Performance Of Wireless Systems Research Articles

Enhancing MPTCP performance in wireless networks with PRS-MPTCP

In recent years, there has been a significant increasing demand for wireless networks, particularly mobile communication. Additionally, smart devices like mobile phones and tablets are able to use multiple interfaces simultaneously. In this regard, the concept of Multipath TCP (MPTCP) has been introduced, enabling the utilization of multiple interfaces for concurrent communication. However, packet loss and subflow heterogeneity, especially in wireless networks, cause an increase in Out-of-Order (OfO) packets at the receiver node, which leads to a decrease in the total MPTCP throughput. To address these performance-related challenges, numerous schedulers have been proposed. However, most existing methods have primarily focused on improving performance without adequately considering the impact of packet loss. This research paper provides a comprehensive overview of MPTCP schedulers. Subsequently, we propose a Practical and Robust Scheduler for MPTCP (PRS-MPTCP) with the specific aim of minimizing OfO packets to improve MPTCP performance in wireless systems. The PRS-MPTCP scheduler takes into account various characteristics of each subflow, including RTT, CWND, and the number of packet losses, to effectively decide which packets should be assigned to which subflow. By using Mininet-WiFi emulation, fair comparisons between PRS-MPTCP and the state-of-the-art schedulers have been conducted, considering throughput, the number of OfO packets, and retransmission rates as performance metrics. The evaluation results reveal the profound impact of selected parameters on the behavior of the schedulers and the overall performance of MPTCP. Ultimately, the results demonstrate that PRS-MPTCP guarantees acceptable throughput and achieves lower retransmission rates and fewer OfO packets compared to other methods. In the PRS-MPTCP, the number of OfO packets has decreased by 38 %, 37 %, 45 %, and 44 % compared to BLEST, ECF, RR, and the Default scheduler, respectively.

MDE and LLM Synergy for Network Experimentation: Case Analysis of Wireless System Performance in Beaulieu-Xie Fading and κ-µ Co-Channel Interference Environment with Diversity Combining.

Channel modeling is a first step towards the successful projecting of any wireless communication system. Hence, in this paper, we analyze the performance at the output of a multi-branch selection combining (SC) diversity receiver in a wireless environment that has been distracted by fading and co-channel interference (CCI), whereby the fading is modelled by newer Beaulieu-Xie (BX) distribution, and the CCI is modelled by the κ-µ distribution. The BX distribution provides the ability to include in consideration any number of line-of-sight (LOS) useful signal components and non-LOS (NLOS) useful signal components. This distribution contains characteristics of some other fading models thanks to its flexible fading parameters, which also applies to the κ-µ distribution. We derived here the expressions for the probability density function (PDF) and cumulative distribution function (CDF) for the output signal-to-co-channel interference ratio (SIR). After that, other performances are obtained, namely: outage probability (Pout), channel capacity (CC), moment-generating function (MGF), average bit error probability (ABEP), level crossing rate (LCR), and average fade duration (AFD). Numerical results are presented in several graphs versus the SIR for different values of fading and CCI parameters, as well as the number of input branches in the SC receiver. Then, the impact of parameters on all performance is checked. From our numerical results, it is possible to directly obtain the performance for all derived and displayed quantities for cases of previously known distributions of fading and CCI by inserting the appropriate parameter values. In the second part of the paper, a workflow for automated network experimentation relying on the synergy of Large Language Models (LLMs) and model-driven engineering (MDE) is presented, while the previously derived expressions are used for evaluation. Due to the aforementioned, the biggest value of the obtained results is the applicability to the cases of a large number of other distributions for fading and CCI by replacing the corresponding parameters in the formulas for the respective performances.

