Analytical Modeling of Interference Aware Power Control for the Uplink of Heterogeneous Cellular Networks

Abstract

Abstract-Inter-cell interference is one of the main limiting factors in current Heterogeneous Cellular Networks (HCNs). Uplink Fractional Power Control (FPC) is a well known method that aims to cope with such limiting factor as well as to save battery live. In order to do that, the path losses associated with Mobile Terminal (MT) transmissions are partially compensated so that a lower interference is leaked towards neighboring cells. Classical FPC techniques only consider a set of parameters that depends on the own MT transmission, like desired received power at the Base Station (BS) or the path loss between the MT and its serving BS, among others. Contrary to classical FPC, in this paper we use stochastic geometry to analyze a power control mechanism that keeps the interference generated by each MT under a given threshold. We also consider a maximum transmitted power and a partial compensation of the path loss. Interestingly, our analysis reveals that such Interference Aware (IA) method can reduce the average power consumption and increase the average spectral efficiency. Additionally, the variance of the interference is reduced, thus improving the performance of Adaptive Modulation and Coding (AMC) since the interference can be better estimated at the MT.

On the Meta Distribution of Coverage Probability in Uplink Cellular Networks

“…For tractable analysis, the transmission power correlations are ignored and the interference seen from {Φ\u • } at b o is approximated with the interference seen from a PPP Φ ∈ R 2 with intensity function λ(x) = 1 − e −πλ b x 2 λ b . Such approximations are shown to be accurate in [3], [4], [8] for the spatially averaged P s (θ) and are validated in this letter for the meta distributionF (θ, α). For the sake of mathematical convenience, we first use the following lemma to average out the transmission powers of the interfering UEs and to facilitate the subsequent stochastic geometry analysis.…”

“…In the analysis, the Palm probability in (1) is captured via the intensity function of Φ • and the probability density function (pdf) of P i , which describe the panorama of interferers as seen from the test BS perspective [3], [4], [7], [8]. The result in (1) is obtained by the substitution P • = ρr η • and averaging over the channel gains and the UEs activity (i.e., a i ) (cf.…”

“…Despite that Ψ is a PPP, the UEs point process Φ is not a PPP [3], [4], [7], [8]. 2 Furthermore, the transmission powers of 2 A comprehensive study for the user point process is available in [9].…”

“…Interestingly, (8) and (9) show that all moments of the CP, and hence the meta distribution, are independent from the intensity of BSs. Such independence was also reported in [2] for the downlink scenario.…”

Treating Interference as Noise in Cellular Networks: A Stochastic Geometry Approach

“…An analytical framework to study the performance of UL heterogeneous cellular networks that employ IAFPC has been proposed in [15]. According to the IAFPC scheme, the UEs that generate higher interference than a maximum threshold limit their transmit power so that the interference is below an admissible maximum value.…”