Digital Self-interference Cancellation Research Articles

A Full-Duplex 60 GHz Transceiver with Digital Self-Interference Cancellation

This paper presents the design and measurement of an IEEE 802.11ad standard compatible RF transceiver for 60 GHz wireless communication systems. In addition to the traditional half-duplex (HD) mode, this work supports full-duplex (FD) operations to deliver better channel utilization and faster response times for the system. The isolation between the transmitter and receiver from the architecture design to system integration for FD operations has been fully considered. A digital self-interference cancellation (DSIC) is implemented in MATLAB to verify the FD performance. The super-heterodyne architecture with an intermediate frequency (IF) of 12 GHz is designed to suppress the image frequencies without using extra filters. A flexible phase-locked loop (PLL) synthesizer provides a local oscillator (LO) frequency with a 2 kHz resolution. Other than the time division duplex (TDD) mode used in the conventional 60 GHz system, a wide-bandwidth baseband digital variable-gain amplifier (DVGA) with a 3 dB bandwidth of more than 4 GHz also supports frequency division duplex (FDD) operations. The transceiver chip is fabricated using the Tower Jazz 0.18 µm SiGe BiCMOS process. With an on-board antenna, the transceiver covers all four channels in the 802.11ad standard, with MCS-12 (7.04 Gbps under 1.76 GSym/s and 16-QAM) under 1.5 m. In the proposed system design, the RF frontend-based self-interference (SI) suppression from the local transmitter to receiver LNA is around 54 dB. To achieve a practical FD application, the SI is further suppressed with the help of a digital SI compensation. The measured power consumption for the transmitter and receiver configurations are 194 mW and 231 mW, respectively, in HD mode and 398 mW for the FDD or FD operation mode.

A hybrid digital self-interference cancellation method with attention-based TCN-GRU for full-duplex systems

Full-duplex (FD) technology is expected to be widely used in future communication systems due to its excellent performance in spectral efficiency. Self-interference (SI) is the main problem affecting the transmission quality of the FD systems, thus it is crucial to research the SI cancellation (SIC) techniques. In this paper, we present an innovative hybrid digital SIC method named sliding time window, temporal convolutional network (TCN), gated recurrent unit (GRU) and attention mechanism (AM)-based deep learning network (STGAN). The proposed method can extract complete features and time information from the input sequence, and accurately estimate the SI in FD systems. We first present a preprocessing module that utilizes sliding time windows to handle the original signal sequence. Then, we utilize the TCN and GRU to extract the short-term features and long-term dependencies within the sequence. Finally, the AM is adopted to explore the significance of the information conveyed by the sequence at different time steps. The effectiveness of the STGAN is verified in multiple experimental scenarios. Simulation results indicate that the interference cancellation ratio (ICR) of the STGAN is significantly higher than existing methods.

Augmented Envelope Neural Networks on RF-SoC for Digital Self-Interference Cancellation

Augmented Envelope Neural Networks on RF-SoC for Digital Self-Interference Cancellation

On the Learning of Digital Self-Interference Cancellation in Full-Duplex Radios

On the Learning of Digital Self-Interference Cancellation in Full-Duplex Radios

A Fiber-Transmission-Assisted Fast Digital Self-Interference Cancellation for Overcoming Multipath Effect and Nonlinear Distortion

A Fiber-Transmission-Assisted Fast Digital Self-Interference Cancellation for Overcoming Multipath Effect and Nonlinear Distortion

A Sparse Shared Aperture Design for Simultaneous Transmit and Receive Arrays with Beam Constraints

