Self-interference Channel Research Articles

Digital Self-Interference Canceler with Joint Channel Estimator for Simultaneous Transmit and Receive System.

Simultaneous transmit and receive wireless communications have been highlighted for their potential to double the spectral efficiency. However, it is necessary to mitigate self-interference (SI). Considering both the SI channel and remote transmission (RT) channel need to be estimated before equalizing the received signal, we propose two adaptive algorithms for linear and nonlinear self-interference cancellation (SIC), based on a multi-layered joint channel estimator structure. The proposed algorithms estimate the RT channel while performing SIC, and the multi-layered structure ensures improved performance across various interference-to-signal ratios. The M-estimate function enhances the robustness of the algorithm, allowing it to converge even when affected by impulsive noise. For nonlinear SIC, this paper introduces an adaptive algorithm based on generalized Hammerstein polynomial basis functions. The simulation results indicate that this approach achieves a better convergence speed and normalized mean squared difference compared to existing SIC methods, leading to a lower system bit error rate.

LoneSTAR: Analog Beamforming Codebooks for Full-Duplex Millimeter Wave Systems

This work develops LONESTAR, a novel enabler of full-duplex millimeter wave (mmWave) communication systems through the design of analog beamforming codebooks. LONESTAR codebooks deliver high beamforming gain and broad coverage while simultaneously reducing the self-interference coupled by transmit and receive beams at a full-duplex mmWave transceiver. Our design framework accomplishes this by tolerating some variability in transmit and receive beamforming gain to strategically shape beams that reject self-interference spatially while accounting for digitally-controlled analog beamforming networks and self-interference channel estimation error. By leveraging the coherence time of the self-interference channel, a mmWave system can use the same LONESTAR design over many time slots to serve several downlink-uplink user pairs in a full-duplex fashion without the need for additional self-interference cancellation. Compared to those using conventional codebooks, full-duplex mmWave systems employing LONESTAR codebooks can mitigate higher levels of self-interference, tolerate more cross-link interference, and demand lower SNRs in order to outperform half-duplex operation—all while supporting beam alignment. This makes LONESTAR a potential standalone solution for enabling simultaneous transmission and reception in mmWave systems, from which it derives its name.

Frequency-Domain RF Self-Interference Cancellation for In-Band Full-Duplex Communications

Wireless backhaul has recently gained a significant amount of interest as a cost-effective solution in comparison with conventional backhaul technologies with dedicated microwave links or fiber optics. Self-interference cancellation (SIC) is an enabling technology that allows wireless backhaul to operate in the more spectrum-efficient in-band full-duplex (IBFD) operation mode instead of the out-of-band mode. Compared to Wi-Fi IBFD transceivers, wireless in-band backhaul systems face some unique challenges, such as significantly higher transmission power and much larger propagation delay spread for the self-interference signal, especially in the low-frequency bands under 1 GHz, which often prevent accurate SIC performance. The SIC is often implemented with an interference-cancelling filter, where the filter weights are essentially the channel estimates of the self-interference signals. In this paper, a frequency-domain Radio Frequency (RF) SIC (RF-SIC) framework with a novel filter weight optimization algorithm is proposed to tackle the challenges of wireless in-band backhaul. The proposed RF-SIC does not require a dedicated training phase which needs to stop the transmission of the backhaul signal. Moreover, it has the capability of tracking the self-interference channel variation since the filter weights are updated in a block-by-block fashion.

Self-interference cancellation in underwater acoustic communications systems using orthogonal pilots in IBFD

This paper proposes a Self-interference (SI) cancellation system model of Underwater acoustic (UWA) communication for in-band full-duplex (IBFD) technology. The SI channel is separated from the Far channel by exploiting a concurrently orthogonal pilot channel estimation technique using two orthogonal frequency-division multiplexing (OFDM) blocks to establish orthogonality between them based on a unitary matrix. Compared to the half-duplex channel estimator, the mean squared error (MSE) and the bit error rate (BER) provided strong evidence for the efficiency of the proposed SI cancellation. Since full-duplex systems are more efficient than half-duplex ones, the proposed approach might be seen as a viable option for them. The proposed method proved effective when used with a fixed full-duplex (FD) position and FD shifting of up to 4°. Different channel lengths and distances are adopted to evaluate the proposed method. Initial findings indicate that MSE for the SI channel minimum mean-square error (MMSE) estimator at 20 dB is 0.118 · 10−3, for fixed FD. In addition, this paper presents a geometry channel model for the Far channel in the IBFD underwater communication system that describes the propagation delay of the multipath reflection. The simulation results for the multipath propagation delay spread are similar to the traditional results, with the delay spread of the suggested model reaching (79 ms), which is close to the Bellhop simulator result (78 ms).

