Parameter | Meaning |
---|---|
Τ | Past observation length in terms of number of slot(s) |
| Output of the neuron of the k th layer |
v βα | Connection weights, connecting the neuron β of the k th layer to the neuron α in the (k −1)th layer |
| Weighted sum of inputs coming from the output neuron in the (k − 1) th layer |
b β | Bias input in the neuron |
O | Neuron in the output layer |
s Ï„ + 1 | The actual slot(s) state from the MLP-based CSIT predictor |
| The desired slot(s) state |
i Ï„ + 1 | Actual predictor idle time slot(s) |
| Desired idle time slot(s) |
φ'() | Activation function, i.e., ‘purelin’ for the output layer and ‘log sigmoid’ for the hidden layer |
| Local gradient of the neuron β in the k th layer |
e s | Error between the desired and actual slot(s) state of the predictor |
e i | Error between the desired and the actual idle time slot(s) of the predictor |
N is | Total number of idle time slot(s) in the system |
N i | Total number of idle time slot(s) sensed by CUsense |
N ip | Total number of idle time slot(s) sensed by CUpredict |
X | Unit energy required for sensing a slot(s) |
Y | Total number of slot(s) predicted to be idle |
Z | Number of slots a CUsense sensed in a finite duration of time slot(s) |
N s | Total number of slot(s) to be sensed |
C | Sensing threshold for the event PLR to occur |
p m | Probability of the m th slot(s) appearing to be idle |
Δ s | Time duration of the slot(s) |
C 0 | Referred transmission capacity of the SU |
| This corresponds to how fast the a SU can find the idle slot(s) among total of Ns |