Shadowing is believed to degrade the quality of service (QoS) in wireless cellular networks. Assuming log-normal shadowing, and studying mobile's path-loss with respect to the serving base station (BS) and the corresponding interference factor (the ratio of the sum of the path-gains form interfering BS's to the path-gain from the serving BS), which are two key ingredients of the analysis and design of the cellular networks, we discovered a more subtle reality. We observe, as commonly expected, that a strong variance of the shadowing increases the mean path-loss with respect to the serving BS, which in consequence, may compromise QoS. However, in some cases, an increase of the variance of the shadowing can significantly reduce the mean interference factor and, in consequence, improve some QoS metrics in interference limited systems, provided the handover policy selects the BS with the smallest path loss as the serving one. We exemplify this phenomenon, similar to stochastic resonance and related to the "single big jump principle" of the heavy-tailed log-nornal distribution, studying the blocking probability in regular, hexagonal networks in a semi-analytic manner, using a spatial version of the Erlang's loss formula combined with Kaufman-Roberts algorithm. More detailed probabilistic analysis explains that increasing variance of the log-normal shadowing amplifies the ratio between the strongest signal and all other signals thus reducing the interference. The above observations might shed new light, in particular on the design of indoor communication scenarios.
Some papers (see e.g. @cite_4 @cite_6 ) propose more explicit approximations of the interference factor and its moments (mean and variance) assuming only deterministic propagation loss models (without random shadowing). @cite_17 studies the distribution of the interference factor in such a case.
@cite_4 @cite_6 @cite_17
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We establish a closed form formula of the other-cell interference factor f for omni-directional and sectored cellular networks, as a function of the location of the mobile. That formula is based on a fluid model of cellular networks: The key idea is to consider the discrete base stations (BS) entities as a continuum of transmitters which are spatially distributed in the network. Simulations show that the obtained closed-form formula is a very good approximation, even for the traditional hexagonal network. From f, we are able to derive the global outage probability and the spatial outage probability, which depends on the location of a mobile station (MS) initiating a new call. Although initially focused on CDMA (UMTS, HSDPA) and OFDMA (WiMax) networks, we show this approach is applicable to any kind of wireless system such as TDMA (GSM) or even ad-hoc ones. The f-factor, which is roughly the interference to signal power ratio, plays a crucial role in the performance evaluation of wireless cellular networks. The objective of the present paper is to study the properties of the f-factor and establish approximations for it which we compare to previously proposed approximations. We consider the hexagonal network model, where the base stations are placed on a regular hexagonal grid which may be infinite. The propagation loss is assumed to be a power of the distance between the transmitter and the receiver. In this context, we build a reference method to calculate the f-factor to which previously proposed approximations as well as a new one are compared. It is shown that the previous approximations are not always close to the reference. One should choose the approximation carefully since the performance of cellular networks depend strongly on the f-factor. The results in our paper help to make the appropriate choice. This is particularly important for operational needs as for example dimensioning a real network. We present an analytical model for computing the othercell interference distribution in a third generation UMTS network with inhomogeneous user distribution. Our proposed model is based on an iterative calculation of a fixed-point equation which describes the interdependence of the interference levels at neighboring base stations. Furthermore, we develop an efficient algorithm based on lognormal approximations to compute the mean and standard deviation of the othercell interference. We show that our model is accurate and fast enough to be used efficiently in the planning process of large UMTS networks.