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.

Iterative phase noise suppression for full-duplex communication systems

Oscillator phase noise is one of the bottlenecks that limits the self-interference (SI) cancellation capability of full-duplex systems. In this paper, we propose a method for the suppression of common phase error (CPE) and intercarrier interference (ICI) induced by the phase noise in full-duplex orthogonal frequency division multiplexing (OFDM) systems. First, we regard the effect of CPE as a portion of the SI channel and perform estimation, reconstruction and elimination in the time domain. Then, the ICI signal is estimated and suppressed in the frequency domain. Additionally, by analysing the performance of proposed algorithm, we further develop an iterative mechanism to reduce the parameter estimation error and improve SI cancellation capability. Simulation results show that the proposed method has a significant SI cancellation capability improvement over the traditional SI cancellation schemes.

Performance Analysis of Self-Interference Cancellation in Full-Duplex Massive MIMO Systems: Subtraction Versus Spatial Suppression

Massive multiple-input multiple-output (MIMO) and full-duplex (FD) are promising candidates for achieving the spectral efficiency to meet the needs of 5G communications. One essential key to realizing practical FD massive MIMO systems is how to effectively mitigate the self-interference (SI). Conventionally, however, the performance comparison of different SI methods by reflecting the actual channel characteristics was insufficient in the literature. Accordingly, this paper presents a performance analysis of SI cancellation (SIC) methods in FD massive MIMO systems. Analytical and numerical results confirm that, in an imperfect channel-estimation case, the ergodic rates performance of the spatial suppression in the uplink outperforms those of the SI subtraction, due to the correlation between the precoder and the estimation error of the SI channel. In addition, we discuss which method performs better under different given system constraints such as uplink and downlink sum rates, the total transmit power, and the power scaling law.

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.

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.

Hybrid Beamforming Design for Self-Interference Cancellation in Full-Duplex Millimeter-Wave MIMO Systems with Dynamic Subarrays.

Full-duplex (FD) millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication is a promising solution for the extremely high-throughput requirements in future cellular systems. The hybrid beamforming structure is preferable for its low hardware complexity and low power consumption with acceptable performance. In this paper, we introduce the hardware efficient dynamic subarrays to the FD mmWave MIMO systems and propose an effective hybrid beamforming design to cancel the self-interference (SI) in the considered system. First, assuming no SI, we obtain the optimal fully digital beamformers and combiners via the singular value decomposition of the uplink and downlink channels and the water-filling power allocation. Then, based on the obtained fully digital solutions, we get the dynamic analog solutions and digital solutions using the Kuhn-Munkres algorithm-aided dynamic hybrid beamforming design. Finally, we resort to the null space projection method to cancel the SI by projecting the obtained digital beamformer at the base station onto the null space of the equivalent SI channel. We further analyze the computational complexity of the proposed method. Numerical results demonstrate the superiority of the FD mmWave MIMO systems with the dynamic subarrays using the proposed method compared to the systems with the fixed subarrays and the half-duplex mmWave communications. When the number of RF chains is 6 and the signal-to-noise ratio is 10 dB, the proposed design outperforms the FD mmWave MIMO systems with fixed subarrays and the half-duplex mmWave communications, respectively, by 22.4% and 47.9% in spectral efficiency and 19.9% and 101% in energy efficiency.

