Multicarrier Signals Research Articles

A Jitter-Robust 40 Gb/s ADC-Based Multicarrier Receiver Front-End With 4-GS/s Baseband Pipeline-SAR ADCs in 22-nm FinFET

Demand for increased data rates in serial link transceivers calls for innovative architectures capable of overcoming impairments such as limited channel bandwidth (BW) and stringent jitter specifications. This article presents a receiver front-end (RXFE) architecture that supports multicarrier signaling to provide a ~3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> relaxation in clock jitter requirements. A total of 40 Gb/s data rate is supported by three 4-GS/s bands with baseband (BB) four-level pulse amplitude modulation (PAM4) and mid-band (MB) and high-band (HB) 16-state quadrature amplitude modulation (QAM16) on 4- and 8-GHz orthogonal carriers, respectively. The RXFE uses three per-band optimized continuous-time linear equalizers (CTLEs) to partially equalize the in-band channel loss and four-way time-interleaved 7-b pipelined-successive approximation register (SAR) analog-to-digital converters (ADCs). Tight band spacing is achieved with tolerable inter-channel interference (ICI) using resettable integrators in the receiver segments. Fabricated in a 22-nm fin field-effect transistor (FinFET), the proposed 40-Gb/s multicarrier RXFE can tolerate up to 1.6-psrms jitter and achieve a bit error rate (BER) < 10−5 operating over a channel with 20-dB loss at 10 GHz when combined with an off-chip one-tap digital ICI canceller. The ADC-based front-end achieves 3.05-pJ/bit power efficiency, including all the front-ends, ADC, and clocking power.

Design of Low Probability Detection Signal with Application to Physical Layer Security

In this work, we mainly focus on low probability detection (LPD) and low probability interception (LPI) wireless communication in cyber-physical systems. An LPD signal waveform based on multi-carrier modulation and an under-sampling method for signal detection is introduced. The application of the proposed LPD signal for physical layer security is discussed in a typical wireless-tap channel model, which consists of a transmitter (Alice), an intended receiver (Bob), and an eavesdropper (Eve). Since the under-sampling method at Bob’s end depends very sensitively on accurate sampling clock and channel state information (CSI), which can hardly be obtained by Eve, the security transmission is initialized as Bob transmits a pilot for Alice to perform channel sounding and clock synchronization by invoking the channel reciprocal principle. Then, Alice sends a multi-carrier information-bearing signal constructed according to Bob’s actual sampling clock and the CSI between the two. Consequently, Bob can coherently combine the sub-band signals after sampling, while Eve can only obtain a destructive combination. Finally, we derived the closed-form expressions of detection probability at Bob’s and Eve’s ends when the energy detector is employed. Simulation results show that the bit error rate (BER) at Alice’s end is gradually decreased with the increase in the signal-to-noise ratio (SNR) in both the AWGN and fading channels. Meanwhile, the BER at Eve’s end is always unacceptably high no matter how the SNR changes.

Performance Analysis of PAPR minimization in OFDM System Using Clipping, SLM and PTS Techniques

In wireless communications, Orthogonal Frequency Division Multiplexing (OFDM) is a method of modulating multicarrier signals to transmit high speed data. OFDM systems use multiple subcarriers to transmit the modulated symbols. There is a high peak to average power ratio (PAPR) in OFDM. PAPR can be reduced by using various methods. Different PAPR minimization techniques, like clipping, selective mapping (SLM) and partial transmit sequence (PTS) are presented in this project. This paper also focuses on Bit Error Rate (BER) and Signal to Noise Ratio (SNR) relative performance. A significant reduction in the PAPR and computational complexity can be seen from the results. The purpose of this study is to compare the results of an analysis recommended for PAPR reduction methods.

Multimodality-aided Multicarrier Waveform Recognition in low SNR Regimes based on Denoised Cyclic Autocorrelation Transformation

