Rate-latency optimization for NB-IoT with adaptive resource unit configuration in uplink transmission

Narrowband Internet of Things (NB-IoT) is a cellular IoT communication technology standardized by 3rd Generation Partnership Project (3GPP) for supporting massive machine type communication and its deployment can be realized by a simple firmware upgrade on existing long term evolution (LTE) networks. The NB-IoT requirements in terms of energy efficiency, achievable rates, latency, extended coverage, make the resource allocation, in a limited bandwidth, even a more challenging problem w.r.t. to legacy LTE. The allocation, done with subcarrier (SC) granularity in NB-IoT, should maintain adequate performance for the devices while keeping the power consumption as low as possible. Nevertheless, the optimal solution of the resource allocation problem is typically unfeasible since nonconvex, NP-hard and combinatorial because of the use of binary variables. In this article, after the formulation of the optimization problem, we study the resource allocation approach for NB-IoT networks aiming to analyze the tradeoff between rate and latency. The proposed suboptimal algorithm allocates radio resource (i.e., SCs) and transmission power to the NB-IoT devices for the uplink transmission and the performance is compared in terms of latency, rate, and power. By comparing the proposed allocation to a conventional round robin (RR) and to a brute-force approach, we can observe the advantages of the formulated allocation problem and the limited loss of the suboptimal solution. The proposed algorithm outperforms the RR by a factor 2 in terms of spectral efficiency and, moreover, the study includes techniques that reduce the dropped packets from 29% to 1.6%

Radio Resource Management Scheme in NB-IoT Systems

Narrowband Internet of Things (NB-IoT) is the prominent technology that fits the requirements of future IoT networks. However, due to the limited spectrum (i.e., 180 kHz) availability for NB-IoT systems, one of the key issues is how to efficiently use these resources to support massive IoT devices? Furthermore, in NB-IoT, to reduce the computation complexity and to provide coverage extension, the concept of time offset and repetition has been introduced. Considering these new features, the existing resource management schemes are no longer applicable. Moreover, the allocation of frequency band for NB-IoT within LTE band, or as a standalone, might not be synchronous in all the cells, resulting in intercell interference (ICI) from the neighboring cells' LTE users or NB-IoT users (synchronous case). In this paper, first a theoretical framework for the upper bound on the achievable data rate is formulated in the presence of control channel and repetition factor. From the conducted analysis, it is shown that the maximum achievable data rates are 89.2 Kbps and 92 Kbps for downlink and uplink, respectively. Second, we propose an interference aware resource allocation for NB-IoT by formulating the rate maximization problem considering the overhead of control channels, time offset, and repetition factor. Due to the complexity of finding the globally optimum solution of the formulated problem, a sub-optimal solution with an iterative algorithm based on cooperative approaches is proposed. The proposed algorithm is then evaluated to investigate the impact of repetition factor, time offset and ICI on the NB-IoT data rate, and energy consumption. Furthermore, a detailed comparison between the non-cooperative, cooperative, and optimal scheme (i.e., no repetition) is also presented. It is shown through the simulation results that the cooperative scheme provides up to 8% rate improvement and 17% energy reduction as compared with the non-cooperative scheme

Latest research trends in gait analysis using wearable sensors and machine learning: a systematic review

Gait is the locomotion attained through the movement of limbs and gait analysis examines the patterns (normal/abnormal) depending on the gait cycle. It contributes to the development of various applications in the medical, security, sports, and fitness domains to improve the overall outcome. Among many available technologies, two emerging technologies that play a central role in modern day gait analysis are: A) wearable sensors which provide a convenient, efficient, and inexpensive way to collect data and B) Machine Learning Methods (MLMs) which enable high accuracy gait feature extraction for analysis. Given their prominent roles, this paper presents a review of the latest trends in gait analysis using wearable sensors and Machine Learning (ML). It explores the recent papers along with the publication details and key parameters such as sampling rates, MLMs, wearable sensors, number of sensors, and their locations. Furthermore, the paper provides recommendations for selecting a MLM, wearable sensor and its location for a specific application. Finally, it suggests some future directions for gait analysis and its applications

Machine Learning Meets Communication Networks: Current Trends and Future Challenges

The growing network density and unprecedented increase in network traffic, caused by the massively expanding number of connected devices and online services, require intelligent network operations. Machine Learning (ML) has been applied in this regard in different types of networks and networking technologies to meet the requirements of future communicating devices and services. In this article, we provide a detailed account of current research on the application of ML in communication networks and shed light on future research challenges. Research on the application of ML in communication networks is described in: i) the three layers, i.e., physical, access, and network layers; and ii) novel computing and networking concepts such as Multi-access Edge Computing (MEC), Software Defined Networking (SDN), Network Functions Virtualization (NFV), and a brief overview of ML-based network security. Important future research challenges are identified and presented to help stir further research in key areas in this direction

The prevalence of HBV infection in the cohort of IDPs of war against terrorism in Malakand Division of Northern Pakistan

<p>Abstract</p> <p>Background</p> <p>Hepatitis B is an important public health problem in the Pakistani population and is the major cause of chronic hepatitis, cirrhosis, fibrosis and hepatocellular carcinoma. High prevalence of HBV infections has been observed especially in areas of low economic status. In spite of effective immunization programs, no significant change has been observed in the epidemiology of HBV in the rural areas of Pakistan (~67.5% of the total population) mainly due to lack of interest from government authorities and poor hygienic measures. The current study was aimed at estimating the prevalence and risk factors associated with HBV infection within internally displaced persons (IDPs) due to war against terrorism in the Malakand Division of Northern Pakistan.</p> <p>Methods</p> <p>Blood samples from 950 IDPs suspected with HBV infection (including both males and females) were collected and processed with commercial ELISA kits for HBsAg, Anti HBs, HBeAg, Anti HBe antibodies. The samples positive by ELISA were confirmed for HBV DNA by real-time PCR analysis.</p> <p>Results</p> <p>The overall prevalence of HBV observed was 21.05% of which 78.5% were males and 21.5% were females. Most confirmed HBV patients belong to the Malakand and Dir (lower) district. High-risk of infection was found in the older subjects 29.13% (46-60 years), while a lower incidence (11.97%) was observed in children aged <15 years. Lack of awareness, socioecomic conditions, sexual activities and sharing of razor blades, syringes and tattooing needles were the most common risk factors of HBV infection observed during the cohort of patients.</p> <p>Conclusion</p> <p>The present study, revealed for the first time a high degree of prevalence of HBV infection in rural areas of Northern Pakistan. The noticed prevalence is gender- and age-dependent that might be due to their high exposures to the common risk factors. To avoid the transmission of HBV infection proper awareness about the possible risk factors and extension of immunization to the rural areas are recommended.</p