High-order Modulation Research Articles

LDM-Ex-FDM: A Novel Multi-Service Transmission Scheme for the ATSC 3.0 System

In order to improve system coverage performance, in this paper, a multi-service transmission scheme on the basis of the puncturing technique, namely layered division multiplexing extension frequency-division multiplexing (LDM-Ex-FDM), is proposed. The key idea of the proposed scheme is that the symbols punctured from the enhanced layer (EL) of fixed services will be independently transmitted on a certain number of subcarriers orthogonal to the LDM signal of the core layer (CL) and most of the EL. By doing so, the punctured symbols will be demodulated with a higher signal-to-noise ratio (SNR) on the receiver side and can be recovered well, thus improving the reception performance of the EL fixed services. Moreover, two puncturing strategies based on bit-interleaved coded modulation (BICM) symbols of the LDM-Ex-FDM scheme, namely equal interval symbol puncturing (EISP) and non-equal interval symbol puncturing (NEISP), are developed to improve the performance of the EL services. Simulation results are given to show that, when the puncturing rate in the LDM-Ex-FDM scheme is configured as 1/12, the performance of the fixed service can be improved by 1.8 dB, meanwhile the bit error rate (BER) performance of the mobile service is not affected. Thus, the overall system coverage performance can be improved. Furthermore, to reduce the computational complexity and the demodulation delay of fixed service carried in the EL, at the receiver, a direct interference cancellation (DIC) detector is proposed as well. Simulation results are given to show that, under high injection level and high modulation order, the proposed DIC scheme is able to achieve almost the same BER performance as that of the traditional successive interference cancellation (SIC) scheme while with lower computational complexity.

Performance Simulation of Underwater Acoustic Spread Spectrum Communication Based on LDPC Code

As we all know, the underwater acoustic channel is a time-varying, space-changing, and frequency-varying fading channel with limited bandwidth and severe noise interference. This paper studies and analyzes the main factors restricting the transmission of underwater acoustic channels, and establishes an underwater acoustic multipath time-varying fading channel. The channel coding adopts Quasi-Cyslic Low-Density Parity-Check Codes (QC-LDPC), combined with spread spectrum technology and high-order modulation technology, and utilizes Log-likelihood Ratios Belief Propagation (LLR-BP) is decoded, the simulation results show that LDPC codes have stronger error correction capabilities in underwater acoustic spread spectrum communication systems, ensuring that the system can operate reliably under low SNR conditions.

Shaping duo binary turbo-coded BICM scheme for JPWL image transmission using a link adaptation strategy over wireless channels

In order to guarantee a robust transmission of JPWL (JPEG Wireless: Joint Photographic Experts Group Wireless) images through time and frequency selective wireless channels, an efficient adaptive communication strategy is proposed. It is based on an optimization of a closed-loop adaptive multiple-input multiple-output, orthogonal frequency division multiplexing (MIMO-OFDM) scheme associated with a shaping BICM (bit-interleaved coded modulation) technique composed of a duo binary turbo code (DBTC), high-order modulations such as 64–256 QAM (Quadrature Amplitude Modulation) and a shaping code. According to the CSI (channel state information) knowledge at the transmitter side, an algorithm based on unequal error protection (UEP) and unequal power allocation (UPA) is used to select the transmitter key parameters (source/channel encoder rate, modulation order, power, number of quality layers and number of iterations of the Turbo decoder) to achieve the target Quality of Service (QoS). The proposed DBTC-shaping BICM scheme reaches a shaping gain of 1.2 dB for a 256 QAM modulation over a SISO Gaussian channel, whereas only 0.7 dB of shaping gain can be achieved in a scheme that uses the LDPC shaping BICM scheme for the same modulation order. Based on a DBTC shaping BICM scheme and an adaptive algorithm, the proposed MIMO-OFDM strategy achieves better performance compared to a strategy using an iterative process between an RS (Reed-Solomon) and arithmetic decoders. As a result, and on the one hand, a gain of 5.38 dB can be achieved in terms of PSNR (peak signal-to-noise ratio). On the other hand, a gain of 78% in terms of power consumption is obtained for the same QoS level. Moreover, the adaptive number of iterations in the proposed strategy can minimize the computational complexity of the turbo decoding compared to a scheme using four iterations whatever the channel conditions.

