Improve Data Rate Research Articles

Investigation of channel state information conditions in VL-NOMA using power allocation technique for 6G network

Abstract This paper investigates the channel state information (CSI) conditions in visible light non-orthogonal multiple access (VL-NOMA) using the power allocation technique (PA) for a sixth-generation (6G) network. One light-emitting diode (LED) is used as a carrier to transmit the signal to three-user-positioned at certain distances. The challenge of allocating power to the system is solved using the PA technique. The PA technique uses to assign signal powers to the three users. The VL-NOMA channel with CSI symbols is synchronized for the performance of signal propagation. We deployed perfect CSI, imperfect CSI, and partial CSI to coordinate the signal enhancement that results in an improved data rate, higher channel capacity, and improved signal-to-noise ratio (SNR). The synchronized system model guarantees successful signal enhancement where perfect CSI performs better than partial CSI and imperfect CSI. We have enabled interference plus noise to see how the system behaves. We notice low channel capacity region, low data rate performance, etc. Hence, we analyse the PA to determine the outage probability effect on the signal.

Hybrid FSK–FDM Scheme for Data Rate Enhancement in Dual-Function Radar and Communication

In this paper, we present a hybrid frequency shift keying and frequency division multiplexing (i.e., FSK–FDM) approach for information embedding in dual-function radar and communication (DFRC) design to achieve an improved communication data rate. Since most of the existing works focus on merely two-bit transmission in each pulse repetition interval (PRI) using different amplitude modulation (AM)- and phased modulation (PM)-based techniques, this paper proposes a new technique that doubles the data rate by using a hybrid FSK–FDM technique. Note that the AM-based techniques are used when the communication receiver resides in the side lobe region of the radar. In contrast, the PM-based techniques perform better if the communication receiver is in the main lobe region. However, the proposed design facilitates the delivery of information bits to the communication receivers with an improved bit rate (BR) and bit error rate (BER) regardless of their locations in the radar’s main lobe or side lobe regions. That is, the proposed scheme enables information encoding according to the transmitted waveforms and frequencies using FSK modulation. Next, the modulated symbols are added together to achieve a double data rate using the FDM technique. Finally, each transmitted composite symbol contains multiple FSK-modulated symbols, resulting in an increased data rate for the communication receiver. Numerous simulation results are presented to validate the effectiveness of the proposed technique.

Spectrum-Efficient Analog Pulse Index Modulation for High-Volume Wireless Data Telemetry

Spectrum-efficient, high-density, and high-speed data transmission are essential to store and exchange sensitive information through Internet-of-Things (IoT) networks. However, the resource-constrained IoT devices and the limited existing frequency spectrum pose a significant challenge to employing the more efficient technique for the next-generation technology. This paper presents an innovative pulse index modulation (PIM) architecture with a randomization technique for analog pulse-based packet-less high-volume data transmission. The pulse-based compression simplifies the encoding and decoding schemes for short-range wireless telemetry. The pulse randomization technique creates the pulse blinding by reordering the pulse positions and adds an extra level of physical layer security. This paper describes the design, simulation, and prototype development of PIM to validate the feasibility and compatibility of pulse-based data telemetry using the standard architecture. Simulation results show that the proposed PIM increases the data compression ratio by 2.61 times and improves the processing time by 5.56 time compared to the Huffman coding for a 3-bit system. Test results show that the BER is 7.5×10-4 at 10.0 dB SNR, which satisfies the lower bound for data communication and increases the transmission speed k-times by supporting 2k*k bits data using 2k number of pulses, where k is a non-negative integer number. The proposed PIM has the potential to improve data rate with added security to support the next-generation IoT networks.

