Channel Holding Time Distribution in Public Cellular Telephony

2007

Call holding times in telephony networks are commonly approximated by exponential distributions to facilitate traffic engineering. However, for traffic engineering of cellular networks, channel occupancy times need to be modeled instead to facilitate analytical modeling or to feed network simulations. In this paper, we classify channel occupancy times and present an empirical study based on data obtained from a real cellular network to determine which probability distribution functions can approximate them better. The results are environment dependent, but no assumptions that can be influential are made, as opposed to previous analytical and simulation studies which results are highly dependent on the assumptions made by the authors. We show that all types of channel occupancy times can be approximated by lognormal distribution. For stationary users, channel occupancy times are commonly approximated by exponential distribution due to its tractability, assuming that cell residence times are also exponentially distributed. However, we show that lognormal distribution fits much better to both channel occupancy and call holding times regardless of whether users are stationary or mobile.

2011

Handoff failure probability in cellular systems is defined as the probability that a handoff request is denied for lack of resources, and premature call termination probability is defined as the probability that an accepted ongoing call is terminated due to lack of recourses, are two of the main parameters used to study and analyze several cellular system performance measures. Further, they are the main parameters that are used in quality of service studies and teletraffic analysis of such a network during the planning and development stages. To evaluate the handoff failure probability, premature call termination probability, and other system performance measures such as call dropping probability, several statistical distributions have been used in the literature to model the channel holding time distribution in 3 rd and 4 th generations cellular systems, such as exponential, Erlang, Gamma, and generalized Gamma, hence, the complexity of the analytical and simulation models introduc...

International Journal of Computer Applications, 2012

This research work is aimed at the study of arrival rate and holding time used in mobile communication networks, also to determine the best suitable statistical probability distribution of both arrival rate and holding time or service time in mobile communication network. The most general acceptable assumption about arrival rate is Poisson distribution and the holding time is exponential distribution in traffic modeling of mobile communication networks. Exhaustive literature review is deployed for details explanation on discrete random variables of arrival rate and continuous holding time use in traffic modeling of mobile communication networks. From the research work, the arrival rate is explained using point process or counting process, which leads to two unique properties, they are orderly and memorylessness. These unique properties are possessed by Bernoulli process with is discrete time, having Geometric distribution function, also with Poisson process, which is continuous time and discrete space, having Exponential distribution function which is used to characterize arrival rate based on interarrival rate process. Therefore, from the research work, it is assumed that arrivals rate is Poisson distribution and service time or holding time is exponentially distributed in traffic situation in mobile communication networks. These statistical properties since to the best suitable in mobile communication networks because of their unique parameters and are simple to analyses.

IEEE Transactions on Vehicular Technology, 2000

Call-completion probability, call-dropping probability, and handoff rate are important performance measures of wireless networks. In this paper, we study the joint effect of channel fading and handover failure on these performance measures. For the case of Rayleigh and lognormal fading channels and for generalized distributions of the cell dwell time and the call-holding time, we derive simple closed-form expressions that

2009

In cellular networks, quantities such as number of handoff probability and handoff rate are very important parameters in the cellular system performance analysis. In previous literature, several techniques were introduced to evaluate these parameters; however, there are some limitations in the introduced techniques. In this paper, we approximate number of handoff probability and handoff rate in cellular systems in which the call holding time and cell residence time follow arbitrary statistical distributions. Specifically, we derive approximate expressions to evaluate the probability mass function of handoff number and handoff rate. The technique used does not require knowledge of the distribution of the cell residence times but only their first two moments, which may be determined easily from empirical data. The analytical results are validated by computer simulation.

IEEE Transactions on Wireless Communications, 2004

In this paper, we propose a new technique for the performance analysis of cellular mobile communication networks based on a frequency division multiple access/time division multiple access scheme (such as global system for mobile communications), in which the utilization of two separate frequency bands leads to a complex cellular structure with overlapping microcells and macrocells. Call durations and dwell times are described by random variables with general distributions; the call duration distribution is then approximated by a two-phase hyper-exponential distribution with the same first and second moments as the original general distribution. The analysis technique is based on Markovian assumptions as regards the traffic flows entering both microcells and macrocells, as well as an assumption of flow balance between handovers into and out of any cell. The analytical model is validated against results of detailed simulation experiments for various system configurations, and shown to provide quite accurate predictions.

Journal of the Operations Research Society of Japan, 2005

Knowing the distribution of the number of handovers during a call session of a given user is particularly important in cellular mobile communication networks in order to make appropriate dimensioning of virtual circuits for wireless cells. In this paper, we study the probability distributions and statistical moments for the number of handovers per call for a variety of cornbinations of the cal1 holding time (CHT) and cell residence tirne (CRT) distributions. Wt} assume that the first CIU] in the originating cell has different statistics from the CiU]s in the subsequent cells. In particular, we consider circular cells. Based on the formulation in terms of delayed renewal processes, we obtain analytical expressions for the probability mass functions and mornents of the handover number distribution. We also include some numerical results for the mean nurnber of handovers.

1997

In this paper the statistics of the message arrivals to a PAMR trunked system are investigated. The tools used to perform the statistical analysis have been previously used in similar works and are extremely simple. First, probability density functions are fitted to the channel idle time (time between the end of a message and the beginning of the next one on the same channel). To characterise the population that generates the offered traffic it is more important the time between call attempts. This is a difficult measure as it needs to be induced from other measures: attempts are not seen when they really occur, but when the system allocates a radio-channel to them. Two methods to obtain the coefficient of variation of the time between call attempts are presented. Based on the proposed procedures we show that in our system the infinite population assumption is far from the true situation. The measures presented in this paper show that the time between call attempts follows a probability distribution smoother than the exponential and that models such as finite population or unbalanced multipopulation should be considered.

IEEE Transactions on Vehicular Technology, 1998

In recent years, handover request queueing has been extensively analyzed as a handover protection scheme for future cellular networks. In this frame, however, while channel holding time distribution and cell boundary crossing rate have been modeled, the distribution of the allowed queue waiting time-i.e., the handover dwell time-has remained an open question from the modeling standpoint. In this frame, this paper proposes a model of the handover dwell time in circular cells coverage. The agreement between modeling and simulation results is very satisfactory. A fitting of an asymptotic behavior of the handover dwell-time distribution with a truncated Gaussian function is also provided, measuring the fitting goodness in various test cases. The practical insights the model can provide are also outlined in the paper.

Wireless Personal Communications, 2017

This paper develops an empirical statistical channel occupancy model for downlink long-term evolution (LTE) cellular systems. The model is based on statistical distributions mixtures for the holding times of the channels. Moreover, statistical distribution of the time when the channels are free is also considered. The data is obtained through an extensive measurement campaign performed in Stockholm, Sweden. Two types of mixtures are considered, namely, exponential and log-normal distributions to fit the measurement findings. The log-likelihood of both mixtures is used as a quantitative measure of the goodness of fit. Moreover, finding the optimal number of linearly combined distributions using the Akaike information criterion is investigated. The results show that good fitting can be obtained by using either exponential or log-normal distributions mixture. Even though, the fitting is done for a representative case with a tempo-spatial consideration, the model is yet applicable in general for LTE and other cellular systems in a wider sense.