2,026 research outputs found
An Approximation of the First Order Marcum -Function with Application to Network Connectivity Analysis
An exponential-type approximation of the first order Marcum -function is
presented, which is robust to changes in its first argument and can easily be
integrated with respect to the second argument. Such characteristics are
particularly useful in network connectivity analysis. The proposed
approximation is exact in the limit of small first argument of the Marcum
-function, in which case the optimal parameters can be obtained
analytically. For larger values of the first argument, an optimization problem
is solved, and the parameters can be accurately represented using regression
analysis. Numerical results indicate that the proposed methods result in
approximations very close to the actual Marcum -function for small and
moderate values of the first argument. We demonstrate the accuracy of the
approximation by using it to analyze the connectivity properties of random ad
hoc networks operating in a Rician fading environment.Comment: 6 pages, 4 figures, 1 tabl
On the Monotonicity of the Generalized Marcum and Nuttall Q-Functions
Monotonicity criteria are established for the generalized Marcum Q-function,
\emph{Q}_{M}, the standard Nuttall Q-function, \emph{Q}_{M,N}, and the
normalized Nuttall Q-function, , with respect to their real
order indices M,N. Besides, closed-form expressions are derived for the
computation of the standard and normalized Nuttall Q-functions for the case
when M,N are odd multiples of 0.5 and . By exploiting these results,
novel upper and lower bounds for \emph{Q}_{M,N} and are
proposed. Furthermore, specific tight upper and lower bounds for
\emph{Q}_{M}, previously reported in the literature, are extended for real
values of M. The offered theoretical results can be efficiently applied in the
study of digital communications over fading channels, in the
information-theoretic analysis of multiple-input multiple-output systems and in
the description of stochastic processes in probability theory, among others.Comment: Published in IEEE Transactions on Information Theory, August 2009.
Only slight formatting modification
Error Rates of the Maximum-Likelihood Detector for Arbitrary Constellations: Convex/Concave Behavior and Applications
Motivated by a recent surge of interest in convex optimization techniques,
convexity/concavity properties of error rates of the maximum likelihood
detector operating in the AWGN channel are studied and extended to
frequency-flat slow-fading channels. Generic conditions are identified under
which the symbol error rate (SER) is convex/concave for arbitrary
multi-dimensional constellations. In particular, the SER is convex in SNR for
any one- and two-dimensional constellation, and also in higher dimensions at
high SNR. Pairwise error probability and bit error rate are shown to be convex
at high SNR, for arbitrary constellations and bit mapping. Universal bounds for
the SER 1st and 2nd derivatives are obtained, which hold for arbitrary
constellations and are tight for some of them. Applications of the results are
discussed, which include optimum power allocation in spatial multiplexing
systems, optimum power/time sharing to decrease or increase (jamming problem)
error rate, an implication for fading channels ("fading is never good in low
dimensions") and optimization of a unitary-precoded OFDM system. For example,
the error rate bounds of a unitary-precoded OFDM system with QPSK modulation,
which reveal the best and worst precoding, are extended to arbitrary
constellations, which may also include coding. The reported results also apply
to the interference channel under Gaussian approximation, to the bit error rate
when it can be expressed or approximated as a non-negative linear combination
of individual symbol error rates, and to coded systems.Comment: accepted by IEEE IT Transaction
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