Advancements of MultiRate Signal processing for Wireless Communication Networks: Current State Of the Art

1
Dr. D V Srihari Babu
Dr. D V Srihari Babu
2
Dr. P Chandrashekhar Reddy
Dr. P Chandrashekhar Reddy
1 Jawaharlal nehru university - Hyderabad.

Send Message

To: Author

GJCST Volume 12 Issue E13

Article Fingerprint

ReserarchID

CSTNWSV46VV

Advancements of MultiRate Signal processing for Wireless Communication Networks: Current State Of the Art Banner
  • English
  • Afrikaans
  • Albanian
  • Amharic
  • Arabic
  • Armenian
  • Azerbaijani
  • Basque
  • Belarusian
  • Bengali
  • Bosnian
  • Bulgarian
  • Catalan
  • Cebuano
  • Chichewa
  • Chinese (Simplified)
  • Chinese (Traditional)
  • Corsican
  • Croatian
  • Czech
  • Danish
  • Dutch
  • Esperanto
  • Estonian
  • Filipino
  • Finnish
  • French
  • Frisian
  • Galician
  • Georgian
  • German
  • Greek
  • Gujarati
  • Haitian Creole
  • Hausa
  • Hawaiian
  • Hebrew
  • Hindi
  • Hmong
  • Hungarian
  • Icelandic
  • Igbo
  • Indonesian
  • Irish
  • Italian
  • Japanese
  • Javanese
  • Kannada
  • Kazakh
  • Khmer
  • Korean
  • Kurdish (Kurmanji)
  • Kyrgyz
  • Lao
  • Latin
  • Latvian
  • Lithuanian
  • Luxembourgish
  • Macedonian
  • Malagasy
  • Malay
  • Malayalam
  • Maltese
  • Maori
  • Marathi
  • Mongolian
  • Myanmar (Burmese)
  • Nepali
  • Norwegian
  • Pashto
  • Persian
  • Polish
  • Portuguese
  • Punjabi
  • Romanian
  • Russian
  • Samoan
  • Scots Gaelic
  • Serbian
  • Sesotho
  • Shona
  • Sindhi
  • Sinhala
  • Slovak
  • Slovenian
  • Somali
  • Spanish
  • Sundanese
  • Swahili
  • Swedish
  • Tajik
  • Tamil
  • Telugu
  • Thai
  • Turkish
  • Ukrainian
  • Urdu
  • Uzbek
  • Vietnamese
  • Welsh
  • Xhosa
  • Yiddish
  • Yoruba
  • Zulu

With the hasty growth of internet contact and voice and information centric communications, many contact technologies have been urbanized to meet the stringent insist of high speed information transmission and viaduct the wide bandwidth gap among ever-increasing highdata-rate core system and bandwidth-hungry end-user complex. To make efficient consumption of the limited bandwidth of obtainable access routes and cope with the difficult channel environment, several standards have been projected for a variety of broadband access scheme over different access situation (twisted pairs, coaxial cables, optical fibers, and unchanging or mobile wireless admittance). These access situations may create dissimilar channel impairments and utter unique sets of signal dispensation algorithms and techniques to combat precise impairments. In the intended and implementation sphere of those systems, many research issues arise. In this paper we present advancements of multi-rate indication processing methodologies that are aggravated by this design trend. The thesis covers the contemporary confirmation of the current literature on intrusion suppression using multi-rate indication in wireless communiqué networks.

