LINK ADAPTATION BASED ON GENERIC CINR MEASUREMENT ACCORDING TO LOG-LIKELIHOOD RATIO DISTRIBUTION

• US 20090086855A1
• Filed: 09/19/2008
• Published: 04/02/2009
• Est. Priority Date: 09/28/2007
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Jin, Hang, Hedayat, Ahmadreza, Lou, Hanqing
• Granted Patent: US 8,077,809 B2
• Time in Patent Office: Days
• US Class Current: 375/341
• CPC Class Codes: H04L 1/0003 by switching between different modulation schemes
• CPC Class Codes: H04L 1/0009 by adapting the channel coding H04L1/1812 takes precedence
• CPC Class Codes: H04L 1/0026 Transmission of channel quality indication
• CPC Class Codes: H04L 1/0618 Space-time coding
• CPC Class Codes: H04L 1/20 using signal quality detector

Abstract

Techniques are provided to compute the carrier to interference-plus-noise ratio (CINR) in a wireless communication system using log-likelihood ratio (LLR) data generated from a received transmission. The LLR data are collected as they are sent from a detector to a forward error correction (FEC) decoder in a wireless communications device. In one embodiment, decision-aided LLR based CINR is computed using the decoded bits output from the FEC decoder as feedback. In another embodiment, blind LLR based CINR is computed without feedback. The CINR may be used to adjust a modulation and/or coding parameters associated with wireless communication between wireless communication devices.

Claims

1. A method comprising:

receiving at a first device a wireless transmission transmitted from a second device;

generating log-likelihood ratio data from the received wireless transmission;

computing a carrier to interference plus noise ratio (CINR) based on the log-likelihood ratio data; and

adjusting a modulation and/or coding parameter associated with the wireless transmission based on the CINR.

2. The method of claim 1, and further comprising computing adjustment data for the modulation and/or coding parameter at the first device and transmitting the adjustment data to the second device.

3. The method of claim 1, and further comprising transmitting the CINR from the first device to the second device, wherein the second device computes an adjustment for the modulation and/or coding parameter based on the CINR.

4. The method of claim 1, wherein generating comprises generating the log-likelihood ratio data at a detector in the first device, and outputting the log-likelihood ratio data from the detector to an input of a decoder in the first device.

5. The method of claim 4, wherein computing the CINR is based on decisions made by the decoder using the log-likelihood ratio data.

6. The method of claim 5, wherein computing the CINR comprises computing:

$\mathrm{CINR}=\frac{1}{N}<br><br>\underset{n=1}{\overset{N}{\sum <br><br>}}<br><br>\frac{{\mathrm{mean}<br><br>\left({\mathrm{LLR}}_n\right)}^2}{{\mathrm{std}<br><br>\left({\mathrm{LLR}}_n\right)}^2}$

where N is the number of addressing bits corresponding to a constellation and/or modulation symbol used to transmit the wireless transmission, and LLR_n is a subset of log-likelihood ratio data corresponding to the addressing bit n.

7. The method of claim 6, wherein receiving the wireless transmission comprises receiving a plurality of signal streams simultaneously transmitted from the second device to the first device using multiple-input multiple-output techniques, each signal stream comprising a stream of symbols, and wherein computing comprises computing the CINR such that the number of addressing bits N is equal to the number of bits within a symbol multiplied by the number of signal streams.

8. The method of claim 6, wherein computing further comprises computing the mean and standard deviation over an entire set of available log-likelihood ratio data.

9. The method of claim 6, wherein receiving the wireless transmission comprises receiving a plurality of signal streams simultaneously transmitted from the second device to the first device using multiple-input multiple-output techniques, each signal stream comprising a stream of symbols transmitted according to a different constellation/modulation scheme, and wherein computing comprises computing the CINR such that the number of addressing bits N is equal to a sum of the number of bits within each symbol over the plurality of signal streams.

10. The method of claim 1, wherein computing the CINR comprises computing:

$\mathrm{CINR}=\frac{1}{N}<br><br>\underset{n=1}{\overset{N}{\sum <br><br>}}<br><br>\frac{{\mathrm{mean}<br><br>\left(\mathrm{abs}<br><br>\left({\mathrm{LLR}}_n\right)\right)}^2}{{\mathrm{std}<br><br>\left(\mathrm{abs}<br><br>\left({\mathrm{LLR}}_n\right)\right)}^2}$

where N is the number of addressing bits corresponding to a constellation and/or modulation scheme used to transmit the wireless transmission, and LLR_n is the subset of log-likelihood ratio data that correspond to the addressing bit n.

11. The method of claim 10, wherein receiving the wireless transmission comprises receiving a plurality of signal streams simultaneously transmitted from the second device to the first device using multiple-input multiple-output techniques, each signal stream comprising a stream of symbols, and wherein computing comprises computing the CINR such that the number of addressing bits N is equal to the number of bits within a symbol multiplied by the number of signal streams.

12. The method of claim 10, wherein computing further comprises computing the mean and standard deviation over an entire set of available log-likelihood ratio data.

