For mobile user equipments (UEs), a careful power management is essential. Despite this fact, quite an amount of energy is wasted in today's UEs’ analogue (AFEs) and digital frontends (DFEs). These are engineered for extracting the wanted signal from a spectral environment defined in the corresponding communication standards with their extremely tough requirements. These requirements define a worst-case scenario still ensuring reliable communication. In a typical receiving process the actual requirements can be considered as less critical. Knowledge about the actual environmental spectral conditions allows to reconfigure both frontends to the actual needs and to save energy. In this paper, the authors present a highly efficient generic spectrum sensing approach, which allows to collect information about the actual spectral environment of an UE. This information can be used to reconfigure both the AFE and DFE, thus endowing them with increased intelligence. A low-complex multiplier free filter bank extended by an efficient power calculation unit will be introduced. They also present simulation results, which illustrate the performance of the spectrum sensing approach and a complexity comparison with different well-known implementations is given. Furthermore, estimates on the chip area and power consumption based on a 65 nm CMOS technology database are provided, considering the Smarti4G chip as a reference.

References

1. 1)
  - 20. Byrd, R.H., Gilbert, J.: ‘A trust region method based on interior point techniques for nonlinear programming’, Math. Program., 1996, 89, pp. 149–185 (doi: 10.1007/PL00011391).
2. 2)
  - 2. Goertzel, G.: ‘An algorithm for the evaluation of finite trigonometric series’, Am. Math. Mon., 1958, 65, pp. 34–35 (doi: 10.2307/2310304).
3. 3)
  - 41. Fettweis, A.: ‘Digital circuits and systems’, IEEE Trans. Circuit Syst., 1984, 31, (1), pp. 31–48 (doi: 10.1109/TCS.1984.1085417).
4. 4)
  - 4. Jacobsen, E., Lyons, R.: ‘The sliding DFT’, Signal Process. Mag., 2003, 20, (2), pp. 74–80 (doi: 10.1109/MSP.2003.1184347).
5. 5)
  - 52. Quatieri, T.J.: ‘Short-time spectral analysis with the conventional and sliding CZT’, IEEE Trans. Acoust. Speech Signal Process., 1978, 26, (6), pp. 561–566 (doi: 10.1109/TASSP.1978.1163163).
6. 6)
  - 26. Mallat, S.: ‘A theory for multiresolution signal decomposition: The wavelet representation’, IEEE Trans. Pattern Anal. Mach. Intell., 1989, 11, (7), pp. 674–693 (doi: 10.1109/34.192463).
7. 7)
  - 31. Vaidyanathan, P.: ‘Theory and design of M-channel maximally decimated quadrature mirror filters with arbitrary M, having the perfect-reconstruction property’, IEEE Trans. Acoust. Speech Signal Process., 1987, 35, (4), pp. 476–492 (doi: 10.1109/TASSP.1987.1165155).
8. 8)
  - 47. Bluestein, L.I.: ‘A linear filtering approach to the computation of the discrete Fourier transform’, IEEE Trans. Audio Electroacoust., 1970, 18, (4), pp. 451–455 (doi: 10.1109/TAU.1970.1162132).
9. 9)
  - 23. Lustig, I.J., Marsten, R.E., Shanno, D.F.: ‘Interior point methods for linear programming: computational state of the art’, ORSA J. Comput., 1994, 6, pp. 1–14 (doi: 10.1287/ijoc.6.1.1).
10. 10)
  - 2. Mitola, J., Maguire, G.Q.: ‘Cognitive radio: making software radios more personal’, IEEE Pers. Commun., 1999, 6, (4), pp. 13–18 (doi: 10.1109/98.788210).
11. 11)
  - 27. Smith, M.J.T., Barnwell, T.P.I.: ‘Exact reconstruction techniques for tree-structured subband coders’, IEEE Trans. Acoust. Speech Signal Process., 1986, 34, (3), pp. 434–441 (doi: 10.1109/TASSP.1986.1164832).
12. 12)
  - 29. Mintzer, F.: ‘Filters for distortion-free two-band multirate filter banks’, IEEE Trans. Acoust., Speech Signal Process., 1985, 33, (3), pp. 626–630 (doi: 10.1109/TASSP.1985.1164587).
13. 13)
  - 22. Gonzaga, C.C.: ‘Path-following methods for linear programming’, SIAM Rev., 1992, 34, pp. 167–224 (doi: 10.1137/1034048).
14. 14)
  - 33. Vaidyanathan, P.P.: ‘Multirate digital filters, filter banks, polyphase networks, and applications: a tutorial’, Proc. IEEE, 1990, 78, (1), pp. 56–93 (doi: 10.1109/5.52200).
