A Developed DS-CDMA Detection based on ICA

Sadkhan, Sattar B.

doi:10.1109/icict52195.2021.9568418

Cited by 5 publications

(1 citation statement)

References 13 publications

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“…In [7], a new DS-CDMA detector is designed based on chaotic neuron network that prevents equilibrium at local minima and achieves global minimum. In [8], fastICA algorithm is used for blind DS-CDMA detection, without any pilot or training sequences, by adopting Gold codes for signal separation. In [9], blind adaptive detection of DS-CDMA signal is implemented using the correlation matrix inversion which provides multi-accessinterference cancellation.…”

Section: Related Workmentioning

confidence: 99%

Smart DS-CDMA Receiver Based on Feed Forward Neural Network

Drakshayini

Kounte

2022

Advances in Parallel Computing

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Direct Sequence Code Division Multiple Access (DS-CDMA) is a schemewhere several users transmit their data simultaneously over a common wireless communication channel,by spreading each data by distinct codes. At the receiver, the individual data are detected by appropriate decoding. In this paper, a new smart receiver is proposed for detecting DS-CDMA signals based on a multi-layer Feed Forward Neural Network (FFNN). The proposed receiver detects the transmitted data when the received signal is distorted due to channel noise, near-far effect and Rayleigh fading. The channel state information is indirectly captured during the training of the FFNN and hence the conventional channel state estimation using pilot signal or training sequences is eliminated. Experimental results show that the performance of the proposed receiver in terms of detection accuracy is superior to similar competitive demodulators.

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Section: Related Workmentioning

confidence: 99%