Enhanced Data Rates Research Articles

SSK-ICS LoRa: A LoRa-Based Modulation Scheme With Constant Envelope and Enhanced Data Rate

Long-range (LoRa) modulation is an orthogonal modulation scheme that uses linearly-modulated up chirps to represent information bits. Its constant envelope and good bit-error-rate performance make it one of the key players in establishing low-power wide-area networks for the Internet of things applications. However, LoRa modulation has low data rates. In this letter, we propose a new constant-envelope modulation scheme, named slope-shift-keying and interleaved-chirp spreading (SSK-ICS) LoRa modulation, that can deliver higher data rates than the conventional LoRa modulation scheme. Succinctly, the proposed SSK-ICS-LoRa modulation uses up chirps, down chirps, interleaved up chirps and interleaved down chirps to expand the signal set and hence can carry more bits per transmission symbol. For the same spreading factor and bandwidth consumption, the proposed scheme is able to improve the data rate of the conventional LoRa scheme up to 28.6%. We also present the optimal maximum-likelihood detectors for both coherent and non-coherent demodulators for the proposed scheme. Simulation results show that the proposed scheme outperforms LoRa modulation in both data rate and bit-error rate.

Deep Q-Learning for Intelligent Band Coordination in 5G Heterogeneous Network Supporting V2X Communication

A heterogeneous or hybrid 5G network is required to support connected vehicles to implement the full range of cooperative ITS (intelligent transport system) services in diverse scenarios. In order to enhance data rate or reduce latency by increasing transmission bandwidth, 5G utilizes frequency bands below and above 6 GHz. The challenge is that multiple band coordination in 5G will be essential to mobile network operators. Even worse, traditional strategies could not meet the demand. Most current 5G research is focused in 5G network optimization. However, frequency coordination in 5G, as one of the most important requirements from operators, is left untouched. In this paper, a multi-agent deep Q-learning network (DQN) is developed as coordination solution. Transfer learning is introduced in DQN to decrease the deployment complexity of the proposed solution on 5G gNB (next-generation NodeB). By deploying the proposed solution in the system level simulation, the simulation shows an average 10% throughput enhancement, an about 24% accessed user number increasing, and around 70% training time saving, compared with normal Q-learning solution, and it enables the operators to optimally utilize all the valuable frequency resources to the best commercial value.

Multi-tier delay-aware load balancing strategy for 5G HC-RAN architecture

The fifth-generation (5G) cellular network aim to provide ultra-low latency and enhance data rate service to its associated users. The centralized baseband processing of incoming traffic increases the computational complexity and end-to-end delays in a conventional C-RAN architecture. This paper proposes a multi-tier HC-RAN architecture using the edge computing concept at the Remote Radio Head (RRH) to overcome the above limitations. Further, to reduce load at the C-BBU and fronthaul, we have proposed a multi-tier delay-aware load balancing (MDALB) algorithm. The proposed algorithm is run over the EO to strategically distribute incoming flow between eRRH and C-BBU based on a load distribution ratio. The efficiency of the proposed strategy is analyzed through mathematical models and simulations based on various performance matrices. The performance parameters’ results show that the use of multi-tier processing in HC-RAN minimizes end-to-end delay and packet loss whereas increases the system throughput and packet delivery ratio.

Multimedia Conferencing at the Network Edge

The fifth generation (5G) mobile system provides enhanced data rates, ultra-low latency, and better network resource usage for Internet of Things (IoT) devices in a dense environment. The integration of 5G IoT and multimedia conferencing enables collaboration between humans and devices by launching new capabilities. In this paper, an approach to define Application Programming Interfaces (API) for multimedia conference control is presented. The API design follows the principles of Multi-access Edge Computing (MEC) and features the inherent advantages of MEC. The API is described by resource structure, data types, and sequence diagrams that illustrate the API functionality. Some implementation issues are discussed, and the injected latency is evaluated.