116 Cites in Articles

References

  1. F Harris (2005). Multirate Signal Processing for Communication Systems.
  2. G Wornell (1996). Emerging applications of multirate signal processing and wavelets in digital communications.
  3. A Akansu,M Tazebay,M Medley,P Das (1997). Wavelet and subband transforms: fundamentals and communication applications.
  4. S Mirabbasi,K Martin (2000). Classical and modern receiver architectures.
  5. D Chester (1999). Digital IF lter technology for 3G systems: An introduction.
  6. L Erup,F Gardner,R Harris (1993). Interpolation in digital modems. II. Implementation and performance.
  7. R Kumar,T Nguyen,C Wang,G Goo (1999). Signal processing techniques for wideband communications systems.
  8. V Bojan (1993). Multirate signal processing concepts in digital communications.
  9. P Vaidyanathan,B Vrcelj (2001). Biorthogonal partners and applications.
  10. M Unser,A Aldroubi,M Eden (1993). B-spline signal processing. I. Theory.
  11. B Vrcelj,P Vaidyanathan (2001). Efficient implementation of all-digital interpolation.
  12. Lei Huang,; Fu-Chun Zheng (2004). Space-time blind multiuser detection for multi-rate DS/CDMA signals.
  13. S Verdú (1998). Multiuser Detection.
  14. J Chen,U Mitra (1999). Analysis of decorrelatorbased detectors formultirate DS/CDMA communications.
  15. Mohammad Saquib,Roy Yates,Narayan Mandayam (1998). Decorrelating Detectors for a Dual Rate Synchronous DS/CDMA System.
  16. M Saquib,R Yates,A Ganti (2000). An asynchronous multiratedecorrelator.
  17. J Choi,S Kim (2002). Adaptive MMSE receiver for multirate CDMAsystems.
  18. A Sabharwal,U Mitra,R Moses (2001). MMSE receiver for multirateDS-CDMA systems.
  19. Markku Juntti (1999). Performance of Multiuser Detection in Multirate CDMA Systems.
  20. U Mitra (1999). Comparison of maximum-likelihood-based detection for two multirate access schemes for CDMA signals.
  21. M Saquib,R Yates,N Mandayam (1998). Decision feedback detection for a dual-rate CDMA system.
  22. H Ge (1997). Multiuser detection for integrated multi-rate CDMA.
  23. H Ge,J Ma (1998). Multirate LMMSE detectors for asynchronous multi-rate CDMA systems.
  24. A Chkeif,K Abed-Meraim,G Kawas-Kaleh,Yingbo Hua (2000). Spatio-temporal blind adaptive multiuser detection.
  25. K Meraim,A Chkeif,Y Hua (2000). Fast orthonormal PAST algorithm.
  26. R Prendergast,B Levy,P Hurst (2004). Reconstruction of band-limited periodic inconsistently sampled signals through multi-rate filter banks.
  27. H Nyquist (1928). Certain Topics in Telegraph Transmission Theory.
  28. C Shannon (1949). Communication in the Presence of Noise.
  29. J Yen (1956). On nonuniform sampling of bandwidthlimited signals.
  30. A Papoulis (1977). Generalized sampling expansion.
  31. J Brown (1981). Multi-channel sampling of low-pass signals.
  32. P Vaidyanathan,V Liu (1988). Classical sampling theorems in the context of multirate and poly-phase digital filter bank structures.
  33. P Vaidyanathan,V Liu (1990). Efficient reconstruction of band-limited sequences from nonuniformly decimated versions by use of polyphase filter banks.
  34. Y Eldar,A Oppenheim (2000). Filterbank reconstruction of bandlimited signals from nonuniform and generalized samples.
  35. H Johansson,P L¨owenborg (2002). Reconstruction of nonuniformly sampled band limited signals by means of digital fractional delay filters.
  36. W Namgoong (2002). Finite-length synthesis filters for non-uniformly time-interleaved analog-to-digital converter.
  37. R Venkataramani,Y Bresler (2000). Perfect reconstruction formulas and bounds on aliasing error in sub-Nyquist nonuniform sampling of multiband signals.
  38. R Venkataramani,Y Bresler (2001). Optimal sub-Nyquist non uniform sampling and reconstruction for multiband signals.
  39. Y. -C Jenq (1997). Perfect reconstruction of digital spectrum from non uniformly sampled signals.
  40. F Marvasti (2001). Non uniform Sampling, Theory and Practice.
  41. R Prendergast,B Levy,P Hurst (2002). Multirate filter banker construction of band limited signals from bunched samples.
  42. Jiandong Wang,; Tongwen Chen,; Biao Huang (2005). On spectral theory of cyclo-stationary signals in multirate systems.
  43. Barry Masters (1999). The Digital Signal Processing Handbook.
  44. E Gladyshev (1961). Periodically and Almost-Periodically Correlated Random Processes with a Continuous Time Parameter.
