Transmit processing using receiver functions

Information

  • Patent Grant
  • 8531938
  • Patent Number
    8,531,938
  • Date Filed
    Wednesday, September 2, 2009
    15 years ago
  • Date Issued
    Tuesday, September 10, 2013
    11 years ago
Abstract
A method and apparatus for transmitting data in code division multiple access communications. The method includes processing spread first data with a channel response matrix using an equalization circuit to pre-equalize the spread data to compensate for a channel response prior to transmission. The pre-equalized data is received and recovered by a receiver. Second data, transmitted from the receiver, is received and recovered using the equalization circuit to equalize the second data to compensate for a channel response that the first data encountered.
Description
FIELD OF INVENTION

The application is related to wireless communications.


BACKGROUND

In code division multiple access (CDMA) communication systems, multiple communications may be simultaneously sent over a shared frequency spectrum. Each communication is distinguished by the code used to transmit the communication.


In some CDMA communication systems, to better utilize the shared spectrum, the spectrum is time divided into frames having a predetermined number of time slots, such as fifteen time slots. This type of system is referred to as a hybrid CDMA/time division multiple access (TDMA) communication system. One such system, which restricts uplink communications and downlink communications to particular time slots, is a time division duplex communication (TDD) system.


One approach to receive the multiple communications transmitted within the shared spectrum is joint detection. In joint detection, the data from the multiple communications is determined together. In the following description a capitalized symbol X represents a matrix, and the symbol {right arrow over (x)} represents a column vector. The joint detection is typically modeled per Equation 1:

{right arrow over (r)}=A{right arrow over (d)}+{right arrow over (n)};  Equation 1

The received signal vector {right arrow over (r)} is a function of the system transmission matrix A, the transmittal data vector {right arrow over (d)}, and the noise vector {right arrow over (n)}. The system transmission matrix A contains the contributions of individual users as per Equation 2:

A=└A(1), A(2), . . . ,A(K)┘;   Equation 2

where A(k) represents the contribution of user k to the system transmission matrix A. Each user system transmission matrix is a function of the channel impulse response and the spreading code of that user per Equation 3:

A(k)=H(k)C(k);   Equation 3

Where H(k) is the channel response matrix and C(k) is the code matrix for user k.


A Minimum Mean Square Error (MMSE) estimate for the data vector custom character is obtained from Equation 4:











d

->
^


=



(


A
H



R
n

-
1



A

)


-
1




A
H



R
n

-
1




r
->



;




Equation





4








where Rn is the covariance matrix of the noise. When the noise is white, Rn is a diagonal matrix and the MMSE estimate for the data is per Equations 5A and 5B:











d

->
^


=



(



A
H


A

+


σ
2


I


)


-
1




A
H



r
->



;




Equation





5

A








which may alternatively be written as:











d

->
^


=




A
H



(


AA
H

+


σ
2


I


)



-
1




r
->



;




Equation





5

B








Equations 5A and 5B are interchangeable using matrix inversion lemma.


Similarly, a zero forcing (ZF) estimate is obtained from Equations 6A and 6B:











d

->
^


=



(


A
H


A

)


-
1




A
H



r
->



;




Equation





6





A








which may also be written as:











d

->
^


=




A
H



(

AA
H

)



-
1




r
->



;




Equation





6





B







Equations 6A and 6B are interchangeable using matrix inversion lemma.


In a CDMA system, when all codes go through the same propagation channel, as in the case of a typical downlink transmission or when one uplink user monopolizes a time slot (H(k)=H) the transmitted vector of spread symbols {right arrow over (s)} are obtained from Equation 7:











s
->

=


C


d
->


=




k
=
1

K








C

(
k
)





d
->


(
k
)






;




Equation





7








The received signal is modeled using Equation 8:

{right arrow over (r)}=H{right arrow over (s)}+{right arrow over (n)};   Equation 8


The MMSE estimate for the spread symbols {right arrow over (s)} is obtained as shown in Equations 9A and 9B:











s

->
^


=



(



H
H


H

+


σ
2


I


)


-
1




H
H



r
->



;




Equation





9

A








or equivalently:










s

->
^


=




H
H



(


HH
H

+


σ
2


I


)