The utilization of efficient digital self-interference cancellation technology enables the simultaneous transmit and receive (STAR) phased array system to meet most application requirements through STAR capabilities. However, the development of application scenario requirements makes array configuration technology for STAR phased arrays increasingly important. Thus, this paper proposes a sparse shared aperture STAR reconfigurable phased array design based on beam constraints which are achieved by a genetic algorithm. Firstly, a design scheme for transmit and receive arrays with symmetrical shared apertures is adopted to improve the aperture efficiency of both transmit and receive arrays. Then, on the basis of shared aperture, sparse array design is introduced to further reduce system complexity and hardware costs. Finally, the shape of the transmit and receive arrays is determined by constraining the side lobe level (SLL), main lobe gain, and beam width. The simulated results indicate that the SLL of the transmit and receive patterns under beam-constrained design have been reduced by 4.1 dBi and 7.1 dBi, respectively. The cost of SLL improvement is a reduction in transmit gain, receive gain, and EII of 1.9 dBi, 2.1 dBi, and 3.9 dB, respectively. When the sparsity ratio is greater than 0.78, the SLL suppression effect is also significant, and the attenuation of EII, transmit, and receive gains do not exceed 3 dB and 2 dB, respectively. Overall, the results demonstrate the effectiveness of a sparse shared aperture design based on beam constraints in producing high gain, low SLL, and low-cost transmit and receive arrays.

Digital self-interference cancellation for full-duplex systems based on deep learning

Full-duplex (FD) systems can double the spectrum efficiency by allowing users to transmit and receive signals at the same time and in the same frequency band. However, in FD systems the receiver suffers severe self-interference (SI) caused by the transmitter and eliminating the SI is challenging. In this paper, we propose a novel digital self-interference cancellation (SIC) scheme based on deep learning, which combines the power of sliding window, gated recurrent unit (GRU) network and attention mechanism (AM). The proposed scheme can accurately reconstruct the SI through two steps. It first processes the sample signals utilizing the sliding window and then extracts the dependence in preprocessed signals by applying the GRU with AM. We adopt the orthogonal frequency division multiplexing (OFDM) signal as the baseband transmitted signal to verify the proposed scheme. Extensive experiments demonstrate that the SIC capability of the developed scheme is at least 14.46 dB higher than the existing polynomial and neural network (NN) schemes. Furtherly, the effectiveness of the scheme is verified in different interference-to-noise ratio (INR), multipath channel, training sample and OFDM symbol situations.

Joint Analog and Digital Self-Interference Cancellation for Full Duplex Transceiver With Frequency-Dependent I/Q Imbalance

An effective and practical joint analog and digital self-interference cancellation (SIC) scheme without additional signalling overhead for an I/Q imbalanced full duplex transceiver is proposed in this paper. This scheme combines an I/Q imbalanced analog least mean square (ALMS) loop at the transceiver radio frequency frontend and a two-stage digital signal processing (DSP) at the digital baseband to achieve excellent SIC performance with low complexity. The steady state weighting coefficients of the I/Q imbalanced ALMS loop with periodical transmitted signal and the loop’s convergence behaviour are firstly analysed. The residual SI is then modelled as the output of a time-varying widely linear system. With a track/hold control mechanism applied to the ALMS loop, the system model for digital SIC is further presented, followed by the DSP algorithms suitable for real-time implementation. The noise enhancement in each stage digital cancellation is also analysed and formulated. Finally, simulation results are provided to verify the theoretical analyses and demonstrate the overall SIC performance.

Digital Self-Interference Cancellation for Full-Duplex UAV Communication System over Time-Varying Channels

Full-duplex unmanned aerial vehicle (UAV) communication systems are characterized by mobility, so the self-interference (SI) channel characteristics change over time constantly. In full-duplex UAV communication systems, the difficulty is to eliminate SI in time-varying channels. In this paper, we propose a pilot-aid digital self-interference cancellation (SIC) method. First, the pilot is inserted into the data sequence uniformly, and the time-varying SI is modeled as a linear non-causal function. Then, the time-varying SI channel is estimated by the discrete prolate spheroidal basis expansion model (BEM). The error of block edge channel estimation is reduced by cross-block interpolation. The result of channel estimation is convolved with the transmitted data to obtain the reconstructed SI, which is subtracted from the received signal to achieve SIC. The simulation results show that the SIC performance of the proposed method outperforms the dichotomous coordinate descent recursive least square (DCD-RLS) and normalized least mean square (NLMS) algorithms. When the interference to noise ratio (INR) is 25 dB, the performance index normalized least mean square (NMSE) is reduced by 5.5 dB and 4 dB compared with DCD-RLS and NLMS algorithms, which can eliminate SI to the noise floor, and the advantage becomes more obvious as the INR increases.

