In-phase And Quadrature-phase Research Articles

Joint estimation of IQ imbalance and PA nonlinearity: An iterative scheme

Power amplifier (PA) nonlinearity and in-phase and quadrature-phase (IQ) imbalance in the transmitter are of critical concern in modern communication systems due to their significant impact on the transmitter performance. In this paper, in order to eliminate their effects without increasing the complexity at the transmitter, we propose an iterative structure for IQ imbalance and PA nonlinearity joint estimation at the receiver side. The strategic design aims to mitigate the influence of one distortion before estimating the other, ultimately improving the accuracy of estimating each distortion. The proposed approach comprises two primary modules: an IQ imbalance estimation module and a PA nonlinearity estimation module. In addition, there are two supporting modules, namely the PA nonlinearity compensation module and the IQ imbalance reconstruction module, positioned before these two primary modules respectively. Furthermore, we have derived the theoretical Cramér–Rao lower bound (CRLB) for the joint distortion model of IQ imbalance and PA nonlinearity. Finally, extensive experiments are conducted to demonstrate the proposed algorithm's capability in estimating hardware distortions and mitigating them.

Reconstruction of OFDM Signals Using a Dual Discriminator CGAN with BiLSTM and Transformer.

Communication signal reconstruction technology represents a critical area of research within communication countermeasures and signal processing. Considering traditional OFDM signal reconstruction methods' intricacy and suboptimal reconstruction performance, a dual discriminator CGAN model incorporating LSTM and Transformer is proposed. When reconstructing OFDM signals using the traditional CNN network, it becomes challenging to extract intricate temporal information. Therefore, the BiLSTM network is incorporated into the first discriminator to capture timing details of the IQ (In-phase and Quadrature-phase) sequence and constellation map information of the AP (Amplitude and Phase) sequence. Subsequently, following the addition of fixed position coding, these data are fed into the core network constructed based on the Transformer Encoder for further learning. Simultaneously, to capture the correlation between the two IQ signals, the VIT (Vision in Transformer) concept is incorporated into the second discriminator. The IQ sequence is treated as a single-channel two-dimensional image and segmented into pixel blocks containing IQ sequence through Conv2d. Fixed position coding is added and sent to the Transformer core network for learning. The generator network transforms input noise data into a dimensional space aligned with the IQ signal and embedding vector dimensions. It appends identical position encoding information to the IQ sequence before sending it to the Transformer network. The experimental results demonstrate that, under commonly utilized OFDM modulation formats such as BPSK, QPSK, and 16QAM, the time series waveform, constellation diagram, and spectral diagram exhibit high-quality reconstruction. Our algorithm achieves improved signal quality while managing complexity compared to other reconstruction methods.

DL-Based OTFS Signal Detection in Presence of Hardware Impairments

Orthogonal time frequency space (OTFS) modulation is an emerging technique for next-generation communication due to its robustness to the doubly dispersive channels under high mobility scenarios. We have designed and analyzed a deep learning (DL)-based OTFS system (DL-OTFS) in the presence of hardware impairments (HI) such as in-phase and quadrature-phase (IQ) component mismatch and DC offset. Further, data augmentation is also considered for the proposed DL-OTFS to enhance the system performance. Numerical results show that the DL-OTFS model can efficiently learn the input and output relation and leads to improved bit error rate (BER) performance than the conventional message passing and minimum mean square error (MMSE)-based receiver with and without HI.

