Performance analysis of adaptive OFDM system for Broadband Power Line Network

Power Line Network is proposed as an alternative for broadband data transmission especially in developing countries like India. The power line channel is affected by stochastic attenuation, multipath propagation and noise which can lead to the limitation of channel capacity and achievable data rate. One of the promising approaches to mitigate the problem is adaptive OFDM (AOFDM). Adaptive transmission methods can potentially aid to achieve high data rates in Broadband Power Line Communication (BPLC) system. To realize this potential, the transmitter needs accurate Channel State Information (CSI) for the upcoming transmission frame. Several fundamental issues arise in the design and testing of fading prediction algorithms for adaptive transmission methods using OFDM system. These include complexity, robustness, channel estimation and noise reduction. This paper proposes an optimal approach of Exponential Effective SNR Mapping (EESM) on prediction of the BER over all subcarriers. A fading prediction scheme using Neural Network for OFDM system is investigated to select a suitable Modulation and Coding Scheme (MCS) for the current PLC channel realization which renders high throughput. The proposed method of EESM with selective modulation for OFDM enhances the system throughput about 9% and reduces the feedback overhead compared to the conventional EESM scheme in PLC system. Simulation results show that the proposed adaptive algorithm with Neural network prediction scheme can achieve a considerable improvement in the processing time over the conventional method.