Coalition Formation for Outsourced Spectrum Sensing in Cognitive Radio Network

We inspect an opportunistic Cognitive Radio Network formed between a Primary Network Provider (PNP) and secondary IoT operators. In our system, spectrum-sensing duty is offloaded to a Sensing Agent (SA), which allows the IoT operators to improve data rate and reduce energy consumption otherwise needed for spectrum-sensing. IoT operators pay PNP for accessing licensed spectrum and SA for providing sensing as a service. We use Nash bargaining to finalize negotiations among PNP, IoT operators, and SA. Our investigation shows that incorporating SA improves the throughput and utility of PNP and IoT operators. Coalition formation among IoT operators helps them avoid intra-coalitional interference by accessing the spectrum in time-shared fashion. As the valuation of a coalition depends on other coalitions, we analyze coalition formation as a Partition Function Game. We emphasize economic fairness among the coalitions to prevent monopolization. We define a proportional fairness-based metric based on which the final coalition structure is determined. In general, finding an optimal coalition structure is an NP-hard problem. The fairness criterion, along with the unique properties of the Nash bargaining solution allows us to transform the coalition formation problem into a more tractable Number Partitioning Problem and develop an efficiently computable coalition formation technique.

Improving Isolation in MIMO Antenna for WLAN Applications

The system Wireless Local Area Network (WLAN) presents minimum bandwidths to provide required transmission data rates, isolation can also be improved using multiple input multiple output (MIMO) scheme increasing their capacity. In this paper, the Decoupling Networks technique is presented to reduce the coupling between the elements of the MIMO antenna and thus improve data rate with a 2x2 MIMO antenna system. The dielectric used was FR4 substrate with dielectric constant εr = 4.4 and thickness of substrate 1.544 mm. The S11 and S12 scattering parameters were obtained as well as ECC at the resonance frequency and bandwidth. The radiation pattern and the current density are simulated by HFSS. The antenna size is 80x65mm^2.

Optimal Power Allocation and Power Splitting Ratio Assignments for SWIPT-Enabled Orthogonal Multiple Access with Distributed Antenna Systems

This study proposes an integrated framework of single-selection distributed antenna systems (DAS) and simultaneous wireless information and power transfer (SWIPT) with orthogonal multiple access (OMA), and analyzes the synergetic effects of SWIPT and DAS. To demonstrate the performance gains of the proposed SWIPT-enabled OMA with DAS, we jointly optimize power allocation for the OMA and power splitting (PS) ratio for energy harvesting of SWIPT with three different optimization goals: sum-rate maximization, user fairness, and energy efficiency. Although all of the above optimization problems are non-convex, the closed-form solutions of the problems maximizing the sum-rate and fairness are presented. Owing to difficult analytical tractability of the problem maximizing the energy efficiency, the problem is divided into three subproblems: power allocation for the base station (BS), power allocation for radio remote unit (RRU), and PS ratio assignment. Then, an iterative algorithm is presented to provide the energy-efficient SWIPT-enabled OMA with DAS. Theoretical findings are validated by numerical results, which show that the framework of applying DAS to SWIPT-OMA improves data rates and energy efficiency compared to SWIPT-OMA without DAS, while satisfying the minimum rate and harvested energy requirements.

Future of 5G Wireless Systems: A Review

Everybody loves speed and moreover speedy internet, so it’s no surprise that every major telecom in the world is working to make it even faster. Smartphone’s, watches, homes, and cars are increasingly requiring stable internet connections. In order to survive in the world where in
 every second the speed changes and where we urge for more and more technology, here comes the fifth generation technology: 5G. In future, i.e., a world beyond 4G, some of the prime objectives that need to be fulfilled are increased capacity, improved data rate, decreased latency, and quality service. To meet these demands, large scale improvement in the cellular architecture of 5G is required .This paper basically lays emphasis on the 5th generation i.e. 5G cellular network architecture and some of the essential emerging technologies that can prove fruitful in humanizing the architecture and summiting the demands of users.
 This paper is contented with the details related to 5g with the prime focus on the massive multiple input multiple output technology and device-to-device communication (D2D). A general credible 5G cellular network architecture is being proposed with the guideline taken from the internet books and by the detailed study of the topic.
 Beginning with an exploration of the evolution from 4G to 5G, we dissect the technical intricacies that empower 5G networks, including spectrum allocation, massive MIMO, and network slicing.
 The paper navigates through the diverse spectrum of applications that 5G facilitates, from Enhanced Mobile Broadband (eMBB) .As 5G integrates with emerging technologies such as edge computing and artificial intelligence, we unravel the synergies that are reshaping industries and fostering innovation.

