scholarly journals Adaptive Relay Selection Scheme Based on Bayesian Inference (AS-BI) for Cooperative Communication in 5G Networks

TEM Journal ◽  
2021 ◽  
pp. 839-846
Author(s):  
Madeeha Ishtiaq ◽  
Shakeel A. Waqas ◽  
Muhammad Saifullah ◽  
Nazih K. Mallat

In this paper, a Bayesian inference-based relay selection scheme, also called Adaptive Selection on Bayesian Inference (AS-BI) for cooperative networks in 5G networks is invoked. This scheme works on the principle of Amplify-and-Forward (AF) protocol which selects the most optimal relay towards the destination. This paper proposed a probabilitybased relay selection scheme in which posterior probability is calculated for the selection of relay node based on the prior and conditional probabilities. The proposed scheme has been accepted as optimal solution for relay selection, which significantly enhances the network performance by reducing (BER) for constant SNR.


2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Jie Li ◽  
Jianrong Bao ◽  
Shenji Luan ◽  
Bin Jiang ◽  
Chao Liu

To improve the reliability and efficiency in cooperative communications, a power optimized single relay selection scheme is proposed by increasing the diversity effort with an improved link-adaptive-regenerative (ILAR) protocol. The protocol determines the forwarding power of a relay node by comparing the signal-to-noise ratio (SNR) at both sides of the node; thus it improves the power efficiency. Moreover, it also proposes a single relay selection strategy to maximize the instantaneous SNR product, which ensures the approximate best channel link quality for good relay forwarding. And the system adjusts the forwarding power in real time and also selects the best relay node participated in the cooperative forwarding. In addition, the cooperation in the protocol is analyzed and the approximate expression of the bit-error-rate (BER) and the outage probability at high SNRs are also derived. Simulation results indicate that the BER and outage probability of the relay selection scheme by the ILAR protocol outperform other contrast schemes of current existing protocols. At BER of 10−2, the proposed scheme with ILAR protocol outperforms those of the decoded-and-forward (DF), the selected DF (SDF), and the amplify-and-forward (AF) protocols by 3.5, 3.5 and 7 dB, respectively. Moreover, the outage probability of the relay system decreases with the growth of the relay number. Therefore, the proposed relay selection scheme with ILAR strategies can be properly used in cooperative communications for good reliability and high power efficiency.







Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6284
Author(s):  
Donatella Darsena ◽  
Giacinto Gelli ◽  
Ivan Iudice ◽  
Francesco Verde

While the combination of multi-antenna and relaying techniques has been extensively studied for Long Term Evolution Advanced (LTE-A) and Internet of Things (IoT) applications, it is expected to still play an important role in 5th Generation (5G) networks. However, the expected benefits of these technologies cannot be achieved without a proper system design. In this paper, we consider the problem of jointly optimizing terminal precoders/decoders and relay forwarding matrices on the basis of the sum mean square error (MSE) criterion in multiple-input multiple-output (MIMO) two-way relay systems, where two multi-antenna nodes mutually exchange information via multi-antenna amplify-and-forward relays. This problem is nonconvex and a local optimal solution is typically found by using iterative algorithms based on alternating optimization. We show how the constrained minimization of the sum-MSE can be relaxed to obtain two separated subproblems which, under mild conditions, admit a closed-form solution. Compared to iterative approaches, the proposed design is more suited to be integrated in 5G networks, since it is computationally more convenient and its performance exhibits a better scaling in the number of relays.



2015 ◽  
Vol 64 (2) ◽  
pp. 553-565 ◽  
Author(s):  
Zhao Tian ◽  
Gaojie Chen ◽  
Yu Gong ◽  
Zhi Chen ◽  
Jonathon A. Chambers




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