Rayleigh Channels Research Articles

Optimizing Spatial Complexity of the Hard Decision Decoder Based on Hash and Syndrome Decoding (HSDec)

In this article, we propose an optimized version of the Hard Decision Decoder based on Hash and Syndrome Decoding (HSDec) decoder, named Reduced Memory Space of HSDec (RMS-HSDec), which uses less memory space. In this article, we aim to reduce the spatial complexity of the HSDec decoding algorithm while preserving its error correction capabilities. Our methodology involves allocating only the essential memory space for correctable error patterns and optimizing the hashing mechanism to effectively handle potential collisions. While maintaining the integrity of error correction, this new method guarantees memory reduction rates of over 96 % for the BCH(63, 39, 9) code and over 84 % for the QR(47, 24, 11) code compared to HSDec. Simulations were conducted to evaluate the performance of RMS-HSDec on various BCH and QR codes over AWGN and Rayleigh channels. The results demonstrated significant memory reduction rates and coding gains ranging from 0.8 dB to 2.8 dB over the AWGN channel and from 14 dB to 32 dB over the Rayleigh channel, confirming the robustness of the algorithm under different channel conditions. Comparative analyses showed that RMS-HSDec maintains competitive performance with existing decoders while offering effective error correction. These findings confirm the robustness of the RMS-HSDec algorithm under different channel conditions. Overall, the proposed decoder proves to be an effective solution, optimizing memory usage without compromising error correction capabilities, making it ideal for high-density data applications and environments with limited memory resources.

MIMO Technology is Used to Improve the Security Capacity Stability of Rayleigh Wiretap Channel

This paper analyzes the security capacity when the Rayleigh channel codec is known, and studies the relationship between the transmit power, the estimation error and the security capacity difference. The results show that the increase of transmit power can make the security capacity difference tend to a stable value, which indicates that the influence of imperfect channel state information on the security capacity tends to be stable. By comparing the transmission power of SISO system and MIMO system, it is proved that MIMO system usually has higher transmission power under the same received power, so it is more suitable for improving the security capacity stability of Rayleigh channel.

Comparative Evaluation of NOMA and OFDMA over Multipath Fading Rayleigh Channels in Downlink SISO System

Comparative Evaluation of NOMA and OFDMA over Multipath Fading Rayleigh Channels in Downlink SISO System

Capacity analysis over fractional order Rayleigh fading channel under additive white generalized Gaussian noise

AbstractThis study presents an innovative fractional order Rayleigh fading model that can be used for channel capacity estimation in the presence of additive white generalized Gaussian noise. The proposed model assumes that the real and imaginary parts of channel gains are generalized Gaussian random variables, which makes it possible to consider the traditional Rayleigh fading model as a special case of fractional order Rayleigh fading. Compared to the Rayleigh model, the fractional order Rayleigh fading model offers a more precise representation of new real‐world communication, such as integrating terrestrial and underwater networks in sixth‐generation communications channels. The probability density function of the channel gain with additive white generalized Gaussian noise is analyzed here. Furthermore, the ergodic and outage capacities of the channel are determined, taking into account the assumption that the channel state information is only available at the receiver. The ergodic capacity is calculated using Meijer's G‐functions, resulting in a closed‐form expression. Numerical simulations demonstrate the superiority of the fractional order Rayleigh fading model over the Rayleigh channel. Moreover, the impact of ergodic and outage capacities under diverse channel characteristics is assessed.

An innovative method for improving the performance of unmanned aerial vehicle‐based generalized spatial modulation and non‐orthogonal multiple access in 6G networks

AbstractThe rapid evolution of wireless networks is leading to the emergence of 6G, promising unprecedented performance. We propose a nonorthogonal multiple access (NOMA)‐based multiuser generalized spatial modulation (GSM) system that allows various transmitting antennas. Integrating unmanned aerial vehicles (UAVs) with NOMA and GSM enhances overall network performance. This paper proposes optimizing UAV‐GSM‐NOMA systems in 6G using the butterfly optimization algorithm (BOA) in the two‐wave with diffuse power (TWDP) channel. Results are compared with those obtained from Nakagami and Rayleigh channels. Objectives include enhancing the sumrate, outage probability (OP), and energy efficiency (EE) in perfect and imperfect channel state information (CSI). Simulation results yield significant improvements in the TWDP channel compared with the Nakagami and Rayleigh channels. The OP is reduced, the sumrate is enhanced, and the EE is notably improved. These findings underscore the BOA's potential for 6G UAV‐GSM‐NOMA networks in challenging channel environments, ensuring reliable and efficient communication.

