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3–10 GHz ultra wideband front‐end transceiver in 0.13 μm complementary metal oxide semiconductor for low‐power biomedical radar
Author(s) -
Wang Xubo,
Dinh Anh,
Teng Daniel
Publication year - 2014
Publication title -
iet circuits, devices and systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.251
H-Index - 49
eISSN - 1751-8598
pISSN - 1751-858X
DOI - 10.1049/iet-cds.2013.0331
Subject(s) - diplexer , transceiver , transmitter , ultra wideband , radar , electrical engineering , electronic engineering , amplifier , low noise amplifier , noise figure , front and back ends , engineering , computer science , telecommunications , cmos , channel (broadcasting) , mechanical engineering
A new integrated low‐power, low‐complexity ultra wideband (UWB) transceiver front‐end in standard 130 nm complementary metal oxide semiconductor technology which can be used in UWB radar biomedical sensing applications is proposed in this study. The transceiver comprises of a full UWB band transmitter, an on‐chip diplexer and a full UWB band receiver front‐end. The transmitter generates Gaussian‐pulse‐modulated and rectangular‐pulse‐modulated signals at different carrier frequencies within the designated UWB by using a digitally controlled oscillator. The transmitter consumes an average power of 8 mW at a 10 MHz pulse rate. The on‐chip diplexer has a 1 dB insertion loss and an isolation of −30 dB. Its switch is co‐designed with the receiver's input matching network to optimise the power matching while achieving good noise performance. The receiver low noise amplifier has a 3–10 GHz input matching bandwidth with a power gain of 16 dB. The overall receiver front‐end consumes an average power of 12 mW. The core area of the transceiver circuit is 500 μm by 1100 μm. The experiments show that the proposed radar transceiver can successfully detect a human respiration pattern within 50 cm. This novel design using a DCO‐type UWB transceiver integrated with an on‐chip diplexer demonstrates the use of the low power UWB radar detection in biomedical applications.

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