Wireless signal recognition driven by artificial intelligence (AI) plays a pivotal role in 6G ultra-reliable wireless communications, facilitating spectrum surveillance to impede illegal radio interference. As a promising wireless technique, multicarrier waveform recognition (MWR) has been explored to enhance the reliability of wireless data transmission. However, existing works fail to achieve reliable recognition accuracy under strong noise. It remains a daunting task for MWR in signal-to-noise ratio (SNR) regimes. To deal with this issue, we propose a denoised cyclic autocorrelation-based multimodality fusion network (DCA-MFNet). Specifically, we first leverage the cyclic autocorrelation transformation to convert intercepted signals into cyclic autocorrelation (CA) features in cyclic frequency domains, which have the robust property of being insensitive to low SNR. Next, the singular value decomposition (SVD) method is employed to weaken the strong noise effects on useful CA peak values. Based on the denoised CA matrix (DCAM), the projection accumulation strategy is proposed to generate the time delay accumulation vector (TDV) and cyclic frequency accumulation vector (CFV), which can enlarge the discrimination among multicarrier signals. Finally, we fed the multimodality features of DCAM, TDV, and CFV into the developed DCA-MFNet to perform hierarchical learning, feature aggregation training, and multicarrier type prediction. Experimental results demonstrate that the proposed DCA-MFNet obtains better recognition performance than existing algorithms. Moreover, DCA-MFNet can effectively identify six multicarrier signals with a recognition accuracy of 100% at a low SNR of even -2 dB.

Dual-Blind Deconvolution for Overlaid Radar-Communications Systems

The increasingly crowded spectrum has spurred the design of joint radar-communications systems that share hardware resources and efficiently use the radio frequency spectrum. We study a general spectral coexistence scenario, wherein the channels and transmit signals of both radar and communications systems are unknown at the receiver. In this dual-blind deconvolution (DBD) problem, a common receiver admits a multi-carrier wireless communications signal that is overlaid with the radar signal reflected off multiple targets. The communications and radar channels are represented by continuous-valued range-time and Doppler velocities of multiple transmission paths and multiple targets. We exploit the sparsity of both channels to solve the highly ill-posed DBD problem by casting it into a sum of multivariate atomic norms (SoMAN) minimization. We devise a semidefinite program to estimate the unknown target and communications parameters using the theories of positivehyperoctant trigonometric polynomials (PhTP). Our theoretical analyses show that the minimum number of samples required for near-perfect recovery is dependent on the logarithm of the maximum of number of radar targets and communications paths rather than their sum. We show that our SoMAN method and PhTP formulations are also applicable to more general scenarios such as unsynchronized transmission, the presence of noise, and multiple emitters. Numerical experiments demonstrate great performance enhancements during parameter recovery under different scenarios.

Single-lane 200 Gbit/s photonic wireless transmission of multicarrier 64-QAM signals at 300 GHz over 30 m

Single-lane 200 Gbit/s photonic wireless transmission of multicarrier 64-QAM signals at 300 GHz over 30 m

Multi-carrier broadband signal generation based on a mutually dual-domain mode-locked optoelectronic oscillator

A novel dual-domain mode-locked optoelectronic oscillator (DDML-OEO) is proposed and demonstrated to generate multi-carrier broadband signal. The DDML-OEO is built up by mode-locking a conventional OEO at the time domain and Fourier domain mutually. The Fourier domain mode locking (FDML) is achieved by driving the laser with a period triangular waveform voltage, of which the frequency is synchronized with the round-trip time of the OEO loop. Meanwhile, an electrical signal synchronizing with the free spectrum range (FSR) of the OEO loop is injected to realize the time domain mode locking (TDML) process. Through combined mechanisms of the FDML and TDML, the multi-carrier broadband signal can be directly generated via the DDML-OEO. Thanks to the TDML, different multi-carrier bands of the signal are coherent and the phase noise of the generated broadband waveform is strongly suppressed compared with free-running FDML-OEO. With the proposed scheme, an ultra-low phase noise of −111.1 dBc/Hz at 10 kHz offset for the generated multi-broadband signal waveform is achieved when the cavity length is about 3000 m. The bands interval, the bandwidth and the central frequency tunability are all discussed, which have great potential usage in multi-channel radar transmitter.

FFSCN: Frame Fusion Spectrum Center Net for Carrier Signal Detection

Carrier signal detection is a complicated and essential task in many domains because it demands a quick response to the existence of several carriers in the wideband, while also precisely predicting each carrier signal’s frequency centers and bandwidths, including single-carrier and multi-carrier modulation signals. Multi-carrier modulation signals, such as FSK and OFDM, could be incorrectly recognized as several single-carrier signals by using the spectrum center net (SCN) or FCN-based method. This paper designed a deep convolutional neural network (CNN) framework for multi-carrier signal detection by fusing the features of multiple consecutive frames of the broadband power spectra and estimating the information of each single-carrier or multi-carrier modulation signal in the broadband, called frame fusion spectrum center net (FFSCN), including FFSCN-R, FFSCN-MN, and FFSCN-FMN. FFSCN includes three base parts, the deep CNN-based backbone, the feature pyramid network (FPN) neck, and the regression network (RegNet) head. FFSCN-R and FFSCN-MN fusing the FPN out features, which use the Residual and MobileNetV3 backbone, respectively, and FFSCN-MN cost less inference time. To further reduce the complexity of FFSCN-MN, the designed FFSCN-FMN modifies the MobileNet blocks and fuses the features at each block of the backbone. The multiple consecutive frames of broadband power spectra not only preserve the high-resolution ratio of the broadband frequency, but also add the features of the signal changes in the time dimension. Extensive experimental results demonstrate that the proposed FFSCN can effectively detect multi-carrier and single-carrier modulation signals in the broadband power spectrum and outperform SCN in accuracy and efficiency.