15. 15)
  - 5. Hueber, G., Stuhlberger, R., Springer, A.: ‘An adaptive digital front-end for multimode wireless receivers’, IEEE Trans. Circuits Syst. II, Express Briefs, 2008, 55, (4), pp. 349–353 (doi: 10.1109/TCSII.2008.918976).
16. 16)
  - 20. Waltz, R.A., Morales, J.L., Nocedal, J., et al: ‘An interior algorithm for nonlinear optimization that combines line search and trust region steps’, Math. Program. J., 2006, 107, (3), pp. 391–408 (doi: 10.1007/s10107-004-0560-5).
17. 17)
  - 17. Jacobsen, E., Lyons, R.: ‘An update to the sliding DFT’, IEEE Signal Process. Mag., 2014, 21, (1), pp. 110–111 (doi: 10.1109/MSP.2004.1516381).
18. 18)
  - 16. Byrd, R., Hribar, M.E., Nocedal, J.: ‘An interior point algorithm for large-scale nonlinear programming’, SIAM J. Optim., 1999, 9, (4), pp. 877–900 (doi: 10.1137/S1052623497325107).
19. 19)
  - R. Byrd , J. Gilbert , J. Nocedal . A trust region method based on interior point techniques for nonlinear programming. Math. Program. , 1 , 149 - 185
20. 20)
  - 54. 24 Selesnick: ‘Short-time Fourier transform’, Connexion Web site, August 2005, (last access: 25.10.2011). [Online]. Available at http://www.cnx.org/content/m10570/2.4/.
21. 21)
  - 60. Schlechter, T.: ‘Overview on energy detection based spectral estimation approaches in communication systems’. Proc. Int. Conf. Wireless Information Technology and Systems (ICWITS), Maui, November 2012.
22. 22)
  - 25. Jacobsen, E., Lyons, R.: ‘The sliding DFT’, IEEE Signal Process. Mag., 2003, 20, (2), pp. 74–80 (doi: 10.1109/MSP.2003.1184347).
23. 23)
  - 41. Fettweis, A.: ‘Digital circuits and systems’, IEEE Trans. Circuit Syst., 1984, 31, (1), pp. 31–48 (doi: 10.1109/TCS.1984.1085417).
24. 24)
  - 22. Gonzaga, C.C.: ‘Path-following methods for linear programming’, SIAM Rev., 1992, 34, pp. 167–224 (doi: 10.1137/1034048).
25. 25)
  - F. Fernandes , I. Selesnick , R. van Spaendonck , C. Burrus . Complex wavelet transforms with allpass filters. Signal Process. , 1689 - 1670
26. 26)
  - 61. Kammeyer, K.-D.: ‘Nachrichtenübertragung’ (Teubner Verlag, Wiesbaden, Deutschland, 2004, 3rd edn.).
27. 27)
  - 66. Danube Mobile Communications Engineering: ‘S4GV100_PowerDistribution_over_Chip.xls’, February 2011.
28. 28)
  - S.G. Mallat . A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans. Pattern Anal. Mach. Intell. , 7 , 674 - 693
29. 29)
  - 62. Schlechter, T.: ‘MRLC filter banks for blocker detection in LTE systems’ (ser. Advances in Mechatronics, Trauner Verlag, August 2013).
30. 30)
  - L.R. Rabiner , R.W. Shafer , C.M. Rader . The chirp z-transform algorithm. IEEE Trans. Audio Electroacoustics , 2 , 86 - 92
31. 31)
  - P.P. Vaidyanathan . Theory and design of M-channel maximally decimated quadrature mirror filters with arbitrary M, having the perfect-reconstruction property. IEEE Trans. Acoust. Speech Signal Process. , 4 , 476 - 492
32. 32)
  - 5. Hueber, G., Stuhlberger, R., Springer, A.: ‘An adaptive digital front-end for multimode wireless receivers’, IEEE Trans. Circuits Syst. II, Express Briefs, 2008, 55, (4), pp. 349–353 (doi: 10.1109/TCSII.2008.918976).
33. 33)
  - 39. Schlechter, T., Huemer, M.: ‘Complexity-optimized filter design for a filter bank based blocker detection concept for LTE systems’, in Quesada-Arencibia, A., Rodriguez, J.C., Moreno Diaz, R.Jr., Moreno-Diaz, R. (Eds.): ‘Eurocast 2011 – computer aided system theory – extended abstracts’, (Springer Verlag GmbH, Berlin, Heidelberg, New York, 2011), pp. 182–183.
