DESIGN OF LOW-COMPLEXITY BLIND CFO ESTIMATION FOR OFDM SYSTEMS
Author(s):
k.bhavani shankar, Neelima
ISSN:
2349-6002
Cite This Article:
DESIGN OF LOW-COMPLEXITY BLIND CFO ESTIMATION FOR OFDM SYSTEMSInternational Journal of Innovative Research in Technology(www.ijirt.org) ,ISSN: 2349-6002 ,Volume 6 ,Issue 6 ,Page(s):174-177 ,November 2019 ,Available :IJIRT148810_PAPER.pdf
Keywords:
Abstract
The estimation of carrier frequency offset (CFO) is an important issue in the study of the orthogonal frequency division multiplexing (OFDM) systems. In the past, many CFO estimation methods have been proposed. In this paper, we propose a new blind CFO estimation for OFDM systems based on the so-called demodulated received vectors. The CFO estimate is given by a closed form formula. The proposed method has very low complexity and its performance is robust to different modulation symbols and the presence of virtual carriers. Orthogonal frequency division multiplexing (OFDM) is a multicarrier modulation technique that is widely used in wireless broadband communication systems. The spectral e ciency of OFDM is very high since the subcarriers are spaced as closely as possible while maintaining orthogonality. However, one of the major problems with OFDM that can cause performance degradation is carrier frequency o set (CFO) which impairs the orthogonality among OFDM subcarriers, as a consequence, results in inter-subcarrier interference. In this thesis, an iterative algorithm for joint CFO estimation and data detection in OFDM systems over frequency selective channels is proposed. The proposed algo-rithm is performing both CFO estimation and data detection in the frequency domain based on the Expectation-Maximization (EM) algorithm. The proposed algorithm can achieve the same bit-error-rate (BER) performance as that of its time-domain counterpart with much lower complexity. Simulation results show that the proposed algorithm can converge after three iterations and an estimate of CFO can be obtained with high accuracy.
Article Details
Unique Paper ID: 148810

Publication Volume & Issue: Volume 6, Issue 6

Page(s): 174 - 177
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