Skip to main content
Log in

Block-Circulant Inverse Orthogonal Jacket Matrices and Its Applications to the Kronecker MIMO Channel

  • Published:
Circuits, Systems, and Signal Processing Aims and scope Submit manuscript

Abstract

This paper presents a note on the block-circulant generalized Hadamard matrices, which is called inverse orthogonal Jacket matrices of orders \(N=2p, 4p, 4^kp, np\), where k is a positive integer for the Kronecker MIMO channel. The class of block Toeplitz circulant Jacket matrices not only have many properties of the circulant Hadamard conjecture but also have the construction of block-circulant, which can be easily applied to fast algorithms for decomposition. The matrix decomposition is with the form of the products of block identity \(I_2\) matrix and block Hadamard \(H_2\) matrix. In this paper, a block fading channel model is used, where the channel is constant during a transmission block and varies independently between transmission blocks. The proposed block-circulant Jacket matrices can also achieve about 3db gain in high SNR regime with MIMO channel. This algorithm for realizing these transforms can be applied to the Kronecker MIMO channel.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. N. Ahmed, K.R. Rao, Orthogonal Transforms for Digital Signal Processing (Springer, New York, 1975)

    Book  MATH  Google Scholar 

  2. S. Bouguezel, M.O. Ahmad, M.N.S. Swamy, An efficient algorithm for the computation of the reverse Jacket transform, in 2006 IEEE International Symposium on Circuits and Systems, ISCAS 2006, Proceedings, 21–24 May 2006, Island of Kos, pp. 1–4. (2008). https://doi.org/10.1109/ISCAS.2006.1692780

  3. S. Bouguezel, M.O. Ahmad, M.N.S. Swamy, A new class of reciprocal-orthogonal parametric transforms. IEEE Trans. Circuits Syst. I Reg. Pap. 56(4), 795–804 (2009). https://doi.org/10.1109/TCSI.2008.2002923

    Article  MathSciNet  Google Scholar 

  4. Z. Chen, M.H. Lee, G. Zeng, Fast cocyclic Jacket transform. IEEE Trans. Signal Process. 56(5), 2143–2148 (2008). https://doi.org/10.1109/TSP.2007.912895

    Article  MathSciNet  MATH  Google Scholar 

  5. Y.S. Cho, J. Kim, W.Y. Yang, C.G. Kang, MIMO-OFDM Wireless Communications with MATLAB (Wiley-IEEE Press, New York, 2010)

    Book  Google Scholar 

  6. J.J. Ding, S.C. Pei, P.H. Wu, Jacket Haar transform, in ISCAS (Rio de Janeiro, Brazil, 2011), pp. 1520–1523. https://doi.org/10.1109/ISCAS.2011.5937864

  7. J.J. Ding, S.C. Pei, P.H. Wu, Arbitrary-length Walsh-Jacket transforms, in APSIPA Annual Summit and Conference (Xi’an, China, 2011). https://doi.org/10.1007/978-3-319-27122-4_23

  8. C.P. Fan, J.F. Yang, Fast center weighted Hadamard transform algorithms. IEEE Trans. Circuits Syst.-II Analog Digit. Signal Process. 45(3), 429–432 (1998). https://doi.org/10.1109/82.664256

    Article  Google Scholar 

  9. L. Fan, R. Zhao, F. Gong, N. Yang, G.K. Karagiannidis, Secure multiple amplify-and-forward relaying over correlated fading channels. IEEE Trans. Commun. 65(7), 2811–2820 (2017). https://doi.org/10.1109/TCOMM.2017.2691712

    Article  Google Scholar 

  10. A.V. Geramita, J. Seberry, Orthogonal Designs: Quadratic forms and Hadamard Matrices (Marcel Dekker Inc, New York, 1979)

    MATH  Google Scholar 

  11. G.H. Golub, Charles F. van Van Loan, Matrix Computations, 3rd edn. (Johns Hopkins University Press, Baltimore, 1996)

    MATH  Google Scholar 

  12. R.M. Gray, Toeplitz and circulant matrices: a review. Found. Trends Commun. Inf. Theory 2(3), 155–239 (2006). https://doi.org/10.1561/0100000006

    Article  MATH  Google Scholar 

  13. J. Gutierrez-Gutierrez, P.M. Crespo, Block Toeplitz matrices: asymptotic results and applications. Found. Trends Commun. Inf. Theory 8(3), 179–257 (2011). https://doi.org/10.1561/0100000066

