The future 6G network will enhance smart cities' data integration and analysis capabilities through Integrated Sensing and Communication (ISAC) technology. This paper proposes a millimeter wave (mmW) in-band full-duplex (IBFD) ISAC system architecture and explores three direction-finding techniques based on subarray splitting for its architecture. Firstly, the mutual interference problem in the IBFD ISAC system was analyzed. Using the Taylor synthesis method to suppress array sidelobes and reduce false alarm rate, combined with a two-dimensional fast Fourier transform (2D-FFT), the direction-finding accuracy is improved under an extremely low signal-to-noise ratio (SNR). Then, the performance of three direction-finding methods was compared through simulation. The simulation results showed that the sum difference beam direction-finding method has better mean square error (MSE) performance. In addition, a sum difference beam direction-finding experiment was conducted, and the direction-finding errors for moving and static targets were as low as 0.6° and 0.5°, respectively, demonstrating excellent direction-finding capability.

This paper proposes an integrable analog domain linearization architecture for power amplifiers (PAs) in multi-input multi-output (MIMO) systems, using a spectrum shaping circuit with nonlinear feedback. This architecture consists of a nonlinear distortion extracting loop and an N-order spectrum shaping circuit. The extracting loop aligns the PA input and output signals in amplitude with a 180-degree phase difference and then adds them together to extract the nonlinear distortion signal. The spectrum shaping circuit reshapes the spectrum of the extracted nonlinear distortion signal using N identical analog chains but with different group delays and attenuation parameters, and finally injects it back to the PA input to suppress the nonlinear distortion of the target frequency. Moreover, the delay in the remaining spectrum shaping channels has multiple relationships to the first channel, which can be easily integrated into the PA design stage with low complexity. Particularly, the center frequency of the nonlinearity suppression can be easily shifted by modifying the attenuation parameters in the N-order spectrum shaping circuit. We designed the proposed architecture using off-the-shelf discrete components and demonstrated its nonlinear distortion suppression performance at different target frequencies for the PA chip CMPA006002F.

Blind Image Quality Assessment (BIQA) aims to simulate human assessment of image quality. It has a great demand for labeled data, which is often insufficient in practice. Some researchers employ unsupervised methods to address this issue, which is challenging to emulate the human subjective system. To this end, we introduce a unified framework that combines semi-supervised and incremental learning to address the mentioned issue. Specifically, when training data is limited, semi-supervised learning is necessary to infer extensive unlabeled data. To facilitate semi-supervised learning, we use knowledge distillation to assign pseudo-labels to unlabeled data, preserving analytical capability. To gradually improve the quality of pseudo labels, we introduce incremental learning. However, incremental learning can lead to catastrophic forgetting. We employ Experience Replay by selecting representative samples during multiple rounds of semi-supervised learning, to alleviate forgetting and ensure model stability. Experimental results show that the proposed approach achieves state-of-the-art performance across various benchmark datasets. After being trained on the LIVE dataset, our method can be directly transferred to the CSIQ dataset. Compared with other methods, it significantly outperforms unsupervised methods on the CSIQ dataset with a marginal performance drop (-0.002) on the LIVE dataset. In conclusion, our proposed method demonstrates its potential to tackle the challenges in real-world production processes.

Due to the popularity of unmanned aerial vehicles (UAVs), UAV detection technology has attracted considerable attention. In order to widely deploy UAV detection for preventing civil UAVs, a UAV detection method that can be used with any transceiver and operate in parallel with any communication system is proposed in this paper. UAV flights influence electromagnetic environments during signal propagation, and the proposed method detects UAVs based on the variance of higher-order cumulants. In this paper, the principle of the method is deduced and proven, and the detection performance is analysed. Explicit expressions for the detection and false alarm probabilities are obtained, and the influencing factors are investigated. Finally, the feasibility of the proposed method is verified experimentally, and the detection distance, signal-to-noise ratio and detection height are analysed. The results give the effective detection distance and show that the proposed method has superior anti-noise performance.

