Better Bit Error Rate Research Articles

Performance Analysis of Filtered OFDM using MLE for Wireless Communication Networks

Introduction: OFDM has evolved as an effective modulation format for 4G mobile network technologies, Long-Term Evolution, and Worldwide Interoperability for Microwave Access. OFDM is the modulation technique adopted for communication standards such as DSL, wireless LAN, DVB, and DAB. However, because CP-OFDM has considerable out-of-band emission that may interfere with transmissions in adjacent bands and applies a single set of parameters to the whole band to fulfill a given service, it is unable to accommodate the diversity of services. The objective of the research is to develop a novel waveform with better adaptability than CP-OFDM that employs filters to increase spectrum containment. In this view, an FIR filter that uses the Blackman window function to lessen the OOBE is proposed in this manuscript. Filtered OFDM is sensitive to carrier frequency offset (CFO). CFO increases the Inter-Carrier Interference (ICI) in F-OFDM systems. However, research work that combines the CFO compensation technique with filtered OFDM has not been listed in the literature so far. Methods: In this paper, Maximum likelihood estimation is used to cancel the ICI caused by the CFO. The high PAPR of filtered OFDM is one of its drawbacks. The amplitude clipping method is used to reduce the PAPR. The distortion caused by amplitude clipping is prevented by filters used in the FOFDM system. Highlights: • A novel waveform addressing OOBE issues in OFDM is developed for 4G wireless communication networks. • An innovative solution using MLE is proposed to address the challenges faced by the filtered OFDM system due to the CFO. • Article addresses the high PAPR problem of filtered OFDM. Results: The performance of filtered OFDM with amplitude clipping is analyzed in terms of BER, PSD, and PAPR over the AWGN channel. Conclusion: Simulation results show that, when compared to the traditional OFDM system, such a combined method effectively suppresses PAPR while maintaining good BER (Bit Error Rate) and OOBE performance.

Exploring FSO link performance in varied atmospheric conditions to optimize 5G communication with a polarized quasi-diffuse transmitter

Abstract Free space optical (FSO) communication is an innovative technology that holds immense promise for numerous applications thanks to its high data transmission rates, rapid scalability, cost-effectiveness, superior security, and comprehensive capacity access techniques for Gbps data transmission. FSO communication relies on the Earth’s atmosphere as the medium, which introduces atmospheric disturbances that have driven the development of spatial diversity techniques aimed at enhancing the technology’s performance. Our proposed system employs a polarized quasi-diffused system with a fork as a spatial diversity scheme, which eliminates the need for multiple transmitters. We have developed a model that integrates both simulation designs to achieve optimal results. The proposed model has demonstrated excellent performance under various atmospheric turbulences, including rain, fog, and haze, exhibiting a very high maximum quality factor, improved received power, and better bit error rate (BER). Finally, we have obtained, analyzed, and extensively discussed the simulation results to provide a comprehensive understanding of the proposed model’s potential benefits. Our simulations show a maximum quality factor of 23 compared to existing models in much better, a 34 % increase in received power, and a 31 % decrease in BER compared to existing models. These results highlight the potential benefits of the proposed model for FSO communication systems.

Polar-Coded Cooperation With Optimized Relay Selection in Multi-Satellite and Wireless Integrated Systems

Optimized polar-coded cooperation with an approximate prior probability-based threshold decision is proposed to improve the reliability and complexity in selective decode-and-forward (SDF) cooperation of multiple satellite constellation systems. First, an SDF scheme with polar coding is adopted in cooperative communications for efficient code construction and relay forwarding. Second, in the logarithmic belief propagation (BP) polar decoding, the variable iterative threshold is derived with independent and variable signal-to-noise ratio (SNR)-based approximate prior probability. This threshold reduces complexity by eliminating active nodes with high reliability in each decoding iteration. Third, the information detection factor is introduced to evaluate the accuracy of decoded bits, thereby limiting the average decoding iterations to improve decoding efficiency. Simulation results show that the proposed polar-coded SDF cooperation obtains 1.5 dB performance gain at a bit error rate (BER) of 10-3 compared with that of existing LDPC-related schemes. The complexity of the optimized logarithmic BP decoding is reduced by 25%–50% compared with that of the traditional BP decoding. Therefore, the proposed scheme has good BER performance and low complexity in cooperative communications of multi-satellite and wireless integrated systems.

