Quadrature Amplitude Modulation Signals Research Articles

Efficient QAM Signal Detector for Massive MIMO Systems via PS/DPS-ADMM Approaches

In this paper, we design two efficient quadrature amplitude modulation (QAM) signal detectors for massive multiple-input multiple-output (MIMO) communication systems via the penalty-sharing alternating direction method of multipliers (PS-ADMM). The content of the paper is summarized as follows: first, we transform the maximum-likelihood detection model to a non-convex sharing optimization problem for massive MIMO-QAM systems, where a high-order QAM constellation is decomposed to a sum of multiple binary variables, integer constraints are relaxed to box constraints, and quadratic penalty functions are added to the objective function to result in a favorable integer solution; second, a customized ADMM algorithm, called PS-ADMM, is presented to solve the formulated non-convex optimization problem. In the implementation, all variables in each vector can be solved analytically and in parallel; and third, in order to solve the penalty-sharing distributively, we improve the proposed PS-ADMM algorithm to a distributed one, named DPS-ADMM. In the end, performance analyses of the proposed two algorithms, including convergence properties and computational cost, are provided. Simulation results demonstrate the effectiveness of the proposed approaches.

Novel Algorithm for Nonlinear Distortion Reduction Based on Clipping and Compressive Sensing in OFDM/OQAM System

Orthogonal Frequency Division Multiplexing with Offset Quadrature Amplitude Modulation (OFDM/OQAM) signal has high peak-to-average power ratio (PAPR) problem. It not only affects the distortion in High Power Amplifier (HPA) but also results in bit error ratio (BER) degradation. In this paper an improved algorithm based on Clipping and Compressed Sensing (CS) is proposed. The transmitter uses clipping to reduce the PAPR and, the receiver uses an improved inverse model, to reduce the nonlinear distortion introduced by HPA and CS cancels the signal distortion introduced by clipping. Simulation results show that the proposed method not only significantly reduces the PAPR of OFDM/OQAM signals, but also effectively improves the BER performance of the system.

Blind frequency offset estimation using the optimal decision threshold-assisted QPSK-partition method for probabilistically shaped MQAM systems.

Moderate or strong shaping conditions reduce the occurrence probability of the outermost ring constellation points of probabilistically shaped (PS)-M quadrature amplitude modulation (QAM) signals, which easily causes the peaks in the 4th power periodogram of received signals be submerged, accordingly the classical frequency offset estimation (FOE) scheme using 4th power fast Fourier transform (FFT) cannot be applied in PS-MQAM system. To solve this issue, we have proposed an optimal decision threshold assisted quadrature phase shift keying (QPSK)-partition blind FOE scheme. Firstly, the proposed scheme utilizes an optimal decision threshold assisted method for the symbol decision of received symbols, then chooses the symbols on multiple specific QPSK-shape rings. Secondly, the amplitude of each symbol selected above is normalized and uniformly augmented to 18. Finally, it carries out FOE using an improved time-domain 4th power feedforward method that eliminates the time interval. The effectiveness of the proposed scheme has been verified by 28 GBaud polarization division multiplexing (PDM) PS-16/64QAM simulations and 28/8 GBaud PS-16/64QAM experiments. The results obtained by this scheme present that under moderate or strong shaping conditions, the generalized mutual information (GMI) increases with optical signal-to-noise ratio (OSNR) and eventually exceeds the corresponding GMI threshold. Besides that, the FOE range can reach [-Rs/8, Rs/8], where Rs denotes the baud rate. When OSNRs are higher than 16 dB and 19.5 dB, the NMSEs of PS-16QAM-3/3.6 are lower than 1e-7, respectively. For PS-64QAM-4.4/5, the NMSEs achieve lower than 1e-6 after OSNR increases to 20.3 dB and 23.4 dB, respectively. More importantly, the overall complexity can be reduced to O(N), which is at most as 26.5% as that of FFT FOE scheme.

Model-based end-to-end learning for a self-homodyne coherent system.

We investigate the statistical properties of the inherent intensity fluctuation in a low-cost and low-complexity self-homodyne coherent system employing an amplified spontaneous emission (ASE) source. The noise distribution model of the considered system is established, which is shown to be highly consistent with the experimental results for a 10 GBd 256-ary quadrature amplitude modulation (QAM) signal transmission over a 10 m duplex fiber. With the help of the proposed noise model, we then design advanced mappers and demappers. The optimized system alleviates the need for ASE bandwidth and is evaluated by applying forward error correction codes. Furthermore, we demonstrate an information rate increase of 6.67% with respect to 64-QAM.

