System and method for detecting spatially multiplexed and space time block coded multiple-input multiple-output (MIMO) signals

• US 10,411,836 B2
• Filed: 03/17/2017
• Issued: 09/10/2019
• Est. Priority Date: 03/17/2017
• Status: Active Grant

• Current Assignee: Uurmi Systems Pvt., Ltd.
• Original Assignee: Uurmi Systems Pvt., Ltd.
• Inventors: Chavali, Nanda Kishore, Bade, Dharma Teja, Sheela, Mounika, Kilari, Anusha, Kuchi, Kiran Kumar
• Primary Examiner(s): Zhao, Wei
• Application Number:
  US15/462,550
• Publication Number:
  US 20180270019A1
• Time in Patent Office: 907 Days
• CPC Class Codes: H04B 7/0417 Feedback systems
• CPC Class Codes: H04B 7/0456 Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
• CPC Class Codes: H04L 1/0054 Maximum-likelihood or sequential decoding, e.g. Viterbi, Fano, ZJ algorithms
• CPC Class Codes: H04L 1/0643 block codes

Abstract

A system and method for detecting Spatially Multiplexed (SM), Space Time Block Coded (STBC), or Hybrid Space Time Block Coded-Spatially Multiplexed (STBC-SM) Multiple-Input Multiple-Output (MIMO) signals is disclosed. QR decomposition of the MIMO signal is performed. A constellation of symbols present in the MIMO signals is partitioned into subsets of symbols, using a set partitioning technique. A-posteriori probability (APP) of each branch is determined. Log Likelihood Ratios (LLRs) corresponding to the transmitted bits are determined using the a-posteriori probabilities. Successively, transmitted bits are determined by providing the LLRs corresponding to the transmitted bits, to a Viterbi decoder.

Claims

1. A method for detecting Spatially Multiplexed (SM) Multiple-Input Multiple-Output (MIMO) signals, the method comprising:

performing, by a processor, QR decomposition of a Multiple-Input Multiple-Output (MIMO) channel matrix (H) of Spatially Multiplexed (SM) MIMO signals into a matrix Q and a matrix R, wherein the matrix Q is orthonormal and the matrix R is upper triangular in nature;

partitioning, by the processor, a constellation of symbols present in the Spatially Multiplexed (SM) MIMO signals into subsets of symbols, using a set partitioning technique, wherein branches are developed upon occurrence of transitions between nodes at multiple stages, in a subset state tree, and wherein the symbols present in each of the subsets are represented as the branches;

determining, by the processor, a-posteriori probability (APP) of each branch using a forward metric (α

_k), a backward metric (β

_k), and a modified branch metric, wherein the modified branch metric uses a path history vector (p_k) determined as p_k=[{circumflex over (x)}<sub>n−

k−

1</sub>p<sub>k−

1</sub>], and wherein the path history vector (p_k) uses equalized soft symbols of a previous state {circumflex over (x)}<sub>n−

k−

1</sub>;

determining, by the processor, a-posteriori bit level probabilities for bit-0 and bit-1, using the APP of each branch;

determining, by the processor, Log Likelihood Ratios (LLRs) corresponding to transmitted bits using the a-posteriori bit level probabilities; and

determining, by the processor, transmitted bits by providing the LLRs corresponding to the transmitted bits, to a Viterbi decoder, thereby detecting the Spatially Multiplexed (SM) Multiple-Input Multiple-Output (MIMO) signals.

2. The method of claim 1, wherein the constellation of symbols is a square constellation with gray mapping.

3. The method of claim 1, wherein the modified branch metric is determined as:

4. The method of claim 1, wherein determining the path history vector (p_k) comprises determining equalized soft symbols ({circumflex over (x)}_i) using received data symbols ({circumflex over (z)}_i) and corresponding row vector of the matrix R.

5. The method of claim 4, wherein the set partitioning technique uses a set partitioning vector defined as [M,1,1,1 . . . 1(m−

1)times] and the matrix R is of order m×

m, and wherein M is a size of the constellation.