  45. Jiandong Wang,Tongwen Chen,Biao Huang (2006). Cyclo-period estimation for discrete-time cyclo-stationary signals.
  46. D Martin (1999). Detection of periodic autocorrelation in time series data via zerocrossing.
  47. Jiandong Wang,Tongwen Chen,Biao Huang (1994). Cyclo-period estimation for discrete-time cyclo-stationary signals.
  48. L Tong,G Xu,T Kailath (1994). Blind identification and equalization based on second-order statistics: A time domain approach.
  49. L Tong,G Xu,B Hassibi,T Kailath (1995). Blind identification and equalization based on secondorder statistics: A frequency-domain approach.
  50. S Ohno,H Sakai (1996). Optimization of filter-banks using cyclo stationary spectral analysis.
  51. H Sakai,S Ohno (1997). Theory of cyclo stationary processes andits application.
  52. (1990). Identification of systems with cyclo stationary input and correlated input/output measurement noise.
  53. G Giannakis (1995). Polyspectral and cyclostationary approaches for identification of closed-loop systems.
  54. L Sun,H Ohmori,A Sano (2000). Frequency domain approach to closed-loop identification based on output inter-sampling scheme.
  55. J Wang,T Chen,B Huang (2004). Closed-loop identification via output fast sampling.
  56. E Gladyshev (1961). Periodically and Almost-Periodically Correlated Random Processes with a Continuous Time Parameter.
  57. W Gardner (1988). Statistical Spectral Analysis: A Non probabilistic Theory.
  58. Hilary Deason (1990). Science and Technology Supplements: <i>The McGraw-Hill Yearbook of Science and Technology</i> . David I. Eggenberger, Exec. Ed. McGraw-Hill, New York, 1966. 461 pp. Illus. $24.; <i>McGraw-Hili Modern Men of Science</i> . Jay E. Greene, Ed. McGrawHill, New York, 1966. 630 pp. Illus. $19.50.; <i>McGraw-Hill Basic Bibliography of Science and Technology</i> . David I. Eggenberger, Exec. Ed. McGraw-Hill, New York, 1966. 748 pp. $19.50..
  59. B Lall,S Joshi,R Bhatt (1999). Second-order statistical characterization of the filter bank and its elements.
  60. S Akkarakaran,P Vaidyanathan (2000). Bifrequency and bispectrummaps: A new look at multirate systems with stochastic inputs.
  61. V Sathe,P Vaidyanathan (1993). Effects of Multirate Systems on the Statistical Properties of Random Signals.
  62. C Therrien (2001). Issues in multirate statistical signal processing.
  63. C Therrien,R Cristi (2002). Two-dimensional spectral representation of periodic, cyclo stationary, and more general random processes.
  64. C Therrien (2002). Some considerations for statistical characterization of nonstationary random processes.
  65. R Meyer,C Burrus (1975). A unified analysis of multirate and periodically time-varying digital filters.
  66. P Vaidyanathan (1993). Multirate Systems and Filterbanks.
  67. Tongwen Chen,Bruce Francis (1995). Optimal Sampled-Data Control Systems.
  68. P Khargonekar,K Poolla,A Tannenbaum (1985). Robust control oflinear time-invariant plants using periodic compensation.
  69. R Meyer,C Burrus (1975). A unified analysis of multirate and periodically time-varying digital filters.
  70. P Esquef,L Biscainho (2006). An efficient model-based multirate method for reconstruction of audio signals across long gaps.
  71. N Jayant,S Christensen (1981). Effects of Packet Losses in Waveform Coded Speech and Improvements Due to an Odd-Even Sample-Interpolation Procedure.
  72. P Wilson (1965). Measurement of loudspeaker characteristics.
  73. A Papoulis,P Ferreira (2001). Iterative and noniterative recovery of missing samplesfor 1-D band-limited signals.
  74. D Goodman,G Lockhart,O Waen,W Wong (1986). Waveform substitution techniques for recovering missing speech segmentsin packet voice communications.
  75. M Niediwiecki,K Cisowski (2001). Smart copying-a new approach to reconstruction of audio signals.
  76. Robert Maher (1994). Audio Forensic Interpretation of the Trump Rally Assassination Attempt (July 13, 2024).
  77. S Godsill,P Rayner (1998). Digital Audio Restoration-A Statistical Model Based Approach.
  78. S Montresor,J Valiere,J Allard,M Baudry (1991). Evaluation of two interpolation methods applied to old recordings restoration.
  79. B.-S Chen,Y.-L Chen (1995). Multirate modeling of AR/ARMA stochastic signals and its application to the combined estimation-interpolation problem.
