Improved Sequential Stopping Rule for Monte Carlo Simulation

This paper presents an improved result on the negative-binomial Monte Carlo technique analyzed in a previous paper for the estimation of an unknown probability p. Specifically, the confidence level associated to a relative interval [p/\mu_2, p\mu_1], with \mu_1, \mu_2 > 1, is proved to exceed its asymptotic value for a broader range of intervals than that given in the referred paper, and for any value of p. This extends the applicability of the estimator, relaxing the conditions that guarantee a given confidence level.Comment: 2 figures. Paper accepted in IEEE Transactions on Communication

Illustrating multipath propagation by means of sound waves

A method is presented that uses sound waves to illustrate multipath propagation concepts. This is based on the existing analogy between radio and sound waves, and has the advantage that the required equipment is easily available. Different measurement techniques are introduced to respectively examine time dispersion, time variation, and both aspects of the multipath channel simultaneously. The proposed techniques are justified, example results are given, and the specific features that are illustrated by each type of measurement are discussed. Suggestions are given regarding application in courses on wireless communications

Time-frequency characterization of a sound propagation channel as an educational tool

This paper discusses the use of sound waves to illustrate multipath radio propagation concepts. Specifically, a procedure is presented to measure the time-varying frequency response of the channel. This helps demonstrate how a propagation channel can be characterized in time and frequency, and provides visualizations of the concepts of coherence time and coherence bandwidth. The measurements are very simple to carry out, and the required equipment is easily available. The proposed method can be useful for wireless or mobile communication courses

Estimation of a Probability with Guaranteed Normalized Mean Absolute Error

The estimation of a probability p from repeated Bernoulli trials is considered in this letter. A sequential approach is followed, using a simple stopping rule. A closed-form expression and an upper bound are obtained for the mean absolute error of the unbiased estimator of p. The results given permit the estimation of an arbitrary probability with a prescribed level of normalized mean absolute error

Using the Spectrum Analyzer as an Educational Tool for Mobile Communications

Application of the spectrum analyzer for illustrating several concepts associated with mobile communications is discussed. Specifically, two groups of observable features are described. First, time variation and frequency selectivity of multipath propagation can be revealed by carrying out simple measurements on commercial-network GSM and UMTS signals. Second, the main time-domain and frequency-domain features of GSM and UMTS radio signals can be observed. This constitutes a valuable tool for teaching mobile communication courses

Estimation of a probability in inverse binomial sampling under normalized linear-linear and inverse-linear loss

Sequential estimation of the success probability $p$ in inverse binomial sampling is considered in this paper. For any estimator $\hat p$, its quality is measured by the risk associated with normalized loss functions of linear-linear or inverse-linear form. These functions are possibly asymmetric, with arbitrary slope parameters $a$ and $b$ for $\hat pp$ respectively. Interest in these functions is motivated by their significance and potential uses, which are briefly discussed. Estimators are given for which the risk has an asymptotic value as $p$ tends to $0$, and which guarantee that, for any $p$ in $(0,1)$, the risk is lower than its asymptotic value. This allows selecting the required number of successes, $r$, to meet a prescribed quality irrespective of the unknown $p$. In addition, the proposed estimators are shown to be approximately minimax when $a/b$ does not deviate too much from $1$, and asymptotically minimax as $r$ tends to infinity when $a=b$.Comment: 4 figure

On Dimension Reduction for the Power Control Problem

In this paper we show how the dimension of power control equation systems can be reduced from K, the number of users in the system, to M, the number of cells, without any loss of generality in the analysis. Decentralized downlink power control algorithms are then presented which generalize previously proposed ones, broadening the range of application while maintaining reduced complexity

System-Level Analysis of Closed-Loop Power Control in the Uplink of DS-CDMA Cellular Networks

A system-level model for power control in the uplink of direct-sequence code-division multiple access (DS-CDMA) cellular networks is presented. The model takes into account the effects of the closed loop, namely average transmit power rise, power headroom, and variable soft hand-off gains, which are not considered in existing power control models. The power control problem is analyzed in this setting, and a number of properties are derived which generalize results from the classical model without closed-loop effects. Based on this analysis, an algorithm is given that determines required transmit powers taking into account these effects. This algorithm is a generalization of classical iterative algorithms without closed-loop effects. Finally, simulation results are presented to assess the validity of the approach

A Simple Sequential Stopping Rule for Monte Carlo Simulation

In this paper, a sequential stopping rule for the estimation of a probability p by means of Monte Carlo simulation is analyzed. It is shown that the proposed estimator is almost unbiased, and guarantees a given relative precision irrespective of p. Under very mild conditions, the method also guarantees a certain confidence level for a given relative estimation error, provided that p does not exceed a maximum value. An extension to importance sampling is discussed