Stochastic geometry modeling and energy efficiency analysis of millimeter wave cellular networks

Current wireless networks face unprecedented challenges because of the exponentially increasing demand for mobile data and the rapid growth in infrastructure and power consumption. This study investigates the optimal energy efficiency of millimeter wave (mmWave) cellular networks, given that these networks are some of the most promising 5G-enabling technologies. Based on the stochastic geometry, a mathematical framework of coverage probability is proposed and the optimal energy efficiency is obtained with coverage performance constraints. Numerical results show that increasing the base station density damages coverage performance exceeding the threshold. This work demonstrates an essential understanding of the deployment and dynamic control of energy-efficient mmWave cellular networks.     

Stochastic models for ATM switching networks

Models that take into account the fact that the switching speed may be appreciably greater than the speed at which some sources generate their respective cells are considered. The case is investigated where the cells making up individual bursts are spaced according to some prescribed probability distribution. It is shown that the switch performance is strongly dependent on the input parameters and it is demonstrated that analytical approaches provide useful alternatives to the lengthy simulation runs needed to evaluate probabilities of rare events, such as cell losses     

Inter-cell interference modeling for cellular networks

We develop and analyze several inter-cell interference modeling methods for various fading scenarios in wireless systems. The models can analyze multiple interfering signals under different fading scenarios. Incoherent addition of multiple interfering signals is assumed. In this paper, we present two approaches, i.e., the approximate and exact analysis methods to calculate the probability density function (PDF) of the power of the interference signals. We propose the use of the generalized Gram-Charlier Series to analyze the error of the reference model. Although the computational complexity of exact analysis is high, it can be used to ensure the accuracy of the approximate analysis method. Hermite polynomials are used to simplify the integration operation into the summation operation, thus reduces the computational complexity of the exact method dramatically. The approximate method is simple although it may lead to increased errors. The methods proposed are useful in designing and analyzing practical systems.     

Stochastic geometry and architecture of communication networks

This paper proposes a new approach for communication networks planning based on stochastic geometry. We first summarize the state of the art in this domain, together with its economic implications, before sketching the main expectations of the proposed method. The main probabilistic tools are point processes and stochastic geometry. We show how several performance evaluation and optimization problems within this framework can actually be posed and solved by computing the mathematical expectation of certain functionals of point processes. We mainly analyze models based on Poisson point processes, for which analytical formulae can often be obtained, although more complex models can also be analyzed, for instance via simulation. This revised version was published online in June 2006 with corrections to the Cover Date.     

Stochastic control of handoffs in cellular networks

A dynamic programming formulation is used to obtain an optimal strategy for the handoff problem in cellular radio systems. The formulation includes the modeling of the underlying randomness in received signal strengths as well as the movements of the mobile. The cost function is designed such that there is a cost associated with switching and a reward for improving the quality of the call. The optimum decision is characterized by a threshold on the difference between the measured power that the mobile receives from the base stations. Also we study the problem of choosing the “best” fixed threshold that minimizes the cost function. The performance of the optimal and suboptimal strategies are compared     

Stochastic context-free grammars and hidden Markov models for modeling of bursty channels

In order to design good error-control schemes for bursty channels and also to facilitate performance analysis, it is important to develop accurate and simple statistical channel error models for the channels of interest. We propose two novel generative methods to model the end-to-end error profile of radio channels described by long well-defined error bursts interleaved with long error-free intervals. The first method makes use of the power of stochastic context-free grammars to model palindromes. The second utilizes simple hidden Markov models with specific structures, which are suggested by the ideas presented in the first method. Both methods achieve much better performance than previously proposed approaches without introducing more complexity. Although the complexity of the second method is slightly greater than that of the first, its advantage is that it can be easily applied in decoding implementations specifically tailored to deal with bursty channels.     

On the study of location measurements in urban cellular networks

This work presents a statistical field study of the availability of time sources used by location techniques in a true wireless network. Terrestrial (base stations) and satellite (GPS) sources were investigated in three different urban scenarios. The density function of a specific number of sources available for triangulation is presented along with other statistical data in order to assess coverage. Since the fusion of terrestrial and satellite sources to obtain the location in wireless networks has been proposed as a way of improving coverage, the joint density function and cross-correlation between the availability of both types of sources are also presented. This correlation depends on the scenario, leading to the conclusion that the improvement obtained through the fusion of sources depends on both the fusion type and the scenario.     

