One of the challenging issues in Spread-Spectrum Modulation (SSM) is the design of the Pseudo – Random or Pseudo - Noise (PN) sequence generator. Though several approaches are available that deals with the PN – sequence generator, there always exists the possibility of exploring the use of innovative methods through which shortcomings of the known techniques can be minimized and the performance of communication systems using SSM improved. This work is related to the use of Artificial Neural Network (ANN) for generation of the PN sequence during transmission and reception of a SSM based system. The benefit of the ANN - assisted PN generator shall be that it will simplify the design process of the PN - generator and yet provide high reliability against disruptions due to intentional disruptions and degradation of signal quality resulting out of variations in channel condition. The experiments carried out show that the ANN - assisted system is robust enough to deal with the unpredictability in the wireless channels and provide satisfactory performance under Gaussian and Rayleigh /Rician fading. The performance of the SSM system can be further enhanced by the use of coding. Hamming and cyclic redundancy check (CRC) codes have been used here with the data stream to explore if performance of the SSM system is improved further.
"PERFORMANCE COMPARISON OF SPREAD SPECTRUM MODULATION FOR WIRELESS CHANNELS USING ANN – ASSISTED PSEUDO - NOISE SEQUENCE GENERATOR,"
International Journal of Electronics Signals and Systems: Vol. 3:
4, Article 4.
Available at: https://www.interscience.in/ijess/vol3/iss4/4