We propose analytical models for the interference power distribution in a cellular system employing MIMO beamforming in rich and limited scattering environments, which capture non line-of-sight signal propagation in the microwave and mm-wave bands, respectively. Two candidate models are considered: the inverse Gaussian and the inverse Weibull, both are two-parameter heavy tail distributions. We further propose a mixture of these two distributions as a model with three parameters. To estimate the parameters of these distributions, three approaches are used: moment matching, individual distribution maximum likelihood estimation (MLE), and mixture distribution MLE with a designed expectation maximization algorithm. We then introduce simple fitted functions for the mixture model parameters as polynomials of the channel path loss exponent and shadowing variance. To measure the goodness of these models, the information-theoretic metric relative entropy is used to capture the distance from the model distribution to a reference one. The interference models are tested against data obtained by simulating a cellular network based on stochastic geometry. The results show that the three-parameter mixture model offers remarkably good fit to simulated interference power. The mixture model is further used to analyze the capacity of a cellular network employing joint transmit and receive beamforming and confirms a good fit with simulation.
We argue for the important role that interference characterization plays in evaluating and predicting the network performance in , including both microwave and mmWave bands. Traditionally, mmWave bands are considered for backhaul in cellular systems and for high-volume consumer electronics such as personal area and local area networks, but not for cellular access due to concerns about short-range and non-line-of-sight coverage issues @cite_38 @cite_39 . MmWave has, however, recently been shown to be suitable for cellular communications, provided short cell radius of the order of 100-200 meters and sufficient beamforming gain between communicating nodes @cite_39 . Reducing the cell radius leads to dense base station (BS) deployments. Even under beamforming, these high BS and user densities can drive cellular networks to be more interference rather than noise limited. While large adaptive arrays with narrow beams can boost the received signal power and hence reduce the impact of out-of-cell interference @cite_40 @cite_41 , this interference remains an important performance-limiting factor in dense mmWave networks @cite_34 .
@cite_38 @cite_41 @cite_39 @cite_40 @cite_34
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Millimeter wave (mmWave) cellular systems will require high-gain directional antennas and dense base station (BS) deployments to overcome a high near-field path loss and poor diffraction. As a desirable side effect, high-gain antennas offer interference isolation, providing an opportunity to incorporate self-backhauling , i.e., BSs backhauling among themselves in a mesh architecture without significant loss in the throughput, to enable the requisite large BS densities. The use of directional antennas and resource sharing between access and backhaul links leads to coverage and rate trends that significantly differ from conventional UHF cellular systems. In this paper, we propose a general and tractable mmWave cellular model capturing these key trends and characterize the associated rate distribution. The developed model and analysis are validated using actual building locations from dense urban settings and empirically derived path loss models. The analysis shows that, in sharp contrast to the interference-limited nature of UHF cellular networks, the spectral efficiency of mmWave networks (besides the total rate) also increases with the BS density, particularly at the cell edge. Increasing the system bandwidth does not significantly influence the cell edge rate, although it boosts the median and peak rates. With self-backhauling, different combinations of the wired backhaul fraction (i.e., the fraction of BSs with a wired connection) and the BS density are shown to guarantee the same median rate (QoS). The millimeter-wave (mmWave) band offers the potential for high-bandwidth communication channels in cellular networks. It is not clear, however, whether both high data rates and coverage in terms of signal-to-noise-plus-interference ratio can be achieved in interference-limited mmWave cellular networks due to the differences in propagation conditions and antenna topologies. This article shows that dense mmWave networks can achieve both higher data rates and comparable coverage relative to conventional microwave networks. Sum rate gains can be achieved using more advanced beamforming techniques that allow multiuser transmission. The insights are derived using a new theoretical network model that incorporates key characteristics of mmWave networks. Cellular systems were designed for carrier frequencies in the microwave band (below 3 GHz) but will soon be operating in frequency bands up to 6 GHz. To meet the ever increasing demands for data, deployments in bands above 6 GHz, and as high as 75 GHz, are envisioned. However, as these systems migrate beyond the microwave band, certain channel characteristics can impact their deployment, especially the coverage range. To increase coverage, beamforming can be used but this role of beamforming is different than in current cellular systems, where its primary role is to improve data throughput. Because cellular procedures enable beamforming after a user establishes access with the system, new procedures are needed to enable beamforming during cell discovery and acquisition. This paper discusses several issues that must be resolved in order to use beamforming for access at millimeter wave (mmWave) frequencies, and presents solutions for initial access. Several approaches are verified by computer simulations, and it is shown that reliable network access and satisfactory coverage can be achieved in mmWave frequencies. With the severe spectrum shortage in conventional cellular bands, millimeter-wave (mmWave) frequencies have been attracting growing attention for next-generation micro- and picocellular wireless networks. A fundamental and open question is whether mmWave cellular networks are likely to be noise- or interference-limited. Identifying in which regime a network is operating is critical for the design of MAC and physical-layer procedures and to provide insights on how transmissions across cells should be coordinated to cope with interference. This work uses the latest measurement-based statistical channel models to accurately assess the Interference-to-Noise Ratio (INR) in a wide range of deployment scenarios. In addition to cell density, we also study antenna array size and antenna patterns, whose effects are critical in the mmWave regime. The channel models also account for blockage, line-of-sight and non-line-of-sight regimes as well as local scattering, that significantly affect the level of spatial isolation.