Deep Learning Aided Multi-Level Transmit Power Recognition in Cognitive Radio Networks

According to the regulations of the hybrid access strategy in cognitive radio network, the secondary user (SU) needs to identify the primary user’s (PU) specific transmit power level to avoid unacceptable interference with the PU. However, the conventional transmit power recognition methods cannot accurately identify the transmit power in conditions with low signal-to-noise ratio, fading channels and the existence of noise uncertainty, since those methods are based on a fixed statistical theory to model the dynamic electromagnetic environment mathematically. To address these issues, a ResNet-based multi-level transmission power recognition (MTPR) architecture is presented in this paper. Furthermore, the proposed architecture is implemented in two cases with different observation data. In the first case, the received signal’s covariance matrix (CM) containing rich energy information is used as the observation data of CM-MTPR scheme. To further improve the identification accuracy, in the second case, the in-phase and quadrature-phase (IQ) data sampled from the received signal that preserves more original information is configured as the observation data of IQ-MTPR scheme. The IQ-MTPR scheme, however, consumes additional computing resources which forms a trade-off between identification performance and computational consumption with the CM-MTPR scheme. Simulation results demonstrate the identification performance of the proposed schemes.

Photonic Generation of Multi-Format Radar Waveforms Based on an Integrated Silicon IQ Modulator

We propose and demonstrate a photonic scheme to generate reconfigurable radar waveforms based on an integrated silicon in-phase and quadrature-phase (IQ) modulator. It has significant advantages over commercial LiNbO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> modulator-based schemes in terms of the compatibility with CMOS technology, compact size, light weight, low cost and low power consumption. Experimentally, multi-format radar waveforms, including dual-chirp microwave waveforms, phase-shift keying signals, and amplitude-shift keying signals are successfully generated. The generated waveforms have flexible tunability of center frequency and bandwidth. Our scheme shows the great potential of an on-chip scheme to generate multi-format microwave waveforms for modern radars and electronic warfare systems.

Deep Learning-Based Indoor Localization Using Multi-View BLE Signal.

In this paper, we present a novel Deep Neural Network-based indoor localization method that estimates the position of a Bluetooth Low Energy (BLE) transmitter (tag) by using the received signals’ characteristics at multiple Anchor Points (APs). We use the received signal strength indicator (RSSI) value and the in-phase and quadrature-phase (IQ) components of the received BLE signals at a single time instance to simultaneously estimate the angle of arrival (AoA) at all APs. Through supervised learning on simulated data, various machine learning (ML) architectures are trained to perform AoA estimation using varying subsets of anchor points. In the final stage of the system, the estimated AoA values are fed to a positioning engine which uses the least squares (LS) algorithm to estimate the position of the tag. The proposed architectures are trained and rigorously tested on several simulated room scenarios and are shown to achieve a localization accuracy of 70 cm. Moreover, the proposed systems possess generalization capabilities by being robust to modifications in the room’s content or anchors’ configuration. Additionally, some of the proposed architectures have the ability to distribute the computational load over the APs.

Joint Demodulation and Error Correcting Codes Recognition Using Convolutional Neural Network

Demodulation of the communication signals and blind identification of error-correcting codes (ECC) are two essential purposes in adaptive modulation and coding (AMC) techniques and non-cooperative communication fields. The existing approaches treat them as two separate problems, namely the demodulation of signals with known a <i>priori</i> knowledge (such as channel state information (CSI) or channel noise) and the ECC type identification that depends on the demodulation results. In this paper, a novel one-stage ECC identification approach based on a multi-task deep convolutional neural network (MT-DCNN) is presented. With this architecture, the proposed method automatically recognizes the ECC types of the baseband in-phase and quadrature-phase (IQ) data without relying on any conventional demodulators. Precisely, the proposed MT-DCNN consists of three modules: the feature extraction module, the demodulation module, and the ECC types recognition module. Experiment results show that the proposed architecture can accurately identify the ECC types of the baseband IQ signals and is superior to those of the existing two-stage recognition approaches.

Experimental demonstration of a broadband optoelectronic chaos system based on highly nonlinear configuration of IQ modulator.