-
1




r
->






Equation





9





B







Equations 9A and 9B are interchangeable using matrix inversion lemma. The ZF estimate, (derived from Equation 6) for {right arrow over (ŝ)} is obtained by Equations 10A and 10B:











s

->
^


=



(


H
H


H

)


-
1




H
H



r
->



;




Equation





10





A








or equivalently:











s

->
^


=




H
H



(

HH
H

)



-
1




r
->



;




Equation





10





B







Equations 10A and 10B are interchangeable using matrix inversion lemma. The estimate of the spread symbols custom character can be followed by a code Matched Filter (MF) to recover the data symbols.


When multiple antennas are used at the receiver, the received vector may also be represented by Equation 1. The definition of the vectors and matrix involved are modified to represent the contributions from different antennas as per Equation 11:











[





r
->

1












r
->

N




]

=



[




A
1











A
N




]



d
->


+

[





n
->

1












n
->

N




]



;




Equation





11








where {right arrow over (r)}i, Ai, and {right arrow over (n)}i are the terms associated with receive antenna element i. Ai is constructed for each antenna with a different channel response per Equation 3 and A has components associated with each of K users per Equation 12:

A=[A(1), A(2), . . . , A(K)];   Equation 12


When multiple transmit antenna elements, such as M transmit elements, are used at the transmitter, the received vector {right arrow over (r)}i is also per Equation 1. The appropriate definition of the vectors and matrix involved is represented in Equation 13:











r
->

=



[


A
1














A
M



]



[





d
->

1












d
->

M




]


+

n
->



;




Equation





13








where {right arrow over (r)} is the composite received signal, and A′m, m=1,2, . . . ,M is the system transmission matrix for signal transmission from the mth transmit element to the receiver, {right arrow over (d)}m, m=1, 2 . . . M is the data vector transmitted from transmit antenna m.


The components of A due to an ith antenna element is denoted as Ai′. Each Ai′ component has contributions from all K users per Equation 14:

A′=[A′(1), A′(2), . . . , A′(K)];   Equation 14

The contribution of each user to each antenna element is a function of the channel impulse response and the spreading (derived from Equation 3) codes as shown in Equation 15:

A′(k)=H′(k)C(k);   Equation 15


Multiple antennas at both the transmitter and the receiver are referred to as a Multiple Input Multiple Output (MIMO) system. The received signal for a MIMO system may be represented by Equation 11 rewritten as Equation 16.











[





r
->

1












r
->

N




]

=




[




A
1











A
N




]



[


A
1














A
M



]




[





d
->

1












d
->

M




]


+

[





n
->

1












n
->

N




]



;




Equation





16








Where N is the number of receive antennas; M is the number of transmit antennas; An, n=1,2, . . . ,N is the transmission matrix for reception; and A′m, m=1, 2, . . . ,M is the transmission matrix for transmission. With appropriate definitions of vectors and matrices involved, Equation 16 is rewritten as Equation 17:

{right arrow over (r)}=Λ{right arrow over (d)}+{right arrow over (n)};   Equation 17

where Λ is the composite system transmission matrix for both transmission and reception. The MMSE estimate for the data vector shown in Equation 5 is represented by Equations 18A and 18B:











d

->
^


=



(



Λ
H


Λ

+


σ
2


I


)


-
1




Λ
H



r
->



;




Equation





18





A








or equivalently










d

->
^


=




Λ
H



(


Λ






Λ
H


+


σ
2


I


)



-
1




r
->






Equation





18





B








Equations 18A and 18B are interchangeable using matrix inversion lemma. The ZF estimate can be obtained from Equations 19A and 19B:











d

->
^


=



(


Λ
H


Λ

)


-
1




Λ
H



r
->



;




Equation





19





A








or equivalently:











d

->
^


=




Λ
H



(

Λ






Λ
H


)



-
1




r
->



;




Equation





19





B








Equations 19A and 19B are interchangeable using matrix inversion lemma.


A receiver implementing these approaches effectively performs a matrix inversion, which has a high complexity. To reduce the complexity, an approximate Cholesky decomposition or fast Fourier transforms are used. Although these approaches reduce the receiver complexity, it is desirable to have alternate approaches to simplify the transmitting and receiving of data.


