Towards the Performance Limit of Data-Aided Channel Estimation for 5G

Pilot-aided channel estimation has been popular for 4G wideband communication systems. Even though it is convenient, its limitation comes from the fact that the performance is bounded by the density of pilot symbols. Increasing pilot symbols improves channel estimation quality, but it also hurts bandwidth efficiency. In this paper, we advocate data-aided channel estimation for 5G. It is potentially the only solution to improve channel estimation quality without increasing pilot density. In particular, we aim to answer two fundamental questions for data-aided channel estimation: (1) What is the optimal scheme for data-aided channel estimation? (2) How can we make the optimal scheme practical by reducing its complexity? We present how we tackle these problems of data-aided channel estimation and show that the proposed iterative scheme yields significant gain in long term evolution (LTE) signal demodulation.