Mobility management in multi-RAT multiI-band heterogeneous networks

Support for user mobility is the raison d'etre of mobile cellular networks. However, mounting pressure for more capacity is leading to adaption of multi-band multi-RAT ultra-dense network design, particularly with the increased use of mmWave based small cells. While such design for emerging cellular networks is expected to offer manyfold more capacity, it gives rise to a new set of challenges in user mobility management. Among others, frequent handovers (HO) and thus higher impact of poor mobility management on quality of user experience (QoE) as well as link capacity, lack of an intelligent solution to manage dual connectivity (of user with both 4G and 5G cells) activation/deactivation, and mmWave cell discovery are the most critical challenges. In this dissertation, I propose and evaluate a set of solutions to address the aforementioned challenges. The beginning outcome of our investigations into the aforementioned problems is the first ever taxonomy of mobility related 3GPP defined network parameters and Key Performance Indicators (KPIs) followed by a tutorial on 3GPP-based 5G mobility management procedures. The first major contribution of the thesis here is a novel framework to characterize the relationship between the 28 critical mobility-related network parameters and 8 most vital KPIs. A critical hurdle in addressing all mobility related challenges in emerging networks is the complexity of modeling realistic mobility and HO process. Mathematical models are not suitable here as they cannot capture the dynamics as well as the myriad parameters and KPIs involved. Existing simulators also mostly either omit or overly abstract the HO and user mobility, chiefly because the problems caused by poor HO management had relatively less impact on overall performance in legacy networks as they were not multi-RAT multi-band and therefore incurred much smaller number of HOs compared to emerging networks. The second key contribution of this dissertation is development of a first of its kind system level simulator, called SyntheticNET that can help the research community in overcoming the hurdle of realistic mobility and HO process modeling. SyntheticNET is the very first python-based simulator that fully conforms to 3GPP Release 15 5G standard. Compared to the existing simulators, SyntheticNET includes a modular structure, flexible propagation modeling, adaptive numerology, realistic mobility patterns, and detailed HO evaluation criteria. SyntheticNET’s python-based platform allows the effective application of Artificial Intelligence (AI) to various network functionalities. Another key challenge in emerging multi-RAT technologies is the lack of an intelligent solution to manage dual connectivity with 4G as well 5G cell needed by a user to access 5G infrastructure. The 3rd contribution of this thesis is a solution to address this challenge. I present a QoE-aware E-UTRAN New Radio-Dual Connectivity (EN-DC) activation scheme where AI is leveraged to develop a model that can accurately predict radio link failure (RLF) and voice muting using the low-level measurements collected from a real network. The insights from the AI based RLF and mute prediction models are then leveraged to configure sets of 3GPP parameters to maximize EN-DC activation while keeping the QoE-affecting RLF and mute anomalies to minimum. The last contribution of this dissertation is a novel solution to address mmWave cell discovery problem. This problem stems from the highly directional nature of mmWave transmission. The proposed mmWave cell discovery scheme builds upon a joint search method where mmWave cells exploit an overlay coverage layer from macro cells sharing the UE location to the mmWave cell. The proposed scheme is made more practical by investigating and developing solutions for the data sparsity issue in model training. Ability to work with sparse data makes the proposed scheme feasible in realistic scenarios where user density is often not high enough to provide coverage reports from each bin of the coverage area. Simulation results show that the proposed scheme, efficiently activates EN-DC to a nearby mmWave 5G cell and thus substantially reduces the mmWave cell discovery failures compared to the state of the art cell discovery methods

Engagement of private healthcare providers for case finding of tuberculosis and diabetes mellitus in Pakistan