34. 34)
  - 49. Poularikas, A.D.: ‘The transforms and applications handbook’ (CRC Press LLC, Boca Raton, 2000, 2nd edn.).
35. 35)
  - 9. Hueber, G., Stuhlberger, R., Springer, A.: ‘Concept for an adaptive digital front-end for multi-mode wireless receivers’. Proc. IEEE Int. Symp. Circuits Systems (ISCAS 2008), Seattle, WA, May 2008, pp. 89–92.
36. 36)
  - F. Mintzer . Filters for distortion-free two-band multirate filter banks. IEEE Trans. Acoust., Speech, Signal Process. , 3 , 626 - 630
37. 37)
  - 20. Gill, P.E., Murray, W., Wright, M.H.: ‘Practical optimization’ (Academic Press, London, 1981).
38. 38)
  - 64. ‘Data Book - ucstarlib lpreg 9t - C65LP’ (Infineon Technologies AG, 2008, 3rd edn.).
39. 39)
  - 32. Regalia, P.A., Mitra, S.K., Vaidyanathan, P.P., Renfors, M.K., Neuvo, Y.: ‘Tree-structured complementary filter banks using all-pass sections’, IEEE Trans. Circuits Syst., 1987, 34, (12), pp. 1470–1484 (doi: 10.1109/TCS.1987.1086086).
40. 40)
  - 46. Bluestein, L.I.: ‘A linear filtering approach to the computation of the discrete Fourier transform’, Northeast Electron. Res. Eng. Meet. Rec., 1968, 10, pp. 218–219.
41. 41)
  - 24. Wright, M.H.: ‘Interior methods for constrained optimization’, Acta Numer., 1992, 1992, pp. 341–407 (doi: 10.1017/S0962492900002300).
42. 42)
  - P.P. Vaidyanathan . Multirate digital filters, filter banks, polyphase networks and applications: a tutorial. Proc. IEEE , 1 , 56 - 93
43. 43)
  - 26. Croiser, A., Esteban, D., Galand, C.: ‘Application of quadrature mirror filters to split band voice coding systems’. Proc. Int. Conf. Acoustics, Speech, Signal Processing, 1977, pp. 191–195.
44. 44)
  - 45. von Grnigen, D.C.: ‘Digitale Signalverarbeitung mit einer Einfhrung in die kontinuierlichen signale und systeme’ (Fachbuchverlag Leipzig, 2004, 3rd edn.).
45. 45)
  - 42. Abdulla, S.S., Nam, H., McDermot, M., Abraham, J.A.: ‘A high throughput FFT processor with no multipliers’. Proc. IEEE Int. Conf. Computer Design (ICCD 2009), Lake Tahoe, CA, October 2009, pp. 485–490.
46. 46)
  - 35. Taubman, D.S., Marcellin, M.W.: ‘JPEG2000 – image compression fundamentals, standards and practice’ (Kluwer Academic Publishers, Boston, Mass., 2002).
47. 47)
  - 25. Croiser, A., Esteban, D., Galand, C.: ‘Perfect channel splitting by use of interpolation/decimation/tree decomposition techniques’. Proc. Int. Conf. Information Science and Systems, August 1976, pp. 443–446.
48. 48)
  - 13. TS 36.101 Evolved Universal Terrestrial Radio Access (E-UTRA): User equipment (UE) radio transmission and reception, 3rd Generation Partnership Project (3GPP) Std., Rev. 10.4.0, October 2011.
49. 49)
  - R. Byrd , M. Hribar , J. Nocedal . An interior point algorithm for large-scale nonlinear programming. SIAM J. Optim. , 4 , 877 - 900
50. 50)
  - 56. Rbel, A.: ‘Lecture on analysis, modeling and transformation of audio signals’. Institute of communication science TU-Berlin, IRCAM Analysis/Synthesis Team, August 2006, ch. Analysis/resynthesis with the short time Fourier transform.
51. 51)
  - 32. Jacobsen, E., Lyons, R.: ‘An update to the sliding DFT’. IEEE Signal Process. Mag., 2004, 21, (1), pp. 110–111 (doi: 10.1109/MSP.2004.1516381).
52. 52)
  - 34. Vaidyanathan, P.P.: ‘Multirate systems and filter banks’ (Prentice-Hall, Englewood Cliffs, NJ, 1993).
53. 53)
  - 36. Mallat, S.G.: ‘A wavelet tour of signal processing’ (Academic Press, 1999, 2nd edn.).
54. 54)
  - 52. Quatieri, T.J.: ‘Short-time spectral analysis with the conventional and sliding CZT’, IEEE Trans. Acoust. Speech Signal Process., 1978, 26, (6), pp. 561–566 (doi: 10.1109/TASSP.1978.1163163).
