8 research outputs found

    Robust Schemes to Enhance Energy Consumption Efficiency for Millimeter Wave-Based Microcellular Network in Congested Urban Environments

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    Future wireless communication networks will be largely characterized by small cell deployments, typically on the order of 200 meters of radius/cell, at most. Meanwhile, recent studies show that base stations (BS) account for about 80 to 95 % of the total network power. This simply implies that more energy will be consumed in the future wireless network since small cell means massive deployment of BS. This phenomenon makes energy-efficient (EE) control a central issue of critical consideration in the design of future wireless networks. This paper proposes and investigates (the performance of) two different energy-saving approaches namely, adaptive-sleep sectorization (AS), adaptive hybrid partitioning schemes (AH) for small cellular networks using smart antenna technique. We formulated a generic base-model for the above-mentioned schemes and applied the spatial Poisson process to reduce the system complexity and to improve flexibility in the beam angle reconfiguration of the adaptive antenna, also known as a smart antenna (SA). The SA uses the scalable algorithms to track active users in different segments/sectors of the microcell, making the proposed schemes capable of targeting specific users or groups of users in periods of sparse traffic, and capable of performing optimally when the network is highly congested. The capabilities of the proposed smart/adaptive antenna approaches can be easily adapted and integrated into the massive MIMO for future deployment. Rigorous numerical analysis at different orders of sectorization shows that among the proposed schemes, the AH strategy outperforms the AS in terms of energy saving by about 52 %. Generally, the proposed schemes have demonstrated the ability to significantly increase the power consumption efficiency of micro base stations for future generation cellular systems, over the traditional design methodologies

    Robust Schemes to Enhance Energy Consumption Efficiency for Millimeter Wave-Based Microcellular Network in Congested Urban Environments

    Get PDF
    Future wireless communication networks will be largely characterized by small cell deployments, typically on the order of 200 meters of radius/cell, at most. Meanwhile, recent studies show that base stations (BS) account for about 80 to 95 % of the total network power. This simply implies that more energy will be consumed in the future wireless network since small cell means massive deployment of BS. This phenomenon makes energy-efficient (EE) control a central issue of critical consideration in the design of future wireless networks. This paper proposes and investigates (the performance of) two different energy-saving approaches namely, adaptive-sleep sectorization (AS), adaptive hybrid partitioning schemes (AH) for small cellular networks using smart antenna technique. We formulated a generic base-model for the above-mentioned schemes and applied the spatial Poisson process to reduce the system complexity and to improve flexibility in the beam angle reconfiguration of the adaptive antenna, also known as a smart antenna (SA). The SA uses the scalable algorithms to track active users in different segments/sectors of the microcell, making the proposed schemes capable of targeting specific users or groups of users in periods of sparse traffic, and capable of performing optimally when the network is highly congested. The capabilities of the proposed smart/adaptive antenna approaches can be easily adapted and integrated into the massive MIMO for future deployment. Rigorous numerical analysis at different orders of sectorization shows that among the proposed schemes, the AH strategy outperforms the AS in terms of energy saving by about 52 %. Generally, the proposed schemes have demonstrated the ability to significantly increase the power consumption efficiency of micro base stations for future generation cellular systems, over the traditional design methodologies

    Epidemiology, diagnostics and factors associated with mortality during a cholera epidemic in Nigeria, October 2020-October 2021: a retrospective analysis of national surveillance data.

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    OBJECTIVES: Nigeria reported an upsurge in cholera cases in October 2020, which then transitioned into a large, disseminated epidemic for most of 2021. This study aimed to describe the epidemiology, diagnostic performance of rapid diagnostic test (RDT) kits and the factors associated with mortality during the epidemic. DESIGN: A retrospective analysis of national surveillance data. SETTING: 33 of 37 states (including the Federal Capital Territory) in Nigeria. PARTICIPANTS: Persons who met cholera case definition (a person of any age with acute watery diarrhoea, with or without vomiting) between October 2020 and October 2021 within the Nigeria Centre for Disease Control surveillance data. OUTCOME MEASURES: Attack rate (AR; per 100 000 persons), case fatality rate (CFR; %) and accuracy of RDT performance compared with culture using area under the receiver operating characteristic curve (AUROC). Additionally, individual factors associated with cholera deaths and hospitalisation were presented as adjusted OR with 95% CIs. RESULTS: Overall, 93 598 cholera cases and 3298 deaths (CFR: 3.5%) were reported across 33 of 37 states in Nigeria within the study period. The proportions of cholera cases were higher in men aged 5-14 years and women aged 25-44 years. The overall AR was 46.5 per 100 000 persons. The North-West region recorded the highest AR with 102 per 100 000. Older age, male gender, residency in the North-Central region and severe dehydration significantly increased the odds of cholera deaths. The cholera RDT had excellent diagnostic accuracy (AUROC=0.91; 95% CI 0.87 to 0.96). CONCLUSIONS: Cholera remains a serious public health threat in Nigeria with a high mortality rate. Thus, we recommend making RDT kits more widely accessible for improved surveillance and prompt case management across the country

    MCLMR: A Multicriteria Based Multipath Routing in the Mobile Ad Hoc Networks

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    In Mobile Ad hoc Networks (MANETs), nodes’ mobility, traffic congestion, and link quality estimation of the intermediate nodes are very crucial factors for establishing a reliable forwarding path between a source and destination node pairs. The unpredictable movement of nodes and random data traffic flow at a single node can cause congestion and network topology instability, which significantly lowers the performance of the ad hoc network. Indeed, the above-highlighted issues can be mitigated by implementing a more reliable mobility-centric, contention, and link quality-aware routing protocol for efficient data transmissions in a mobile network. This paper proposes a routing strategy called Mobility, Contention window, and Link quality sensitive multipath Routing (MCLMR) in MANETs, which considers the nodes mobility, contention window size, and link quality estimated value of the intermediate nodes in the optimal route selection. Also, Technique for Order of Preference by Similarity to Ideal Solution; a multicriteria decision-making technique, which provides weights according to node mobility, contention window size, and link quality estimated values, is also employed for the selection of intermediate nodes, whereas the Expected Number of Transmissions metric is used to minimize the effect of control message storm. The extensive simulations results prove that the proposed MCLMR routing scheme outperforms the conventional Multipath Optimized Link State Routing (MP-OLSR) and MP-OLSRv2 routing schemes in terms of network throughput, end-to-end delay, energy consumption, and packets loss ratio. © 2020, Springer Science+Business Media, LLC, part of Springer Nature
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