Low Complexity Resource Allocation in Frequency Domain Non-Orthogonal Multiple Access

This paper proposes low complexity resource allocation in frequency domain non-orthogonal multiple access where many devices access with a base station. The number of the devices is assumed to be more than that of the resource for network capacity enhancement, which is demanded in massive machine type communications (mMTC). This paper proposes two types of resource allocation techniques, all of which are based on the MIN-MAX approach. One of them seeks for nicer resource allocation with only channel gains. The other technique applies the message passing algorithm (MPA) for better resource allocation. The proposed resource allocation techniques are evaluated by computer simulation in frequency domain non-orthogonal multiple access. The proposed technique with the MPA achieves the best bit error rate (BER) performance in the proposed techniques. However, the computational complexity of the proposed techniques with channel gains is much smaller than that of the proposed technique with the MPA, whereas the BER performance of the proposed techniques with channel gains is only about 0.1 dB inferior to that with the MPA in the multiple access with the overloading ratio of 1.5 at the BER of 10-4. They attain the gain of about 10 dB at the BER of 10-4 in the multiple access with the overloading ration of 2.0. Their complexity is 10-16 as small as the conventional technique.

Video perception enhancement using effective encoding optimization in future generation wireless network

<span>The cumulative effects of network transmission link imperfections and real-time limitations of video data result in multiple challenges for video transmission in massive millimeter wave (mmwave) network. The challenges, together with the increasing expectations of users for good-quality videos, further extend the complexity particularly in dense areas. To address the issues this work proposes perceptual quality aware video encoding (PQAVE) scheme in two phases: in phase 1 an effective perceptual quality encoding method leveraging low-rank approximation to reduce overall video size is done. In phase 2, a novel bitstream optimization technique is introduced to improve perceptual quality of videos. Experiment are conducted using standard video dataset show the proposed PQAVE model attain better bit error rate (BER), symbol error rate (SER), error vector magnitude (EVM), and coding gain in comparison with existing perceptual video encoding scheme.</span>

Temporal Convolutional Network-Based Signal Detection for Magnetotactic Bacteria Communication System.

Molecular communication (MC) aims to use signaling molecules as information carriers to achieve communication between biological entities. However, MC systems severely suffer from inter symbol interference (ISI) and external noise, making it virtually difficult to obtain accurate mathematical models. Specifically, the mathematically intractable channel state information (CSI) of MC motivates the deep learning (DL) based signal detection methods. In this paper, a modified temporal convolutional network (TCN) is proposed for signal detection for a special MC communication system which uses magnetotactic bacteria (MTB) as information carriers. Results show that the TCN-based detector demonstrates the best overall performance. In particular, it achieves better bit error rate (BER) performance than sub-optimal maximum a posteriori (MAP) and deep neural network (DNN) based detectors. However, it behaves similarly to the bidirectional long short term memory (BiLSTM) based detector that has been previously proposed and performs worse than the optimal MAP detector. When both BER performance and computational complexity are taken into account, the proposed TCN-based detector outperforms BiLSTM-based detectors. Furthermore, in terms of robustness evaluation, the proposed TCN-based detector outperforms all other DL-based detectors.

Improved Frequency Domain Turbo Equalization with Expectation Propagation Interference Cancellation in Underwater Acoustic Communications.

