In this paper, we propose a handoff scheme with two-level priority for the reservation of handoff request calls in mobile cellular radio systems. We assume two types of mobile subscribers with different distributions of moving speed, that is, users with low average moving speed (e.g., pedestrians) and high average moving speed (e.g., people in moving cars). A fixed number of channels in each cell are reserved exclusively for handoff request calls. Out of these number of channels, some are reserved exclusively for the high speed handoff request calls. The remaining channels are shared by both the originating and handoff request calls. In the proposed scheme, both kinds of handoff request calls make their own queues. The system is modeled by a three-dimensional Markov chain. We apply the Successive Over-Relaxation (SOR) method to obtain the equilibrium state probabilities. Blocking probabilities of calls, forced termination probabilities and average queue length of handoff calls of each type are evaluated. We can make the forced termination probabilities of handoff request calls smaller than the blocking probability of originating calls. Moreover, we can make the forced termination probability of high speed handoff request calls smaller than that of the low speed ones. Necessary queue size for the two kinds of handoff request calls are also estimated.

The importance sampling simulation technique has been exploited to obtain an accurate estimate for a very small probability which is not tractable by the ordinary Monte Carlo simulation. In this paper, we will investigate the simulation for a sample average of an output sequence from a Markov chain. The optimal simulation distribution will be characterized by the Kullback-Leibler divergence of Markov chains and geometric properties of the importance sampling simulation will be presented. As a result, an effective computation method for the optimal simulation distribution will be obtained.

This paper presents a model for a wide-band fading channel for terrestrial mobile applications. The model is based on the results of measurements made in a heavily built-up urban environment using a 25 MHz signal centred at approximately 2.6 GHz. This paper presents measured impulse responses and details the parameter extraction process used to determine the characteristics of the channel. These parameters are used in the channel simulation package and the output of these simulations are compared to the original data.

A new recursive method for obtaining the mean waiting time in a polling system with general service order and gated service discipline is proposed. The analytical approach used to obtain the mean waiting time is via an imbedded Markov chain and a new recursive method is used to obtain the moments of pseudocycle time which are parameters in the formula for the mean waiting time. This method is computationally tractable, so the analytical results can cover a wide range of applications. Simulations are also conducted to verify the validity of the analysis.

The generation and design of a stationary Markov signal are discussed as an inverse problem, in which one looks for a transition probability when a stationary probability distribution is given. This paper presents a new solution to the inverse problem, which makes it possible to design and generate a Markov random signal with arbitrary probability distribution and an exponential correlation function. Several computer results are illustrated in figures.

This paper gives a systematic approach to generate a Markov chain by a discrete-valued auto-regressive equation, which is a a nonlinear auto-regressive equation having a discrete-valued solution. The power spectrum, the correlation function and the transition probability are explicitly obtained in terms of the discrete-valued auto-regressive equation. Some computer results are illustrated in figures.

This paper proposes a second order auto-regressive equation with discrete-valued random coefficients. The auto-regressive equation transforms an independent stochastic sequence into a binary sequence, which is a special case of a stationary Markov chain. The power spectrum, correlation function and the transition probability are explicitly obtained in terms of the random coefficients. Some computer results are illustrated in figures.

A group-based random access communication system which consists of two groups of many users is considered. The two different groups share a common random multiple access channel. Users from a group are allocated a high transmitting power level and have a high probability of correct reception among overlapping packets. We set a threshold, θ, which is such that the group with the high power level will occupy the channel if less than or equal to θ packets are transmitted from the group with the low power level. We obtain a two-dimensional Markovian model by tracing the number of backlogged users in the two groups. The two-dimensional Markov chain is shown to be not ergodic and thus the system is not stable. A two-dimensional retransmission algorithm is developed to stabilize the system and the retransmission control parameters are chosen so as to maximize the channel throughput. An equilibrium point analysis is performed by studying the drift functions of the system backlog and it is shown that there is a unique global equilibrium point. The channel capacity for the system is found to be in the range from 0.47 up to 0.53, which is a remarkable increase compared to the conventional slotted ALOHA system.

The embedded Markov processes associated with Markovian queueing systems are closely related, and their relationships are important for establishing an analytical basis for performance evaluation techniques. As a first step, we analyze the embedded processes associated with a general M/M/1 queueing system. Linear transformations between the infinitesimal generators and the transition probability matrices of embedded processes at arrival and departure times are explicitly derived. Based upon these linear transformations, the equilibrium distributions of the system states at arrival and departure times are obtained and expressed in terms of the equilibrium distribution at arbitrary times. The approach presented here uncovers an underlying algebraic structure of M/M/1 queueing systems, and establishes an algebraic methodology for analyzing the equilibrium probabilities of the system states at arrival and departure times for more general Markovian queueing systems.