Low-complexity carrier-phase estimator suited to on-board implementation

Morlet, C.; Boucheret, Marie‐Laure; Buret, Isabelle

doi:10.1109/26.870008

Cited by 23 publications

(9 citation statements)

References 3 publications

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“…In particular, when m=0, it's a kind of self-normalizing detector. Therefore, it still seems to be a good choice when the PEDs are implemented with the reduced complexity structures which was well examined in [11].…”

Section: Analysis and Improvementmentioning

confidence: 98%

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Maximum Likelihood Clockless Feedback Phase Recovery for MPSK Signals

Wang

Yan

et al. 2010

2010 IEEE 72nd Vehicular Technology Conference - Fall

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For the symbol timing recovery techniques which are susceptible to carrier phase offset, clockless phase recovery is necessary in advance. In this paper, we propose a clockless nondata-aided (NDA) feedback phase error detector (PED) for M-ary phase-shift keying (MPSK) signal. Its derivation is given based on maximum likelihood (ML) criterion. The clockless NDA (Mthpower) PED can also be generalized with a design parameter 0≤ m ≤M to improve performance at low SNR. The openloop S-curves and closed-loop phase error variances of these PEDs are given with extensive simulations. Results show that the S-curve of clockless Mth-power PED is robust to signal-tonoise ratio (SNR). Its phase error variance is investigated with excellent performance under different shaping roll-off factors and parameter m. We also analyze the clockless decision-directed (DD) PED which may not be a good choice for over-sampled signals due to its unstable equilibrium point of S-curve.

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Section: Analysis and Improvementmentioning

confidence: 98%

“…For the clock aided phase recovery, the pdf of Mth-power nonlinearity regressions (11) can be derived in [3], [4], [15]. It was also examined in [13] for MQAM signals.…”

Section: Analysis and Improvementmentioning

confidence: 99%

Maximum Likelihood Clockless Feedback Phase Recovery for MPSK Signals

Wang

Yan

et al. 2010

2010 IEEE 72nd Vehicular Technology Conference - Fall

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“…2) Perform one Cartesian-to-Polar coordinate conversion [10] and one phase unwrapping operation. Without considering the data removal process, the operations needed in linear phase interpolation method and slidingwindow method to get the phases of a block of 2L +1 symbols are summarized and compared in Table I.…”

Section: B Complexity Comparisonmentioning

confidence: 99%

Study on Phase Interpolation Filters for Coherent Optical Communications

Huang

Cheng

Chen

2013

IEEE Photon. Technol. Lett.

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In most of the carrier phase estimation (CPE) algorithms, there is a need to average a block of symbols to mitigate the noise effect. The symbols within a block may share the same derived phase (block estimation), or alternatively, a symbol by symbol sliding-window filter can be used to get each symbol a unique phase (sliding-window estimation). It is well-known that block estimation has lower estimation accuracy but consumes less computational power compared with sliding-window estimation. To improve the performance of CPE employing block estimation, we study and propose a phase interpolation filter that is simpler than the sliding-window filter, and show analytically that linear phase interpolation yields the best performance. Simulation and experimental results show that the phase interpolation filter effectively improves the performance of block estimation to the level similar to that of the sliding-window estimation.

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“…C. Morlet, et. al proposed a feed forward low complexity algorithm while it doesn't take into account the coding structure in [3]. Some researches did think of the structure of turbo iteration, but these researches just utilized traditional turbo iterative structure in which soft extrinsic information for information bits going between the two constituent coders iteratively.…”

Section: Introductionmentioning

confidence: 99%

Novel iterative APPA carrier phase recovery and detection for turbo-coded systems

2009

2009 IEEE International Conference on Communications Technology and Applications

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This paper introduced a novel a priori probability aided (APPA) carrier phase recovery and signal detection algorithm. The algorithm utilized the soft value of the extrinsic information generated by iterative MAP decoders by means of iteration after iteration. This method provided robust carrier phase estimation along with reliable signal decoding with a wide range of phase errors at such low signal-tonoise ratio (SNR) conditions that turbo coded systems operate on. In order to take full advantage of turbo iterative decoding structure and the output soft information we improved turbo decoding iterative structure and proposed a novel turbo iterative scheme which include iterative calculation of both information and parity bits Log-likelihood Ratio (LLR). We applied the above iterative structure into APPA carrier estimator. Compared with traditional turbo iteration methods, the novel turbo iteration algorithm can improve the acquisition region from -40 to 40 degrees while acquisition region is from -30 to 30 degrees in traditional methods at the same 3 rd iteration stage. The overall BER decreases greatly at the same number of turbo iteration. The algorithm has additional advantages including reasonable hardware complexity and easy to be implemented.

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Low-complexity carrier-phase estimator suited to on-board implementation

Cited by 23 publications

References 3 publications

Maximum Likelihood Clockless Feedback Phase Recovery for MPSK Signals

Maximum Likelihood Clockless Feedback Phase Recovery for MPSK Signals

Study on Phase Interpolation Filters for Coherent Optical Communications

Novel iterative APPA carrier phase recovery and detection for turbo-coded systems

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