Approximation models of wireless cellular networks using momentmatching

In this paper we present an analytical model for micro- and pico-cell wireless networks for any arbitrary topology in a high mobility feedforward environment. We introduce an approximation technique which uses a single-cell decomposition analysis which incorporates moment matching of handoff processes into the cell. The approximation technique can provide close approximations for non-Poisson arrival traffic and it is easily parallelized. Performance measures such as new calls blocked, handoff calls lost, and forced termination are derived for any general independent call arrival distribution in a heterogeneous traffic environment. We produce some numerical examples for some simple topologies with varying mobility for several call arrival distributions and compare our results to those from simulation studies     

Stochastic geometry modeling and analysis of downlink coverage and rate in small cell network

Telecommunication Systems - Due to the massive wireless traffic demand in fifth generation (5G) network, small cell have been attracted growing attention as a key solution and scalable approach for...     

Inter-cell interference in multi-tier heterogeneous cellular networks: modeling and constraints

Telecommunication Systems - Interference is the main source of capacity limitation in wireless networks. In some medium access technologies in cellular networks, such as OFDMA, the allocation of...     

Novel scheme for interference avoidance in cognitive radio based cellular networks

The cognitive radio (CR) technology is believed to improve the spectrum efficiency.However,the interference problem has become a critical issue due to the coexistence of primary systems and CR systems....     

一种基于量子细胞自动机的三维量子细胞神经网络

以量子细胞自动机为神经元,提出了一种三维的量子细胞神经网络结构;该量子细胞网络包含上下两层的量子细胞自动机阵列,并引入了A模板、B模板以及阈值的概念.以量子细胞自动机的极化率为像素值,通过选择不同的模板、阈值等参数.使得量子细胞神经网络实现了"与"、"或"、"非"操作以及边缘提取等图像处理功能,并利用MATLAB进行了仿真验证,数值仿真结果验证了其在图像处理上的有效性.与传统的细胞神经网络相比,量子细胞神经网络易于实现超大规模且具有超低功耗、超高集成度等优点.     

Bandwidth-reservation scheme based on road information for next-generation cellular networks

Channel-reservation techniques have been widely studied in cellular networks in order to meet the desired quality-of-service requirements. In this paper, a distributed predictive channel-reservation scheme, called the road-map-based channel-reservation scheme (RMCR), and a call-admission-control algorithm are proposed. The goal is to reduce the handoff-dropping probability and to improve the bandwidth utilization. In the RMCR scheme, we assume that base stations (BSs) are equipped with road-map information and that mobile stations (MSs) are equipped with global positioning systems (GPS) devices. MSs periodically report their GPS location information to their BSs. Based on the location information of the MSs at two consecutive epochs, the BSs estimate the speed and moving direction of the MSs. Furthermore, the BSs estimate the probability that the MSs will enter the neighboring cells based on their velocity and the road-map information stored in the BSs. The BSs then compute the amount of bandwidth to be reserved, based on such estimation. With the road-map information, the BSs can make a more-accurate prediction on the user's mobility and, hence, reduce unnecessary bandwidth reservation. Simulation results show that RMCR is capable of keeping the handoff-dropping probability low and allocating bandwidth to new/handoff calls efficiently. We also show that RMCR is robust with respect to system parameters such as user's speed, the density of roads, the accuracy of mobility measurement, and so on.     

Stochastic geometry effects in MOS transistor

The influence of random edge effects and oxide thickness variations on MOS transistor characteristics is investigated. The variance of the drain current is calculated as a function of the parameters of the stochastic geometry effects. Finally, the relation with the scaling down of the transistor dimensions is also included.     

