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Exact(9)
The coherent detector is often referred to as a maximum likelihood detector [13].
A lattice-based maximum likelihood detector is used for decoding, which is computationally more complex than the decoupled decoding of orthogonal space-time block codes.
The maximum likelihood detector (MLD) is known to be an optimal detector; however, it is impractical for realization owing to its great computational complexity.
The ideal Maximum Likelihood detector [26, 27] can solve this issue; however, the complexity of the ML detector is excessively high so that it is impossible to implement in practical communication systems.
It is seen that the proposed detectors achieve similar performance to that of well-known optimum Maximum Likelihood Detector (MLD) at a significantly lower computational complexity and outperform the traditional MMSE MUD.
However, the OMUD, such as, the maximum likelihood detector [20], is still very high-complexity, which usually becomes extreme when the number of users supported per cell is relatively high.
Similar(51)
The maximum likelihood detectors (MLD) [3 5] which are the performance-optimal detectors suffer from exponential complexity in terms of the number of the transmitted signal, and they are not practical when the number of the transmitted signal becomes large.
The authors present an unified framework for list-based iterative multiuser detection, striking a good balance between performance and complexity as compared to the traditional linear and joint maximum likelihood detectors at the two extremes.
The optimal detector, known as maximum likelihood (ML) detector, has been proposed in [9].
The maximum likelihood (ML) detector having log-likelihood ratio (LLR) output is known as the optimum detector.
Since the combined interference and noise is not white anymore (its covariance is shown in (4)), the optimal maximum likelihood (ML) detector is equivalent to whitening the received signal, followed by applying the ML detector designed for white noise [33, 34].
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