Conditional probability for normally R.V

AI Thread Summary
The discussion focuses on calculating the conditional probability that two normally distributed independent random variables (w1 and w2) are smaller than three others (w3, w4, and w5) under the condition that their means are greater than zero. The initial approach involves calculating the probabilities of w1 being less than w3, w4, and w5, and then extending this to w2, considering the relationship between w1 and w2. The user is exploring different formulations for the probability of correct detection, ultimately questioning the validity of two derived equations (Eq. 3 and Eq. 4) and the independence of the slots. The discussion also touches on the concept of order statistics to better understand the relationships between the maximum and minimum values among the random variables. Understanding these probabilities is crucial for accurate detection in the given setup.
ehudwe
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kGRAN.png


w1,w2,w3,w4,w5 are normally distributed i.i.d R.V.

I want to calculate the probability that slots 1&2(w1,w2) are smaller than slots 3,4,5 (where mu>0)

I'm able to calculate the probability that slot 1 is smaller than 3,4,5, now I'm stuck on the calculation for slot 2, where i know that i have to consider the outcomes from the first calculation, for example if i know that w1(slot 1) is larger than w2(slot 2), than the probability that w2(slot 2) is smaller than (3,4,5) is 1.

until now i was sure that the whole probability is :

$$
P_{correct}= P(w_1<\mu+w_3)P(w_1<\mu+w_4)P(w_1<\mu+w_5)P(w_2<\mu+w_3)P(w_2<\mu+w_4)P(w_2<\mu+w_5)
$$
now i am thinking of:
$$
P_{correct}= P(w_1<\mu+w_3)P(w_1<\mu+w_4)P(w_1<\mu+w_5)P(w_2<\mu+w_3|w_1<w_2)P(w_2<\mu+w_4|w_1<w_2)P(w_2<\mu+w_5|w_1<w_2)P(w_2<\mu+w_3|w_2<w_1)P(w_2<\mu+w_4|w_2<w_1)P(w_2<\mu+w_5|w_2<w_1)
$$where the last 3 terms are equal to 1 because i have the knowledge that $$P(w1<μ+w3)P(w1<μ+w4)P(w1<μ+w5) $$
any help will be appreciated.
 
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How do i edit my post ? i want to revise the question
 
rewrite my question, i didn't find how to just edit

the following modulation is in the frequency domain, x-axis is frequency , y-axis is amplitude of electric current.

the signal is a pulse divided to 5 equally slots by means of electrical current where 2 "holes" indicating the binary message.
for this example my constellation size is 2^3. therefore 5C2 = 10 combinations is possible in this setup (5 slots and 2 "holes") and i'll will use 8 of them.

i am trying to calculate probability as described :


kGRAN.png


w1,w2,w3,w4,w5 are normally distributed i.i.d R.V (AWGN).

A correct detection is when the noise in slots 1 and 2 both is smaller than the noise + mu(the current related to the slot).

$$
w_1,w_2<min(\mu+w_3,\mu+w_4,\mu+w_5)
$$


so the probability for correct detection as I'm thinking is:

$$
1. P_{correct}= P(w_1<\mu+w_3\cap w_1<\mu+w_4\cap w_1<\mu+w_5\cap w_2<\mu+w_3\cap w_2<\mu+w_4\cap w_2<\mu+w_5)
$$

if I'm right, i can calculate just one of the terms , because of the i.i.d properties.
$$
2. P_{correct}= P(w_1<\mu+w_3)P(w_1<\mu+w_4)P(w_1<\mu+w_5)P(w_2<\mu+w_3)P(w_2<\mu+w_4)P( w_2<\mu+w_5)
$$
$$
P_{correct}= P(w_1<\mu+w_3)^6
$$
where
$$
P(w_1<\mu+w_3)= \int_{-\infty}^{\infty}\frac{1}{\sqrt{2\pi}\sigma}e^{-\frac{w_1^2}{2\sigma^2}}Q(\frac{w_1-\mu}{\sigma})dw_1
$$
hence the error probability is :
$$
P_{error}=1-P_{correct}
$$
therefore the general case with n- slots and k- "holes" the probability is
$$
3.P_{correct}=\left[\int_{-\infty}^{\infty}\frac{1}{\sqrt{2\pi}\sigma}e^{-\frac{x^2}{2\sigma^2}}Q(\frac{x-\mu}{\sigma})dx\right]^{(n-k)k}
$$
i did another calculation with my friend and we got:
$$
4.P_{correct}=\left[\int_{-\infty}^{\infty}\frac{1}{\sqrt{2\pi}\sigma}e^{-\frac{x^2}{2\sigma^2}}\left[Q(\frac{x-\mu}{\sigma})\right]^{(n-k)}dx\right]^k
$$

i'm trying to understand which of Eq.3 or Eq.4 is the correct answer ? and the transition from Eq.1 to Eq.2 is legal, meaning, are slots 1,2,3,4,5 are absolutely independent ?
 
ehudwe said:
A correct detection is when the noise in slots 1 and 2 both is smaller than the noise + mu(the current related to the slot).

$$
w_1,w_2<min(\mu+w_3,\mu+w_4,\mu+w_5)
$$

A way to put that in familiar territory is:

max(w_1,w_2) &lt; min(\mu+w_2,\mu+w_4,\mu+w_5)

Look at the theory of "order statistics" to find out how the max and min are distributed.
 
thanks I'm hoping it will do the work.
 
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