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However, this task is difficult due to fast channel fading conditions and data ill-conditioning, which limit the performance of least-squares-based techniques.
Nakagami-m fading conditions.
Its performance is evaluated in AWGN and Rayleigh fading conditions.
Considering fading conditions, a dynamic programming solution is proposed.
They formulate the optimization problem considering the delays in both Gaussian and Rayleigh fading conditions.
In this section, we also define and calculate the RC gain for the two fading conditions.
However, this DAR method does not work well under frequency selective fading conditions.
In this section, we analyze the retaining probability of a node under fading conditions.
The precise BER results are obtained using a combination of analysis and simulation under fading conditions.
By changing m d,F, we can get a variety of fading conditions.
Under fast fading conditions, additional effects influence the performance of LTE uplink transmissions.
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