標題: MLP/BP-based MIMO DFEs for Suppressing ISI and ACI to Recover Distorted QPSK Signal in Severe ISI Channels
作者: Hsu, Terng-Ren
Hsu, Terng-Yin
Chao, Kuan-Chieh
Chiang, Shih-Yuan
資訊工程學系
Department of Computer Science
公開日期: 2008
摘要: In this work, we base oil multi-layered perceptron neural networks with backpropagation algorithm (MLP/BP) to construct multi-input multi-output (MIMO) decision feedback equalizers (DFEs). The proposal is used to recover distorted quadrature phase-shift keying (QPSK) signal. From the simulations, we note that the proposed scheme can recover severe distorted signals as well as suppress intersymbol interference (ISI), adjacent channel interference (ACI) and background additive white Gaussian noise (AWGN). The better bit-error-rate (BER) and packet-error-rate (PER) performance as compared to a set of least-mean-square (LMS) DFEs is achieved. The presented MLP/BP-based MIMO DFE under the severe ISI channels with ACI and AWGN can improve over 1.5dB at PER=10(-1) and BER=10(-3).
URI: http://dx.doi.org/10.1109/EMAP.2008.4784274
http://hdl.handle.net/11536/135033
ISBN: 978-1-4244-3619-4
DOI: 10.1109/EMAP.2008.4784274
期刊: 2008 EMAP CONFERENCE PROCEEDINGS
起始頁: 243
結束頁: +
Appears in Collections:Conferences Paper