In this work, we show that using Intelligent Reflecting Surfaces (IRS) can enhance 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 by carefully choosing the IRS parameters, the computation rate of such scenario will be greatly improved. Mores pecifically, we formulate an optimization problem to maximizethe computation rate, and tackle the problem via an alternating optimization approach. Our results confirm the usefulness of IRS technology for future wireless networks –such as 6G– with massive computation requirements.
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