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Exact(6)
This can be explained by examining the particular distribution involved, for one single as well as for multiple interfering cells.
This consequently validates the proposed model (7) in the case of multiple interfering cells, which we show for both frequency reuse patterns FR1 and FR3.
Remarkably, a maximum difference of 1,250 Mbps can be observed at the cell-edge of multiple interfering cells (macro- and femtocells).
Probability density functions of inter-cell interference in different frequency bands are derived and then used to deduce the expectation and variance of inter-cell interference from multiple interfering cells.
To reduce the complexity of simulation, instead of generating multiple interfering cells, we model the interference from the surrounding cells of the cluster as white noise, which is the worst‐case interference and results in pessimistic performance [18].
Since the neighboring cells have identical relative locations to the cell of interest, it would be tractable to analyze the interference from one interfering cell at first and then extend to the multiple interfering cells' scenario.
Similar(54)
Locating interfering cells.
Incoherent addition of summing multiple interfering signals is assumed.
The results obtained can be extended to multiple interfering users by using laguerre polynomials to approximate the multiple integration resulting from the multiple interfering users.
We next bound the number of interfering cells.
The models can analyze multiple interfering signals under different fading scenarios.
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