We experimentally investigated a novel broadband optoelectronic chaos generation scheme. The proposed system is achieved by adopting the highly nonlinear operation of an electro-optical exclusive-NOR (XNOR) logic gate and two delayed feedback loops that refer to the Boolean chaos model. The XNOR gate is established by a commercial use inphase and quadrature-phase (IQ) modulator that works at a specific bias point. The resulting power spectrum of the broadband chaos signal extends from DC to 29.1 GHz (10 dB bandwidth), and the probability density distribution is Gaussian distribution like. Owing to the strong nonlinearity of XNOR operation, the conditions to enter the chaos region are more relaxed compared to traditional optoelectronic oscillator (OEO) chaos systems, and the time delay signature (TDS) of the feedback loop is also suppressed. Moreover, to further enhance the performance of the generated chaos signal, we injected the optoelectronic chaotic signal into a semiconductor laser. Experimental results indicate that after the cascade optical injection, the bandwidth of the output chaos signal is extended to 38.4 GHz and the TDS is completely concealed; meanwhile, a perfect Gaussian distribution can be obtained.

In-Phase and Quadrature-Phase Sinusoidal Signal Generation Using DDS Technique

In-phase and quadrature-phase (IQ) sinusoidal signals are used as bases functions in many phase modulation schemes in communication systems. Generating such signals in engineering education laboratories without higher-end signal generators is quite challenging. Most of the time, the IQ signals used in undergraduate engineering education laboratories are in audio frequency range that is used to demonstrate or experiment with various phase modulation schemes. This paper presents a method to generate IQ sinusoids in the audio frequency range using direct digital synthesis technique. The system developed is simulated using MathWorks® Simulink and implemented on commonly available Xilinx’s® Spartan 6 FPGA. The system designed is capable of producing phase correct sine and cosine waves having frequencies between 1 Hz and 20 kHz.

Self-copy-shift-based differential phase extracting method for fiber distributed acoustic sensing

A differential phase extracting method based on self-copy-shift for distributed acoustic sensing is proposed. Heterodyne and optical hybrids are used to realize high signal-to-noise ratio in-phase and quadrature-phase (IQ) signal measurement. The measured signals are self-copied and shifted for certain data points, and then they are digitally mixed with the original signals to construct the differential phase. The four produced signals are then combined to carry out IQ demodulation. An experiment with strain having an amplitude modulation waveform is carried out. The results showed that waveform information can be recovered well, and the signal-to-noise ratio achieves 32.8 dB.

Microwave photonic RF front-end for co-frequency co-time full duplex 5G communication with integrated RF signal self-interference cancellation, optoelectronic oscillator and frequency down-conversion.

A novel RF front-end, which could simultaneously realize wideband RF signal self-interference cancellation (SIC), local oscillator (LO) generator based on optoelectronic oscillator (OEO) and frequency down-conversion has been proposed and experimentally demonstrated. In our microwave photonic RF front-end, only one single-polarization optical in-phase and quadrature-phase (IQ) modulator are required. The upper Mach-Zehnder modulator (MZM) of this optical IQ modulator works as a mixer; the lower MZM works as a reference arm; the parent Mach-Zehnder interferometer (MZI) is used to combine two output optical signals of these two child MZMs. In this way, not only self-interference signal is cancelled in optical domain but also frequency down-conversion is realized at the same time. On the other hand, the upper MZM is also shared to form an OEO by using a self-polarization-stabilization technique. By this means, no external LO signal for frequency down-conversion and electrical attenuator for SIC are needed in our scheme, contributing to compact structure and cost reduction. In our proof-of-concept experiment, a LO signal with central frequency of 10 GHz and phase noise of -108.66 dBc/Hz@10kHz is generated. By optimizing the bias points of the used optical IQ modulator, a 5×20MHz 64-ary quadrature amplitude modulation-orthogonal frequency division multiplexing (64QAM-OFDM) LTE-A signal with central frequency of 12.6 GHz is down-converted to 2.6 GHz, and about 28 dB cancellation ratio is achieved. The proposed scheme is suitable for wideband, integrated co-frequency co-time full duplex 5G communication.