Secrecy Performance Analysis of Cooperative NOMA with AF and DF Protocol over Rayleigh Channel

Secrecy Performance Analysis of Cooperative NOMA with AF and DF Protocol over Rayleigh Channel

Reducing PAPR in OTFS 6G Waveforms Using Particle Swarm Optimization-Based PTS and SLM Techniques with 64, 256, and 512 Sub-Carriers in Rician and Rayleigh Channels

Reducing PAPR in OTFS 6G Waveforms Using Particle Swarm Optimization-Based PTS and SLM Techniques with 64, 256, and 512 Sub-Carriers in Rician and Rayleigh Channels

Reduction of OFDM PAPR Using a Combined Hadamard Transformation and Selective Mapping for Terrestrial DAB+ System under Rayleigh and AWGN Channel

Reduction of OFDM PAPR Using a Combined Hadamard Transformation and Selective Mapping for Terrestrial DAB+ System under Rayleigh and AWGN Channel

Performance Evaluation of mm-Wave Based System in GFDM- 5G and Beyond Channel Model with Dust Storm Scenario

Telecommunication has made tremendous improvements in terms of bandwidth, requiring good frequency location, high data rates, and wideband spectrum availability. One solution to these requirements is the millimeter wave frequency band of 30 GHz. However, communication in this band is facing new challenges due to climate effects such as humidity, dust storms, and temperature. For fifth-generation (5G) mobile networks and beyond, Generalized Frequency Division Multiplexing (GFDM) has been proposed as a compelling candidate to substitute Orthogonal Frequency Division Multiplexing (OFDM). The GFDM's ability to adapt the block size and type of pulse shaping filters enables it to meet various crucial requirements, including low latency, low Out-Of-Band(OOB) radiation, and high data rates. This paper evaluated the overall GFDM performance and investigated the Bit Error Rate (BER) across a Rayleigh channel under various weather conditions. The simulation results show that GFDM outperforms the current OFDM candidate system. Also, GFDM offers better resistance to the Rayleigh channel with moderate and heavy dust storms in terms of BER.

Assessment for operational assimilation of horizontal line of sight winds from the European Space Agency's Aeolus at the Met Office

AbstractThe European Space Agency's Aeolus satellite was launched in August 2018 and began delivering horizontal line‐of‐sight (HLOS) wind observations in early September 2018. In early 2019, the Met Office began assessing the suitability of the HLOS winds for operational assimilation into its global numerical weather prediction system. We performed a number of assimilation experiments to assess the impact of HLOS wind observations on our global forecasts. We have found that assimilating HLOS winds changes the zonal winds in the analysis fields predominantly in the Tropics and Southern Hemisphere, with the largest changes being in the upper troposphere and lower stratosphere. This has a positive impact on the accuracy of the global weather forecasts, with improvements in the root‐mean‐square error seen throughout the troposphere. Assimilation of Aeolus HLOS winds improves the standard deviation of the observation minus background (a 6 hr forecast) of almost all other observation types, suggesting that the numerical weather prediction model analysis is improved, which consequently improves the 6 hr forecast. In a set of short‐period observation denial experiments, we found that assimilating Aeolus has an impact similar in magnitude to assimilating surface winds from scatterometers. Assimilating winds from the Rayleigh channel has approximately three times the impact that assimilating HLOS winds from the Mie channel does. Both channels contribute a measureable improvement to the global forecast, and we therefore started operational assimilation of winds from the Mie channel in December 2020 and the Rayleigh channel operationally in May 2022.

Application of Q-learning algorithm based on heterogeneous sensor networks in higher education teaching management

With the rapid advancement of information technology and online technologies, it has become imperative for all colleges and universities to address the challenge of leveraging modern management methods to enhance management efficiency, level, and practices. In the realm of educational institution management, the learning management system stands as the cornerstone of contemporary campus management and the entire campus computer network. In this article, the Q-learning algorithm, specifically applied to a heterogeneous cellular network, is employed to investigate the issues pertaining to teaching management in colleges and universities.The design and implementation of the university teaching management system mainly uses heterogeneous cellular networks to establish a physical model of the Q-learning algorithm, and then in the Rayleigh channel, the coverage factor and the system rate expression are derived in a closed form, and in a closed form Derive the energy efficiency expression, and then optimize the density of the basic micro-station algorithm to maximize performance. In the process of system design, this paper uses an algorithm to analyze the current research status of university teaching management, then proposes the research purpose and subject content, and analyzes the university's teaching management function and potential future functional requirements. When designing the university learning management system, it describes in detail the overall design concept, key technologies, system structure, and operating system structure and system topology. This research mainly focuses on the research of campus information management and Q learning algorithm. Based on the cellular network, a large number of campus management cases were analyzed and data fitting at the same time, and a set of Q-learning algorithm teaching management system based on heterogeneous cellular network was designed.

