Additive White Gaussian Noise Channel Research Articles

Ultra-high-cardinality geometric shaping in the finite SNR regime.

Four-dimensional (4D) constellations with up to 131 072 points (17 bit/4D-sym) are designed for the first time using geometric shaping. The constellations are optimized in terms of mutual information (MI) and generalized MI (GMI) for the additive white Gaussian noise (AWGN) channel, targeting a forward error correction (FEC) rate of 0.8 at finite signal-to-noise ratios. The presented 15-17 bit constellations are currently the highest-performing constellations in the literature, having a gap to the AWGN capacity as low as 0.17 dB (MI) and 0.45 dB (GMI) at 17 bit/4D-sym. For lower cardinalities, our constellations match or closely approach the performance of previously published optimized constellations. We also show that (GMI-)optimized constellations with a symmetry constraint, optimized for a FEC rate of 0.8, perform nearly identical to their unconstrained counterparts for cardinalities above 8 bit/4D-sym. A symmetry constraint for MI-optimized constellations is shown to have a negative impact in general. The proposed procedure relies on a Monte-Carlo-based approach for evaluating performance and is extendable to other (nonlinear) channels. Stochastic gradient descent is used for the optimization algorithm for which the gradients are computed using automatic differentiation. This article is part of the theme issue 'Celebrating the 15th anniversary of the Royal Society Newton International Fellowship'.

A noncoherent chaotic communication system with multidimensional index modulation based on cyclic permutation grouping

With the surge in technological advancements and application demands, the study of high-data-rate communication systems has become increasingly significant. To enhance the data transmission rate and spectral efficiency of traditional DCSK systems, we have designed a differential chaos shift keying (DCSK) system with multidimensional index modulation based on cyclic permutation grouping (CPG-MIM-DCSK). Multidimensional index resources are efficiently combined by the CPG-MIM-DCSK system using the proposed cyclic permutation grouping method. In the CPG-MIM-DCSK system, both selected and unselected subcarriers, as well as selected and unselected time slots, are distinguished through different groups of cyclic permutations. Permutation, carrier, and time slot resources are fully utilized by this modulation method, thereby enhancing the data rate and spectral efficiency of traditional DCSK systems. The theoretical Bit Error Rate (BER) expressions of the CPG-MIM-DCSK system under Additive White Gaussian Noise (AWGN) and multipath Rayleigh fading channels are derived. The data rate, complexity, and spectral efficiency of the CPG-MIM-DCSK system are covered in further analysis. The simulation results highlight the superiority of the CPG-MIM-DCSK system in terms of data rate and spectral efficiency. Additionally, the proposed CPG-MIM-DCSK system exhibits better BER performance in both Gaussian and multipath Rayleigh fading channels compared to its comparative systems.

Enhanced mutual information neural estimators for optical fiber communication.

The accurate estimation of mutual information (MI) plays a vital role in understanding channel capacity and optimizing the performance of optical communications. While MI computations for the additive white Gaussian noise (AWGN) channel are well-established, they fall short when dealing with the challenges posed by nonlinear optical fiber channels due to an unknown channel model. For the first time, to our knowledge, this Letter introduces a mutual information neural estimator (MINE) for MI estimation in optical fiber communications. We propose an enhanced MINE (E-MINE), achieved by enlarging the training batch size to improve estimation accuracy and stability. Our findings reveal that the E-MINE achieves highly accurate estimations in the AWGN channel and maintains strong consistency with symbol-by-symbol MI estimations, comparable to Monte Carlo (MC) methods based on a Gaussian distribution in long-haul optical fiber channels. Furthermore, with multi-symbol estimation, the E-MINE yields a 0.16 bits/4D-symbol improvement in our experiments. We anticipate that our findings will drive further research in the field, opening new possibilities for enhancing communication systems design and performance using deep learning techniques.