Parallel Distribution Matcher Base on CCDM for Probabilistic Amplitude Shaping in Coherent Optical Fiber Communication

As a typical high-order modulation format optimization technology, constellation probability shaping enhances generalized mutual information (GMI) by optimizing the probability distribution of each constellation point of the signal. It can improve the transmission capacity of the same order M Quadrature Amplitude Modulation (QAM) signal under the condition of limited average transmission power, and further narrow the gap with the Shannon limit capacity. The distribution matcher is a key part of constellation probability shaping since it not only ensures the one-to-one mapping of input and output sequences but also realizes the function of probability shaping. The constant composition distribution matcher (CCDM) structure is a widely utilized distribution matcher in the current probability shaping technology. Based on CCDM, a parallel distribution matcher scheme is proposed in this paper. It has a lower rate loss than CCDM for short output lengths (n is less than 100). Block lengths can be reduced by up to 30% with the same rate loss. When the GMI is the same as for the probability shaping (PS) 64QAM signal using CCDM, the OSNR required by the PS-64QAM signal using this scheme can be enhanced by 0.12dB, the block length can be reduced by 40%, and the transmission distance in a standard single-mode fiber can be slightly extended.

Low-Complexity Triplet-Correlative Perturbative Fiber Nonlinearity Compensation for Long-Haul Optical Transmission

In this paper, we propose a triplet-correlative perturbative nonlinearity compensation (TC-PNC) scheme to compensate for intra-channel fiber nonlinear impairments. The complexity of TC-PNC is much lower than both of the conventional perturbative nonlinearity compensation (PNC) and degenerate PNC (DPNC), while the compensation performance of TC-PNC is much better than DPNC and is slightly worse than PNC. Compared to PNC and DPNC, the implementation complexity of TC-PNC is reduced by 94.73% and 22.53%, respectively. The compensation performance is evaluated by both simulations and experiments. In simulations with a transmission distance of 2000 km for 70 Gbaud dual-polarization 16-ary quadrature amplitude modulation (16QAM) signals, the signal-to-noise ratio (SNR) gains of TC-PNC are 0.3 dB and 0.77 dB compared to DPNC and the uncompensated case, respectively. In experiments for 30 Gbaud dual-polarization probabilistically shaped 16QAM (PS-16QAM) signals with a transmission distance of 432 km, the effectiveness of TC-PNC is validated by comparing the performance relative to PNC and DPNC.

Linear Regression vs. Deep Learning for Signal Quality Monitoring in Coherent Optical Systems

Error vector magnitude (EVM) is a metric for assessing the quality of m-ary quadrature amplitude modulation (mQAM) signals. Recently proposed deep learning techniques, e.g., feedforward neural networks (FFNNs) -based EVM estimation scheme leverage fast signal quality monitoring in coherent optical communication systems. Such a scheme estimates EVM from amplitude histograms (AHs) of short signal sequences captured before carrier phase recovery (CPR). In this work, we explore further complexity reduction by proposing a simple linear regression (LR) -based EVM monitoring method. We systematically compare the performance of the proposed method with the FFNN-based scheme and demonstrate its capability to infer EVM from an AH when the modulation format information is known in advance. We perform both simulation and experiment to show that the LR-based EVM estimation method achieves a comparable accuracy as the FFNN-based scheme. The technique can be embedded with modulation format identification modules to provide comprehensive signal information. Therefore, this work paves the way to design a fast-learning scheme with parsimony as a future intelligent OPM enabler.

IRS-Assisted Physical Layer Network Coding Over Two-Way Relay Fading Channels

This article investigates the performance of intelligent reflective surfaces (IRS)-aided physical layer network coding (PNC) in two-way relaying channels (TWRC). Specifically, IRS is used to eliminate carrier phase offset (CPO) at the relay node. To this end, the IRS reflectors’ phase shifts are optimized to align the received signals from two source nodes at the relay. This facilitates using a simple mapping function at the relay to map the superimposed signal to a network-coded signal. Two scenarios are considered, the first of which assumes that each source node is served by a separate IRS panel, while the second scenario considers the more challenging case where only one IRS panel is available for the two source nodes. In the latter case, the IRS panel is seen by both source nodes and its phase shifts are optimized to mitigate the CPO problem while maximizing the received signal amplitude at the relay. This optimization problem is formulated and solved over the complex circle manifold. Finally, we extend the IRS-assisted PNC system to include channel coding and higher modulation orders, for which a repeat accumulate (RA) channel-coded IRS-aided PNC scheme is proposed for general quadrature amplitude modulation (QAM) signals. A belief propagation (BP) based algorithm is designed to decode the network-coded sequences over a q-Ring using modular arithmetic. Our simulation results validate the theoretical error expressions derived for the two-IRS scenario as well as the efficacy of the proposed manifold optimization approach for the one-IRS scenario. The results also confirm the efficacy of the designed channel-coded IRS-aided PNC using high QAM modulation orders.