Entropy loading for capacity maximization of RGB-based visible light communications.

In this work, we propose and experimentally demonstrate an entropy loading technique based on probabilistic constellation shaping for a visible light communication (VLC) system. The aggregated achievable bit rate of a multi-carrier signal is maximized, considering a given pre-estimated signal-to-noise ratio. A study of the ideal number of subcarriers and signal bandwidth was performed using multiplexed red, green and blue lasers diodes with a bandwidth of 1 GHz. With a 20 degree optical diffuser, the communication system is able to cover a wide area at a free-space distance of 0.90 m, while achieving a record aggregate bit rate of 31.2 Gbit/s for single-polarization RGB-VLC systems.

Carrier Selection Strategy of Generalized Discontinuous PWM Method for Current Reduction in DC-Link Capacitors of VSI

This article proposes a new carrier selection strategy of generalized discontinuous pulsewidth modulation (GDPWM) method for the two-level three-phase voltage source inverter to reduce the dc-link capacitor current under all operating conditions while keeping the minimum switching losses. First, the root-mean-square value of dc-link capacitor current is effectively reduced by selectively using both single and double carrier signals and modifying the switching patterns of existing GDPWM method. Although the proposed carrier selection strategy depends on the power factor (PF), the PF calculation is avoided because the multicarrier signals are properly chosen based on the information of three-phase modulation signals and measured three-phase currents. Also, the switching losses can be kept to a minimum as the modulation signals of conventional GDPWM method, which are optimal in terms of the switching losses, remain the same and the proposed carrier selection strategy has little effect on the total number of switching events. The operating principle of proposed GDPWM method is theoretically analyzed. Then, its practical effectiveness is verified by experimental tests on a motor drive system.

General Form of the Power Spectral Density of Multicarrier Signals

Multicarrier modulation has been adopted in many modern communication systems because of its many appealing properties. Its relatively high out-of-band radiation has spurred many techniques to shape the power spectral density (PSD) of multicarrier signals, including spectral precoding and pulse shaping. We derive a general expression for the PSD which is valid for subcarrier-specific pulses and for spectral precoders operating over multiple blocks. The only statistical assumptions on the vector-valued sequence modulating the active subcarriers are wide-sense cyclostationarity and properness. The applicability of the result to a number of popular multicarrier formats is discussed.

High-Efficiency Mitigation of Nonlinear Distortion in Microwave Photonics Link Assisted by Artificial Neural Network

A microwave photonics radio over fiber link can deliver the radio frequency (RF) signal to realize the antenna remote. When the signal is a broadband and multicarrier RF signal, there are some linear distortions in the link, such as the crossmodulation distortion (XMD) and third-order intermodulation distortion (IMD3). It will destroy the wide-bandwidth performance of the link. Traditional postdigital compensation methods for XMD and IMD3 mitigation extract the baseband signal and reconstruct the compensation signal with calculated compensation factor. Here, a kind of artificial neural network genetic algorithm (ANN-GA) distortion compensation technique is proposed to seek the compensation factor instead of calculations. The neural network algorithm is used to fit the mapping function between the compensation factor and the distortion and give a set of predicted data as the original individual fitness value for the genetic algorithm. Based on the original value, the minimal distortion, the corresponding optimal compensation factors γ and α are found with optimization iterations. Taking advantage of the optimal compensation factors, based on the traditional postdigital compensation method, the distortion is mitigated with a suppression ratio of -84.4 dB. In our paper, the mitigation technology of the XMD and IMD3 can be applied for any kinds of link instead of mathematically modelling the link and calculating the compensation factor. The technology can improve the intelligence and flexibility of microwave photonic link linearization design.