Full/half-duplex unmanned aerial vehicles assisted wireless systems: Performance analysis and optimization

In this paper, we explore the utilization of both full-duplex (FD) and half-duplex (HD) transmission modes on unmanned aerial vehicles (UAVs) to enhance wireless system performance. We consider two practical scenarios: one without a direct transmitter-user link and the other with such a link. For both cases, we derive mathematical expressions of outage probabilities (OPs) and throughputs of FD-UAV and HD-UAV systems, employing a realistic channel model aligned with the fifth and beyond generations (5G-B5G) standards. In cases where imperfect self-interference cancellation (SIC) occurs in FD-UAV systems, we introduce an optimal power allocation approach to enhance system performance. Numerical results underscore the benefits of cooperative communications, particularly when combining the direct link with the UAV link at the user, leading to an overall enhancement in system performance. Furthermore, we conduct a comprehensive analysis of various system parameters, including predefined rates, residual self-interference (RSI) levels, high carrier frequencies of Wi-Fi networks, and high altitudes of UAVs. The impact of RSI is particularly notable, and the proposed optimal power allocation approach significantly improves system performance in such cases. Specifically, the introduced scheme helps avoid error floors in regions of high transmit power, enabling throughputs to reach desired targets in FD-UAV systems. Crucially, the optimal power value is considerably lower than the traditional value often used without optimal power allocation, extending the operational duration of FD-UAV. Finally, to validate the derived mathematical expressions and affirm the effectiveness of the proposed approaches, we conduct Monte-Carlo simulations.

Bandwidth‐enhanced horizontally polarized omnidirectional slot antenna based on single‐ridge trapezoidal waveguide

AbstractThis letter presents a Ku‐band horizontally polarized (HP) omnidirectional antenna based on single‐ridge trapezoidal waveguide (STW). Four groups of longitudinal slots are etched on a pair of back‐to‐back arranged STWs to achieve the HP omnidirectional radiation performance. The number and distribution of each radiation slot group are optimized to reduce the gain variation. An out‐of‐phase stripline power divider cascaded with two probe‐based vertical power dividers is used to excite all radiating slots in a series‐parallel hybrid structure, which helps to enhance the boresight radiation bandwidth. For demonstration, a prototype covering 14.5 to 15.5 GHz is designed, fabricated, and measured. Experimental results show that the good impedance matching (|S11|←14 dB) and the measured out‐of‐roundness for the omnidirectional radiation pattern are less than 4.4 dB within the desired frequency band. High gain and wideband omnidirectional radiation characteristics can provide a wide range of coverage and good signal transmission performance for outdoor wireless communication systems.

Integrated beamforming and trajectory optimization algorithm for RIS-assisted UAV system

Unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) have garnered considerable research interest in the fields of 5G and 6G wireless communication due to their remarkable flexibility and cost-effectiveness. However, the inherent openness of wireless communication environments renders these technologies vulnerable to eavesdropping. This paper presents a penalty-based successive convex approximation algorithm and a minorize–maximization algorithm to optimize the transmission beamforming vector, RIS beamforming vector, and UAV–RIS trajectory. The objective of this study was to enhance the physical layer security performance of wireless communication systems using UAVs and RISs. Our simulation results demonstrate that the proposed technique achieves a higher security transmission rate compared to existing techniques.

Intelligent Reflecting Surface Assisted Secure Computation of Wireless Powered MEC System

The integration of mobile edge computing (MEC) and wireless power transfer (WPT) can effectively improve the computing ability and energy sustainability of energy-constrained wireless devices in the Internet of Things (IoT) networks. Intelligent reflecting surface (IRS) has recently emerged as an effective technique to improve the performance of wireless systems by intelligently reconfiguring wireless environments. This paper studies the exploitation of IRS to improve the secure computation performance of WPT-MEC systems with a passive eavesdropper. A wireless access point (AP) first charge multiple users with the emitted energy signals, and then the users perform local computing and partial offloading to complete their computation tasks with the harvested energy in the presence of an eavesdropper, where the local computing can be executed during the whole process of WPT and offloading. Meanwhile, deploying IRS can improve the energy capture and secure offloading performance of the users. We maximize the secure computation task bits of users by jointly optimizing the AP energy transmit beamforming, the IRS phase shifts, the transmit power, users' offloading time, and the local computation frequency of users, which are tangled with each other. An iterative optimal algorithm is developed to solve this non-convex problem by combining Taylor expansion method, semidefinite relaxation (SDR) algorithm, the Lagrange duality theory and Karush-Kuhn-Tucker (KKT) conditions. The numerical results show that the proposed scheme can effectively increase the secure computation task bits compared with other benchmark schemes, especially for the maximum transmit power of AP, the improvement is above 45 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

