Project DetailsIntelligent Reflective Surface (IRS) is a promising technology for improving the data transmission rate in hard direct channel conditions. In this paper, we describe our solution to estimate the relevant channels and configure the IRS for efficient wireless communications, as part of the 2021 IEEE Signal Processing Cup (SP Cup) competition. First, we estimate the wireless channel and then find an IRS configuration that maximizes the rate of that channel. We begin with the provided
far-from-optimal IRS configurations and apply an iterative optimization technique based on gradient descent and adaptive quantization. Further optimization is obtained by training a deep generative neural network to find a configuration that maximizes the rate function. The best configurations we have discovered provide a significant improvement of the weighted average rate from 104.07 Mbit/s to 120.70 Mbit/s, compared to the best provided configurations over all users. Non-IRS based solution provides an average rate of 4.38 Mbit/s.
