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dc.contributor.authorKopta, V.
dc.contributor.authorEnz, C. C.
dc.date.accessioned2021-12-09T14:03:59Z
dc.date.available2021-12-09T14:03:59Z
dc.date.issued2019
dc.identifier.citationIeee Journal of Solid-State Circuits, vol. 54 (9), pp. 2462-2474, Sep 2019.
dc.identifier.urihttps://yoda.csem.ch/handle/20.500.12839/344
dc.description.abstractThis paper presents a 4-GHz FM ultra-wideband (UWB) transceiver designed for the Internet of Things and body area network applications. Robustness to interferers and low power spectral density allow FM-UWB to coexist with narrowband radios, while large signal bandwidth strongly relaxes constraints on the frequency synthesis blocks enabling the full integration of the radio at low power. The transceiver, integrated with a 65-nm standard CMOS technology, consists of a transmitter and two receivers that provide two modes of operation. The transmitter consumes 575 mu W while transmitting a 100-kb/s signal at 4 GHz at an output power of -11.4 dBm. A single RF IO pad is used and the fully integrated matching network is shared among the transmitter and the receivers. The low-power receiver consumes 267 mu W and provides a single communication channel at 100 kb/s in the 4-GHz band, with a -57-dBm sensitivity. The second receiver provides a better performance and takes full advantage of the FM-UWB features, as it implements wireless communication with up to four parallel channels sharing the same RF band. It consumes 550 mu W and provides -68-dBm sensitivity at 100 kb/s per channel. The FM-UWB architecture can tolerate a very large reference frequency offset of up to and/- 8000 ppm. This unique feature potentially allows for a quartz free synthesizer, resulting in a radio with no off-chip components.
dc.subjectFM ultra-wideband (UWB), FSK, fully integrated, Internet of Things, (IoT), low power, multi-user (MU), transceiver, wideband, wireless, receiver, design, filter, range, Engineering
dc.titleA 4-GHz Low-Power, Multi-User Approximate Zero-IF FM-UWB Transceiver for IoT
dc.typeJournal Article
dc.type.csemdivisionsDiv-M
dc.type.csemresearchareasIoT & Vision
dc.identifier.doihttps://doi.org/10.1109/jssc.2019.2917837


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