Beamformed Self-Interference Measurements at 28 GHz: Spatial Insights and Angular Spread

We present measurements and analysis of self-interference in multi-panel millimeter wave (mmWave) full-duplex communication systems at 28 GHz. In an anechoic chamber, we measure the self-interference power between the input of a transmitting phased array and the output of a colocated receiving phased array, each of which is electronically steered across a number of directions in azimuth and elevation. These self-interference power measurements shed light on the potential for a full-duplex communication system to successfully receive a desired signal while transmitting in-band. Our nearly 6.5 million measurements illustrate that more self-interference tends to be coupled when the transmitting and receiving phased arrays steer their beams toward one another but that slight shifts in steering direction (on the order of one degree) can lead to significant fluctuations in self-interference power. We analyze these measurements to characterize the spatial variability of self-interference to better quantify and statistically model this sensitivity. Our analyses and statistical results can be useful references when developing and evaluating mmWave full-duplex systems and motivate a variety of future topics including beam selection, beamforming codebook design, and self-interference channel modeling.

Optical Multi-Tap RF Canceller for In-Band Full-Duplex Wireless Communication Systems

In-band full-duplex (IBFD) technology has become important for future wireless communications, due to its ability of increasing the radio-frequency (RF) spectrum efficiency. However, the benefits can only be realized if the self-interference (SI) is sufficiently suppressed. RF cancellation is important for IBFD systems due to its ability of SI mitigation. But it becomes more difficult for RF cancellation while the frequency and bandwidth increase. In real scenarios, the response of the multi-path SI channel is not frequency-flat, which also limits the cancellation performance. To solve these problems, we present a photonic-enabled multi-tap RF canceller in this paper. The proposed RF canceller has the ability of cancelling multi-path SI. The tap coefficients are precisely adjusted by optical spectrum processing. A prototype system with 8 taps is demonstrated in this paper. The measured results show 25 dB average cancellation depth over 1 GHz cancellation bandwidth under over-the-air conditions. To verify the signal of interest (SOI) recovery capability of the novel RF canceller, an IBFD wireless communication experiment based on 16-quadrature amplitude modulation (16-QAM) was demonstrated, the SOI was successfully recovered.

Digitally assisted photonic analog domain self-interference cancellation for in-band full-duplex MIMO systems via the LS algorithm with adaptive order.

A digitally assisted photonic analog domain self-interference cancellation (SIC) and frequency downconversion method is proposed for in-band full-duplex multiple-input multiple-output (MIMO) systems using the least square (LS) algorithm with adaptive order. The SIC and frequency downconversion are achieved in the optical domain via a dual-parallel Mach-Zehnder modulator, while the downconverted signal is processed by the LS algorithm with adaptive order that is used to track the response of the multipath self-interference (SI) channel and reconstruct the reference signal for SIC. The proposed method can overcome the reconstruction difficulty of the multipath analog reference signal for SIC with high complexity in the MIMO scenario and can also solve the problem that the order of the reference reconstruction algorithm is not optimized when the wireless environment changes. An experiment is carried out to verify the concept. SIC depths of 30.2, 26.9, 23.5, 19.5, and 15.8 dB are achieved when the SI signal has a carrier frequency of 10 GHz and baud rates of 0.1, 0.25, 0.5, 1, and 2 Gbaud, respectively. The convergence of the LS algorithm with adaptive order is also verified for different MIMO multipath SI signals.

Robust Transceiver Design for IRS-Assisted Cascaded MIMO Communication Systems.

Intelligent reconfigurable surfaces (IRSs) have gained much attention due to their passive behavior that can be a successor to relays in many applications. However, traditional relay systems might still be a perfect choice when reliability and throughput are the main concerns in a communication system. In this work, we use an IRS along with a decode-and-forward relay to provide a possible solution to address one of the main challenges of future wireless networks which is providing reliability. We investigate a robust transceiver design against the residual self-interference (RSI), which maximizes the throughput rate under self-interference channel uncertainty-bound constraints. The yielded problem turns out to be a non-convex optimization problem, where the non-convex objective is optimized over the cone of semidefinite matrices. We propose a novel mathematical method to find a lower bound on the performance of the IRS that can be used as a benchmark. Eventually, we show an important result in which, for the worst-case scenario, IRS can be helpful only if the number of IRS elements are at least as large as the size of the interference channel. Moreover, a novel method based on majorization theory and singular value decomposition (SVD) is proposed to find the best response of the transmitters and relay against worst-case RSI. Furthermore, we propose a multi-level water-filling algorithm to obtain a locally optimal solution iteratively. We show that our algorithm performs better that the state of the art in terms of time complexity as well as robustness. For instance, our numerical results show that the acheivable rate can be increased twofold and almost sixfold, respectively, for the case of small and large antenna array at transceivers.

