Cell Selection in Wireless Two-Tier Networks: A Context-Aware Matching Game

The deployment of small cell networks is seen as a major feature of the next generation of wireless networks. In this paper, a novel approach for cell association in small cell networks is proposed. The proposed approach exploits new types of information extracted from the users' devices and environment to improve the way in which users are assigned to their serving base stations. Examples of such context information include the devices' screen size and the users' trajectory. The problem is formulated as a matching game with externalities and a new, distributed algorithm is proposed to solve this game. The proposed algorithm is shown to reach a stable matching whose properties are studied. Simulation results show that the proposed context-aware matching approach yields significant performance gains, in terms of the average utility per user, when compared with a classical max-SINR approach.Comment: 11 pages, 11 figures, Journal article in ICST Wireless Spectrum, 201

Device-to-Device Communications in the Millimeter Wave Band: A Novel Distributed Mechanism

In spite of its potential advantages, the large-scale implementation of the device-to-device (D2D) communications has yet to be realized, mainly due to severe interference and lack of enough bandwidth in the microwave ($\mu$W) band. Recently, exploiting the millimeter wave (mmW) band for D2D communications has attracted considerable attention as a potential solution to these challenges. However, its severe sensitivity to blockage along with its directional nature make the utilization of the mmW band a challenging task as it requires line-of-sight (LOS) link detection and careful beam alignment between the D2D transceivers. In this paper, we propose a novel distributed mechanism which enables the D2D devices to discover unblocked LOS links for the mmW band communication. Moreover, as such LOS links are not always available, the proposed mechanism allows the D2D devices to switch to the $\mu$W band if necessary. In addition, the proposed mechanism detects the direction of the LOS links to perform the beam alignment. We have used tools from stochastic geometry to evaluate the performance of the proposed mechanism in terms of the signal-to-interference-plus-noise ratio (SINR) coverage probability. The performance of the proposed algorithm is then compared to the one of the single band (i.e., $\mu$W/mmW) communication. The simulation results show that the proposed mechanism considerably outperforms the single band communication.Comment: 6 Pages, 6 Figures, Accepted for presentation in Wireless Telecommunication Symposium (WTS'18

Heterogeneous UAV Cells: An Effective Resource Allocation Scheme for Maximum Coverage Performance

This paper develops an effective approach for the 3D deployment of a heterogeneous set of unmanned aerial vehicles (UAVs) acting as aerial base stations that provide maximum wireless coverage for ground users in a given geographical area. This problem is addressed in two steps. First, in order to maximize the utilization of each UAV, its optimal flight altitude is found based on the UAV’s transmit power which provides maximum coverage radius on the ground. The UAVs are classified into separate groups based on their transmit powers and optimal flight altitudes. Next, given a repository of UAVs belonging to different classes, the proposed technique finds an optimal subset of the available UAVs along with their optimal 3D placement to provide the maximum network coverage for a given area on the ground with the minimum power consumption. This optimization problem is proved to be NP-hard, for which a novel algorithm is proposed to solve the problem. Simulation results demonstrate the effectiveness of the proposed solution and provide valuable insights into the performance of the Heterogeneous UAV-supported small cell networks

Multi-Objective Optimization in Space Planning: A Graph-Based Approach

Abstract This thesis investigates the integration of multi-objective optimization, space syntax, and graph analysis in the context of space planning for single-unit buildings. Focused on demonstrating the effectiveness of advanced techniques in generating diverse design options, the study emphasizes optimization based on specific criteria. Building regulations, client needs, and architectural considerations are central to achieving optimal solutions. The research methodology involves a comprehensive exploration of design possibilities that adeptly balances conflicting elements. Utilizing space syntax and graph analysis, the study visualizes relationships between spaces and movements within the building. The integration of sophisticated plugins, Termite Nest and Wallacei, within the Grasshopper platform enhances the analysis. Termite Nest employs space syntax and graph analysis to generate design options, while Wallacei leverages multi-objective optimization, specifically through genetic algorithms, to harmonize conflicting design considerations. This study contributes insights into the practical application of these advanced techniques in space planning, demonstrating their capacity to yield optimized design solutions aligned with specific criteria