Ultra-long-haul digital coherent PSK Y-00 quantum stream cipher transmission system.

A record-long 10,118-km fiber transmission with physical layer encryption is demonstrated utilizing a Y-00 cipher based on signal masking by quantum (shot) noise. The Y-00 cipher enables symmetric-key data encryption to ensure the security of the physical layer of optical communications. Irreducible secrecy without significant negative impact on transmission performance is achieved by the synergistic effect of combining seed-key-based high-order modulation and truly random shot noise inevitable in optical detection. This paper reports a comprehensive study of applying a phase-shift-keying (PSK) Y-00 cipher for ultra-long haul fiber transmission. Theoretical analysis shows that security-enhanced transmission over transoceanic-distance (>10,000 km) fiber is feasible when the quadrature PSK data signal is encrypted by converting to a PSK signal with 218 levels. Subsequently, 10,118-km standard single-mode fiber transmission of 48-Gbit/s line-rate dual-polarization PSK Y-00 cipher with 218 levels is experimentally demonstrated. An adequate signal quality above the Q-factor threshold of soft decision forward error correction is achieved together with sufficient signal masking by shot noise, yielding balanced transmission performance and high security in an ultra-long-haul PSK Y-00 cipher transmission system.

High-Order Modulation Based on Deep Neural Network for Physical-Layer Network Coding

Physical-layer network coding (PNC) is an effective technique for enhancing wireless network throughput. Recently, it has been demonstrated that convolutional autoencoders effectively works in point-to-point communication systems, but their application to wireless relay networks is scarcely explored. In this letter, we propose a convolutional autoencoder for PNC in a two-way relay channel. The constellation mapping and demapping of symbols at each node are determined adaptively through a deep learning technique, such that the bit error rate performance is improved for high-order modulation. Simulation results verify the advantages of the proposed scheme over the conventional PNC scheme for various modulation types.

Error Floor Estimation of LDPC Coded Modulation Systems Using Importance Sampling

One of the key weaknesses of low-density parity-check (LDPC) codes is the error floor that they typically exhibit at high signal-to-noise ratios (SNRs). Such an error floor is usually attributed to problematic structures known as trapping sets (TSs). The overwhelming majority of existing error floor estimation schemes consider the case of binary phase shift keying (BPSK) signalling. Unfortunately, these schemes are not readily extensible to estimate the error floor of high order LDPC coded modulation systems considered herein. To provide such a scheme, in this work, we use mean-shift importance sampling (MS-IS) to develop a novel error floor estimation methodology for high-order pulse amplitude modulation (PAM) and quadrature amplitude modulation (QAM) LDPC coded systems. First, a computationally efficient graphical-based approach is used to identify the TSs of a given LDPC code. Subsequently, a novel analytical approach is devised to identify the TSs that are likely to have a higher contribution in the error floor. These TSs are referred to as potentially dominant TSs (PDTSs). Finally, a new methodology for categorizing the PDTSs into equivalence classes is developed. A representative PDTS of each equivalence class is chosen and an MS-IS framework is devised to obtain the error rate corresponding to each equivalence class. To arrive at the desired MS-IS scheme, we develop an algorithm that invokes the geometry of the constellation to determine the MS value. In contrast with the conventional MS-IS method used in BPSK signalling, in the proposed MS-IS scheme, the MS value is a variable that is determined based on the TS and the transmitted codeword. The computational complexity of the three main steps of our methodology, viz. extracting the PDTSs, determining the MS values, and applying the MS-IS scheme, depends merely on the size of the constellation and the structure of the code, but not on the SNR. Numerical simulations confirm the efficacy and accuracy of the proposed technique at different SNRs.

A modified convolutional neural network-based signal demodulation method for direct detection OFDM/OQAM-PON

Orthogonal frequency division multiplexing/offset quadrature amplitude modulation (OFDM/OQAM) is a promising modulation candidate for passive optical network (PON) due to its high flexibility, better time–frequency focusing characteristic, great resistance to the inter symbol and inter carrier interferences and higher spectrum efficiency compared to OFDM. However, the intrinsic imaginary interference together with linear and nonlinear distortions make it more difficult to recover the transmitted OFDM/OQAM signal at the receiver side. To mitigate the transmission impairments, a modified convolutional neural network (CNN) is utilized to learn the channel state information and the constellation demapping mechanism for OFDM/OQAM-PON. The distorted received signals are equalized implicitly to obtain the transmitted binary bits directly. The simulation results show that the CNN based receiver (Rx) can compensate the linear and nonlinear distortions more effectively compared to traditional pilot-based Rx, especially for the high order modulation long-reach PON.

