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Existing works on IRS have mainly considered IRS being deployed in theenvironment to dynamically control the wireless channels between the BS and itsserved users. In contrast, we propose in this paper a new integrated IRS BSarchitecture by deploying IRSs inside the BS antenna radome. Since the distancebetween the integrated IRSs and BS antenna array is practically small, the pathloss among them is significantly reduced and the real time control of the IRSreflection by the BS becomes easier to implement. However, the resultant nearfield channel model also becomes drastically different. Thus, we propose anelement wise channel model for IRS to characterize the channel vector betweeneach single antenna user and the antenna array of the BS, which includes thedirect (without any IRS reflection) as well as the single and doubleIRS-reflection channel components. Then, we formulate a problem to optimize thereflection coefficients of all IRS reflecting elements for maximizing theuplink sum rate of the users. By considering two typical cases with/withoutperfect CSI at the BS, the formulated problem is solved efficiently by adoptingthe successive refinement method and iterative random phase algorithm (IRPA),respectively. Numerical results validate the substantial capacity gain of theintegrated IRS BS architecture over the conventional multi antenna BS withoutintegrated IRS. Moreover, the proposed algorithms significantly outperformother benchmark schemes in terms of sum rate, and the IRPA without CSI canapproach the performance upper bound with perfect CSI as the training overheadincreases.

Integrating Intelligent Reflecting Surface into Base Station: Architecture, Channel Model, and Passive Reflection Design