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Our study illustrates that in theory, this understanding seems to be there but that this does not automatically imply that it is implemented in practical work.
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The previously determined optimal trajectories are implemented in practical operation.
However, the application of CS theory to practical remote sensing imaging systems involves some key challenges: (i) Many random projections cannot be implemented in practical systems.
There is thus an important role to be played by perception research in determining how the ELC can best be implemented in practical terms.
Moreover, for feedforward systems with decreasing powers, the proposed approach will enable us to design a locally linear saturation control law which is easier to be implemented in practical applications.
It can be implemented in practical urban shelter evaluation and location-allocation work.
This can hardly be implemented in practical systems because of the heavy feedback overhead.
When Professor Sicuranza started working on nonlinear signal processing, many techniques were too complex to be implemented in practical applications.
Despite of its optimality, this technique is not feasible to be implemented in practical system as it brings high complexity at the transmitter side.
Soft combination CSS scheme [14] has the optimal performance through using the accurate sensing results from different SUs; however, its overhead is large, which makes it difficult to be implemented in practical networks.
Finally, we draw the conclusion that the proposed scheme can achieve a useful performance tradeoff between system capacity and feedback overhead, which gives it high potential to be implemented in practical massive MIMO systems.
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