SUMMARY

A channel response is determined as a channel response matrix H approximating a wireless channel that the data will experience after transmission. The data to be transmitted is spread, and the spread data is processed with the channel response matrix H. The spread and processed data is then transmitted. The data is received and recovered from the transmitted spread and processed data.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 is a simplified diagram of a transmitter and receiver using transmit processing using receiver functions.



FIG. 2 is a flow chart of transmission using receiver functions.





DETAILED DESCRIPTION

A system is described herein in conjunction with a time division duplex (TDD) mode of a CDMA system, (such as the proposed TDD mode of the third generation partnership project (3GPP) wideband CDMA system). However, the following can be applied to any spread spectrum communication system, such as frequency division duplex (FDD) system or a time division synchronous code division multiple access (TD-SCDMA) system.



FIG. 1 is a diagram of a simplified transmitter 10 and receiver 12 for use in transmit processing using receiver functions. The transmitter 10 can be located at a base station, user equipment (UE) or both, and the receiver 12 can be located at a UE, base station or both. Data to be communicated from the transmitter 10 to the receiver 12 is input into a spreading and modulation device 14 and a pre-equalizer 15. The data can be for a single code transmission to a single receiver, for a multi-code transmission to a single receiver, single code transmissions to multiple receivers, multi-code transmissions to multiple receivers or a combination of single and multi-code transmissions to multiple receivers.


The data is spread using the appropriate code(s), pre-equalized to compensate for the anticipated channel responses of the wireless radio interface 18 and modulated, such as by using quadrature phase shift keying (QPSK), M-ary quadrature amplitude modulation (QAM) or other modulation schemes, and to upconvert to radio frequency. The radio frequency signal is radiated by an antenna or M element antenna array 161-16M through a wireless radio interface 18.


An antenna, or N element antenna array 201-20N, at the receiver 12 receives the radiated signal with other signals and noise as a received vector {right arrow over (r)}. A data detector 22 processes the received vector to recover the data {right arrow over (d)}. The structure of the data detector 22 may be simplified over a typical joint detection receiver due to the pre-equalization at the transmitter 10, such as by being implemented by code matched filters.


The transmitter 10 effectively compensates for the channel distortion prior to transmission. As a result, the received vector {right arrow over (r)} is approximately the spread data vector {right arrow over (s)}.


The pre-equalization makes use of the channel and code information available at a receiver 12 to process the transmit vector appropriately so that when that signal is received at the receiver 12 it is already compensated for channel impairments. The channel information can be signaled from the receiver 12, may be derived from signals received at the transmitter 10 within the same frequency spectrum. To illustrate, for a base station of a TDD/CDMA communication system, the channel information may be gathered in an uplink time slot for a subsequent downlink transmission time slot.


When processing at the transmitter 10 is used, the received signal obtained from Equation 20A:











r
->

=



[


A
1














A
M



]



[





d
->

1












d
->

M




]


+

n
->



;




Equation





20





A








In terms of the channel and code matrices, Equation 20A becomes Equation 20B:










r
->

=




[


H
1














H
M



]



[




C
1









































C
M




]




[





d
->

1












d
->

M




]


+

n
->






Equation





20





B







The code matrix C1 through CM can differ based on the transmission scheme. One such scheme is space code transmit diversity (SCTD), where each antenna is assigned a different transmission code. In some transmit diversity schemes the same code matrix is used for each antenna. One such scheme is transmit adaptive antennas (TxAA). Although transmit processing using receiver functions is described in conjunction with each antenna transmitting the same code matrix C, it is also applicable to systems where the code matrix varies by antenna using an analogous approach.


