Method and system for an efficient channel quantization method for MIMO pre-coding systems
A method and system for processing communication signals is provided and may comprise, minimizing a cost function in a MIMO pre-coding system by choosing a smallest scalar cost from a plurality of scalar costs, wherein each one of the scalar costs is generated from one or more sums and one or more products of elements of a product matrix, and wherein the product matrix is generated from one of the plurality of unitary matrices, a matrix comprising the channel estimate, and their respective Hermitian Transposes. The codebook is selected based on the minimized cost function. The channel estimate is quantized onto the selected codebook.
1. A method for processing communication signals, the method comprising:
minimizing a cost function in a MIMO pre-coding system by choosing a smallest scalar cost from a plurality of scalar costs, wherein each one of said scalar costs is generated from one or more sums and one or more products of elements of a product matrix, wherein said product matrix is generated from one of a plurality of unitary matrices of a codebook, a matrix comprising a channel estimate, and their respective Hermitian Transposes;
selecting said codebook based on said minimized cost function; and
quantizing said channel estimate onto said selected codebook.
2. The method according to claim 1 , wherein said matrix comprising said channel estimate is a matrix Ĥ.
3. The method according to claim 1 , wherein said cost function comprises a function f(A), which is defined by the following relationship:
f
(
A
)
=
∑
i
=
1
N
∑
j
=
1
,
j
≠
i
N
a
i
,
j
2
where A is said product matrix of size N by N and a ij is element (i,j) of matrix A.
4. The method according to claim 1 , wherein said scalar cost function comprises a function f(A), which is defined by the following relationship:
f
(
A
)
=
∑
i
=
1
N
∑
j
=
1
,
j
≠
i
N
a
i
,
j
2
-
∑
i
=
1
N
a
i
,
j
where A is said product matrix of size N by N and a ij is element (i,j) of matrix A.
5. The method according to claim 4 , wherein said cost function is defined by the following relationship:
V q =arg min {circumflex over (V)} i εC f ( {circumflex over (V)} i H ·Ĥ H ·Ĥ·{circumflex over (V)} i )
where V q , {circumflex over (V)} i εC, and Ĥ are matrices of appropriate dimensions and C is said codebook.
6. The method according to claim 1 , comprising transmitting an index of an element of said selected codebook onto which said channel estimate is quantized, from a MIMO receiver to a MIMO transmitter in said MIMO pre-coding system.
7. The method according to claim 6 , wherein a number of transmit antennas of said MIMO transmitter and a number of receive antennas of said MIMO receiver is at least one each.
8. The method according to claim 6 , comprising linearly transforming a vector signal at said MIMO transmitter based on said index of said element of said selected codebook.
9. The method according to claim 6 , comprising adjusting said codebook dynamically.
10. The method according to claim 6 , comprising selecting said codebook statically.
11. A system for processing communication signals, the system comprising:
one or more circuits for use in a MIMO pre-coding system, wherein said one or more circuits are operable to minimize a cost function in a MIMO pre-coding system by choosing a smallest scalar cost from a plurality of scalar costs, wherein each one of said scalar costs is generated from one or more sums and one or more products of elements of a product matrix, wherein said product matrix is generated from one of a plurality of unitary matrices of a codebook, a matrix comprising a channel estimate, and their respective Hermitian Transposes;
said one or more circuits are operable to select said codebook based on said minimized cost function; and
said one or more circuits are operable to quantize said channel estimate onto said selected codebook.
12. The system according to claim 11 , wherein said matrix comprising said channel estimate is a matrix Ĥ.
13. The system according to claim 11 , wherein said cost function comprises a function f(A), which is defined by the following relationship:
f
(
A
)
=
∑
i
=
1
N
∑
j
=
1
,
j
≠
i
N
a
i
,
j
2
where A is said product matrix of size N by N and a ij is element (i,j) of matrix A.
14. The system according to claim 11 , wherein said cost function comprises a function f(A), which is defined by the following relationship:
f
(
A
)
=
∑
i
=
1
N
∑
j
=
1
,
j
≠
i
N
a
i
,
j
2
-
∑
i
=
1
N
a
i
,
i
where A is said product matrix of size N by N and a ij is element (i,j) of matrix A.
15. The system according to claim 12 , wherein said cost function is defined by the following relationship:
V q =arg min {circumflex over (V)} i εC f ( {circumflex over (V)} i H ·Ĥ H ·Ĥ·{circumflex over (V)} i )
where V q , {circumflex over (V)} i εC, and Ĥ are matrices of appropriate dimensions and C is said codebook.
16. The system according to claim 15 , wherein a number of transmit antennas of said MIMO transmitter and a number of receive antennas of said MIMO receiver is at least one each.
17. The system according to claim 15 , wherein said one or more circuits are operable to linearly transform a vector signal at said MIMO transmitter based on said index of said element of said selected codebook.
18. The system according to claim 15 , wherein said one or more circuits are operable to adjust said codebook dynamically.
19. The system according to claim 15 , wherein said one or more circuits are operable to select said codebook statically.
20. The system according to claim 11 , wherein said one or more circuits are operable to transmit an index of an element of said selected codebook onto which said channel estimate is quantized, from a MIMO receiver to a MIMO transmitter in said MIMO pre-coding system.