Background: The rising co-epidemic of tuberculosis (TB) and diabetes mellitus (DM) is a challenge for constrained health systems in low and middle-income countries. Diabetes is a known risk factor for tuberculosis and associated with poor tuberculosis treatment outcomes, while tuberculosis is associated with worsening glycemic control. We investigated the performance of bi-directional TB and DM case finding approaches through a private-sector engagement model in Karachi, Pakistan.Methods: Between July 2016 and July 2018, private health care providers were engaged to generate referrals for bi-directional TB and DM screening at private diagnostic and treatment centers in Karachi, Pakistan. Individuals diagnosed with TB underwent glycated hemoglobin (HbA1c) testing at the time of anti-tuberculous treatment initiation and at three -month follow up stage. All individuals with a history of diabetes or random blood sugar of greater than 200 mg/dl were screened for TB using a chest X-ray and Xpert MTB/RIF.Results: A total of 6312 persons with tuberculosis were tested on HbA1c at treatment initiation, of whom 1516 (24%) were newly diagnosed with DM. About one third of those with HbA1c in the diabetic range (≥ 6.5%) at baseline were found to have a normal HbA1c (\u3c 5.7%) result at 3-month follow-up. A total of 3824 individuals with DM, of whom 2396 (63%) were known cases and 1428 (37%) were newly identified with random blood sugar \u3e 200 mg/dl, underwent chest x-ray and Xpert MTB/RIF testing, with 321 (13.4%) known and 54 (3.8%) new diabetics respectively identified with tuberculosis.Conclusion: This study demonstrates a high yield of TB and DM through bidirectional screening and the feasibility of engagement of private sector in finding missing cases of tuberculosis and diabetes. Given the high prevalence of undiagnosed DM in individuals with TB tuberculosis patients, there is a need to scale-up DM screening within TB programmes. Increased awareness of the high risk of TB among individuals with DM is needed among private health providers and screening for TB among diabetics should be strongly considered

Barriers to access of healthcare services for rural women – Applying gender lens on TB in a rural district of Sindh, Pakistan

Background: Women in rural districts of Pakistan face numerous barriers to healthcare, rendering gender-responsive health programming important, including for Tuberculosis (TB). This study was conducted to assess the general understanding of TB and of access to healthcare for women, as a first step towards implementation of a gender responsive TB programme in TandoAllayar, a rural district of Pakistan.Methods: A total of 36 participants were interviewed. The focus group discussion guide comprised of questions on: (1) family/household dynamics (2) community norms (3) healthcare system (4) women’s access to healthcare (5) TB Awareness;, and (6) women’s access to TB Care.Results: Limited autonomy in household financial decision-making, disapproval of unassisted travel, long travel time, lack of prioritization of spending on women’s health and inadequate presence of female health providers, were identified as barriers to access of healthcare for women, higher in younger women. Facilitators to access of TB care included a reported lack of TB-related stigma, moderate knowledge about TB disease, and broad understanding of tuberculosis as a curable disease. Other suggested facilitators include health facilities closer to the villages and the availability of higher quality services.Conclusion: Significant barriers are faced by women in access to TB care in rural districts of Pakistan. Programme implementers in high burden countries, should shift towards improved gender-responsive TB programming

Effectiveness of 10-valent pneumococcal conjugate vaccine against vaccine-type invasive pneumococcal disease in Pakistan

Objective: To assess the effectiveness of 10-valent pneumococcal conjugate vaccine (PCV10) against invasive pneumococcal disease (IPD) due to vaccine serotypes of Streptococcus pneumoniae post introduction of the vaccine into the routine immunization program in Pakistan.Methods: A matched case-control study was conducted at 16 hospitals in Sindh Province, Pakistan. Children aged (eligible to receive PCV10) who presented with radiographically confirmed pneumonia and/or meningitis were enrolled as cases. PCR for the lytA gene was conducted on blood (for radiographic pneumonia) and cerebrospinal fluid (for meningitis) samples to detect S. pneumoniae. The proportion of IPD due to vaccine serotypes (including vaccine-related serogroups) was determined through serial multiplex PCR. For each case, at least five controls were enrolled from children hospitalized at the same institution, matched for age, district, and season.Results: Of 92 IPD patients enrolled during July 2013 to March 2017, 24 (26.0%) had disease caused by vaccine serotypes. Most case (87.5% of 24) and control (66.4% of 134) children had not received any PCV10 doses. The estimated effectiveness of PCV10 against vaccine-type IPD was 72.7% (95% confidence interval (CI) -7.2% to 92.6%) with at least one dose, 78.8% (95% CI -11.9% to 96.0%) for at least two doses, and 81.9% (95% CI -55.7% to 97.9%) for all three doses of vaccine.Conclusion: The vaccine effectiveness point estimates for PCV10 were high and increased with increasing number of doses. However, vaccine effectiveness estimates did not reach statistical significance, possibly due to low power. The findings indicate the likely impact of vaccine in reducing the burden of vaccine-type IPD if vaccine uptake can be improved