This paper proposes an improved frequency domain turbo equalization (IFDTE) with iterative channel estimation and feedback to achieve both a good performance and low complexity in underwater acoustic communications (UWACs). A selective zero-attracting (SZA) improved proportionate normal least mean square (SZA-IPNLMS) algorithm is adopted by utilizing the sparsity of the UWAC channel to estimate it using a training sequence. Simultaneously, a set-membership (SM) SZA differential IPNLMS (SM SZA-DIPNLMS) with variable step size is adopted to estimate the channel status information (CSI) in the iterative channel estimation with soft feedback. In this way, the computational complexity for iterative channel estimation is reduced effectively with minimal performance loss. Different from traditional schemes in UWACs, an IFDTE with expectation propagation (EP) interference cancellation is adopted to estimate the a posteriori probability of transmitted symbols iteratively. A bidirectional IFDTE with the EP interference cancellation is proposed to further accelerate the convergence. THe simulation results show that the proposed channel estimation obtains 1.9 and 0.5 dB performance gains, when compared with those of the IPNLMS and the l0-IPNLMS at a bit error rate (BER) of 10-3. The proposed channel estimation also effectively reduces the unnecessary updating of the coefficients of the UWAC channel. Compared with traditional time-domain turbo equalization and FDTE in UWACs, the IFDTE obtains 0.5 and 1 dB gains in the environment of SPACE'08 and it obtains 0.5 and 0.4 dB gains in the environment of MACE'04 at a BER of 10-3. Therefore, the proposed scheme obtains a good BER performance and low complexity and it is suitable for efficient use in UWACs.

A 3.84-Gbit/s FBMC-NOMA-based VLC transmission system using DAC-based pre-equalization and DHT precoding technique

The transmission data rate of visible light communication (VLC) systems is mainly limited by the modulation bandwidth of light-emitting diodes (LEDs). Pre-equalization (PE) techniques in combination with advanced modulation formats have been employed to enhance the data rate of LED-based VLC systems. In this paper, we experimentally demonstrated a high spectral-efficiency filter bank multi-carrier (FBMC) and non-orthogonal multiple access (NOMA)-based VLC transmission system using digital-to-analog converter-based PE (DAC-PE) and discrete Hartley transform (DHT) precoding technique. Two PE techniques, i.e., DAC-PE and digital pre-equalization (DPE), are comparatively investigated in both orthogonal frequency-division multiplexing (OFDM)-NOMA-based VLC systems and FBMC-NOMA-based VLC systems. The results exhibit that, with the help of DHT precoding, the DAC-PE scheme outperforms the DPE scheme at the optimal power ratios (PRs). Besides, the FBMC-NOMA scheme can provide better bit error rate (BER) performance and higher data rate than OFDM-NOMA. At the optimal PR of 6 dB, the FBMC-NOMA signal with a record net data rate of 3.84 Gbit/s after 2.3-m free-space link transmission can be achieved with the BER below 3.8 × 10−3.

A Reliable and Intelligent Deep Learning Based Demodulator for M-Ary Code Shifted Differential Chaos Shift Keying System With Power Allocation

In high-speed railway systems, channel conditions are dramatically changing, which brings great challenges to information transmissions. Our objective is to improve the reliability performances by utilizing the deep learning (DL) scheme to intelligently extract the features of signals to combat the complex dynamically changing channel conditions. In this paper, we propose a DL-aided demodulation scheme for the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> -ary code shifted differential chaos shift keying system with power allocation (PA-GCS-MDCSK) to enhance reliability performance. In this design, the deep neural network (DNN) adopts fully-connected layers (FCLs) to conduct the joint de-spreading of Walsh codes and chaotic demodulations. Meanwhile, the long short-term memory (LSTM) unit with the residual structure is constructed to extract the correlation between the chaotic sequences, thus the interferences induced by real-valued chaotic sequences can be suppressed, thereby improving the reliability performance. Then the computational complexity is analyzed and compared with benchmark schemes. Simulation results over both additive white Gaussian noise (AWGN), fading, and railway channels validate that the proposed design can achieve better bit error rate (BER) and robustness performances than benchmark schemes.

