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Please use this identifier to cite or link to this item: http://10.10.120.238:8080/xmlui/handle/123456789/409
Title: Analysis of Hierarchical Rate Splitting for Intelligent Reflecting Surfaces-Aided Downlink Multiuser MISO Communications
Authors: Bansal A.
Singh K.
Li C.-P.
Keywords: downlink
Intelligent reflecting surface (IRS)
multiple-input single-output (MISO)
multiuser
rate splitting (RS)
Issue Date: 2021
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: An intelligent reflecting surface (IRS) is an emerging technology in the next-generation (B5G and 6G) wireless communications with the aim of improving the spectral/energy efficiency of the wireless networks. In this paper, we focus on multiple IRS-aided multiuser multiple-input single-output (MISO) downlink network, where each IRS is deployed near to the cell boundary of the cellular network in order to help the downlink transmission to the cell-edge users. To achieve the significant performance benefits provided by the rate-splitting (RS) transmission in multiuser scenario, two-layer hierarchical rate splitting (2L-HRS) technique is deployed at the base station (BS) to serve all the users. Furthermore, we propose an On-Off scheme for controlling the IRSs with practical phase shifts. In order to analyze the performance of the users, we derive the closed-form expressions of outage probability for both cell-edge users and near users. By extensive Monte Carlo simulations, we demonstrate that the proposed design framework outperforms the corresponding one-layer RS (1L-RS), the multiuser linear precoding (MU-LP) and 2L-HRS without IRS. In addition, we reveal the advantages of introducing RS-based IRS in improving the cell-users' performance. The impact of channel estimation errors due to imperfect channel state information, and the various network's parameters, such as the number of reflecting elements and the number of cell-users, on the network performance is demonstrated. © 2020 IEEE.
URI: https://dx.doi.org/10.1109/OJCOMS.2021.3070340
http://localhost:8080/xmlui/handle/123456789/409
ISSN: 2644125X
Appears in Collections:Journal Article

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