An Adaptive-Iterative Nonlinear Interference Cancellation in Time-Varying Full-Duplex Channels

In this paper, first, the sensitivity of traditional Full-Duplex (FD) communication systems to time variation in the self-interference (SI) channel is demonstrated via performance analysis. It is seen that conventional schemes are not capable of providing efficient operation regarding practical concerns such as spectral efficiency, SI channel aging and learning accuracy, and the contamination of signal-of-interest (SoI). Then, in regard to the aforementioned concerns, a practical FD operation together with a novel iterative SoI-contamination-aware digital SI cancellation (DSIC) algorithm that relieves the sensitivity against time variation considerably is proposed. The proposed scheme, namely <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Turbo</i> DSIC, is practical in terms of training and computational complexity thanks to its two-stage structure such that complex nonlinear parameter learning (NPL) is conducted very rarely in the first stage, and linear processing is performed adaptively at symbol-rate in the second stage, where SoI is iteratively estimated at each data block and eliminated from the received signal to improve SI channel estimation accuracy. Finally, the performance of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Turbo</i> DSIC, under hardware impairments and time-varying (TV) propagation, is evaluated via both computer simulation environment and actual experimental hardware setup in terms of bit error rate (BER) and achievable information rate (AIR) metrics.

Lake Experimentation of in-Band Full-Duplex Underwater Acoustic Communications With a Receiving Array

In-band full-duplex (IBFD) communications is a promising technique to achieve spectral-efficient communication in the underwater environment. To achieve IBFD underwater communications, suppression of self-interference (SI) is a prerequisite. In this paper, SI suppression using physical separation and digital SI cancellation is investigated under different transmitter-receiver geometries. An iterative IBFD receiver combining joint channel estimation, SI cancellation, and multichannel decision feedback equalizer is developed. Due to the potential deterioration of the channel estimation accuracy, a digital SI cancellation control mechanism is used to regulate the suppression process. The feasibility of coherent IBFD underwater acoustic communications was tested in a lake environment. The two SI suppression methods, the SI cancellation control mechanism, and the receiver performance were evaluated using the experimental measurements. A bit error rate (BER) in the order of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$10^{-2}$ </tex-math></inline-formula> was achieved at the range of 80 m for IBFD communications.

A Digital Self-Interference Cancellation Scheme for In-Band Full-Duplex-Applied 5G System and Its Software-Defined Radio Implementation

The development of mobile communication technology toward 6G is difficult because the required spectrum resources have already been allocated to existing systems. Therefore, new communication systems must have high spectral efficiency to effectively utilize the available resources. This article proposes a digital self-interference (SI) canceller that can be applied to full-duplex cellular systems based on the current 5G signal format (5G-FDC) to introduce in-band full-duplex systems beyond 5G. Specifically, we reorganize the 5G demodulation reference signal (DMRS) and define a novel DMRS configuration, in which the DMRSs for uplink and downlink communications do not interfere with each other. The proposed DMRS configuration effectively improves the accuracy of the SI channel estimation. Moreover, we propose a channel extrapolation scheme that suppresses the channel estimation degradation, which deteriorates the block error rate performance. Additionally, we propose a noise estimation method to improve the low-density parity check decoding performance of the desired signal in 5G-FDC systems. The effectiveness of the proposed method is demonstrated through computer simulations and experimentally by using our developed and implemented software-defined radio-based 5G-FDC prototype. Digital SI cancellation performances of 50 dB and 30.6 dB are observed in the simulation and experimental evaluations, respectively.

Widely-Linear Digital Self-Interference Cancellation in Full-Duplex USRP Transceiver.

