脑电可穿戴无线射频发射芯片系统的研究
Research of Brain EEG Wireless Radio Transmitter IC System for Wearable Application
DOI: 10.12677/OE.2016.62007,
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作者:
孙建辉*, 刘军涛, 王蜜霞, 徐声伟, 蔡新霞:中国科学院电子学研究所,传感技术联合国家重点实验室(北方基地),北京;中国科学院大学,北京
关键词:
脑电EEG;数模混合芯片设计;FSK/OOK;射频直接上变频;相位噪声;DSP流水硬件加速器;Brain EEG; Mixed Analog/Digital IC Design; FSK/OOK; Radio Frequency Direct-up-Conversion; Phase Noise; Pipeline DSP Hardware Accelerator
摘要:
针对脑电EEG (electroencephalograph)传感网络近距离无线传输与可穿戴应用的需要,给出了一款无线射频电路控制系统:集成了模拟电路(8通道低噪声脑电放大器与中速SAR-ADC模数转换)、信道编码EEG-DSP加速器、射频发射芯片。在ISM-2.4 GHz波段,射频物理层使用射频直接上变频架构,通过FSK/OOK (on-off-keying)的数据调制方式;重点优化基于PLL的频率综合器(PLL-FS)与可开关的E类功率放大器(PA-E);PLL-FS具有低相位噪声(−119 dBc/Hz@1 MHz)、锁定时间短(28~60 us)、环路特性好的特点;PA优化了输出功率(4~5 dBm)、功率增加效率PAE(25%)、S-参数等。流水EEG-DSP负责整体系统控制、数据缓存、精简无线信道编码以及输出码流调制射频电路。设计利用Cadence Co.的SpecterRF软件、Synopsys Co.的系列数字软件/Caliber软件进行了功能仿真/物理版图验收,设计使用SmicRF180 nm数模混合工艺进行了加工,流片回来的测试结果表明EEG-DSP与射频发射芯片可以满足实际应用。
Abstract:
Focus on the brain EEG (electroencephalograph) transducer network short range transmitting and wearable application, the design gives an integrated wireless controlling system which is composed by analog circuit (eight-channel EEG low-noise amplifier and intermediate speed SAR-ADC), wireless channel coding EEG-DSP accelerator, low-power and robust radio frequency chip. At the ISM-2.4 GHz frequency band, the radio frequency chip uses the radio frequency di-rect-up-conversion architecture, with FSK/OOK data modulation method. The design has opti-mized the frequency synthesizer based on PLL, the PA’s outputting power (4 - 5 dBm), PAE (power added efficiency: 25%), S-Parameters have been optimized too. The pipeline EEG-DSP is responsible for the whole system’s controlling, data storage, reduced wireless channel coding and bit-stream outputting. The design uses the Cadence Co’s SpectreRF, Synopsys Co.’s serial logic-design tools, Caliber Co.’s tool to complete the function verify/physical layout signoff. These chips have been manufactured by the SmicRF180 nm analog/digital mixed technology, and the back’s chips test results show that the EEG-DSP and RF chip’s critical parameters satisfy the expected proposed requirements.
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