Generation Wireless Technology Research Articles

Research challenges in 5G communication technology: Study

In this article, a study have been done for 5th generation wireless technology and it is the key to enable a wide range of application scenarios in order to modernize the existing the technology. It has a lot of social impact as well as economical impact. This paper is going to describe the evolution of 5G technology and it’s advantages and disadvantages and also going to describe the architecture of 5G, currently there are some field experiments are going on and in this paper we also going to discuss the capabilities and challenges which 5G need to face. In particular this paper creates complete awareness of the 5G technology.

5G Wireless Technology

This 5G stands for fifth generation wireless technology. It is the latest version of cellular technology that has main features: Grater speed, lower latency, and ability to connect a lot more devices simultaneously. A commercial 5G wireless network is expected to be deployed by 2021.

A REVIEW ON 5G WIRELESS NETWORK IMPLEMENTATION STRATEGIES IN NIGERIA

The 5G networks stand for fifth generation mobile technology and can outperform earlier versions of wireless communication technology. The new technology provides diverse abilities and encourages full networking among countries globally. Fifth Generation (5G) wireless communication network development was an initiative in furtherance to the current Fourth Generation (4G) wireless communication network technology. The 5G networks for future applications in all domains provide prospects for a fully connected society. The proliferation of all connectivity between the devices provides a broader range of new governance, business structures, health care delivery, Economic growth and insecurity reduction which subsequently paves a path towards different industry profiles, such as energy, Communication and manufacturing sectors. This paper discusses the Concept of 5G Network, 5G network implementation strategies and technology requirements, deployment challenges as well as suggestions on the way forward based on Nigerian context

Retracted: An improvement in the teaching of college English writing and communication tools for fifth generation network: Comparative study

SummaryThere are many disadvantages in traditional college English writing teaching in wireless network. Consequently, the research and development for the fifth generation (5G) systems have already been started. It has a close‐to‐wide look of European 5G network. Literature reviews are limited to recent thematic IEEE Communications Magazine 5G issues and related white papers from a variety of sources. 5G network is the fifth generation wireless network communication technology for digital cellular networks, which supports a large amount of data traffic and massive number of wireless connections. In order to accomplish higher order teaching skills, the application of latest technology must be integrated into the curriculum. The rapid development of network communication technology provides a new perspective for English writing teaching, so teachers should make full use of network resources, especially 5G network communication tools, to improve English writing teaching. By exploring this new mode of network English writing teaching, this paper argues that network communication tools can further resource sharing, strengthen the interaction between teachers and students, and comprehensively improve their performance in English writing. In this study, 5G network‐based English writing and communication tools are used to improve the performance.

Beamforming and Power Optimization for Physical Layer Security of MIMO-NOMA Based CRN Over Imperfect CSI

The physical layer security (PLS) has become crucial in the fifth generation (5G) wireless technology where non-orthogonal multiple-access (NOMA) plays an essential role for sharing the spectrum among multiple users. Multiple-input multiple-output (MIMO)-NOMA based cognitive radio network (CRN) enhances the spectral-efficiency at the cost of PLS. In this paper, a transmit-zero-forcing beamforming (ZFBF) technique with signal alignment is proposed to improve the PLS for MIMO-NOMA based CRN when perfect channel state information (CSI) is available at the base station (BS). In this study, a generalized cellular model with multi-cell is considered where each cluster is formed with a primary user (PU) and a secondary user (SU) to adopt the CRN. The locations of PU and SU are kept arbitrary within the cells. We also propose an eigen beamforming technique to improve the PLS for MIMO-NOMA based CRN when the imperfect CSI is available at the BS. For both beamforming techniques, optimum power allocation algorithms are developed for further enhancement of the PLS. Finally, a closed-form expression of the secrecy outage probability for the Nakagami-m fading channels is derived and compared with simulation results and other existing techniques.

5G and its impact on environment, biodiversity and human health: An overview

5G stands for the fifth generation of wireless technology. Millimetre waves are a higher frequency wavelength than the radio wavelength generally used today for transmission of information through this wireless technology. Both the wireless infrastructure of today and the modern era of 5G are seen as an asset in the intelligent system. It has been widely implemented throughout the world without discuss its adverse effects on future generations. It is argued that the addition of this added high-frequency 5G radiation to an already complex mix of lower frequencies, will contribute to a negative public health outcome both from both physical and mental health perspectives. This paper presents the adverse effects of 5G radiations on human health, plant and ecosystem. The thermal factors are also discussed in this article.

