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Sensors 2018, 18(7), 2256;

极速赛车玩法规则:A Novel Carrier Loop Algorithm Based on Maximum Likelihood Estimation (MLE) and Kalman Filter (KF) for Weak TC-OFDM Signals

School of Electronic Engineering, Beijing University of Posts & Telecommunications, No. 10 Xitucheng Road, Haidian District, Beijing 100876, China
Author to whom correspondence should be addressed.
Received: 16 May 2018 / Revised: 25 June 2018 / Accepted: 9 July 2018 / Published: 13 July 2018
(This article belongs to the Special Issue Selected Papers from UPINLBS 2018)


Digital broadcasting signals represent a promising positioning signal for indoors applications. A novel positioning technology named Time & Code Division-Orthogonal Frequency Division Multiplexing (TC-OFDM) is mainly discussed in this paper, which is based on China mobile multimedia broadcasting (CMMB). Signal strength is an important factor that affects the carrier loop performance of the TC-OFDM receiver. In the case of weak TC-OFDM signals, the current carrier loop algorithm has large residual carrier errors, which limit the tracking sensitivity of the existing carrier loop in complex indoor environments. This paper proposes a novel carrier loop algorithm based on Maximum Likelihood Estimation (MLE) and Kalman Filter (KF) to solve the above problem. The discriminator of the current carrier loop is replaced by the MLE discriminator function in the proposed algorithm. The Levenberg-Marquardt (LM) algorithm is utilized to obtain the MLE cost function consisting of signal amplitude, residual carrier frequency and carrier phase, and the MLE discriminator function is derived from the corresponding MLE cost function. The KF is used to smooth the MLE discriminator function results, which takes the carrier phase estimation, the angular frequency estimation and the angular frequency rate as the state vector. Theoretical analysis and simulation results show that the proposed algorithm can improve the tracking sensitivity of the TC-OFDM receiver by taking full advantage of the characteristics of the carrier loop parameters. Compared with the current carrier loop algorithms, the tracking sensitivity is effectively improved by 2–4 dB, and the better performance of the proposed algorithm is verified in the real environment. View Full-Text
Keywords: carrier loop; MLE; LM; KF; TC-OFDM carrier loop; MLE; LM; KF; TC-OFDM

秒速赛车是哪里的开奖 Figure 1

Figure 1
<p>TC-OFDM signal Frame Structure.</p> ">
Figure 2
<p>Conventional carrier loop structure.</p> ">
Figure 3
<p>The principle of MLE.</p> ">
Figure 4
<p>LM algorithm flow chart.</p> ">
Figure 5
<p>The proposed carrier loop structure based on MLE and KF.</p> ">
Figure 6
<p>The Relationship between Loss of Lock Probability and SNR.</p> ">
Figure 7
<p>The RMS Frequency Tracking Error with SNR under different sample observations.</p> ">
Figure 8
<p>The residual carrier and phase convergence curve estimated by LM algorithm.</p> ">
Figure 9
<p>Frequency error comparison results by MLE and MLE&amp;KF.</p> ">
Figure 10
<p>Comparison results of frequency estimation errors by three algorithms under different SNR.</p> ">
Figure 11
<p>Comparison of the tracking probabilities between the three algorithms.</p> ">
Figure 12
<p>Each component of the modified base stations.</p> ">
Figure 13
<p>The TC-OFDM receiver. (<bold>a</bold>) is the internal and external structure of the TC-OFDM receiver; and (<bold>b</bold>) is the communication between the positioning receiver and the mobile phone.</p> ">
Figure 14
<p>Actual test diagram of the tracking sensitivity between the three algorithms.</p> ">
Figure 15
<p>The base station distribution of the test environment on the campus.</p> ">
Figure 16
<p>The RMSE positioning accuracy error in horizontal direction.</p> ">
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Liu, W.; Bian, X.; Deng, Z.; Mo, J.; Jia, B. A Novel Carrier Loop Algorithm Based on Maximum Likelihood Estimation (MLE) and Kalman Filter (KF) for Weak TC-OFDM Signals. Sensors 2018, 18, 2256.

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