Enhanced Signal Sets for Hybrid Reflection Modulation

Hybrid reflection modulation (HRM) is a promising modulation technique which employs a combination of active and passive reflecting elements in reconfigurable intelligent surfaces (RIS). In addition to applying phase tuning, the active elements apply an amplification to its incident signal, which can alleviate the double-fading effect inherent in RIS systems. The choice of the elements to be made active conveys information bits through indexing. Additional bits can be conveyed through symbols from a modulation alphabet. In this letter, we propose methods to design improved HRM signal sets that achieve better bit error performance. The idea is to schedule the activation of tiles of elements in an ordered way that picks tiles with highest effective response and ignores those with lowest effective response. Specifically, we propose a signal set design procedure that efficiently packs non-equidistant signal points on the positive real line when all active elements use the same amplification factor. We further improve this signal set by obtaining the optimum amplification factors that maximize the minimum Euclidean distance of the signal set. Simulation results show improved performance of the proposed HRM signal sets compared to the that of basic HRM signal set introduced in the recent literature.

Authors

Institutions

Publication Details

Journal
IEEE Communications Letters
Published
2025-02-13
DOI
https://doi.org/10.1109/lcomm.2025.3541974
Primary Topic
Advanced Fiber Optic Sensors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Enhanced Signal Sets for Hybrid Reflection Modulation

Nirupam Roy, A. Chockalingam
IEEE Communications Letters
Advanced Fiber Optic Sensors
article

Enhanced Signal Sets for Hybrid Reflection Modulation

Nirupam Roy, A. Chockalingam
article en

Abstract

Hybrid reflection modulation (HRM) is a promising modulation technique which employs a combination of active and passive reflecting elements in reconfigurable intelligent surfaces (RIS). In addition to applying phase tuning, the active elements apply an amplification to its incident signal, which can alleviate the double-fading effect inherent in RIS systems. The choice of the elements to be made active conveys information bits through indexing. Additional bits can be conveyed through symbols from a modulation alphabet. In this letter, we propose methods to design improved HRM signal sets that achieve better bit error performance. The idea is to schedule the activation of tiles of elements in an ordered way that picks tiles with highest effective response and ignores those with lowest effective response. Specifically, we propose a signal set design procedure that efficiently packs non-equidistant signal points on the positive real line when all active elements use the same amplification factor. We further improve this signal set by obtaining the optimum amplification factors that maximize the minimum Euclidean distance of the signal set. Simulation results show improved performance of the proposed HRM signal sets compared to the that of basic HRM signal set introduced in the recent literature.

IEEE Communications LettersVol. 29(4)
Indian Institute of Management Bangalore (IN), Indian Institute of Science Bangalore (IN)
Affordable and clean energy
Openalex Percentile: Top 98%
Advanced Fiber Optic Sensors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Enhanced Signal Sets for Hybrid Reflection Modulation — Nirupam Roy, A. Chockalingam · IEEE Communications Letters (2025) | TGRS Research Map | TGRS