Jointly-Mapped Reflection Modulation with Reconfigurable Intelligent Surfaces
Karunasena, Pasan; Rajatheva, Nandana; Rajapaksha, Nuwanthika; Dampahalage, Dilin; Marasinghe, Dileepa; Latva-Aho, Matti (2024-08-20)
Karunasena, Pasan
Rajatheva, Nandana
Rajapaksha, Nuwanthika
Dampahalage, Dilin
Marasinghe, Dileepa
Latva-Aho, Matti
IEEE
20.08.2024
P. Karunasena, N. Rajatheva, N. Rajapaksha, D. Dampahalage, D. Marasinghe and M. Latva-Aho, "Jointly-Mapped Reflection Modulation with Reconfigurable Intelligent Surfaces," ICC 2024 - IEEE International Conference on Communications, Denver, CO, USA, 2024, pp. 581-586, doi: 10.1109/ICC51166.2024.10622855
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© 2024 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.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202412097099
https://urn.fi/URN:NBN:fi:oulu-202412097099
Tiivistelmä
Abstract
Reconfigurable intelligent surfaces (RIS)-based communications with reflection modulation (RM) is a novel area of research that opens up a range of unconventional modulation techniques. Existing literature primarily focuses on specific applications where the RIS encodes its own information onto its reflection pattern. Quadrature reflection modulation (QRM) and reflection pattern modulation (RPM) are two promising reflection pattern designs that effectively deliver local data available at the RIS. This paper explores a more general application of RIS-based information transfer for a single-user downlink system via jointly mapped RM (JRM), where the RIS and the access point (AP) jointly deliver the information available at the AP. The data symbols are mapped to a constellation of tuples, each tuple containing a transmit signal and a reflection pattern. Two JRM constellation designs are proposed, namely jointly-mapped QRM (JQRM) and jointly-mapped RPM (JRPM). The proposed constellation design employs a smaller transmit signal set size compared to a generic modulation scheme, increasing the separation among adjacent constellation points. A jointly active and passive beamforming design is adopted for a multiple-input-single-output (MISO) downlink system. The simulation results analyze and compare the bit-error-rate (BER) performance of the proposed JQRM and JRPM schemes, with their respective separately-mapped counterparts and theoretical upper bounds as benchmarks.
Reconfigurable intelligent surfaces (RIS)-based communications with reflection modulation (RM) is a novel area of research that opens up a range of unconventional modulation techniques. Existing literature primarily focuses on specific applications where the RIS encodes its own information onto its reflection pattern. Quadrature reflection modulation (QRM) and reflection pattern modulation (RPM) are two promising reflection pattern designs that effectively deliver local data available at the RIS. This paper explores a more general application of RIS-based information transfer for a single-user downlink system via jointly mapped RM (JRM), where the RIS and the access point (AP) jointly deliver the information available at the AP. The data symbols are mapped to a constellation of tuples, each tuple containing a transmit signal and a reflection pattern. Two JRM constellation designs are proposed, namely jointly-mapped QRM (JQRM) and jointly-mapped RPM (JRPM). The proposed constellation design employs a smaller transmit signal set size compared to a generic modulation scheme, increasing the separation among adjacent constellation points. A jointly active and passive beamforming design is adopted for a multiple-input-single-output (MISO) downlink system. The simulation results analyze and compare the bit-error-rate (BER) performance of the proposed JQRM and JRPM schemes, with their respective separately-mapped counterparts and theoretical upper bounds as benchmarks.
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