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Emerging consumer devices rely on the next generation IoT for connected support to undergo the much-needed digital transformation. The main challenge for next-generation IoT is to fulfil the requirements of robust connectivity, uniform coverage and scalability to reap the benefits of automation, integration and personalization. Next generation mobile networks, including beyond 5G and 6G technology, play an important role in delivering intelligent coordination and functionality among the consumer nodes. This paper presents a 6G-enabled scalable cell-free IoT network that guarantees uniform quality-of-service (QoS) to the proliferating wireless nodes or consumer devices. By enabling the optimal association of nodes with the APs, it offers efficient resource management. A scheduling algorithm is proposed for the cell-free model such that the interference caused by the neighbouring nodes and neighbouring APs is minimised. The mathematical formulations are obtained to carry out the performance analysis with different precoding schemes. Further, the allocation of pilots for obtaining the association with minimum interference is managed using different pilot lengths. It is observed that the proposed algorithm offers an improvement of 18.9% in achieved spectral efficiency using partial regularized zero-forcing (PRZF) precoding scheme at pilot length τp=10. In the end, the performance comparison with two other models incorporating random scheduling and no scheduling at all is carried out. As compared to random scheduling, the proposed scheduling shows improvement of 10.9% in obtained spectral efficiency by 95% of the user nodes.

The fast-moving world relies on intelligent connected networks to support the numerous applications of the expanded Internet-of-Things (IoT). The evolving communication requirements of this connected world require a new sixth generation (6G) radio to enable intelligent interaction with the massive number of connected objects. The energy management of billions of connected devices supporting massive Internet-of-Things (IoT) applications is the main challenge. These IoT devices and connected nodes are energy limited, and hence, energy-aware solutions are needed to enable seamless information flow between these communicating nodes. This paper presents an intelligent network solution for improved energy efficiency in a 6G-enabled expanded IoT network. A cell-free massive multiple input multiple output (mMIMO) technology is utilized for maximum energy efficiency with optimum network resource allocation. A practical power consumption model is proposed for the designed network topology which contains all the power components related to data transmission and circuit power. The proposed scheme aims to achieve maximum energy efficiency by the optimal allocation of pilot reuse factor and access point (AP) density for a given number of antennas at each AP and number of users. It is observed that the maximum energy efficiency of 5.2362 Mbit/Joule is achieved at the AP density of 29 and pilot reuse factor of 4 with PMMSE receive combining. In the end, the role of energy efficiency and area throughput tradeoff on the system performance is also evaluated, which suggests that both the energy efficiency and area throughput can be jointly increased until maximum energy efficiency is reached at a point.

Internet-of-Things (IoT) networks are witnessing a rapid proliferation of connected devices and mobile terminals each day. The wireless information flow between these massive battery-powered devices has a huge energy burden and will lead to an energy crisis in the near future; thus, there is an urgent search for sustainable energy networks. To offer a sustainable energy solution in order to meet the energy demands of these massive IoT networks, this paper presents a dynamic practical model that enables the efficient management of power resources. Two user-scheduling algorithms, namely, minimum distance scheduling (MDS) and maximum channel gain scheduling (MCS), are proposed; when these algorithms were used alongside a power optimization, they led to improved network efficiency. Further, the network’s performance was measured with parametric variations in the number of access points (APs); the deployment of APs and AP configuration is carried out for different precoding schemes. The impact of spatial correlation and the access to perfect channel state information (CSI) on the spectral efficiency of the system was also evaluated. In the end, the study compares the performance of different power-allocation methods and suggests that the power allocated to a particular user node by an AP can be controlled using the proposed algorithms. It is observed that, as compared to the MDS algorithm, the MCS algorithm results in better spectral efficiency for all the users with fractional power allocation. In addition, each AP assigns a maximum power of 141.7 mW to a user with strong channel conditions with the AP, and a minimum power of 3.1882 mW to the user with the worst channel conditions using centralized PMMSE precoding.

This paper considers a cooperative wireless system with multiple antennas at the source. A multi-antenna relay equipped with a power splitter is introduced between the source and destination. It ut...

Background: The paper considers the wireless system with large number of users (more than 50 users) and each user is assigned large number of antennas (around 200) at the Base Station (BS). Objective: The challenges associated with the defined system are increased power consumption and high complexity of associated circuitry. The antenna selection is introduced to combat these problems while the usage of linear precoding reduces computational complexity. The literature suggests number of antenna selection techniques based on statistical properties of signal. However, each antenna selection technique suits well to specific number of users. Methods: In this paper, the random antenna selection is compared with norm-based antenna selection. It is analysed that the random antenna selection leads to inefficient spectral efficiency if the number of users are more than 50 in Multi-User Multiple-Input Multiple Output (MU-MIMO) system. Results: The paper proposes the optimization of Energy-Efficiency (EE) with random transmit antenna selection for large number of users in MU-MIMO systems. Conclusion: Also the computation leads to optimization of number of transmit antennas at the BS for energy efficiency. The proposed algorithm results in improvement of the energy efficiency by 27% for more than 50 users.

