In this Letter, we propose and experimentally demonstrate a novel, to the best of our knowledge, IQ-receiver architecture for high-capacity D-band wireless transmission, enabled by delta-sigma modulation (DSM). An improved IQ-maximal-ratio-combining (IQ-MRC) algorithm is introduced to mitigate performance degradation induced by frequency-selective fading and IQ imbalance, providing an additional signal-to-noise ratio (SNR) gain of approximately 1 dB. Using the proposed system, we demonstrate 30.2 km transmission of an 8 Gbaud DSM 256 quadrature amplitude modulation (QAM) signal with a net data rate of 13.91 Gb/s, achieving a BER below the threshold of 15% overhead soft decision forward error correction (SD-FEC). To the best of our knowledge, this is the longest reported transmission distance for DSM-modulated signals in the D-band.

This paper addresses moving target detection in the presence of an Interfering Target (IT) using Passive Bistatic Radar (PBR) systems affected by hardware mismatches. We focus on In-phase/Quadrature-phase Imbalances (IQIs) common in Direct-Conversion Receivers (DCRs), where IT echoes mask the Main Target (MT). When unmitigated, both effects significantly degrade detection performance. Unlike existing approaches, we assume unknown noise power and unknown target Doppler Shifts (DSs), further increasing the detection challenge. We develop a new signal model for this scenario, formulate a Binary Composite Hypothesis Testing (BCHT) problem, and derive a closed-form asymptotically optimal Generalized Likelihood Ratio Test (GLRT) detector using the Neyman-Pearson criterion. To improve computational efficiency, we exploit Fast Fourier Transform (FFT) symmetry properties and employ batch data processing, substantially reducing computational complexity and execution time. We also analyze the impact of amplitude and phase mismatches on the PBR signal model. Theoretical analysis and simulations demonstrate improved detection probability and enhanced robustness to IQI compared with state-of-the-art methods.

Terahertz (THz) communication is envisioned as a key technology for 6G and beyond wireless systems owing to its multi-GHz bandwidth. To maintain the same aperture area and the same link budget as the lower frequencies, ultra-massive multi-input and multi-output (UM-MIMO) with hybrid beamforming is promising. Nevertheless, the hardware imperfections particularly at THz frequencies, can degrade spectral efficiency and lead to a high symbol error rate (SER), which is often overlooked yet imperative to address in practical THz communication systems. In this paper, the hybrid beamforming is investigated for THz UM-MIMO systems accounting for comprehensive hardware imperfections, including DAC and ADC quantization errors, in-phase and quadrature imbalance (IQ imbalance), phase noise, amplitude and phase error of imperfect phase shifters and power amplifier (PA) nonlinearity. Then, a two-stage hardware imperfection compensation algorithm is proposed. In the first stage, a deep neural network (DNN) based unified hardware imperfection model is developed to represent the combined hardware imperfections. Furthermore, to balance the performance and model complexity, a tailored network slimming framework is proposed using three slimming methods including pruning, parameter sharing, and power-aware scheme to slim the network in the first stage. In the second stage, the digital precoder in the transmitter (Tx) or the combiner in the receiver (Rx) is designed using neural network (NN) to effectively compensate for these imperfections. Numerical results show that the Tx compensation can perform better than the Rx compensation. Additionally, using the combined slimming methods can reduce parameters by 97.2% and running time by 39.2% while maintaining nearly the same performance in both uncoded and coded systems.

Cognitive radios adaptively sense and use available spectrum but suffer performance loss due to IQ imbalance, which causes interference from gain and phase mismatches in transceivers. Blind IQ-imbalance compensation avoids pilots and suits cognitive radios that must continually adjust to changing channels. While OFDM and SC-FDE have known blind-compensation methods, CE-OFDM has not been studied, and immunity to frequency-dependent imbalance remains unreported. This paper presents the first unified comparison of OFDM, CE-OFDM, and SC-FDE under frequency-independent IQ imbalance, enabled by adapting an SC-FDE blind-compensation technique.

Cooperative jamming is one of the promising technologies for securing wireless communications. The cooperative jammer transmits jamming to deteriorate the eavesdropping channel, while the authorized receiver implements cooperative jamming cancellation (CJC) using the pre-stored prior information, thus achieving confidential communication at the physical layer. However, the signal transmission will introduce time delay and frequency offset, as well as zero-intermediate-frequency structures that will cause in-phase and quadrature (IQ) imbalances and local oscillator (LO) leakage, which lead to degradation of the CJC performance. In this paper, we specifically analyze the combined effect of time-frequency mismatch, IQ imbalance and LO leakage on the CJC performance by deducing the closed-form expression for the jamming cancellation ratio. A CJC architecture considering time-frequency mismatch, IQ imbalance and LO leakage is proposed, and the corresponding recursive algorithm for CJC is presented. Simulation results show that the proposed algorithm can effectively improve the CJC performance with the presence of time-frequency mismatch, IQ imbalance and LO leakage, and thus improves the security of the communication system.