  80. G Cocchi,A Uncini (2001). Subbands audio signal recovering using neural nonlinear prediction.
  81. S Vaseghi (1988). Algorithms for Restoration of Archived Gramophone Recordings.
  82. A Janssen,R Veldhuis,L Vries (1986). Adaptive interpolation of discrete-time signals that can be modeled as autoregressive processes.
  83. R Veldhuis (1990). Restoration of Lost Samples in Digital Signals.
  84. J Ruanaidh Andw,Fitzgerald (1994). Interpolation of missing samples for audio restoration.
  85. P Rayner,S Godsill (1991). The Detection and Correction of Artefacts in Degraded Gramophone Recordings.
  86. M Niedz´wiecki (1993). Statistical Reconstruction of Multivariate Time Series.
  87. S Godsill,P Rayner (1995). A Bayesian approach to the restoration of degraded audio signals.
  88. (1998). Statistical reconstruction and analysis of autoregressive signalsin impulsive noise using the Gibbs sampler.
  89. W Etter (1996). Restoration of a discrete-time signal segment by interpolation based on the left-sided and right-sided autoregressive parameters.
  90. I Kauppinen,K Roth (2001). Improved noise reduction in audio signals using spectral resolution enhancement with time-domain signal extrapolation.
  91. I Kauppinen,J Kauppinen (2002). Methods for detecting impulsive noise in speech and audio signals.
  92. I Kauppinen,K Roth (2002). Improved noise reduction in audio signals using spectral resolution enhancement with time-domain signal extrapolation.
  93. S Pavljasevic,F Dawson (2006). Synchronization to Disturbed Utility-Network Signals Using a Multi-rate Phase-Locked Loop.
  94. R Weidenbrüg,F Dawson (1993). New synchronization method for thyristor power converters to weak AC-systems.
  95. S Valiviita,S Ovaska (1998). Delayless method to generate current reference for active filters.
  96. M Fleyer,A Linden,M Horowitz,A Rosenthal (2010). Multi-rate Synchronous Sampling of Sparse Multiband Signals.
  97. Avi Zeitouny,Zeev Tamir,Alfred Feldster,Moshe Horowitz (2005). Optical sampling of narrowband microwave signals using pulses generated by electroabsorption modulators.
  98. Amir Rosenthal,Alex Linden,Moshe Horowitz (2008). Multirate asynchronous sampling of sparse multiband signals.
  99. Arthur Kohlenberg (1953). Exact Interpolation of Band-Limited Functions.
  100. P Feng,Y Bresler (1996). Spectrum-blind minimum-rate sampling andrecon struction of multiband signals.
  101. R Venkataramani,Y Bresler (2001). Optimal sub-Nyquist nonuniform sampling and reconstruction for multiband signals.
  102. Y Lu,M Do (2008). A Theory for Sampling Signals From a Union of Subspaces.
  103. M Mishali,Y Eldar (2009). Blind Multiband Signal Reconstruction: Compressed Sensing for Analog Signals.
  104. T Aach,H Fuehr Shift Variance Measures for Multi-rate LPSV Filter Banks with Random Input Signals.
  105. Ronald Crochiere,Lawrence Rabiner (1983). Multirate digital signal processing.
  106. C Loeffler,C Burrus (1984). Optimal design of periodically time-varying and multirate digital filters.
  107. A Mehr,Tongwen Chen (2002). Representations of linear periodically time-varying and multirate systems.
  108. J Wang,T Chen,B Huang (2005). On spectral theory of cyclo stationary signals in multirate systems.
  109. U Petersohn,N Fliege,H Unger (1994). Exact analysis of aliasing effects and non-stationary quantization noise in multirate systems.
  110. T Aach (2007). Comparative analysis of shift variance and cyclo stationarity in multirate filter-banks.
  111. T Aach,H Fuhr (2009). On Bounds of Shift Variance in Two-Channel Multirate Filter Banks.
  112. R Yu (2009). A new shift-invariance of discrete-time systems and its application to discrete wavelet transform analysis.
  113. K Chaudhury,M Unser (2010). On the shift ability of dual-tree complex wavelet transforms.
  114. Runyi Yu (2011). Shift-Variance Measure of Multichannel Multirate Systems.
  115. Til Aach,Hartmut Fuhr (2011). Shift variance, cyclostationarity and expected shift variance in multirate LPSV systems.
  116. Tongwen Chen,Li Qiu (1997). Linear periodically time-varying discrete-time systems: Aliasing and LTI approximations.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Dr. D V Srihari Babu. 2012. \u201cAdvancements of MultiRate Signal processing for Wireless Communication Networks: Current State Of the Art\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 12 (GJCST Volume 12 Issue E13): .