Development of PCCNN-Based Network Intrusion Detection System for EDGE Computing

Intrusion Detection System (IDS) plays a crucial role in detecting and identifying the DoS and DDoS type of attacks on IoT devices. However, anomaly-based techniques do not provide acceptable accuracy for efficacious intrusion detection. Also, we found many difficulty levels when applying IDS to IoT devices for identifying attempted attacks. Given this background, we designed a solution to detect intrusions using the Convolutional Neural Network (CNN) for Enhanced Data rates for GSM Evolution (EDGE) Computing. We created two separate categories to handle the attack and non-attack events in the system. The findings of this study indicate that this approach was significantly effective. We attempted both multiclass and binary classification. In the case of binary, we clustered all malicious traffic data in a single class. Also, we developed 13 layers of Sequential 1-D CNN for IDS detection and assessed them on the public dataset NSL-KDD. Principal Component Analysis (PCA) was implemented to decrease the size of the feature vector based on feature extraction and engineering. The approach proposed in the current investigation obtained accuracies of 99.34% and 99.13% for binary and multiclass classification, respectively, for the NSL-KDD dataset. The experimental outcomes showed that the proposed Principal Component-based Convolution Neural Network (PCCNN) approach achieved greater precision based on deep learning and has potential use in modern intrusion detection for IoT systems.

Machine Learning for Physical Layer in 5G and beyond Wireless Networks: A Survey

Fifth-generation (5G) technology will play a vital role in future wireless networks. The breakthrough 5G technology will unleash a massive Internet of Everything (IoE), where billions of connected devices, people, and processes will be simultaneously served. The services provided by 5G include several use cases enabled by the enhanced mobile broadband, massive machine-type communications, and ultra-reliable low-latency communication. Fifth-generation networks potentially merge multiple networks on a single platform, providing a landscape for seamless connectivity, particularly for high-mobility devices. With their enhanced speed, 5G networks are prone to various research challenges. In this context, we provide a comprehensive survey on 5G technologies that emphasize machine learning-based solutions to cope with existing and future challenges. First, we discuss 5G network architecture and outline the key performance indicators compared to the previous and upcoming network generations. Second, we discuss next-generation wireless networks and their characteristics, applications, and use cases for fast connectivity to billions of devices. Then, we confer physical layer services, functions, and issues that decrease the signal quality. We also present studies on 5G network technologies, 5G propelling trends, and architectures that help to achieve the goals of 5G. Moreover, we discuss signaling techniques for 5G massive multiple-input and multiple-output and beam-forming techniques to enhance data rates with efficient spectrum sharing. Further, we review security and privacy concerns in 5G and standard bodies’ actionable recommendations for policy makers. Finally, we also discuss emerging challenges and future directions.

5G Media Action Group (5G-MAG): Bridging Media and 5G

The evolution in connectivity, particularly, the introduction of the fifth-generation technology standard for mobile telecommunications (5G), worldwide is opening doors for new applications, use cases, and business opportunities in many industries. 5G comes with improved technical capabilities targeting enhanced data rates, lower latencies, or high connection densities, among others. However, it is not just a new air interface technology, such as New Radio (NR). It comes as part of a complete ecosystem complemented by computing capabilities integral to networks, highly softwarized functions, new ways of traffic management and isolation together with an increasing disaggregation between processes, equipment, network operators, service providers, and spectrum license holders. While previous mobile technologies established a closed solution, 5G introduces a paradigm shift with respect to industry engagement.

Bluetooth/GSM Based Android Controlled Robot

The project aims in designing a robot that can be operated using Android Apps. The controlling of the Robot is done wirelessly through Android smart phone using the Bluetooth module feature present in it. Here in the project the Android smart phone is used as a remote control for operating the Robot. Android is a software stack for mobile devices that includes an operating system, middleware and key applications. Android boasts a healthy array of connectivity options, including Wi-Fi, Bluetooth, and wireless data over a cellular connection (for example, GPRS, EDGE (Enhanced Data rates for GSM Evolution), and 3G). Android provides access to a wide range of useful libraries and tools that can be used to build rich applications. Bluetooth is an open standard specification for a radio frequency (RF)-based, short-range connectivity technology that promises to change the face of computing and wireless communication. It is designed to be an inexpensive, wireless networking system for all classes of portable devices, such as laptops, PDAs (personal digital assistants), and mobile phones. The controlling device of the whole system is a Microcontroller. Bluetooth module, DC motors are interfaced to the Microcontroller. The data received by the Bluetooth module from Android smart phone is fed as input to the controller. The controller acts accordingly on the DC motors of the Robot. The robot in the project can be made to move in all the four directions using the Android phone. The direction of the robot is indicated using LED indicators of the Robot system. In achieving the task, the controller is loaded with a program written using Embedded ‘C’ language.