In some systems, the transmit data bits {right arrow over (d)}1 through {right arrow over (d)}M can differ based on the transmission scheme, in particular whether transmit diversity is used. Although an analogous approach can be applied to systems having differing data vectors per antenna, the following is described in conjunction with each antenna transmitting the same data vector {right arrow over (d)}. For systems where the same data and code matrix is transmitted from each antenna, the system is modeled per Equation 21.













r
->

=



[


A
1














A
M



]



[




d
->











d
->




]


+

n
->








=




[


H
1














H
M



]



[



C







































C



]




[




d
->











d
->




]


+

n
->









=



[


H
1














H
M



]



[




C


d
->












C


d
->





]


+

n
->



;







Equation





21








The transmit vector is shown by Equation 22:










[




C


d
->












C


d
->





]

;




Equation





22







The pseudo-inverse of H from the right is HH(HHH)−1. The data signal after processing is transmitted with this pseudo-inverse. Accordingly, the transmitted signal {right arrow over (t)}′ is shown by Equation 23:

{right arrow over (t)}′=HH(HHH)−1C{right arrow over (d)};   Equation 23


The resulting received vector is shown in Equation 24:













r
->

=




HH
H



(

HH
H

)



-
1



C


d
->









=

C


d
->



;







Equation





24







If the pre-equalization is ideal, a clean signal is received 12 at the receiver without any need for further processing. However, in practice due to noise and variations in the channel conditions, typically some degradation to the received signal occurs. However, the required processing to remove degradation is greatly decreased, further increasing the required complexity of the receiver 12.


One of the advantages of a MMSE or ZF type receiver is that MMSE or ZF circuits are commonly at the transmitter 10 site. To illustrate, a base station typically has an MMSE type receiver. Accordingly, a single MMSE circuit can be used for processing the received and transmitted data at the base station. As a result, the circuitry for a receiver 12 and a transmitter 10 implementing transmit processing using receiver functions can be consolidated into either the UE or the base station, with the other communicating unit having simplified circuitry.


For example, the base station may use the pre-equalization transmitter 10 and a MMSE receiver. The matrix or effective matrix inversion can be performed by the same circuit. As a result, the receiver circuitry at the UE can be simplified, such as a single or group of code matched filters. The simplified receiver circuitry also extends the battery life at the receiver 12.


The common used circuitry is not limited to MMSE or ZF receiver circuitry, but it is rather general in that any receiver 12 structure that is capable of performing matrix operations and calculating matrix inverse is suited to do processing at the transmitter 10. Another advantage of the pre-equalization is that the transmitted signal is focused on the receiver 12. For downlink signals in particular, the interference to other users is reduced.


Referring to FIG. 2, a method 30 is shown. The method commences with obtaining wireless channel information, which may be in the form of a channel impulse response H (step 32). The data for transmission is then pre-equalized using the channel impulse response H (step 34). The pre-equalized data is transmitted across the wireless radio interface (step 36) and is received as a received vector (step 38) at the receiver. The data is then recovered from the received vector, such as by using code matched filters (step 40).

Claims
  • 1. A transmitter comprising: a spreading and modulation device configured to spread data using multiple codes; anda pre-equalizer configured to process the spread data with a channel response matrix to pre-equalize the spread data to compensate for a channel response prior to transmission, to receive channel and code information used by the pre-equalizer to equalize the spread data to compensate for channel impairments that the spread data will encounter upon transmission and to transmit the equalized spread data;wherein the pre-equalizer is configured to multiply the spread data by HH(HHH+σ2I)−1, where H is the channel response matrix, σ2 is a noise variance, and I is an identity matrix.
  • 2. The transmitter of claim 1 wherein the channel and code information is gathered in an uplink time slot for a subsequent downlink transmission slot.
  • 3. A method of transmitting data in code division multiple access communications, the method comprising: spreading data using multiple codes;receiving channel and code information;processing the spread data with a channel response matrix to pre-equalize the spread data to compensate for a channel response prior to transmission, wherein the spread data is equalized to compensate for channel impairments that the spread data will encounter upon transmission, wherein the spread data is multiplied by HH(HHH+σ2I)−1, where H is the channel response matrix, σ2 is a noise variance, and I is an identity matrix; andtransmitting the equalized spread data.
  • 4. The method of claim 3 wherein the channel and code information is gathered in an uplink time slot for a subsequent downlink transmission slot.
  • 5. Apparatus for performing code division multiple access communications, the apparatus comprising: a receiver configured to transmit channel and code information; anda transmitter configured to spread data using multiple codes, process the spread data with a channel response matrix to pre-equalize the spread data to compensate for a channel response prior to transmission, to receive and use the channel and code information to equalize the spread data to compensate for channel impairments that the spread data will encounter upon transmission, and to transmit the equalized spread data to the receiver;wherein the spread data is multiplied by HH(HHH+σ2I)−1, where H is the channel response matrix, σ2 is a noise variance, and I is an identity matrix.
  • 6. The apparatus of claim 5 wherein the channel and code information is gathered in an uplink time slot for a subsequent downlink transmission slot.
CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No. 10/335,347 filed on Dec. 31, 2002,which claims the benefit of U.S. Provisional Application No. 60/396,490 filed on Jul. 17, 2002,and U.S. Provisional Application No. 60/368,639 filed on Mar. 28, 2002,which are incorporated by reference as if fully set forth.

