Almost rejectionless sampling from Nakagami-m distributions (m≥1)

Channel Capacity Comparison of MIMO Systems with Rician Distributions, Rayleigh Distributions and Nakagami-m

This paper represents the MIMO channel capacity over Rician fading, Rayleigh fading and Nakagami fading channel. Here Rician fading model employs a zero-mean stochastic sinusoid as the line-of-sight component. This paper offers analyses and simulations to the behavior of MIMO system and its expected capacity for various channel distribution under flat fading. Several types of distributions (Ric...

Sampling Distributions Sampling Distributions

Sampling from Gibbs distributions

Sampling from Gibbs distributions by Eric Joseph Vigoda Doctor of Philosophy in Computer Science University of California at Berkeley Professor Alistair Sinclair, Chair This thesis considers computational questions concerning statistical mechanical models of idealized physical systems. The equilibrium state of the physical system is described by a probability distribution over the allowed con g...

Sampling from Discrete Distributions:

At the 2001 FCSM Research Conference, Greene et al. introduced a problem in editing and imputation based on fire data. The editing problem consists of imputing values to cells in a 2x2 contingency table subject to extensive item and unit nonresponse. Mathematically, the nonresponse creates an incomplete 2-way table with partial counts for individual cells and marginal totals. Statistically, the...

Nakagami-m Fading Channels

Abstract: This paper is concerned with the analysis of exact symbol error probability (SEP) for cooperative diversity using amplify-and-forward (AF) relaying over independent and non-identical Nakagami-m fading channels. The mathematical formulations for Probability Density Function (pdf) and Moment Generating Function (MGF) of a cooperative link have been derived for calculating symbol error p...