Editorial: Special Issue “Antenna Design for 5G and Beyond”

Note: In lieu of an abstract, this is an excerpt from the first page.The demand for high data rate transfer and large capacities of traffic is continuously growing as the world witnesses the development of the fifth generation (5G) of wireless communications with the fastest broadband speed yet and low latency [...

Internal insulation condition identification for high-voltage capacitor voltage transformers based on possibilistic fuzzy clustering

The internal insulation condition of capacitor voltage transformers (CVTs) is a key influence factor that affects their measurement performance and safe operation. However, the internal insulation would age along with long-time operation and degrade due to environmental factors, and once the insulation degradation grows, serious damage and even explosion may happen in CVTs; hence, it is necessary to monitor the internal insulation condition of CVTs, and the fault type and fault degree need to be identified. In this paper, a data-driven internal insulation condition identification method for CVTs is proposed. Both the amplitude and phase of the output voltage of CVTs are collected, and then, recognition models based on the combination of the output voltages and distribution topology of CVTs in substations are built. A possibilistic fuzzy clustering method is used to monitor the internal insulation condition of CVTs, and different types and different degrees of insulation faults could be identified effectively. Finally, the proposed method is verified in several cases; not only the preset typical faults in the method could be identified effectively but also the faults beyond the preset faults could be diagnosed

Editorial on Antennas

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Accelerated Diagnosis of Novel Coronavirus (COVID-19)—Computer Vision with Convolutional Neural Networks (CNNs)

Early detection and diagnosis of COVID-19, as well as exact separation of non-COVID-19 cases in a non-invasive manner in the earliest stages of the disease, are critical concerns in the current COVID-19 pandemic. Convolutional Neural Network (CNN) based models offer a remarkable capacity for providing an accurate and efficient system for detection and diagnosis of COVID-19. Due to the limited availability of RT-PCR (Reverse transcription-polymerase Chain Reaction) test in developing countries, imaging-based techniques could offer an alternative and affordable solution to detect COVID-19 symptoms. This case study reviewed the current CNN based approaches and investigated a custom-designed CNN method to detect COVID-19 symptoms from CT (Computed Tomography) chest scan images. This study demonstrated an integrated method to accelerate the process of classifying CT scan images. In order to improve the computational time, a hardware-based acceleration method was investigated and implemented on a reconfigurable platform (FPGA). Experimental results highlight the difference between various approximations of the design, providing a range of design options corresponding to both software and hardware. The FPGA based implementation involved a reduced pre-processed feature vector for the classification task which is a unique advantage for this particular application. To demonstrate the applicability of the proposed method, results from the CPU based classification and the FPGA were measured separately and compared retrospectively

On the Fast DHT Precoding of OFDM Signals over Frequency-Selective Fading Channels for Wireless Applications

Due to high power consumption and other problems, it is unlikely that orthogonal frequency-division multiplexing (OFDM) would be included in the uplink of the future 6G standard. High power consumption in OFDM systems is motivated by the high peak-to-average power ratio (PAPR) introduced by the inverse Fourier transform (IFFT) processing kernel in the time domain. Linear precoding of the symbols in the frequency domain using discrete Hartley transform (DHT) could be used to minimise the PAPR problem, however, at the cost of increased complexity and power consumption. In this study, we minimise the computation complexity of the DHT precoding on OFDM transceiver schemes and the consequent power consumption. We exploit the involutory properties of the processing kernels to process the DHT and IFFT as a single-processing block, thus reducing the system complexity and power consumption. These also enable a novel power-saving receiver design. We compare the results to three other precoding schemes and the standard OFDM scheme as the baseline; while improving the power consumption efficiency of a Class-A power amplifier from 4.16% to 16.56%, the bit error ratio is also enhanced by up to 5 dB when using a 1/2−rate error-correction coding and 7 dB with interleaving

6G Wireless Communication Systems: Applications, Opportunities and Challenges

As the technical specifications of the 5th Generation (5G) wireless communication standard are being wrapped up, there are growing efforts amongst researchers, industrialists and standardisation bodies on the enabling technologies of a 6G standard or the so-called Beyond 5G (B5G) one. Although the 5G standard has presented several benefits, there are still some limitations within it. Such limitations have motivated the setting up of study groups to determine suitable technologies that should operate in the year 2030 and beyond, i.e., after 5G. Consequently, this Special Issue on Future Internet concerning what possibilities lie ahead for a 6G wireless network includes four high-quality research papers (three of which are review papers with over 412 referred sources and one regular research). This editorial piece summarises the major contributions of the articles and the Special Issue, outlining future directions for new research. The 5th Generation (5G) network standard is the latest wireless telecommunication network standard for data transfer from one location to another, which is presently being rolled out globally. In developed countries, non-standalone 5G network examples were deployed in a limited number of cities (e.g., London, Manchester, and Edinburgh in the UK) to learn more about their real-world performances; these were non-standalone because they used the existing 4G network infrastructure. Afterwards, the lessons operators learned from the 5G non-standalone deployments were used to revise and improve the technologies. It is these revised systems that are presently being deployed around the world. It has been said that all the technologies that could not be incorporated into the 5G standard by the end of 2020 will be considered for the Beyond 5G (B5G) network standard [1]. In the literature, the B5G network is also referred to as the 6th Generation (6G) network. This editorial piece summarises th

