Method for the soft bit metric calculation with linear MIMO detection for LDPC codes

• US 20070127603A1
• Filed: 12/01/2005
• Published: 06/07/2007
• Est. Priority Date: 12/01/2005
• Status: Active Grant

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Niu, Huaning, Ngo, Chiu
• Granted Patent: US 7,751,506 B2
• Time in Patent Office: Days
• US Class Current: 375/341
• CPC Class Codes: H03M 13/1102 Codes on graphs and decoding on graphs, e.g. low-density parity check [LDPC] codes
• CPC Class Codes: H04L 1/0045 Arrangements at the receiver end
• CPC Class Codes: H04L 1/0057 Block codes H04L1/0061, H04L1/0064 take precedence
• CPC Class Codes: H04L 2025/03414 Multicarrier
• CPC Class Codes: H04L 2025/03426 transmission using multiple-input and multiple-output channels
• CPC Class Codes: H04L 2025/03605 Block algorithms
• CPC Class Codes: H04L 25/03159 operating in the frequency domain H04L25/03165, H04L25/03178 take precedence

Abstract

A MIMO receiver implements a method for the soft bit metric calculation with linear MIMO detection for LDPC codes, after linear matrix inversion MIMO detection. In the receiver, a detector detects the estimated symbol and the noise variance. Further, a soft metric calculation unit computes the distance between the estimated symbol and the constellation point, and then divides the distance by the noise variance to determine the soft bit metrics.

Claims

1. A method of soft bit metric calculation for received data signals via a channel in a telecommunications receiver utilizing LDPC decoding, comprising the steps of:

detecting data symbols in the received signal by applying a linear MIMO detection;

determining the channel noise variance;

calculating the soft bit metrics as a function of the distance and the noise variance.

2. The method of claim 1 further including the steps of LDPC decoding using the soft bit metrics to determine data values in the received signals.

3. The method of claim 1 wherein the step of calculating the soft bit metrics further includes the steps of dividing the distance by the noise variance.

4. The method of claim 1 wherein the step of determining the noise variance further includes the steps of performing MMSE criterion MIMO detection.

5. The method of claim 4 wherein the channel is defined by a NrxNt channel matrix H in a MIMO system having a receiver with Nt transmitter antennas and Nr receiver antennas, x is the Ntx1 transmitted signal vector, the received symbol is represented by a Nrx1 received symbol vector y=Hx+n, n represents a Nrx1 noise vector, the method further comprising the steps of applying a linear filter W to the received symbols y to compute estimated symbols {circumflex over (x)} as:

{circumflex over (x)}=Wy=WHx+Wn,

where W=(H^HH+σ

_n²I)<sup>−

1</sup>H^H with MMSE criterion and σ

_n² represents the noise variance.

6. The method of claim 1 wherein the step of determining the noise variance further includes the steps of performing ZF criterion MIMO detection.

7. The method of claim 6 wherein the channel is defined by a NrxNt channel matrix H in a MIMO system having a receiver with Nt transmitter antennas and Nr receiver antennas, x is the Ntx1 transmitted signal vector, the received symbol is represented by a Nrx1 received symbol vector y=Hx+n, n represents a Nrx1 noise vector, the method further comprising the steps of applying a linear filter W to the received symbols y to compute estimated symbols {circumflex over (x)} as:

{circumflex over (x)}=Wy=WHx+Wn,

where W=(H^HH)<sup>−

1</sup>H^H with ZF criterion.

8. The method of claim 1, wherein the step of calculating the soft bit metrics further includes the steps of:

determining the new noise term

v=(WH−

diag(WH))x+Wn where filtering effect and cross-talk are considered,

selecting the diagonal elements σ

_v² of the noise variance matrix E[vv^H],

calculating the soft bit metrics as a function of the distance and σ

_v².

9. The method of claim 8, wherein the step of determining the noise variance further includes the steps of performing ZF criterion MIMO detection, wherein the channel is defined by a NrxNt channel matrix H in a MIMO system having a receiver with Nt transmitter antennas and Nr receiver antennas, x is the Ntx1 transmitted signal vector, the received symbol is represented by a Nrx1 received symbol vector y=Hx+n, n represents a Nrx1 noise vector, the method further comprising the steps of applying a linear filter W to the received symbols y to compute estimated symbols {circumflex over (x)} as:

{circumflex over (x)}=Wy =WHx+Wn,

where W=(H^HH)<sup>−

1</sup>H^H with ZF criterion,

such that for ZF estimation;

WH=(H^HH)<sup>−

1</sup>H^HH=I,

where the diagonal matrix σ

_v² is defined as;

σ

_v²=E[diag{vv^H}]
=σ

_n²diag{WW^H}

10. The method of claim 8 wherein the soft bit metric of a first received data stream is divided by a first diagonal element of the noise variance matrix, and the soft metric of a second received data stream is divided by a second diagonal element of the noise variance matrix.