Investigation of the performance of multi-input multi-output detectors based on deep learning in non-Gaussian environments

&lt;span lang="EN-US"&gt;The next generation of wireless cellular communication networks must be energy efficient, extremely reliable, and have low latency, leading to the necessity of using algorithms based on deep neural networks (DNN) which have better bit error rate (BER) or symbol error rate (SER) performance than traditional complex multi-antenna or multi-input multi-output (MIMO) detectors. This paper examines deep neural networks and deep iterative detectors such as OAMP-Net based on information theory criteria such as maximum correntropy criterion (MCC) for the implementation of MIMO detectors in non-Gaussian environments, and the results illustrate that the proposed method has better BER or SER performance.&lt;/span&gt;

An In-Phase/Quadrature Index Modulation-Aided Spread Spectrum Communication System for Underwater Acoustic Communication

In a multiple-sequences-spread-spectrum (MSSS) communication system, the transmitted signal is made up of superimposed cyclic shift sequences, each sequence carrying a symbol, so the data rate is inceased. In this context, we propose an in-phase/quadrature index modulation-aided MSSS system (MSSS-I/Q-IM), which achieves higher data rate and better bit-error-rate (BER) performance. The new system maps the additional bits to the cyclic shift length of the superimposed sequences of I/Q branches. The sequences in two branches carry the real and imaginary parts of the M-ary phase-shift-keying (MPSK) symbols, respectively. We derive the theoretical BER of the MSSS-I/Q-IM system over an additive white Gaussian noise (AWGN) channel. Then, the simulation experiments of the proposed system and MSSS system over an underwater acoustic channel are analyzed and compared. Finally, field experiments are carried out in the pool environment. The experiment results show that the proposed scheme can achieve higher data rate or better BER performance via adjusting the IM parameter. This is important for the time-variant underwater acoustic transmission environments.

An enhanced 2-D color space diversity using RGB-LED overlapping for optical camera communication

In this paper, an enhanced two-dimension (2-D) color space diversity technique using red, green, and blue light emitting diode (RGB LED) overlapping is proposed and investigated experimentally to improve the system reliability for optical camera communication (OCC). The transmitter adopts an 8-color shift keying (8-CSK) modulation scheme with two RGB LED overlapping. The receiver uses a camera to form a multi-input single-output system to improve capacity. Different mapping methods are proposed and compared in 2-D YCbCr and CIElab color space to avoid the influence of brightness in conventional 3-D RGB space. Besides, clustering-based demapping is applied in the OCC system to transfer the color information into a data stream. The experimental results show that the mapping scheme with the maximum Euclidean distance in 2-D YCbCr color space has the best bit error rate (BER) performance. Compared with the conventional 3-D RGB color space, the proposed enhanced 2-D YCbCr color space diversity has a higher resolution to signal, which can realize 1.46 dB Q-factor improvement at an illumination of 660 lux. In addition, it can achieve a net data rate of 11.52 kb/s and maintain a 7% forward error correction (FEC) requirement even under low illumination. It is verified that the proposed scheme is a potential application for capacity and performance improvement.

Joint RIS Grouping Design Assisted Generalized Quadrature Reflection Modulation

In this paper, a novel joint reconfigurable intelligent surface (RIS) grouping design assisted generalized quadrature reflection modulation (JGD-GQRM) scheme is proposed for a single radio frequency (RF) multiple-input multiple-output (MIMO) system. In JGD-GQRM, a limited number of RIS elements are spatially grouped, and the remaining reflection patterns are utilized for joint mapping to improve the reliability of the transmission. Moreover, it maps additional information bits by full reflection passive beamforming to improve the system's spectral efficiency (SE). In addition to the optimal maximum likelihood (ML) detector that has high computational complexity, a low-complexity sequential greedy detection (SGD) for JGD-GQRM is proposed. Simulation results show that the proposed scheme can achieve better bit error rate (BER) performance than the existing reflection modulation.

