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This paper considers the link-level and network-level performance of code division multiple access (CDMA) pilot interference cancellation (pilot IC) technology, a low-complexity advanced receiver technology being considered for use in commercial third generation (3G) CDMA cellular systems. The concept behind this technology is to estimate and cancel at the handset receiver the interference effects associated with CDMA downlink pilot signals broadcast from the base stations of the network. The canceling of interference at the receiver improves the signal-to-interference/noise ratio (SINR), which enables increased cell capacity or throughput. In this paper, we derive SINR expressions for evaluating the probability of error performance of both the RAKE and pilot IC handset receivers, under conventional random spreading code assumptions. The approach can easily and accurately model a wide variety of transmitter, channel, and receiver conditions, including the effects of channel estimation. We also utilize radio network simulations to illustrate and quantify the capacity gains available for 3G CDMA networks through the use of pilot IC handsets. Network simulations are also used to examine the reduced level of soft-handoff found to be possible in pilot IC-based networks and the increased flexibility available in setting pilot power levels. We further consider the impact of using stronger pilot signals for improving the demodulation performance of sensitive higher-order modulation constellations that are needed to support spectrally efficient high-rate data services. Index Terms--Code division multiple access (CDMA), interference cancellation, multiuser detection, pilot signal, RAKE.

The wide-sense stationary-uncorrelated scattering (WSSUS) channel model is a commonly employed model for the multipath channel experienced in mobile communications. The second-order statistics of these channels are described by the delay cross-power density [[Phi].sub.h]([Tau]; [Delta]t) or by its [Delta]t-Fourier transform, the scattering function [S.sub.h]([Tau]; [Lambda]). This paper presents an analysis of the delay cross-power density and scattering functions for mobile communications channels. We assume an arbitrary spatially uncorrelated scattering (US) field with arbitrary propagation-loss factors. Our first result is a general integral expression for [[Phi].sub.h]([Tau]; [Delta]t) that holds with both transmitter and receiver being mobile. We then derive more detailed results for the case of a stationary base station. We derive an infinite Bessel series for [[Phi].sub.h]([Tau]: [Delta]t) and a closed-form expression for [S.sub.h]([Tau]: [Lambda]). These results generalize the well-known classical approximation for the time-correlation function [Mathematical Expression Omitted], which corresponds to the zeroth term of our Bessel series.

Two importance sampling techniques are presented for estimating the distribution of computation of sequential decoding for specific convolutional codes (not ensemble averages). Only stack algorithm decoders are considered. Numerical examples are presented for both the BSC and the AWGN channel.

Some extensions that allow new estimating and bounding techniques for certain sequences of random variables controlled by a large deviation principle are given. These results can be thought of as generalizations and extensions of the Chernoff Bound used in communications theory.

Let S(sub n) = summation of k to the n where k = 1 X(sub k) be a sum of n i.i.d. random variables. Estimation of the large deviations probability p(sub n) = P(S(sub n) greater than or equal to gamma(sub n) via importance sampling, a Monte Carlo technique based on sampling (X(sub 1), ..., X(sub n)) from a sampling distribution Q(center dot) not equal to P(center dot), is considered. It has been previously shown that within the nonparametric candidate family all i.i.d. (or, more generally, Markov) distributions, the optimized exponentially twisted distribution is the unique asymptotically optimal sampling distribution. As n arrow to the right infinity, the sampling cost required to stabilize the normalized variance var (Mathematical Expression Omitted) grows with strictly positive exponential rate for any suboptimal sampling distribution, while this sampling cost for the optimal exponentially twisted distribution is only O(n to the 1/2). Here, it is established that the optimality is actually much stronger. As n arrow to the right infinity, this solution simultaneously stabilizes all error moments of both the sample mean and the sample variance estimators with sampling cost O(n to the 1/2). In addition, it is shown that the embedded parametric family of exponentially twisted distributions has a certain uniform asymptotic stability property. The technique is stable even if the optimal twisting parameter(s) cannot be precisely determined.

This correspondence addresses the problem of finding an input signal u that maximizes the output energy of a linear filter subject to the constraint absolute value of u is less than or equal to e where e is a specified envelope. The main contribution is to provide a new direct proof of the necessity of a certain fixed point condition. Using the weak* topology on the input signal space, we also prove certain compactness and continuity properties that further illuminate the nature of the problem.

Byline: Loick Roche, John Sadowsky In this paper, the authors discuss the compelling power of stories and storytelling. After reviewing some of the most important literature about storytelling, they focus on four principal reasons for the power of story. First, stories are universal, crossing boundaries of language, culture and age. Second, they mirror human thought. All evidence from neurology and psychology leads to the conclusion that humans think in narrative structures. Concepts conveyed in story form more than ideas explained with logic and analysis imprint themselves naturally into human minds. Third, stories define who we are. Our sense of identity is forged by the stories we tell ourselves, the ones we come to believe and those we choose to dismiss. Fourth, stories build and preserve a group's sense of community. Stories align and motivate by portraying the world in vivid terms that build emotional connections among constituents, giving them a sense of shared purpose.