Impact of 10-valent pneumococcal conjugate vaccine (PCV10) on nasopharyngeal carriage in children 2 years of age: Data from a four-year time series cross-sectional study from Pakistan

The dataset described in this paper was collected for a time-series cross-sectional study exploring the impact of 10-valent Pneumococcal Conjugate Vaccine (PCV10) on nasopharyngeal (NP) carriage in children under 2 years of age from a rural population in Sindh, Pakistan. The study was carried out in two union councils of Matiari - Khyber and Shah Alam Shah Jee Wasi (Latitude 25.680298 / Longitude 68.502711). Data was collected on socio-demographics, clinical characteristics and vaccination status using android phone-based application. NP samples were collected using standard World Health Organisation (WHO) techniques, culture and serotyping was done using sequential Multiplex PCR described by Centre for Disease Control, USA. We looked at the carriage rate of vaccine type (VT) and non-vaccine type (NVT) serotypes over time in vaccinated and unvaccinated children. We additionally looked at the predictors for pneumococcal carriage. The uploaded dataset, available on Mendeley data repository (Nisar, Muhammad Imran (2021), Impact of PCV10 on nasopharyngeal carriage in children in Pakistan , Mendeley Data, V1, doi:10.17632/t79h6g97gr.1), has 3140 observations in CSV format. Additional files uploaded include a data dictionary and the set of questionnaires. The dataset and accompanying files can be used by other interested researchers to replicate our analysis, carry similar analysis under varying set of assumptions or perform additional exploratory or metanalysis

Direct and indirect effect of 10 valent pneumococcal vaccine on nasopharyngeal carriage in children under 2 years of age in Matiari, Pakistan

Background: Pakistan introduced Ten-valent pneumococcal-conjugate-vaccine PCV10 in 2012 as a 3 + 0 schedule without catch-up.Methods: Children \u3c2 years old in Matiari, Sindh provided nasopharyngeal swabs between 2014 and 2018, which were cultured for pneumococcus and serotyped through multiplex PCR at the Aga Khan University Hospital. Carriage rates over time for Vaccine-Type (VT) and Non-VT (NVT) serotypes were used to estimate direct, indirect, total and overall effects of vaccination. Regression analysis was used to determine factors associated with VT carriage.Results: Pneumococcus was detected in 2370/3140 (75%). VT carriage decreased overall, 16.1-9.6% (p-trend \u3c0.001); vaccinated (all 3 doses of PCV10 received) 11.3-8.1% (p-trend 0.031) and unvaccinated (no PCV10 dose received) 17.4-10.3% (p-trend 0.003) with a decline in serotypes 6B, 9V/9A and 19F. Immunization increased from 41.0% to 68.4% (p-trend 0.001). Direct effect of vaccine was 32.8% (95% CI 14.7-47.0%) and indirect effect 44.6%(95% CI 40.6-48.6%). Factors associated with decreased VT colonization were education 1-5 years (aOR 0.7, 95%CI 0.6-1.0), history of difficulty breathing (aOR 0.7, 95%CI 0.5-1.0), exposure to smoke (aOR 0.8, 95% CI 0.6-1.0), child fully immunized (aOR 0.7, 95%CI 0.5-1.0) and enrolled in 3rd (aOR 0.6, 95%CI 0.4-0.8) and 4th (aOR 0.6, 95%CI 0.5-0.9) year of the study whereas history of runny nose (aOR 1.5, 95% CI 1.2-1.9) was positively associated.Conclusions: Decrease in VT pneumococcal carriage in vaccinated and unvaccinated children indicates herd immunity. Sustained increase in vaccine coverage and close long-term surveillance is warranted