55. 55)
  - 15. Schlechter, T.: ‘Optimized filter design in LTE systems using nonlinear optimization’. Proc. 17th European Wireless Conf. (EW 2011), Vienna, Austria, April 2011, pp. 333–339.
56. 56)
  - 2. Mayer, A., Maurer, L., Hueber, G., Dellsperger, T., Christen, T., Burger, T., Chen, Z.: ‘RF front-end architecture for cognitive radios’. Proc. 18th Annual IEEE Int. Symp. Personal, Indoor, Mobile Radio Communications (PIMRC 2007), Athens, Greece, September 2007, pp. 1–5.
57. 57)
  - 8. Vajje, S., Schlechter, T.: ‘Hardware-software co-simulation environment for a multiplier free blocker detection approach for LTE systems’. Proc. Joint Conf. Third Int. Workshop on Nonlinear Dynamics and Synchronization and 16th Int. Symp. Theoretical Electrical Engineering (INDS & ISTET 2011), Klagenfurt, Austria, July 2011, pp. 356–361.
58. 58)
  - 6. Schlechter, T., Huemer, M.: ‘Overview on blocker detection in LTE systems’. Proc. Austrochip 2010, Villach, Austria, October 2010, pp. 99–104.
59. 59)
  - 7. Schlechter, T.: ‘Output-to-spectrum assignment algorithm for a LTE cognitive radio filter bank’. Proc. Joint Conf. Third Int. Workshop on Nonlinear Dynamics and Synchronization and 16th Int. Symp. Theoretical Electrtical Engineering (INDS & ISTET 2011), Klagenfurt, Austria, July 2011, pp. 186–190.
60. 60)
  - 48. Gold, B., Rader, C.M.: ‘Digital processing of signals’ (McGraw-Hill, New York, 1969).
61. 61)
  - 38. Schlechter, T.: ‘Estimating complexity in multi rate systems’. Proc. 17th IEEE Int. Conf. Electronic Circuits and Systems (ICECS 2010), Athens, Greece, December 2010, pp. 728–731.
62. 62)
  - 12. Schlechter, T.: ‘Multiplier free filter bank based concept for blocker detection in LTE systems’. Proc. Conf. Design and Architectures for Signal and Image Processing (DASIP 2011), Tampere, Finland, November 2011, pp. 291–297.
63. 63)
  - M.J.T. Smith , T.P. Barnwell . Exact reconstruction techniques for tree-structured sub-band coders. IEEE Trans. Acoust. Speech Signal Process. , 3 , 434 - 441
64. 64)
  - 23. Lustig, I.J., Marsten, R.E., Shanno, D.F.: ‘Interior point methods for linear programming: computational state of the art’, ORSA J. Comput., 1994, 6, pp. 1–14 (doi: 10.1287/ijoc.6.1.1).
65. 65)
  - 63. ‘TS 25.101 User Equipment (UE) radio transmission and reception (FDD)’, 3rd Generation Partnership Project (3GPP) Std., Rev. 10.3.0, October 2011.
66. 66)
  - 21. Fletcher, R.: ‘Practical methods of optimization’ (John Wiley & Sons, New York, 1987, 2nd edn.).
67. 67)
  - 43. Manolakis, D.G., Ingle, V.K., Kogon, S.M.: ‘Statistical and adaptive signal processing’ (Artech House, Inc., 685 Canton Street, Norwood, MA 02062, 2005).
68. 68)
  - 11. Schlechter, T., Huemer, M.: ‘Advanced filter bank based approach for blocker detection in LTE systems’. Proc. IEEE Int. Symp. Circuits and Systems (ISCAS 2011), Rio De Janeiro, Brazil, May 2011, pp. 2189–2192.
69. 69)
  - J. Mitola , G.Q. Maguire . Cognitive radio: making software radios more personal. IEEE Pers. Commun. , 9 , 13 - 18
70. 70)
  - 30. Vetterli, M.: ‘Filter banks allowing perfect reconstruction’, J. Signal Process., 1986, 10, (3), pp. 219–244 (doi: 10.1016/0165-1684(86)90101-5).
71. 71)
  - 53. Sowares, A.B., Berzin, F., Andrada, A.d.O.: ‘Power spectrum estimation of EMG signals via chirp-z transform’. Proc. Congress Int. Society of Electrophysiology and Kinesiology, Vienna, Austria, 2002, pp. 42–43.
