Reordering of a beamforming matrix based on encoding

• US 9,281,885 B2
• Filed: 09/03/2014
• Issued: 03/08/2016
• Est. Priority Date: 04/07/2014
• Status: Active Grant

• Current Assignee: Nordic Semiconductor ASA
• Original Assignee: Imagination Technologies, LLC
• Inventors: Raju, Meesaraganda Surendra, Chari, Sujai
• Primary Examiner(s): Bolourchi, Nader
• Application Number:
  US14/476,550
• Publication Number:
  US 20150288437A1
• Time in Patent Office: 552 Days
• Field of Search: 375/219
• US Class Current: 1/1
• CPC Class Codes: H03M 13/1102 Codes on graphs and decoding on graphs, e.g. low-density parity check [LDPC] codes
• CPC Class Codes: H04B 7/0434 using multiple eigenmodes
• CPC Class Codes: H04B 7/0456 Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
• CPC Class Codes: H04B 7/0486 taking channel rank into account
• CPC Class Codes: H04B 7/0617 for beam forming
• CPC Class Codes: H04B 7/0634 Antenna weights or vector/matrix coefficients
• 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 1/0059 Convolutional codes
• CPC Class Codes: H04L 1/0071 Use of interleaving interleaving per se H03M13/27

Abstract

Apparatuses, methods and systems for beamforming based on encoding are disclosed. One embodiment of a method includes generating a beamforming matrix, including obtaining a channel matrix of a multiple-input, multiple-output (MIMO) channel between multiple transmitter antennas and at least one receiver antenna, determining an initial beamforming matrix based on a singular value decomposition of the channel matrix, and generating, by a transceiver, a final beamforming matrix comprising reordering columns of the initial beamforming matrix for at least one sub-carrier of a multi-carrier signal, wherein the reordering of the columns is based on knowledge of encoding of a transmit signal.

Claims

1. A method of beamforming, comprising:

generating a beamforming matrix, comprising;

obtaining a channel matrix of a multiple-input, multiple-output (MIMO) channel between multiple transmitter antennas and at least one receiver antenna;

determining an initial beamforming matrix based on a singular value decomposition of the channel matrix; and

generating, by a transceiver, a final beamforming matrix comprising reordering columns of the initial beamforming matrix for at least one sub-carrier of a multi-carrier signal, wherein the reordering of the columns is based on knowledge of encoding of a transmit signal.

2. The method of claim 1, further comprising:

identifying a set of column reordering permutations;

partitioning every block of n input bit predictive log likely ratios (LLRs) to a low-density parity-check (LDPC) decoder into a low confidence subset or a high confidence subset for each of the set of column reordering permutations, wherein the LDPC decoder is decoding based on knowledge of LDPC encoding of the transmit signal.

3. The method of claim 2, further comprising:

counting a number of elements within the low confidence subset for each of the set of column reordering permutations; and

selecting a reordering permutation from the set of column reordering permutations based on the number of elements within the low confidence subset of each of the column reordering permutations.

4. The method of claim 2, further comprising:

computing a mean reliability of the low confidence subset for each of the column reordering permutations; and

selecting a reordering permutation from the set of column reordering permutations based on the mean reliability of the low confidence subset of each of the column reordering permutations.

5. The method of claim 2, further comprising:

computing number of elements of the low confidence subset having a reliability lower than a poor reliability threshold for each of the column reordering permutations; and

selecting a reordering permutation from the set of column reordering permutations based on the computed number of elements of the low confidence subset having reliability lower than the poor reliability threshold, for each of the set of column reordering permutations.

6. The method of claim 1, wherein the encoding of the transmit signal includes LDPC encoding, and further comprising:

specifying a parity check matrix based on the LDPC encoding;

generating a set of parity check bits, comprising multiplying a block of n input bits by the parity check matrix;

wherein the input bits and any information associated with the input bits are denoted as a variable nodes; and

wherein the parity check bits and any information associated with the parity check bits are denoted as check nodes.

7. The method of claim 6, further comprising:

identifying a plurality of column reordering permutations;

selecting a one of the plurality of column reordering permutations based on a number of check nodes connected to a worst variable node having a reliability below a reliability threshold.

8. The method of claim 6, further comprising:

identifying a plurality of column reordering permutations;

selecting a one of the plurality of column reordering permutations based on a percent of check nodes connected to a worst variable node having a reliability below a reliability threshold.

9. The method of claim 6, further comprising:

identifying a plurality of column reordering permutations;

selecting a one of the plurality of column reordering permutations based on an average reliability of a worst variable node connected to each check node below a threshold.

10. The method of claim 1, wherein reordering columns of the initial beamforming matrix is further based on a signal characteristic, and wherein the columns of the initial beamforming matrix are re-ordered upon changes of the signal characteristic.

11. The method of claim 1, further comprising:

constructing a plurality of K demapped blocks of confidence levels based on singular values per subcarrier of a plurality spatial streams of the MIMO channel, wherein the confidence levels comprise functions of SNRs (signal to noise ratios), wherein each of the plurality of K demapped blocks corresponds to a one of K encoded data streams of the multiple antenna transmitter;

computing an average confidence level for each of the plurality of K demapped blocks; and

identifying a lowest average confidence level of the plurality from the computed average confidence levels;

wherein the reordering of the columns of the initial beamforming matrix of at least one of the subcarriers increases the lowest average confidence level;

wherein K is an integer greater the 1.

12. The method of claim 1, further comprising selecting the reordering of the columns to reduce decoding errors at a receiver of the plurality of multi-carrier signals as compared to decoding errors at the receiver utilizing the initial beamforming matrix.

