A Signal-Level Maximum Likelihood Detection Based on Partial Candidates for MIMO FBMC-QAM System With Two Prototype Filters

Dongkyu Sim; Kyeongyeon Kim; Chanhong Kim; Chungyong Lee

doi:10.1109/TVT.2019.2894941

A Signal-Level Maximum Likelihood Detection Based on Partial Candidates for MIMO FBMC-QAM System With Two Prototype Filters

Dongkyu Sim, Kyeongyeon Kim, Chanhong Kim, Chungyong Lee

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

In this paper, we consider a signal-level maximum likelihood detection for multiple-input multiple-output filter-bank multicarrier-quadrature amplitude modulation (MIMO FBMC-QAM) system with two prototype filters. Under high-frequency selective channels, the conventional symbol-level maximum likelihood detection suffers from degraded bit error rate performances because it cannot utilize the oversampling characteristics of the signal-level. However, due to intrinsic interference and high computational complexity, a maximum likelihood detection cannot be applied directly to the signal-level. To solve this problem, we propose a signal-level maximum likelihood detection based on partial candidates. Utilizing the diagonal dominant characteristics of effective channels, the proposed signal-level maximum likelihood detection can reduce the effect of intrinsic interference with practical computational complexity. Moreover, a region ordering algorithm based on Euclidean distance can improve the efficiency of the proposed signal-level maximum likelihood detection. Simulation results show that the proposed signal-level maximum likelihood detection can outperform the bit error rate performance of the conventional symbol-level maximum likelihood detection.

Original language	English
Article number	8624275
Pages (from-to)	2598-2608
Number of pages	11
Journal	IEEE Transactions on Vehicular Technology
Volume	68
Issue number	3
DOIs	https://doi.org/10.1109/TVT.2019.2894941
Publication status	Published - 2019 Mar

Bibliographical note

Funding Information:
Manuscript received July 18, 2018; revised November 8, 2018 and December 18, 2018; accepted January 15, 2019. Date of publication January 23, 2019; date of current version March 14, 2019. This work was sponsored by Samsung Electronics Co., Ltd., Gyeonggi-do 16677, South Korea. The review of this paper was coordinated by Prof. S.-H. Leung. (Corresponding author: Chungyong Lee.) D. Sim and C. Lee are with the Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea (e-mail:, dongkyu. sim@yonsei.ac.kr; cylee@yonsei.ac.kr).

Publisher Copyright:
© 1967-2012 IEEE.

All Science Journal Classification (ASJC) codes

Automotive Engineering
Aerospace Engineering
Applied Mathematics
Electrical and Electronic Engineering

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10.1109/TVT.2019.2894941

Cite this

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abstract = "In this paper, we consider a signal-level maximum likelihood detection for multiple-input multiple-output filter-bank multicarrier-quadrature amplitude modulation (MIMO FBMC-QAM) system with two prototype filters. Under high-frequency selective channels, the conventional symbol-level maximum likelihood detection suffers from degraded bit error rate performances because it cannot utilize the oversampling characteristics of the signal-level. However, due to intrinsic interference and high computational complexity, a maximum likelihood detection cannot be applied directly to the signal-level. To solve this problem, we propose a signal-level maximum likelihood detection based on partial candidates. Utilizing the diagonal dominant characteristics of effective channels, the proposed signal-level maximum likelihood detection can reduce the effect of intrinsic interference with practical computational complexity. Moreover, a region ordering algorithm based on Euclidean distance can improve the efficiency of the proposed signal-level maximum likelihood detection. Simulation results show that the proposed signal-level maximum likelihood detection can outperform the bit error rate performance of the conventional symbol-level maximum likelihood detection.",

author = "Dongkyu Sim and Kyeongyeon Kim and Chanhong Kim and Chungyong Lee",

note = "Funding Information: Manuscript received July 18, 2018; revised November 8, 2018 and December 18, 2018; accepted January 15, 2019. Date of publication January 23, 2019; date of current version March 14, 2019. This work was sponsored by Samsung Electronics Co., Ltd., Gyeonggi-do 16677, South Korea. The review of this paper was coordinated by Prof. S.-H. Leung. (Corresponding author: Chungyong Lee.) D. Sim and C. Lee are with the Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, South Korea (e-mail:, dongkyu. sim@yonsei.ac.kr; cylee@yonsei.ac.kr). Publisher Copyright: {\textcopyright} 1967-2012 IEEE.",

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A Signal-Level Maximum Likelihood Detection Based on Partial Candidates for MIMO FBMC-QAM System With Two Prototype Filters

Abstract

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