paper-with-me

Papers

Cognitive IoT based Health Monitoring Scheme using Non-Orthogonal Multiple Access

2020-07-21 · Ashiqur Rahman Rahul, Saifur Rahman Sabuj, Majumder Fazle Haider, Shakil Ahmed

It has become very essential to address the limited spectrum capacity and their efficient utilization to support the increasing number of Internet of Things devices. When it comes to medical infrastructure, it becomes very imperative for medical devices to communicate with the base station. In such situations, communication over the wireless medium must provide optimized throughput (data rate) with effectual energy usage, which will ensure precise medical feedback by the responsible staff. Taking into account, it is necessary to operate wireless communication precisely at a higher frequency with more substantial bandwidth and low latency. Cognitive Radio (CR) is traditionally a viable choice, where it identifies and utilizes the vacant spectrum, thus maximizing the primary user's capacity and achieving spectral efficiency. To ensure such outcomes, the Non-Orthogonal Multiple Access (NOMA) techniques have proven to deliver an effective solution to the increasing number of devices with unimpaired performance, especially when the communication shifts towards a higher frequency band such as the mmWave band. In this chapter, IoT based CR network in uplink communication is proposed alongside employing NOMA techniques for optimal throughput, and energy efficiency for a medical infrastructure. Numerical results show that effectual throughput and energy efficiency for a High Reliable Communication (HRC) device and Moderate Reliable Communication (MRC) device improve over 83.13% and 73.95%, respectively and their corresponding energy efficacy values show vast improvement (83.11% and 73.96% respectively). Likewise, for interference case both the throughput and the energy efficiency improve approximately over 93% for all devices.

📄 PDF Abstract BibTeX arXiv:2007.10607

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

InfoGAN-MSF: a data augmentation approach for correlative bridge monitoring factors

2021-08-09 · IOP Publishing Ltd 2021 8 · Ping Wan1, Hongli He2, Ling Guo1, Jiancheng Yang1 and Jie Li3 외

Bridge health evaluation has been a challenging issue due to high assessment errors with imbalanced and insufficient monitoring data of correlative bridge monitoring factors. We propose a data augmentation model as the p…

Data Augmentation

Joint Transmission in QoE-Driven Backhaul-Aware MC-NOMA Cognitive Radio Network

2020-08-30 · Hosein Zarini, Ata Khalili, Hina Tabassum, Mehdi Rasti

In this paper, we develop a resource allocation framework to optimize the downlink transmission of a backhaul-aware multi-cell cognitive radio network (CRN) which is enabled with multi-carrier non-orthogonal multiple acc…

Scheduling

Robust Beamforming Design in a NOMA Cognitive Radio Network Relying on SWIPT

2018-07-11

This paper studies a multiple-input single-output non-orthogonal multiple access cognitive radio network relying on simultaneous wireless information and power transfer. A realistic non-linear energy harvesting model is …

Artificial Noise Aided Secure Cognitive Beamforming for Cooperative MISO-NOMA Using SWIPT

2018-02-20

Cognitive radio (CR) and non-orthogonal multiple access (NOMA) have been deemed two promising technologies due to their potential to achieve high spectral efficiency and massive connectivity. This paper studies a multipl…

VCR: Learning Valid Contextual Representation for Incomplete Wearable Signals

2026-05-13 · Yuxuan Weng, Wenhan Luo, Qijia Shao arxiv

Wearable devices enable continuous health monitoring from multimodal signals, but real-world deployment is hindered by limited labeled data and pervasive sensor incompleteness. While large-scale self-supervised pretraini…