Handbook of Propagation Effects for Vehicular and ... - Courses

11-20
Propagation Effects for Vehicular and Personal Mobile Satellite Systems
summarized in Table 11-5. The resultant probability distribution model is expressed in
terms of the contributions for the "no shadowing" and "shadowing" cases in the following
way
( A A ) = P ( − S)
+ P S
P > q ns 1 s , (11-59)
where Pns is the probability distribution for the case of no shadowing of the line of sight
and is given by
⎡ ( ) ( A + U ) ⎤
A > A = exp⎢−
1
⎥⎦
Pns q
, (11-60)
⎣ U2
where the parameters U1 and U2 are functions of K and are given by
and
2
U 1 = 0.
01K
− 0.
378K
+ 3.
98
(11-61)
−2.
29
U 2 = 331.
35K
. (11-62)
In (11-59), Ps is the probability distribution for the case of shadowing of the line of sight
and is
Ps
V2
⎛ 50 − Aq
⎞
> q =
⎜
V ⎟ , (11-63)
⎝ 1 ⎠
( A A )
where the parameters V1 and V2 are given by the following functions of K as well as the
mean m and standard deviation s of the lognormal signal
V = −0.
275K
+ 0.
723m
+ 0.
336 s + 56.
979
(11-64)
1
2
( ) 1 −
− 0.
006 K − 0.
008m
+ 0.
013 + 0.
121
V = s
(11-65)
Typical fade predictions calculated from (11-59) have been plotted in Figure 11-2 for
light and heavy as well as in Figure 11-3 for medium heavy shadowing, for infrequent
(S=0.25), moderate (S=0.5) and frequent (S=0.75) shadowing occurrences. In the worst
case scenario corresponding to heavy and frequent shadowing, the calculated fade
probabilities may exceed 1.0, but should be limited to that value.