US Referenced Citations (26)
Number Name Date Kind
5224122 Bruckert Jun 1993 A
5550810 Monogioudis et al. Aug 1996 A
5881108 Herzberg et al. Mar 1999 A
6011812 Laakso et al. Jan 2000 A
6044083 Citta et al. Mar 2000 A
6175588 Visotsky et al. Jan 2001 B1
6233273 Webster et al. May 2001 B1
6233454 Sato May 2001 B1
6314147 Liang et al. Nov 2001 B1
6473467 Wallace et al. Oct 2002 B1
6741643 McGibney May 2004 B1
6959047 Al-Dhahir Oct 2005 B1
7154935 Kowalewski et al. Dec 2006 B1
7593357 Ozluturk et al. Sep 2009 B2
20010017881 Bhatoolaui et al. Aug 2001 A1
20020060990 Bohnke et al. May 2002 A1
20020061005 Lee et al. May 2002 A1
20020126741 Baum et al. Sep 2002 A1
20020159537 Crilly, Jr. Oct 2002 A1
20020160731 Hashimoto et al. Oct 2002 A1
20020173286 Lindoff et al. Nov 2002 A1
20020177447 Walton et al. Nov 2002 A1
20030026348 Llang et al. Feb 2003 A1
20030081656 Buehrer May 2003 A1
20030108117 Ketchum et al. Jun 2003 A1
20040196892 Reznik Oct 2004 A1
Foreign Referenced Citations (16)
Number Date Country
2 396 571 Jul 2001 CA
1106094 Apr 2003 CN
0 180 066 May 1986 EP
52-006011 Jan 1977 JP
63-279623 Nov 1988 JP
1051424 Feb 1998 JP
11-266232 Sep 1999 JP
2000-224076 Aug 2000 JP
2001-267989 Sep 2001 JP
2001-520492 Oct 2001 JP
2002-374224 Dec 2002 JP
355892 Apr 1999 TW
9216054 Sep 1992 WO
9509493 Apr 1995 WO
9920061 Apr 1999 WO
0001092 Jan 2000 WO
Non-Patent Literature Citations (6)
Entry
Choi, “Interference Mitigation Using Transmitter Filters in CDMA Systems,” The 12th IEEE International Symposium on PIMRC 2001, vol. 1, pp. 30-34.
Kang, Shao-Ii et al., Comparison of ZF-BLE and MMSE-BLE in TD-SCDMA System, Oct. 29, 2001.
Kowaleski et al. “Joint Predistortion and Transmit Diversity.” IEEE, Nov. 27, 2000. pp. 245-249.
Lee, Edward A., “Digital Communications” 2nd Edition, 1994, Kluwer Academic Publishers, pp. 460-464.
Rappaport, “Equalization, Diversity and Channel Coding”, Wireless Communication—Principles and Practice, Chapter 6, pp. 299-324, 2002.
Wang et al., “Wireless Multicarrier Communications Where Fourier Meets Shannon,” IEEE Signal Processing Magazine, vol. 17, No. 3, (May 2000).
Related Publications (1)
Number Date Country
20090323775 A1 Dec 2009 US
Provisional Applications (2)
Number Date Country
60396490 Jul 2002 US
60368639 Mar 2002 US
Continuations (1)
Number Date Country
Parent 10335347 Dec 2002 US
Child 12552831 US