    Article  MATH  Google Scholar 

  14. J. Gutierrez-Gutierrez, P.M. Crespo, Asymptotically equivalent sequences of matrices and Hermitian block Toeplitz matrices with continuous symbols: applications to MIMO systems. IEEE Trans. Inf. Theory 54(12), 5671–5680 (2008). https://doi.org/10.1109/TIT.2008.2006401

    Article  MathSciNet  MATH  Google Scholar 

  15. R.A. Horn, C.R. Johnson, Topics in Matrix Analysis (Cambridge University, Cambridge, 1991)

    Book  MATH  Google Scholar 

  16. K.J. Horadam, Hadamard Matrices and Their Applications (Princeton University Press, Princeton, 2007)

    MATH  Google Scholar 

  17. H. Huh, A.M. Tulino, G. Caire, Network MIMO with linear zero-forcing beamforming: large system analysis, impact of channel estimation and reduced-complexity scheduling. IEEE Trans. Inf. Theory 58(5), 2911–2934 (2012). https://doi.org/10.1109/TIT.2011.2178230

    Article  MathSciNet  MATH  Google Scholar 

  18. X.-Q. Jiang, M. Wen, J. Li, W. Duan, Distributed generalized spatial modulation based on Chinese remainder theorem. IEEE Commun. Lett. 21(7), 1501–1504 (2017). https://doi.org/10.1109/LCOMM.2017.2688368

    Article  Google Scholar 

  19. X.-Q. Jiang, M. Wen, H. Hai, J. Li, S. Kim, Secrecy-enhancing scheme for spatial modulation. IEEE Commun. Lett. 22(3), 550–553 (2018). https://doi.org/10.1109/LCOMM.2017.2783955

    Article  Google Scholar 

  20. M.H. Lee, Jacket Matrices: Constructions and Its Applications for Fast Cooperative Wireless Signal Processing (LAP LAMBERT Publishing, Saarbrücken, 2012)

    Google Scholar 

  21. M.H. Lee, The center weighted Hadamard transform. IEEE Trans. Circuits Syst. Analog Digit. Signal Process 36(9), 1247–1249 (1989). https://doi.org/10.1109/31.34673

    Article  Google Scholar 

  22. M.H. Lee, A new reverse Jacket transform and its fast algorithm. IEEE Trans. Circuits Syst.-II Analog Digit. Signal Process 47(1), 39–47 (2000). https://doi.org/10.1109/82.818893

    Article  MATH  Google Scholar 

  23. M.H. Lee, H. Hai, X.-D. Zhang, MIMO Communication Method and System using the Block Circulant Jacket Matrix, USA Patent. no. 9,356,671, 05/31/2016

  24. M.H. Lee, J. Hou, Fast block inverse Jacket transform. IEEE Signal Process. Lett. 13(8), 461–464 (2006). https://doi.org/10.1109/LSP.2006.873660

    Article  Google Scholar 

  25. M.H. Lee, M. Kaveh, Fast Hadamard transform based on a simple matrix factorization. IEEE Trans. Acoust. Speech Signal Process ASSP–34(6), 1666–1667 (1986). https://doi.org/10.1109/TASSP.1986.1164972

    Article  Google Scholar 

  26. M.H. Lee, M.H.A. Khan, K.J. Kim, D. Park, A fast hybrid Jacket–Hadamard matrix based diagonal block-wise transform. Signal Process. Image Commun. 1(29), 49–65 (2014). https://doi.org/10.1016/j.image.2013.11.002

    Article  Google Scholar 

  27. M.H. Lee, F. Szollosi, A note on inverse-orthogonal Toeplitz matrices. Electron. J. Linear Algebra 26, 898–904 (2013). https://doi.org/10.13001/1081-3810.1694

    Article  MathSciNet  MATH  Google Scholar 

  28. M.H. Lee, F. Szollosi, Hadamard Matrices Modulo 5. J. Comb Des. 22(4), 171–178 (2014). https://doi.org/10.1002/jcd.21369

    Article  MathSciNet  MATH  Google Scholar 

  29. M.H. Lee, X.-D. Zhang, W. Song, X.-G. Xia, Fast reciprocal Jacket transform with many parameters. IEEE Trans. Circuits Syst. I Reg. Pap. 59(7), 1472–1481 (2012). https://doi.org/10.1109/TCSI.2011.2177013

    Article  MathSciNet  Google Scholar 

  30. K.H. Leung, B. Schmidt, New restrictions on possible orders of circulant Hadamard matrices. Des. Codes Cryptogr. 64, 143–151 (2012). https://doi.org/10.1007/s10623-011-9493-1

