LTE Narrowband Internet of Things (NB-IoT) is a 3GPP 1 defined cellular technology that is designed to enable connectivity to many low-cost and low power/throughput IoT devices running delay-tolerant applications. NB-IoT can coexist within LTE spectrum either in a standalone mode, in-band with LTE or in guard-band of LTE. With NB-IoT designed to operate in very low signal to noise power ratios, the uplink receiver design presents several challenges. In this paper the design and performance of a NB-IoT uplink receiver is studied in detail. First, receiver design for NB-IoT uplink channels, with corresponding mathematical analysis, is presented. Specifically, it is shown how the time/frequency structure of signals can be exploited to enhance the receiver performance. Second, the performance of each channel is characterized with both link level simulations and implementation on a commercially deployed Qualcomm ® FSM TM platform 2 [1]. Comparisons against the 3GPP defined Radio Performance and Protocol aspect requirements 3 are also provided. Finally, implementation details are addressed and discussions on proposed enhancements to NB-IoT in 3GPP Release 15 are provided. It is shown how the proposed receiver algorithms can be adopted to Release 15 enhancements with minor or no modifications. The work in this paper is of significance to system designers looking to implement efficient NB-IoT uplink receiver to coexist with legacy LTE systems.

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Electrocardiograms (ECG) are extensively used for the diagnosis of cardiac arrhythmias. This paper investigates the use of machine learning classification algorithms for ECG analysis and arrhythmia detection. This is a crucial component of a conventional electronic health system, and it frequently necessitates ECG signal reduction for long-term data storage and remote transmission. Signal processing methods must be used to extract the function of the morphological properties of the ECG signal changing with time, which is difficult to discern in the typical visual depiction of the ECG signal. In biomedical research, signal processing and data analysis are commonly employed methodologies. This work proposes the use of an ECG arrhythmia classification method based on Fast Fourier Transform (FFT) for feature extraction and an improved AlexNet classifier to distinguish the difference between four types of arrhythmia conditions that were collected from records. The Convolutional Neural Network (CNN) algorithm’s results are compared to those of other algorithms, and the simulation results prove that the proposed technique is more effective for various parameters. The final results of the proposed system show that its ability to find deviations is 20% better than that of traditional systems.

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The 3rd Generation Partnership Project (3GPP) specification of the fifth generation (5G) New Radio (NR) allows for a highly scalable and flexible radio access technology to cater to network operators with different requirements. Such scalability and flexibilities in network configurations inevitably translate to complications in the design and implementation of 5G-NR systems. Radio access in 5G-NR is much more complex and involved than its predecessor, 4G long term evolution (LTE) and LTE-Advanced technology. Therefore, the 5G-NR specifications turn out to be quite dense. Specifically, the specifications are concise, design motivations rarely explained, and the information can be convoluted or distributed across several documents. Moreover, there are several key design details associated with the access layer procedures for any given physical layer channel, which are often omitted in the specifications. For example, design motivation aspects of initial access channels or signal generation can be quite difficult to follow or understand in 5G-NR. In this paper, all the design details associated with initial access channels and signal generation in 5G-NR specifications are laid out. The contributions of the paper are three folds. First, the design details and justifications associated with both downlink and uplink access channels are presented along with signal generation details. Secondly, receiver design aspects of NR PRACH short formats are discussed. Lastly, PRACH receiver implementation aspects and performance reports from different network operators are presented and compared with 3GPP specified Radio Performance and Protocol aspect requirements 1 for millimeter wave (mmW) access. The work in this paper is of significant value to researchers and system engineers looking to design and build initial access algorithms as part of 5G NR systems.