Transmission of OCDM Based on Asymmetric Pair Mapping Over a Seven Core Fiber

In this paper, transmission of orthogonal chirp division multiplexing (OCDM) based on asymmetric pair mapping over a seven core fiber is proposed. High-order 32 quadrature amplitude modulation (QAM) is reduced to quadrature phase-shift keying (QPSK) and 8 QAM signal employing asymmetric pair mapping, which will not affect the rate of the system. Combined with geometric shaping (GS), the average transmission power is successfully lowered, realizing signal damage suppression. In order to verify the performance of the proposed asymmetric pair mapping scheme, a 140 Gb/s asymmetric pair mapping OCDM signal transmission over 2 km seven core fiber is experimentally demonstrated. The experimental results show that the proposed transmission scheme has the best performance when the power distribution ratio (PDR) is 4 dB. Meanwhile, compared with GS 32 QAM with QPSK+rectangle 8 QAM, GS 32 QAM with QPSK+star 8 QAM and GS 32 QAM, the proposed asymmetric pair mapping OCDM signal has improved by 1.55 dB, 1.45 dB, and 0.7 dB, respectively. It has a wide range of applications in the future optical transmission system due to its outstanding performance in the suppression of high-order modulation signal degradation.

Deep graph neural network optimized with fertile field algorithm based detection model for uplink multiuser massive multiple‐input and multiple‐output system

AbstractThe core requirements are generated for sixth generation (6G) wireless communication with low‐latency and ultra‐high speeds to increase the count of ultra scale intelligent factors, like smart cars, mobile root users. The advancement of 6G communication can lead the interference exploitation. To manage the exploitation of uplink multiuser massive (UMM), the multiple‐input and multiple‐output (MIMO) is very difficult to detect the mechanisms, particularly, quadrature amplitude modulation (QAM) signals. To overcome these issues, a novel deep graph neural network optimized with fertile field algorithm based detection model (DGNNO‐FFA) is proposed in this article for uplink multiuser massive MIMO System. The proposed DGNNO‐FFA approach minimizes the channel estimation errors under low signal to noise ratio (SNR) with better bit error rate (BER). Finally, the proposed DGNNO‐FFA approach attains 11.02%, 12.22%, and 25.27% lower BER value, 14.55%, 18.66%, and 29.49% higher energy efficiency, 15.59%, 19.06%, and 29.59% lower NMSE, and 15.59%, 19.06%, and 29.59% lower computational complexity compared with other existing approaches, like deep neural network based semi definite relaxation (DNN‐SDR), QR based zero forcing algorithms (QR‐ZF), and QAM based 2‐dimensional double successive projection model (QAM‐2D‐DSP).

Wireless transmission of a 200-m PS-64QAM THz-wave signal using a likelihood-based selection radius-directed equalizer.

Based on a photonics-aided scheme, we achieve an experimental demonstration of a, to the best of our knowledge, record-breaking 200-m terahertz (THz)-wave wireless delivery at 335 GHz with the aid of a pair of high-gain polytetrafluoroethylene (PTFE) lenses. By using a 10-GBaud probabilistically shaped 64-ary quadrature amplitude modulation (PS-64QAM) signal and advanced digital signal processing (DSP) including a likelihood-based selection radius-directed equalizer (LBS-RDE), the single-carrier net bit rate of the wireless delivery reaches 44 Gbit/s. High-speed THz-wave communication with up to 200-m wireless distance is successfully realized based on a photonics-aided scheme for the first time.

Cascaded digital-analog radio-over-fiber for efficient SNR scaling at >10 dB per extra bandwidth.

Efficient signal-to-noise ratio (SNR) and spectral efficiency (SE) trade-off can offer fundamental guiding law for future large-capacity and high-fidelity mobile fronthaul. In this Letter, we propose and experimentally demonstrate a cascaded digital-analog radio-over-fiber (CDA-RoF) scheme, which transmits digitized and analog segments using time-division-multiplexing aggregation. Specifically, multiple digital parts generated by a rounding function describe the main features of the original waveform, while the residual error is magnified and delivered as analog RoF with SE advantage. Based on a 20-GHz O-band directly modulated laser (DML), an SNR enhancement of >10 dB is observed for each extra bandwidth. Up to 70.4-dB SNR is also achieved for a 3.5-GHz 1048576-ary quadrature amplitude modulation (1048576-QAM) signal after 20-km standard single-mode fiber (SSMF) transmission.

