Positioning Information-Based Codebook for Reconfigurable Intelligent Surface Passive Beamforming

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Abstract
In this paper, we design a positioning information (PI) based codebook (PI-CB) for reconfigurable intelligent surface (RIS) passive beamforming (PBF), in online stage. In which, corresponding to each reflection pattern (RP), the current user equipment (UEs) PI, which are widely and easily available in communication networks, are stored. Moreover, for further overhead reduction, and based on the stored PI, we propose a partial PI-CB scheme for PBF of the RIS, where a group of candidate RPs, that are highly probable to serve the UEs, is determined depending on a distance metric. Consequently, the system can select the best RP by training only this group of RPs instead of searching the entire PI-CB. The proposed full and partial PI-CB schemes highly reduce the overhead and complexity, especially in large RIS. Also, they outperform channel estimation and alternating optimization (CE&AO) based and randomly generated CB based schemes in terms of effective achievable rate, particularly in rapidly changing channels. The proposed schemes can obtain about 35% increase in the effective achievable rate compared to CE&AO based scheme in 4 users’ scenario with extremely low complexity. In addition, using the partial PI-CB, further reduction in overhead and complexity can be achieved with a slight decrease in performance due to the positioning error.
Funding Information
  • Project ‘MObility and Training fOR Beyond 5G Eco-Systems (MOTOR5G),’
  • European Union’s Horizon 2020 Programme under the Marie Skłodowska Curie Actions (MSCA) Innovative Training Network (861219)

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