Optimal Adaptive Waveform Design Utilizing an End-to-End Learning-Based Pre-Equalization Neural Network in an UVLC System

Visible light communication (VLC) has emerged as a promising communication method in the special field of 6G, such as intersatellite communication (ISC) and underwater wireless optical communication (UWOC). Green light-emitting diode (LED)-based underwater visible light communication (VLC) is considered a potential candidate for UWOC of mobile autonomous underwater vehicle (AUV) and remotely operated underwater vehicle, particularly in coastal and harbor environments. However, due to bandwidth limitations and variable underwater channels, implementing high-speed underwater VLC remains a challenge. In this paper, a neural network-based auto equalization model (NNAEM) using end-to-end learning is proposed to achieve a high-speed underwater VLC link with a bandwidth-limited green LED. The entire NNAEM includes a neural network-based channel model, a pre-equalization neural network, and a post-equalization neural network. Based on the data-driven channel model, our auto equalization (AE) method can dynamically pre-equalize the discrete multitone (DMT) modulated signal in different bandwidth-limited cases and various nonlinearity cases. An underwater VLC link with a data rate of 3.451 Gbps and a transmission distance of 1.2 m is experimentally demonstrated by employing the proposed NNAEM under the hard decision-forward error correction (HD-FEC) threshold of 3.8 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> . The data rate improvement is up to 30.4% compared to other advanced digital signal processing (DSP) methods. The scenario adaptation and robustness of the NNAEM are also verified in the experiments, which demonstrate that the NNAEM can serve an important role in underwater high-speed VLC transmission.

Practical Considerations in Direct Detection Under Tukey Signalling

The deliberate introduction of controlled intersymbol interference (ISI) in Tukey signalling enables the recovery of signal amplitude and (in part) signal phase under direct detection, giving rise to significant data rate improvements compared to intensity modulation with direct detection (IMDD). The use of an integrate-and-dump detector makes precise waveform shaping unnecessary, thereby equipping the scheme with a high degree of robustness to nonlinear signal distortions introduced by practical modulators. Signal sequences drawn from star quadrature amplitude modulation (SQAM) formats admit an efficient trellis description that facilitates codebook design and low-complexity near maximum-likelihood sequence detection in the presence of both shot noise and thermal noise. Under the practical (though suboptimal) allocation of a 50% duty cycle between ISI-free and ISI-present signalling segments, at a symbol rate of 50 Gbaud and a launch power of -10 dBm the Tukey scheme has a maximum theoretically achievable throughput of 200 Gb/s with an (8,4)-SQAM constellation, while an IMDD scheme achieves about 145 Gb/s using PAM-8. Note that the two mentioned constellations have the same number of magnitude levels and the difference in throughput is resulting from exploiting phase information under using a complex-valued signal constellation.

Cloud based IoT Electronic Healthcare Data Warehouse Integration in emerging 5G Health Grid Ecosystem