Principles, applications, and challenges of digital predistortion technology

A power amplifier plays a crucial role in the transmitter end of wireless communication systems. Despite enhancing operational efficiency, it inadvertently introduces nonlinear distortion, leading to signal degradation and spectral regrowth. This occurrence necessitates the incorporation of additional linearization techniques in transmitter terminals to optimize both efficiency and linearity concurrently. Among these, Digital Pre-Distortion (DPD) technology stands out as a well-researched and extensively employed strategy for alleviating the nonlinear distortion induced by power amplifiers. This paper embarks on a comprehensive exploration of DPD technology, offering insight into its evolutionary path and elaborating on its foundational principles and essential techniques. The discussion extends to elucidate the significant technical challenges and the burgeoning trends within the DPD technology landscape. The narrative underscores the significance of DPD in enhancing the performance and efficiency of wireless communication systems, particularly in the context of burgeoning technological advancements and escalating demands for superior communication quality and broader bandwidth. Through a meticulous examination of the DPD technology paradigm, this paper contributes to the ongoing discourse and research, shedding light on prospective developmental avenues and potential enhancements that could further augment the efficacy and reliability of DPD technology in contemporary communication systems.

Energy efficient optimal deployment of industrial wireless mesh networks using transient trigonometric Harris Hawks optimizer

Wireless mesh networks (WMNs) play a vital role in modern communication systems, and optimizing the placement of wireless mesh routers is crucial for achieving efficient network performance in terms of coverage and connectivity. However, network congestion caused by overlapping routers poses challenges in WMN optimization. To address these issues, researchers have explored metaheuristic algorithms to strike a balance between coverage and connectivity in WMNs. This study introduces a novel hybrid optimization algorithm, namely Transient Trigonometric Harris Hawks Optimizer (TTHHO), specifically designed to tackle the optimization problems in WMNs. The primary objective of TTHHO is to find an optimal placement of routers that maximizes network coverage and ensures full connectivity among mesh routers. Notably, TTHHO's unique advantage lies in its efficient utilization of residual energy, strategically placing the sink node in areas with higher energy levels. The effectiveness of TTHHO is demonstrated through a comprehensive comparison with seven well-known algorithms, including Harris Hawks optimization (HHO), Sine Cosine Algorithm (SCA), Gray Wolf Optimization (GWO), Particle Swarm Optimization (PSO), Moth Flame Optimization (MFO), Equilibrium Optimizer (EO), and Transient Search Optimizer (TSO). The proposed algorithm is rigorously validated using 33 benchmark functions, and statistical analyses and simulation results confirm its superiority over other algorithms in terms of network connectivity, coverage, congestion reduction, and convergence. The simulation outcomes demonstrate the effectiveness and efficacy of the proposed TTHHO algorithm in optimizing WMNs, making it a promising approach for enhancing the performance of wireless communication systems.

Optimization of Wireless Charging Techniques in Electric Vehicle Applications through Machine Learning

The integration of electric vehicles (EVs) into mainstream transportation systems is contingent upon the development of efficient and convenient charging technologies. Wireless charging, in particular, presents a promising solution to address the limitations of traditional plug-in charging methods. However, optimizing wireless charging techniques for EVs remains a complex challenge, with factors such as efficiency, alignment, and safety needing careful consideration. This paper explores the potential of leveraging machine learning (ML) algorithms to enhance the performance of wireless charging systems for EVs. By employing ML techniques, such as neural networks and genetic algorithms, in conjunction with real-time data analysis, the aim is to develop adaptive and intelligent charging systems capable of optimizing various parameters to improve efficiency, reliability, and user experience. This research paper discusses the current state of wireless charging technologies, explores the application of machine learning in optimizing these systems, and presents potential avenues for future research and development

Optimization of magnetic coupling mechanism of dynamic wireless power transfer based on NSGA-II algorithm

Optimization of magnetic coupling mechanism is an important way to improve the performance of a dynamic wireless power transfer system. Inspired by the common radial magnetic core for circular coils, a new radial magnetic core for rectangular coils is adopt. Through simulation and experimental results comparison, which has higher coupling coefficient with the same core area. Combined with the magnetic circuit analysis, the magnetic flux leakage and conduction regions are divided into magnetic fluxes with different shapes, which magnetic resistances are calculated respectively. Based on the simulation results, parameter distributions of fluxes under different conditions are obtained. Therefore, the expressions of the coupling coefficient k of the adopt magnetic cores and coils and the design parameters of coils and cores are obtained. Taking the maximum k and the minimum rate of change of coupling coefficient with 100 mm displacement as the optimization objectives, a multi-objective optimization solution is carried out by using NSGA-II algorithm. The coil optimization scheme is obtained and verified by experiments. k and Δk are 0.442 and 6.8% respectively, and the errors are less than 5%. In the optimization process, there is no simulation model constructed. The optimization modeling combined of magnetic field segmentation method and parameter fitting has lower complexity and calculation time of optimization.