Performance Evaluation of Fractal Wavelet Packet Transform on Wireless Communication Systems

The performance of the phase shift keying (PSK) modulation technique over additive white Gaussian noise (AWGN) and multipath propagation channels generally becomes worse for higher-order modes. Therefore, a new modulation technique should be provided in order to have a system that is capable of transmitting data with higher efficiency while maintaining better performance at the same time. This paper presents the development of a fractal wavelet packet transform incorporated within the M-ary PSK system, namely M-ary PSK orthogonal wavelet division multiplexing (OWDM), which is proposed to obtain high performance of modulation in terms of spectrum efficiency and bandwidth resources intended for wireless communication systems. To demonstrate performance improvement over a Rayleigh frequency selective fading channel and in the presence of AWGN noise, the proposed system was evaluated and compared to the basic modulation system and M-ary PSK employing orthogonal frequency division multiplexing (OFDM). The performance results show that M-ary PSK OWDM had better performance in comparison with M-ary PSK OFDM and the conventional system. By utilizing 16 subcarriers, QPSK OWDM achieved bit error rate performance improvement from 1.5 × 10-3 to 1 × 10-4 for Eb/N0 of 20 dB with efficient bandwidth.

Method for predicting the lost input of iterative learning control systems over AWGN channels

This paper researches the method for predicting the lost input of iterative learning control (ILC) systems over additive white Gaussian noise (AWGN) channels. It directly takes into account a proportional ILC controller, which guarantees the convergence of objects under ideal communication conditions. By employing prior information on ILC controllers and AWGN channels, a state space model is built. According to this model and the innovation analysis theory, a predictor is developed for actuators to calculate the input transmitted by ILC controllers but lost in AWGN channels. Compared with the iteration compensation in existing literature, the proposed prediction compensation simultaneously guarantees the convergence accuracy and speed of ILC systems over AWGN channels. Numerical simulation demonstrates the usefulness of the developed prediction method.

A high-data-rate hybrid index communication system based on quadrature chaos shift keying

To address the rapidly increasing challenges posed by the demands for large-scale data transmission and processing, this paper proposes a high-data-rate hybrid index modulation communication system based on quadrature chaos shift keying (HR-HIM-QCSK). The system employs a hybrid modulation involving carrier index and slot index. In this approach, three mutually orthogonal reference signals are constructed using Walsh codes. These reference signals are then utilized to create three distinct QCSK signals, distinguishing between the activation modes of carriers and time slots. This design allows all slots to carry QCSK signals, significantly enhancing the data rate of the HR-HIM-QCSK system. Theoretical analysis and simulations conducted under additive white Gaussian noise and multipath Rayleigh fading channels demonstrate that the HR-HIM-QCSK system outperforms other competing systems in terms of bit error rate (BER) performance. Further analysis covers aspects such as data rate, spectral efficiency, complexity and covertness, highlighting the superior performance of the HR-HIM-QCSK system in high-data-rate communication. This study provides valuable insights for the design of efficient chaotic communication systems.

Sign of slant receiver for skewed alpha-stable noise shift keying-based random communication system

Purpose In contrast to traditional communication systems, slower data rate has always remained a weak link for non-traditional random communication systems (RCSs), which use alpha-stable (a-stable) noise as a carrier. This paper aims to introduce a fast receiver for skewed a-stable noise shift keying (SkaSNSK)-based RCSs. Design/methodology/approach The introduced receiver is based on the sign of slant estimator (SoSE), which provides rapid estimation of the skewed a-stable random noise signals (RNSs) received from the additive white Gaussian noise channel. The SoSE-based receiver minimizes the number of samples required to extract the encoded information from the received RNSs. This is achieved by manipulating the antipodal properties of the slant/skewness parameter of the a-stable carrier. Hence, a high data rate with relatively low complexity is guaranteed. Findings In comparison with the previously introduced sinc, logarithmic and modified extreme value method-based receivers, the proposed SoSE-based receiver also achieves improved bit error rate (BER) along with the better covertness values so that the essence of security provided by SkaSNSK-based RCSs remains intact. Research limitations/implications Because of the selected range of the associated parameters of the a-stable noise as a carrier, the BER vs MSNR results are may lack applicability for the complete range of values. Therefore, further research is required to produce results in different ranges. Practical implications The study includes implications for the hardware development based on the proposed communication scheme. Originality/value It can be seen that the paper fulfils the desired need of a fast receiver design for RCS.