A 28-GHz High Linearity Up-Conversion Mixer Using Second-Harmonic Injection Technique in 28-nm CMOS Technology

A 28-GHz high linearity active up-conversion mixer using 28-nm CMOS is presented in this letter. To enhance the modulated output power level under high-order modulation with IM3 improvement in the high IF input power region, the second-order intermodulation (IM2) signal injection technique is adopted. The positive third-order intermodulation (IM3) signal is generated by mixing the IM2 signal and IF input signal with transistors in the transconductance stage biasing in triode region. Therefore, by combining these opposite IM3 signal at the output of transconductance stage, the IM3 distortion can be alleviated. Besides, the proposed mixer achieves an IM3 distortion improvement in a wide IF power range. The measurement results demonstrate conversion gain (CG) of −6.4 dB and output 1-dB compression point (OP1 dB) of −2.2 dBm with 19 mW. The two-tone measurement results exhibit 10.2 dBm output third-order intercept point (OIP3). Furthermore, with the modulation measured results using single-carrier 256-QAM signal, the proposed mixer also exhibits a distinguished output power enhancement when the linearizer turns on. To the best of the author’s knowledge, this design is the first demonstration and implemented of an IM2 signal injection technique in millimeter-wave frequency, which also improves the output power level of the high-order modulation measurement.

A 660 MHz–5 GHz 6-Phase/3-Phase Transmitter With Cancellation of Counter-Intermodulation Distortion and Improved Image Rejection

In the transmit signal path of a cellular terminal that supports the Long-Term Evolution (LTE) standard, the third-order counter-intermodulation (CIM3) product can be a significant contributor to spurious emissions in protected bands, primarily in cases where all the transmit power is concentrated in one resource block at the edge of the allocated bandwidth. This problem can be addressed with a harmonic rejection architecture for the up-conversion mixer in the transceiver. Prior work in this area retains the four-phase baseband inputs of a conventional quadrature mixer, utilizes various techniques in the local oscillator (LO) path involving overlapping LO waveforms to suppress harmonics and requires the digitally-controlled oscillator (DCO) to be operated at two or more times the LO frequency. The harmonic rejection architecture presented in this paper has six baseband phases and six non-overlapping LO phases and, for higher-frequency bands, allows the DCO to run at 1.5 times the LO frequency. It also provides an inherently higher uncalibrated image rejection than architectures with quadrature baseband inputs, which is advantageous for any wireless communication standard that supports higher-order quadrature amplitude modulation (QAM) schemes such as 1024-QAM and 4096-QAM.

Quaternion Model of Higher-Order Rotating Polarization Wave Modulation for High Data Rate M2M LPWAN Communication.

With growing interest in Industry 4.0, machine-to-machine communication (M2M) will become the key enabler for low-power wide area networks (LPWANs) in connecting machines and sensor nodes distributed across a distance in the industrial environment. The choice of modulation and diversity techniques, and the selection of spectrum (licensed/unlicensed) will impact and influence the requirements of wireless M2M systems. Link reliability is one of the most important requirements for LPWAN deployment in industrial scenarios. Rotating Polarization Wave (RPW) system has been recently proposed as an LPWAN solution for reliable M2M communication in high clutter environment and it deploys BPSK modulation with polarization diversity (PD). This paper proposes a new multi-level Rotating Polarization Phase-Shift Keying (RP-MPSK) modulation to provide high data rate and energy efficiency. A novel quaternion model for RPW system (Q-RPW) is also proposed to reduce the complexity in modeling, simulation, and implementation. Results using Q-RPW model show that RP-MPSK modulation offers a high diversity gain over BPSK with second-order diversity. Bit error rate (BER) performance of RP-MPSK modulation compared against other LPWAN modulation like MPSK, FSK and QAM has shown high reliability and substantial improvement in SNR. To overcome the degradation in error performance caused by the proposed higher-order modulation, sampling rates are recommended based on BER performance. BER performance of RP-MPSK under multipath and interference conditions is also investigated.