6. A system for detecting Spatially Multiplexed (SM) Multiple-Input Multiple-Output (MIMO) signals, the system comprising:

a processor to;

perform QR decomposition of a Multiple-Input Multiple-Output (MIMO) channel matrix (H) of the Spatially Multiplexed (SM) MIMO signals into a matrix Q and a matrix R, wherein the matrix Q is orthonormal and the matrix R is upper triangular in nature;

partition a constellation of symbols present in the Spatially Multiplexed (SM) MIMO signals into subsets of symbols using a set partitioning technique, wherein branches are developed upon transition occurrence between nodes at multiple stages, in a subset state tree, and wherein the symbols present in each of the subsets are represented as the branches;

determine a-posteriori probability (APP) of each branch using a forward metric (α

_k), a backward metric (β

_k), and a modified branch metric, wherein the branch metric uses a path history vector (p_k) determined as p_k=[{circumflex over (x)}<sub>n−

k−

1</sub>p<sub>k−

1</sub>], and wherein the path history vector (p_k) uses equalized soft symbols of a previous state {circumflex over (x)}<sub>n−

k−

1</sub>;

determine a-posteriori bit level probabilities for bit-0 and bit-1, using the APP of each branch;

determine Log Likelihood Ratios (LLRs) corresponding to transmitted bits using the a-posteriori bit level probabilities; and

determine transmitted bits by providing the LLRs corresponding to the transmitted bits, to a Viterbi decoder, thereby detecting the Spatially Multiplexed (SM) Multiple-Input Multiple-Output (MIMO) signals.

7. The system of claim 6, wherein the constellation of symbols is a square constellation with gray mapping.

8. The system of claim 6, wherein the modified branch metric is determined as:

9. The system of claim 6, wherein determining the path history vector (p_k) comprises determining equalized soft symbols ({circumflex over (x)}_i) using received data symbols ({circumflex over (z)}_i) and corresponding row vector of the matrix R.

10. The system of claim 9, wherein the set partitioning technique uses a set partitioning vector defined as [M,1,1,1 . . . 1(m−

1)times] and the matrix R is of order m×

m, and wherein M is a size of the constellation.

11. A method of detecting Space Time Block Coded (STBC) Multiple-Input Multiple-Output (MIMO) signals or Hybrid Space Time Block Coded-Spatially Multiplexed (STBC-SM) Multiple-Input Multiple-Output (MIMO) signals, the method comprising:

determining, by a processor, an effective Multiple-Input Multiple-Output (MIMO) channel matrix (H) of MIMO signals, by rearranging signals received at consecutive time instances and rearranging corresponding channel coefficients of the signals;

performing, by the processor, QR decomposition of the effective MIMO channel matrix (H) into a matrix Q and a matrix R, wherein the matrix Q is orthonormal and the matrix R is upper triangular in nature;

partitioning, by the processor, a constellation of symbols present in the MIMO signals into subsets of symbols, using a set partitioning technique, wherein branches are developed upon occurrence of transitions between nodes at multiple stages, in a subset state tree, and wherein the symbols present in each of the subsets are represented as the branches;

determining, by the processor, a-posteriori probability (APP) of each branch using a forward metric (α

_k), a backward metric (β

_k), and a modified branch metric, wherein the branch metric uses a path history vector (p_k) determined as p_k=[{circumflex over (x)}<sub>n−

k−

1</sub>p<sub>k−

1</sub>], and wherein the path history vector (p_k) uses equalized soft symbols of a previous state {circumflex over (x)}<sub>n−

k−

1</sub>;

determining, by the processor, a-posteriori bit level probabilities for bit-0 and bit-1, using the APP of each branch;

determining, by the processor, Log Likelihood Ratios (LLRs) corresponding to transmitted bits using the a-posteriori bit level probabilities; and

determining, by the processor, transmitted bits by providing the LLRs corresponding to the transmitted bits, to a Viterbi decoder, thereby detecting the Multiple-Input Multiple-Output (MIMO) signals.