The integration of heterogeneous enterprise cloud data warehouses enables the formation of national health grid ecosystem that links public and private health databases to enable supervision of healthcare utilities, costs, quality of care and observance of national healthcare administrative protocols. The development of cloud data warehouse requires information communication technology to condense the costs of patient’s healthcare by supporting care, away from hospitals, where increasingly detailed data can move from patients to centralized cloud server data warehouse, allowing efficiency in diagnosis and treatment options. The global democratization of 5G telecommunication broadband creates entirely new use case scenarios for consumers addressing healthcare sector and industries, intending to improve citizen’s life expectancy. The improved data rate transmission revolutionizes healthcare sector and offers prospects that enable the telecommunication merchants to penetrate the supply chains and initiate partnerships that profit the entire healthcare business ecosystem. This paper analyses the 5G network implementation business potentials, focusing on the 5G business opportunities that originate from industrial healthcare automation, allowing patient data aggregation required for citizens’ healthcare management. The research entrenches the 5G radio frequency access network and distributed cloud IoT server systems in constructing a healthcare grid data warehouse to enable self-optimized service-level agreements. Moreover, this paper observes that the healthcare sector prioritized telecommunication operators when partnership issues were debated above every other service sector addressing healthcare development. The cloud IoT platform offers solution to synchronize-able global device connectivity management for e-healthcare and demonstrates how these improvements enable development of new systems for public healthcare policy formulation and delivery in Nigeria.

Hybrid Optical Wireless Communication for Versatile IoT Applications: Data Rate Improvement and Analysis

Hybrid Optical Wireless Communication for Versatile IoT Applications: Data Rate Improvement and Analysis

A survey on state of the inter body radio communication channel: Performance and solutions

AbstractThe development of in‐vivo communications and networking systems has the potential for improving the healthcare delivery while also enabling the creation of new services and applications. In‐vivo communications provide wireless networked cyber‐physical systems of the embedded devices that enable accurate, quick, and cost‐effective responses under a variety of circumstances. Also, it is focused upon modeling and characterizing in‐vivo wireless channel, as well as contrasting it to other well‐known channels. In this paper, channel coding is also mentioned because it improves data rates and performance gain. This work also discusses present problems and potential research topics for in‐vivo communications. This article aims to show the researchers how the orthogonal frequency multiple access (OFDMA) technique improved the performance of in‐vivo channel and how it is outperformed compared to the other techniques (TDM, TDMA, CDMA and OFDM) also how the OFDMA outperformed equalizers and channel coding in terms of bit error rate with giving a significant improvement of data transmitting and avoiding inter symbol interference. However, when it comes to the in‐vivo communications, the modeling of in‐vivo wireless channel is vital. Understanding the features of the in‐vivo channel is critical for achieving optimal processing and designing successful procedures that allow WBANs to be arranged inside the human body.

Design and Optimization of Liquid Crystal RIS-Based Visible Light Communication Receivers

In the design of reconfigurable intelligent surfaces (RISs)-aided visible light communication (VLC) systems, most studies have focused on the deployment of mirror arrays and metasurfaces on walls to influence signal propagation and enhance communication performance. This paper provides a new research direction in the design and performance optimization of RIS-aided VLC systems whereby voltage-controlled tunable liquid crystals (LCs) are deployed as part of the VLC receiver. The purpose of the LC RIS is to provide incident light steering and intensity amplification in order to improve the received signal strength and the corresponding achievable data rate. More specifically, an LC RIS-based VLC receiver design is proposed and its operating principles and the channel model for a VLC system with such a receiver are provided. Since the refractive index of the LC RIS plays a critical role in the wave-guiding and light amplification capabilities of this novel receiver, a rate maximization problem is considered to achieve the optimal refractive index and the required voltage to obtain the best light amplification and data rate performances. This communication design problem is a non-convex optimization problem for which a metaheuristic approach is developed based on the sine-cosine algorithm. Simulation results are used to confirm the considerable data rate improvement by the proposed LC RIS-based VLC receiver and optimization algorithm when compared to a VLC receiver without the LC RIS and a baseline scheme, respectively.

