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EE5401 <strong>Cellular</strong> Mobile Communications<br />

EE5401 <strong>Cellular</strong> Mobile Communications<br />

P<br />

0<br />

=<br />

C<br />

∑ − 1<br />

n=<br />

0<br />

1 ⎛ λ ⎞<br />

⎜ ⎟<br />

n!<br />

⎝ µ ⎠<br />

n<br />

1<br />

1 ⎛ λ ⎞<br />

+ ⎜ ⎟<br />

C!<br />

⎝ µ ⎠<br />

C<br />

1<br />

⎛ λ ⎞<br />

⎜1<br />

− ⎟<br />

⎝ µ C ⎠<br />

<strong>The</strong> probability that the call will not have<br />

immediate access to a channel (i.e. having nonzero<br />

delay)<br />

Pr( delay<br />

> 0) = ∑ ∞ P<br />

=<br />

k<br />

k C<br />

C<br />

A 1<br />

= P<br />

C!<br />

A<br />

1−<br />

C<br />

where A = λ / µ . This is the Erlang C formula.<br />

- This probability of non-zero delay that can be<br />

tolerated is also known to be the GoS parameter of<br />

the Erlang C system.<br />

- If no channels are immediately available, the call<br />

is delayed, and the probability that the delayed<br />

call is forced to wait more than t seconds is given<br />

by the probability that a call is delayed, multiplied<br />

by the conditional probability that the delay is<br />

greater than t seconds (the delay threshold).<br />

Pr(delay > t)<br />

= Pr(delay > 0) Pr(delay > t delay > 0)<br />

= Pr(delay > 0) exp[ −(<br />

C − A)<br />

t / H ]<br />

- <strong>The</strong> average delay D for all calls in a queued<br />

system is given by<br />

∞<br />

H<br />

D = ∫ Pr(delay > t)<br />

dt = Pr(delay > 0)<br />

0<br />

C − A<br />

or the average delay for those calls which are<br />

queue is given by H /( C − A)<br />

.<br />

0<br />

Note: Proof for<br />

Pr( delay > t delay > 0) = exp[ −(<br />

C − A)<br />

t / H ]<br />

Consider C=1, this corresponding to the M/M/1 queue<br />

model. <strong>The</strong> waiting time W consists of the service times of<br />

the existing N customers in the system, ie.,<br />

W = S1 + S2<br />

+ L+<br />

S N where S i follows exponential<br />

distribution fS ( t)<br />

= µ exp( − µ t)<br />

and W is the sum of these N<br />

i<br />

independent random variables. Note that implicity we<br />

assume that N > 0 .<br />

λ λ n<br />

Also can easily show that P n = (1 − )( ) , i.e. n follows a<br />

µ µ<br />

geometric distribution (memoryless property).<br />

<strong>The</strong> pdf of W is then given by<br />

Erlang(<br />

n+<br />

1, µ )<br />

64748 4<br />

∞<br />

∞ n<br />

( µ t)<br />

−µ<br />

t λ λ n<br />

fW<br />

( t)<br />

= ∑ f<br />

W | n<br />

( t,<br />

n)<br />

Pn<br />

= ∑ µ e ⋅ (1 − )( )<br />

n=<br />

0<br />

n=<br />

0 n!<br />

µ µ<br />

−(<br />

µ −λ)<br />

t<br />

= ( µ − λ)<br />

e<br />

Note that µ = 1/ H , A = λH<br />

, integrate this from t to ∞ will<br />

obtain Pr( delay > t delay > 0)<br />

For M/M/C queue, the system behaves as an M/M/1 queue<br />

with higher service rate C µ (rather than µ ).<br />

Institute for Infocomm Research 69 National University of Singapore<br />

Institute for Infocomm Research 70 National University of Singapore

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