Discrete FBMC-based orthogonal time frequency space in wireless communications considering different prototype filters

Designing a proper multicarrier signaling technique for the next generation of mobile network communications is one of the challenging fields of study. Orthogonal Frequency Division Multiplexing (OFDM) as the standard multicarrier technique in 5G suffers from the out-of-band (OOB) leakage where using the filter-based multicarrier techniques like Filter Bank Multi-Carrier (FBMC) could reduce the OOB emission. Also, due to the requirement of serving under high mobility conditions such as vehicle to vehicle (V2V) and high-speed train communications, employing a functional multicarrier technique like Orthogonal Time Frequency Space (OTFS) is quite desirable. Besides, to gain good frequency localization, it is required to have a long symbol duration where the more longer symbol duration provides the less robustness of the waveform to mobility. Hence, the combination of OTFS and FBMC could be interesting to fit in at the same time and frequency localization, and support the mobility. As a phenomenal property, OTFS could be understood as a pre- and post-processing steps for the OFDM-based techniques which enables OTFS to cooperate with them. Therefore, to achieve a better performance, we extended the FBMC by applying the OTFS and implemented the FBMC-based OTFS technique which benefits from both OTFS and FBMC qualities. Besides, to reduce the computational complexity of the continuous form and contributing more analytical results, the discrete FBMC-based OTFS formulation is provided. Our accomplished analyses and simulated results certificate the FBMC-based OTFS superiority over different schemes in Peak to Average Power Ratio (PAPR) and error probability terms.

Design and performance evaluation of FBMC-based Orthogonal Time–Frequency Space (OTFS) system

The idea of an efficient multicarrier signaling technique is one of the critical challenges for beyond fifth-generation (B5G) of wireless communication networks. The B5G mobile networks require the multicarrier scheme featuring, immunity to multipath fading and inter-symbol interference (ISI), robustness against inter-carrier interference (ICI) and Doppler spread to outreach their purposes. Several Filter-based techniques such as Filter Bank Multicarrier (FBMC) and various Orthogonal Frequency Division Multiplexing (OFDM)-based techniques such as Universal Filtered Multicarrier (UFMC) and Generalized Frequency Division Multiplexing (GFDM) are proposed in recent studies. Besides, Orthogonal Time–Frequency Space (OTFS) technique is introduced newly as one of the potential waveform nominees for B5G which can outperform OFDM-based techniques in high mobility situations. One of the prominent benefits of the OTFS method is that it can be regarded as the pre- and post-processing steps for OFDM-based techniques. In this paper, we extended the FBMC scheme using the OTFS technique and propose a novel structure as FBMC-based OTFS technique which benefits from both strategies while reducing their deficiencies. Our concluded analyses and results can certificate our system superiority in error probability and time-spectral efficiency terms where the FBMC-based OTFS employing different types of filters are compared to the OFDM-based OTFS system.

Precoded and pre-equalized multi-band FBMC transmission enabled by radio-frequency DACs and the undersampling technique.

In this Letter, we use radio-frequency digital-to-analog converters (DACs) operating in different frequency response modes to generate a high spectral-efficiency multi-band (MB) filter bank multicarrier (FBMC) signal. In the receiver, the undersampling technique is employed to realize down-conversions. No electrical mixers are required. Besides, discrete Fourier transform and orthogonal circulant matrix transform precoding techniques combined with channel-independent digital pre-equalization are enabled to enhance transmission performance. Both numerical simulations and offline experiments are performed. The relevant results show that the MB-FBMC without a cyclic prefix (CP) is robust against inter-symbol interference induced by the band-pass filtering. By using precoding and pre-equalization techniques, the bit error rate can be improved by more than one order of magnitude. In contrast, an additional 12.5% CP overhead is required for the MB orthogonal frequency division multiplexing system to achieve such an improvement.

Multi-Carrier Signal Recognition Method Based on Multi-Feature Input and Hybrid Training Neural Network

In order to achieve automatic identification of modulation formats in orthogonal frequency division multiplexing (OFDM) subcarrier signals, a recognition method based on multiple feature inputs and a Hybrid Training Neural Network (HTNN) is proposed, in which an HTNN structure is designed to obtain high-order statistical correlation features and constellations of OFDM subcarriers. The recognition performance of the proposed method in free space channel transmission and atmospheric time-varying channel transmission is studied by simulation. Simulation results show that the overall identification accuracy of the recognition model based on the proposed method exceeded 93.37% in the wide Signal-to-Noise Ratio (SNR) range of the free space channel. With an SNR higher than 7.5 dB, identification accuracy performance of the learning model culminated, achieving 100% identification accuracy of OFDM subcarrier signals. Under weak turbulent atmospheric and time-varying channel conditions, the overall identification accuracy curve tended to increase as SNR increased and stabilized at more than 95%. Compared with the two comparison methods, the proposed method reduced the sensitivity to channel variations and improved the convergence speed on the basis of the guaranteed identification accuracy, and enabled reliable identification of OFDM subcarrier signals in a wide SNR range.