Coordinates-Based Resource Allocation Through Supervised Machine Learning

Appropriate allocation of system resources is essential for meeting the increased user-traffic demands in the next generation wireless technologies. Traditionally, the system relies on channel state information (CSI) of the users for optimizing the resource allocation, which becomes costly for fast-varying channel conditions. In such cases, an estimate of the terminals’ position information provides an alternative to estimating the channel condition. In this work, we propose a coordinates-based resource allocation scheme using supervised machine learning techniques, and investigate how efficiently this scheme performs in comparison to the traditional approach under various propagation conditions. We consider a simple system setup as a first step, where a single transmitter serves a single mobile user. The performance results show that the coordinates-based resource allocation scheme achieves a performance very close to the CSI-based scheme, even when the available user’s coordinates are erroneous. The performance is quite consistent, especially when complex learning frameworks like random forest and neural network are used for resource allocation. In terms of applicability, a training time of about 4 s is required for coordinates-based resource allocation using random forest algorithm, and the appropriate resource allocation is predicted in less than 90 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula> with a learnt model of size < 1 kB.

Millimeter Wave High-Gain Antenna Array for Wireless Applications

With the growing demand of mobile and wireless users, there is a need to switch from fourth generation (4G) to fifth generation (5G) wireless technology for better data rate, coverage, and spectral efficiency. In 4G technology, data rate is around 1.0 Gbps, but in 5G technology data rate is more than 1.0 Gbps to reduce delay and latency. A properly implemented array can enhance the gain in 5G technology. A 2:1 VSWR-based array antenna with a single element is designed on the Rogers RT Duroid 5880 substrate to cover the 27.06–28.35 GHz frequency band for 5G application. The dimension of the substrate is 51.44 × 18.34 mm2. The approximate size of each patch is 3.8 × 4.5 mm2. The proposed array antenna has 16.07 dBi gain, 93.5% radiation efficiency, and 93.5% total efficiency at the 28.0 GHz resonant frequency. MEG for Gaussian medium with XPR = 0 dB is in the range of −9.85– −13.05 dB, while with XPR = 6.0 dB, MEG for Gaussian medium lies in the range −7.50– −10.71 dB.

Review on next generation wireless power transmission technology for implantable biomedical devices

Wireless power transmission (WPT) is a promising technology that causes drastic changes in the field of biomedical, especially in medical implantable devices such as pacemakers, cardiac defibrillator and cochlear implants. The traditional implantable biomedical devices get power supply from batteries or lead wires through the skin, which not only increases the burden on the patient, but also increases the pain and risk of surgery. To reduce the cost of biomedical devices, risk of wire snapping, periodic surgery to replace the batteries and wireless delivery of energy to these devices is desirable. WPT is a promising technology capable of addressing limitations in implantable devices. This technology not only negates the risk of infection due to cables passing through the skin but also negates need for recurrent surgeries to replace batteries and minimises the size of the device by excising bulky components such as batteries. This paper provides an overview of wireless power transmission history, the basic principle of WPT and their recent research and developments in implantable biomedical applications.

Review on next generation wireless power transmission technology for implantable biomedical devices

Wireless power transmission (WPT) is a promising technology that causes drastic changes in the field of biomedical, especially in medical implantable devices such as pacemakers, cardiac defibrillator and cochlear implants. The traditional implantable biomedical devices get power supply from batteries or lead wires through the skin, which not only increases the burden on the patient, but also increases the pain and risk of surgery. To reduce the cost of biomedical devices, risk of wire snapping, periodic surgery to replace the batteries and wireless delivery of energy to these devices is desirable. WPT is a promising technology capable of addressing limitations in implantable devices. This technology not only negates the risk of infection due to cables passing through the skin but also negates need for recurrent surgeries to replace batteries and minimises the size of the device by excising bulky components such as batteries. This paper provides an overview of wireless power transmission history, the basic principle of WPT and their recent research and developments in implantable biomedical applications.

Possible adoption of various machine learning techniques in cognitive radio - a survey

The concept of cognitive radio (CR) system is the need for next generation wireless communication technology in terms of providing intelligence and superior performance to a wireless device. The CR is mainly an intelligent system which is aware of its environment and is well capable to adapt in accordance with the changing environment and user needs. The concept of adaptation of the communication system can be realised well with machine learning capability inculcated within the system. It is a well-known fact that, the key strengths of any machine learning paradigm is its ability to adapt with respect to the dynamic changing system parameters. In this paper, an attempt has been made to compile various applications of machine learning techniques for different activities of CR cycle. Further, this note reviews the work on development of machine learning techniques for spectrum sensing of CR in order to make the CR system as a whole practically feasible and robust, thus mitigating its existing computational limitations due to the use of conventional techniques.

