Phase domain maximum likelihood carrier recovery: framework and application in wireless TDMA systems

Frantzeskakis, E.; Koukoulas, P.

doi:10.1109/vetecf.1999.800251

Cited by 2 publications

(4 citation statements)

References 6 publications

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“…Herein, to save hardware resources of FPGA, the sign decision and the multiplication operation within (19) are replaced by a multiplexer controlled by the most significant bit (MSB) of the outputs of the two low pass filtersand an inverter shown in Figure 2 (because the outputs of the two low pass filters are signed numbers). Therefore, the output characteristic of the PD can be obtained: Based on (20), the output characteristics curve of the PD can be obtain and shown in Figure 3.…”

Section: Parameter Calculation Of All-digital Qpsk Phase-lockedmentioning

confidence: 99%

“…When SNR is as low as 10 dB, numerical results have been demonstrated that can be considered as the Gaussian approximation accurate which has a zero mean and variance 2 [19]. Let's set 2 Δ + Δ + to be , namely,…”

Section: Phase Domain Maximum Likelihood Frequency Estimation Algorithmmentioning

confidence: 99%

“…The maximum likelihood estimators in (36) and (37) are minimum variance unbiased estimations achieving the Cramer Rao Bound [19,20]. On the other side, the higher the estimation accuracy is, the larger the sample points and SNR are.…”

Section: Phase Domain Maximum Likelihood Frequency Estimation Algorithmmentioning

confidence: 99%

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FPGA-Based Implementation of All-Digital QPSK Carrier Recovery Loop Combining Costas Loop and Maximum Likelihood Frequency Estimator

Wang

Song

et al. 2014

International Journal of Reconfigurable Computing

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This paper presents an efficient all digital carrier recovery loop (ADCRL) for quadrature phase shift keying (QPSK). The ADCRL combines classic closed-loop carrier recovery circuit, all digital Costas loop (ADCOL), with frequency feedward loop, maximum likelihood frequency estimator (MLFE) so as to make the best use of the advantages of the two types of carrier recovery loops and obtain a more robust performance in the procedure of carrier recovery. Besides, considering that, for MLFE, the accurate estimation of frequency offset is associated with the linear characteristic of its frequency discriminator (FD), the Coordinate Rotation Digital Computer (CORDIC) algorithm is introduced into the FD based on MLFE to unwrap linearly phase difference. The frequency offset contained within the phase difference unwrapped is estimated by the MLFE implemented just using some shifter and multiplyaccumulate units to assist the ADCOL to lock quickly and precisely. The joint simulation results of ModelSim and MATLAB show that the performances of the proposed ADCRL in locked-in time and range are superior to those of the ADCOL. On the other hand, a systematic design procedure based on FPGA for the proposed ADCRL is also presented.

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Section: Parameter Calculation Of All-digital Qpsk Phase-lockedmentioning

confidence: 99%

Section: Phase Domain Maximum Likelihood Frequency Estimation Algorithmmentioning

confidence: 99%

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FPGA-Based Implementation of All-Digital QPSK Carrier Recovery Loop Combining Costas Loop and Maximum Likelihood Frequency Estimator

Wang

Song

et al. 2014

International Journal of Reconfigurable Computing

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“…The use of Fast Fourier Transform (FFT), peak amplitude and Kalman Filtering is one way which maybe used for the recovery of carrier [1]. Other methods include the Open Loop Tanlock Carrier Recovery Structure [2], the Dual Mode Carrier Recovery Circuit for Adaptive Carrier Tracking [3], Constant Modulus Algorithm [4] and Maximum Likelihood (ML) Carrier Recovery [5].…”

Section: Introductionmentioning

confidence: 99%

Non-Data Aided Approach for Carrier Recovery and Modulation Identification of an M-ary PSK System

Khokhar

Iftikhar

Nawaz

et al. 2007

2007 International Conference on Emerging Technologies

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Modulation identification and the recovery of the carrier lead to many applications in the digital communication system. Techniques developed so far for carrier recovery and modulation identification are all statistical. In this paper efforts are made to use a deterministic method rather than statistical. Zero crossing detection method is recommended for use to recover carrier from frequency and amplitude modulated systems. In this paper some modifications have been suggested for the application of the same system to make it useful for QAM and PSK as well. Based on the method presented by R. W. Wall, a modified Zero Crossing Detection algorithm has been used for carrier and phase extraction from an M-ary PSK (differential and non-differential) system. In addition, method has been developed for M-ary PSK system identification.

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Phase domain maximum likelihood carrier recovery: framework and application in wireless TDMA systems

Cited by 2 publications

References 6 publications

FPGA-Based Implementation of All-Digital QPSK Carrier Recovery Loop Combining Costas Loop and Maximum Likelihood Frequency Estimator

FPGA-Based Implementation of All-Digital QPSK Carrier Recovery Loop Combining Costas Loop and Maximum Likelihood Frequency Estimator

Non-Data Aided Approach for Carrier Recovery and Modulation Identification of an M-ary PSK System

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