Planning Wireless Cellular Networks of Future: Outlook, Challenges and Opportunities

Cell planning (CP) is the most important phase in the life cycle of a cellular system as it determines the operational expenditure, capital expenditure, as well as the long-term performance of the system. Therefore, it is not surprising that CP problems have been studied extensively for the past three decades for all four generations of cellular systems. However, the fact that small cells, a major component of future networks, are anticipated to be deployed in an impromptu fashion makes CP for future networks vis-a-vis 5G a conundrum. Furthermore, in emerging cellular systems that incorporate a variety of different cell sizes and types, heterogeneous networks (HetNets), energy efficiency, self-organizing network features, control and data plane split architectures (CDSA), massive multiple input multiple out (MIMO), coordinated multipoint (CoMP), cloud radio access network, and millimetre-wave-based cells plus the need to support Internet of Things (IoT) and device-to-device (D2D) communication require a major paradigm shift in the way cellular networks have been planned in the past. The objective of this paper is to characterize this paradigm shift by concisely reviewing past developments, analyzing the state-of-the-art challenges, and identifying future trends, challenges, and opportunities in CP in the wake of 5G. More specifically, in this paper, we investigate the problem of planning future cellular networks in detail. To this end, we first provide a brief tutorial on the CP process to identify the peculiarities that make CP one of the most challenging problems in wireless communications. This tutorial is followed by a concise recap of past research in CP. We then review key findings from recent studies that have attempted to address the aforementioned challenges in planning emerging networks. Finally, we discuss the range of technical factors that need to be taken into account while planning future networks and the promising research directions that necessitates the paradigm shift to do so

What constitutes responsiveness of physicians: A qualitative study in rural Bangladesh

Responsiveness entails the social actions by health providers to meet the legitimate expectations of patients. It plays a critical role in ensuring continuity and effectiveness of care within people centered health systems. Given the lack of contextualized research on responsiveness, we qualitatively explored the perceptions of outpatient users and providers regarding what constitute responsiveness in rural Bangladesh. An exploratory study was undertaken in Chuadanga, a southwestern Bangladeshi District, involving in-depth interviews of physicians (n = 17) and users (n = 7), focus group discussions with users (n = 4), and observations of patient provider interactions (three weeks). Analysis was guided by a conceptual framework of responsiveness, which includes friendliness, respecting, informing and guiding, gaining trust and optimizing benefits. In terms of friendliness, patients expected physicians to greet them before starting consultations; even though physicians considered this unusual. Patients also expected physicians to hold social talks during consultations, which was uncommon. With regards to respect patients expected physicians to refrain from disrespecting them in various ways; but also by showing respect explicitly. Patients also had expectations related to informing and guiding: they desired explanation on at least the diagnosis, seriousness of illness, treatment and preventive steps. In gaining trust, patients expected that physicians would refrain from illegal or unethical activities related to patients, e.g., demanding money against free services, bringing patients in own private clinics by brokers (dalals), colluding with diagnostic centers, accepting gifts from pharmaceutical representatives. In terms of optimizing benefits: patients expected that physicians should be financially sensitive and consider individual need of patients. There were multiple dimensions of responsiveness- for some, stakeholders had a consensus; context was an important factor to understand them. This being an exploratory study, further research is recommended to validate the nuances of the findings. It can be a guideline for responsiveness practices, and a tipping point for future research

Analytical Modelling for Mobility Signalling in Ultra-Dense HetNets

Multi-band and multi-tier network densification is being considered as the most promising solution to overcome the capacity crunch problem of cellular networks. In this direction, small cells (SCs) are being deployed within the macro cell (MC) coverage, to off-load some of the users associated with the MCs. This deployment scenario raises several problems. Among others, signalling overhead and mobility management will become critical considerations. Frequent handovers (HOs) in ultra dense SC deployments could lead to a dramatic increase in signalling overhead. This suggests a paradigm shift towards a signalling conscious cellular architecture with smart mobility management. In this regards, the control/data separation architecture (CDSA) with dual connectivity is being considered for the future radio access. Considering the CDSA as the radio access network (RAN) architecture, we quantify the reduction in HO signalling w.r.t. the conventional approach. We develop analytical models which compare the signalling generated during various HO scenarios in the CDSA and conventionally deployed networks. New parameters are introduced which can with optimum value significantly reduce the HO signalling load. The derived model includes HO success and HO failure scenarios along with specific derivations for continuous and non-continuous mobility users. Numerical results show promising CDSA gains in terms of saving in HO signalling overhead

A policy analysis regarding education, career, and governance of the nurses in Bangladesh: A qualitative exploration

Nurses, short in production and inequitable in the distribution in Bangladesh, require the government’s efforts to increase enrolment in nursing education and a smooth career progression. Given the importance of an assessment of the current nursing scenario to inform the decision makers and practitioners to implement the new policies successfully, we analyzed relevant policies on education, career, and governance of nurses in Bangladesh. We used documents review and qualitative methods such as key informant interviews (n = 13) and stakeholder analysis. We found that nursing education faced several backlashes: resistance from diploma nurses while attempting to establish a graduate (bachelor) course in 1977, and the reluctance of politicians and entrepreneurs to establish nursing institutions. Many challenges with the implementation of nursing policies are attributable to social, cultural, religious, and historical factors. For example, Hindus considered touching the bodily excretions as the task of the lower castes, while Muslims considered women touching the body of the men immoral. Nurses also face governance challenges linked with their performance and reward. For example, nurses have little voice over the decisions related to their profession, and they are not allowed to perform clinical duties unsupervised. To improve the situation, the government has made new policies, including upliftment of nurses’ position in public service, the creation of an independent Directorate General, and improvement of nursing education and service. New policies often come with new apprehensions. Therefore, nurses should be included in the policy processes, and their capacity should be developed in nursing leadership and health system governance

