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Channel quality estimation in wireless links.
We employ a simple channel quality estimation method using the signal strength of the OFDM symbol.
Although a longer signature has a lower false positive probability, it may suffer from the decrease in the channel quality estimation accuracy.
In this paper, we propose a channel quality estimation method based on the concept of Gaussian process regression to predict users' channel states for varying user mobility profiles.
To achieve this goal, we apply an OFDM-based variable-length Bloom filter (VBF) that synergistically integrates the channel quality estimation and QoS channel coordination.
Both works make use of the users' Doppler shift to determine the time duration of the channel quality estimation; this procedure, although well established, might lead to erroneous predictions, a negative correlation is generally present between prediction quality and Doppler shift.
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However, the performance gain is achieved at the cost of some cooperative overheads including the exchange of information like access channel, location, link quality estimation and mobility of PUs among femtocells.
In order to make LBPS work for LTE, the mechanism of channel capacity estimation by channel quality indicator (CQI) reporting as well as two revised LBPS schemes, namely LTE-LBPS-Aggr and LTE-LBPS-Merge, are proposed in this paper.
The tasks performed include the channel estimation, the channel quality indicators management, and the control of the radio resources assigned to the BS.
The model is able to consider multiple channel quality assumptions for the terminals through different estimation approaches.
Depending on the channel quality and the protection level, the channel model provides an average estimation of the bit error rate (BER), which we will denote.
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