A Coordinate Positioning Technique Based on Region Partitioning for EV Wireless Charging System

The performance of wireless charging systems is very sensitive to the relative position of couplers. A small displacement between the transmitting and the receiving coils may lead to severe efficiency drop and degradation in system performance. Therefore, it is necessary to include a positioning-technique-based parking guiding program in EV wireless charging systems. To offer fast and clear location information of the couplers to the driver or automatic parking program, a coordinate positioning technique based on region partitioning for determining the relative position between the transmitting and receiving coils as well as the correct moving direction of the receiving coil is proposed in this paper. Meanwhile, a simple exciting circuit is also proposed to energize the source coil. Therefore, the proposed positioning system consists of the transmitting coil, receiving coil, two auxiliary coils and the corresponding low power converters. With the proposed technique, an EV can move to the near-perfect-coupling zone. Theoretical analysis and experimental verifications are provided.

Aerial intelligent reflecting surface for improving the secrecy performance of wireless systems with hardware impairments

SummaryIt has been confirmed that the aerial intelligent reflecting surface (AIRS) can dramatically improve the coverage and quality of service of wireless communication systems. This paper proposes to exploit an AIRS to enhance the physical layer security (PLS) of wireless communication systems. In particular, the AIRS flies at convenient positions for enhancing legitimate channel gain and reducing eavesdropping channel gain. Moreover, the worst‐case security is determined where the legitimate user is affected by hardware impairments (HIs) while the eavesdropper hardware is ideal (ID). The analytical expression of secrecy outage probability (SOP) of the considered systems (referred to as the AIRS‐HI systems) is derived over realistic Nakagami‐ channels recommended for application in the fifth and beyond generations (5G &amp; B5G). To clarify the behaviors of the considered systems, the asymptotic expressions of signal‐to‐distortion‐plus‐noise ratio (SDNR) at the legitimate user, signal‐to‐noise ratio (SNR) at the eavesdropper, and SOP are also provided. Monte‐Carlo simulations are employed to confirm the accuracy of the derived theorem. Numerical results confirm that the SOP of the AIRS‐HI systems is dramatically higher than the SOP of the AIRS‐ID systems. In other words, a strong effect of HIs on the SOP of the AIRS‐HI systems is clearly indicated. Consequently, utilizing the high transmit power is not an effective solution to improve the secrecy performance of the AIRS‐HI systems. In contrast, it is essential to employ an appropriate transmit power tailored to the specific system parameters. Furthermore, the considerable advantages of incorporating AIRS are demonstrated through a comparison between the SOPs of AIRS‐HI systems and HI systems lacking AIRS. Additionally, a comprehensive examination of AIRS‐HI system behaviors is conducted by varying various system parameters, including the predefined secrecy rate, HI level, the number of reflecting elements (REs) in AIRS, WiFi network frequency, AIRS altitude, bandwidth, and channel fading order. These observations lead to the identification of numerous recommended solutions for enhancing the SOP performance of the considered AIRS‐HI systems.

Performance Analysis and Simulation of IRS-Aided Wireless Networks Communication

This paper introduces the novel IRS-based Optimal Relay Selection (ORS-IRS) method, aimed at analyzing the performance of wireless communication systems with an emphasis on symmetry. The ORS-IRS approach presents an innovative communication algorithm that seamlessly integrates Intelligent Reflecting Surfaces (IRS) with relay selection techniques. Through adaptive adjustments of reflection coefficients, IRS elements efficiently manipulate incoming signals, fostering symmetry in signal strength enhancement and latency reduction for improved signal delivery to the intended destination. This symmetrical optimization in channel capacity and transmission power ensures reliable data transmission with low latency, achieved through the seamless integration of IRS and relay selection techniques. In contrast, the Cell-Free Massive MIMO (CF-M-MIMO), with its decentralized architecture, excels in serving a larger user base and attaining remarkable capacity gains, showcasing a different dimension of symmetry. The Decode-and-Forward (DF) relaying approach demonstrates its potential in enhancing signal reliability across extended distances, contributing to the overall symmetry of the comparative analysis. This comprehensive evaluation provides valuable insights into selecting appropriate transmission strategies, particularly for applications that demand high capacity and reliability in the design of modern wireless communication systems with a symmetrical focus.