Possible adoption of various machine learning techniques in cognitive radio - a survey

The concept of cognitive radio (CR) system is the need for next generation wireless communication technology in terms of providing intelligence and superior performance to a wireless device. The CR is mainly an intelligent system which is aware of its environment and is well capable to adapt in accordance with the changing environment and user needs. The concept of adaptation of the communication system can be realised well with machine learning capability inculcated within the system. It is a well-known fact that, the key strengths of any machine learning paradigm is its ability to adapt with respect to the dynamic changing system parameters. In this paper, an attempt has been made to compile various applications of machine learning techniques for different activities of CR cycle. Further, this note reviews the work on development of machine learning techniques for spectrum sensing of CR in order to make the CR system as a whole practically feasible and robust, thus mitigating its existing computational limitations due to the use of conventional techniques.

Technological Leadership and 5G Patent Portfolios: Guiding strategic policy formulation1 and licensing decisions

Fifth generation (5G) wireless technology is beginning to appear commercially after years of development. Patent licensing is an important element of how firms will capture value from the technology they've invested in because many firms own relevant technologies. Yet analyses of patent value for purposes such as cross-national comparisons tend to be superficial, failing to account for substantial differences in the quality and value of specific patents. There is no single accurate measure for the commercial significance of a patent portfolio. Proxies such as family counts, forward cites, and geographic coverage each have their flaws. Existing licensing deals can and should be used when available. Another alternative is expert appraisal of key patents. And another is the use of econometric techniques to discern how consumers value the patented technology.

Radio Access Technology characterisation through object detection

Radio Access Technology (RAT) classification and monitoring are essential for efficient coexistence of different communication systems in shared spectrum. Shared spectrum, including operation in license-exempt bands, is envisioned in the fifth generation of wireless technology (5G) standards (e.g., 3GPP Rel. 16). In this paper, we propose a Machine Learning (ML) approach to characterise the spectrum utilisation and facilitate the dynamic access to it. Recent advances in Convolutional Neural Networks (CNNs) enable us to perform waveform classification by processing spectrograms as images. In contrast to other ML methods that can only provide the class of the monitored RATs, the solution we propose can recognise not only different RATs in shared spectrum, but also identify critical parameters such as inter-frame duration, frame duration, centre frequency, and signal bandwidth by using object detection and a feature extraction module to extract features from spectrograms. We have implemented and evaluated our solution using a dataset of commercial transmissions, as well as in a Software-Defined Radio (SDR) testbed environment. The scenario evaluated was the coexistence of WiFi and LTE transmissions in shared spectrum. Our results show that our approach has an accuracy of 96% in the classification of RATs from a dataset that captures transmissions of regular user communications. It also shows that the extracted features can be precise within a margin of 2%, and can detect above 94% of objects under a broad range of transmission power levels and interference conditions.

Carrier aggregation‐enabled non‐orthogonal multiple access approach towards enhanced network performance in 5G Ultra‐Dense Networks

SummaryThe need for fifth generation (5G) wireless technology to meet stringent demands on high throughput, ultra low latency, high reliability, massive connectivity, and fairness among users has seriously constrained the limited radio spectrum. Non‐orthogonal multiple access (NOMA) has been identified as one of the promising enabling radio access techniques to solve this problem. The basic principle of NOMA is the ability to serve multiple users in the same time and frequency resources but differentiated by their power domains. However, the inherent power‐domain multiplexing requires channel gain disparity between the strong and weak users, thereby reducing the sum‐rate gain of the network. In this paper, we propose NOMA scheme, integrated with carrier aggregation (CA) to further increase the bandwidth and data rate of users. Simulation results show considerable improvement in terms of throughput, energy efficiency, and fairness among users.