Low-complexity and blind receiver in-phase/quadrature imbalances compensation and estimation in the frequency domain for high-order modulation formats.

A frequency domain (FD) 4×2 multi-input and multi-output (MIMO) equalizer based on radially directed equalizer is proposed to compensate receiver in-phase/quadrature (IQ) imbalances of M-ary quadrature amplitude modulation signals. This algorithm has a significantly lower complexity compared with a conventional time-domain 4×2 MIMO equalizer. Furthermore, each of imperfection estimations is derived from the converged discrete frequency response of the FD 4×2 MIMO equalizer. The simulation and experimental results indicated that the receiver (Rx) IQ imbalances were fully compensated by the proposed equalizer and precisely estimated by estimators, even for long-haul transmission with Rx IQ imbalances varying over a wide range.

Blind and low-complexity modulation format identification based on signal envelope flatness for autonomous digital coherent receivers.

Modulation format identification (MFI) is a critical technology for autonomous digital coherent receivers in next-generation elastic optical networks. A novel and simple MFI scheme, to the best of our knowledge, based on signal envelope flatness is proposed without requiring any training or other prior information. After amplitude normalization and partition, the incoming polarization division multiplexed (PDM) signals can be classified into quadrature phase shift keying (QPSK), 8 quadrature amplitude modulation (QAM), 16QAM, and 64QAM signals according to envelope flatnesses R1, R2, and R3 of signals in different amplitude ranges. The feasibility of the proposed MFI scheme is first verified via numerical simulations with 28 GBaud PDM-QPSK/-8QAM/-16QAM/-64QAM signals. Only by using 4000 symbols can the proposed MFI scheme achieve a 100% correct identification rate for the four modulation formats over a wide optical signal-to-noise ratio (OSNR) range. Proof-of-concept experiments among 28 GBaud PDM-QPSK/-8QAM/-16QAM systems under back-to-back and long-haul fiber transmission links are implemented to further demonstrate the effectiveness of the proposed MFI scheme. The experimental results show that the proposed MFI scheme can obtain a 100% correct identification rate when the OSNR value of each modulation format is higher than the threshold corresponding to 7% FEC and is resilient towards fiber nonlinearities. More importantly, the proposed MFI scheme can significantly reduce computational complexity.

Feedforward Neural Network-Based EVM Estimation: Impairment Tolerance in Coherent Optical Systems

Error vector magnitude (EVM) is commonly used for evaluating the quality of m-ary quadrature amplitude modulation (mQAM) signals. Recently proposed deep learning techniques for EVM estimation extend the functionality of conventional optical performance monitoring (OPM). In this article, we evaluate the tolerance of our developed EVM estimation scheme against various impairments in coherent optical systems. In particular, we analyze the signal quality monitoring capabilities in the presence of residual in-phase/quadrature (IQ) imbalance, fiber nonlinearity, and laser phase noise. We use feedforward neural networks (FFNNs) to extract the EVM information from amplitude histograms of 100 symbols per IQ cluster signal sequence captured before carrier phase recovery. We perform simulations of the considered impairments, along with an experimental investigation of the impact of laser phase noise. To investigate the tolerance of the EVM estimation scheme to each impairment type, we compare the accuracy for three training methods: 1) training without impairment, 2) training one model for all impairments, and 3) training an independent model for each impairment. Results indicate a good generalization of the proposed EVM estimation scheme, thus providing a valuable reference for developing next-generation intelligent OPM systems.

On‐Chip High‐Speed Coherent Optical Signal Detection Based on Photonic Spin‐Hall Effect

AbstractThe use of coherent optical signal processing in long‐distance optical communication systems has dramatically increased data capacity enabling encoding of multiple‐bit information in the phase of a light beam. Direct detection of phase information of a high‐speed modulated light remains challenging and requires an external, local oscillator for referencing, which is expensive for short‐reach optical communications, for example, in data centers. The availability of less‐complex integrated photonics devices for coherent signal detection will alleviate this bottleneck. On the other hand, phase information of coherent, orthogonally polarized light beams can be extracted from their polarization states, and it is, therefore, possible to achieve phase measurements via fast polarization detection. Here, an on‐chip nanodisk device is demonstrated for high‐speed coherent optical signal detection enabled by spin–orbit coupling in Si‐photonics circuitry. In a coherent communication experiment with up to 32 GBaud rate, the high‐speed phase‐shift keying and quadrature amplitude modulation signals detected by a Si nanodisk based polarization measurements at multiple wavelengths in the C‐band are recovered with a bit error rate below the forward error correction threshold. The proposed on‐chip nanodisk device shows promise in high‐speed coherent optical communication applications where phase detection is required at low cost and small footprint.