Novel Prediction Methods of Multicarrier Multipactor for Space Industry Standards

Multipactor prediction methods are of high relevance for the space industry in order to prevent its appearance during the design phase of RF high-power components. Up to the present time, prediction for multicarrier signals has been covered by an empirical rule, the 20-gap-crossing rule (20GCR), proposed in the 2003 version of the multipactor standard published by the European Cooperation for Space Standardization (ECSS). The 20GCR has been widely used by the space industry, although some studies have demonstrated that it might be inaccurate in some situations. The latest version of the ECSS multipactor standard, published in 2020, presents two novel methods for multipactor prediction with multicarrier signals: the pulsed method and the envelope sweep (ES) method, both simple, accurate enough, and suitable for industry standards. While the pulsed model is a simple and fast method based on a 1-D analytical theory, the ES method is more accurate and able to deal with real 3-D microwave structures. This article details both multipactor prediction methods, as well as their practical validation with a large dataset from previous analytical studies and experimental activities.

Filter Distortions in Ultra High-Throughput Satellites: Models, Parameters and Multicarrier Optimization

Ultra high-throughput satellite systems are expected to play an essential role in future beyond 5G and 6G networks. These systems must remain as flexible as possible to adapt to heterogeneous traffic demands, while also delivering the highest possible rate for dedicated services. Satellites flexible payloads are increasingly employing wideband output multiplexers. In this context, it is now more important than ever to evaluate frequency-dependent degradations on multicarrier signals. In particular, it is critical to characterize the distortions entailed by the output multiplexers filters. In this paper, models are presented and novel formulas are derived to determine the carrier-to-interference ratio resulting from these distortions. Derivations are oriented towards the applicability of either high-accuracy (e.g., for link budget) or low-complexity calculations (e.g., for real-time carrier allocation). The influence of key parameters such as the optimal decision instant, symbol rate and roll-off factor is thoroughly analyzed. Furthermore, formulas are evaluated in a practical scenario: the dynamic carrier allocation optimization. They are combined with efficient optimization algorithms to obtain the best performance based on user fairness. Relevant metrics such as accuracy, complexity and allocation gain are also investigated. In the end, the application of the proposed formulas and algorithms leads to a significant allocation gain that is increasing with the number of carriers. The feasibility of real-time dynamic carrier allocation to further increase the capacity of the next generation of satellite systems is emphasized.

Adaptive Codebook-Based Channel Estimation in OFDM-Aided Hybrid Beamforming mmWave Systems

In order to reduce the hardware complexity and cost of mmWave transceivers, hybrid beamforming techniques have been developed, which rely on the channel state information (CSI) available to the receiver and/or transmitter. In mmWave channel estimation, the compressed sensing (CS)-based algorithms like orthogonal matching pursuit (OMP) have been widely studied to take the advantages of the sparse characteristics of mmWave channels. Specifically, the OMP-assisted adaptive codebook channel estimation has the merit of reduced implementation complexity, but it performs undesirably in low signal to noise ratio (SNR) scenarios. To circumvent this problem, in this paper, we develop an improved adaptive codebook channel estimation algorithm for orthogonal frequency division multiplexing (OFDM) mmWave systems, which enhances the estimation performance by exploiting the multi-carrier signals for joint decision making. Our studies show that the proposed channel estimation is capable of significantly improving the estimation accuracy at low SNR, while enjoying a low complexity for implementation.

3 × 3 MIMO Fiber–Wireless System in W-Band With WDM/PDM RoF Transmission Capability

We propose and demonstrate a 3 × 3 full multiple-input multiple-output (MIMO) fiber–wireless system in the W-band with wavelength-division multiplexing (WDM) and polarization-division multiplexing (PDM) radio-over-fiber (RoF) transmission capability. The system is realized using two highly stable RoF links based on the optical self-heterodyne method and PDM transmission in one of the RoF links. We experimentally demonstrate and confirm satisfactory performances for a 3 × 3 MIMO offset quadrature amplitude modulation-based filter-bank multicarrier signal. Total capacities of approximately 110 and 132 Gb/s, corresponding to spectral efficiencies of approximately 8.5 and 10.2 bits/s/Hz, respectively, are achieved for the system using antennas placed in the same and alternately different polarizations, respectively. The system is applicable to WDM and combined WDM/PDM RoF transmissions. It provides a scalable solution for facilitating large-scale MIMO signal transportation and can be a promising solution for future mobile transport and radio access networks in high-frequency bands.