Technical appraisal of solar home systems in Bangladesh: a field investigation

Solar Home System (SHS) based rural electrification has experienced a considerable growth in Bangladesh since the start of the Rural Electrification and Renewable Energy Development Project (REREDP) in 2003. The initial target of 50,000 SHS installations in off-grid areas was achieved within 2.5 years, 3 years ahead of schedule. After achieving a revised target of 200,000 SHSs, ahead of schedule in early 2009, a new target of 1 million SHS installations by 2012 was set. The installation of about 0.5 million systems by March 2010 indicates that the current target may well be achieved before the deadline. The size of the SHS market and its impact on the regeneration of the rural economy make it necessary to investigate the quality and reliability of the installed SHSs, if the continued success of the initiative is to be maintained. This paper reports on the findings from a field-based technical appraisal of SHS installations in Bangladesh. Sixty geographically dispersed installation sites were visited. Physical characteristics of the SHSs and their system components were tested to ascertain compliance with and deviations from the approved specifications. Despite the overwhelming success of the REREDP project, the study revealed various shortcomings. Notable among these are: incompatible and sub-optimal component configurations, faulty installations and a lack of effective quality assurance mechanism. The findings are contextualized and the ways to address the identified shortcomings are discussed

A New Beamforming Approach Using 60 GHz Antenna Arrays for Multi-Beams 5G Applications

Recent studies and research have centred on new solutions in different elements and stages to the increasing energy and data rate demands for the fifth generation and beyond (B5G). Based on a new-efficient digital beamforming approach for 5G wireless communication networks, this work offers a compact-size circular patch antenna operating at 60 GHz and covering a 4 GHz spectrum bandwidth. Massive Multiple Input Multiple Output (M−MIMO) and beamforming technology build and simulate an active multiple beams antenna system. Thirty-two linear and sixty-four planar antenna array configurations are modelled and constructed to work as base stations for 5G mobile communication networks. Furthermore, a new beamforming approach called Projection Noise Correlation Matrix (PNCM) is presented to compute and optimise the fed weights of the array elements. The key idea of the PNCM method is to sample a portion of the measured noise correlation matrix uniformly in order to provide the best representation of the entire measured matrix. The sampled data will then be utilised to build a projected matrix using the pseudoinverse approach in order to determine the best fit solution for a system and prevent any potential singularities caused by the matrix inversion process. The PNCM is a low-complexity method since it avoids eigenvalue decomposition and computing the entire matrix inversion procedure and does not require including signal and interference correlation matrices in the weight optimisation process. The suggested approach is compared to three standard beamforming methods based on an intensive Monte Carlo simulation to demonstrate its advantage. The experiment results reveal that the proposed method delivers the best Signal to Interference Ratio (SIR) augmentation among the compared beamformers

A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics

This is an accepted manuscript of an article published by IEEE in IEEE Transactions on Intelligent Transportation Systems on 04/01/2022. Available online: https://doi.org/10.1109/TITS.2021.3138255 The accepted version of the publication may differ from the final published version.The dependency on vehicles is increasing tremendously due to its excellent transport capacity, fast, efficient, flexible, pleasant journey, minimal physical effort, and substantial economic impact. As a result, the demand for smart and intelligent feature enhancement is growing and becoming a prime concern for maximum productivity based on the current perspective. In this case, the Internet of Everything (IoE) is an emerging concept that can play an essential role in the automotive industry by integrating the stakeholders, process, data, and things via networked connections. But the unavailability of intelligent features leads to negligence about proper maintenance of vehicle vulnerable parts, reckless driving and severe accident, lack of instructive driving, and improper decision, which incurred extra expenses for maintenance besides hindering national economic growth. For this, we proposed a conceptual framework for a central VHMS exploiting IoE-driven Multi-Layer Heterogeneous Networks (HetNet) and a machine learning technique to oversee individual vehicle health conditions, notify the respective owner driver real-timely and store the information for further necessary action. This article transparently portrayed an overview of central VHMS and proposed the taxonomy to achieve such an objective. Subsequently, we unveiled the framework for central VHMS, IoE-driven Multi-tire HetNet, with a secure and trustworthy data collection and analytics system. Finally, anticipating this proposition’s outcome is immense in the automotive sector. It may motivate the researcher to develop a central intelligent and secure vehicular condition diagnostic system to move this sector towards Industry 4.0.The authors would like to thank University Malaysia Pahang for providing the laboratory facilities and financial support under the University FLAGSHIP Research Grants (Project number RDU192203), International Matching Grant (No. RDU192704), and Postgraduate Research Scheme Grant (No. PGRS200325)

Angle and Time of Arrival Characteristics of 3D Air-to-Ground Radio Propagation Environments