Purpose The major challenges in the modern-day wireless communication systems are increased co-channel interference owing to large number of users and the increased energy consumption owing to high circuit and/or hardware power consumption. Hence, the purpose of this paper is to present a practical approach involving linear precoding, channel estimation, user selection (US) and transmit antenna selection (AS) for enhanced reliability in multiuser multiple-input multiple output (MU-MIMO) system. Design/methodology/approach The proposed technique considers systematic and optimum deployment of users and transmits antennas for each selected user which enhances the sum rate or the system capacity. The comparison of algorithms, namely, norm-based and capacity-based US is presented with its implementation with precoding techniques, namely, block-diagonalization (BD) and zero-forcing with combining (ZFC) which is used to minimize co-channel interference. In this paper, a power consumption model is proposed for energy efficiency calculation in MU-MIMO system. Also, post analysis, the variant of US and AS algorithms optimizing the performance of BD and ZFC precoding technique is proposed. Findings It is seen that the proposed MU-MIMO system with norm-based US and norm-based AS improves over existing US-based systems by 43% in terms of sum rate and 19% in terms of energy efficiency for 100 users. Originality/value It is seen that the proposed MU-MIMO system with norm-based US and norm-based AS improves over existing US-based systems by 43% in terms of sum rate and 19% in terms of energy efficiency for 100 users.

The major challenges faced by the mobile users are the poor quality of communication and the fast battery drainage. The varying channel characteristics in wireless communication is the main reason for huge signal drops and poor signal quality. The channel estimation plays an important role and is crucial for determining the accuracy of the system. In this paper, the two channel estimation techniques, namely least square (LS) and minimum mean square error (MMSE) are analyzed for multi-antenna communication scenario. The different practical channel scenarios are considered to evaluate the performance of the proposed system in terms of average sum spectral efficiency (SE). It is observed that the maximum average sum SE is obtained with MMSE channel estimation for Rician fading channels. The impact of varying channel statistics with spatial correlation is also evaluated for different pilot reuse factors. Further, the comparison of different receive combiners based on the channel estimates for signal detection is performed in terms of computational complexity.

This paper presents the progress made by India and China in the field of waste management and its disposal since l996 to 2020. To access it, bibliometric analysis has been carried out using SCOPUS linked SCImago electronic database. Different bibliometric indicators such as documents, citable documents, external and self-citations, and external and self-citations per document along with their annual corresponding growth (ACG) have been calculated in order to explore the progresses made in both the countries. China has contributed 16.3% and India 4.3% to the total documents produced worldwide during 1996–2020 in waste management with the average ACG of 26.42% and 15.37%, respectively, during the same time span. Also, the average ACG for self-citations of published research documents is more than that of external citations for both the countries. In addition to that, the average self-citation magnitude reported for China (28,475) is more than that of India (5223), whereas this trend reverses in the case of average external citation per document with values 16.9 and 28.94, respectively. Moreover, the waste management practices being followed in both countries have also been compared and also presented so that it could be beneficial for the country which is relatively not good in the same.

The major challenge in the current scenario of wireless system is increasing number of users and hence increased co-channel interference within the limited spectrum available for communication. The compromise in terms of user quality and reliability of communication system is evitable from increased number of call drops and busy channels during mobile voice calls. The above mentioned challenge is attributed for increase in the number of users accommodated in the defined spectrum. The paper presents a novel user selection and transmit antenna selection based approach for enhanced reliability in multi-user multiple input multiple output system, which is next generation wireless system. In contrast to existing technique for multiple antennas and which is evolution of regular channel inversion with block diagonalization, the proposed technique considers systematic and optimum deployment of user selection in the system to enhance sum rate or the system capacity. The comparison of algorithms viz. random, norm based and capacity based user selection is presented with its implementation with precoding techniques which is used to minimize co-channel interference. The analysis proposes that, for each selected user if the transmit antennas are chosen with presented algorithm, the sum rate is improved by 17%. Also, the bit error rate performance of linear precoding with user selection is equivalent to non-linear precoding without user selection.

Wireless technologies are growing at a rapid speed in all around the world. In wireless technologies domain 5G is the next big thing to research. This topic elaborates about internet of things in 5G system which is definitely a game changer in upcoming generations. It’ll enhance the wireless services in upcoming times and will open the sea of opportunities as well as services. Recent 4G LTE technology is insufficient in matching up the data transfer speed, AI, self-driven vehicles, health systems, space technology and multiple instruments connectivity for next times. For these concerns 5G is going to be the pristine technology to meet our demands in future. Health systems and space technologies are changing at a superfast speed and these are currently on 4G technology. All the futuristic applications will require high band width, faster connectivity at multiple devices and latency with data rates. We’ll have an elaborative detailing about the obstacles and possibilities in 5G IOT systems.

