Process for estimating the channel in a OFDM communication system, and receiver for doing the same
View Patent ↗A process for estimating a channel in an OFDM communication system, wherein an OFDM sample is based on a time-frequency grid comprising a set of pilots may include the steps of receiving, by a receiver, OFDM sample based subframes comprising a set of pilot signals, performing an iterative loop for the purpose of computing (M k , k k ) respectively corresponding to the covariance matrix and the mean of the probability distribution of p(h k |y k , l k ) at time instant k, y k , and l k respectively corresponding to the received signal and to a priori known information, the value of (M k , k k ) being computed as a function of (M k−1 , k k−1 ) as well as the values of the pilots received at instant k.
1. A process for estimating a channel in an OFDM communication system, wherein an OFDM sample is based on a time-frequency grid comprising a set of pilots, the process comprising the steps of:
receiving, by a receiver, OFDM sample based subframes comprising a set of pilot signals;
performing an iterative loop for the purpose of computing (M k , k k ) respectively corresponding to the covariance matrix and the mean of the probability distribution of p(h k |y k , l k ) at time instant k, y k , and l k respectively corresponding to the received signal and to a priori known information and h k being a true channel at time instant k; and
said value of (M k , k k ) being computed as a function of (M k−1 , k k−1 ) as well as the values of the pilots received at instant k.
2. The process for estimating the channel in an OFDM communication system according to claim 1 further comprising the steps of:
receiving OFDM sample based subframes comprising a set of pilots signals;
performing an estimation of the channel based on the mean k k and variance M k of the distribution of the true channel h k in accordance with the following formulation:
{
M
k
=
λ
2
(
M
k
-
1
+
1
-
λ
3
λ
2
Q
)
×
(
λ
2
σ
2
P
k
(
M
k
-
1
+
1
-
λ
2
λ
2
Q
)
+
I
N
)
-
1
k
k
=
λ
k
k
-
1
+
1
σ
2
M
k
P
k
(
h
k
′
-
λ
k
k
-
1
)
with
N being the number of sub carriers in the OFDM symbol;
k k being the mean of the inferred probability distribution p(h k |y k , l k ) at time instant k;
M k being a N×N matrix representative of the variance of the probability distribution of p(h k |y k , l k ) at time instant k;
Q being a matrix initialized to a predetermined value;
P k is an N×N diagonal matrix comprising a “1” at the location of a pilot symbol and a “0”elsewhere;
I N being the N×N identity matrix;
λ corresponding to the known channel time correlation between instant k−1 and k;
σ 2 being the variance of the noise; and
h′ k being equal to the received signal y k pointwise divided by the corresponding pilot s k .
3. The process according to claim 2 wherein Q is an a priori frequency covariance matrix for an L-tap uniform channel.
4. The process according to claim 2 wherein the time correlation factor (λ) corresponds to the correlation factor in the auto regressive model of the first order of h k .
5. The process according to claim 1 wherein said parameter M k is forwarded to the base station as an information representative of the quality of the channel estimation.
6. The process according to claim 1 adapted to the 3GPP Long Term Evolution (LTE) standard.
7. A process for estimating a channel in an OFDM communication system, wherein an OFDM sample is based on a time-frequency grid comprising a set of pilots, the process comprising the steps of:
receiving, by a receiver, OFDM sample based subframes comprising a set of pilots signals;
performing an iterative loop for the purpose of computing (M k (λ) , k k (λ) ) respectively corresponding to the variance and the mean of the probability distribution of p(h k |y k , l k ) at time instant k, y k , and l k respectively corresponding to the received signal and to a priori known information;
said value of (M k (λ) , k k (λ) ) being computed as a function of (M k−1 (λ) , k k−1 (λ) ) for λspanning a predetermined set of values {λ n } with n=1 to M between true channel h k and h k−1 respectively at time instant k and k−1, as well as the values of the pilots received at instant k,
h
^
k
=
∑
n
=
1
N
ⅇ
-
x
(
λ
n
)
det
[
X
(
λ
n
)
]
k
k
(
λ
n
)
1
N
∑
n
=
1
N
ⅇ
-
x
(
λ
n
)
det
[
X
(
λ
n
)
]
With
{
M
k
(
λ
)
=
λ
2
(
M
k
-
1
(
λ
)
+
1
-
λ
2
λ
2
Q
)
×
(
λ
2
σ
2
P
k
(
M
k
-
1
(
λ
)
+
1
-
λ
2
λ
2
Q
)
+
I
N
)
-
1
k
k
(
λ
)
=
λ
k
k
-
1
(
λ
)
+
1
σ
2
M
k
(
λ
)
P
k
(
h
k
′
-
λ
k
k
-
1
(
λ
)
)
And
{
X
(
λ
)
=
(
I
+
P
k
σ
2
(
λ
2
M
k
-
1
(
λ
)
+
(
1
-
λ
2
)
Q
)
)
-
1
x
(
λ
)
=
(
λ
k
k
-
1
(
λ
)
-
h
k
′
)
H
X
(
λ
)
P
k
σ
2
(
λ
k
k
-
1
(
λ
)
-
h
k
′
)
with k k (λ) being the mean of the probability distribution of p(h k |y k , l k ) at instant k depending on λ, . . .
