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Of course, the iterative implementation of the problem is sub-optimal.
Because of this, iterative implementation in the short term requires intensive labor and knowledge of developers.
At last, a novel RAB is developed based on the iterative implementation of this feedback loop.
We call this iterative implementation as iterative robust adaptive beamformer (IRAB).
The idea of the proposed beamformer is to use iterative implementation.
Two DEMPC methodologies are designed for sequential and iterative implementation, respectively.
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However, we will show in section 5.2 that the theoretical performance of the ML estimator is degraded when adopting iterative implementations as cases of non-convergence often occur.
This enables the efficient iterative computational implementation of the HFGMC as a stand alone.
In addition to the modulation order and the code rate, a third parameter should be considered regarding the iterative demapping implementation choice.
Some algorithms such as Radon and Hough transforms [13] and polar mapping [15] can solve this problem by an iterative optimization implementation of exhaustive searching in a wide angle range.
The iterative MapReduce implementation of the connected components algorithm is shown in Algorithm 4. In each iteration, the input of the map function is the node id v, its neighbors set (N_{v}), and its component id (C_{v}).
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