Data rate enhancement of free space optical communication using pulse positioned differential phase shift keying.

In this paper, a pulse positioned-differential phase shift keying technique is proposed to enhance the data rate in free space optical communication. Using the schematics of polarization rotation differential phase shift keying, multi-rate functionality can be achieved without using delay-line interferometers. Furthermore, the proposed novel modulation format-differential phase shift keying combined with pulse-position modulation-enables a high data rate owing to the use of an average power limited amplifier. By using the average power limited amplifier, the signal power is increased as the pulse position order increases, which enhances the bit-error-rate performance. The increased signal power can be converted to an enhanced data rate. We demonstrated that the data rate above 625 Mbps can be increased in every step, as the pulse position order increases in the pulse positioned-differential phase shift keying. The performance enhancement of the proposed technique is theoretically and experimentally demonstrated.

Deep Learning-Based Channel Prediction for LEO Satellite Massive MIMO Communication System

Low Earth orbit (LEO) satellite is one of the most promising infrastructures for realizing next-generation global wireless networks with enhanced data rates. Applying massive multiple-input multiple-output (mMIMO) to LEO satellite communication systems is a novel idea to enhance communication capacity and realize the global high-speed interconnection. However, obtaining effective instantaneous channel state information (iCSI) is challenging due to the time-varying propagation environment and long transmission delay. In this letter, a deep learning (DL)-based CSI prediction scheme is proposed to address channel aging problem by exploiting the correlation of changing channels. Specifically, we design a satellite channel predictor (SCP) that is composed by long short term with memory (LSTM) units. The predictor is first trained by offline learning and then feeds back the corresponding output results online based on the input data to realize channel feature extraction and future CSI prediction in LEO satellite scenarios. Numerical results demonstrate that the proposed DL-based predictor can mitigate the channel aging problem in LEO satellite mMIMO system effectively.

Vision towards 5G: Comparison of radio propagation models for licensed and unlicensed indoor femtocell sensor networks

Sensors and sensor networks are the future of fully automated industry solutions. With more capability and complex machinery, the requirements for sensing in larger factories are critical, considering the data amount, latency, and the number of sensors in operation. Given the excellent time-critical operation, bandwidth and the number of devices connected, the 5G indoor femtocells could prove an excellent option for building industrial sensor grids. For more flexibility in control and reliability, operating the 5G indoor femtocell network in license-free frequency bands could be an alternative to commercial 5G services. The 5G networks incorporate a very dense network of indoor femtocells. The Femtocells also enhance data rates, indoor performance, and coverage area both in residential and industrial environments. Therefore, keeping in view the above-stated actualities, this paper addresses different indoor scenarios for radio wave propagation and simulates several path loss models to calculate the likely and most suitable propagation model for indoor signaling. Multiple models for frequencies in the unlicensed band below 6 GHz and above 6 GHz (licensed) 5G femtocells are discussed in the paper considering the constraints of material types, attenuation due to obstacles, various floors, carrier frequency, and distance from the transmitter. The comparative analysis indicates that the ITU model and Keenan–Motley model give the highest path loss in residential and industrial environments, respectively, while the log-distance model has the lowest path loss in both environments for below 6 GHz frequencies in the unlicensed spectrum. For the above 6 GHz licensed bands, the Alpha Beta Gamma (ABG) model and Path Loss Exponent (CIF) model are observed to have the minimum path loss difference.

MIMO to Enhance the Performance of VLC Systems

In general, visible light communication (VLC) systems run at low data rates. By introducing multiple input and multiple output (MIMO) techniques, service at enhanced data rates can be viable for VLC systems. This work proposes MIMO technique to attain VLC system with high data rates. To attain MIMO method this system includes a number of photodiodes with a narrow field of view (FOV), which highlights the benefit of using MIMO technology in improving the data rate. The results show that using MIMO technique leads to enhance the VLC system when it is compared with the traditional system (without using MIMO). The results show that an improvement in the signal-to-noise ratio (SNR) level, which is the most attempt to determine communication quality, increasing the channel bandwidth and reducing the delay spread are achieved when MIMO technique is used.

