Joint relay assignment and energy‐efficiency maximization in energy‐harvesting downlink/uplink clustered nonorthogonal multiple‐access networks

2020 ◽  
Vol 31 (6) ◽  
Author(s):  
Mohammed W. Baidas
Keyword(s):  
Energy Efficiency ◽  
Energy Harvesting ◽  
Multiple Access ◽  
Access Networks ◽  
Relay Assignment

scholarly journals Secrecy Energy Efficiency Maximization in an Underlying Cognitive Radio–NOMA System with a Cooperative Relay and an Energy-Harvesting User

2020 ◽  
Vol 10 (10) ◽  
pp. 3630 ◽  
Author(s):  
Carla E. Garcia ◽  
Mario R. Camana ◽  
Insoo Koo
Keyword(s):  
Energy Efficiency ◽  
Cognitive Radio ◽  
Energy Harvesting ◽  
Multiple Access ◽  
Pso Algorithm ◽  
Critical Issue ◽  
Primary User ◽  
Secondary User ◽  
Cooperative Relay ◽  
Security Issue

Security is considered a critical issue in the deployment of 5G networks because of the vulnerability of information that can be intercepted by eavesdroppers in wireless transmission environments. Thus, physical layer security has emerged as an alternative for the secure enabling of 5G technologies and for tackling this security issue. In this paper, we study the secrecy energy efficiency (SEE) in a downlink underlying cognitive radio (CR)—non-orthogonal multiple access (NOMA) system with a cooperative relay. The system has an energy-harvesting (EH) user and an eavesdropper, where the transmitter provides direct communication with a close secondary user and a distant secondary user via the relay. Our objective is to maximize the SEE of the CR-NOMA system under the constraints of a minimum information rate for the secondary users, a minimum amount of energy harvested by the EH user, and maximum power availability at the transmitter and the relay that still prevents them from causing unacceptable interference with the primary user. The proposed solution to maximize the SEE is based on the low-computational—complexity particle swarm optimization (PSO) algorithm. For validation purposes, we compare the optimization outcomes obtained by the PSO algorithm with the optimal exhaustive search method. Furthermore, we compare the performance of our proposed CR-NOMA scheme with the conventional orthogonal multiple access (OMA) scheme.

scholarly journals Outage performance analysis of relay-aided non-orthogonal multiple access networks with energy harvesting schemes

2020 ◽  
Vol 14 (17) ◽  
pp. 3013-3021
Author(s):  
Hong T. Nguyen ◽  
Nam-Phong Nguyen ◽  
Tien-Hoa Nguyen ◽  
Chuyen T. Nguyen
Keyword(s):  
Performance Analysis ◽  
Energy Harvesting ◽  
Multiple Access ◽  
Access Networks ◽  
Outage Performance

scholarly journals Age of Information in Energy Harvesting Aided Massive Multiple Access Networks

2022 ◽  
pp. 1-1
Author(s):  
Zhengru Fang ◽  
Jingjing Wang ◽  
Yong Ren ◽  
Zhu Han ◽  
H. Vincent Poor ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Multiple Access ◽  
Access Networks ◽  
Age Of Information

Wireless Sensor Network in IoT and Performance Optimization

2020 ◽  
Vol 13 ◽  
Author(s):  
Sunita Gupta ◽  
Sakar Gupta ◽  
Dinesh Goyal
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Energy Harvesting ◽  
Performance Optimization ◽  
Design Space ◽  
Life Time ◽  
Wireless Sensor ◽  
Topology Management ◽  
Management Application ◽  
Energy Latency

: A serious problem in Wireless Sensor Networks (WSNs) is to attain high-energy efficiency as battery is used to power and have limited stored energy. They can’t be suitably replaced or recharged. Appearance of renewable energy harvesting techniques and their combination with sensor devices gives Energy Harvesting Wireless Sensor Networks (EHWSNs). IoT is now becoming part of our lives, comforting simplifying our routines and work life. IoT is very popular . It connects together, computes, communicates and performs the required task. IoT is actually a network of physical devices or things that can interact with each other to share information. This paper gives an overview of WSN and IoT, related work, different ways of connecting WSN with internet, development of smart home, challenges for WSN etc. Next a Framework for performance optimization in IoT is given and QC-PC-MCSC heuristic is analyzed in terms of Energy Efficiency and Life Time of a sensor on Energy Latency Density Design Space, a topology management application that is power efficient. QC-PC-MCSC and QC-MCSC are compared for Energy Efficiency and Life Time of a sensor over energy latency density design space, a topology management application.

Resource Allocation Based on User Pairing and Subcarrier Matching for Downlink Non-Orthogonal Multiple Access Networks

2021 ◽  
Vol 8 (3) ◽  
pp. 679-689
Author(s):  
Zhixin Liu ◽  
Changjian Liang ◽  
Yazhou Yuan ◽  
Kit Yan Chan ◽  
Xinping Guan
Keyword(s):  
Resource Allocation ◽  
Multiple Access ◽  
Access Networks ◽  
User Pairing

scholarly journals User Clustering and Power Allocation for Energy Efficiency Maximization in Downlink Non-Orthogonal Multiple Access Systems

2021 ◽  
Vol 11 (2) ◽  
pp. 716
Author(s):  
Ruibiao Chen ◽  
Fangxing Shu ◽  
Kai Lei ◽  
Jianping Wang ◽  
Liangjie Zhang
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Multiple Access ◽  
Spectrum Efficiency ◽  
Lagrangian Multiplier ◽  
Efficiency Gain ◽  
Optimal Power Allocation ◽  
Optimal Power ◽  
User Clustering ◽  
Cluster Dynamic

Non-orthogonal multiple access (NOMA) has been considered a promising technique for the fifth generation (5G) mobile communication networks because of its high spectrum efficiency. In NOMA, by using successive interference cancellation (SIC) techniques at the receivers, multiple users with different channel gain can be multiplexed together in the same subchannel for concurrent transmission in the same spectrum. The simultaneously multiple transmission achieves high system throughput in NOMA. However, it also leads to more energy consumption, limiting its application in many energy-constrained scenarios. As a result, the enhancement of energy efficiency becomes a critical issue in NOMA systems. This paper focuses on efficient user clustering strategy and power allocation design of downlink NOMA systems. The energy efficiency maximization of downlink NOMA systems is formulated as an NP-hard optimization problem under maximum transmission power, minimum data transmission rate requirement, and SIC requirement. For the approximate solution with much lower complexity, we first exploit a quick suboptimal clustering method to assign each user to a subchannel. Given the user clustering result, the optimal power allocation problem is solved in two steps. By employing the Lagrangian multiplier method with Karush–Kuhn–Tucker optimality conditions, the optimal power allocation is calculated for each subchannel. In addition, then, an inter-cluster dynamic programming model is further developed to achieve the overall maximum energy efficiency. The theoretical analysis and simulations show that the proposed schemes achieve a significant energy efficiency gain compared with existing methods.

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