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.
Bibliographical noteFunding 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. email@example.com; firstname.lastname@example.org).
All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Aerospace Engineering
- Applied Mathematics
- Electrical and Electronic Engineering