Digital Signal Processing Reference
In-Depth Information
The DOAs are estimated using the H k ( t ) values during an estimation period P, which
is defined to be a set of L mini-slots. Each estimation period is divided into Q subestima-
tion periods P i , i = 1, , Q , such that P = P 1 ∪P 2 P Q and P i ∩P j = 0, i j . Each P q
is composed of L q mini-slots with
1
Q
L
=
L q
.
q
=
In subestimation period P q , the artificial phase shift ϕ( t ) of adaptive opportunistic
beamforming is set to ϕ q , i.e., ϕ( t ) = ϕ q ∈[0,2π), for t ∈P q , q = 1, 2, , Q .* For example,
we can set ϕ q = ( q / Q )2π, for q = 1, 2, , Q . We define A k,q , Ω k,q , and K k,q as follows: A k,q =
A k ( t )| t ∈P q , Ω k,q = Ω k ( t )| t ∈P q = A k,q + σ 2 , and K k,q = K k ( t )| t ∈P q .
Given σ k and A k,q at the base station, the ML estimation of θ k is given by
Q
L
q
2
2
HtA
()
+
2
HtA
()
2
P
ˆ
k
k q
,
k
k q
,
θ
ML
=
argmax
H
(
t
)exp
I
(7. 2 6)
k
k
0
σ
2
σ
2
σ k
2
θ
[,
02
π
)
k
k
k
q
=
1
t
q
for k = 1, , M . Taking logarithm, a simpler estimator is given by
Q
2
HtA
()
ˆ
ML
k
k q
,
2
θ
=
argmax
ln
I
A kq
(7. 27)
k
0
,
2
σ
θ
∈ 02
[,
π
)

k
k
q
=
1
tP
q
for k = 1, , M . In order to reduce the computational complexity further at the loss of
the ML optimality, suboptimum estimators may be considered. In particular, noting
that G k ( t ) is maximized when ϕ q = -θ k , an efficient and very simple suboptimum estima-
tor can be given by
ˆ
=− ( )
θ
SUB
qQ
2
π
,
(7. 2 8)
k
1
2
q
=
argmax
Ht
().
(7. 29)
k
L
=
q
1
,,
Q q
t q
7.4.3 Estimation of K -Factors of the Physical Channels
In the proposed DOA estimation algorithms, it was assumed that the exact { K k } k =1
values were known at the base station. In practical systems, however, each user needs
* Recall that in conventional opportunistic beamforming, ϕ( t ) is randomly chosen from [0,2π).
Also, note that the pilot overhead is the same for the adaptive and conventional schemes, because
only one mini-slot of fixed length is used for pilot signaling in each time slot for both schemes.
 
 
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