Data transfer for health monitoring can be highly critical because of life dependency transmitted data. IEEE 802.15.6 is a standard for wireless body area network published in 2012 to satisfy the reliability which is required by health monitoring systems. Ultra wideband is one of proposed physical layer technologies specified in the wireless body area network standard which offers high bandwidth, low power, and low interference with other devices. Orthogonal frequency-division multiplexing is commonly used to transmit the data in many wireless communication standards due to its high spectral efficiency and immunity to the inter symbol interference. In this study, bit-error rate performance for orthogonal frequency-division multiplexing with different interpolation based least square channel estimation is given for wireless body area network channel model. OFDM symbol length and pilot length used in OFDM symbol is investigated in bit error rate -signal to noise ratio graphs.
In this paper, a Look-Up- Table (LUT) based calculation for implementing loglikelihood ratio (LLR) of the Maximum a Posterior (MAP) decoder is introduced and analysed. In the region of low signal to noise ratio, the analysed performances of turbo coding have been found very satisfying. However, when implementing the MAP turbo decoder, the required calculation for LLR is too complex prohibiting its applications. In order to reduce the complexity a dynamic-LUT based simplification is proposed whereas a static-LUT never converge the expectations, since the limited size and resolution of LUT dramatically degrade the performance. In order to maintain simplicity for a high performance implementation, a dynamic LUT, which has partial resolutions in separate decision regions and being re-calculated for further iterations of decoding, is proposed. One of the most important results obtained is that our proposed dynamic-LUT based MAP algorithm removes "ln(·)" process, which is the natural logarithm in LLR's calculation. Therefore, it reduces high computational complexity in the MAP algorithm with some reasonable performance degradations.
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