An Hybrid Heuristic optimal relay selection strategy for energy efficient multi hop cooperative cellular communication

One of the major constraints for mobile relay networks is energy-efficient communication owing to the restricted battery power of user terminals. Among them, the production method is cooperative cellular networks that focus on enhancing the data rate, network reliability, and network system capacity and also improving the spectrum resources in the Fifth Generation (5 G) networks. Thus, recent research works investigate the selection of mobile relays in vehicular networks and also the relay selection in cooperative communication. Here, the mobile relay is selected by the base station (operator) for every mobile user for reducing the cost with improved data rates and reducing the total transmission power. The selection of relay is performed by considering the benefits or utilities offered to three players such as mobile relay, mobile user, and operator. Conventional relay node selection approaches face challenges regarding reduced network lifetime, delay, increased energy consumption, and collusion attacks. For next-generation wireless networks, both energy efficiency and capacity are vital. To cope with these problems, a new multi-objective derived energy efficient accurate selection of relay in multi-hop cooperative cellular communication in the vehicular network through a hybrid heuristic strategy is implemented. The conventional approaches are utilized for probability-based multi-hop broadcasting for low latency. On the other hand, the major demerits of cellular communication are developing an effective multi-hop communication strategy that generates hidden node problems, and also it decreases the speed of the vehicles and the lack of infrastructure in network topology. Thus, this paper aims to propose a hybrid optimization model to choose the lowest count of multi-hops among the source and destination for the cooperative cellular vehicular communication network. The major issue well thought-out here is accurately choosing the count of hops or relays for appropriate communication, which is carried out through the multi-objective function regarding link reliability, energy consumption, outage probability, mobility factor, and transmission delay of the system. The adoption of the new hybrid algorithm with the aid of the Best Fitness-derived Crow Tunicate Swarm Optimization (BF-CTSO) algorithm is designed as the major contribution for optimally selecting the multi-hops between source and destination in a cooperative cellular communication network. Numerical results show that the proposed energy-efficient cooperative communication system outperforms traditional methods.

Demonstration of Spatial Modulation Using a Novel Active Transmitter Detection Scheme with Signal Space Diversity in Optical Wireless Communications.

Line-of-sight (LOS) indoor optical wireless communications (OWC) enable a high data rate transmission while potentially suffering from optical channel obstructions. Additional LOS links using diversity techniques can tackle the received signal performance degradation, where channel gains often differ in multiple LOS channels. In this paper, a novel active transmitter detection scheme in spatial modulation (SM) is proposed to be incorporated with signal space diversity (SSD) technique to enable an increased OWC system throughput with an improved bit-error-rate (BER). This transmitter detection scheme is composed of a signal pre-distortion technique at the transmitter and a power-based statistical detection method at the receiver, which can address the problem of power-based transmitter detection in SM using carrierless amplitude and phase modulation waveforms with numerous signal levels. Experimental results show that, with the proposed transmitter detection scheme, SSD can be effectively provided with ~0.61 dB signal-to-noise-ratio (SNR) improvement. Additionally, an improved data rate ~7.5 Gbit/s is expected due to effective transmitter detection in SM. The SSD performances at different constellation rotation angles and under different channel gain distributions are also investigated, respectively. The proposed scheme provides a practical solution to implement power-based SM and thus aids the SSD realization for improving system performance.

Design of matched filter for signal‐to‐noise ratio maximization to improve data rate

AbstractThe matched filter is an optimal linear filter for maximizing signal‐to‐noise ratio (SNR) in the presence of additive random noise. Learning‐based matched filter is the proposed work. The proposed model supports (i) maximizing the SNR and (ii) setting the threshold, it is also called an intelligent matched dual tire filter. This improves the SNR by about 20 dB and the corresponding data rate to over 400 MBit/s. The bit error rate for 20 dB is very lower than FEC (10−3) of up to 10−7. The accuracy of the proposed matched learning filter is proved to be above 95%. Indoor visible light communication is one of the applications, and it can also be used for image processing and outdoor communication such as satellite and radar communication. It is obvious for communication as it avoids signal degradation, lobing, and overfitting to achieve a better data rate. This requires funding support and infrastructure facility that can be used to deploy the proposed algorithm in the real‐time scenario in the future.