Full Duplex Integrated Access and Backhaul for 5G NR: Analyses and Prototype Measurements

Researchers for the third-generation partnership project (3GPP) have been exploring — as a cost-effective alternative to wired backhaul — integrated access and backhaul (IAB) frameworks for 5G new radio (NR). A promising solution for this framework is the integration of full duplex (FD) technologies to enhance the spectral efficiency and efficiently utilize network resources. This approach, which we refer to as FD IAB, involves a significant technical challenge — self-interference (SI) in the IAB framework. In fact, this challenge casts doubt over the performance and feasibility of FD IAB. In this article, we introduce the FD IAB framework and its enabling technologies and also evaluate the framework's link-level SI reduction and system-level downlink throughput performance. Thereafter, we validate the attenuation level in the SI channel with antenna separation and high directional gain through 28 GHz hardware prototype measurements. Our numerical evaluations and hardware prototype measurements confirm that FD IAB represents a promising framework for 5G NR.

Ray-Tracing Simulation and Verification of Full-Duplex Self-Interference Channels in an Urban Scenario

Compared with the half-duplex (HD), co-time co-frequency full-duplex (CCFD) technology can effectively improve spectrum utilization. Self-interference (SI) is one of the major factors limiting full-duplex (FD) performance. In this letter, we build the same scattering environment as the field measurement campaign, and simulate the FDSI and the conventional base station-to-base station (B2B) channels using ray-tracing technology. We simulate all the multi-path components (MPCs) and observe the power delay profiles (PDPs), received power, and delay spreads (DS) by changing the angular gap between and the height of the transmitting (Tx) and the receiving (Rx) antennas. The parameters and profiles of the simulated SI channel are consistent with and thus verify the measurement results. To further compare the FD channels and the conventional base station-to-user equipment (B2U) channel, we also compare the measured and simulated SI channels with the 3GPP channel model. It is interesting to find out that the channel characteristics are quite similar in the same scenario.

Secrecy Coding Analysis of Short-Packet Full-Duplex Transmissions with Joint Iterative Channel Estimation and Decoding Processes.

This paper studies the secrecy coding analysis achieved by the self-jamming technique in the presence of an eavesdropper by considering a short-packet Full-Duplex (FD) transmission developed based on iterative blind or semi-blind channel estimation and advanced decoding algorithms. Indeed, the legitimate receiver and eavesdropper can simultaneously receive the intended signal from the transmitter and broadcast a self-jamming or jamming signal to the others. Unlike other conventional techniques without feedback, the blind or semi-blind algorithm applied at the legitimate receiver can simultaneously estimate, firstly, the Self-Interference (SI) channel to cancel the SI component and, secondly, estimate the propagation channel, then decode the intended messages by using 5G Quasi-Cyclic Low-Density Parity Check (QC-LDPC) codes. Taking into account the passive eavesdropper case, the blind channel estimation with a feedback scheme is applied, where the temporary estimation of the intended channel and the decoded message are fed back to improve both the channel estimation and the decoding processes. Only the blind algorithm needs to be implemented in the case of a passive eavesdropper because it achieves sufficient performances and does not require adding pilot symbols as the semi-blind algorithm. In the case of an active eavesdropper, based on its robustness in the low region of the Signal-to-Noise Ratio (SNR), the semi-blind algorithm is considered by trading four pilot symbols and only requiring the feedback for channel estimation processes in order to overcome the increase in noise in the legitimate receiver. The results show that the blind or semi-blind algorithms outperform the conventional algorithm in terms of Mean Square Error (MSE), Bit Error Rate (BER) and security gap (). In addition, it has been shown that the blind or semi-blind algorithms are less sensitive to high SI and self-jamming interference power levels imposed by secured FD transmission than the conventional algorithms without feedback.

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.