Dual-mode Index Modulation based on Affine Frequency Division Multiplexing

IF 2 4区 计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC
Anoop A. , Christo Kurisummoottil Thomas , Kala S. , J.V. Bibal Benifa , Walid Saad
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引用次数: 0

Abstract

Affine Frequency Division Multiplexing (AFDM) has been recognized for its superior bit error rate (BER) performance compared to Orthogonal Frequency Division Multiplexing (OFDM), especially under conditions of high mobility. This paper introduces a novel transmission method termed AFDM with Dual-Mode Index Modulation (AFDM-DM-IM), aiming to achieve an optimal balance between transmission reliability and spectral efficiency. To facilitate effective demodulation, two baseline detectors based on minimum mean squared error (MMSE) maximum likelihood (MMSE-ML) and MMSE log-likelihood ratio (MMSE-LLR) algorithms are developed. Furthermore, a deep learning-based demodulator (DeepADM) is proposed to account for the channel estimation error compared to baseline detectors such as MMSE-ML and MMSE-LLR. A theoretical analysis of the BER performance of AFDM-DM-IM is provided, along with simulation results. These results demonstrate superior performance of AFDM-DM-IM over both traditional AFDM and other existing index modulation system based on AFDM (AFDM-IM). This novel approach provides a promising pathway for the development of resilient and efficient communication systems in future high-mobility scenarios.
基于仿射频分复用的双模折射率调制
与正交频分复用技术(OFDM)相比,仿射频分复用技术(AFDM)具有更优越的误码率(BER)性能,尤其是在高移动性条件下。本文介绍了一种新型传输方法,称为双模索引调制 AFDM(AFDM-DM-IM),旨在实现传输可靠性和频谱效率之间的最佳平衡。为促进有效解调,开发了两种基于最小均方误差(MMSE)最大似然(MMSE-ML)和 MMSE 对数似然比(MMSE-LLR)算法的基线检测器。此外,与 MMSE-ML 和 MMSE-LLR 等基线检测器相比,还提出了一种基于深度学习的解调器(DeepADM),以考虑信道估计误差。本文对 AFDM-DM-IM 的误码率性能进行了理论分析,并提供了仿真结果。这些结果表明,AFDM-DM-IM 的性能优于传统的 AFDM 和其他基于 AFDM 的现有指数调制系统(AFDM-IM)。这种新方法为在未来的高移动性场景中开发弹性和高效的通信系统提供了一条大有可为的途径。
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来源期刊
Physical Communication
Physical Communication ENGINEERING, ELECTRICAL & ELECTRONICTELECO-TELECOMMUNICATIONS
CiteScore
5.00
自引率
9.10%
发文量
212
审稿时长
55 days
期刊介绍: PHYCOM: Physical Communication is an international and archival journal providing complete coverage of all topics of interest to those involved in all aspects of physical layer communications. Theoretical research contributions presenting new techniques, concepts or analyses, applied contributions reporting on experiences and experiments, and tutorials are published. Topics of interest include but are not limited to: Physical layer issues of Wireless Local Area Networks, WiMAX, Wireless Mesh Networks, Sensor and Ad Hoc Networks, PCS Systems; Radio access protocols and algorithms for the physical layer; Spread Spectrum Communications; Channel Modeling; Detection and Estimation; Modulation and Coding; Multiplexing and Carrier Techniques; Broadband Wireless Communications; Wireless Personal Communications; Multi-user Detection; Signal Separation and Interference rejection: Multimedia Communications over Wireless; DSP Applications to Wireless Systems; Experimental and Prototype Results; Multiple Access Techniques; Space-time Processing; Synchronization Techniques; Error Control Techniques; Cryptography; Software Radios; Tracking; Resource Allocation and Inference Management; Multi-rate and Multi-carrier Communications; Cross layer Design and Optimization; Propagation and Channel Characterization; OFDM Systems; MIMO Systems; Ultra-Wideband Communications; Cognitive Radio System Architectures; Platforms and Hardware Implementations for the Support of Cognitive, Radio Systems; Cognitive Radio Resource Management and Dynamic Spectrum Sharing.
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