12. The method of claim 11, wherein the Multiple-Input Multiple-Output (MIMO) signals are Space Time Block Coded (STBC) signals.

13. The method of claim 11, wherein the Multiple-Input Multiple-Output (MIMO) signals are Hybrid Space Time Block Coded-Spatially Multiplexed (STBC-SM) signals.

14. The method of claim 11, wherein the constellation of symbols is a square constellation with gray mapping.

15. The method of claim 11, wherein the modified branch metric is determined as:

16. The method of claim 11, wherein determining the path history vector (p_k) comprises determining equalized soft symbols ({circumflex over (x)}_i) using received data symbols ({circumflex over (z)}_i) and corresponding row vector of the matrix R, and wherein determining the equalized soft symbols ({circumflex over (x)}_i) comprises determining an effective noise (w_i) for fourth stage due to a soft symbol feedback.

17. The method of claim 16, wherein the set partitioning technique uses a set partitioning vector defined as [M,M,1,1 . . . 1(m−

2) times] for the matrix R of order m×

m.

18. A system for detecting Space Time Block Coded (STBC) Multiple-Input Multiple-Output (MIMO) signals or Hybrid Space Time Block Coded-Spatially Multiplexed (STBC-SM) Multiple-Input Multiple-Output (MIMO) signals, the system comprising:

a processor to;

determine an effective Multiple-Input Multiple-Output (MIMO) channel matrix (H) of MIMO signals by rearranging signals received at consecutive time instances and rearranging corresponding channel coefficients of the signals;

perform QR decomposition of the effective MIMO channel matrix (H) into a matrix Q and a matrix R, wherein the matrix Q is orthonormal and the matrix R is upper triangular in nature;

partition a constellation of symbols present in the MIMO signals into subsets of symbols using a set partitioning technique, wherein branches are developed upon occurrence of transitions between nodes at multiple stages, in a subset state tree, and wherein the symbols present in each of the subsets are represented as the branches;

determine a-posteriori probability (APP) of each branch using a forward metric (α

_k), a backward metric (β

_k), and a modified branch metric, wherein the branch metric uses a path history vector (p_k) determined as p_k=[{circumflex over (x)}<sub>n−

k−

1</sub>p<sub>k−

1</sub>], and wherein the path history vector (p_k) uses equalized soft symbols of a previous state;

determine a-posteriori bit level probabilities for bit-0 and bit-1, using the APP of each branch;

determine Log Likelihood Ratios (LLRs) corresponding to transmitted bits using the a-posteriori bit level probabilities; and

determine transmitted bits by providing the LLRs corresponding to the transmitted bits, to a Viterbi decoder, thereby detecting the Multiple-Input Multiple-Output (MIMO) signals.

19. The system of claim 18, wherein the Multiple-Input Multiple-Output (MIMO) signals are Space Time Block Coded (STBC) signals.

20. The system of claim 18, wherein the Multiple-Input Multiple-Output (MIMO) signals are Hybrid Space Time Block Coded-Spatially Multiplexed (STBC-SM) signals.

21. The system of claim 18, wherein the constellation of symbols is a square constellation with gray mapping.

22. The system of claim 18, wherein the modified branch metric is determined as:

23. The system of claim 18, wherein determining the path history vector (p_k) comprises determining equalized soft symbols ({circumflex over (x)}_i) using received data symbols ({circumflex over (z)}_i) and corresponding row vector of the matrix R, and wherein determining the equalized soft symbols ({circumflex over (x)}_i) comprises determining an effective noise (w_i) for fourth stage due to a soft symbol feedback.

24. The system of claim 23, wherein the set partitioning technique uses a set partitioning vector defined as [M, M,1,1 . . . 1(m−

2) times] for the matrix R of order m×

m.