Faster-than-Nyquist (FTN) tight filtering introduces serious inter-symbol interference (ISI) impairment, leading to an insufficient compensation range for conventional IQ imbalance compensation algorithms. Furthermore, receiver (Rx) IQ imbalance and ISI impairments significantly increase the convergence cost required by the squared Gardner phase detector (SGPD) timing recovery algorithm to establish a timing synchronization loop. This paper proposes a joint Rx IQ compensation and timing recovery scheme. By embedding a two-stage IQ imbalance compensation algorithm into the timing recovery feedback loop, the proposed scheme could effectively estimate and compensate for Rx IQ imbalance. Meanwhile, thanks to the innovative scheme, which equalizes Rx IQ imbalance and ISI during the timing feedback loop, the convergence cost of timing recovery could be reduced compared with the conventional blind frequency domain (BFD) scheme. The simulation results of 128 GBaud polarization multiplexing (PM) 16-quadrature amplitude modulation (QAM) FTN wavelength division multiplexing (WDM) transmission systems demonstrate that the proposed scheme could bring about 14%, 12.5%, and 16.6% improvements in the compensation range for Rx IQ amplitude imbalance, phase imbalance, and skew, respectively, compared with the conventional one. Meanwhile, the convergence cost is reduced by at least 31% with a 0.9 acceleration factor. In addition, 40 GBaud PM-16QAM FTN experiment results show that the proposed scheme could bring about a 0.8 dB improvement in the optical signal noise ratio (OSNR) compared with the conventional BFD scheme.

In the beyond 5G/6G, the usage of the wideband transmission in the higher frequency band is expected. In this paper, we propose a method to compensate IQ imbalance caused by the path length differences between I and Q channels in the direct conversion transmitter in the wideband OFDM systems. In the proposed method, compensation signals are generated using the path length difference and the modulation symbols transmitted on the paired subcarriers which are known in the transmitter side. We analyzed the IQ imbalance and the proposed compensation method, then the effects of the proposed method are explained through the simulation.

This work presents a software-defined visible light communication (SD-VLC) system that integrates carrierless amplitude and phase (CAP) modulation with an adaptive sign-data least mean squares (SDLMS) equalizer. The proposed solution is designed to address key challenges in VLC systems, such as LED bandwidth constraints, inter-symbol interference, and nonlinear distortions, and leverages the PYNQ platform to offer a flexible, reconfigurable, and cost-effective communication architecture tailored for IoT applications. Simulation results demonstrate that CAP modulation not only delivers high spectral efficiency but also inherently mitigates issues such as IQ imbalance and phase noise, thereby reducing hardware complexity. Moreover, the adaptive SDLMS equalizer significantly improves performance in multipath fading environments and reduces the bit error rate by approximately two orders of magnitude. These results underscore the potential of the proposed SD-VLC system to achieve low-cost and highly flexible wireless communication.

This study investigates the performance of Dual-mode index modulation aided orthogonal frequency division multiplexing (DM-OFDM) systems under hardware impairments and varying channel conditions. The spectral efficiency provided by dual-mode operation is analyzed in comparison to conventional index modulation OFDM (OFDM-IM) over Rayleigh and Rician fading channels. Practical hardware impairments, such as phase noise and IQ imbalance, are incorporated into the model to evaluate their effects. Simulations conducted for different subcarrier numbers (N=64/128/256) and active subcarrier configurations (K=1/2/3) demonstrate that DM-OFDM outperforms conventional OFDM-IM in terms of bit error rate (BER) performance under both channel conditions. In high signal to noise ratio (SNR) regions, an error floor caused by hardware distortions is observed, emphasizing the need to consider this effect in system design. While increasing the number of subcarriers and optimizing active subcarrier selection enhances performance, the line-of-sight component in the Rician channel further improves the system's performance.

