellation to bring the SI to the Rx noise floor level.…”

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confidence: 99%

Machine Learning-Based Self-Interference Cancellation for Full-Duplex Radio: Approaches, Open Challenges, and Future Research Directions

Elsayed,

El-Banna,

Dobre

et al. 2024

IEEE Open J. Veh. Technol.

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In contrast to the long-held belief that wireless systems can only work in half-duplex mode, full-duplex (FD) systems are able to concurrently transmit and receive information over the same frequency bands to theoretically enable a twofold increase in spectral efficiency. Despite their significant potential, FD systems suffer from an inherent self-interference (SI) due to a coupling of the transmit signal to its own FD receive chain. Selfinterference cancellation (SIC) techniques are the key enablers for realizing the FD operation, and they could be implemented in the propagation, analog, and/or digital domains. Particularly, digital domain cancellation is typically performed using modeldriven approaches, which have proven to be insufficient to seize the growing complexity of forthcoming communication systems. For the time being, machine learning (ML) datadriven approaches have been introduced for digital SIC to overcome the complexity hurdles of traditional methods. This paper reviews and summarizes the recent advances in applying ML to SIC in FD systems. Further, it analyzes the performance of various ML approaches using different performance metrics, such as the achieved SIC, training overhead, memory storage, and computational complexity. Finally, this paper discusses the challenges of applying ML-based techniques to SIC, highlights their potential solutions, and provides a guide for future research directions.

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Software Defined Radio Implementation of a Digital Self-interference Cancellation Method for Inband Full-Duplex Radio Using Mobile Processors

Aghababaeetafreshi

Korpi

Koskela

et al. 2017

J Sign Process Syst

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Software defined radio implementation of adaptive nonlinear digital self-interference cancellation for mobile inband full-duplex radio

Cited by 6 publications

References 10 publications

Third-order passive intermodulation distortion cancellation using a cubic Volterra filter for wireless relay systems

Third-order passive intermodulation distortion cancellation using a cubic Volterra filter for wireless relay systems

Machine Learning-Based Self-Interference Cancellation for Full-Duplex Radio: Approaches, Open Challenges, and Future Research Directions

Software Defined Radio Implementation of a Digital Self-interference Cancellation Method for Inband Full-Duplex Radio Using Mobile Processors

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