A Novel Energy-Efficient MIMO-OFDM Decoder Architecture with Error Detection

Abstract

Medical data transmission is a major challenge in wireless communication to preserve their integrity and coherence. As the transmission takes place at high data rate, the complexity and throughput of the system, pertaining to the fetal ECG signal, is crucial. In addition to the accumulation of noises in the channel, the observation of fetal ECG signal, using diagnostic devices, also provides additive noise, thereby reducing the quality of the transmitted signal. The major motive of this paper is to demarcate the fetal ECG signal from noise at early stages of transmission using Chambolle-Pock based hybridized classifiers. This technique provides sensitivity of 91.1% followed by performance validation of Error Detection and correction adders for different decoder architectures in transceiver. Thereby area and power reduction of 86.3% and 91.1% is achieved. The simulations are carried out with MIT-BIH Arrhythmia using simulation tools, such as MATLAB 2013b, ModelSim 10.0b, and Cadence Virtuoso under 90 nm on over 200 data sets.

Keywords:

• Additive noises
• Decoder architectures
• Error detection and correction adders
• Evolution algorithms

Additional information

Notes on contributors

D. Preethi

D Preethi received the BE degree in electronics and communication engineering from Avinashilingam University, Tamil Nadu, India, in 2013, ME degree in VLSI design from Avinashilingam University, Tamil Nadu, India, in 2015, and is currently pursuing PhD degree in information and communication engineering from Anna University, Tamil Nadu, India. Presently, she is working as assistant professor in the Department of Electronics and Communication Engineering at Bannari Amman Institute of Technology, Tamil Nadu, India. Her research interests include machine learning algorithms, optimization of digital circuits and signal processing.

R. S. Valarmathi

R S Valarmathi received the BE degree in electronics and communication engineering from Bharathiyar University, Tamil Nadu, India, in 1989, ME degree in applied electronics from Bharathiyar University, Tamil Nadu, India, in 2000, and PhD degree in information and communication engineering from Anna University, Tamil Nadu, India in 2009. Presently, she is working as senior professor and dean faculty development and industry relations in the Department of Electronics and Communication Engineering at Bannari Amman Institute of Technology, Tamil Nadu, India. Her research interests include machine learning algorithms, image processing, biometrics and signal processing. Email: [email protected]