    Article  MathSciNet  MATH  Google Scholar 

  31. J. Li, M. Wen, X. Cheng, Y. Yan, S. Song, M.H. Lee, Generalized precoding-aided quadrature spatial modulation. IEEE Trans. Veh. Technol. 66(2), 1881–1886 (2017). https://doi.org/10.1109/TVT.2016.2565618

    Article  Google Scholar 

  32. J. Li, M. Wen, X. Jiang, W. Duan, Space-time multiple-mode orthogonal frequency division multiplexing with index modulation. IEEE Access 5, 23212–23222 (2017). https://doi.org/10.1109/ACCESS.2017.2761845

    Article  Google Scholar 

  33. F.J. Macwilliams, N.J.A. Sloane, The theory of error correcting codes (North-Holland, New York, 1977)

    MATH  Google Scholar 

  34. S.C. Pei, J.J. Ding, Generalizing the Jacket transform by sub orthogonality extension, in EUSIOCO (European Signal Processing Conference), pp. 408–412 (2009)

  35. B.S. Rajan, M.H. Lee, Quasi-cyclic dyadic codes in the Walsh–Hadamard transform domain. IEEE Trans. Inf. Theory 48(8), 2406–2412 (2000). https://doi.org/10.1109/TIT.2002.800475

    Article  MathSciNet  MATH  Google Scholar 

  36. K.W. Schmidt, E.T.H. Wang, The weight of Hadamard matrices. J. Comb. Theory A23, 257–263 (1977). https://doi.org/10.1016/0097-3165(77)90017-6

    Article  MathSciNet  MATH  Google Scholar 

  37. G. Strang, Linear Algebra and Its Applications, 4th edn. (Cengage Learning, Boston, 2005)

    MATH  Google Scholar 

  38. G. Strang, Essays in Linear Algebra (Wellesley-Cambridge Press, Wellesley, 2012)

    MATH  Google Scholar 

  39. E. Telatar, Capacity of multi-antenna Gaussian channels. Eur. Trans. Telecommun. 10(6), 585–595 (1999). https://doi.org/10.1002/ett.4460100604

    Article  MathSciNet  Google Scholar 

  40. D. Tse, P. Viswanath, Fundamentals of Wireless Communication (Cambridge University Press, Cambridge, 2005)

    Book  MATH  Google Scholar 

  41. M. Wen, E. Basar, Q. Li, B. Zheng, M. Zhang, Multiple-mode orthogonal frequency division multiplexing with index modulation. IEEE Trans. Commun. 65(9), 3892–3906 (2017). https://doi.org/10.1109/TCOMM.2017.2710312

    Article  Google Scholar 

  42. R.K. Yarlagadda, J.E. Hershey, Hadamard Matrix Analysis and Synthesis With Applications to Communications Signal/Image Processing (Kluwer Academic Publishers, Norwell, 1997)

    Google Scholar 

Download references

Acknowledgements

The second author visited Concordia University from July 4 to July 25, 2008, in Canada, and talked about Jacket Matrix many times, thanks to Professor M. Omair Ahmad and Professor M.N.S. Swamy.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Moon Ho Lee.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

This work was supported by the National Natural Science Foundation of China (Nos. 61801106, 11531001), the Joint NSFC-ISF Research Program (jointly funded by the National Natural Science Foundation of China and the Israel Science Foundation (No. 11561141001)), National Research Foundation; also, this work was extended from USA patent [23].

Appendix

Appendix

1.1 The Proof of Eq. (1) is as follows:

To analyze the fundamentals of the Jacket patterns and their related properties, first the basic format is investigated: Symmetric Jacket Matrix of Rank 2. Some important properties and patterns are investigated.

Given an two-by-two symmetric pattern, such as

$$\begin{aligned} {[}A]_2=\left( \begin{array}{cc} a &{} b \\ b &{} -c \end{array}\right) . \end{aligned}$$
(42)

where abc can be arbitrary.

Theorem A1

A two-by-two symmetric Jacket matrix pattern is

$$\begin{aligned} {[}J]_2=\left( \begin{array}{cc} a &{} \sqrt{ac} \\ \sqrt{ac} &{} -c \end{array}\right) \ \ or \ \ [J]_2=\left( \begin{array}{cc} a &{} -\sqrt{ac} \\ -\sqrt{ac} &{} -c \end{array}\right) , \end{aligned}$$
(43)

where the entries of this Jacket are nonzero.

