Dual Hop Differential Amplify-and-Forward relaying with selection combining cooperative diversity over Nakagami-m fading channels

Harb, Mariam M.; Al-Mistarihi, Mamoun F.

doi:10.1109/iccsn.2016.7586654

Cited by 9 publications

(12 citation statements)

References 10 publications

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“…Furthermore, we propose and investigate the impact of NN-based RTN on the AF relaying network. • Further, without CSI knowledge, the amplification factor for the conventional AF relay node becomes a fixed value depending on the second-order statistics of the channel between the source to relay node and noise variances [22]- [28]. It is evident that fixed amplification factor is a sub-optimal approach for the AF scheme, thus, we also show that by utilizing a power normalization layer that normalizes the transmission power of n symbols to n at the AF relay node, we can improve the process of deciding the amplification factor, while keeping the signal transmission-reception in the analog domain and removing the requirement of second-order channel statistics and noise variances at the relay and CSI knowledge at the destination node.…”

Section: B Contributionsmentioning

confidence: 99%

“…without the CSI knowledge, we utilize traditional differential modulation and demodulation techniques at the source and destination node, such as differential QPSK (d-QPSK) and MLD decoding. The traditional differential schemes are near optimal because there is no selection combining cooperative diversity at the destination nodes [22]- [28]. However, the amplification factor designed in (2) utilizes the channel gain information and noise variances.…”

Section: System Modelmentioning

confidence: 99%

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End-to-End Learning-Based Framework for Amplify-and-Forward Relay Networks

Gupta

Sellathurai

2021

IEEE Access

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We study end-to-end learning-based frameworks for amplify-and-forward (AF) relay networks, with and without the channel state information (CSI) knowledge. The designed framework resembles an autoencoder (AE) where all the components of the neural network (NN)-based source and destination nodes are optimized together in an end-to-end manner, and the signal transmission takes place with an AF relay node. Unlike the literature that employs an NN-based relay node with full CSI knowledge, we consider a conventional relay node that only amplifies the received signal using CSI gains. Without the CSI knowledge, we employ power normalization-based amplification that normalizes the transmission power of each block of symbols. We propose and compare symbol-wise and bit-wise AE frameworks by minimizing categorical and binary cross-entropy loss that maximizes the symbol-wise and bit-wise mutual information (MI), respectively. We determine the estimated MI and examine the convergence of both AE frameworks with signal-to-noise ratio (SNR). For both these AE frameworks, we design coded modulation and differential coded modulation, depending upon the availability of CSI at the destination node, that obtains symbols in 2n-dimensions, where n is the block length. To explain the properties of the 2n-dimensional designs, we utilize various metrics like minimum Euclidean distance, normalized second-order and fourth-order moments, and constellation figures of merit. We show that both these AE frameworks obtain similar spherical coded-modulation designs in 2n-dimensions, and bit-wise AE that inherently obtains the optimal bit-labeling outperforms symbol-wise AE (with faster convergence under low SNR) and the conventional AF relay network with a considerable SNR margin.INDEX TERMS Amplify-and-forward, autoencoder, feed-forward neural networks, learning, and relay networks.

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Section: B Contributionsmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

End-to-End Learning-Based Framework for Amplify-and-Forward Relay Networks

Gupta

Sellathurai

2021

IEEE Access

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“…In Section 6, a conclusion about this article is given. It is worth mentioning that preliminary analytical derivations and results of this work have been presented in Reference 56.…”

Section: Introductionmentioning

confidence: 99%

On the performance analysis of dual hop relaying systems using differential amplify‐and‐forward along with post‐detection selection combining techniques over Nakagami‐m fading channels

Al-Mistarihi

Harb

Darabkh

et al. 2020

Trans Emerging Tel Tech

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The proposed work analyzes the performance of dual‐hop relaying systems by means of the differential amplify‐and‐forward relaying method. The post‐detection selection combining reception scheme proposed in this article allows receivers to approximate existing fading gain in a branch by using previously received samples to achieve a cooperative diversity at cases that exclude the need of having explicit channel estimation. Assuming independent fading channels, tight closed‐form expressions for the system bit error rate and outage probability are ultimately derived considering Nakagami‐m fading channels and additive white Gaussian noise. Different fading parameters were used to plot simulation results.

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“…These methods are easy to implement but they don't utilize the channel efficiently. Amplify-and-Forward (AF) and the DF relaying techniques were explained in [16][17][18][19][20][21][22][23][24][25][26]. On the other hand, in [27,28], the authors derived the BER and the OP of Rayleigh channels with AF fixed relaying.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of decode and forward cooperative diversity systems over nakagami-m fading channels with non-identical interferers

Al-Mistarihi

Mohaisen

Darabkh

2020

IJECE

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The deficiencies of regular cooperative relaying schemes were the main reason behind the development of Incremental Relaying (IR). Fixed relaying is one of the regular cooperative relaying schemes and it relies on using the relay node to help in transmitting the signal of the source towards the destination despite the channel’s condition. However, adaptive relaying methods allocate the channel resources efficiently; thus, such methods have drawn the attention of researchers in recent years. In this study, we analyze a two-hop Decode-and-Forward (DF) IR system’s performance via Nakagami-m fading channels with the existence of the several L distinguishable interferers placed close to the destination which diminishes the overall performance of the system due to the co-channel interference. Tight formulas for the Bit Error Rate (BER) and the Outage Probability (OP) are drawn. The assumptions are consolidated by numerical calculations.

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Dual Hop Differential Amplify-and-Forward relaying with selection combining cooperative diversity over Nakagami-m fading channels

Cited by 9 publications

References 10 publications

End-to-End Learning-Based Framework for Amplify-and-Forward Relay Networks

End-to-End Learning-Based Framework for Amplify-and-Forward Relay Networks

On the performance analysis of dual hop relaying systems using differential amplify‐and‐forward along with post‐detection selection combining techniques over Nakagami‐m fading channels

Performance evaluation of decode and forward cooperative diversity systems over nakagami-m fading channels with non-identical interferers

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