Intelligent reflecting surface (IRS) is a revolutionizing approach for achieving low-cost yet spectral and energy efficient wireless communications. By properly tuning its massive reflecting elements, IRS is able to construct favorable channels and thereby significantly improve the wireless communication performance in various setups. In this paper, we consider the general wireless network consisting of multiple base stations (BSs), users and IRSs, and investigate their joint association optimization in the downlink communication. Specifically, each IRS assists in the communication from its associated BS to user and in the meanwhile randomly scatters the signals from the other non-associated BSs. As such, the joint BS-IRS-user association is more involved as compared to the BS-user association in conventional wireless networks without IRS. To address this new problem, we first derive the average signal-to-interference-plus-noise ratio (SINR) of each user in closed-form and then formulate the joint association problem to maximize the users' utility in the downlink communication. Both the optimal and low-complexity suboptimal solutions are proposed for the formulated problem. Numerical results demonstrate significant performance gains of the proposed solutions over benchmark schemes.
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