Making the Switch to 5G and 60 GHz in mHealth Applications Using USRP Hardware

Bruendl, Stefan A; Fang, Hua

doi:10.1109/mic.2019.2962797

Cited by 6 publications

(2 citation statements)

References 16 publications

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“…Following the success of 2G, 3G, and 4G technologies, 5G technology has been proposed for its higher throughput. This new technology aims to provide benefits to the development of Internet of Things (IoT) that incorporates wireless sensor networks, wireless mesh networks, wearable health care systems [19][20][21], etc. According to the report by the World Health Organization (WHO), a lack of healthcare workers is expected by 2035 [22].…”

Section: Biomedical Devices Through 5g and Next-generation Technologiesmentioning

confidence: 99%

Magic of 5G Technology and Optimization Methods Applied to Biomedical Devices: A Survey

2022

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Wireless networks have gained significant attention and importance in healthcare as various medical devices such as mobile devices, sensors, and remote monitoring equipment must be connected to communication networks. In order to provide advanced medical treatments to patients, high-performance technologies such as the emerging fifth generation/sixth generation (5G/6G) are required for transferring data to and from medical devices and in addition to their major components developed with improved optimization methods which are substantially needed and embedded in them. Providing intelligent system design is a challenging task in medical applications, as it affects the whole behaviors of medical devices. A critical review of the medical devices and the various optimization methods employed are presented in this paper, to pave the way for designers to develop an apparatus that is applicable in the healthcare industry under 5G technology and future 6G wireless networks.

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Section: Biomedical Devices Through 5g and Next-generation Technologiesmentioning

confidence: 99%

Magic of 5G Technology and Optimization Methods Applied to Biomedical Devices: A Survey

2022

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“…In the last decade, reconfigurable PHYbased software-defined radios (SDR) were envisioned, which can reconfigure itself on-the-fly, thereby offering flexible and upgrade-able architectures [8], [25], [26]. For the realization of PHY, the first step is to validate its functionality in the real-radio environment, and Universal Software Radio Peripheral (USRP) based testbed is widely used for such performance analysis [27]- [30]. These testbeds allow the software-based implementation of the baseband algorithms and RF front-end to validate the performance in a real radio environment.…”

Section: Related Workmentioning

confidence: 99%

Toward Intelligent Reconfigurable Wireless Physical Layer (PHY)

Singh

Santosh

Darak

2021

IEEE Open J. Circuits Syst.

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Next-generation wireless networks are getting significant attention because they promise 10factor enhancement in mobile broadband along with the potential to enable new heterogeneous services. Services include massive machine type communications desired for Industrial 4.0 along with ultra-reliable low latency services for remote healthcare and vehicular communications. In this article, we present the design of intelligent and reconfigurable physical layer (PHY) to bring these services to reality. First, we design and implement the reconfigurable PHY via a hardware-software co-design approach on system-on-chip consisting of the ARM processor and field-programmable gate array (FPGA). The reconfigurable PHY is then made intelligent by augmenting it with online machine learning (OML) based decision-making algorithm. Such PHY can learn the environment (for example, wireless channel) and dynamically adapt the transceivers' configuration (i.e., modulation scheme, word-length) and select the wireless channel on-the-fly. Since the environment is unknown and changes with time, we make the OML architecture reconfigurable to enable dynamic switch between various OML algorithms on-the-fly. We have demonstrated the functional correctness of the proposed architecture for different environments and word-lengths. The detailed throughput, latency, and complexity analysis validate the feasibility and importance of the proposed intelligent and reconfigurable PHY in next-generation networks.INDEX TERMS Intelligent reconfigurable architecture, zynq SoC, physical layer, machine learning, multiarmed bandit.

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