Combining Adaptive Smoothing And Decision-Directed Channel Estimation Algorithm And Implementation

Due to the high spectrum efficiency and low cost, the OFDM technology is widely used in all kinds of communication system. But with various kinds of complex channel environment, it's difficult to guarantee communication's quality. So the research on channel estimation algorithm which can adapt to a variety of signal noise ratio(SNR) conditions is necessary. Otherwise, considering the need to implement ideal algorithm with hardware, the algorithm should be simple enough.In this paper, the traditional pilot aided channel estimation scheme is improved. In order to improve OFDM system's performance in wireless environment, a combining adaptive smoothing and decision-directed channel estimator has been designed. Adaptive smoothing filter is used to improve system's bit error rate(BER) performance when the channel's SNR is low. While the Decision-Directed Channel Estimation is used to improve system's BER performance when the channel's SNR is high. Simulation result shows that the algorithm has 0.8~3dB SNR-BER performance improved than the least square(LS) estimation algorithm. After implementing the design with FPGA, it decreases the use of flip-flop(FF) resources by 8.83% and look up table(LUT) resources by 8.44%. Otherwise, the estimator is simple enough to be implemented with very large scale integration(VLSI). After Tape-out, the chip's area is 2421*1645um2, and the power consumption is 18.09 mW. The test results show that the algorithm's VLSI design has 12.55% less area and 12.61% less power dissipation than the similar design.