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For the case of channel capacity, the algorithm was independently invented by Suguru Arimoto [1] and Richard Blahut. [2] In addition, Blahut's treatment gives algorithms for computing rate distortion and generalized capacity with input contraints (i.e. the capacity-cost function, analogous to rate-distortion).
GPkit is a Python package for cleanly defining and manipulating geometric programming models. There are a number of example GP models written with this package here . GGPLAB is a MATLAB toolbox for specifying and solving geometric programs (GPs) and generalized geometric programs (GGPs).
It is easily measured empirically and can be used to extract certain channels' parameters such as the delay spread. For Small Scale channel modeling, the power delay profile of the channel is found by taking the spatial average of the channel's baseband impulse response i.e. | h b ( t , τ ) | 2 {\displaystyle |h_{b}(t,\tau )|^{2}} over a local ...
A binomial distribution with parameters n = 1 and p is a Bernoulli distribution with parameter p. A negative binomial distribution with parameters n = 1 and p is a geometric distribution with parameter p. A gamma distribution with shape parameter α = 1 and rate parameter β is an exponential distribution with rate parameter β.
Generally, the minimum number of parameters required to describe a model or geometric object is equal to its dimension, and the scope of the parameters—within their allowed ranges—is the parameter space. Though a good set of parameters permits identification of every point in the object space, it may be that, for a given parametrization ...
Alternatively, the Nakagami distribution (;,) can be generated from the chi distribution with parameter set to and then following it by a scaling transformation of random variables. That is, a Nakagami random variable X {\displaystyle X} is generated by a simple scaling transformation on a chi-distributed random variable Y ∼ χ ( 2 m ...
The sum of independent geometric random variables with parameter is a negative binomial random variable with parameters and . [14] The geometric distribution is a special case of the negative binomial distribution, with r = 1 {\displaystyle r=1} .