Full-duplex (FD) communication systems allow for increased spectral efficiency but require effective self-interference cancellation (SIC) techniques to enable the proper reception of the signal of interest. The underlying idea of digital SIC is to estimate the self-interference (SI) channel based on the received signal and the known transmitted waveform. This is a challenging task since the SI channel involves, especially for mass-market FD transceivers, many nonlinear distortions produced by the impairments of the analog components from the receiving and transmitting chains. Hence, this paper first analyzes the power of the SI components under practical conditions and focuses on the most significant one, which is proven to be produced by the I/Q mixer imbalance. Then, a widely-linear digital SIC approach is adopted, which simultaneously deals with the direct SI and its image component caused by the I/Q imbalance. Finally, the performances achieved by linear and widely-linear SIC approaches are evaluated and compared using an experimental FD platform relying on software-defined radio technology and GNU Radio. Moreover, the considered experimental framework allows us to set different image rejection ratios for the transmission path I/Q mixer and to study its influence on the SIC capability of the discussed approaches.

Full-Duplex Massive Multiple-Input, Multiple-Output Architectures: Recent Advances, Applications, and Future Directions

The increasingly demanding objectives for next-generation wireless communications have spurred recent research activities on multiantenna transceiver hardware architectures and relevant intelligent communication schemes. Among them belong full-duplex (FD) multiple-input, multiple-output (MIMO) architectures, which offer the potential for simultaneous uplink (UL) and downlink (DL) operations in the entire frequency band. However, as the number of antenna elements increases, the interference signal leaking from the transmitter (Tx) of the FD radio to its receiver (Rx) becomes more severe. In this article, we present a unified FD massive MIMO architecture comprising analog and digital transmit and receive beamforming (BF) as well as analog and digital self-interference (SI) cancellation, which can be jointly optimized for various performance objectives and complexity requirements. The performance evaluation results for applications of the proposed architecture to fully digital and hybrid analog and digital-BF operations using recent algorithmic designs as well as simultaneous communication of data and control (SCDC) signals are presented. It is shown that the proposed architecture, for both small and large numbers of antennas, enables improved spectral-efficient FD communications with fewer analog-cancellation elements compared to various benchmark schemes. The article concludes with a list of open challenges and research directions for future FD massive MIMO communication systems and their promising applications.

Full-Duplex UAC Receiver With Two-Sensor Transducer

In this brief we present a design of a full-duplex (FD) underwater acoustic communication (UAC) receiver with a two-sensor transducer. The transducer consists of two piezo-ceramic cylinders cast together in polyurethane resin; one acts as a hydrophone and the other a projector. As the distance between the projector and hydrophone is extremely short, a high level of self-interference (SI) from the projector is received at the hydrophone. This SI must be eliminated to enable far-end data demodulation. In this brief, we adopt a digital SI cancellation scheme based on adaptive filtering. We investigate the SI cancellation and far-end data demodulation performance with the two-sensor transducer in tank and lake experiments. The Rake receiver is used for the far-end data demodulation. As demonstrated by the experimental results, the far-end SNR loss in the FD experiment is less than 3 dB compared to the half-duplex experiment when there is only far-end transmission.

Digital SI Cancellation Based on LSTM for Co-frequency Co-time Full Duplex Communication Systems

To address the high self-interference (SI) in co-frequency co-time full duplex (CCFD) communication systems, a digital SI suppression method based on deep learning is proposed. A memory polynomial is firstly utilized to simulate the SI channel. Then a long short-term memory network (LSTM) is used to reconstruct the SI signal. The clean signal after interference suppression can be achieved by subtracting the SI signal at the receiver. To better reflect the changes of the SI signals after being transmitted through the multiple channels and reduce dependence on data volume, feature preprocessing and feature reconstruction are performed at the input of the LSTM. We use the multi-segment delayed transmitted signal as the multiple features and utilize the brainstorm optimization (BSO) technique to estimate the ideal time delay. We verify the proposed SI suppression scheme in the OFDM transmission system. The experimental results show that compared with the traditional least squares estimation (LS) and adaptive filter least mean square (LMS) algorithms, the proposed scheme has a significant performance boost. A SI signal suppression capability of 47.19 dB is achieved.