Proof

If the two-by-two symmetric matrix pattern \([S]_2\) should have Eq. (44).

$$\begin{aligned} {[}A]_2^{-1}=\frac{1}{2}\left( \begin{array}{cc} a^{-1} &{} b^{-1} \\ b^{-1} &{} c^{-1} \end{array}\right) . \end{aligned}$$
(44)

then

$$\begin{aligned} {[}A]_2 \cdot [A]_2^{-1}=[I]_2, \left( \begin{array}{cc} a &{} b \\ b &{} -c \end{array}\right) \cdot \frac{1}{2}\left( \begin{array}{cc} a^{-1} &{} b^{-1} \\ b^{-1} &{} c^{-1} \end{array}\right) =[I]_2, \end{aligned}$$
(45)

thus it can be obtained

$$\begin{aligned} \frac{1}{2}\left( a\cdot \frac{1}{a} +b \cdot \frac{1}{b}\right) =1, \nonumber \\ \frac{1}{2}\left( a\cdot \frac{1}{b} -b \cdot \frac{1}{c}\right) =0, \nonumber \\ \frac{1}{2}\left( b\cdot \frac{1}{a} -c \cdot \frac{1}{b}\right) =0, \nonumber \\ \frac{1}{2}\left( b\cdot \frac{1}{b} +c \cdot \frac{1}{c}\right) =1, \nonumber \\ \end{aligned}$$
(46)

clearly, it should be forced that

$$\begin{aligned} \frac{a}{c}-\frac{b}{c}=0 \ \ \mathrm{and} \ \ \frac{b}{a}-\frac{c}{b}=0, \end{aligned}$$
(47)

thus

$$\begin{aligned} \frac{ac-b^2}{bc}=0 \ \ \mathrm{and} \ \ \frac{b^2-ac}{ab}=0, \end{aligned}$$
(48)

then it can be obtained

$$\begin{aligned} b=\pm \sqrt{ac}. \end{aligned}$$
(49)

\(\square \)

Lemma A1

An orthogonal symmetric two-by-two Jacket matrix considers always with Hadamard matrix, if the entries of the matrix are nonzero.

Proof

The orthogonal property has

$$\begin{aligned} {[}J]_2 \cdot [J]_2^T=2[I]_2, \end{aligned}$$
(50)

thus it can be obtained

$$\begin{aligned} {[}J]_2^T=2[J]_2^{-1}. \end{aligned}$$
(51)

If \([J]_2=\left( \begin{array}{cc} a &{} \sqrt{ac} \\ \sqrt{ac} &{} -c \end{array}\right) \), then it can be obtained

$$\begin{aligned}{}[J]_2[J]_2^T=\left( \begin{array}{cc} a &{} \sqrt{ac} \\ \sqrt{ac} &{} -c \end{array}\right) \left( \begin{array}{cc} a^{-1} &{} \sqrt{ac}^{-1} \\ \sqrt{ac}^{-1} &{} -c^{-1} \end{array}\right) =2[I]_2. \end{aligned}$$
(52)

If \([J]_2=\left( \begin{array}{cc} a &{} -\sqrt{ac} \\ -\sqrt{ac} &{} -c \end{array}\right) \), then it can be obtained

$$\begin{aligned}{}[J]_2[J]_2^T=\left( \begin{array}{cc} a &{} -\sqrt{ac} \\ -\sqrt{ac} &{} -c \end{array}\right) \left( \begin{array}{cc} a^{-1} &{} -\sqrt{ac}^{-1} \\ -\sqrt{ac}^{-1} &{} -c^{-1} \end{array}\right) =2[I]_2. \end{aligned}$$
(53)

Clearly, the solution is \(a=c=1\). Thus, the Jacket pattern can be written by

$$\begin{aligned} {[}J]_2=\left( \begin{array}{cc} a &{} -\sqrt{ac} \\ -\sqrt{ac} &{} -c \end{array}\right) =\left( \begin{array}{cc} 1 &{} -1 \\ -1 &{} -1 \end{array}\right) , \end{aligned}$$
(54)

also

$$\begin{aligned} {[}J]_2=\left( \begin{array}{cc} a &{} \sqrt{ac} \\ \sqrt{ac} &{} c \end{array}\right) =\left( \begin{array}{cc} 1 &{} 1 \\ 1 &{} -1 \end{array}\right) , \end{aligned}$$
(55)

\(\square \)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hai, H., Lee, M.H. & Zhang, XD. Block-Circulant Inverse Orthogonal Jacket Matrices and Its Applications to the Kronecker MIMO Channel. Circuits Syst Signal Process 38, 1847–1875 (2019). https://doi.org/10.1007/s00034-018-0995-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00034-018-0995-1

Keywords

Navigation