Editor’s notes: Direct-conversion receivers are used in integrated receivers and communication systems. This article proposes a methodology to measure IQ imbalance in direct-conversion receivers. —Partha Pratim Pande, Washington State University, USA

Ambient backscatter communication (AmBC) offers low-cost and low-power connectivity for Internet of Things (IoT), where a backscatter tag (BT) modulates incident signals transmitted by an ambient radio frequency (RF) source and reflects them to its associated AmBC receiver. In multi-channel multi-tag AmBC, one of major challenges from the aspect of symbol detection is the image channel crosstalk, which is induced by the inevitable in-phase/quadrature (IQ) imbalance. To address this issue, in this paper, we study symbol detection in multi-channel multi-tag AmBC under IQ imbalance. Considering the differential encoding scheme at the BTs, we propose a novel symbol detection model that incorporates IQ imbalance parameters, the presence or absence of both the incident signal and the backscattered signal of the image channel. On this basis, considering an energy difference detector at the AmBC receiver, we derive the closed-form expressions for the bit error rate (BER) as well as the near-optimal detection threshold to minimize BER. However, calculating the near-optimal detection threshold requires prior information, such as the IQ imbalance parameters, the presence probability of the incident signal of the image channel and the backscattered signal of the image channel, the signal power of the ambient RF source, and the noise power, which are typically unknown to the AmBC receiver in practice. To eliminate the need for the prior information, we propose a threshold estimation method using the received samples. Numerical results indicate that under IQ imbalance, directly using the existing method leads to a significant degradation in BER performance. However, this degradation can be effectively mitigated by our derived detection threshold.

In the field of wireless communications, the mitigation of in-phase (I) and quadrature (Q) imbalance and the nonlinearity of power amplifiers (PAs) is a very important issue. In this letter, we propose a new neural network (NN) model, which can be used for joint digital pre-distortion (DPD) of non-ideal IQ modulators and PAs in a transmitter with multiple signal states. The model is based on the methodology of multi-task learning (MTL). In this model, the hidden layers of the main NN are shared by all signal states, and the output layer’s weights and biases are dynamically generated by another NN. The experimental results show that the proposed model can effectively perform joint DPD for IQ-PA systems, and it achieves better overall performance within multiple signal states than the existing methods.

In this paper, an in-field and low-complexity calibration scheme based on cross-power-spectrum (CPS) analysis for in-phase and quadrature (IQ) imperfections of coherent optical transceivers is proposed. This CPS method allows for high-precision estimation of time delays by calculating the cross-spectrum between two signals and extracting phase information. Its computation process only requires FFT operations and simple linear fitting, contributing to lower complexity and simpler implementation for estimating IQ skew compared to other schemes. The robustness of the proposed scheme is investigated through simulation against the mutual influence of IQ skews, amplitude imbalances, and phase imbalances of transceivers, as well as various channel impairments such as local oscillator frequency offset, phase noise, and fiber chromatic dispersion. Moreover, simultaneous calibration of transceiver IQ skews, amplitude imbalances, and phase imbalances in dual-polarization after fiber transmission has been experimentally conducted. The measurement errors for Tx/Rx IQ skews, amplitude imbalances, and phase imbalances are less than 0.2 ps, 0.5 dB, and 1°, respectively. The proposed CPS scheme exhibits a substantial dynamic measurement range of up to ±200 ps for the skew of the coherent optical transceivers. The aforementioned methods effectively compensate for the IQ skews (1.6 ps/4ps), amplitude imbalances (0.58 dB/0.23 dB), and phase imbalances (−2.1°/0.8°) of the Tx/Rx in experimental scenarios involving 20/40Gbaud 16/64 QAM signal transmissions over an 80 km standard single-mode fiber. Thanks to the proposed scheme, the compensated signal exhibits an optical signal-to-noise ratio reduction of about 3 dB at the hard-decision forward error correction threshold and 4 dB at the soft-decision forward error correction threshold for the 20 GBaud 16 QAM and 40 GBaud 16 QAM signals, respectively.

This paper presents an efficient method for compensation of frequency-dependent (FD) transmitter In-phase Quadrature (IQ) imbalance. Proposed method compensates imbalance by exploiting indirect learning architecture (ILA) and complex filters whose coefficients are determined in an iterative process. Compensation performance is assessed after the method has been implemented in a Software Defined Radio (SDR) platform, capable of transmitting modulations at different central frequencies. Measured results demonstrate that the imbalance related images are reduced down to the noise floor. After applying the proposed IQ imbalance correction method, the transmitter image rejection ratio (IRR) is increased by 15dB in the case of an SDR transmitter operating at central frequency of 1.7 GHz. The ADC/DAC sampling rate is 61.44MS/s, while the signal bandwidth, for which the compensation is performed, is 30.72MHz. The advantage of the proposed method is low complexity in terms of a reduced number of coefficients. The method is generic and can be utilized for IQ imbalance compensation when wideband signals are transmitted.

