Computing and bounding the generalized Marcum Q-function via a geometric approach

R Li, PY Kam - 2006 IEEE International Symposium on …, 2006 - ieeexplore.ieee.org
R Li, PY Kam
2006 IEEE International Symposium on Information Theory, 2006ieeexplore.ieee.org
The generalized Marcum Q-function, Q m (a, b), is here explained geometrically as the
probability of a 2m-dimensional, real, Gaussian random vector, whose mean vector has a
Frobenius norm of a, lying outside a hypersphere of 2m dimensions, with radius b, and
centered at the origin. Based on this new geometric interpretation, a new closed-form
representation Q m (a, b) is derived for the case where m is an odd multiple of 0.5. This
representation involves only the exponential and the erfc functions, and thus is easy to …
The generalized Marcum Q-function, Q m (a,b), is here explained geometrically as the probability of a 2m-dimensional, real, Gaussian random vector, whose mean vector has a Frobenius norm of a, lying outside a hypersphere of 2m dimensions, with radius b, and centered at the origin. Based on this new geometric interpretation, a new closed-form representation Q m (a,b) is derived for the case where m is an odd multiple of 0.5. This representation involves only the exponential and the erfc functions, and thus is easy to handle, both numerically and analytically. For the case where m is an even multiple of 0.5, Q m+0.5 (a,b) and Q m-0.5 (a,b), which can be evaluated using our new representation mentioned above, are shown to be tight upper and lower bounds on Q m (a,b), respectively. They are shown in most cases to be much tighter than the existing bounds in the literature, and are valid for the entire ranges of a and b concerned. Their average is also a good approximation to Q m (a,b)
ieeexplore.ieee.org
Showing the best result for this search. See all results