M k (λ) being a matrix representative of the variance of the estimated channel at instant k; depending on λ,
Q being a matrix initialized to a predetermined value;
P k is a diagonal N×N matrix comprising a “1” at the location of a pilot symbol;
I N being the N×N identity matrix;
σ 2 being the variance of the noise;
h′ k being equal to the received signal y k pointwise divided by the corresponding pilot s k;
λ corresponding to the known channel time correlation between instant k−1 and k;
H is the Hermitian transpose; and
det[X] is the determinant of the matrix X.
8. The process according to claim 7 wherein Q is an a priori frequency correlation matrix for an L-tap uniform channel.
9. The process according to claim 7 wherein the set of time correlation factors {λ n } corresponds to hypothetical values for the time correlation parameter λ.
10. The process according to claim 7 wherein said parameter M k is forwarded to the base station as an information representative of the quality of the channel estimation.
11. The process according to claim 7 wherein it is adapted to the Long Term Evolution (LTE) standard.
12. A receiver for an OFDM communication system comprising:
a means for receiving a OFDM sample based subframes comprising a set of pilots signals;
a means for performing an iterative loop for the purpose of computing (M k , k k ) respectively corresponding to the variance and the mean of the probability distribution of p(h k |y k , l k ) at time instant k, y k , and l k respectively corresponding to the received signal and to a priori known information; and
said value of (M k , k k ) being computed as a function of (M k−1 , k k−1 ) as well as the values of the pilots received at instant k, with h k corresponding to the channel at the kth sampled time instant.
13. A receiver according to claim 12 , said receiver being incorporated to a mobile communication device for an LTE communication system.
14. The receiver according to claim 12 , further comprising:
a means for performing an estimation of the channel based on the mean k k and variance M k of the distribution of the channel estimation in accordance with the following formulation:
{
M
k
=
λ
2
(
M
k
-
1
+
1
-
λ
2
λ
2
Q
)
×
(
λ
2
σ
2
P
k
(
M
k
-
1
+
1
-
λ
2
λ
2
Q
)
+
I
N
)
-
1
k
k
=
λ
k
k
-
1
+
1
σ
2
M
k
P
k
(
h
k
′
-
λ
k
k
-
1
)
with
N being the number of sub carriers in the OFDM symbol;
k k being the mean of the probability distribution of p(h k |y k , l k ) at time instant k;
M k being a N×N matrix representative of the variance of the probability distribution of p(h k |y k , l k ) at instant k;
Q being a matrix initialized to a predetermined value;
P k is an N×N diagonal matrix comprising a “1” at the location of a pilot symbol and a “0”elsewhere;
I N being the N×N identity matrix; and
λ corresponding to the known channel time correlation between instant k−1 and k;
σ 2 being the variance of the noise; and
h′ k being equal to the received signal y k pointwise divided by the corresponding pilot s k .
15. A receiver for an OFDM communication system comprising a means for estimating the channel and characterized in that it further comprises:
a means for receiving a OFDM sample based subframes comprising a set of pilots signals;
a means for performing an iterative loop for the purpose of computing (M k (λ) , k k (λ) ) respectively corresponding to the variance and the mean of the probability distribution of p(h k |y k , l k ) at time instant k, y k , and l k respectively corresponding to the received signal and to a priori known information;
said value of (M k (λ) , k k (λ) ) being computed as a function of (M k−1 , k k−1 ) for a predetermined set of values of time correlation (λ n ) with n=1 to M between the true channels h k and h k−1 , with h k corresponding to the channel at the kth sampled time instant,as well as the values of the pilots received at instant k,
h
^
k
=
∑
n
=
1
N
ⅇ
-
x
(
λ
n
)
det
[
X
(
λ
n
)
]
k
k
(
λ
n
)
1
N
∑
n
=
1
N
ⅇ
-
x
(
λ
n
)
det
[
X
(
λ
n
)
]
with
{
M
k
(
λ
)
=
λ
2
(
M
k
-
1
(
λ
)
+
1
-
λ
2
λ
2
Q
)
×
(
λ
2
σ
2
P
k
(
M
k
-
1
(
λ
)
+
1
-
λ
2
λ
2
Q
)
+
I
N
)
-
1
k
k
(
λ
)
=
λ
k
k
-
1
(
λ
)
+
1
σ
2
M
k
(
λ
)
P
k
(
h
k
′
-
λ
k
k
-
1
(
λ
)
)
and
{
X
(
λ
)
=
(
I
+
P
k
σ
2
(
λ
2
M
k
-
1
(
λ
)
+
(
1
-
λ
2
)
Q
)
)
-
1
x
(
λ
)
=
(
λ
k
k
-
1
(
λ
)
-
h
k
′
)
H
X
(
λ
)
P
k
σ
2
(
λ
k
k
-
1
(
λ
)
-
h
k
′
)
With k k (λ) being the mean of the probability distribution of p(h k |y k , l k ) at instant k depending on λ,
M k (λ) being a matrix representative of the variance of the estimated channel at instant k; depending on λ,
Q being a matrix initialized to a predetermined value;
P k is a diagonal N×N matrix comprising a “1” at the location of a pilot symbol;
I N being the N×N identity matrix;
σ 2 being the variance of the noise; and
h′ k being equal to the received signal y k pointwise divided by the corresponding pilot s k;
λ corresponding to the known channel time correlation between instant k−1 and k;
H is the Hermitian transpose; and
det[X] is the determinant of the matrix X.