Semi-Blind SI Cancellation for In-Band Full-Duplex Wireless Communications

Liu, Donglin; Zhao, Bo; Wu, Fei; Shao, Shihai; Pu, Xumin; Tang, Youxi

doi:10.1109/lcomm.2018.2809622

Cited by 8 publications

(7 citation statements)

References 16 publications

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“…With powerful digital signal processing techniques, digital cancellers with various features have been developed, as shown in TABLE I. In this field, it is common to deal with RF impairments [12], [16], [22]- [29], [34], [37], [38], phase noise [35], [36], and application to multi-input and multi-output (MIMO) systems [24], [25], [40], [41], and application of blind signal processing [42], [43]. In addition to the research focused on digital cancellers composed only of digital signal processing, there are also studies integrating auxiliary receivers [31]- [33].…”

Section: B Review Of Previous Research: Digital Approachmentioning

confidence: 99%

“…To achieve higher channel capacity on in-band full-duplex communications, cancellers should have a lower number of training symbols. For example, self-interference cancellers with blind signal processing have been proposed on orthogonal frequency-division multiplexing (OFDM) systems [42], [43]. However, these techniques require symbol synchronization between the self-interference and the desired signal because they are applied in the frequency domain [43].…”

Section: B Review Of Previous Research: Digital Approachmentioning

confidence: 99%

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Iterative Nonlinear Self-Interference Cancellation for In-Band Full-Duplex Wireless Communications Under Mixer Imbalance and Amplifier Nonlinearity

Komatsu

Miyaji

Uehara

2020

IEEE Trans. Wireless Commun.

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This paper presents an iterative estimation and cancellation technique for nonlinear in-band full-duplex transceivers with IQ imbalances and amplifier nonlinearities. The estimation process of the proposed scheme consists of three stages, namely, the channel response estimation, IQ imbalance estimation, and power amplifier and low-noise amplifier (LNA) nonlinearities estimation. For the estimation of the parameters and improvement of the accuracy, distortions are compensated by cancellation or inversion with the latest estimated parameters. On the one hand, the channel response is estimated on the time domain; on the other hand, the IQ imbalance and nonlinearities are estimated on the frequency domain for a more straightforward estimation and superior accuracy. In the cancellation process of the proposed scheme, the received signal is compensated with the estimated parameters of the LNA and receiver IQ imbalance before cancellation because the desired signal is received with a high-power self-interference and is distorted by the radiofrequency receiver impairments. Simulation results show that the proposed technique can achieve higher cancellation performance compared with the Hammerstein canceller when the LNA is saturated by the self-interference. Additionally, the performance of the proposed canceller converges much faster than that of the Hammerstein canceller.

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Section: B Review Of Previous Research: Digital Approachmentioning

confidence: 99%

Section: B Review Of Previous Research: Digital Approachmentioning

confidence: 99%

Iterative Nonlinear Self-Interference Cancellation for In-Band Full-Duplex Wireless Communications Under Mixer Imbalance and Amplifier Nonlinearity

Komatsu

Miyaji

Uehara

2020

IEEE Trans. Wireless Commun.

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“…, M , N m is circularly symmetric complex Gaussian (CSCG) noise, and X m is the training signal for calibration. It is worth mentioning thatD n J = diag {N m /(d m t X m )} means that transmitter noise is dominant since calibration occurs in short-range communication scenarios, and transmitter noise is much more significant than receiver noise [14,20,21]. Thus, the variance of the mth entry in D n J can be written in the form of δ e (m) = 1/SNR J (m), where SNR J (m) is the SNR in the mth transmitter.…”

Section: Downlink Beamforming With Reciprocity Calibrationmentioning

confidence: 99%

“…As shown in (20), a larger ξ k means we potentially lower the achievable rates due to imperfect calibration. Mathematically, L → ∞ if ξ k grows without bound.…”

Section: Remarkmentioning

confidence: 99%

Energy- and spectral-efficiency of zero-forcing beamforming in massive MIMO systems with imperfect reciprocity calibration: bound and optimization

Liu

Quan

et al. 2018

Sci. China Inf. Sci.