Background: Respiratory viruses like coronavirus disease (COVID-19) spread when mucus or dropletscontaining the virus get into your body through your eyes, nose or throat. Most often, this happens throughyour hands. Hands also are one among the foremost common ways in which the virus spreads from oneperson to subsequent. During a worldwide pandemic, one among the most cost-effective, easiest, and mostvital ways to stop the spread of an epidemic is to scrub your hands frequently with soap and water1. But theremay be mild to moderate skin reactions related to hand hygiene.Objective: To find out the consequences of repeated washing of hands to protect against coronavirus(COVID-19).Methods: 106 candidates were asked by questionnaire to fill 20 different questions related to time, duration,frequency and consequences of hand wash they are feeling.Result: The result of this study supports that 56% of people who are washing their hands at least 25-100times a day are suffering from skin dryness.Conclusion: study suggests that repeated or frequent washing of hands can cause dryness and crack skin ofhands even in individuals with no history of skin diseases

The outbreak of (COVID-19) has created a global health crisis that has had a deep impact on the way weperceive our world and our everyday lives. This survey was helpful to know the impact of neck pain andleisure activity during lockdown of Female IT workers while remaining at work, and to analyse psychosocial effect on neck pain.Methodology: Female office workers with neck pain (n = 60) completed a survey about impact of their neckpain and leisure activities. Consequences of neck pain were evaluated with questions on self-reported impacton work and leisure activity. Responses to survey questions were analysed using descriptive analyses.Result: The point prevalence of NP was significantly related to age, gender, health status, job satisfaction,and length of employment.Conclusions: The findings provide evidence that the impact on work and leisure was substantial

Background: The explosion of coronavirus disease Covid-19 has created as a worldwide health crisis thathas had a deep impact on the way we perceive our world and our everyday lives. Not only the Speed,but the security measures put in situ to contain the spread of the virus also require social distancing byrefraining from doing what’s inherently human, Quarantine keeps such people far away from others so thatthey don’t unknowingly infect anyone in their vicinity. It’s employed by Governments to stop the spread ofcommunicable diseases. Such a survey would help me to understand the impact of psychological state andStress during Quarantine to guard against (COVID-19).Objective: To find out the impact of Quarantine on Mental Health and Stress to protect against the coronavirus(COVID-19).Methods: 65 PEOPLE were asked by questionnaire to fill 20 different questions related to Social, distancingis a public health strategy to limit the spread of COVID-19.Result: The result of this study supports that 65 people, who they are Quarantine. At least or more than 15days, are suffering from moderate to high-level Stress.Conclusion: The social isolation, quarantine, and lockdown can increase stress responses and generate morestatus of uncertainty

Intelligent reflecting surfaces (IRSs) are considered as a promising candidate enabling technology for future green wireless communication. Such intelligent surfaces have real-time reconfigurable properties that beamform the signal to a desired destination. In this paper, our objective is to study the performance optimization in an IRS-assisted wireless network. An array of reflecting elements is individually configured in IRS system set up, which is installed between the source and the destination to assist the communication between both without any obstacle. IRS-assisted network achieves significant performance gain as compared to wireless networks without IRS. However, there are severe practical challenges with IRSs including hardware impairments, size of IRS, and distribution of reflecting elements in the IRS. To tackle these issues, we analyzed the performance of the network for maximum achievable rates, minimum transmit power, and maximum energy efficiency (EE). The selection of optimal number of reflecting elements in the IRS enables huge savings in energy to achieve target rate with minimal power. We show that by incorporating optimal number of reflecting elements in IRSs, high EE can be achieved, which outperforms the direct transmission method. Moreover, we show the impact of increasing the number of reflecting elements on the trade-off between EE and achievable rates.

The purpose of this paper is to analyse the learning behaviour of students towards a technical course using online mode and offline mode. Due to the outbreak of Covid-19 pandemic, the educational fraternity has successfully reached out to the students using the various virtual tools available. Although, the offline mode of teaching-learning i.e. the actual classroom interaction is quite important as far as a technical course is concerned, but during these tough times the online platforms like Zoom, Webex meetings, Google meet have made the teaching-learning feasible remotely at any time from any place. This paper compares the learning behaviour of students in the two modes, online mode, and offline mode. A total of 213 students studying a technical course participated in the survey and their responses based on a questionnaire were recorded. The questionnaire considered all aspects related to the delivery of contents, the evaluation method, the preferred way of clarifying students’ doubts, course difficulty level and duration of the course. The analysis suggests that 72.3% of students are in favour of learning this course using offline mode, while 27.7 % of students are comfortable with online mode. Furthermore, the present study reveals that 95.7%, 95.3%, and 75.1 % of students are congenial with the offline mode in terms of teacher competency, content delivery, and interaction possibility respectively, whereas 85%, 76.9% and 48.4% of students are congenial with the online mode in terms of same parameters. The higher magnitude of average mean value for offline mode (3.99) anticipates its dominance over online mode (3.18). More than 50% students favoured online mode along with multiple choice question papers for the evaluation process irrespective of their preference to offline mode for teaching-learning. Based on the present analysis, some recommendations are proposed as the future strategies to improve the performance of teaching-learning activities during the times of crisis.