A Simple Neural-Network-Based Decoder for Short Binary Linear Block Codes

The conventional soft decision decoding (SDD) methods require various hard decision decoders (HDDs) based on different codes or re-manipulate the generator matrix by the complicated Gaussian elimination technique according to the bit reliability. This paper presents a general multi-class neural network (NN)-based decoder for the short linear block codes, where no HDD and Gaussian elimination are required once the NN is constructed. This network architecture performs multi-classification to select the messages with high occurrence probabilities and chooses the best codeword on a maximum likelihood basis. Simulation results show that the developed approach outperforms the existing deep neural network (DNN)-based decoders in terms of decoding time and bit error rate (BER). The error-correcting performance is also superior to the conventional Chase-II algorithm and is close to the ordered statistics decoding (OSD) in most cases. For Bose–Chaudhuri–Hocquenghem (BCH) codes, the SNR is improved by 1dB to 4dB as the BER is 10−4. For the (23, 12) quadratic residue (QR) code, the SNR is improved by 2dB when the BER is 10−3. The developed NN-based decoder is quite general and applicable to various short linear block codes with good BER performance.

Curve Fitting Based Piecewise Nonlinear Companding Scheme for PAPR Reduction in OFDM Systems

Peak-to-average power ratio (PAPR) is an important issue for orthogonal frequency division multiplexing (OFDM) systems. In this letter, we derive a new piecewise nonlinear companding scheme for reducing PAPR in OFDM systems. Compared with current state-of-art companding scheme, the new companding scheme improves the power spectral density (PSD) performance. The companding function is derived according to the cumulative distribution function (CDF) of companded OFDM signals’ amplitudes, which is fitted by using several piecewise linear functions to approximate the original Rayleigh distribution CDF. The constraint optimization problem is formulated, and parameter selection method is provided. Simulation results verify that under precondition of similar PAPR reduction levels, the proposed companding scheme could achieve better bit error rate (BER) and PSD performance compared with other typical companding schemes.

Sparse Code Multiple Access Scheme Based on Variational Learning

Sparse code multiple access (SCMA) technology has been widely studied thanks to its outstanding overload performance, which provides greater device access on limited time-frequency resources. We propose a variational learning based end-to-end SCMA network model termed as V-SCMA. In our model, SCMA codebooks are generated by a deep neural network (DNN) encoder. Motivated by the idea of variational learning, we derive the posterior probability of SCMA codeword send by each user from the point view of binary coding using the variational method. Then, we design an SCMA decoding network to learn this process of approaching the real posterior probability. The SCMA decoding network designed by us is a truncated recurrent neural network, which is simpler than other networks. In addition, a novel loss function is proposed to optimize V-SCMA. Compared with previous works, the new loss function is a tighter variational lower bound which improves the BER performance. Simulation results show that the proposed V-SCMA offers a better bit error rate (BER) performance and a lower computational complexity than conventional schemes.

Adaptive Detector for FDA-Based Ambient Backscatter Communications

Ambient backscatter communication (AmBC), whose passive tags transmit information to readers through radio frequency (RF) signals in the air, has attracted much attention due to its promising prospects in green internet of things (IoTs). However, AmBC detection has faced a new challenge at the reader because the received signal is mainly a hybrid signal from direct link and backscatter link, which makes it difficult to detect symbols of the backscatter tag. To address this problem, in this paper, frequency diverse array (FDA) is utilized to transmit time-variant ambient signal, which can separate the two link signals received by the reader. We propose an adaptive dual-threshold detector by employing the time-variant characteristic of FDA RF signal, which is based on the position of the boundary backscatter tag defined. Specifically, the closed form expressions for maximum likelihood (ML) threshold and adaptive thresholds are derived, respectively. Furthermore, the computational complexities are analyzed. Finally, numerical results are presented to show that the proposed adaptive dual-threshold detector achieves better bit error rate (BER) performance than the conventional ML detector.

