Abstract

Due to the complex and variable environments of mobile communication, the mobile multiuser networks become a hot topic. To process active complex event in mobile multiuser networks, it is important to predict the system performance. In this work, the authors consider the multiuser networks which utilizes transmit antenna selection (TAS). We derive novel closed-form expressions for the outage probability (OP) in terms of the Meijer's G-function. Then, a extreme learning machine (ELM)-based OP performance prediction algorithm is proposed. We use the theoretical results to generate training data. We test back-propagation (BP) neural network, locally weighted linear regression (LWLR), wavelet neural network, ELM, and support vector machine (SVM) methods. Compared with wavelet neural network, SVM, BP neural network, and LWLR methods, the Monte-Carlo results shows that the proposed prediction algorithm can consistently achieve higher OP performance prediction results.

Highlights

  • In recent years, 5G mobile wireless network has developed rapidly [1]–[4]. 5G mobile wireless network can support higher capacity, and higher density of mobile users [5]–[7]

  • To improve the quality of service (QoS), multiple-input multiple-output (MIMO) and cooperative communication have been employed in mobile multiuser networks

  • The contributions are as follows: First, considering transmit antenna selection (TAS), we investigate the mobile multiuser networks with amplifyand-forward (AF) relaying over the N-Nakagami fading channels.We derive the novel exact closed-form mathematical expressions for outage probability (OP)

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Summary

INTRODUCTION

5G mobile wireless network has developed rapidly [1]–[4]. 5G mobile wireless network can support higher capacity, and higher density of mobile users [5]–[7]. The outage performance of dual-hop multiuser relay systems was investigated in [14]. H. Wang et al.: OP Performance Prediction for Complex Mobile Multiuser Networks Based on ELM. Reference [26] proposed an online channel estimation and equalization scheme using fully complex ELM for OFDM systems. There is a lack of research on QoS prediction of mobile multiuser networks due to the complex and variable environments. The contributions are as follows: First, considering transmit antenna selection (TAS), we investigate the mobile multiuser networks with amplifyand-forward (AF) relaying over the N-Nakagami fading channels.We derive the novel exact closed-form mathematical expressions for OP. We propose the ELM-based OP performance prediction algorithm.

THE SYSTEM MODEL
ELM NEURAL NETWORK STRUCTURE
NUMERICAL RESULTS
CONCLUSION
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