Present to Future Antennas for Wireless Communication

Antenna is an essential part of the human life in present world and will be indistinguishable part of the life in coming days. Various generations of antenna designs are required to enhance data rate from 2 kbps to 1 Gbps and higher. Even uplink and downlink delays are dependent on the mobile generations. Modern wireless communication works on the low latency and high data rates for the VOD and BOD services. As, the population of mobile phones demand is growing exponentially, so the higher frequency bands are in demand and compactness of the devices is the prime object along with reliability of the signals/data. Various generations of the antennas are available and have enhancement in applications as well as enhancement in the data rates. Therefore, SISO, MIMO, arrays, MIMO-arrays are available for specific requirements. A thorough literature review has been done to focus the light on the antenna technologies.

Data Rate Enhancement of FSK Transmission Scheme for IEEE 802.15.4-Based Field Area Network

Due to the merits of simple implementation and low-power consumption, frequency shift keying (FSK) is widely used in wireless communication systems for the Internet of things (IoT) such as Wi-SUN field area network (Wi-SUN FAN). To expand IoT capacity or diversify IoT application scenarios, higher data rates are highly expected. In this paper, we propose a novel design of data rate enhancement for IEEE 802.15.4-based 2-FSK transmission scheme which meets the radio requirements defined by ARIB STD-T108 regulation in Japan. Fundamental evaluations and field experiments with developed integrated circuits (ICs) are conducted to evaluate the transmission performance of FSK with enhanced data rate parameters. Results show that with the ICs, the data rate of 600 kbps is achieved with a required input power increase of 7.0 dB compared with the conventional data rate of 100 kbps, and can achieve the packet error rate (PER) smaller than 10% for 250 m on line-of-sight (LoS) routes in urban environments. Moreover, the frequency interference level of the proposed FSK scheme is measured to evaluate the performance in practical radio conditions. Results provide reference for the channel management to operate FSK-based communication systems.

Improved BER Performance Using Novel ELM Based Demodulator for CAP-VLC System

Recent trends in the field of communication science show that most devices are built and governed by Visible Light Communication (VLC) and Light Emitting Diodes (LED). The communication process depends on source characteristics and bandwidth restriction, and effective methods of modulation and demodulation can enhance data rate. Attractive and practical Carrierless Amplitude-Phase (CAP) modulation is used for higher efficiency and easier implementation. However, the performance of the CAP-VLC system gets adversely affected by factors like jamming, scattering, and low sensitivity to receiver signal. Hence, this paper examines the mitigation of available system degrading factors, based on a high-speed, extreme learning machine algorithm (ELM). Prediction analysis and simulation are processed using trained raw dataset for CAP demodulation, to prove the level of performance in terms of accuracy as 92%, under various parametric conditions. This system that is proposed can achieve bit error rate (BER) of 40% to 50% of noise ratio and can be effectively used in sectors like medical health care, banking, and finance.

Power-Aware Coexistence of Wi-Fi and LTE in the Unlicensed Band Using Time-Domain Virtualization

The rapid increase of mobile devices requires more network capacity as limited licensed spectrum is diminishing access to long-term evolution (LTE) users. As increasing licensed spectrum becomes costly, a cost-effective solution that improves network capacity is needed. Another overlooked issue is spectrum efficiency, where unused resources could be allocated to more LTE users. This article proposes two solutions to address network capacity and spectrum efficiency: moving into unlicensed spectrum and implementing wireless resource virtualization. In addition, as these solutions enhance data rate, thus increasing power consumption, this article includes power-aware optimization as a solution. Operating in the unlicensed band poses a challenge as 5-GHz bands are predominately used by Wi-Fi systems. Based on this challenge, we are proposing a time-sharing wireless resource virtualization (WRV)-based LTE/Wi-Fi coexistence solution that considers joint resource/access point (AP) allocation and power control problems for both technologies. Accordingly, we formulate a mixed-integer nonlinear programming problem and solve using the Lagrangian dual decomposition. We also propose low-complexity heuristics to solve these problems. Results show that the coexistence of Wi-Fi and LTE can be achieved in the unlicensed band with improved power savings using virtualization. Moreover, there is little to no difference in power savings in heterogeneous-traffic scenarios as the algorithm prioritizes maximizing rate to minimizing power.

