Receiver Design for Uplink Multiuser Code Division Multiple Access Communication System Based on Neural Network

Abstract

In this paper, we consider the receiver design problem for the uplink multiuser code division multiple access (CDMA) communication system based on the neural network technique. The uplink multiuser CDMA communication system model is described in the form of space-time domain through antenna array and multipath fading expression. Novel suitable neural network technique is proposed as an effective signal processing method for the receiver of such an uplink multiuser CDMA system. By the appropriate choice of the channel state information for the neural network parameters, the neural network can collectively resolve the effects of both the inter-symbol interference due to the multipath fading channel and the multiple access interference in the receiver of the uplink multiuser CDMA communication system. The dynamics of the proposed neural network receiver for the uplink multiuser CDMA communication system is also studied.

Big Data Perspective and Challenges in Next Generation Networks

“…Zheng et al [89] suggested that non-linearity such as inter-symbol interference and multipath fading in core division multiple access (CDMA) technique can be overcome by using multilayer feed forward neural networks (ML-FFNN). The authors in [89] described that ML-FFNN can efficiently reconstruct the signal removing non-linearity. Similarly, for 4G LTE networks, MIMO-OFDM has been adapted.…”

Acquisition of PN sequences using multilayer perceptron neural network adaptive processor for multiuser detection in spread‐spectrum communication systems

“…In the last 2 decades, these researches also picked up the possibility of solving this problem using ANNs. Different architectures of ANNs have been successfully used in DS‐CDMA multiuser detection (MUD) using different training algorithms . All these research activities did not take into consideration the CFAR technique.…”

“…Different architectures of ANNs have been successfully used in DS-CDMA multiuser detection (MUD) using different training algorithms. [27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42] All these research activities did not take into consideration the CFAR technique. Note that this technique was considered for the first time in my knowledge by Benkrinah et al 43 but only for nonhomogeneous AWGN channel.…”

Efficient complex radial basis function model for multiuser detection in a space division multiple access/multiple‐input multiple‐output–orthogonal frequency division multiplexing system

“…This problem can be resolved by employing highly non-linear classifiers such as artificial neural networks (ANNs) [20]. During the past decade, these ANN models have been extensively utilised as multiuser detectors for code division multiple access system [21][22][23][24][25], but not applied for the SDMA-OFDM system. In this literature, we have tried to explore the possibility of using ANN-based MUD schemes in such systems.…”