Comparative Analysis of Channel Coding in Communication Technology

The performance analysis of Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK) employing error-correcting code is highlighted in this work. Several error-correcting code types were employed via an Additive White Gaussian Noise (AWGN) channel to determine the bit error rate. Two techniques were utilized as encoders and decoders: hamming code and cyclic code. Source coding used Huffman coding. Essentially, signal energy to noise power density ratio (Eb/No) and the bit rate error (BER) were used to measure performance. Comparisons were also made between BPSK and QPSK in terms of symbol error capability. MATLAB R2022b was the program used for all the simulations. The conclusion is that different coding methods have a certain error correction range, and the signal-to-noise ratio (SNR) can only reduce the BER in the error correction range, and if it is not within the error correction range, it will increase the bit error rate.

Deep learning-based receiver design for generalized frequency division multiplexing (GFDM)

Generalized frequency division multiplexing (GFDM) is a new efficient multi-carrier system in highly dispersive channels. In a conventional GFDM receiver, if the length of a GFDM block is the power of two (an even number), the equalizer can be implemented with low complexity using the fast Fourier transform (FFT). On the downside, if the block length is even, the GFDM matrix will be singular, leading to severe performance loss. Thus, in the conventional GFDM system, high performance and low complexity cannot be achieved jointly. This paper proposes a new GFDM receiver based on deep learning (DL) methods that can achieve high performance regardless of the GFDM block length. In the proposed GFDM receiver, a deep neural network (DNN) is used to demodulate GFDM symbols. A particular case of a convolutional neural network (CNN) and a fully connected layer are employed in the DNN block. We simulate the proposed DL-based GFDM system in additive white Gaussian noise (AWGN) and multipath channels. Simulation results show that the proposed receiver achieves a significantly higher bit error rate (BER) performance than the conventional GFDM receiver when the length of the GFDM block is even in both AWGN and fading channels. Therefore, the proposed DL-based GFDM receiver can achieve low complexity and high performance simultaneously.

Comparative analysis of coding schemes for effective wireless communication

Communication systems have recently focused on sending information efficiently and effectively from one sending point to another across a communication channel in the shortest amount of time. The main objective of this work is to compare the high-range coding scheme types, such as low density parity check (LDPC), turbo, and convolution, to see which works better and is more efficient. to establish a coding system with quadrature amplitude modulation (QAM) modulation and an additive white gaussian noise (AWGN) noisy channel to find which is more reliable and resilient for encoding and decoding. Because of this, digital media has to be sent over wireless channels and through satellites, requiring a connected network all the time, which has become a major concern over time. Furthermore, the high amount of data and efficiency are the focus points. After running the simulation, it was found that 64 QAM with a rate of 0.455 and an efficiency of 2.731 has a bit error rate (BER) of 0.001 and a 7.08 dB energy per bit Eb/No, and the 256 QAM simulation revealed that it has a BER of 0.001 and 11.88 dB Eb/No with a rate of 0.736 and an efficiency of 5.891. Over the AWGN channel noise, the simulation built a standard orthogonal frequency division multiplexing (OFDM) system, which used MATLAB.

Cross layered adaptive rate optimized irregular LDPC for WSN

This paper proposes a cross layered adaptive rate optimized technique that uses irregular low-density parity-check (LDPC) codes over an additive white Gaussian noise (AWGN) channel in wireless sensor networks (WSNs). Irregular LDPC is used as error control code. Cross layer design along with error control code gives the energy balance in the network. This new algorithm uses the physical layer parameters such as coherence time of the channel, BER and SNR and the routing layer parameter such as demanded data rate to determine the rate of the LDPC coder. The algorithm adaptively changes the code rates as ¾, ½, and 1/3. We have conducted the simulations to verify our methods using MATLAB and find that the proposed scheme increases the network performance in terms of energy balance and quality of data by using irregular LDPC codes in the cross-layer environment.