13. The method of claim 10, wherein receiving the wireless transmission comprises receiving a plurality of signal streams simultaneously transmitted from the second device to the first device using multiple-input multiple-output techniques, each signal stream comprising a stream of symbols transmitting according to a different constellation/modulation scheme, and wherein computing comprises computing the CINR such that the number of addressing bits N is equal to a sum of the number of bits within each symbol over the plurality of signal streams.

14. The method of claim 1, wherein computing the CINR is on a bit-level basis.

15. The method of claim 1, wherein computing the CINR is on a symbol-level basis.

16. An apparatus comprising:

a receiver that receives a wireless transmission transmitted from a second communication apparatus;

a detector coupled to the receiver and configured to generate log-likelihood ratio data from the received wireless transmission; and

a controller coupled to the detector and configured to;

compute a carrier to interference plus noise ratio (CINR) based on the log-likelihood ratio data; and

generate adjustment data for a modulation and/or coding parameter associated with the wireless transmission based on the CINR.

17. The apparatus of claim 16, and further comprising a transmitter configured to transmit the adjustment data for the modulation and/or coding parameter, and/or to transmit the CINR to the second communication apparatus.

18. The apparatus of claim 16, further comprising a decoder coupled to the detector, wherein the log-likelihood ratio data is output from the detector to an input of the decoder.

19. The apparatus of claim 18, wherein the controller is further configured to compute the CINR based on decisions made by the decoder using the log-likelihood data.

20. The apparatus of claim 19, wherein the controller is further configured to compute the CINR as:

$\mathrm{CINR}=\frac{1}{N}<br><br>\underset{n=1}{\overset{N}{\sum <br><br>}}<br><br>\frac{{\mathrm{mean}<br><br>\left({\mathrm{LLR}}_n\right)}^2}{{\mathrm{std}<br><br>\left({\mathrm{LLR}}_n\right)}^2}$

where N is the number of addressing bits corresponding to a constellation and/or modulation scheme used to transmit the wireless transmission, and LLR_n is the subset of log-likelihood ratio data that correspond to the addressing bit n.

21. The apparatus of claim 16, wherein the controller is further configured to compute the CINR as:

$\mathrm{CINR}=\frac{1}{N}<br><br>\underset{n=1}{\overset{N}{\sum <br><br>}}<br><br>\frac{{\mathrm{mean}<br><br>\left(\mathrm{abs}<br><br>\left({\mathrm{LLR}}_n\right)\right)}^2}{{\mathrm{std}<br><br>\left(\mathrm{abs}<br><br>\left({\mathrm{LLR}}_n\right)\right)}^2}$

where N is the number of addressing bits corresponding to a constellation and/or modulation scheme used to transmit the wireless transmission, and LLR_n is the subset of log-likelihood ratio data that correspond to the addressing bit n.

22. Logic encoded in one or more tangible media for execution and when executed operable to:

generate log-likelihood ratio data associated with reception of a wireless transmission at a first device that is transmitted from a second device;

compute a carrier to interference plus noise ratio (CINR) based on the log-likelihood ratio data; and

adjust a modulation and/or coding parameter associated with the wireless transmission based on the CINR.

23. The logic of claim 22, and further comprising logic to compute adjustment data for the modulation and/or coding parameter at the first device for transmission to the second device.

24. The logic of claim 22, wherein the logic that generates the log-likelihood ratio data is implemented in a detector in the first device, and wherein the log-likelihood ratio data is output from the detector to an input of a decoder in the first device.

25. The logic of claim 24, wherein the logic that computes the CINR is based on decisions made by the decoder using the log-likelihood ratio data.

26. The logic of claim 25, wherein the logic that computes the CINR comprises logic that computes:

$\mathrm{CINR}=\frac{1}{N}<br><br>\underset{n=1}{\overset{N}{\sum <br><br>}}<br><br>\frac{{\mathrm{mean}<br><br>\left({\mathrm{LLR}}_n\right)}^2}{{\mathrm{std}<br><br>\left({\mathrm{LLR}}_n\right)}^2}$

where N is the number of addressing bits corresponding to a constellation and/or modulation scheme used to transmit the wireless transmission, and LLR_n is the subset of log-likelihood ratio data that correspond to the addressing bit n.

27. The logic of claim 22, wherein the logic that computes the CINR comprises logic that computes:

$\mathrm{CINR}=\frac{1}{N}<br><br>\underset{n=1}{\overset{N}{\sum <br><br>}}<br><br>\frac{{\mathrm{mean}<br><br>\left(\mathrm{abs}<br><br>\left({\mathrm{LLR}}_n\right)\right)}^2}{{\mathrm{std}<br><br>\left(\mathrm{abs}<br><br>\left({\mathrm{LLR}}_n\right)\right)}^2}$

where N is the number of addressing bits corresponding to a constellation and/or modulation scheme used to transmit the wireless transmission, and LLR_n is the subset of log-likelihood ratio data that correspond to the addressing bit n.