Information theoretic considerations for cellular mobile radio
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Cites background from "Information theoretic consideration..."
...Finally, although previous work focuses primarily on ergodic settings and characterizes performance via Shanno n capacity or capacity regions, we focus on non-ergodic or delay-constrained scenarios and characterize performanc e by outage probability [11]....
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...In this section, we characterize performance of the protoco ls of Section III in terms of outage events and outage probabili ties [11]....
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...Throughout the rest of the paper, w assume that the reader is familiar with these latter areas, a nd refer the interested reader to [2]–[4], [9], [10], and refer nces therein, for an introduction to the relevant concepts from m ultiantenna systems and to [11] for an introduction to outage capacity for fading channels....
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...Consequently, we focus on delay-limited or non-ergodic sce narios, and evaluate performance of our protocols in terms of outage probability [11]....
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Cites methods from "Information theoretic consideration..."
...As a step to prove Theorem 2, we will first discuss another commonly used concept for multiple-antenna channels: the outage capacity formulation, proposed in [11] for fading channels and applied to multiantenna channels in [1]....
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...Thus, instead of using the machinery of the error exponent theory, we exploit the special properties of fading channels and develop a simple approach, based on the outage capacity formulation [11], to analyze the diversity–multiplexing tradeoff in the high-SNR regime....
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4,385 citations
Cites background from "Information theoretic consideration..."
...below some fixed spectral efficiencyis referred to as an outage event, and the probability of an outage event, , is referred to as the outage probability of the channel [8]....
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References
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"Information theoretic consideration..." refers background or methods in this paper
...where the asymptotic properties of the eigenvalues [42], [ 43 ] along with the strict bandlimitness assumption, that is: Ss(f) = O,V(fl > W, have been incorporated....
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...against the Poisson kernel [ 43 ] giving 1/r [(l - r2)/(1 + r2 - 27 cos O)] exp-2q(1--7 ‘Os @) do. Substituting q = P/( 1 r2) and assembling all the relevant sums in (D8) gives the expression for the probability distribution function...
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