Improved PHY-layer authentication utilizing multi-modal features for mmWave MIMO UAV-enabled systems

Probabilistic constellation shaping (PCS) has played a pivotal role in facilitating capacity enhancement towards Shannon limits. However, the higher cardinality PCS is susceptible to transmission system non-idealities such as transmitter IQ imbalance. In this paper, we demonstrate a phase noise correction algorithm that simultaneously adapts the ideal constellation points and, hence, the decision boundaries, using the gradient descent adaption to tolerate the transmitter IQ imbalance for PCS signals. The equalizer uses a common error signal obtained using the least mean square approach to recover the carrier phase and adapt the ideal constellation points. We numerically investigate the algorithm’s efficacy for 200 GBaud polarization multiplexed PCS-64QAM signal for a range of imbalance and entropy values. We also validate the performance of the proposed algorithm at various optical signal-to-noise ratio (OSNR) values and at larger laser linewidth values. The proposed algorithm applies to any modulation format and does not require any pilot symbols, hence improving the spectral efficiency compared to traditional algorithms that employ pilot symbols.

An end-to-end testbed for In-phase and Quadrature (I/Q) Imbalance (IQI) communication systems based on Software-Defined Radio (SDR) is presented. The scenario under consideration is a Single-Input–Single-Output (SISO) single-carrier communication where the transmitter is heavily affected by IQI, whose effects are mitigated through digital signal processing at the receiver. The presented testbed is highly configurable, enabling the testing of different communication and IQI parameters. Crucial insights into the practical implementation of IQI mitigation techniques, specifically through the use of asymmetric signaling at the receiver, are provided. Initially, a detailed description of the mathematical framework is given. This framework serves as the foundation for the subsequent discussion on system implementation, effectively bridging the gap between research on IQI mitigation and its practical application in single-carrier architectures. Over-The-Air (OTA) Symbol Error Rate (SER) measurements for different constellations validate the receiver design and implementation. The source code of the presented testbed is publicly available.

Automatic modulation classification (AMC) plays a vital role in military and civilian applications, which identifies the modulation schemes of received signals before signal demodulation. Orthogonal frequency division multiplexing (OFDM) technology against the frequency-selective fading channel is widely applied in fourth generation (4G) and fifth generation (5G) communication systems, which may suffer from various hardware impairments, including in-phase and quadrature (IQ) imbalance and carrier frequency offset (CFO). This paper proposes an OFDM modulation classification framework, which incorporates the initial blind IQ imbalance and CFO compensation modules and the cross-selective kernel network (Cross-SKNet). Firstly, a small segment of OFDM signals is utilized for consecutive IQ imbalance and CFO compensation modules to estimate compensation coefficients and reconstruct the received burst OFDM symbols. Subsequently, the Cross-SKNet is initiated using the reconstructed signals. The network comprises the consecutive Cross-Down sampling (Cross-DS) module, the Cross-selective kernel (Cross-SK) module, and the channel and spatial attention classifier, which integrate asymmetric convolution to extract intra-symbol and inter-symbol correlation with reduced computational complexity and leverage selective kernel technology to adaptively learn the receptive field. The proposed framework can identify four different OFDM modulation formats and enhance performance by IQ imbalance and CFO compensation with a fraction of additional computation. Simulation results demonstrate that the proposed Cross-SKNet outperforms the state-of-the-art method across a range of signal-to-noise ratio (SNR) levels and exhibits superior generalization capabilities at low SNR conditions. Based on the simulation results of the generated dataset, the Cross-SKNet achieves a classification accuracy of over <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\bm {95\%}$</tex-math></inline-formula> at SNR > <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\bm {8}$</tex-math></inline-formula> dB. Moreover, the incorporation of IQ imbalance and CFO compensation modules enhances the performance of the Cross-SKNet, which can obtain an accuracy gain of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\bm {8\%}$</tex-math></inline-formula> at low SNR condition of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\bm {-10}$</tex-math></inline-formula> dB.

Optical generation of microwave signals using photonic techniques offers benefits of frequency agility, ease of frequency scaling, and reduced hardware complexity. We demonstrate the generation and detection of QPSK modulated with symbol rates up to 5 GBaud at carrier frequencies of 8-12 GHz through optical heterodyning of two-phase-locked lasers. The received data is demodulated through appropriate post-processing to correct for the phase noise and IQ imbalance. The approach is scalable to mmWave and THz communication.

Joint Channel and IQ Imbalance Compensation Method for MIMO-OFDM Using in Coastal Railway