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Machine learning-optimized relay selection method for mitigating interference in next generation communication networks

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Abstract

In an effective Wireless Network (WN), low latency and reliability are essential to provide adequate infrastructure for better communication. Cooperative Communication is one efficient way to achieve these wireless network goals. In this research, the machine learning-based Decode and Forward (DF) coding was developed in conjunction with the network coding algorithm to improve cooperative communication and system functionality that select relays which will not cause interference in a wireless network. Here, the Interference-Thwarting Relay Selection (ITRS) technique is intended to aid reliable communication while reducing self-interference. It is possible to monitor and measure suitable relays in the communication process with the help of a machine learning system. Thus, the proposed Interference-Thwarting Relay Selection technique is implemented with the parameters like Bit Error Rate (BER) as 10−6, Signal to Noise Ratio (SNR) as 36 dB, Symbol Error Rate (SER) as 10−8 and throughput with the power allocation factors. The simulated Machine Learning-Optimized Relay Selection Method (ML-ORSM) results achieve the improved optimal power allocation with symbol error rate.

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Data availability statement

Data sharing applies to this article on request.

Abbreviations

ANN:

Artificial neural network

AF:

Amplify-and-forward

BER:

Bit error rate

BRSS:

Best relay selection scheme

BRS-DF:

Best relay selection based decode & forward

CSI:

Channel state information

CRS-No-NC:

Conventional relay selection with no network coding

DF:

Decode-and-forward

DRS-NC:

Dual relay selection with network coding

DT:

Direct transmission

FD-AF-RN:

Full duplex amplify and forward relay networks

ITRS:

Interference thwarting relay selection

SNR:

Signal to noise ratio

SER:

Symbol error rate

MCS:

Modulation & coding scheme

ML-ORSM:

Machine learning-optimal relay selection method

ORSM:

Optimal relay selection method

RP-DF:

Relay participate decode and forward

SRS-NC:

Single relay selection with network coding

NC-No-RS:

Network coding with no relay selection

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Author notes

  1. P. Sivakumar

    Present address: Department of ECE, Dr. N.G.P Institute of Technology, Coimbatore, India

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  1. Department of ECE, Kingston Engineering College, Vellore, India

    M. Rathika

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  1. M. Rathika
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Rathika, M., Sivakumar, P. Machine learning-optimized relay selection method for mitigating interference in next generation communication networks. Wireless Netw 29, 1969–1981 (2023). https://doi.org/10.1007/s11276-023-03258-z

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