PAPR Reduction Techniques and Their BIT Error Rate Measurement at OFDM in LTE System

Orthogonal frequency division multiplexing (OFDM) has become an indispensable part of waveform generation in wideband digital communication since its first appearance in digital audio broadcasting (DAB)and it is indeed in use. These descriptions are simplified version of the detailed descriptions provided by 3gpp. It is a superior technology for the high-speed data rate of wire-line and wireless communication systems. The OFDM has many advantages over other techniques such as its high capacity and immunity against multipath fading channels. However ,one of the main drawbacks of the OFDM system is the high-peak-to-average power ratio (PAPR) that leads the system to produce in-band distortion and out-of-band radiation because of the non-linearity and reduces its efficiency is the distortion of the signal caused at the High Power Amplifier (HPA) of a transmitter . Therefore, it is highly desirable to reduce the PAPR of an OFDM signal. For this, numerous techniques have been proposed to overcome the PAPR problem such as i) selective mapping(SLM) ii) partial transmit sequence (PTS), iii) clipping, iv) clipping and filtering. In this paper, the PTS technique was analytically reviewed as one of the important methods to reduce the high PAPR problem. Simulations are used to analyze the efficiency of the techniques used which signifies OFDM to be providing much better PAPR reduction and a better Bit Error Rate (BER) . From simulation results clipping method shows good PAPR reduction with significant amount of BER degradation. Clipping and filtering method shows slight increase in PAPR with small degradation in BER performance than Clipping method and both methods are computationally less complex. PTS provides good PAPR reduction with high computational complexity.

Synthesis of a GS-16QAM signal for a simplified optical ISB system and direct detection with the K-means clustering algorithm.

An independent sideband (ISB) is a promising scheme for short-reach and metro applications because of its high spectral efficiency, low complexity, and tolerance to chromatic dispersion. Here, we develop a signal synthesis scheme to further reduce the complexity of ISB direct-detection (DD) systems. Two lower-order quadrature amplitude modulation (QAM) sideband signals are generated digitally, then the left sideband (LSB) and right sideband (RSB) are modulated with regular quadrature phase shift keying (QPSK) and geometrically shaped shifted QPSK (GS-S-QPSK), respectively. Then, the two independent sideband signals are received in a single photodiode to synthesize a GS-16QAM signal. The LSB and RSB signals can be separated and demodulated by a digital signal process (DSP) instead of using two optical bandpass filters. The proposed scheme significantly reduces the complexity of the ISB-DD receiver, thus saving system cost. Three different GS-S-QPSK signals are evaluated, with the square GS-S-QPSK achieving the best bit error rate (BER) with its optimal shaping factor. Considering signal-signal beating interference, a sub-blind K-means clustering algorithm is used to improve the BER performance, and the results indicate that it can achieve a large received optical power (ROP) gain at a threshold of 3.8 × 10-3.

Index Modulation Pattern Design for Non-Orthogonal Multicarrier Signal Waveforms

Spectral efficiency improvement is a key focus in most wireless communication systems and achieved by various means such as using large antenna arrays and/or advanced modulation schemes and signal formats. This work proposes to further improve spectral efficiency through combining non-orthogonal spectrally efficient frequency division multiplexing (SEFDM) systems with index modulation (IM), which can efficiently make use of the indices of activated subcarriers as communication information. Recent research has verified that IM may be used with SEFDM to alleviate inter-carrier interference (ICI) and improve error performance. This work proposes new SEFDM signal formats based on novel activation pattern designs, which limit the locations of activated subcarriers and enable a variable number of activated subcarriers in each SEFDM subblock. SEFDM-IM system designs are developed by jointly considering activation patterns, modulation schemes and signal waveform formats, with a set of solutions evaluated under different spectral efficiency scenarios. Detailed modelling of coded systems and simulation studies reveal that the proposed designs not only lead to better bit error rate (BER) but also lower peak-to-average power ratio (PAPR) and reduced computational complexity relative to other reported index-modulated systems.