Performance analysis of two-way multi-users cooperative communication system based on GSPIM-DCSK scheme

Based on the Joint Grouping Subcarrier-Permutation Index Modulation-DCSK (GSPIM-DCSK) system, we provide a new two-way multi-user half-duplex cooperative communication system in this work. Given its many benefits, the GSPIM-DCSK modulation is specifically selected as a choice for network coding techniques. A permutation index is used in the GSPIM-DCSK system to incorporate additional data bits with the modulating and carrier index bits. Establishing a cooperative multiuser system where users attempt to make contact with one another over a common relay is the main goal of this effort. Multi-user nodes and a single relay with a cooperative operator on staff for decoding and forwarding make up this system. To avoid interference from other users, the user’s nodes multiplex across various time intervals. We derive analytical expressions for the average bit error rate (BER) of the GSPIM-DCSK multi-user cooperative communication system in the presence of additive white Gaussian noise (AWGN) and multiple paths Rayleigh fading channels. The analytical and simulated average BER findings have been contrasted to verify the accurateness of the average BER analysis. Additionally, a comparison is presented between the average bit error rate (BER) performance of a novel GSPIM-DCSK cooperative system and an established DCSK cooperative system. The throughput and link spectral efficiency of this novel cooperative system are analyzed and compared with those of existing traditional cooperative systems. For the two-way two-user cooperative system, this comparison is done with two-way two-user systems like DCSK-CC and one-way cooperative system based on CIM-SR-DCSK-CC; for the two-way three-user cooperative system, it is done with scheme1 and scheme2. To compare and assess the performance of various systems, simulation results are employed. Furthermore, an analysis demonstrates how the proposed cooperative system, when combined with GSPIM-DCSK techniques, improves the efficiency of conventional cooperative DCSK systems.

End-to-end learning of adaptive coded modulation schemes for resilient wireless communications

Adaptive modulation and coding schemes play a crucial role in ensuring robust data transfer in wireless communications, especially when faced with changes or interference in the transmission channel. These schemes involve the use of variable coding rates, which can be achieved normally through code puncturing or shortening, and have been adopted in 4G and 5G communication standards. In recent works, auto-encoders for wireless communications have demonstrated the ability to learn short code representations that achieve gains over conventional codes. Such a methodology is attractive as it can learn optimal representations under a variety of channel conditions. However, due to its structure the auto-encoder does not currently support multiple code rates with a single model. This article draws upon the discipline of multi-task learning, as it applies to deep learning and therefore devises a branching architecture for the auto-encoder and custom training algorithm in training transmitter and receiver for adaptive modulation and coding. In this article we aim to demonstrate improvements in Block Error Rate over conventional methods in the Additive White Gaussian Noise channel, and to analyse the performance of the model under Rayleigh fading channels without retraining the auto-encoder on the new channel. This article demonstrates a novel approach towards training auto-encoder models to jointly learn adaptive modulation and coding schemes framed as a multi-task learning problem. The research outcomes extend end-to-end learning approaches to the design of adaptive wireless communications systems.

A Temporal Methodology for Assessing the Performance of Concatenated Codes in OFDM Systems for 4K-UHD Video Transmission