CR2Net: A Neural Network-Based Classifier for Rician and Rayleigh Channels via Hankelization

CR2Net: A Neural Network-Based Classifier for Rician and Rayleigh Channels via Hankelization

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.

Encapsulation of Energy Efficient, Clustering Algorithm and Spectrum Sensing for Cognitive Radio Based Internet of Things Networks

Since the two decade the Internet of Things (IoT) plays an important role in the field of communication technology. Out of maximum of IoT devices are battery operated. So there should be energy efficient devices that can operate more functions with less power consumption. The main power constraints in the IoT devices are in the communication like spectrum selection, data transmission, etc. To perform communication between the two nodes the spectrum must be available. But as spectrums are limited and a lot of data is to be transmitted there may the issue of spectrum scarcity. The dynamic spectrum access is done using Cognitive Radio (CR) technology that can overcome spectrum scarcity issue. This paper gives the research work on energy efficient, clustering algorithm and spectrum sensing for CR based IoT networks in terms of the methods, merits, demerits and implementation. For efficiency in the spectrum sensing and energy consumption in 5G wireless communication network and data transfer between the IoT devices this study is essential. The biblometric analysis is shown by using VOSviewer to visualize the bibliometric information and the result as an analysis of ROC curve for Rayleigh and Rician channel is plotted using Matlab.

Dynamic Spectrum Sensing For 5G Cognitive Radio Networks Using Optimization Technique

With increasing development of 5G technology, the rapid growth of various technologies and the growth of various wireless devices, demand for wireless spectrum becomes more urgent. Wireless communication technologies have been advancing rapidly, leading to the emergence of 5G communication systems .Spectrum sensing is the key model utilized to access the spectrum dynamically in CRN. Various researchers are done in spectrum sensing scenario and different methods are designed to perform the task of spectrum resource sharing. Most of the methods design a decision statistics for identifying the signal by analyzing the features of noise and signals. One promising approach to address the challenges of spectrum sensing in cognitive radio networks for 5G communication is the integration of deep learning with hybrid optimization techniques. By combining the power of deep learning algorithms with optimization methods, it becomes possible to improve the efficiency and accuracy of spectrum sensing in dynamic and diverse communication scenarios. One of the key advantages of MIMO-based spectrum sensing is its ability to exploit the spatial diversity inherent in the environment. By using multiple antennas at both the transmitter and receiver, MIMO systems can distinguish between signals arriving from different directions, thereby improving the accuracy of spectrum sensing. Moreover, MIMO technology also enables the cognitive radio network to utilize the available spectrum more efficiently. With the ability to establish multiple parallel communication links, MIMO-based cognitive radio networks can achieve higher data rates and improved spectral efficiency, especially in dynamic and challenging radio environments. Research in this field is focused on further enhancing the performance of MIMO-based spectrum sensing in cognitive radio networks through advanced signal processing algorithms and machine learning technique Spectrum sensing detect existence of primary users (PUs) and it becomes a main research topic of CRN in industry and academic domain. This research developed a new framework based on algorithm to progress the mechanism of spectrum sensing in the CRN by detecting the availability of free channel. The signal components are extracted from the received signal and thereby spectrum availability of detected through fusion center using proposed Feedback Artificial Optimization Algorithm-based Deep Q network. However, Simulation results show that the proposed multiple-input-multiple-output(MIMO) spectrum sensing method achieves good performance Cognitive Radion Network attains maximum probability of detection and minimum probability of false alarm as 70%, and 38% for Rayleigh channel.

A hybrid detection algorithm for 5G OTFS waveform for 64 and 256 QAM with Rayleigh and Rician channels

Abstract Signal detection in orthogonal time frequency space modulation is one of the critical aspects for enhancing the throughput of the beyond fifth-generation framework, especially in challenging environments characterized by high mobility and multipath propagation. In this work, we proposed a hybrid detection algorithm by combining zero-forcing equalization (ZFE) and minimum square error equalization (MMSE), also known as ZFE–MMSE, with Rician and Rayleigh channels for 64 and 256 quadrature amplitude modulation. The combination of ZFE and MMSE allows for a more comprehensive approach to equalization. ZFE addresses channel-induced distortions, while MMSE tackles the impact of noise. Together, they enhance the overall performance of the equalization process, resulting in improved signal detection accuracy. The analysis and comparison of the simulation parameters with traditional detection systems include bit error rate, power spectral density (PSD), and complexity. The projected algorithms achieve a signal-to-noise ratio and a PSD gain of 2 dB and −800, respectively, outperforming the traditional detection techniques.