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In a time-division duplex (TDD) system with massive multiple input multiple output (MIMO), channel reciprocity calibration (RC) is generally required in order to cope with the reciprocity mismatch between the uplink and downlink channel state information. Currently, evaluating the achievable spectral efficiency (SE) and energy efficiency (EE) of TDD massive MIMO systems with imperfect RC (IRC) mainly relies on exhausting Monte Carlo simulations and it is infeasible to precisely and concisely quantify the achievable SE and EE with IRC. In this study, a novel method is presented for tightly bounding the achievable SE of massive MIMO systems with zero-forcing beamforming under IRC. On the basis of the analytical results, we demonstrate key insights for practical system design with IRC in three aspects: the scaling rule for interference power, saturation region of the SE, and the bound on the SE loss. Finally, the trade-off between spectral and energy efficiencies in the presence of IRC is determined with algorithms developed to optimize SE (EE) under a constrained EE (SE) value. The loss of optimal total SE and EE due to IRC is also quantified, which shows that the loss of optimal EE is more sensitive to IRC in a typical range of transmit power values.

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“…In order to overcome such mobile device sustainability challenges, wireless energy harvesting (WEH) is proposed for the self-sustained communication through wireless charging [13]. Simultaneous wireless information and power transfer (SWIPT) [14] arose as a breakthrough technology that divides radio frequency (RF) signals into two parts, information transmission and energy collection, providing a feasible solution for excessive network energy consumption [15], [16]. SWIPT is able to apply two different receiver architectures; time switching (TS) periodically switches between information decoding (ID) and energy harvesting (EH), and power splitting (PS) simultaneously executes ID and EH [17].…”

Section: Introductionmentioning

confidence: 99%

Joint Communication and Computation Resource Optimization in FD-MEC Cellular Networks

Chen

Wang

et al. 2019

IEEE Access

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In view of the growing contradiction between the intensive computation demands and the resource limitations of mobile users, mobile edge computing (MEC) and simultaneous wireless information and power transfer (SWIPT) have emerged as new paradigms towards 5G communication. However, coordinating the communication and computation between users and edge servers proves to be challenging for MEC. In this paper, we propose a novel multiuser full-duplex (FD) communication system that combines MEC and SWIPT technology in order to take the advantage of high-speed mobile computing and long-lasting self-sustainability. Through MEC technology, users are able to calculate local computation tasks using their batteries, and can offload partial computation tasks to the base station (BS) to reduce their energy shortage. Moreover, users can refill their batteries while receiving the computation result sent by the BS, thus benefiting from SWIPT technology. The FD mode can potentially increase the system performance by allowing the simultaneous transmitting and receiving of computation tasks. Our work aims to minimize the energy consumption of the system, while formulating resource allocation as a joint non-linear optimization problem. We decouple the original non-convex problem into two subproblems and solve them using a proposed algorithm that applies group iterative optimization. Numerical results prove that the proposed algorithm is superior to other two comparison schemes and can significantly reduce the system energy consumption and the latency. INDEX TERMS Full-duplex, mobile edge computing, offload, simultaneous wireless information and power transfer, group iterative optimization. FANGNI CHEN received the B.S. degree in communication engineering and the Ph.D. degree in information and communication engineering from Zhejiang University, China, in 2003 and 2008, respectively.

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Semi-Blind SI Cancellation for In-Band Full-Duplex Wireless Communications

Cited by 8 publications

References 16 publications

Iterative Nonlinear Self-Interference Cancellation for In-Band Full-Duplex Wireless Communications Under Mixer Imbalance and Amplifier Nonlinearity

Iterative Nonlinear Self-Interference Cancellation for In-Band Full-Duplex Wireless Communications Under Mixer Imbalance and Amplifier Nonlinearity

Energy- and spectral-efficiency of zero-forcing beamforming in massive MIMO systems with imperfect reciprocity calibration: bound and optimization

Joint Communication and Computation Resource Optimization in FD-MEC Cellular Networks

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