The communication channel is a critical part of the process of information degradation. In the 4K ultra-resolution video transmission domain, the communication channel is a crucial part where information degradation occurs, inevitably leading to errors during reception. To enhance the transmission process in terms of fidelity, advanced technologies such as digital video broadcasting terrestrial (DVB-T) and its evolutionary successor, digital video broadcasting terrestrial second generation (DVB-T2), are utilized to mitigate the effects of data transmission errors. Within this scenario, this research presents an innovative methodology for the temporal analysis of 4K ultra-resolution video quality under the influence of additive white Gaussian noise (AWGN) and Rayleigh channels. This analytical endeavor is facilitated through the application of concatenated coding schemes, specifically, the Bose–Chaudhuri–Hocquenghem concatenated low-density parity check (BCH-LDPC) and Reed–Solomon concatenated convolutional (RS-CONV) coders. A more comprehensive understanding of video quality can be attained by considering its temporal variations, a crucial aspect of the ongoing evolution of technological paradigms. In this study, the Structural Similarity Index (SSIM) serves as the main metric for quality assessment during simulations. Furthermore, the simulated Peak Signal-to-Noise Ratio (PSNR) values validate these findings, exhibiting consistent alignment with the SSIM-based evaluations. Additionally, the performance of the BCH-LDPC significantly outperforms that of RS-CONV under the 64-QAM modulation scheme, yielding superior video quality levels that approximate or surpass those achieved by RS-CONV under QPSK (Quadrature Phase Shift Keying) modulation, leading to an increase in spectral efficiency. This enhancement is evidenced by SSIM gains exceeding 78% on average. The computation of average gains between distinct technologies in video quality analysis furnishes a robust and comprehensive evaluation framework, empowering stakeholders to make informed decisions within this domain.

Evaluating Puncture and Non-puncture for the Turbo Code Model based the on AWGN Channel with 16-QAM

In general, a 5G new radio network is defined by three primary utilization situations, namely upgraded versatile broadband, ultra-reliable, and low latency interchanges of information, as well as huge machine-type correspondences. These utilizations require improved throughput, inertness, dependability contrasted, and a 4G framework. As a coding plan for information, 5G Turbo codes attain high throughput, a variable code rate, and length, and crossover programmed rehash with good error-detecting capability. The execution boundaries of 5G advancements are normal and are tens and thousands of times better compared with 4G. In this paper, the evaluations of puncturing and non-puncturing for turbo code depending on the minimization of penetrating of efficient pieces are discussed. It also provides penetrating of equality pieces considering additive white Gaussian noise (AWGN) Channel with 16 quadrature amplitude modulation (QAM) to attain high spectral efficiency. In addition to this, the super encoder encodes the separated progression with a code speed of 1/3. The code block association progressively connects the yields from the super encoder. The sign mapper employed in this paper adjusts the progression using a 16-QAM balance. Also, the mapper takes effective pieces, one uniformity bit from the upper encoder, and the deinterleaved equity bit from the base encoder. The Orthogonal frequency-division multiplexing (OFDM) mapper parts into more modest equivalent channels, named subcarriers and the information is sent on these equivalent channels at a reduced rate.

Low‐density algebra‐check codes for ultra reliable low latency communications

AbstractA novel channel code, the low‐density algebra‐check (LDAC) code, is introduced in this letter. LDAC code is constructed by combining sparse matrice with algebraic constraints from two types of subcodes. Detailed explanations for the encoding and decoding process of the LDAC codes are provided in the paper. Simulation results demonstrate that LDAC codes offer advantages over LDPC codes in constructing low rate codes. The proposed ultra‐low rate LDAC code can achieve approximately 0.4 and 0.2 dB improvement in SNR compared to CA‐polar and 5G LDPC, respectively, at the block error rate (BER) over the additive white Gaussian noise (AWGN) channel. LDAC codes demonstrate superior performance over LDPC codes at low rates, due to the enhanced error correction capabilities of the two types of subcodes and reduced rates without introducing short cycles.

