OTFS-Modulated MIMO Faster-than-Nyquist Signaling in Doubly Selective Fading Channel

This paper proposes a novel reduced-complexity detection scheme for multiple-input multiple-output (MIMO)-assisted faster-than-Nyquist (FTN) signaling scheme in the doubly selective fading channels. By utilizing the channel’s sparse approximation, we exploit a simplified linear minimum mean square error (LMMSE) algorithm with a log-linear complexity. The proposed scheme attains the same bit error rate performance as the conventional LMMSE detector while attaining a significantly lower complexity. Furthermore, we propose the amalgamation of MIMO-FTN signaling and orthogonal time frequency space modulation and conceive the low-complexity delay Doppler domain detection algorithm by exploiting the channel’s sparsity.

Authors

Institutions

Publication Details

Published
2025-06-08
DOI
https://doi.org/10.1109/iccworkshops67674.2025.11162265
Primary Topic
PAPR reduction in OFDM
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

OTFS-Modulated MIMO Faster-than-Nyquist Signaling in Doubly Selective Fading Channel

Shinya Sugiura, Zekun Hong
PAPR reduction in OFDM
article

OTFS-Modulated MIMO Faster-than-Nyquist Signaling in Doubly Selective Fading Channel

Shinya Sugiura, Zekun Hong
article en

Abstract

This paper proposes a novel reduced-complexity detection scheme for multiple-input multiple-output (MIMO)-assisted faster-than-Nyquist (FTN) signaling scheme in the doubly selective fading channels. By utilizing the channel’s sparse approximation, we exploit a simplified linear minimum mean square error (LMMSE) algorithm with a log-linear complexity. The proposed scheme attains the same bit error rate performance as the conventional LMMSE detector while attaining a significantly lower complexity. Furthermore, we propose the amalgamation of MIMO-FTN signaling and orthogonal time frequency space modulation and conceive the low-complexity delay Doppler domain detection algorithm by exploiting the channel’s sparsity.

The University of Tokyo (JP)
Openalex Percentile: Top 75%
PAPR reduction in OFDM
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.