Coverage Analysis of mmWave and THz-Enabled Aerial and Terrestrial Heterogeneous Networks

Heterogeneous networks (HetNets) are becoming a promising solution for future wireless systems to satisfy the high data rate requirements. This paper introduces a stochastic geometry framework for the analysis of the downlink coverage probability in a multi-tier HetNet consisting of a macro-base station (MBS) operating at sub-6 GHz, millimeter wave (mmWave)-enabled unmanned aerial vehicles (UAVs) operating at 28 GHz, and small BSs operating both at mmWave and THz frequencies. The analytical expressions for the coverage probability for each tier have been derived in the paper. Monte Carlo simulations are then performed to validate the analytical expressions. The effectiveness of the HetNet is analyzed on various performance metrics including association and coverage probabilities for different network parameters. We show that the mmWave and THz-enabled cells provide significant improvement in the achievable data rates because of their high available bandwidths, however, they have a degrading effect on the coverage probability due to their high propagation losses.

Optimal User Scheduling in Multi Antenna System Using Multi Agent Reinforcement Learning

Multiple Input Multiple Output (MIMO) systems have been gaining significant attention from the research community due to their potential to improve data rates. However, a suitable scheduling mechanism is required to efficiently distribute available spectrum resources and enhance system capacity. This paper investigates the user selection problem in Multi-User MIMO (MU-MIMO) environment using the multi-agent Reinforcement learning (RL) methodology. Adopting multiple antennas' spatial degrees of freedom, devices can serve to transmit simultaneously in every time slot. We aim to develop an optimal scheduling policy by optimally selecting a group of users to be scheduled for transmission, given the channel condition and resource blocks at the beginning of each time slot. We first formulate the MU-MIMO scheduling problem as a single-state Markov Decision Process (MDP). We achieve the optimal policy by solving the formulated MDP problem using RL. We use aggregated sum-rate of the group of users selected for transmission, and a 20% higher sum-rate performance over the conventional methods is reported.

Advancements in 5G Technology: Enhancing Connectivity and Performance in Communication Engineering

The present research delves into how 5G technology developments can improve communication engineering performance and connectivity. The primary goals are to assess 5G's technical viability, performance potential, and real-world obstacles while offering recommendations for best practices in implementation and use. The study synthesizes current literature, research papers, and industry reports using a secondary data-based review technique to examine the technological underpinnings, performance improvements, real-world applications, and future directions of 5G. According to key findings, 5G dramatically improves data rates, lowers latency, and allows for ample device connectivity, opening up new possibilities for revolutionary applications in industries like industrial automation, smart cities, and healthcare. Strategic policy interventions are necessary to address cybersecurity risks, coverage restrictions, interoperability issues, and expensive infrastructure costs. To overcome these issues, provide fair access, and optimize the socioeconomic benefits of 5G, policymakers are encouraged to prioritize spectrum allocation, simplify regulatory frameworks, and provide incentives for investments. Future studies and developments in Edge Computing and AI-driven network optimization are emphasized as essential to improving 5G networks even more. The potential of 5G to alter communication engineering and accelerate inclusive digital transformation is shown by this thorough examination.

5G System Overview for Ongoing Smart Applications: Structure, Requirements, and Specifications.

Fifth-generation (5G) cellular networks are state-of-the-art wireless technologies revolutionizing all wireless systems. The fundamental goals of 5G are to increase network capacity, improve data rates, and reduce end-to-end latency. Therefore, 5G can support many devices connected to the Internet and realize the Internet of Things (IoT) vision. Though 5 G provides significant features for mobile wireless networks, some challenges still need to be addressed. Although 5 G offers valuable capabilities for mobile wireless networks, specific issues still need to be resolved. This article thoroughly introduces 5G technology, detailing its needs, infrastructure, features, and difficulties. In addition, it summarizes all the requirements and specifications of the 5G network based on the 3rd Generation Partnership Project (3GPP) Releases 15–17. Finally, this study discusses the key specifications challenges of 5G wireless networks.