An Energy-Efficiency Multi-Relay Selection and Power Allocation Based on Deep Neural Network for Amplify-and-Forward Cooperative Transmission

2021 ◽  
pp. 1-1
Author(s):  
Yan-yan Guo ◽  
Jing Yang ◽  
Xiao-long Tan ◽  
Qian Liu
Keyword(s):  
Neural Network ◽  
Energy Efficiency ◽  
Power Allocation ◽  
Relay Selection ◽  
Deep Neural Network ◽  
Cooperative Transmission ◽  
Amplify And Forward

Power Allocation and Relay Selection Algorithm in Multi-Relay Amplify-and-Forward Networks

2014 ◽  
Vol 513-517 ◽  
pp. 3423-3428
Author(s):  
Zhi Kang Zhou ◽  
Qi Zhu
Keyword(s):  
Power Allocation ◽  
Relay Selection ◽  
Relay Network ◽  
Total Power ◽  
Selection Algorithm ◽  
Amplify And Forward ◽  
Power Constraint ◽  
Lower Complexity ◽  
Relay Selection Algorithm ◽  
The Ideal

In this paper, an amplify-and-forward (AF) multi-relay network is considered. In order to minimize the system outage probability, a new power allocation and multi-relay selection algorithm is proposed under total power constraint and each node power constraint. In the proposed algorithm, the ideal of ordering is adopted, which leads to the remarkable decrease of the computation complexity together with simple power reallocation. Simulation results show that the proposed multi-relay selection algorithm performs close to the optimal scheme with optimal power allocation and exhaustive search (OPA-ES) but with much lower complexity.

scholarly journals A Coordinated Direct AF/DF Relay-Aided NOMA Framework for Low Outage

2021 ◽  
Author(s):  
Anand Jee ◽  
KAMAL AGRAWAL ◽  
Shankar Prakriya
Keyword(s):  
Energy Efficiency ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Outage Probability ◽  
Closed Form ◽  
Power Allocation ◽  
Multiple Access ◽  
Performance Gain ◽  
Amplify And Forward ◽  
Decode And Forward

This paper investigates the performance of a framework for low-outage downlink non-orthogonal multiple access (NOMA) signalling using a coordinated direct and relay transmission (CDRT) scheme with direct links to both the near-user (NU) and the far-user (FU). Both amplify-and-forward (AF) and decode-and-forward (DF) relaying are considered. In this framework, NU and FU combine the signals from BS and R to attain good outage performance and harness a diversity of two without any need for feedback. For the NU, this serves as an incentive to participate in NOMA signalling. For both NU and FU, expressions for outage probability and throughput are derived in closed form. High-SNR approximations to the outage probability are also presented. We demonstrate that the choice of power allocation coefficient and target rate is crucial to maximize the NU performance while ensuring a desired FU performance. We demonstrate performance gain of the proposed scheme over selective decode-and-forward (SDF) CDRT-NOMA in terms of three metrics: outage probability, sum throughput and energy efficiency. Further, we demonstrate that by choosing the target rate intelligently, the proposed CDRT NOMA scheme ensures higher energy efficiency (EE) in comparison to its orthogonal multiple access counterpart. Monte Carlo simulations validate the derived expressions.

scholarly journals Linear Processing Design of Amplify-and-Forward Relays for Maximizing the System Throughput

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Qiang Wang ◽  
Tiejun Chen ◽  
Tingting Lan
Keyword(s):  
Power Allocation ◽  
Channel Assignment ◽  
Relay Selection ◽  
Permutation Matrix ◽  
System Throughput ◽  
Amplify And Forward ◽  
Processing Scheme ◽  
Optimal Linear ◽  
Fixed Power ◽  
Dual Domain

In this paper, firstly, we study the linear processing of amplify-and-forward (AF) relays for the multiple relays multiple users scenario. We regard all relays as one special “relay”, and then the subcarrier pairing, relay selection and channel assignment can be seen as a linear processing of the special “relay”. Under fixed power allocation, the linear processing of AF relays can be regarded as a permutation matrix. Employing the partitioned matrix, we propose an optimal linear processing design for AF relays to find the optimal permutation matrix based on the sorting of the received SNR over the subcarriers from BS to relays and from relays to users, respectively. Then, we prove the optimality of the proposed linear processing scheme. Through the proposed linear processing scheme, we can obtain the optimal subcarrier paring, relay selection and channel assignment under given power allocation in polynomial time. Finally, we propose an iterative algorithm based on the proposed linear processing scheme and Lagrange dual domain method to jointly optimize the joint optimization problem involving the subcarrier paring, relay selection, channel assignment and power allocation. Simulation results illustrate that the proposed algorithm can achieve a perfect performance.

scholarly journals A Coordinated Direct AF/DF Relay-Aided NOMA Framework for Low Outage

2021 ◽  
Author(s):  
Anand Jee ◽  
KAMAL AGRAWAL ◽  
Shankar Prakriya
Keyword(s):  
Energy Efficiency ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Outage Probability ◽  
Closed Form ◽  
Power Allocation ◽  
Multiple Access ◽  
Performance Gain ◽  
Amplify And Forward ◽  
Decode And Forward

This paper investigates the performance of a framework for low-outage downlink non-orthogonal multiple access (NOMA) signalling using a coordinated direct and relay transmission (CDRT) scheme with direct links to both the near-user (NU) and the far-user (FU). Both amplify-and-forward (AF) and decode-and-forward (DF) relaying are considered. In this framework, NU and FU combine the signals from BS and R to attain good outage performance and harness a diversity of two without any need for feedback. For the NU, this serves as an incentive to participate in NOMA signalling. For both NU and FU, expressions for outage probability and throughput are derived in closed form. High-SNR approximations to the outage probability are also presented. We demonstrate that the choice of power allocation coefficient and target rate is crucial to maximize the NU performance while ensuring a desired FU performance. We demonstrate performance gain of the proposed scheme over selective decode-and-forward (SDF) CDRT-NOMA in terms of three metrics: outage probability, sum throughput and energy efficiency. Further, we demonstrate that by choosing the target rate intelligently, the proposed CDRT NOMA scheme ensures higher energy efficiency (EE) in comparison to its orthogonal multiple access counterpart. Monte Carlo simulations validate the derived expressions.

scholarly journals Ineffectual Neuron Free Deep Learning Accelerator

2019 ◽  
Vol 8 (9) ◽  
pp. 2819-2826
Keyword(s):  
Neural Network ◽  
Energy Efficiency ◽  
Deep Learning ◽  
Visual Cortex ◽  
Computational Complexity ◽  
Image Recognition ◽  
Deep Neural Network ◽  
Improve Performance ◽  
High Efficient ◽  
Accelerator Design

Convolutional neural network (CNN) is actually a deep neural network which plays an important role in image recognition. The CNN recognizes images similar to visual cortex in our eyes. In this proposed work, an accelerator is used for high efficient convolutional computations. The main aim of using the accelerator is to avoid ineffectusal computations and to improve performance and energy efficiency during image recognition without any loss in accuracy. However, the throughput of the accelerator is improved by adding max-pooling function only. Since the CNN includes multiple inputs and intermediate weights for its convolutional computation, the computational complexity is increased enormously. Hence, to reduce the computational complexity of the CNN, a CNN accelerator is proposed in this paper. The accelerator design is simulated and synthesized in Cadence RTL compiler tool with 90nm technology library.

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