72. 72)
  - R.A. Waltz , J.L. Morales , J. Nocedal , D. Orban . An interior algorithm for nonlinear optimization that combines line search and trust region steps. Math. Program. , 391 - 408
73. 73)
  - 44. Goertzel, G.: ‘An algorithm for the evaluation of finite trigonometric series’, Am. Math. Mon., 1968, 65, pp. 34–35 (doi: 10.2307/2310304).
74. 74)
  - 47. Bluestein, L.I.: ‘A linear filtering approach to the computation of the discrete Fourier transform’, IEEE Trans. Audio Electroacoust., 1970, 18, (4), pp. 451–455 (doi: 10.1109/TAU.1970.1162132).
75. 75)
  - 65. Danube Mobile Communications Engineering: ‘Area_draft_UE2_S4G.xls’, 2010.
76. 76)
  - 28. Grenez, F.: ‘Chebyshev design of filters for subband coders’, IEEE Trans. Acoust. Speech Signal Process., 1988, 36, (2), pp. 182–185 (doi: 10.1109/29.1512).
77. 77)
  - 4. Mayer, A.: ‘A spectral sensing technique enabling adaptive low power receiver for 3G and beyond mobile terminals’, PhD dissertation, Johannes Kepler Universitt Linz, March 2009.
78. 78)
  - 59. Gençay, R., Selçuk, F., Whitcher, B.: ‘An introduction to wavelets and other filtering methods in finance and economics’ (Academic Press, 2002).
79. 79)
  - 28. Grenez, F.: ‘Chebyshev design of filters for subband coders’, IEEE Trans. Acoust. Speech Signal Process., 1988, 36, (2), pp. 182–185 (doi: 10.1109/29.1512).
80. 80)
  - 24. Wright, M.H.: ‘Interior methods for constrained optimization’, Acta Numer., 1992, 1992, pp. 341–407 (doi: 10.1017/S0962492900002300).
81. 81)
  - 30. Vetterli, M.: ‘Filter banks allowing perfect reconstruction’, J. Signal Process., 1986, 10, (3), pp. 219–244 (doi: 10.1016/0165-1684(86)90101-5).
82. 82)
  - 40. Fernandes, F.C.A., Selesnick, I.W., Spaendock, R.L., Burrus, C.S.: ‘Complex wavelet transform with all pass filters’, Signal Process., 2003, 8, pp. 1689–1706 (doi: 10.1016/S0165-1684(03)00077-X).
83. 83)
  - 32. Regalia, P.A., Mitra, S.K., Vaidyanathan, P.P., Renfors, M.K., Neuvo, Y.: ‘Tree-structured complementary filter banks using all-pass sections’, IEEE Trans. Circuits Syst., 1987, 34, (12), pp. 1470–1484 (doi: 10.1109/TCS.1987.1086086).
84. 84)
  - 22. Rabiner, L.R., Schafer, R.W., Rader, C.M.: ‘The chirp z-transform algorithm’, IEEE Trans. Audio Electroacoust., 1969, 17, (2), pp. 86–92 (doi: 10.1109/TAU.1969.1162034).
85. 85)
  - 3. Mayer, A., Maurer, L., Hueber, G., Lindner, B., Wicpalek, C., Hagelauer, R.: ‘Novel digital front end based interference detection methods’. Proc. 10th European Conf. Wireless Technology (ECWT 2007), Munich, Germany, October 2007, pp. 70–74.
86. 86)
  - 55. Smith, J.O.I., Serra, X.: ‘PARSHL: an analysis/synthesis program for non-harmonic sounds based on a sinusoidal representation’. Proc. Int. Comput. Music Conf. (ICMC-87), Center for Computer Research in Music and Acoustics (CCRMA), Stanford University. Tokyo, Computer Music Association, 1987.
87. 87)
  - 50. Smith, J.O.I.: ‘Mathematics of the discrete Fourier transform: with audio applications’ (Booksurge LLC, 2006, 2nd edn.).
88. 88)
  - 14. Schlechter, T., Huemer, M.: ‘Generic low complex filter bank based spectrum sensing approach for LTE cognitive radio’. Proc. Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, November 2012.
89. 89)
  - 18. den Hertog, D.: ‘Interior point approach to linear, quadratic and convex programming: algorithms and complexity’ (Kluwer Academic Publishers, Dordrecht, Boston, London, 1997, 2nd edn.).
90. 90)
  - 10. Dellsperger, T., Burger, T., Maurer, L., Christen, T.: ‘Reconfigurable RF transceivers for multi standard terminals – an E2R view’. Proc. 15th IST Mobile & Wireless Communications Summit, Myconos, Greece, June 2006.

Spectral estimation for long-term evolution transceivers using low-complex filter banks

References

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