13. The method of claim 1, wherein a selected initial beamforming technique includes singular value decomposition (SVD), wherein the initial beamforming matrix includes at least one of Ascending Value SVD (AVSVD) that includes diagonal singular values in an increasing order, or Descending Value SVD (DVSVD) that includes diagonal singular values in a decreasing order.

14. The method of claim 13, wherein if the initial beamforming matrix comprises AVSVD, then the final beamforming matrix comprises DVSVD, and if the initial beamforming matrix comprises DVSVD, then the final beamforming matrix comprises AVSVD.

15. The method of claim 1, wherein the final beamforming matrix is determined at the transceiver and transmitted back to a transmitter associated with the multiple transmitter antennas.

16. The method of claim 1, wherein the final beamforming matrix is generated at the transceiver and the transceiver includes the multiple transmitter antennas.

17. A method of beamforming, comprising:

generating a beamforming matrix, comprising;

obtaining a channel matrix of a multiple-input, multiple-output (MIMO) channel between multiple transmitter antennas and at least one receiver antenna;

determining an initial beamforming matrix based on a singular value decomposition of the channel matrix; and

generating, by a transceiver, a final beamforming matrix comprising reordering columns of the initial beamforming matrix for at least one sub-carrier of a multi-carrier signal based on a signal characteristic, wherein the reordering of the columns is based on knowledge of encoding of a transmit signal.

18. An apparatus, comprising:

a plurality of receive chains;

a processor, wherein the processor is operative to;

obtain a channel matrix of a multiple-input, multiple-output (MIMO) channel between multiple transmitter antennas and at least one receiver antenna;

determine an initial beamforming matrix based on a singular value decomposition of the channel matrix; and

generate, by a transceiver, a final beamforming matrix comprising reordering columns of the initial beamforming matrix for at least one sub-carrier of a multi-carrier signal, wherein the reordering of the columns is based on knowledge of encoding of a transmit signal.

19. The apparatus of claim 18, wherein the processor is operative to:

facilitate processing a plurality of multi-carrier signals using the final beamforming matrix; and

wherein

the apparatus is operative to

transmit the processed plurality of multi-carrier signals through a plurality of antennas of the multiple transmitter antennas.

20. The apparatus of claim 19, wherein the apparatus is operative to provide the final beamforming matrix to a second transceiver that includes the plurality of antennas of the multiple transmitter antennas.

21. The apparatus of claim 18, wherein the processor is further operative to:

identify a plurality of column reordering permutations;

partition every block of n input bit predictive LLRs to an LDPC decoder into a low confidence subset or a high confidence subset for each of the reordering permutations, wherein the LDPC decoder is based on knowledge of LDPC encoding of the transmit signal.

22. The apparatus of claim 21, wherein the processor is further operative to:

count a number of elements within the low confidence subset for each of the column reordering permutations; and

select a reordering permutation from the plurality of column reordering permutations based on the number of elements within the low confidence subset of each of the column reordering permutations.

23. The apparatus of claim 21, wherein the processor is further operative to:

compute a mean reliability of the low confidence subset for each of the column reordering permutations; and

select a reordering permutation from the plurality of column reordering permutations based on the mean reliability of the low confidence subset of each of the column reordering permutations.

24. The apparatus of claim 21, wherein the processor is further operative to:

compute number of elements of the low confidence subset having a reliability lower than a poor reliability threshold for each of the column reordering permutations; and

select a reordering permutation from the plurality of column reordering permutations based on the computed number of elements of the low confidence subset having reliability lower than the poor reliability threshold, for each of the column reordering permutations.

25. The apparatus of claim 18, wherein the encoding of the transmit signal includes LDPC encoding, and wherein the processor is further operative to:

specify a parity check matrix based on the LDPC encoding;

generate a set of parity check bits, comprising multiplying a block of n input bits by the parity check matrix;

wherein the input bits and any information associated with the input bits are denoted as a variable nodes; and

wherein the parity check bits and any information associated with the parity check bits are denoted as check nodes.

26. The apparatus of claim 25, wherein the processor is further operative to:

identify a plurality of column reordering permutations;

select a one of the plurality of column reordering permutations based on a number of check nodes connected to a worst variable node having a reliability below a reliability threshold, wherein the worst variable node.

27. The apparatus of claim 25, wherein the processor is further operative to:

identify a plurality of column reordering permutations;

select a one of the plurality of column reordering permutations based on a percent of check nodes connected to a worst variable node having a reliability below a reliability threshold, wherein the worst variable node.

28. The apparatus of claim 25, wherein the processor is further operative to:

identify a plurality of column reordering permutations;

select a one of the plurality of column reordering permutations based on an average reliability of a worst variable node connected to each check node below a threshold, wherein the worst variable node.

29. The apparatus of claim 18, wherein the processor further is operative to:

construct a plurality of K demapped blocks of confidence levels based on singular values per subcarrier of a plurality spatial streams of the MIMO channel, wherein the confidence levels comprise functions of SNRs (signal to noise ratios), wherein each of the plurality of K demapped blocks corresponds to a one of K encoded data blocks of the multiple antenna transmitter;

compute an average confidence level for each of the plurality of K demapped blocks; and

identify a lowest average confidence level of the plurality from the computed average confidence levels;

wherein the reordering of the columns of the initial beamforming matrix of at least one of the subcarriers increases the lowest average confidence level

wherein K is an integer greater than 1.

30. The apparatus of claim 18, wherein the processor further is operative to adjust the reordering of columns, wherein the adjustment ensures that a maximum number of subcarriers across any spatial stream with a singular value less than a threshold is minimized.

31. The apparatus of claim 18, wherein the processor further is operative to select the reordering of the columns to reduce decoding errors at a receiver of the plurality of multi-carrier signals as compared to decoding errors at the receiver utilizing the initial beamforming matrix.