Probabilities In Cellular Networks Research Articles

Closed-Form Coverage Probability in Cellular Networks With Poisson Point Process

For the cellular networks with Poisson point process and general path-loss exponent, we derive a closed-form expression of the coverage probability. Its graphical profile perfectly matches with the one that is obtained by numerical integration.

Downlink Coverage Probability in Cellular Networks With Poisson–Poisson Cluster Deployed Base Stations

Poisson-Poisson cluster processes (PPCPs) are a class of point processes exhibiting attractive point patterns. Recently, PPCPs are actively studied for modeling and analysis of heterogeneous cellular networks or device-to-device networks. However, surprisingly, to the best knowledge of the author, there is no exact derivation of downlink coverage probability in a numerically computable form for a cellular network with base stations (BSs) deployed according to a PPCP within the most fundamental setup such as single-tier, Rayleigh fading and nearest BS association. In this paper, we consider this fundamental model and derive a numerically computable form of coverage probability. To validate the analysis, we compare the results of numerical computations with those by Monte Carlo simulations and confirm the good agreement.

Dominant factors for device-to-device occurrence probabilities in cellular networks

Device-to-device (D2D) communication is expected to be part of future cellular networks. It is commonly assumed that D2D links will exist and need to be managed. However, the question with what probability D2D links will occur in a network and by which parameters this occurrence is influenced, has not been posed yet. We assume a certain event flow, consisting of (1) the occurrence of communication requirements (2) device pairing and (3) mode selection, that leads to the existence of a D2D flow. Under this event flow, we are interested in the influence of service penetration among UEs, pairing strategies and mode selection types on the occurrence probabilities of D2D communication. We propose a stochastic geometry based formula framework which captures the mean number of D2D links that occur in a certain area. This framework reveals a saturation effect of D2D flows and an interesting interplay among the device pairing and mode selection step. We show that any existing network that uses the considered action flow can be described with this framework and further, by simulation, that it can be used to correctly predict D2D occurrence probabilities.

Polarized Rician Fading Models for Performance Analysis in Cellular Networks

Polarization misalignment can significantly affect wireless communications and should be included in network models to facilitate a performance analysis and design. We therefore derive the distribution of the received signal power for the fading experienced by linearly polarized wireless links, which are misaligned by a fixed angle, and calculate the downlink outage and coverage probabilities in cellular networks using the tools from stochastic geometry. The derived model is therefore tractable and can provide insights into how we design cellular systems.

A Study of Scheduling Algorithms to Maintain Small Overflow Probability in Cellular Networks with a Single Cell

Wireless scheduling algorithms for the download of a single cell that can maximize the asymptotic decay rate of the queue-overflow probability as the overflow threshold approaches infinity. We first derive an upper bound on the decay rate of the queue-overflow probability over all scheduling policies. Specifically, we focus on the class of “α - algorithms,” the base station picks the user for service at each time that has the largest product of the transmission rate multiplied by the backlog raised to the power α. The α-algorithms arbitrarily achieve the highest decay rate of the queue-overflow probability. We design a scheduling algorithm that is both close to optimal in terms of the asymptotic decay rate of the overflow probability and to maintain small queue-overflow probabilities over queue-length ranges of practical interest.

Optimizing the handover call blocking probability in cellular networks with high speed moving terminals

This letter presents a two-layer cellular architecture which optimizes the handoff blocking probability performance of high-speed moving terminals (HSMT) in a congested urban area. The lower layer of the proposed architecture is based on a microcellular solution, for absorbing the traffic loads of both the low-speed moving terminals (LSMT) and the new calls of HSMT. The higher layer is based on a macrocell umbrella solution, for absorbing the traffic load of the existed handoff calls of the HSMT. The results show that using the optimum number of channels in each layer, the handoff call blocking probability of the HSMT is optimized having the minimum effect on the call blocking probability of the microcellular layer.

Estimation of blocking probabilities in cellular networks with dynamic channel assignment

Blocking probabilities in cellular mobile communication networks using dynamic channel assignment are hard to compute for realistic sized systems. This computational difficulty is due to the structure of the state space, which imposes strong coupling constraints amongst components of the occupancy vector. Approximate tractable models have been proposed, which have product form stationary state distributions. However, for real channel assignment schemes, the product form is a poor approximation and it is necessary to simulate the actual occupancy process in order to estimate the blocking probabilities.Meaningful estimates of the blocking probability typically require an enormous amount of CPU time for simulation, since blocking events are usually rare. Advanced simulation approaches use importance sampling (IS) to overcome this problem. In this article, we study two regimes under which blocking is a rare event: low-load and high cell capacity. Our simulations use the standard clock (SC) method. For low load, we propose a change of measure that we call static ISSC , which has bounded relative error. For high capacity, we use a change of measure that depends on the current state of the network occupancy. This is the dynamic ISSC method. We prove that this method yields zero variance estimators for single clique models, and we empirically show the advantages of this method over naïve simulation for networks of moderate size and traffic loads.

A modified distributed call admission control scheme and its performance

Call admission control is one of the key elements to guarantee the handoff call dropping probability in cellular networks. Among numerous proposals in the literature, the distributed call admission control policy (DCAC) seems to be promising, due to its simplicity and adaptability to changing traffic. However, one crucial assumption used in DCAC is that the actually admitted new calls has to obey a Poisson process to enter the network after the call admission control. Given the dynamic and distributed nature of the control process, this can neither be validated nor be easily implemented. In this paper, we will first discuss a generalized DCAC which eliminates the above assumption and can be used in general environments. Then, a mobility-aware DCAC is introduced, which considers the difference of handoff support between low and high mobility calls in making the CAC decision in order to improve channel utilization. The performance of the modified DCAC scheme is investigated through simulation studies.

An approximate model for the computation of blocking probabilities in cellular networks with repeated calls

A novel approximate model is proposed for the evaluation of call blocking probabilities in mobile cellular networks with just one service class. The accuracy of the approximate model is assessed by comparison against results of detailed simulation experiments, a previously proposed model, and upper and lower bounds to the call blocking probability. Numerical results show that the proposed model is accurate, in spite of its remarkably small state space.

Trading CDPD availability and voice blocking probability in cellular networks

Cellular digital packet data (CDPD) offers mobile users access to a low-cost, ubiquitous, wireless data network. CDPD can be overlaid on existing AMPS analog cellular systems and share their infrastructure equipment on a noninterfering basis. Since CDPD utilizes the idle radio resources of AMPS, it is important to ensure that the normal AMPS activities are not affected by CDPD. Several timers and system parameters are defined in CDPD for this purpose. This article investigates how these timers and parameters affect the performance of AMPS/CDPD systems. Our study provides guidelines for the selection of input parameters to aid CDPD network planning. Specifically, we study the trade-off between CDPD availability and voice blocking probability. CDPD availability is defined as the proportion of time that the RF channels can be used to transmit CDPD data. We observe that selecting too large values for CDPD dwell time and the maximum number of CDPD channel streams will degrade the voice blocking probability without improving CDPD availability. On the other hand, selecting a too large value for the CDPD layoff time will degrade CDPD availability without improving voice blocking probability.