BASIS EXPANSION MODEL DESIGN FOR SPARSE DOUBLY SELECTIVE CHANNEL ESTIMATION USING DICTIONAY LEARNING

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MAHMOODI SOMAYEH; OMIDI MOHAMMAD JAVAD; TABATABA FOROOGH SADAT

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Journal: COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING) Year:2017 | Volume:8 | Issue:2 Page(s): 25-39

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Information Journal Paper

Title

BASIS EXPANSION MODEL DESIGN FOR SPARSE DOUBLY SELECTIVE CHANNEL ESTIMATION USING DICTIONAY LEARNING

Author(s)

MAHMOODI SOMAYEH | OMIDI MOHAMMAD JAVAD | TABATABA FOROOGH SADAT | Issue Writer Certificate

Keywords

K-SVD ALGORITHMQ1

SPARSIFYING BASISQ1

SPARSE CHANNEL ESTIMATIONQ1

COMPRESSED SENSINGQ1

OFDM (ORTHOGONAL FREQUENCY DIVISION MODULATION) SYSTEMQ1

DOUBLY SELECTIVE CHANNELQ1

Abstract

In this paper, sparse double selective channel estimation using COMPRESSED SENSING (CS) theory for OFDM systems is investigated. This theory helps to reduce the required pilot ratio and equivalently increases the spectral efficiency to achieve a constant mean square error. This is of great importance especially for double selective channels in which the required number of unknowns to be estimated and also the required number of pilot symbols are high. To take the advantage of COMPRESSED SENSING, it is proposed that the sparsity enhancement of the coefficients of basis expansion model (BEM) should be considered in BEM design. It is also proposed to use K-SVD ALGORITHM that is one of the most popular dictionary learning algorithms. Moreover, in this paper clustered pilot symbols are used to avoid inter-carrier interference. It is noteworthy that the channel coefficients representing intercarrier interference are also estimated to be used in equalization. Numerical experiments have shown that the COMPRESSED SENSING estimator employing the proposed basis, outperforms the one employing DFT-DPSS in terms of NMSE and system BER.

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APA: Copy

MAHMOODI, SOMAYEH, OMIDI, MOHAMMAD JAVAD, & TABATABA, FOROOGH SADAT. (2017). BASIS EXPANSION MODEL DESIGN FOR SPARSE DOUBLY SELECTIVE CHANNEL ESTIMATION USING DICTIONAY LEARNING. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), 8(2 ), 25-39. SID. https://sid.ir/paper/203040/en

Vancouver: Copy

MAHMOODI SOMAYEH, OMIDI MOHAMMAD JAVAD, TABATABA FOROOGH SADAT. BASIS EXPANSION MODEL DESIGN FOR SPARSE DOUBLY SELECTIVE CHANNEL ESTIMATION USING DICTIONAY LEARNING. COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING)[Internet]. 2017;8(2 ):25-39. Available from: https://sid.ir/paper/203040/en

IEEE: Copy

SOMAYEH MAHMOODI, MOHAMMAD JAVAD OMIDI, and FOROOGH SADAT TABATABA, “BASIS EXPANSION MODEL DESIGN FOR SPARSE DOUBLY SELECTIVE CHANNEL ESTIMATION USING DICTIONAY LEARNING,” COMPUTATIONAL INTELLIGENCE IN ELECTRICAL ENGINEERING (INTELLIGENT SYSTEMS IN ELECTRICAL ENGINEERING), vol. 8, no. 2 , pp. 25–39, 2017, [Online]. Available: https://sid.ir/paper/203040/en

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