Misurata Rural Area Path Loss Propagation Prediction and Optimization Using Machine Learning Techniques

Path loss prediction is of great importance in studies of designing, developing, and improving the performance of wireless networks and mobile communication systems of the 5G which requires of accuracy in performance and reduction in losses. Therefore, new models should be proposed to predict path loss propagation with high accuracy and less complexity. In this paper, a path loss model was designed and implemented using artificial intelligence and machine learning techniques, which training and testing on a real database created based on maximum measured distance and received power from the base station in a GSM system operating in 900 MHz band, in a rural environment, Misurata, Libya. Traditional methods like the "simple path loss model" performed poorly, with an average error of 5.87. In contrast, modern models based on artificial intelligence (AI) like GRNN, Fitnet, and Feedforward Net achieved significantly lower errors, ranging from 0.26 to 1.35. Furthermore, the AI models showed a strong correlation between the predicted and actual signal strengths (correlation coefficient R reaching 0.9962 for Fitnet and 0.99399 for Feedforward Net). This indicates highly specific and reliable predictions. Keywords: wireless communications, propagation loss prediction, ANN, machine learning, GRNN, urban area

Study on Anti-offset Performance of Dynamic Wireless Charging System with Reverse Series Double-layer Symmetrical Coil for Electric Vehicles

Study on Anti-offset Performance of Dynamic Wireless Charging System with Reverse Series Double-layer Symmetrical Coil for Electric Vehicles

Deep Learning-Based SC-FDMA Channel Equalization

It is very challenging to design an effective wireless communication system. That’s because of numerous factors affecting the performance of a typical wireless communication system, such as nonlinear channel distortions and impairments. single carrier frequency division multiple access (SC-FDMA) is a multiple access scheme that is an important part of the long-term evolution (LTE) standard for uplink transmission. An advanced mobile radio system’s multiple access schemes should indeed meet stringent requirements, such as a low bit error rate (BER). In this article, we investigate the equalization problem for nonlinear channel distortions and impairments using deep neural networks (NN). We introduce a novel combined deep neural network channel equalization and symbol detection scheme based on a deep learning (DL) recurrent feedback (RF) long short-term memory (LSTM) neural network to achieve blind equalization and decoding for SC-FDMA systems without knowing the channel state information (CSI). To train the model efficiently, the training data is gathered by simulation, with channel effects and noise treated as a complete black box. CSI and constellation demapping are learned by a deep neural network (DNN) model. Then, the frequency-domain sequences that have been corrupted are implicitly equalized to get the broadcasted signal back. Our specified SC-FDMA system, which uses a quadrature phase-shift keying (QPSK) modulation method and the suggested Deep Learning-based model channel equalizer, performs better than the existing equalizers by an average of 1 to 4 dB at moderate signal-to-noise (SNR) ratios, according to simulation data. A complexity comparison between the proposed and the conventional equalizers was conducted in terms of training time, execution time, and number of operations. On combined channel equalization and symbol detection, the suggested system delivers state-of-the-art performance.

EFFECT OF THICK VEGETATION COVER, BUILDING OBSTRUCTIONS, AND EARTH TERRAIN ON THE QUALITY AND PERFORMANCE OF THE GSM SIGNAL AT THE FEDERAL POLYTECHNIC ADO-EKITI

