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AN EFFICIENT CFO ESTIMATION AND ICI REDUCTION IN MC-CDMA SYSTEM THROUGH CONJUGATE WEIGHTED MUSIC BASED RPRCC SCHEME
Author(s) -
S. CHITRA,
N. KUMARATHARAN
Publication year - 2016
Publication title -
latin american applied research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.123
H-Index - 23
eISSN - 1851-8796
pISSN - 0327-0793
DOI - 10.52292/j.laar.2016.347
Subject(s) - carrier frequency offset , computer science , single antenna interference cancellation , code division multiple access , orthogonal frequency division multiplexing , reduction (mathematics) , telecommunications link , algorithm , electronic engineering , real time computing , frequency offset , telecommunications , mathematics , engineering , decoding methods , channel (broadcasting) , geometry
Multicarrier code division multiple access (MC-CDMA) is one of the most attractive method for future broadband wireless systems and long term evolution (LTE) standard. The performance of MC-CDMA systems is greatly deteriorated by carrier frequency offset (CFO) which is due to oscillator instability and Doppler shifts. CFO leads to loss of orthogonality between the subcarriers and introduces intercarrier interference (ICI). Among the numerous ICI cancellation techniques, the proposed receiver phase rotated conjugate cancellation (RPRCC) offers greater ICI reduction compared to other methods. The distributed nature of networks and concurrent transmission from multiple users in uplink, RPRCC needs multiple frequency offset estimation at the receiver. Multiple signal classification (MUSIC) algorithm is the best suited CFO estimation technique in multiuser environment. However the performance of MUSIC algorithm is inferior for closely spaced CFOs. To achieve precise CFO estimation and greater ICI reduction, RPRCC with conjugate weighted MUSIC based CFO estimation is proposed in this paper. The simulation results depict that the ICI power reduction capability and BER performance of the suggested method outperforms the conventional techniques in both properly and closely spaced CFOs.

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