maximum-likelihood signal detection
Non orthogonal multiple access with joint maximum likelihood detection in heterogeneous network
... desired signal with a smaller signal power overlaps with multiple undesired signals, a receiver has to decode all these interference signals for the generation of SIC ...
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Maximum Likelihood Sequence Detection of Multiple Antenna Systems over Dispersive Channels via Sphere Decoding
... received signal at each receive antenna is the combi- nation of the transmitted signals perturbed by noise, in- tersymbol interference (ISI), and by interuser interference ...channel ...
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Maximum likelihood detection for coded combinerless LINC OFDM systems
... for signal transmission, the use of the power combiner can be ...ML detection methods for the CL-LINC-OFDM were proposed, reducing the com- putational complexity to some ...ML detection, LINC-OFDM ...
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Reduced Complexity Near Maximum Likelihood Detection for Decision Feedback Assisted Space Time Equalization
... (6) where u ij is the ( i, j ) th element of U . Equation (4) can be efficiently solved using a binary search-tree, as outlined in [4]. In order to ensure that the algorithm operates efficiently, it is advisable to first ...
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Reduced Complexity Maximum Likelihood Detection in Downlink SDMA Systems
... with the channel matrix yielded an identity matrix. This MUT transformation matrix may be regarded as a perfect pre-equalizer, which effectively results in a MUI-free channel. Furthermore, Choi and Murch [8] proposed an ...
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Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
... The complexity of the OHRSA-aided ML detector is difficult to find precisely as it depends on the signal-to-noise ratio (SNR), but this complexity is increasing with the data length N . The RWBS algorithm is a ...
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Moving Target Estimation in Non-Homogeneous Clutter for MIMO Radar
... and detection for non-stationary target using MIMO radar in non-homogeneous ...a maximum likelihood estimator (MLE) for velocity estimation and general likelihood ratio test (GLRT) for ...
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Signal Recovery using CλaSH
... of detection is the effects of noise and finite resolution. Signal recovery algorithms are used to recover the input signal of a system with a known response, and can be used to improve the level of ...
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Reduced Complexity Maximum Likelihood Detection in Multiple Antenna Aided Multicarrier Systems
... transmitted signal vector ˇ t and the resultant search process is guaranteed to arrive at the ML solution ˆ t, which minimizes the value of the cost function J (ˇ t) of Equation ...
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Maximum Likelihood Detection for Detect and Forward Relay Channels
... new signal combining strategy based on ML criterion for cooperative relay scheme which accounts the potential errors at ...the detection at the destination, we can accurately model the transition ...
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A practical implementation of maximum likelihood voting
... identical likelihood values to choose, and how to resolve the issue? Do we return the average value rounded to tolerance, or a weighted average where weighting is the version reliability, or something else? Random ...
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Readings in Targeted Maximum Likelihood Estimation
... mum likelihood estimation can be applied, or closely related M-estimate ...conditions. Maximum likelihood estimation in semiparametric models has been an extensive research area of ...example, ...
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Analysis of Offset Pulse Position Modulation
... properties of the modulation format. However, a discrete time signal is said to be cyclostationary, or to be wide-sense stationary, if the statistical proper- ties are repeated periodically. Gardner ( [66]- [69]) ...
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Maximum Entropy and Maximum Likelihood Estimation for the Three Parameter Kappa Distribution
... Statistical entropy deals with a measure of uncertainty or disorder associated with a probability distribution. The principle of maximum entropy (ME) is a tool for infer- ence under uncertainty [1,2]. This ...
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Smoothing Algorithms by Constrained Maximum Likelihood
... constrained maximum likelihood, with a fair risk scale determined by constrained maximum likelihood, leading to more robust credit loss ...
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Maximum likelihood estimation of population parameters.
... Under the assumptions that sequences are infinitely long and that the scaled coalescent times can be estimated without error, FELSENSTEIN (1992) showed that the improvement [r] ...
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Efficient maximum likelihood pedigree reconstruction
... One approach to pedigree reconstruction using genotypic data is to find the pedigree having the maximum likelihood. This was developed by Thompson (1976) (see also (Thompson, 1986)) using age and sex ...
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First CMS results at 13 TeV
... visible signal appeared for ...The signal was described with a Crystal-Ball function and background with a Chebyshev polynomial; the fit result is shown in ...
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Noise and Signal Estimation in MRI: Two-Parametric Analysis of Rice-Distributed Data by Means of the Maximum Likelihood Approach
... the maximum likelihood ...the signal within the Rician statistical ...the signal mean value but the value of the Rice distributed signal’s dispersion, as ...the maximum ...
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Maximum Likelihood Under Response Biased Sampling
... develop maximum likelihood and estimating equation theory appropriate to this ...to likelihood based survey inference (Breckling et al ...weighted likelihood based approach described in ...
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