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http://hdl.handle.net/2080/4040| Title: | A low-complexity model for IRS-aided beyond 5G wireless networks |
| Authors: | Mati, Gyana Ranjan Das, Susmita Pradhan, Annapurna |
| Keywords: | Intelligent reflecting surface Received SNR Beamforming |
| Issue Date: | Jun-2023 |
| Publisher: | IEEE |
| Citation: | 2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Boston, USA, June 12-15, 2023 |
| Abstract: | The intelligent reflecting surface is a key reflecting mirror in fifth-generation (5G) and beyond 5G communication which ensures enhanced coverage by generating phase shift at the IRS. Solving IRS’s phase shift optimization problem is challenging and non-convex. In this regard, a low complexity model (LCM) is proposed for a multiple-input single-output (MISO) system to optimize passive and active beamforming. Based on initial results, the proposed method estimates IRS phase shifts accurately while being computationally less complex, which will allow it to be studied for multiple users and multiple-input multiple-output (MIMO) systems in the future. |
| Description: | Copyright belongs to the publisher |
| URI: | http://hdl.handle.net/2080/4040 |
| Appears in Collections: | Conference Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2023_ISWWMM_Gyana R Mati_A low.pdf | 309.55 kB | Adobe PDF | View/Open |
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