Comparison of peptide peak intensity methods for label free relative protein quantification

During the recent years, Liquid chromatography-mass spectrometry (LC-MS) has gained enormous attention to identify and quantify peptides in biological samples. The Current challenge is to quantify the level of proteins as well as identifying them. Recently several computational approaches for protein quantification based on measured peptides have been introduced. The aim of this study is to delve into most commonly employed approaches to estimate relative protein abundance from peak intensity values and have a comparison between different methods

Adaptive Mode Selection in Cognitive Buffer-Aided Full-Duplex Relay Networks with Imperfect Self-Interference Cancellation for Power and Delay Limited Cases

International audienceIn this paper, a cognitive radio network is considered in which the secondary network (SN) consists of a source, a buffer-aided full-duplex decode-and-forward relay, and a destination , underlaid over a primary network (PN). An imperfect self-interference (SI) cancellation is assumed at the secondary relay (SR), such that the SI power is proportional to the transmit power of the SR. For the SN with limited power expenditure, a novel joint mode selection and power allocation policy is proposed to maximize the secondary throughput under the constraints of secondary power consumption and a limited average induced interference power at the primary destination. For delay sensitive SN applications, a statistical delay constraint is imposed in which the queue length at the SR can only exceed a specified threshold with a limited probability. In the two proposed policies, the SN decides optimally when to operate in half duplex mode and/or in full duplex mode, and be silent. To avoid data loss in the SN, buffer is used at the SR for data storage. Simulation results show that, for a given interference threshold and statistical delay constraint, the proposed policy outperforms the non-buffer full-duplex, buffer-aided half-duplex, and non-buffer half-duplex policies in terms of the average secondary throughput, the average secondary delay, and the secondary power expenditure. Index Terms-Full duplex relaying, buffer-aided relaying, cog-nitive radio networks, power allocation, statistical delay constraint

Thing Mutation as a Countermeasure to Safeguard IoT

© 2020 ACM. In the Internet of Things (IoT), mutation aims to enhance functionality and survivability of a thing in the context of dynamic environments by allowing the thing to satisfy a need or seize a potential opportunity. In this paper, we propose a framework based on thing mutation as a countermeasure to certain security threats that could impact things\u27 operations (e.g., sensing and communicating). We then provide a case study which focuses on battery draining attack and propose a mutation-based strategy as a countermeasure to this attack

Clinical Epidemiology of Ventilator-Associated Pneumonia in Open Heart Surgery Patients Admitted to Intensive Care Units in Sari Fatemeh Zahra Hospital, 2017-2019

Background and purpose: Ventilator-associated pneumonia (VAP) is one of the major factors of mortality and morbidity in Intensive care units (ICUS), especially in open-heart surgery patients. The purpose of this study was to investigate VAP in open-heart surgery patients admitted to the ICU in Sari Fatemeh Zahra Hospital, 2017-2019. Materials and methods: In this retrospective descriptive cross-sectional study, demographic, clinical, laboratory, and therapeutic information of patients with VAP were examined. Data were analyzed using SPSS V25. Results: A total of 52 patients with VAP were elevated after open heart surgery. The mean age of patients was 64.41±10.85 years and 55.8% were men. Half of the patients (51.9%) underwent intubation for less than five days and the mean duration of occurrence of VAP after initiation of ventilation was about six hours. The most common microorganisms causing pneumonia were Acinetobacter baumannii (23.63%) and Citrobacter freundii (16.36%). In general, the highest resistance of isolated microorganisms was toward third-generation cephalosporins and their highest sensitivity was to aminoglycosides. Conclusion: Control and prevention of ventilator-associated pneumonia is of particular importance, especially in patients after open-heart surgery admitted to intensive care units