IRLNet: A Short-Time and Robust Architecture for Automatic Modulation Recognition

Automatic modulation recognition with deep learning (DL) is challenging in distinguishing high-order modulation modes and balancing complexity against recognition accuracy. In this paper, we propose a novel dual-path modulation recognition framework named IRLNet, which consists of the improved residual stacks (IRS) and long short-term memory (LSTM). The IRS maintains the more initial residual information, learns the signal features in deep and shallow, and achieves various degrees of feature extraction. The model learns from the time domain I/Q, amplitude and phase information presented in the training data. The simulation results on RadioML2016.10B show that IRLNet performs stable in the training stage and has low spatial-temporal complexity. It also achieves a recognition accuracy of more than 93% at high signal-to-noise ratios (SNRs). Transfer learning is introduced to improve the efficiency of retraining, and robustness is proved by transferring the model to RadioML 2018.01A and HisarMod 2019.1. The simulation result shows that the training time is greatly shortened by about 25.6% in RadioML 2018.01A by introducing transfer learning. Moreover, IRLNet improves the confusion of high-order modulations and achieves a recognition accuracy of more than 90% in high SNRs.

Effective decoding and ambient backscattering phase cancellation mitigation in tag-to-tag communication

Passive sensing system, as the connection engine of the internet of things, changes the living environment and lifestyle of people profoundly. In order to improve the data transmission rate of passive sensing systems, this paper proposes and adopts scalable high-order backscatter modulation technology. While improving the overall throughput performance of the system, the problem of decoding difficulties caused by phase cancellation in the tag-to-tag communication process is solved. The practical problem of improving the throughput performance of the passive communication system in the system design at the expense of the bit error rate is solved. Finally, based on the probability distribution characteristics of the reflected signal, combined with the signal detection theory, an energy estimation strategy conforming to the environmental reflection signal is designed. The throughput performance and recognition efficiency of the passive sensing system are significantly improved.

Stochastic Approximation Aided Adaptive Thresholding for Optical Detection in PAM4 Based FSO Transmission

This study proposes an adaptive thresholding optical detection technique using a stochastic approximation (SA) to enhance receiver performance in multi-level pulse amplitude modulation (PAM) based free-space optical (FSO) transmission. When the receiver detects the symbol by fixed threshold decision (FTD) scheme, the detection performance of high order modulation, including PAM4, becomes degraded due to a random fluctuation of the received signal. Owing to the slow varying characteristic of atmospheric turbulence, we used an adaptive linear prediction (ALP) filter to predict the decision threshold of the upcoming frame. The experiment was conducted on various degrees of turbulence channels. A Mach-Zehnder modulator (MZM) based turbulence channel emulator was used to experimentally investigate the turbulence-induced scintillation effect. The experiment results confirmed that the proposed technique yielded improved receiver performance compared to FTD. In the case of considering the amplified spontaneous emission (ASE) noise of erbium-doped fiber amplifier (EDFA), the adaptive threshold decision (ATD) scheme obtained about 3dB gain compared with an even-valued threshold (EVT) decision scheme when the average EDFA input optical power was below -16dBm.

A Highly Efficient and Linear mm-Wave CMOS Power Amplifier Using a Compact Symmetrical Parallel–Parallel Power Combiner With IMD3 Cancellation for 5G Applications