Low PAPR FBMC

Unlike single carrier-frequency division multiple access (SC-FDMA), just combining discrete Fourier transform (DFT) spreading and filter bank multicarrier with offset quadrature amplitude modulation (FBMC-OQAM) results in only marginal peak to average power ratio (PAPR) reduction. To utilize the single carrier effect of DFT spreading, a special condition of the coefficients at each subcarrier’s in-phase and quadrature-phase (IQ) channels should be satisfied. As a starting point, we first derive this condition, which we call the identically-time-shifted-multicarrier (ITSM) condition. Then, based on this condition, we propose a new type of FBMC for low PAPR. The main features of the proposed scheme are summarized as follows. First, in order to further enhance the amount of PAPR reduction, we generate the four candidate versions of the DFT-spread and ITSM-conditioned FBMC waveform and select the one with minimum peak power. Even with multiple candidate generation, the major computation parts, such as DFT and IDFT are shared and need to be performed only once, unlike the conventional side information (SI)-based PAPR reduction schemes. Consequently, with a fractional complexity overhead compared with the previous DFT-spread FBMC, the proposed scheme achieves a PAPR reduction comparable to that of SC-FDMA. Second, the proposed scheme transmits only two bit SI per data block consisting of multiple FBMC-OQAM symbols. Hence, the SI overhead is significantly low compared with the usual SI-based schemes, such as selective mapping or partial transmit sequence.

An Efficient Method for Skew Estimation and Compensation in Coherent Receivers

The performance of coherent optical systems can be seriously degraded when in-phase and quadrature (IQ) components experience misalignments crossing certain critical limits. The critical limits of IQ phase, gain, and skew misalignments are lower at higher modulation formats and in narrowband systems. In this letter, frequency-domain skew-estimation algorithm and time-domain skew-compensation technique are proposed. When compared with other published methods, the new architecture improves timing performance and relaxes requirements for a multiple-input multiple-output time-domain equalizer at low implementation price. We discuss IQ imperfections on both transmitter and receiver sides and provide an efficient compensation procedure.

Performance of fixed‐gain amplify‐and‐forward nonlinear relaying with hardware impairments

SummaryIn this paper, a fixed‐gain amplify‐and‐forward relaying under non‐ideal hardware is analyzed. The relaying system is impaired because of relay's power amplifier (PA) nonlinearity and in‐phase and quadrature‐phase (IQ) imbalance at a destination. Closed‐form expressions for outage probability as well as ergodic capacity approximation and its upper bound are derived. Also, the outage probability and the ergodic capacity asymptotic expressions in the high signal‐to‐noise ratio are deduced. For the first time, the joint influence of PA nonlinearity and IQ imbalance on the system in terms of outage probability, symbol error rate, and ergodic capacity is investigated. The results are compared with the respect to soft envelope limiter and traveling‐wave tube amplifier at the relay. Based on the analytical and the numerical results, important insights into the impact of IQ imbalance and nonlinearity of the aforementioned PA models on the system performance are gained as well as valuable information on the performance of practically deployed fixed‐gain amplify‐and‐forward relaying system. Copyright © 2015 John Wiley &amp; Sons, Ltd.

Time–Frequency Multiplex Transceiver Design with RX IQ Imbalance, CFO, and Multipath Channel Estimation and Compensation for Multicarrier Systems

The low complexity time---frequency multiplex estimator and equalizer transceiver design are proposed to combat the RF impairment problems for the zero-IF transceiver of multi-carrier systems. Moreover, the proposed preamble can estimate and compensate the receiver (Rx) in-phase and quadrature-phase (IQ) imbalance, carrier frequency offset (CFO), and channel impulse response parameters. There are two parts in the proposed system. Firstly, all parameters of impairments are estimated by the proposed time---frequency multiplex estimator design with the iterative cancellation scheme. Secondly, the iterative group pair equalizer with the estimated parameters is proposed to eliminate the RF impairments effect and detect the transmitted signal with low complexity advantage. Simulation results confirm that the proposed estimator can provide the reliable performance over the severe IQ imbalance, CFO, and multipath fading channel environments.