Secure OFDM-PON using three-dimensional selective probabilistic shaping and chaos.

In this paper, a novel three-dimensional selective probabilistic shaping (3D-SPS) and chaos-based multi-stage encryption scheme is proposed for physical layer security enhancement and transmission performance improvement in orthogonal frequency division multiplexing-based passive optical network (OFDM-PON). On the basis of inherent randomness of symbol sub-sequences with low granularity, the SPS algorithm is performed on the employed cubic constellation within each sub-sequence. Consequently, the probability distribution of inner points significantly increases after the constellation region exchange according to various rules. The generated compressed shaping information (CSI) is encrypted and used as the synchronization head for transmission. Furthermore, 3D scrambling is performed while maintaining the shaping effect. The encrypted signals of 35.3 Gb/s are successfully transmitted over a 25-km standard single-mode fiber (SSMF) and a back-to-back (BTB) system. The results show that by selecting the appropriate system parameter, the proposed scheme can provide about 2.4 dB modulation gain on the received optical power at a bit error rate (BER) of 10‒3 compared with a conventional quadrature amplitude modulation (QAM) signal under the same bit rate, and 0.9 dB shaping gain is brought due to the SPS. The encryption method possesses a relatively low computational complexity and sufficient key space of 10120 is introduced to resist exhaustive attack.

High-Speed Terahertz Band Radio-Over-Fiber System Using Hybrid Time-Frequency Domain Equalization

The radio-over-fiber (RoF) orthogonal frequency division multiplexing (OFDM) system at Terahertz (THz) band has been a promising solution to meet the demand for high capacity and flexibility. The signals transmitted in the RoF system will suffer severe impairments caused by the wireless multi-path effect, optical fiber transmission, and photoelectric device response. The time-frequency domain equalization (TFDE) based on the two-dimension convolution (Conv2D) neural network (NN) is proposed to resist the linear and nonlinear impairments of the RoF-OFDM system. Furthermore, complex convolution is applied to compensate for the complex channel response. Compared with several baseline models, the detailed performance improvement and model size discussion of the complex-valued Conv2D NN TFDE are investigated. With the aid of the complex-valued Conv2D NN TFDE, the 16 Gbaud 16-ary quadrature amplitude modulation (16QAM) signals are delivered over 54.6 m wireless distance and 20 km standard single mode fiber. The line rate of this RoF system achieves 53.5 Gbit/s.

Application of Approximation Constructions with a Small Number of Parameters for the Estimation of a Rayleigh Fading Multipath Channel with Doppler Spectrum Spreading.

In this article, an algorithm for joint estimation of communication channel gains and signal distortions in a direct conversion receiver is proposed. The received signal model uses approximations with a small number of parameters to reduce the computational complexity of the resulting algorithm. The estimation algorithm is obtained under the assumption of a priori uncertainty about the characteristics of the communication channel and noise distribution using the linear least squares method. Estimation is performed first by the test sequence, then by the information symbols obtained after detection. In addition, an analysis of the noise immunity of quadrature amplitude modulation (QAM) signal reception is carried out using different approximating structures in the estimation algorithm for systems with a single transmitting and receiving antenna (SISO) and for systems with multiple transmitting and receiving antennas (MIMO). Furthermore, this article examines the influence of the duration of the test signal, the number of sessions of its transmission, and the channel extrapolation interval on the quality of signal reception.

Full-duplex hybrid optical link with 40 Gbit/s 16-QAM signal for wired or wireless selective access based on polarization division multiplexing.

A full-duplex hybrid optical link with 40 Gbit/s 16-ary quadrature amplitude modulation (16-QAM) signal based on polarization division multiplexing (PDM) is proposed, which can provide wired or wireless selective access for the user terminals. The 16-QAM downlink signal for wired and wireless accesses is only modulated onto one of the polarization states of the light wave. Then the generated data-bearing optical tone orthogonally combines with the other polarization state to constitute the downlink optical signal. At the hybrid optical network unit (HONU), an ordinary laser with the fixed wavelength is not only used to provide the optical local oscillator (OLO) for downlink wireless access but also the optical carrier for its uplink, while the OLO and uplink optical carrier for wired access are extracted from the downlink optical signal. Moreover, since the downlink optical signal is a baseband one with two orthogonal polarization states, the spectrum efficiency of our proposed scheme is high. The obtained constellations and eye diagrams of the demodulated 16-QAM downlink and uplink signals for wired and wireless accesses show that our proposed full-duplex hybrid optical link can still maintain a good transmission performance after being transmitted over 20 km standard single mode fiber (SSMF).