This paper presents a fully integrated linear power amplifier (PA) in a 65-nm CMOS process for mm-wave 5G applications. The proposed linear PA employs a compact symmetrical 4-way parallel–parallel power combiner with a third-order intermodulation distortion (IMD3) cancellation method to achieve high linear output power with a high power-added efficiency (PAE). An on-chip 4-way parallel–parallel power combiner, which combines the output power from 8-unit PAs, is designed with a compact footprint ( $241\,\,\mu \text{m}\,\,\times 241\,\,\mu \text{m}$ ). Conventional series power-combining transformer based power combiners have poor symmetrical performance for the amplitude and phase of the input impedance among unit PAs owing to the parasitic effects of the power combiners. However, the proposed parallel–parallel power combiner, which is based on parallel power-combining transformer structures, shows good symmetrical performances among unit PAs. Moreover, an IMD3 cancellation method using a parallel–parallel power combiner is proposed in this work. The proposed IMD3 cancellation method can support high-order modulation signals without increasing the complexity and reduce the dependence for digital predistortion (DPD). Consequently, the proposed linearization method obtains a high linear POUT and PAE without DPD. The PA in 65-nm CMOS demonstrates a saturated output power (PSAT) of 23.2 dBm, a 15.9-dB power gain, a 1-dB compressed output power ( $\text{P}_{\mathrm {O,1dB}}$ ) of 22 dBm, and a peak power-added efficiency (PAE) of 33.5% at 28 GHz. The measured error vector magnitude with 100 Msym/s of 256/512-QAM is −31.2/−32.1 dB with average output power of 18.02/17.73 dBm, average PAE of 17.6/16.1%, and adjacent channel power ratio (ACPR) of −30/−33.1 dBc without DPD. To the best of the authors’ knowledge, the proposed PA demonstrates high output power with the highest PAE performance supporting 256/512-QAM compared to the recently published fully integrated mm-wave 5G CMOS PAs.

Low Complexity Linear Detectors for Massive MIMO: A Comparative Study

Massive multiple-input multiple-output (M-MIMO) is a significant pillar in fifth generation (5G) networks where a large number of antennas is deployed. It provides massive advantages to modern communication systems in data rate, spectral efficiency, number of users serviced simultaneously, energy efficiency, and quality of service (QoS). However, it requires advanced signal processing for data detection. The growing MIMO size leads to complicated scenarios, which makes the detector design a knotty problem. The problem is also becoming more complicated when high-order modulation schemes are exploited and more users are multiplexed. Therefore, it is not practical to employ the maximum likelihood (ML) detector despite the excellent performance. Linear detectors are alternative solutions and relatively simple. Unfortunately, they still need an exact matrix inversion computation, which bears to a significant high complexity. Therefore, several iterative methods are utilized to approximate or evade the matrix inversion rather than computing it. This paper studies the pros and cons of iterative matrix inversion methods where the number of computations and bit-error-rate (BER) are considered to compare between the methods. The comparison is conducted in several scenarios such as different ratio between the number of base station (BS) antennas and user terminal (UT) antennas (β), the number of iterations (n), and the relaxation parameter (ω). This paper also studies the impact of ω in the performance of Richardson (RI) and the successive over-relaxation (SOR) methods. Numerical results show that the conjugate gradient (CG) and optimized coordinate descent (OCD) methods exhibit the lowest complexity with an acceptable performance. In addition, the Gauss-Seidel (GS) method outperforms all other detectors with a trivial complexity increment. It is also noticed that the performance is not improved with every iteration. It is also shown that ω has a great impact and a significant role in achieving a satisfactory performance in both RI and SOR based detectors. From implementation point of view, detectors based on RI, OCD, and CG methods have achieved the highest hardware efficiency (HE) while Jacobi (JA) based detector has obtained the lowest HE. Recent research advances of detection methods are also presented in the open research direction with a potential impact of linear detection methods in initialization and pre-processing.

A Robust Decision Directed Algorithm for Blind Equalization Under $\alpha$-Stable Noise

This paper reports a solution to a linear blind equalizer used in communication systems under the effect of two factors: i) An unknown linear inter symbol interference and ii) the impulsive noise satisfying the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\alpha$</tex-math></inline-formula> -stable distribution. First, a constellation matching error-based cost function associated with the linear equalizer is designed to effectively compensate for the inter symbol interference and suppress the influence of the impulsive noise. Second, an improved form of the proposed cost function is derived through the finite alphabet property of information symbols. The theoretical analysis shows that the improved cost function significantly reduces the local minima and converges more stably in high-order modulation systems. Furthermore, based on the special structure of the designed cost function, a modified Newton scheme is constructed to quickly minimize it, and then the corresponding optimal blind equalizer can be obtained. Finally, computer simulations are presented to demonstrate the robust equalization performance and fast convergence of the novel algorithm under both impulsive and Gaussian noise environments.