Reduced Graphene Oxide Thin Films with Very Large Charge Carrier Mobility Using Pulsed Laser Deposition

Large area reduced graphene oxide (RGO) thin films have been grown using pulsed laser deposition (PLD) technique. A very large carrier mobility of 372 cm2 V-1s-1 has been observed in a PLD grown RGO thin film with a large sp2 carbon fraction of 87% along with narrow Raman 2D peak profile. The fraction of sp2 carbon and carbon/oxygen ratios are tuned through PLD growth parameters, and these are estimated from X-ray photoelectron spectroscopy (XPS) data. The electrical properties of the RGO thin films are comprehended by the intensity ratios between different optical phonon vibrational modes of Raman Spectra. The photoluminescence spectra also indicate a less intense and broader blue fluorescence spectrum detecting the presence of miniature sized sp2 domains in the near vicinity of π* electronic states which favor the variable range hopping transport phenomena. This study on large area RGO thin films with very large carrier mobility fabricated by PLD process will be very useful for high mobility electronic device applications and could open a roadmap for further extensive research in functionalized 2D materials

Big data analytics for 5G networks: utilities, frameworks, challenges and opportunities

In order to meet the challenges of ambitious capacity, user experience, and resource efficiency gains, the next‐generation cellular networks need to leverage end‐to‐end user and network behavior intelligence. This intelligence can be gathered from the mobile network big data which includes the massive telemetric data about network health and status as well as data about user whereabouts, preferences, context, and mobility patterns. As a result, exploitation of big data on wireless cellular network is emerging as an indispensable approach for harnessing intelligence in future wireless communication networks. In this article, we first identify and classify the big data that can be gathered from different layers and ends of a wireless cellular network. We then discuss several new utilities of the big data that can bridge the existing gaps to meet 5G requirements. After that we summarize the existing literature on data analytics for cellular network performance. We present different platforms and two different frameworks to implement big data analytic‐based solutions in 5G and beyond and compare their pros and cons. We then discuss how key performance indicators (KPIs)‐based data collection may not suffice in 5G. Through an exemplary study, we show how to unleash the full potential hidden within the big data, granularity of low‐level performance indicators, and how context is essential. Finally, we highlight the opportunities that can be availed from big data in cellular network and the challenges therein

Novel Coronavirus (SARS-CoV-2) in Water and Environment—A Scoping Review

A pneumonia outbreak was primarily reported in the fall of 2019 in Wuhan, Hubei province, China, with the identity SARS-CoV-2, a novel coronavirus. It quickly grew from a local epidemic to a global pandemic and was declared a public health emergency by the WHO. A total of three prominent waves were identified across the globe, with a slight temporal variability as per the geographical locations, and has impacted several sectors which connect the world. By March 2022, the coronavirus had infected 444.12 million people and claimed 6.01 million human lives worldwide, and these numbers have not yet stabilized. Our paper enlightens readers on the seven strains of human coronaviruses, with special emphasis on the three severe deadliest outbreaks (SARS-2002, MERS-2012, and COVID-19). This work attempts a comprehensive understanding of the coronavirus and its impact on the possible sectors that link the world through the economic chain, climate conditions, SDGs, recycling of the event, and mitigations. There are many points that are raised by the authors in the possible sectors, which are emerging or are as yet unnoticed and thus have not been taken into consideration. This comprehension will leave sets of new challenges and opportunities for the researchers in various streams, especially in earth sciences. Science-integrated research may help to prevent upcoming disasters as a by-product of (existing) epidemics in the form of coronavirus

Forecast of streamflows to the Arctic Ocean by a Bayesian neural network model with snowcover and climate inputs

Abstract Increasing water flowing into the Arctic Ocean affects oceanic freshwater balance, which may lead to the thermohaline circulation collapse and unpredictable climatic conditions if freshwater inputs continue to increase. Despite the crucial role of ocean inflow in the climate system, less is known about its predictability, variability, and connectivity to cryospheric and climatic patterns on different time scales. In this study, multi-scale variation modes were decomposed from observed daily and monthly snowcover and river flows to improve the predictability of Arctic Ocean inflows from the Mackenzie River Basin in Canada. Two multi-linear regression and Bayesian neural network models were used with different combinations of remotely sensed snowcover, in-situ inflow observations, and climatic teleconnection patterns as predictors. The results showed that daily and monthly ocean inflows are associated positively with decadal snowcover fluctuations and negatively with interannual snowcover fluctuations. Interannual snowcover and antecedent flow oscillations have a more important role in describing the variability of ocean inflows than seasonal snowmelt and large-scale climatic teleconnection. Both models forecasted inflows seven months in advance with a Nash–Sutcliffe efficiency score of ≈0.8. The proposed methodology can be used to assess the variability of the freshwater input to northern oceans, affecting thermohaline and atmospheric circulations