A three dimensional (3D) geometric channel model is proposed for ground-to-air (G2A) and air-toground (A2G) communication links. A low-elevated ground station (GS) and a high-elevated air station (AS) are taken at foci points of a virtual bounding ellipsoid corresponded from known knowledge of delay of longest propagation path. The effective region of scatterers around the GS is designed on the basis of this ellipsoid truncated by the average rooftop level (or average height of sea waves) and ground plane. Closedform expressions for joint and marginal probability density functions (PDFs) of angle of arrival (AoA) observed at AS and GS in correspondence with azimuth and elevation angles are derived. Furthermore, closed-form expressions for density of energy with respect to the delay of arriving multipath waves corresponded from both the elevation and azimuth AoA are derived independently when observed from either end of the communication link. Moreover, effect of different physical parameters of the channel on distribution of energy in angular and temporal domains is presented. The comparison of analytical results with results of a notable model is also presented. In order to verify the derived analytical expressions, a comparison of analytical results with the performed simulation results is presented, which shows a good match

Location-aware cooperative spectrum sensing within cognitive radio networks

Spectrum sensing is the key enabling technology for cognitive radio networks. The main objective of spectrum sensing is to provide more spectrum access opportunities to cognitive radio users without interfering with the operations of the licensed network. Spectrum sensing decisions can lead to erroneous sensing due to fading, shadowing and other interferences caused by either terrain inconsistency or dense urban structure. In order to improve spectrum sensing decisions, in this paper a cooperative spectrum sensing scheme is proposed, which takes the propagation conditions such as the variance and intensity of terrain and urban structure between two points with respect to signal propagation into consideration. We have also derived the optimum fusion rule which takes location reliability into consideration. The analytical results show that the proposed scheme outperform the conventional cooperative spectrum sensing approaches

Adaptive Turbo-Coded Hybrid-ARQ in OFDM

In this paper, the performance of an adaptivemodulated and adaptive-rate hybrid automatic-repeat-request (Hybrid-ARQ) scheme is proposed for wideband communications based on an orthogonal frequency division multiplexing (OFDM). The adaptation scheme presents the optimal code rate and signal constellation in order to maximize the spectral efficiency per sub-carrier. By employing Type-III Turbo Hybrid-ARQ with OFDM, utilization of a complete set of sub-carriers is achieved. The adaptation scheme is presented for both Gaussian and fading channels. It is found that the proposed adaptive approach achieves near capacity rates for wideband transmission. Keywords - information rate, adaptive modulation, adaptive coding, fading channels, concatenated coding, automatic repeat request

A secure and intelligent framework for vehicle health monitoring exploiting big-data analytics

The dependency on vehicles is increasing tremendously due to its excellent transport capacity, fast, efficient, flexible, pleasant journey, minimal physical effort, and substantial economic impact. As a result, the demand for smart and intelligent feature enhancement is growing and becoming a prime concern for maximum productivity based on the current perspective. In this case, the Internet of Everything (IoE) is an emerging concept that can play an essential role in the automotive industry by integrating the stakeholders, process, data, and things via networked connections. But the unavailability of intelligent features leads to negligence about proper maintenance of vehicle vulnerable parts, reckless driving and severe accident, lack of instructive driving, and improper decision, which incurred extra expenses for maintenance besides hindering national economic growth. For this, we proposed a conceptual framework for a central VHMS exploiting IoE-driven Multi-Layer Heterogeneous Networks (HetNet) and a machine learning technique to oversee individual vehicle health conditions, notify the respective owner-driver real-timely and store the information for further necessary action. This article transparently portrayed an overview of central VHMS and proposed the taxonomy to achieve such an objective. Subsequently, we unveiled the framework for central VHMS, IoE-driven Multi-tire HetNet, with a secure and trustworthy data collection and analytics system. Finally, anticipating this proposition's outcome is immense in the automotive sector. It may motivate the researcher to develop a central intelligent and secure vehicular condition diagnostic system to move this sector towards Industry 4.0

INGR Roadmap

Fifth generation (5G) networks represent the first step from evolutionary to revolutionary networks. Use cases driving this transition for 5G networks focus on the need to support heterogeneous traffic such as enhanced Mobile Broad Band (eMBB), massive Machine-Type Communications (mMTC), and Ultra-Reliable Low-Latency Communications (URLLC). On the software and control side, 5G and beyond networks are expected to support Software-Defined Networking (SDN) and Network Function virtualization (NFV) technologies and will leverage the merging of communication and computing through the 'wireless edge'. With the deployment of novel applications and the expected increase in their usage and demand, the scope of innovation within future networks will be governed by: (a) limitations and boundaries of available resources; (b) limitations of the adaptability of legacy solutions (scalability and flexibility); (c) limitations of available decision making entities (network slice orchestrators and SDN controllers will not be enough); and (d) lack of intelligent management and control solutions for multi-variate optimization. Technologies are available for efficient use and self-adaptive optimization of resources using enablers such as AI-powered autonomic control loops. With ever increasing complexity expected for beyond-5G networks, there is a necessity for novel design, planning and operations paradigms. There is a need for assessment of legacy tools versus new Artificial Intelligence solutions for applicability to systems optimization, and a need for introduction of novel methods to model and study the behavior of highly complex systems developed for the realization of 5G and beyond networks. The goal of this working group (WG) is to assess complexity challenges for the 5G era and beyond, explore novel design, planning and operations techniques for networks and services, and explore intelligence sciences to create the roadmap of the IEEE Future Networks Initiative (FNI) Systems Optimization WG.</p