Intelligent Reflecting Surfaces for Compute-and-Forward

In this paper, we show that using Intelligent Reflecting Surfaces (IRS) can enhance the computing capability of a wireless network scenario. We consider a Multiple Access Channel (MAC) where a number of users aim to send data to a Base Station (BS). The BS is interested in decoding a linear combination of the data from different users in the corresponding finite field. By focusing on the Compute-and-Forward framework, we show that through carefully choosing the IRS parameters, such a scenario's computation rate will be significantly improved. More specifically, we formulate an optimization problem to maximize the computation rate and tackle the problem via an alternating optimization (AO) approach. Our results confirm the usefulness of IRS technology for future wireless networks -- such as 6G -- with massive computation requirements.