Abstract
Abstract In this paper, we propose a methodology for estimating the statistics of the intercell interference power in the downlink of a multicellular network. We first establish an analytical expression for the probability law of the interference power when only Rayleigh multipath fading is considered. Next, focusing on a propagation environment where small-scale Rayleigh fading as well as large-scale effects, including attenuation with distance and lognormal shadowing, are taken into consideration, we elaborate a semi-analytical method to build up the histogram of the interference power distribution. From the results obtained for this combined small- and large-scale fading context, we then develop a statistical model for the interference power distribution. The interest of this model lies in the fact that it can be applied to a large range of values of the shadowing parameter. The proposed methods can also be easily extended to other types of networks.
Highlights
In the emerging wireless communication standards LTEAdvanced and Mobile WiMAX, aggressive spectrum reuse is mandatory in order to achieve the increased spectral efficiency required by IMT-Advanced for the 4th generation of standard telephony
We first consider the contribution of one interfering cell, and in this regard, we examine two opposite scenarios: one for which the investigated interferer (i.e., access points (APs) 1) produces the largest dynamic range for the intercell interference power undergone by a user in the grayshaded triangular area of Figure 2; the other one for which the investigated cell (i.e., AP 13) has the smallest dynamics
VI Conclusion and future work In this paper, we have proposed a methodology to estimate the statistics of the intercell interference power in the downlink of a multicellular network
Summary
In the emerging wireless communication standards LTEAdvanced and Mobile WiMAX, aggressive spectrum reuse is mandatory in order to achieve the increased spectral efficiency required by IMT-Advanced for the 4th generation of standard telephony. We know that, for large values of sdB, the distribution of Gn exhibits the heavy-tailed property, which means, as described before, that the least frequently occurring values (i.e., the highest gains) are the most important ones in terms of moments Taking these highest amplitudes into consideration using the ‘classical’ generalized inverse method would require a finer partitioning of the cdf, which would produce a typical set made up of a huge amount of elements. The normalizing factor may be computed by replacing xt by its actual value in (22)
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