Low Power Area Efficient Adaptive Turbo Decoder Architecture For Wireless NoC

This research introduces a novel Turbo encoder and Adaptive Turbo decoder model designed to enhance Bit Error Rate (BER) performance across a spectrum of modulation schemes. The study systematically evaluates the model's efficacy in diverse channel environments, including AWGN, Rayleigh, and Rician channels, employing simulations and comparisons with conventional Adaptive Viterbi Decoder and Turbo decoder methods. Results underscore the Adaptive Turbo Decoding (ATD) model's superior BER performance, particularly as iterations increase. The investigation further extends to RF Wireless Network-On-Chip (WiNoC) scenarios, emphasizing the adaptability of ATD for effective error correction. Furthermore, the research explores the implications of ATD in Orthogonal Frequency Division Multiplexing (OFDM) systems, comparing models based on Fast Fourier Transform (FFT), Discrete Wavelet Transform (DWT), and Dual-Tree Complex Wavelet Transform (DTCWT). Notably, the ATD-DTCWT-OFDM model exhibits a substantial reduction in BER, showcasing the potential advantages of Dual-Tree Complex Wavelet Transform for OFDM modulation in acoustic channels with multipath. This research contributes valuable insights into the optimization of communication channels through the application of adaptive decoding techniques.