Simultaneous Wireless Information and Power Transfer With Cooperative Relaying for Next-Generation Wireless Networks: A Review

Wireless Power Transfer (WPT) is an innovative technology employed for enhancing the energy sustainability of wireless devices with a limited life span. The idea of integrating WPT in wireless communication leads to the idea of Simultaneous Wireless Information and Power Transfer (SWIPT) that transfers information and power to wireless devices simultaneously, thereby resulting in a drastic increase in spectral efficiency of the network. SWIPT aided Cooperative Relaying (CoR) has emerged as a new trend for Fifth Generation (5G) and Beyond 5G (B5G) systems owing to the rapidly increasing challenges faced by these networks. Cooperative relaying combined with SWIPT can be helpful in overcoming the rising demands of next generation wireless networks by providing an enhanced data rate, low latency, shorter coverage, wide spread connectivity of massive number of devices along with energy-efficiency. This article provides a comprehensive review of SWIPT technology that enables the use of CoR networks for 5G and B5G mobile networks including the significance, technologies, and protocols which can be applied. This article also examines the deployment of cooperative SWIPT involving a single relay, multiple relays and optimal relay selection, multi antenna systems and optimal beamforming. SWIPT under the influence of Hardware Impairments (HI), imperfect Channel State Information (CSI), non-linear energy harvesting models, Intelligent Reconfigurable Surface (IRS), massive MIMO, massive access for the Internet of Things (IoT) has been discussed in detail. Meanwhile, this study discusses key challenges being faced in the implementation of SWIPT for future wireless networks that need to be addressed efficiently.

BER Assessment of OFDM System Augmented with MRC Technique under the Effect of CFO

Orthogonal frequency division multiplexing (OFDM) and Multiple input multiple output (MIMO) is capable to enhance data rates over the radio channel providing enough protection against the destructions caused in the path of the signal. But the bit error rate (BER) of the systems degrades due to the presence of Carrier frequency offset (CFO). The presence of CFO results in generation of Inter Carrier Interference (ICI) which in turn results in loss of orthogonality between the sub carriers. The significance of MIMO-OFDM is due to orthogonality among the carriers which is at stake due to presence of CFO. In this paper, the performance of the MIMO–OFDM system is analyzed over the Rayleigh channel for 2 and 3-array antennas under the effect of CFO with Maximal Ratio Combining (MRC) diversity technique at receiver section. It is observed from simulations that the MIMO-MRC reduces the BER and improves the overall performance of the system which is very much useful to combat against the effects of CFO.

MIMO Self-Heterodyne OFDM Using Band Selection Technique.

The 5G technology is a promising technology to cope with the increasing demand for higher data rate and quality of service. In this paper, two proposed techniques are implemented for multiple input multiple output (MIMO) self-heterodyne OFDM system to enhance data rate and minimize the bit error rate (BER). In both of the two proposed techniques, Band Selection (BS) approach is used, once with Space Time Block Coded (STBC) for the first proposed technique (BS- STBC), and once again with Frequency Space Time Block Coded (FSTBC) for the second proposed technique (BS-FSTBC). The use of the BS in the proposed techniques helps to choose the sub-band with better subchannels gains for sending the information and consequently, minimize the BER. Moreover, the use of the FSTBC instead of STBC helps to use the spectral efficiently and hence increase data rate. The simulation results show that the proposed techniques BS-STBC and BS-FSTBC, for the MIMO self-heterodyne OFDM system, provide a great enhancement in the BER performance when compared to the conventional techniques. Moreover, the simulation results show that the first proposed technique BS-FSTBC outperform the second propose technique BS-STBC in term of the BER performance.

A Framework for a Low Power on Body Real-Time Sensor System Using UHF RFID

This article details the use of an acceleration measuring system which can transmit in real-time sensor data through UHF RFID to a computer. Existing methods of real-time transmission of sensor data rely on power-intensive Bluetooth or Wi-Fi technologies which result in devices that require large bulky batteries, this causes the overall device size to be high and thus can potentially cause issue during use. By harnessing status flags within a specific UHF RFID chip and custom reader software conforming to the EPC GEN2 standard, continuous streaming data rates of 5.2KBps were achievable. These enhanced data rates were shown to be reliable up to a range of 2.4M with above 99.99% data integrity. The power consumption of this methodology was found to be below 2mW during full power continuous transmission. In summary this article outlines and lays the foundation for the use of UHF RFID to deliver sub-2mW low latency, high reliability streaming methods within the domain of on body transmission.