Cluster Computing

, Volume 22, Supplement 4, pp 8371–8378 | Cite as

Coded downlink MIMO MC-CDMA system for cognitive radio network: performance results

  • B. RammyaaEmail author
  • K. S. Vishvaksenan
  • Sumathi Poobal
  • M. Mohana Mouli Krishnan


In this letter, the error-rate (ER) performance of multiple input and multiple output multi-carrier code-division-multiple-access (MIMO MC-CDMA) is evaluated with the aid of cognitive radio network (CRN). MIMO is proven to be useful for high data rate application. MC-CDMA is used to accommodate higher number of user by eliminating channel impairments. CRN is suggested for 5G network to offer higher bandwidth by exposing idle spectrum. Multi-carrier modulation is processed inverse fast-Fourier transform at transmitter and demodulation at each receiver using fast-Fourier transform. Multi-carrier technique is introduced to obtain bandwidth efficiency and overcome the problem of frequency selectivity. At each mobile station, we estimate user’s information using MMSE based iterative algorithm. Further; the system performance is tested using channel encoder. We structure channel encoder using turbo code which is designed with the help of two convolutional encoder. The input information is interleaved using random interleaver and is fed to second convolutional encoder. We create puncturing matrix using input information and output of two convolutional encoders. Then we puncture parity bit information to obtain necessary code rate. Further, we decode and estimate information using iterative decoder which ensure higher performance with lower signal-to-noise ratio. It is vindicated from simulations that CRN based MIMO MC-CDMA system with iterative decoder swell better ER while ensuring higher data rate for downlink signal transmission.


Code division multiple-access (CDMA) Cognitive radio network (CRN) Log-MAP turbo decoder Multi-carrier (MC) communication Multi-user interference (MUI) Multiple-input multiple-output (MIMO) Primary user interference (PUI) 


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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • B. Rammyaa
    • 1
    Email author
  • K. S. Vishvaksenan
    • 2
  • Sumathi Poobal
    • 3
  • M. Mohana Mouli Krishnan
    • 2
  1. 1.Department of EIEKCG College of TechnologyChennaiIndia
  2. 2.Department of ECESSN College of EngineeringChennaiIndia
  3. 3.Department of ECEKCG College of TechnologyChennaiIndia

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