Performance Analysis of Alamouti Code MIMO-OFDM Systems for Error Control and IQ Impairments

Bit Error Rate (BER) performance is the most important metric of any digital communication system. MIMO-OFDM systems designed with Alamouti Coding technique, using Error Control Coding schemes has been investigated under this study to achieve BER enhancement and scrutinized for Additive White Gaussian Noise (AWGN) Channel with Inphase and Quadrature-phase (IQ) impairments. This paper details out the model developed using NI LabVIEW and discusses simulation results comparing the error control coding RS, RS-CC and Convolution encoding with 4-PSK and 4-QAM. General Terms Bit Error Rate, Space Time Coding (STC).

Dynamic IQ Data Compression Using Wireless Resource Allocation for Mobile Front-Haul With TDM–PON [Invited

The time-division multiplexed-passive optical network (TDM-PON) architecture can efficiently accommodate densely deployed small cells in a centralized radio access network (C-RAN)-based future radio access (FRA). C-RAN is a type of mobile front-haul network, which connects multiple remote radio heads to a baseband unit pool by optical links. The required optical bandwidth in the mobile front-haul of FRA is very large, so it is necessary to efficiently use the optical bandwidth by using in-phase and quadrature-phase (IQ) data compression techniques. This paper proposes an IQ data compression technique that dynamically reduces the required optical bandwidth based on wireless resource allocation, and provides TDM-PON with statistical multiplexing gain. Simulation results showed the achievable compression ratio of the proposed IQ data compression technique. The feasibility of our technique was confirmed by experiments. The reduction in the average TDM-PON bandwidth was 50% when there were 60 mobile terminals, all of which required 0.18 Mbps bandwidth.

Beam Position and Phase Measurement System for the Proton Accelerator in ADS

A prototype of a beam position and phase measurement system is designed for the proton accelerator in the China Accelerator Driven Sub-critical system (ADS). The signals from the Beam Position Monitor (BPM) detector are narrow pulses with a repetition frequency of 162.5 MHz and the input amplitude would vary for more than 40 dB. By applying the high-speed high-resolution analog-to-digital conversion technique, the input radio-frequency (RF) signals are directly under sampled to orthogonal streams by precisely adjusting the sampling clock frequency. Compared with the traditional method to obtain the in-phase and quadrature-phase (IQ) data, it simplifies both the analog and digital processing circuits. All signal processing algorithms are integrated within one field programmable gate array (FPGA) chip for a good system simplicity. Initial testing results indicate that this prototype achieves a phase resolution better than 0.03° and a position resolution better than 5 μm over the input amplitude range from -44 dBm to -4 dBm, well beyond the requirement.

Before/after precoding massive MIMO systems for cloud radio access networks

In this paper, we investigate two types of in-phase and quadrature-phase (IQ) data transfer methods for cloud multiple-input multiple-output (MIMO) network operation. They are termed “after-precoding” and “before-precoding”. We formulate a cloud massive MIMO operation problem that aims at selecting the best IQ data transfer method and transmission strategy (beamforming technique, the number of concurrently receiving users, the number of used antennas for transmission) to maximize the ergodic sum-rate under a limited capacity of the digital unit-radio unit link. Based on our proposed solution, the optimal numbers of users and antennas are simultaneously chosen. Numerical results confirm that the sum-rate gain is greater when adaptive “after/before-precoding” method is available than when only conventional “after-precoding” IQ-data transfer is available.

Enhanced Joint Channel and IQ Imbalance Parameter Estimation for Mobile Communications

This letter presents an enhanced joint channel and in-phase and quadrature-phase (IQ) imbalance parameter estimation method for communication systems. The proposed method first estimates the channel impulse response (CIR) with integrated IQ imbalance parameters, which contains twice the number of the original CIR parameters. To exploit the additional redundancy in the initial estimate, the alternating least square (ALS) algorithm is used to estimate the channel and the IQ imbalance parameters in an iterative manner. Particularly, the proposed method can exploit the beneficial linear structure of the initial estimate and largely reduce the required number of the estimated parameters, thereby enhancing the estimation performance. Simulation results demonstrate the efficacy of our proposed scheme in multipath fading channels even with severe IQ imbalance impairments.