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Intelligent reflecting surface (IRS)-aided communication is a promisingtechnology for beyond 5G (B5G) systems, to reconfigure the radio environmentproactively. However, IRS-aided communication in practice requires efficientchannel estimation or passive beam training, whose overhead and complexityincrease drastically with the number of reflecting elements/beam directions. Totackle this challenge, we propose in this paper a novel environment-aware jointactive and passive beam selection scheme for IRS-aided wireless communication,based on the new concept of channel knowledge map (CKM). Specifically, byutilizing both the location information of the user equipment (UE), which isreadily available in contemporary wireless systems with ever-increasingaccuracy, and the environment information offered by CKM, the proposed schemeachieves efficient beam selection with either no real-time training required(training-free beam selection) or only moderate training overhead(light-training beam selection). Numerical results based on practical channelsobtained using commercial ray tracing software are presented, which demonstratethe superior performance of the proposed scheme over various benchmark schemes.

Environment-Aware Beam Selection for IRS-Aided Communication with Channel Knowledge Map