Energy Efficiency and Throughput Optimization in 5G Heterogeneous Networks

Device to device communication offers an optimistic technology for 5G network which aims to enhance data rate, reduce latency and cost, improve energy efficiency as well as provide other desired features. 5G heterogeneous network (5GHN) with a decoupled association strategy of downlink (DL) and uplink (UL) is an optimistic solution for challenges which are faced in 4G heterogeneous network (4GHN). Research work presented in this paper evaluates performance of 4GHN along with DL and UL coupled (DU-CP) access scheme in comparison with 5GHN with UL and DL decoupled (DU-DCP) access scheme in terms of energy efficiency and network throughput in 4-tier heterogeneous networks. Energy and throughput are optimized for both scenarios i.e. DU-CP and DU-DCP and the results are compared. Detailed performance analysis of DU-CP and DU-DCP access schemes has been done with the help of comparisons of results achieved by implementing genetic algorithm (GA) and particle swarm optimization (PSO). Both these algorithms are suited for the non linear problem under investigation where the search space is large. Simulation results have shown that the DU-DCP access scheme gives better performance as compared to DU-CP scheme in a 4-tier heterogeneous network in terms of network throughput and energy efficiency. PSO achieves an energy efficiency of 12 Mbits/joule for DU-CP and 42 Mbits/joule for DU-DCP, whereas GA yields an energy efficiency of 28 Mbits/joule for DU-CP and 55 Mbits/joule for DU-DCP. Performance of the proposed method is compared with that of three other schemes. The results show that the DU-DCP scheme using GA outperforms the compared methods

An Acoustic Sensor for Combined Sewer Overflow (CSO) Screen Condition Monitoring in a Drainage Infrastructure

Combined sewer overflow structures (CSO) play an important role in sewer networks. When the local capacity of a sewer system is exceeded during intense rainfall events, they act as a “safety valve” and discharge excess rainfall run-off and wastewater directly to a natural receiving water body, thus preventing widespread urban flooding. There is a regulatory requirement that solids in CSO spills must be small and their amount strictly controlled. Therefore, a vast majority of CSOs in the UK contain screens. This paper presents the results of a feasibility study of using low-cost, low-energy acoustic sensors to remotely assess the condition of CSO screens to move to cost-effective reactive maintenance visits. In situ trials were carried out in several CSOs to evaluate the performance of the acoustic sensor under realistic screen and flow conditions. The results demonstrate that the system is robust within ±2.5% to work successfully in a live CSO environment. The observed changes in the screen condition resulted in 8–39% changes in the values of the coefficient in the proposed acoustic model. These changes are detectable and consistent with observed screen and hydraulic data. This study suggested that acoustic-based sensing can effectively monitor the CSO screen blockage conditions and hence reduce the risk of non-compliant CSO spills

Computer Vision Based Kidney’s (HK-2) Damaged Cells Classification with Reconfigurable Hardware Accelerator (FPGA)

In medical and health sciences, detection of cell injury plays an important role in diagnosis, personal treatment and disease prevention. Despite recent advancements in tools and methods for image classification, it is challenging to classify cell images with higher precision and accuracy. Cell classification based on computer vision offers significant benefits in biomedicine and healthcare. There have been studies reported where cell classification techniques have been complemented by Artificial Intelligence-based classifiers such as Convolutional Neural Networks. These classifiers suffer from the drawback of the scale of computational resources required for training and hence do not offer real-time classification capabilities for an embedded system plat-form. Field Programmable Gate Arrays (FPGAs) offer the flexibility of hardware reconfiguration and have emerged as a viable platform for algorithm acceleration. Given that the logic resources and on-chip memory available on a single device are still limited, hardware/software co-design is proposed where image pre-processing and network training was performed in software and trained architectures were mapped onto an FPGA device (Nexys4DDR) for real-time cell classification. This paper demonstrates that the embedded hardware-based cell classifier performs with almost 100% accuracy in detecting different types of damaged kidney cells

A Novel Meander Bowtie-Shaped Antenna with Multi-Resonant and Rejection Bands for Modern 5G Communications

To support various fifth generation (5G) wireless applications, a small, printed bowtie-shaped microstrip antenna with meandered arms is reported in this article. Because it spans the broad legal range, the developed antenna can serve or reject a variety of applications such as wireless fidelity (Wi-Fi), sub-6 GHz, ultra-wideband (UWB) 5G communications due to its multiband characterization and optimized rejection bands. The antenna is built on an FR-4 substrate and powered via a 50-Ω microstrip feed line linked to the right bowtie’s side. The bowtie’s left side is coupled via a shorting pin to a partial ground at the antenna back side. A gradually increasing meandering microstrip line connected to both sides of the bowtie to enhance the rejection and operating bands. The designed antenna has seven operating frequency bands of (2.43 – 3.03) GHz, (3.71 – 4.23) GHz, (4.76 – 5.38) GHz, (5.83 – 6.54) GHz, (6.85 – 7.44) GHz, (7.56 – 8.01) GHz and (9.27 – 13.88) GHz. The simulated scattering parameter 11 reveals six rejection bands with percentage bandwidth of 33.87%, 15.73%, 11.71, 7.63%, 6.99%, 12.22% respectively. The maximum gain of the proposed antenna is 4.46 dB. The suggested antenna has been built, and the simulation and measurement results are very similar. The reported antenna is expanded to a four-element design to investigate their MIMO characteristics