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Capacity Bounds under Imperfect Polarization Tracking

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Název: Capacity Bounds under Imperfect Polarization Tracking
Autoři: Farsi, Mohammad, 1994, Karlsson, Magnus, 1967, Agrell, Erik, 1965
Zdroj: Frigöra full fiberoptisk kapacitet IEEE Transactions on Communications. 70(11):7240-7249
Témata: multimode fiber, decision-directed least mean square, Achievable information rate, state of polarization, least square error, Channel estimation, Symbols, polarization-mode dispersion, Probability density function, capacity, Signal processing algorithms, channel estimation, mutual information, constant modulus algorithm, space-division multiplexing, lower bound, Optical fiber dispersion, Mutual information, multicore fiber, Optical fiber communication, Kabsch algorithm
Popis: In optical fiber communication, due to the random variation of the environment, the state of polarization (SOP) fluctuates randomly with time leading to distortion and performance degradation. The memory-less SOP fluctuations can be regarded as a two-by-two random unitary matrix. In this paper, for what we believe to be the first time, the capacity of the polarization drift channel under an average power constraint with imperfect channel knowledge is characterized. An achievable information rate (AIR) is derived when imperfect channel knowledge is available and is shown to be highly dependent on the channel estimation technique. It is also shown that a tighter lower bound can be achieved when a unitary estimation of the channel is available. However, the conventional estimation algorithms do not guarantee a unitary channel estimation. Therefore, by considering the unitary constraint of the channel, a data-aided channel estimator based on the Kabsch algorithm is proposed, and its performance is numerically evaluated in terms of AIR. Monte Carlo simulations show that Kabsch outperforms the least-square error algorithm. In particular, with complex, Gaussian inputs and eight pilot symbols per block, Kabsch improves the AIR by 0.20 to 0.30 bits/symbol throughout the range of studied signal-to-noise ratios.
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Přístupová URL adresa: https://research.chalmers.se/publication/532568
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  Data: Capacity Bounds under Imperfect Polarization Tracking
– Name: Author
  Label: Authors
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  Data: <searchLink fieldCode="AR" term="%22Farsi%2C+Mohammad%22">Farsi, Mohammad</searchLink>, 1994<br /><searchLink fieldCode="AR" term="%22Karlsson%2C+Magnus%22">Karlsson, Magnus</searchLink>, 1967<br /><searchLink fieldCode="AR" term="%22Agrell%2C+Erik%22">Agrell, Erik</searchLink>, 1965
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  Data: <i>Frigöra full fiberoptisk kapacitet IEEE Transactions on Communications</i>. 70(11):7240-7249
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  Group: Su
  Data: <searchLink fieldCode="DE" term="%22multimode+fiber%22">multimode fiber</searchLink><br /><searchLink fieldCode="DE" term="%22decision-directed+least+mean+square%22">decision-directed least mean square</searchLink><br /><searchLink fieldCode="DE" term="%22Achievable+information+rate%22">Achievable information rate</searchLink><br /><searchLink fieldCode="DE" term="%22state+of+polarization%22">state of polarization</searchLink><br /><searchLink fieldCode="DE" term="%22least+square+error%22">least square error</searchLink><br /><searchLink fieldCode="DE" term="%22Channel+estimation%22">Channel estimation</searchLink><br /><searchLink fieldCode="DE" term="%22Symbols%22">Symbols</searchLink><br /><searchLink fieldCode="DE" term="%22polarization-mode+dispersion%22">polarization-mode dispersion</searchLink><br /><searchLink fieldCode="DE" term="%22Probability+density+function%22">Probability density function</searchLink><br /><searchLink fieldCode="DE" term="%22capacity%22">capacity</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing+algorithms%22">Signal processing algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22channel+estimation%22">channel estimation</searchLink><br /><searchLink fieldCode="DE" term="%22mutual+information%22">mutual information</searchLink><br /><searchLink fieldCode="DE" term="%22constant+modulus+algorithm%22">constant modulus algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22space-division+multiplexing%22">space-division multiplexing</searchLink><br /><searchLink fieldCode="DE" term="%22lower+bound%22">lower bound</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+fiber+dispersion%22">Optical fiber dispersion</searchLink><br /><searchLink fieldCode="DE" term="%22Mutual+information%22">Mutual information</searchLink><br /><searchLink fieldCode="DE" term="%22multicore+fiber%22">multicore fiber</searchLink><br /><searchLink fieldCode="DE" term="%22Optical+fiber+communication%22">Optical fiber communication</searchLink><br /><searchLink fieldCode="DE" term="%22Kabsch+algorithm%22">Kabsch algorithm</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: In optical fiber communication, due to the random variation of the environment, the state of polarization (SOP) fluctuates randomly with time leading to distortion and performance degradation. The memory-less SOP fluctuations can be regarded as a two-by-two random unitary matrix. In this paper, for what we believe to be the first time, the capacity of the polarization drift channel under an average power constraint with imperfect channel knowledge is characterized. An achievable information rate (AIR) is derived when imperfect channel knowledge is available and is shown to be highly dependent on the channel estimation technique. It is also shown that a tighter lower bound can be achieved when a unitary estimation of the channel is available. However, the conventional estimation algorithms do not guarantee a unitary channel estimation. Therefore, by considering the unitary constraint of the channel, a data-aided channel estimator based on the Kabsch algorithm is proposed, and its performance is numerically evaluated in terms of AIR. Monte Carlo simulations show that Kabsch outperforms the least-square error algorithm. In particular, with complex, Gaussian inputs and eight pilot symbols per block, Kabsch improves the AIR by 0.20 to 0.30 bits/symbol throughout the range of studied signal-to-noise ratios.
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  Data: electronic
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      – Type: doi
        Value: 10.1109/TCOMM.2022.3206803
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
        StartPage: 7240
    Subjects:
      – SubjectFull: multimode fiber
        Type: general
      – SubjectFull: decision-directed least mean square
        Type: general
      – SubjectFull: Achievable information rate
        Type: general
      – SubjectFull: state of polarization
        Type: general
      – SubjectFull: least square error
        Type: general
      – SubjectFull: Channel estimation
        Type: general
      – SubjectFull: Symbols
        Type: general
      – SubjectFull: polarization-mode dispersion
        Type: general
      – SubjectFull: Probability density function
        Type: general
      – SubjectFull: capacity
        Type: general
      – SubjectFull: Signal processing algorithms
        Type: general
      – SubjectFull: channel estimation
        Type: general
      – SubjectFull: mutual information
        Type: general
      – SubjectFull: constant modulus algorithm
        Type: general
      – SubjectFull: space-division multiplexing
        Type: general
      – SubjectFull: lower bound
        Type: general
      – SubjectFull: Optical fiber dispersion
        Type: general
      – SubjectFull: Mutual information
        Type: general
      – SubjectFull: multicore fiber
        Type: general
      – SubjectFull: Optical fiber communication
        Type: general
      – SubjectFull: Kabsch algorithm
        Type: general
    Titles:
      – TitleFull: Capacity Bounds under Imperfect Polarization Tracking
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            NameFull: Farsi, Mohammad
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            NameFull: Karlsson, Magnus
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            NameFull: Agrell, Erik
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            – D: 01
              M: 01
              Type: published
              Y: 2022
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