Full duplex (FD) communication is considered as a promising technology in the development of 5G-advanced and 6G systems as it theoretically doubles the capability of channel. However, this improvement relying on a simultaneously bidirectional manner of communication induces intrinsic self-interference (SI) demanding to be fully cancelled, which is generally intractable. This challenge is minimized in the scenario of integrated access and backhaul (IAB) networks operated in millimeter wave (mmW) band, as its transceivers are stationary and the complexity of SI is greatly reduced by beamforming technique. As a matter of fact, FD can be a pioneering technique to unlock the full potential mmW-based IAB network by releasing its suffering of the half-duplex inefficiency. This article presents the design principle and validation of a practical SI cancellation (SIC) technique in the case of high transmission power class in mmW-based IAB networks. The proposed technique sequentially eliminates SI from the spatial, RF, and digital domains that reduces the SI down to the noise floor. To validate the technique, a prototype system is developed in accordance with 5G IAB specifications and field tests are conducted. Results suggest that the designed mmW SIC transceiver significantly reduces residual-interference to noise ratio (R-INR) to 2.1 dB or less. Additionally, a system-level simulation is conducted in line with 5G IAB evaluation methodology, which explores the potential performance gain of the proposed technique in presence of cross-link interference (CLI). Results indicate that the method could yield a cell throughput gain of about 84%, compared to the current time division duplex deployment.

The ever-increasing roll-out of 5G integrated access and backhaul (IAB) networks in millimeter wave (mmW) band and its current hard-constraint of half duplex operation motivate the study of full duplex (FD) communication in a high power beamforming system. In an mmW IAB network using FD, the intrinsic self-interference inherits the nature of mmW high attenuation and cross link interference can be quite manageable via sharp beamforming between fixed nodes. As a matter of fact, mmW IAB could be a pioneering use case of FD in near future. In this article, a practical self-interference cancellation (SIC) transceiver design is presented targeting for “down to noise floor” SIC in the case of high transmission power class. We developed an mmW prototype testbed system in accordance with 5G IAB specifications. Our experimental results via prototype verifies the feasibility of the designed mmW SIC transceiver and confirms the potential of 2 times throughput gain from FD compared with conventional half duplex in an IAB scenario.

Integrating full duplex and phased arrays is promising for future wireless communication systems. However, in the joint systems, the strong self-interference (SI) signals leaked from the transmit array will superpose on each receiving antenna, which puts forward strict demands for the dynamic range and linearity of the low noise amplifiers. In this work, we focus on how to cancel the superposed SI signal using an analog multi-tap filter in wideband scenarios. We model the wideband near-field SI channel for the full duplex array and analyze the optimal cancellation performance with and without device errors, respectively. The theoretical analysis is verified by simulation, which indicates that the SI signal with 200 MHz bandwidth can be canceled to the noise level by only two taps without device errors. Moreover, the step sizes of the variable attenuators and phase shifters need to be less than 0.6 dB and 4 degrees, respectively, to cancel the SI above 30 dB with two taps, and the RF canceller with more taps is more robust in the existence of device errors, that is, the better cancellation performance.

Full duplex (FD) communication is an enabling technology with simultaneous uplink and downlink transmission over the same spectrum, which could not only virtually double the spectrum but also shorten the latency of bi-directional communications. One of the key challenges to bring full duplex into reality is how to design a practically implementable self-interference cancellation (SIC). This paper promotes a practical joint-design of SIC capable of >120dB SIC gain to make in-band FD practically viable. It consists of novel integrated SIC antenna, multi-tap tunable RF SIC and non-linear digital SIC. Further, a prototype system implemented using in-band FD with 5G NR commercial level hardware components is presented, which not only verifies in-band FD is practically implementable with the proposed joint SIC, but also achieves highest SIC results, i.e. 122.5dB SIC capability with 32dBm transmit power, to our best knowledge. This result confirms the appealing potential of in-band FD and conclusively, the in-band FD communication with the developed effective SIC turns out to be a promising enabler for future business thriving.

In simultaneous transmit and receive (STAR) phased array systems, suffering from the multi-dimensional cross-coupling strong self-interference (SI), the radio frequency (RF) front-end of receive array is severely saturated. Against this issue, we present a transmit beamforming (TxBF) SI cancellation (SIC) design to construct the TxBF vector, where a robust TxBF SIC optimization problem with maximum receive power constraints and a worst-case uncertainty channel error model is formulated, the approximation solution of which is solved by the semidefinite relaxation and S-procedure. Simulation results show that our design effectively avoids the RF front-end saturation at the cost of near-minimum beamforming gain loss within a given uncertainty channel error bound.