Spatial-digital joint self-interference cancellation method for in-band full-duplex underwater acoustic communication

The in-band full-duplex underwater acoustic communication (IBFD-UWAC) mode has twice the information throughput of the traditional half-duplex communication mode, significantly increasing the communication efficiency. Extracting the weak desired signal from the high-power self-interference signal without distortion remains a challenging problem in implementing IBFD-UWAC systems. This paper proposes a spatial-digital joint self-interference cancellation (SDSIC) method for IBFD-UWAC. We first perform spatial self-interference cancellation (SSIC) and propose an improved wideband constant-beamwidth beamformer to overcome the problem of direction- and array-dependent interference in IBFD-UWAC systems. Convex optimization is used to maintain a constant beam response in the main flap and cancel the self-interference signal from a fixed direction, thus increasing the signal-to-interference ratio of the desired signal. Subsequently, we perform digital self-interference cancellation (DSIC) on the residual self-interference signal, and propose a variable-step-size least-mean-squares algorithm based on the spatial noise threshold. This algorithm modifies the least-mean-squares step-size adjustment criterion according to the noise level after SSIC and the desired signal, resulting in better DSIC. A series of simulations are implemented in a hardware-in-the-loop platform to verify the practicality and real-time performance of the proposed SDSIC method. The results show that the self-interference signal power can be reduced by 41.5 dB using the proposed method, an improvement of 13.5 dB over the conventional SIC method.

A Real-Time Digital Self Interference Cancellation Method for In-Band Full-Duplex Underwater Acoustic Communication Based on Improved VSS-LMS Algorithm

Theoretically, the spectral efficiency of in-band full-duplex underwater acoustic communications (IBFD-UWAC) is twice that of a half-duplex one. However, the actual achievable spectral efficiency of IBFD-UWAC is determined by the performance of the self-interference cancellation (SIC). In addition, the hostile underwater environment poses a challenge to the tracking performance of the SIC due to its complexity and variability. In this paper, we propose a digital SIC method based on the improved variable step-size least mean square (IVSS-LMS) algorithm where we modify the step-size adjustment criterion in the classical LMS filter and establishes a nonlinear relationship with the Sigmoid function to control the step-size using the instantaneous state error, thus improving the robustness and tracking performance of IVSS-LMS. Hardware-in-loop simulation (HLS) based on Simulink® platform verifies the real-time implementability and effectiveness of the proposed IVSS-LMS algorithm. Furthermore, the sea trial results show that the digital SIC method based on the proposed algorithm can be implemented in real-time and the convergence speed, and steady-state performance are significantly improved.

Universal Performance Bounds for Joint Self-Interference Cancellation and Data Detection in Full-Duplex Communications

This paper studies the joint digital self-interference (SI) cancellation and data detection in an orthogonal-frequency-division-multiplexing (OFDM) full-duplex (FD) system, considering the effect of phase noise introduced by the oscillators at both the local transmitter and receiver. In particular, an universal iterative two-stage joint SI cancellation and data detection framework is considered and its performance bound independent of any specific estimation and detection methods is derived. First, the channel and phase noise estimation mean square error (MSE) lower bounds in each iteration are derived by analyzing the Fisher information of the received signal. Then, by substituting the derived MSE lower bound into the SINR expression, which is related to the channel and phase noise estimation MSE, the SINR upper bound in each iteration is computed. Finally, by exploiting the SINR upper bound and the transition information of the detection errors between two adjacent iterations, the universal bit error rate (BER) lower bound for data detection is derived.

Neural Network Aided Digital Self-Interference Cancellation for Full-Duplex Communication Over Time-Varying Channels

In-band full duplex communication requires precise self-interference cancellation (SIC) to successfully decode the received desired signal. The existing neural network (NN) based SIC scheme uses offline trained NN to estimate the non-linear component of received self-interference (SI) over a static SI channel without additional NN training. For the time-varying SI channel, the NN-aided SIC method needs to retrain the NN during in-band full duplex communication to adapt time-varying channels. However, NN training is not fast enough to be done during full duplex communication. Thus, the SIC performance degrades. In this paper, we propose a digital SIC scheme using channel robust NN which takes estimates of linear SI channel coefficients as an input. It was found that the NN could learn the static part of the non-linear behavior of the SI channel well. Our solution can adapt the time-varying SI channel with only the channel coefficient estimation of linear components and a pre-trained NN. The proposed scheme can successfully reduce the SI to the noise floor for both time-invariant and time-varying SI channels.