scholarly journals On Polarization Dependent Equalization in 5G mmWave Systems

2019 ◽  
Author(s):  
Farah Arabian ◽  
Michael Rice
Keyword(s):  
Maximum Likelihood ◽  
Discrete Time ◽  
Matched Filter ◽  
Time Model ◽  
Discrete Time Model ◽  
Selection Diversity ◽  
Optimum Combining ◽  
Linear Equalizer ◽  
Frequency Selective ◽  
Frequency Selective Channels

<p>The outputs of a cross-polarized antenna can produce a pair of different parallel frequency-selective channels. The optimum combining strategy is derived from maximum likelihood principles and used to define an equivalent discrete-time model. The simulated post-equalizer BER results show that optimum combining produces the best results, selection diversity can provide reasonably good results, and that both optimum combining and selection diversity can be superior to linear equalizer operating on the </p> <p>channel obtained by combining the antenna outputs before applying a channel matched filter.</p> <br>

scholarly journals On Polarization Dependent Equalization in 5G mmWave Systems

2019 ◽  
Author(s):  
Farah Arabian ◽  
Michael Rice
Keyword(s):  
Maximum Likelihood ◽  
Discrete Time ◽  
Matched Filter ◽  
Time Model ◽  
Discrete Time Model ◽  
Selection Diversity ◽  
Optimum Combining ◽  
Linear Equalizer ◽  
Frequency Selective ◽  
Frequency Selective Channels

<p>The outputs of a cross-polarized antenna can produce a pair of different parallel frequency-selective channels. The optimum combining strategy is derived from maximum likelihood principles and used to define an equivalent discrete-time model. The simulated post-equalizer BER results show that optimum combining produces the best results, selection diversity can provide reasonably good results, and that both optimum combining and selection diversity can be superior to linear equalizer operating on the </p> <p>channel obtained by combining the antenna outputs before applying a channel matched filter.</p> <br>

Some comments concerning a curious singularity

1979 ◽  
Vol 16 (02) ◽  
pp. 440-444 ◽  
Author(s):  
Paul D. Feigin
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Discrete Time ◽  
Maximum Likelihood Estimate ◽  
Likelihood Estimation ◽  
Continuous Observation ◽  
Time Model ◽  
Limit Theory ◽  
Discrete Time Model ◽  
True Value

Consider the maximum likelihood estimation of θ based on continuous observation of the process X, which satisfies dXt = θXtdt + dWt . Feigin (1976) showed that, when suitably normalized, the maximum likelihood estimate is asymptotically normally distributed when the true value of θ ≠ 0. The claim that this asymptotic normality also holds for θ = 0 is shown to be false. The parallel discrete-time model is mentioned and the ramifications of these singularities to martingale central limit theory is discussed.

Some comments concerning a curious singularity

1979 ◽  
Vol 16 (2) ◽  
pp. 440-444 ◽  
Author(s):  
Paul D. Feigin
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Discrete Time ◽  
Maximum Likelihood Estimate ◽  
Likelihood Estimation ◽  
Continuous Observation ◽  
Time Model ◽  
Limit Theory ◽  
Discrete Time Model ◽  
True Value

Consider the maximum likelihood estimation of θ based on continuous observation of the process X, which satisfies dXt = θXtdt + dWt. Feigin (1976) showed that, when suitably normalized, the maximum likelihood estimate is asymptotically normally distributed when the true value of θ ≠ 0. The claim that this asymptotic normality also holds for θ = 0 is shown to be false. The parallel discrete-time model is mentioned and the ramifications of these singularities to martingale central limit theory is discussed.

Non-homogeneous infinitely many sites discrete-time model with exact coalescent

2009 ◽  
Vol 33 (6) ◽  
pp. 713-732
Author(s):  
Adam Bobrowski ◽  
Marek Kimmel ◽  
Małgorzata Kubalińska
Keyword(s):  
Discrete Time ◽  
Time Model ◽  
Discrete Time Model
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