Wireless communication system performance is fundamentally constrained by the mobile radio channels such as the Global System for Mobile Communication (GSM). The transmission path between the base transceiver station and the mobile station can range from line-of-sight to substantially obstructed environmental situations such as buildings, earth undulation valleys, and thick vegetation being the primary cause of poor network performance in and around the school perimeter. Mobile radio channels are incredibly unpredictable and do not provide simple analysis, in contrast to stationary and reliable wired channels. This research work, therefore, investigates the effect of thick vegetation cover, building obstructions, and earth terrain on the quality and performance of the GSM signal at the Federal Polytechnic Ado-Ekiti environs. A model for path loss (attenuation) is developed according to the Longley-Rice propagation model that forecasts the long-term median transmission loss over uneven terrain in comparison to the free-space transmission loss. The model was created for frequencies in the 20 MHz to 40 GHz range and path lengths in the 1 to 2,000 km range. The analysis of the results obtained shows that the path loss (attenuation) produced due to the effect of vegetation, building obstructions, and the earth undulation structures are quite significant. The solution of cell creation as a primary way of improving the quality of the GSM signal reception in the school perimeter without necessarily destroying the natural environment or demolishing any existing building is proposed.

Bitter Rate of Performance in Wireless Communications on 5G Technology

Wireless communications have become an integral part of our modern society, enabling seamless connectivity and data exchange. The bit rate of performance in wireless communication systems plays a crucial role in determining the quality of service and user experience. This abstract provides an overview of key factors influencing bit rate in wireless communications and highlights the challenges and advancements in optimizing performance. The bit rate, often measured in bits per second (bps) or multiples thereof, quantifies the rate at which data can be transmitted over a wireless channel. Several factors impact the bit rate in wireless communications, including the available bandwidth, modulation schemes, signal-to- noise ratio (SNR), and channel conditions. The bit rate is closely related to the achievable data throughput and is a critical metric for assessing the efficiency of wireless networks. Wireless technologies, such as 4G and 5G, have significantly increased the bit rates achievable for mobile communication. These technologies employ advanced modulation techniques and multiple-input, multiple- output (MIMO) systems to enhance spectral efficiency and data rates. Additionally, the deployment of small cells and the use of high-frequency bands have improved data rates and reduced latency in wireless networks. However, challenges persist in optimizing bit rates for wireless communications. Factors like signal interference, fading, and path loss can degrade performance. Moreover, the ever- increasing demand for data-intensive applications and the proliferation of IoT devices put additional pressure on wireless networks to deliver higher bit rates with low latency. To address these challenges, ongoing research focuses on developing advanced signal processing algorithms, beamforming techniques, and error correction mechanisms. Machine learning and artificial intelligence are also being employed to optimize wireless communication systems and enhance bit rates.

The Application of Whale Optimization Algorithm in Array Antennas

Abstract With the continuous improvement of various radio system performance indicators, the research work on antenna has become particularly important. According to different scenarios and requirements, practical projects also need the corresponding antennas to produce different radiation patterns. By reasonably setting the parameters of the array antenna, the target radiation pattern can be obtained to meet real life applications. When the array antenna has a large number of basic units and the expected far-field pattern is complicated, the design of the array antenna becomes a complicated optimization problem. To solve this problem, Whale Optimization Algorithm (WOA) is proposed. WOA is not only simple and fast, but can also get the global optimal solution. Therefore, WOA has developed rapidly in recent years. However, the application of this algorithm in the field of antenna design is still relatively rare, thus using WOA to solve the optimization problem of array antenna design is very valuable.

Co-operative non-orthogonal multiple access networks: a survey

Purpose The purpose of this paper is to present an up-to-date survey on the non-orthogonal multiple access (NOMA) technique with co-operative strategy, a fast-evolving fifth-generation (5 G) technology. NOMA is used for serving many mobile users, both in power and code domains. This paper considers the power-domain NOMA, which is now discussed as NOMA. Design/methodology/approach The first part of the paper discusses NOMA-based cooperative relay systems using different relay strategies over different channel models. In various research works, the analytical expressions of many performance metrics were derived, measured and simulated for better performance of the NOMA systems. In the second part, a brief introduction to diversity techniques is discussed. The multiple input and multiple output system merged with cooperative NOMA technology, and its future challenges were also presented in this part. In the third part, the paper surveys some new conceptions such as cognitive radio, index modulation multiple access, space-shift keying and reconfigurable intelligent surface that can be combined with NOMA systems for better performance. Findings The paper presents a brief survey of diverse research projects being carried out in the field of NOMA. The paper also surveyed two different relaying strategies that were implemented in cooperative NOMA over different channels and compared several performance parameters that were evaluated and derived in these implementations. Originality/value The paper provides a scope for recognizable future work and presents a brief idea of the new techniques that can be united with NOMA for better performance in wireless systems.