Intelligent reflecting surfaces (IRSs) are a promising technology for enhancing coverage and spectral efficiency, especially in the millimeter wave (mmWave) bands. Existing approaches to leverage the benefits of IRS involve a resourceintensive channel estimation step followed by a computationally expensive algorithm to optimize the reflection coefficients at the IRS. In this work, we present and analyze several alternative schemes, where the phase configuration of the IRS is randomized and multi-user diversity is exploited to opportunistically select the best user at each point in time for data transmission. We show that the throughput of an IRS assisted opportunistic system asymptotically converges to the optimal beamformingbased throughput under fair allocation of resources, as the number of users gets large. Further, for all the proposed schemes, we derive the scaling law of the throughput in terms of the number of users and IRS elements, as the number of users gets large. We also introduce schemes that enhance the rate of convergence of the opportunistic rate to the beamforming rate as the number of users is increased. Following this, we extend the setup to wideband channels via an orthogonal frequency division multiplexing (OFDM) system and discuss two opportunistic schemes in an IRS assisted setting that elucidate the superior performance that IRS aided systems can offer over conventional systems at very low implementation cost and complexity.

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