Towards addressing training data scarcity challenge in emerging radio access networks: a survey and framework

The future of cellular networks is contingent on artificial intelligence (AI) based automation, particularly for radio access network (RAN) operation, optimization, and troubleshooting. To achieve such zero-touch automation, a myriad of AI-based solutions are being proposed in literature to leverage AI for modeling and optimizing network behavior to achieve the zero-touch automation goal. However, to work reliably, AI based automation, requires a deluge of training data. Consequently, the success of the proposed AI solutions is limited by a fundamental challenge faced by cellular network research community: scarcity of the training data. In this paper, we present an extensive review of classic and emerging techniques to address this challenge. We first identify the common data types in RAN and their known use-cases. We then present a taxonomized survey of techniques used in literature to address training data scarcity for various data types. This is followed by a framework to address the training data scarcity. The proposed framework builds on available information and combination of techniques including interpolation, domain-knowledge based, generative adversarial neural networks, transfer learning, autoencoders, fewshot learning, simulators and testbeds. Potential new techniques to enrich scarce data in cellular networks are also proposed, such as by matrix completion theory, and domain knowledge-based techniques leveraging different types of network geometries and network parameters. In addition, an overview of state-of-the art simulators and testbeds is also presented to make readers aware of current and emerging platforms to access real data in order to overcome the data scarcity challenge. The extensive survey of training data scarcity addressing techniques combined with proposed framework to select a suitable technique for given type of data, can assist researchers and network operators in choosing the appropriate methods to overcome the data scarcity challenge in leveraging AI to radio access network automation

Nasopharyngeal carriage of Streptococcus pneumoniae in children under 5 years of age before introduction of pneumococcal vaccine (PCV10) in urban and rural districts in Pakistan

Background: Benefits of pneumococcal conjugate vaccine programs have been linked to the vaccine’s ability to disrupt nasopharyngeal carriage and transmission. The 10-valent pneumococcal vaccine (PCV10) was included in the Expanded Program on Immunization (EPI) in Sindh, Pakistan in February 2013. This study was carried out immediately before PCV10 introduction to establish baseline pneumococcal carriage and prevalent serotypes in young children and to determine if carriage differed in urban and rural communities.Methods: Nasopharyngeal specimens were collected from a random sample of children 3-11 and 12-59 months of age in an urban community (Karachi) and children 3-11 months of age in a rural community (Matiari). Samples were processed in a research laboratory in Karachi. Samples were transported in STGG media, enriched in Todd Hewitt broth, rabbit serum and yeast extract, cultured on 5% sheep blood agar, and serotyped using the CDC standardized sequential multiplex PCR assay. Serotypes were categorized into PCV10-type and non-vaccine types.Results: We enrolled 670 children. Pneumococci were detected in 73.6% and 79.5 % of children in the infant group in Karachi and Matiari, respectively, and 78.2% of children 12 to 59 months of age in Karachi. In infants, 38. 9% and 33.5% of those carrying pneumococci in Karachi and Matiari, respectively, had PCV10 types. In the older age group in Karachi, the proportion was 30.7%, not significantly different from infants. The most common serotypes were 6A, 23F, 19A, 6B and 19F.Conclusion: We found that about 3 of 4 children carried pneumococci, and this figure did not vary with age group or urban or rural residence. Planned annual surveys in the same communities will inform change in carriage of PCV10 serotype pneumococci after the introduction and uptake of PCV10 in these communitie