Transmit antenna selection in cognitive relay networks with Nakagami-m fading

2013 ◽  
Author(s):  
Phee Lep Yeoh ◽  
Maged Elkashlan ◽  
Trung Q. Duong ◽  
Nan Yang ◽  
Daniel Benevides da Costa
Keyword(s):  
Antenna Selection ◽  
Relay Networks ◽  
Transmit Antenna Selection ◽  
Cognitive Relay Networks

Transmit Antenna Selection for Interference Management in Cognitive Relay Networks

2014 ◽  
Vol 63 (7) ◽  
pp. 3250-3262 ◽  
Author(s):  
Phee Lep Yeoh ◽  
Maged Elkashlan ◽  
Trung Q. Duong ◽  
Nan Yang ◽  
Daniel Benevides da Costa
Keyword(s):  
Antenna Selection ◽  
Interference Management ◽  
Relay Networks ◽  
Transmit Antenna Selection ◽  
Cognitive Relay Networks ◽  
Selection For

scholarly journals Secure Transmission for Simultaneous Wireless Information and Power Transfer in AF Untrusted Relay Networks

Sensors ◽  
2018 ◽  
Vol 19 (1) ◽  
pp. 76 ◽  
Author(s):  
Hui Shi ◽  
Weiwei Yang ◽  
Dechuan Chen ◽  
Yunpeng Luo ◽  
Yueming Cai
Keyword(s):  
Outage Probability ◽  
Antenna Selection ◽  
Signal To Noise Ratio ◽  
Relay Networks ◽  
Optimal Number ◽  
Maximal Ratio Combining ◽  
High Signal ◽  
Secrecy Outage Probability ◽  
Transmit Antenna Selection ◽  
Untrusted Relay

This paper investigates secure communications of energy harvesting untrusted relay networks, where the destination assists jamming signal to prevent the untrusted relay from eavesdropping and to improve the forwarding ability of the energy constrained relay. Firstly, the source and the destination transmit the signals to the relay with maximal ratio transmission (MRT) technique or transmit antenna selection (TAS) technique. Then, the destination utilizes maximal ratio combining (MRC) technique or receive antenna selection (RAS) technique to receive the forwarded information. Therefore, four transmission and reception schemes are considered. For each scheme, the closed-form expressions of the secrecy outage probability (SOP) and the connection outage probability (COP) are derived. Besides, the effective secrecy throughput (EST) metric is analyzed to achieve a good tradeoff between security and reliability. In addition, the asymptotic performance of EST is also considered at the high signal-to-noise ratio (SNR). Finally, simulation results illustrate that: (1) the EST of the system with MRT and MRC scheme are superior to other schemes, however, in the high SNR regime, the EST of the system with MRT scheme is inferior to TAS; and (2) for the source node, there exists an optimal number of antennas to maximize the EST of the proposed schemes.

scholarly journals Machine Learning-Based Antenna Selection in Untrusted Relay Networks

2019 ◽  
Author(s):  
Rugui Yao ◽  
Yuxin Zhang ◽  
Nan Qi ◽  
Theodoros A. Tsiftsis
Keyword(s):  
Machine Learning ◽  
Antenna Selection ◽  
Relay Networks ◽  
Support Vector ◽  
Secrecy Outage Probability ◽  
Secrecy Rate ◽  
Transmit Antenna Selection ◽  
K Nearest Neighbors ◽  
Selection Scheme ◽  
Untrusted Relay

This paper studies the transmit antenna selection based on machine learning (ML) schemes in untrusted relay networks. First, we state the conventional antenna selection scheme. Then, we implement three ML schemes, namely, the support vector machine-based scheme, the naive-Bayes-based scheme, and the k-nearest neighbors-based scheme, which are applied to select the best antenna with the highest secrecy rate. The simulation results are presented in terms of system secrecy rate and secrecy outage probability. From the simulation, we can conclude that the proposed ML-based antenna selection schemes can achieve the same performance without amplification at the relay, or small performance degradation with transmitted power constraint at the relay, comparing with conventional schemes. However, when the training is completed, the proposed schemes can perform the antenna selection with a small computational complexity.

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