Performance of received power and traffic-driven handover algorithms in urban cellular networks

This article presents an investigation of the handover algorithms suitable for implementation in urban mobile cellular networks based on TDMA. More precisely, the class of received power and traffic-driven handover algorithms, which are based on absolute and relative measured values of received power and on actual traffic load, is analyzed. The algorithms usually investigated in the literature (and often implemented in actual mobile networks) belong to this class. We show the performance of traditional algorithms, and also propose some new ones, in an effort to reduce the probability of dropout due to sudden changes of received power and to distribute the traffic load over several cells; they show performance improvements with respect to those previously known from the literature. The performance of the different handover algorithms is evaluated by means of a simulation tool that allows the consideration of complex scenarios, suitable mobility and propagation models, power control, cell sectorization, nonuniform user distribution, and so on. The metrics used for performance comparison are the outage, blocking, dropout, and satisfaction probabilities, whose different definitions are discussed in the article, and the average number of handovers per call. Several urban scenarios, characterized by uniform and nonuniform traffic distributions, are taken into account. Our results show that one of the proposed algorithms, based on traffic estimates, yields the best performance of all the considered scenarios.     

Stochastic models for random-request availability

The system receives a stream of tasks which arrive according to some random processes. A new availability measure, random-request availability, is proposed. This stochastic model provides closed-form mathematical expressions which incorporate the 3 basic elements: random task arrivals; system state; and operational requirements of the system. An analytic model is derived and illustrated by numerical examples     

Stochastic models for mission effectiveness

A stochastic model of mission effectiveness for a system which is required to perform a random number of tasks during its mission is developed. Mission effectiveness is defined as a combined measure of availability and reliability at each task-arrival time. An analytic model is derived under a general set of assumptions. Other models are outlined to show the wide applicability of this model for mission effectiveness     

Resource allocation in cellular networks based on marketing preferences

As the usage of cellular phones increases wireless subscribers demand many advanced networking capabilities, especially multimedia applications with very high Quality of Service (QoS) requirements. The limited availability of radio spectrum enforces Mobile Network Operators (MNOs) to have efficient resource management strategies. The goal is to offer services that satisfy the QoS requirements of individual users while achieving an efficient utilization of network resources. This paper considers a resource allocation strategy for cellular networks to be applied during call initiation, handoff and allocation of mobile base stations. Long-term customer retention becomes a major challenge for MNOs due to severe competition in the telecommunications industry. Therefore the MNOs need to understand the customer demographics as well as the customer spending behavior in telecommunications market. Our proposed model combines the information about the customer demographics and usage behavior once the call is initiated. Our hypothesis is that using customer information together with call information yields an efficient customer-oriented resource management strategy. We have performed simulations with different real-life scenarios. Our results show that our proposed model performs better in terms of revenue increase when compared to the First-Come First-Serve based approach.     

Reducing overhead in movement based dynamic location management scheme for cellular networks

One of the key issues in cellular mobile communication is to find the current location of mobile terminal (MT) to deliver the services, which is called location management (LM). Much research has been done on dynamic LM that reduced the LM cost up to a large extent. In movement based dynamic LM scheme, the location area is defined in the form of ring of cells for individual user. Whenever an MT visits a cell outside of its current location area (LA), it triggers location update (LU). For this purpose, network must inform the mobile terminal about ID of all the cells present in its current location area. In this paper, a simple way of cell-ID assignment is proposed under which, network sends only the ID of center cell of LA ring to MT and then MT can compute IDs of all other cells in its location area. This saves a significant amount of wireless bandwidth by minimizing the signaling traffic at VLR level and thus reduces the mobility management overhead.     

Outage and energy efficiency analysis for cognitive based heterogeneous cellular networks

Cognitive radio and small cells are the promising techniques to minimize energy consumption and satisfy the exponentially increasing data rates for the heterogeneous cellular network (HCN). In this paper, a theoretical framework is developed to calculate the outage probability of the HCN based on the opportunistic utilization of the traditional cellular bandwidth and television white space (TVWS) for the cognitive femto base stations. This work investigates overlay, underlay, mixed overlay-underlay based two tiers cognitive HCN. It also investigates the impact of the TVWS in the overlay-TVWS mixed spectrum sharing technique (SST). Tools from stochastic geometry are used to model cognitive HCN. Furthermore, the tier selection probability, average ergodic rate, area spectral efficiency (ASE), and energy efficiency (EE) of the HCN are also calculated for different SSTs. Numerical results show that mixed SST achieves a significant reduction in tier outage probability and total outage probability as compared to underlay and overlay techniques alone. It is also demonstrated that compared to the traditional single tier network, cognitive based HCN can improve the total ASE and EE of the order of \(10^{2}\) and 10, respectively.