Design of high-efficiency power amplifier (PA) is one of the key challenges to realize green radios, wherein digital predistortion (DPD) is deployed to reduce the PA's power back-off and thus increase its power efficiency. As the bandwidth of the transmit signal increases, stringent requirements are posed on the DPD linearization performance with limited sampling rate and dynamic range for the analog-to-digital converter (ADC) in the DPD feedback channel. In this paper, under a fixed ADC sampling rate, novel DPD architecture is proposed to compensate for the PA nonlinearity with limited ADC dynamic range. In the feedback channel of the proposed architecture, an extra radio frequency (RF) cancellation chain is introduced to eliminate the linear component of the PA amplified signal, and thus the requirement on the ADC dynamic range can be significantly reduced. Subsequently, by accurately estimating the loop delay and attenuation of the cancellation chain, the baseband replica of the RF cancelling signal is recovered, and the original PA output signal is rebuilt to estimate the DPD coefficients. Finally, experiments show that for the long term evolution (LTE)-advanced signals, the proposed architecture can achieve an adjacent channel leakage ratio lower than -47.6 dBc, which outperforms the conventional DPD by about 3.4 dB, with the effective bits of the ADC being reduced by 4.4 and a power added efficiency of 43.8% with 7.3 dB power back-off being observed for a fabricated Doherty PA with 50-dBm saturation power.

This paper presents the nonlinear effects of the analog self-interference (SI) canceller and a practical solution to suppress the nonlinear distortions in multiple-input multiple-output (MIMO) full-duplex wireless communication systems. Due to the inherent nonlinearities of the active radio frequency (RF) components used to tune the attenuations and the phase shifts in the analog SI cancellers, nonlinear distortions are introduced to the residual SI signal by the analog cancellation and enter the receive chain. In this paper, we build an extra feedback chain for each analog canceller to obtain the reference signal coupled from the transmitted RF signal and observe the characteristics of the canceller. Using the observations, we develop a nonlinear model including all the cancellers at each receive antenna with the presence of MIMO SI channel to estimate the nonlinear components. By subtracting the model estimates from the received signal instantaneously, the corresponding nonlinear distortions are effectively mitigated. After the nonlinearity mitigation, a linear digital cancellation scheme based on the Maximum Likelihood Estimation is applied to further reduce the residual SI signal caused by the MIMO SI channel to the noise floor. Experiments are performed on a 2x2 MIMO full-duplex testbed to validate the effectiveness of the proposed nonlinearity modeling and suppression method using Long Term Evolution signals of 20-MHz bandwidth.

The sampling clock accuracy of the digital predistortion (DPD) feedback path is limited by nonideal electronic components, which introduces random clock jitter and thus degrades the linearization performance. In this paper, we propose a new DPD architecture capable of estimating and mitigating the sampling clock jitter. The theoretical analysis reveals that the sampling clock jitter has a adverse effect on the signal-to-noise ratio (SNR) of the samples received and hence degrades the DPD performance. By applying the proposed reference injection method, the clock jitter can be estimated and mitigated, effectively. Simulation results demonstrate that the proposed DPD architecture can improve the normalized mean square error (NMSE) and the adjacent channel leakage ratio (ACLR) performances, compared with conventional DPD architecture when feedback sampling clock jitter is considered.

Cubic metric (CM) is being regarded as a more accurate metric for envelope fluctuations of orthogonal frequency division multiplexing (OFDM) signals than peak-to-average power ratio (PAPR). Iterative clipping and filtering (ICF) is a simple and efficient technique for PAPR reduction. However, our analysis shows that this technique can not actually achieve sufficient CM reduction due to the difference between the two metrics. In this paper, based on the definition of CM, a new clipping method called descendent clipping is proposed, which can achieve more CM reduction by introducing a new parameter called descent factor. Further, we combine descendent clipping with filtering and develop two iterative descendent clipping and filtering (IDCF) algorithms: adaptive IDCF and fixed IDCF. Simulation results show that these two algorithms offer better performance and much faster convergence than the conventional ICF technique when used to reduce CM.

Iterative clipping and filtering (ICF) is a well-known technique to reduce the peak-to-average power ratio (PAPR) of orthogonal frequency division multiplexing (OFDM) signals. Recently, Wang and Luo investigated the clipped signal and proposed a modified algorithm called optimized ICF (OICF). This is an optimal algorithm since it can achieve the required PAPR reduction with minimum in-band distortion and far fewer iterations. However, OICF needs to solve a convex optimization problem with O(N3) complexity, where N represents the number of subcarriers. In this paper, instead of analyzing the clipped signal, we study the clipping noise and propose a simplified OICF algorithm. In the new algorithm, solving the convex optimization problem is approximated by some simple algebraic operations and the computational complexity reduces to O(N). Simulation results show that after three iterations, the original OICF algorithm can achieve the desired PAPR while the simplified one exhibits almost the same performance: for a 128-subcarrier and quadrature phase shift keying (QPSK) modulated OFDM system, the PAPR-reduction performance difference between the two algorithms are 5×10-3dB at a 10-4clipping probability and the bit-error-rate performance difference is 6×10-3dB at a 10-7error probability.