2,238 research outputs found
Bounds on the Sum Capacity of Synchronous Binary CDMA Channels
In this paper, we obtain a family of lower bounds for the sum capacity of
Code Division Multiple Access (CDMA) channels assuming binary inputs and binary
signature codes in the presence of additive noise with an arbitrary
distribution. The envelope of this family gives a relatively tight lower bound
in terms of the number of users, spreading gain and the noise distribution. The
derivation methods for the noiseless and the noisy channels are different but
when the noise variance goes to zero, the noisy channel bound approaches the
noiseless case. The behavior of the lower bound shows that for small noise
power, the number of users can be much more than the spreading gain without any
significant loss of information (overloaded CDMA). A conjectured upper bound is
also derived under the usual assumption that the users send out equally likely
binary bits in the presence of additive noise with an arbitrary distribution.
As the noise level increases, and/or, the ratio of the number of users and the
spreading gain increases, the conjectured upper bound approaches the lower
bound. We have also derived asymptotic limits of our bounds that can be
compared to a formula that Tanaka obtained using techniques from statistical
physics; his bound is close to that of our conjectured upper bound for large
scale systems.Comment: to be published in IEEE Transactions on Information Theor
Computational Geometry Column 42
A compendium of thirty previously published open problems in computational
geometry is presented.Comment: 7 pages; 72 reference
Accurate Short-Term Yield Curve Forecasting using Functional Gradient Descent
We propose a multivariate nonparametric technique for generating reliable shortterm historical yield curve scenarios and confidence intervals. The approach is based on a Functional Gradient Descent (FGD) estimation of the conditional mean vector and covariance matrix of a multivariate interest rate series. It is computationally feasible in large dimensions and it can account for non-linearities in the dependence of interest rates at all available maturities. Based on FGD we apply filtered historical simulation to compute reliable out-of-sample yield curve scenarios and confidence intervals. We back-test our methodology on daily USD bond data for forecasting horizons from 1 to 10 days. Based on several statistical performance measures we find significant evidence of a higher predictive power of our method when compared to scenarios generating techniques based on (i) factor analysis, (ii) a multivariate CCC-GARCH model, or (iii) an exponential smoothing covariances estimator as in the RiskMetricsTM approach.Conditional mean and variance estimation, Filtered Historical Simulation, Functional Gradient Descent, Term structure; Multivariate CCC-GARCH models
Voronoi diagrams of lines in 3 space under polyhedral convex distance functions
The combinatorial complexity of the Voronoi diagram of n lines in three dimensions under a convex distance function induced by a polytope with a constant number of edges is shown to be O(n 2 (n) logn), where is a slowly growing inverse of the Ackermann function. There are arrangements of n lines where this complexity can be as large as (n
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