Design of a Short Reference Differential Chaotic Shift Keying Communication System Based on Reference Signal Scrambling Transformation

A short reference differential chaotic shift keying communication system based on reference signal scrambling transformation (RSST-SR-DCSK) is proposed in this paper. The system introduces information-bit-driven scramblers at the transmission end to effectively eliminate the correlation between the reference signal and information signal. At the receiving end, a descrambler is used to restore the correlation, thereby enhancing information transmission security. Additionally, the system employs a short reference transmission mechanism to further increase the information transmission rate. The transmitter and receiver structures of the system are designed through signal structure analysis. Theoretical analyses and simulations conducted in an additive white Gaussian noise (AWGN) channel demonstrate promising performance, including a low bit error rate (BER) and a favorable data-energy-to-bit-energy ratio (DBR). Simulation verification is performed to examine the impact of parameters on the bit error rate performance. A comparative analysis with traditional DCSK and SR-DCSK systems highlights the superior performance of the RSST-SR-DCSK system.

Analysis of Filtered Multicarrier Modulation Techniques Using Different Windows for 5G and Beyond Wireless Systems

In contemporary wireless communication systems, multicarrier modulation schemes have become widely adopted over single-carrier techniques due to their improved capacity to address challenges posed by multipath fading channels, leading to enhanced spectral efficiency. Orthogonal frequency division multiplexing (OFDM), a prevalent multicarrier scheme in 4G, is favored for its ease of implementation, interference resilience, and high data rate provision. But it falls short of meeting the requirements for 5G and beyond due to limitations such as out-of-band (OOB) emissions and cyclic prefixes. This paper introduces the filter bank multicarrier (FBMC) and universal filtered multicarrier (UFMC) with quadrature amplitude modulation (QAM) and phase shift keying (PSK) waveforms through Additive White Gaussian Noise channel (AWGN), Rayleigh fading channel and Rician channel. The objective of this paper is to enhance the performance of UFMC with reduced complexity through the new filtering approach for achieving optimal outcomes. The proposed scheme, incorporating Tukey filtering technique, demonstrates superior performance in reducing peak-to-average power ratio (PAPR) and improving bit error ratio (BER) compared to the original UFMC signal without necessitating additional power increments. Specifically, the UFMC system with Tukey filtering achieves a notable net gain of 5 dB. Simulation results demonstrate that utilizing various filter types in FBMC and UFMC systems, combined with QAM modulation, significantly reduces OOB emissions compared to conventional systems. In aspect to BER, Tukey window showed almost 10−6 at 15 dB SNR in UFMC which is better than FBMC.

Two dimensional parallel sequence spread spectrum for wireless communications

A novel two-dimensional parallel sequence spread spectrum (2D-PSSS) structure for the physical layer of wireless communication systems is introduced. The proposed 2D-PSSS system partitions a data block into two groups of bits, representing the two dimensions. The first dimension represents the selected code from a predefined set of Gold codes. While the second dimension determines a shift value applied to the chosen code. The shifted Gold code will represent the data block. By design, the 2D-PSSS system overcomes the challenge of inter-code interference encountered in conventional PSSS systems without introducing additional computational complexity. Moreover, the 2D-PSSS system offers reduced encoder computational complexity compared to PSSS systems, enhancing its suitability for a wide range of wireless communication applications. The performance of the 2D-PSSS system in terms of bit error rate has been evaluated in additive white Gaussian noise (AWGN) channel and under different fading channel conditions.

Differential Entropy-Based Fault-Detection Mechanism for Power-Constrained Networked Control Systems.

In this work, we consider the design of power-constrained networked control systems (NCSs) and a differential entropy-based fault-detection mechanism. For the NCS design of the control loop, we consider faults in the plant gain and unstable plant pole locations, either due to natural causes or malicious intent. Since the power-constrained approach utilized in the NCS design is a stationary approach, we then discuss the finite-time approximation of the power constraints for the relevant control loop signals. The network under study is formed by two additive white Gaussian noise (AWGN) channels located on the direct and feedback paths of the closed control loop. The finite-time approximation of the controller output signal allows us to estimate its differential entropy, which is used in our proposed fault-detection mechanism. After fault detection, we propose a fault-identification mechanism that is capable of correctly discriminating faults. Finally, we discuss the extension of the contributions developed here to future research directions, such as fault recovery and control resilience.