Peng, Tong, Wang, Yi, Burr, Alister Graham orcid.org/0000-0001-6435-3962 et al. (1 more author) (2018) An Adaptive Optimal Mapping Selection Algorithm for PNC using Variable QAM Modulation. IEEE wireless communications letters. 412 - 415. ISSN 2162-2345
Abstract
Fifth generation wireless networks will need to serve much higher user densities than existing 4G networks, and will therefore require an enhanced radio access network (RAN) infrastructure. Physical layer network coding (PNC) has been shown to enable such high densities with much lower back- haul load than approaches, such as Cloud-RAN and coordinated multipoint. In this letter, we present an engineering applicable PNC scheme which allows different cooperating users to use different modulation schemes, according to the relative strength of their channels to a given access point. This is in contrast with compute-and-forward and previous PNC schemes which are designed for the two-way relay channel. A two-stage search algorithm to identify the optimum PNC mappings for given channel state information and modulation is proposed in this letter. Numerical results show that the proposed scheme achieves low bit error rate with reduced backhaul load.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 25 Oct 2018 13:30 |
Last Modified: | 16 Oct 2024 15:13 |
Published Version: | https://doi.org/10.1109/LWC.2018.2874052 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.1109/LWC.2018.2874052 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:137812 |