Non Orthogonal Multiple Access (NOMA) Using a Nonlinear Energy Harvesting Model

This paper derives and optimizes the throughput of NOMA with nonlinear energy harvesting. The Base Station (BS) harvests energy from the received Radio Frequency signal. Then, the BS uses the nonlinear harvested power to diffuse packets to N users. We suggest to optimize harvesting time and the powers of users to optimize the data rate. The optimization of NOMA powers and the harvesting process were not yet performed with a non linear energy harvesting model. The study is performed for Rayleigh channels in the presence of nonlinear energy harvesting model. Furthermore, the theoretical results were confirmed using MATLAB computer simulations.

Improving the latency for 5G/B5G based smart healthcare connectivity in rural area

Smart hospitals are poised to greatly enhance life quality by offering persistent health monitoring capabilities. Remote healthcare and surgery, which are highly dependent on low latency, have seen a transformative improvement with the advent of 5G technology. This has facilitated a new breed of healthcare services, including monitoring and remote surgical procedures. The enhanced features of 5G, such as Enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC), have enabled the development of advanced healthcare systems. These systems reduce the need for direct patient contact in hospitals, which is especially pertinent as 5G becomes more widespread. This research presents novel hybrid detection algorithms, specifically QR decomposition with M-algorithm maximum likelihood-minimum mean square error (QRM-MLD-MMSE) and QRM-MLD-ZF (zero forcing), for use in Massive MIMO (M-MIMO) technology. These methods aim to decrease the latency in MIMO-based Non-Orthogonal Multiple Access (NOMA) waveforms while ensuring optimal bit error rate (BER) performance. We conducted simulations to evaluate parameters like BER and power spectral density (PSD) over Rician and Rayleigh channels using both the proposed hybrid and standard algorithms. The study concludes that our hybrid algorithms significantly enhance BER and PSD with lower complexity, marking a substantial improvement in 5G communication for smart healthcare applications.

Coherence Bandwidth of Rice Channels for Millimeter Wave and Sub-Terahertz Applications

6G research in the millimeter wave and sub-Terahertz domain is targeting very wideband systems with significantly higher data throughput than for 5G systems. Multipath propagation under shadowing conditions is affecting radio propagation, where multipath propagation results in frequency-selective fading, which is characterized by the coherence bandwidth and the time variation by the coherence time. In these frequency ranges shadowing can be overcome by additional means in the network deployment such as reflectors, RIS arrays or repeaters, which provide at the receiver a channel impulse response with a strong component (Rice type channel). Coherence bandwidth and coherence time are well-known for Rayleigh channels. However, both parameters for Rice channels versus the Rice factor K′ are not available. This paper is investigating the coherence bandwidth and time for Rice channels based on an approximative approach for the fading statistics. With the proposed correlation criterion, the coherence bandwidth and time tend to infinity from a Rice factor around K′≥4=ˆ6 dB. These relations are provided by approximative functions for K′≥0 starting at the Rayleigh channel.

Performance analysis of high-spectral-resolution lidar with/without laser seeding technique for measuring aerosol optical properties

High-spectral-resolution lidar (HSRL) is a powerful tool for aerosol measurements. With/without laser seeding technique in the transmitted laser, the HSRL can be distinguished as the single-longitudinal-mode (SLM) HSRL or the multi-longitudinal-mode (MLM) HSRL, and the Mach-Zehnder interferometer (MZI) with periodic transmittance function can be used as the spectral discriminator in both the SLM HSRL and MLM HSRL. To in-depth knowledge of the respective advantages of the SLM HSRL and MLM HSRL for measuring aerosol optical properties, the working principle, optimal parameter setting, and detection performance of the SLM HSRL and MLM HSRL are analyzed and discussed in detail, respectively. The working principle of the SLM HSRL and MLM HSRL indicate that the effective transmittance of MZI is the important parameter of data retrieval, the main source of retrieval uncertainties, and the key factor of MZI optical path difference (OPD) settings. To ensure that the MZI can achieve the preferable separation for aerosol Mie scattering signals and molecular Rayleigh scattering signals, the optimal OPDs of MZI are set at 165 mm and 1000 mm in the SLM HSRL and MLM HSRL from the aspects of the effective transmittance of MZI and the spectral discrimination ratio (SDR). Besides, to analyze the influence of frequency difference and divergence angle for the detection performance of HSRL, the effective transmittance of MZI and SDR are simulated and the results show that the MLM HSRL has higher requirements for the environmental parameters and the echo beam collimation than the SLM HSRL. Moreover, the HSRLs with SLM and MLM transmitted lasers are constructed in Xi'an for measuring aerosol optical properties. The preliminary measurement results show that the range square corrected signal (RSCS) of Rayleigh channel is smaller than that of Mie channel in both the SLM HSRL and MLM HSRL, while the difference between RSCS of Rayleigh channel and RSCS of Mie channel in the SLM HSRL is larger than that in the MLM HSRL, and the detection range of the SLM HSRL is lower than that of the MLM HSRL.