Energy detection investigation over composite [formula omitted]/inverse-gamma wireless channel

Proper utilization of the unused spectrum hole facilitates the expanding necessity of the elevated data rate in the upcoming 5th Generation (5G) wireless communication technology. Energy detection is a widely worked technique to fulfill this requirement with minimal time, cost, and efforts. With this motivation, this work develops an analytical framework to analyze the functioning of an energy detector (ED) based cognitive radio (CR) system over a composite fading distribution, characterized by α-μ/Inverse-Gamma (I-Gamma) composite fading channel. To begin with, closed-form expressions for the probability density function (PDF) are developed for single-input single-output (SISO) and single-input multiple-output (SIMO) channels. Exploiting these expressions, analytical results for the average probability of detection (PD) and the average area under the receiver operating characteristic curve (AUC) are obtained. Further, the breakdown is extended in determining average PD under high and very low signal-to-noise ratio (SNR) regime. Finally, the results are utilized as an application in analyzing the cooperative spectrum sensing (CSS) under different shadowing conditions. The optimization of the number of cognitive radios is carried out using the r-out-of-N voting rule. The validation of all the proposed results and their accuracy is determined using the Monte-Carlo simulations.

Energy-Efficient Resource Allocation With Flexible Frame Structure for Hybrid eMBB and URLLC Services

The key objective of the fifth generation (5G) wireless technology is to support services with highly diverse requirements, which necessitates the specification of flexible numerology and frame structure for radio resource allocation in 5G new radio (NR). In this article, flexible 2-dimensional resource allocation is investigated to exploit the frequency and time diversities of the resource grid, and eventually maximize the overall system energy efficiency (EE) in the scenario where enhanced mobile broadband (eMBB) and ultra-reliable and low latency communication (URLLC) services coexist. A new definition of EE is proposed to capture and fulfill the heterogeneous quality-of-service (QoS) requirements of eMBB and URLLC services. By first sliding a window on the resource grid to determine the candidate resource pool, and then allocating resource blocks (RBs) therein by leveraging linear programming (LP) relaxation, we propose a sliding window (SW) based algorithm with a low complexity for the NP-hard EE optimization problem. In addition, we also analyze the achievable EE performance of the proposed algorithm to demonstrate its scalability with respect to the grid sizes and the maximum transmit power to provide an in-depth understanding. Numerical results show that the proposed algorithm can bring about as much as 16.7% power consumption reduction, and improve EE by about 29.3% compared to other baseline systems.

Ultra‐dense LoRaWAN: Reviews and challenges

Internet of Things (IoT) is one of the most cited terms within the communication research communities. Next generation wireless networks technologies are expected to have massive-connections of tens of billions of devices. Such a huge number of devices raised a number of concerns in regards to how much accessible resources are available and what are the best technologies for managing those resources, all in order to avoid shutdowns/collapses in every means. In terms of wireless networks, and in regards to energy being the backbone of IoT devices, Low Power Wide Area Networks (LPWAN) technologies are considered to be a potential solution for IoT applications. In particular, this study reviews Long-Range (LoRa) technology and advances in the literature of LoRaWAN protocol to date. Furthermore, it discusses the challenges in LoRaWAN and diverts the attention towards applying Ultra-Dense Network concept on LPWAN.

Enhancing live virtual machine migration process via optimized resource allocation in next generation mobile edge network: A hybrid evolutionary approach

SummaryThe evolution of 5th Generation wireless technology introduced Mobile Edge Computing, where edge servers are placed at the edge of the network, and are associated with evolved Node Base Stations (eNBs). This enables mobile users to offload their resource‐intensive tasks to these servers and improve network performance by reducing end‐to‐end delay. However, frequent user mobility leads to frequent re‐planning of network and increases network load. This demands dynamic Virtual Machine (VM) migration in Mobile Edge paradigm for an improved Quality of Service (QoS). For an enhanced VM migration process, an optimal pair of migrating VMs and destination edge servers needs to be chosen. In this paper, we propose an optimized decision‐making policy that chooses such optimal pairs. Several decision parameters such as average wait time, processing delay, migration delay, transmission power, and processing power are modeled. A profit function is developed using these modeled decision parameters that chooses the optimal pairs. This function is maximized using the proposed hybrid evolutionary algorithm, which combines the advantages of PSO and GA. The pairs are chosen in such a manner, that the selection guarantees high network throughput, reduced service delay, and energy consumption which is reflected in the simulation.

On the Probability of Line-of-Sight in Urban Environments

Line-of-Sight communication will play a major role in the next generation of wireless technologies; from UAV-to-UAV networks, to land mobile satellite services, and mmWave cellular coverage. In this letter we present a model for predicting the geometric line-of-sight probability in different urban environments formulated based on stochastic geometry. The model combines simplicity of formulation with high degree of accuracy when compared to real-life geographic data. For two points in the 3D space, it takes the height of each point and the distance between them as input, also it takes 4 other simple parameters that describe the geometric properties of the underlying environment. Based on these inputs, the proposed model produces consistent analytic results aligned with ray-tracing of the geographic data.