A Predistortion-Less Digital Transmitter With −50-dB ACLR Exploiting Output Conductance Linearization

Switched capacitor power amplifiers (SCPAs) are a class of digital transmitters which have shown promising results for high linearity with good drain efficiency (DE). Their linearity is limited by AM-PM distortion, caused by a difference in output conductance in switching and nonswitching driver cells. Often, digital predistortion (DPD) is required to transmit higher-order modulation schemes. In this letter, a driver cell implementation as an inverter with drain resistors is proposed which has equal output conductance in both cases, aiming to eliminate AM-PM distortion. An SCPA with these driver cells is implemented in a 22-nm fully depleted silicon-on-insulator (FD-SOI) CMOS process which demonstrates excellent DPD-less linearity with an adjacent channel leakage ratio (ACLR) of −50 dB and an error vector magnitude (EVM) of −45.5 dB for 5-MHz 1024 QAM signals at a DE of 8.8%. A matching network exploiting bondwires as high-Q inductors removes on-chip inductors and significantly reduces chip area.

A Survey on Modulation Techniques in Molecular Communication via Diffusion

This survey paper focuses on modulation aspects of molecular communication, an emerging field focused on building biologically-inspired systems that embed data within chemical signals. The primary challenges in designing these systems are how to encode and modulate information onto chemical signals, and how to design a receiver that can detect and decode the information from the corrupted chemical signal observed at the destination. In this article, we focus on modulation design for molecular communication via diffusion systems. In these systems, chemical signals are transported using diffusion, possibly assisted by flow, from the transmitter to the receiver. This tutorial presents recent advancements in modulation and demodulation schemes for molecular communication via diffusion. We compare five different modulation types: concentration-based, type-based, timing-based, spatial, and higher-order modulation techniques. The end-to-end system designs for each modulation scheme are presented. In addition, the key metrics used in the literature to evaluate the performance of these techniques are also presented. Finally, we provide a numerical bit error rate comparison of prominent modulation techniques using analytical models. We close the tutorial with a discussion of key open issues and future research directions for design of molecular communication via diffusion systems.

High Order PSK Modulation in Massive MIMO Systems With 1-Bit ADCs

Massive multiple-input multiple-output (MIMO) systems with 1-bit analog-to-digital converters (ADCs) are promising to reduce the energy consumption. However, the serious quantization error caused by 1-bit ADCs will potentially limit the feasibility of high order modulations. This paper focuses on the analysis of the high order phase-shift keying (PSK) signal transmission in the 1-bit ADC massive MIMO system. Firstly, assuming ideal channel estimation and a single mobile station (MS), we theoretically prove that with an asymptotically large number of antennas at the base station, PSK signals with arbitrary modulation order can be recovered in the 1-bit ADC massive MIMO system. Secondly, we analyze the impact of pilot based channel estimation on the recovery of the high order PSK signals, which leads to a periodic asymptotic detection phase error (ADPE) at high signal to noise ratio (SNR). Furthermore, we also propose to optimize the pilot sequence for minimizing the cumulative absolute ADPE. Finally, the analysis is extended to the multi-MS case and the performance with different pilot patterns is discussed. Simulation results validate our analysis and show that using our proposed optimized pilot sequence can significantly improve the detection performance for both single-MS and multi-MS 1-bit ADC massive MIMO systems.

A 32 Gb/s PAM-16 TX and ADC-Based RX AFE with 2-tap embedded analog FFE in 28 nm FDSOI

This paper presents a 32 Gb/s 16-level pulse amplitude modulation (PAM-16) source-series-terminated transmitter (TX) and a receiver (RX) analog front-end (AFE) in 28 nm FDSOI. The 8-way time-interleaved successive-approximation register (SAR) analog-to-digital-converter (ADC) in the RX AFE has an embedded 2-tap analog feed-forward equalizer. The design objective is to optimize the energy efficiency for the target data rate and the moderate-loss channel. For this purpose, the optimum modulation order that has the least ISI sensitivity for the given equalization capability is decided with a modeling study. All the equalization is performed in the analog domain to avoid the circuit complexity and power consumption disadvantages of the digital equalization in the selected high-order modulation. Thanks to the spectral efficiency of PAM-16 and the analog-only equalization, the figure-of-merit is improved significantly. Post-layout simulations show that the TX consumes 26.85 mW while the RX AFE consumes 49.36 mW at 32 Gb/s with PAM-16, which corresponds to 2.38 pJ/bit for the whole system.