ABSTRACT Medical data transmission is a major challenge in wireless communication to preserve their integrity and coherence. Orthogonal frequency division multiplexing (OFDM) has emerged as a modulation scheme that can achieve high data rates over frequency selective fading channel by multipath effects. As the foetal ECG (FECG) signal is large to process, the dimensionality of the data is reduced by linear discriminant analysis (LDA) and is then sent through the space time block coded (STBC) multiple input multiple output (MIMO) upon using cockroach swarm pptimisation algorithm as a classifier to demarcate the FECG signal from noise. This paper also proposes decoder design for STBC transmission over frequency-selective time-variant channels with data recovery at the receiver by using proposed error prediction and correction adders (EPD) to achieve reduced peak to average power ration (PAPR). The simulation results prove that the PAPR reduces by 1.3 dB and the sensitivity of classifier is 96.4%. The implementations are carried out over 200 data sets taken from MIT-BIH arrhythmia using simulation tools such as MATLAB 2013b, ModelSim 10.0b and Cadence Virtuoso under 65 nm. The finally fabricated and tested decoder chip consumes an average power of 0.64 µW.

中文翻译：

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FECG 监测中降低 PAPR 的节能 VLSI 解码器芯片

摘要 医疗数据传输是无线通信中保持其完整性和一致性的主要挑战。正交频分复用 (OFDM) 已成为一种调制方案，它可以通过多径效应在频率选择性衰落信道上实现高数据速率。由于胎儿心电图 (FECG) 信号需要处理很大，因此通过线性判别分析 (LDA) 降低数据的维数，然后在使用蟑螂时通过空时块编码 (STBC) 多输入多输出 (MIMO) 发送swarm pptimisation 算法作为分类器从噪声中区分 FECG 信号。本文还提出了通过使用建议的错误预测和校正加法器 (EPD) 来实现降低的峰均功率比 (PAPR) 的接收端数据恢复的频率选择性时变信道上 STBC 传输的解码器设计。仿真结果证明PAPR降低了1.3 dB，分类器的灵敏度为96.4%。使用 MATLAB 2013b、ModelSim 10.0b 和 Cadence Virtuoso 等仿真工具在 65 nm 下对来自 MIT-BIH 心律失常的 200 多个数据集进行了实施。最终制造和测试的解码器芯片的平均功耗为 0.64 µW。使用 MATLAB 2013b、ModelSim 10.0b 和 Cadence Virtuoso 等仿真工具在 65 nm 下对来自 MIT-BIH 心律失常的 200 多个数据集进行了实施。最终制造和测试的解码器芯片的平均功耗为 0.64 µW。使用 MATLAB 2013b、ModelSim 10.0b 和 Cadence Virtuoso 等仿真工具在 65 nm 下对来自 MIT-BIH 心律失常的 200 多个数据集进行了实施。最终制造和测试的解码器芯片的平均功耗为 0.64 µW。