11. The method of claim 1 wherein the receiver comprises a wireless MIMO receiver.

12. The method of claim 11 wherein the receiver receives multiple data streams signals from a transmitter with multiple antennas.

13. The method of claim 1 wherein:

the step of detecting data symbols further includes the steps of detecting data symbols in the received signal using direct matrix inversion type linear MIMO detection, and

the step of calculating the bits metrics further includes the steps of computing the bit metrics by determining distances between the estimated data symbols and constellation points.

14. A telecommunications receiver, comprising:

a detector that detects data symbols in the received signal by determining distances between received signal points and constellation points, and determines the channel noise variance;

a metric calculator that calculates soft bit metrics for received data signals via a channel, as a function of the distance and the noise variance; and

a decoder that performs LDPC decoding of the received signals using the soft bit metrics.

15. The receiver of claim 14 wherein the decoder performs LDPC decoding using the soft bit metrics to determine data values in the received signals.

16. The receiver of claim 14 wherein the metric calculator calculates the soft bit metrics by dividing the distance by the noise variance.

17. The receiver of claim 14 wherein the detector determines the noise variance by performing MMSE criterion MIMO detection.

18. The receiver of claim 17 wherein the channel is defined by a NrxNt channel matrix H in a MIMO system having a receiver with Nt transmitter antennas and Nr receiver antennas, x is the Ntx1 transmitted signal vector, the received symbol is represented by a Nrx1 received symbol vector y=Hx+n, n represents a Nrx1 noise vector, such that detector applies a linear filter W to the received symbols y to compute estimated symbols {circumflex over (x)} as:

{circumflex over (x)}=Wy=WHx+Wn,

where W=(H^HH+σ

_n²I)<sup>−

1</sup>H^H with MMSE criterion.

19. The receiver of claim 14 wherein the detector determines the noise variance by performing ZF criterion MIMO detection.

20. The receiver of claim 19 wherein the channel is defined by a NrxNt channel matrix H in a MIMO system having a receiver with Nt transmitter antennas and Nr receiver antennas, x is the Ntx1 transmitted signal vector, the received symbol is represented by a Nrx1 received symbol vector y=Hx+n, n represents a Nrx1 noise vector, such that the detector applies a linear filter W to the received symbols y to compute estimated symbols {circumflex over (x)} as:

{circumflex over (x)}=Wy=WHx+Wn,

where W=(H^HH)<sup>−

1</sup>H^H with ZF criterion.

21. The receiver of claim 14, wherein the metric calculator calculates the soft bit metrics by:

selecting the diagonal elements σ

_v² of the noise variance matrix E[vv^H],

calculating the soft bit metrics as a function of the distance and σ

_v².

22. The receiver of claim 21, wherein the detector determines the noise variance by performing ZF criterion MIMO detection, wherein the channel is defined by a NrxNt channel matrix H in a MIMO system having a receiver with Nt transmitter antennas and Nr receiver antennas, x is the Ntx1 transmitted signal vector, the received symbol is represented by a Nrx1 received symbol vector y=Hx+n, n represents a Nrx1 noise vector, such that the detector applies a linear filter W to the received symbols y to compute estimated symbols {circumflex over (x)} as:

{circumflex over (x)}=Wy=WHx+Wn,

where W=(H^HH+σ

_n²I)<sup>−

1</sup>H^H with ZF criterion and σ

_n² represents the noise variance,

such that for ZF estimation;

WH=(H^HH)<sup>−

1</sup>H^HH=I,

where the diagonal matrix σ

_v² is defined as;

σ

_v²=E[diag{vv^H}]
=σ

_n²diag{WW^H}

23. The receiver of claim 21 wherein the soft bit metric of a first received data stream is divided by a first diagonal element of the noise variance matrix, and the soft metric of a second received data stream is divided by a second diagonal element of the noise variance matrix.

24. The receiver of claim 14 wherein the receiver comprises a wireless MIMO receiver.

25. The receiver of claim 24 wherein the receiver receives multiple data streams signals from a transmitter with multiple antennas.

26. The receiver of claim 14 wherein:

the detector detects data symbols in the received signal using direct matrix inversion type linear MIMO detection, and

the metric calculator computes the bit metrics by determining distances between the estimated data symbols and constellation points.