Download Citation

Issue Cover
GJCST Volume 12 Issue E13
Pg. 9- 22
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Classification
Not Found
Version of record

v1.2

Issue date

August 21, 2012

Language

English

Experiance in AR

The methods for personal identification and authentication are no exception.

Read in 3D

The methods for personal identification and authentication are no exception.

Article Matrices
Total Views: 10233
Total Downloads: 2667
2026 Trends
Research Identity (RIN)
Related Research

Published Article

With the hasty growth of internet contact and voice and information centric communications, many contact technologies have been urbanized to meet the stringent insist of high speed information transmission and viaduct the wide bandwidth gap among ever-increasing highdata-rate core system and bandwidth-hungry end-user complex. To make efficient consumption of the limited bandwidth of obtainable access routes and cope with the difficult channel environment, several standards have been projected for a variety of broadband access scheme over different access situation (twisted pairs, coaxial cables, optical fibers, and unchanging or mobile wireless admittance). These access situations may create dissimilar channel impairments and utter unique sets of signal dispensation algorithms and techniques to combat precise impairments. In the intended and implementation sphere of those systems, many research issues arise. In this paper we present advancements of multi-rate indication processing methodologies that are aggravated by this design trend. The thesis covers the contemporary confirmation of the current literature on intrusion suppression using multi-rate indication in wireless communiqué networks.

Our website is actively being updated, and changes may occur frequently. Please clear your browser cache if needed. For feedback or error reporting, please email [email protected]
×

This Page is Under Development

We are currently updating this article page for a better experience.

Request Access

Please fill out the form below to request access to this research paper. Your request will be reviewed by the editorial or author team.
X

Quote and Order Details

Contact Person

Invoice Address

Notes or Comments

This is the heading

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

High-quality academic research articles on global topics and journals.

Advancements of MultiRate Signal processing for Wireless Communication Networks: Current State Of the Art

Dr. D V Srihari Babu
Dr. D V Srihari Babu Jawaharlal nehru university - Hyderabad.
Dr. P Chandrashekhar Reddy
Dr. P Chandrashekhar Reddy

Research Journals