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 On the Retrial-Queuing Model for Strategic Access and Equilibrium-Joining Strategies of Cognitive Users in Cognitive-Radio Networks with Energy Harvesting

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2088
Author(s):  
Kalpana Devarajan ◽  
Muthukrishnan Senthilkumar
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Performance Metrics ◽  
Stackelberg Game ◽  
Retrial Queue ◽  
Primary User ◽  
Secondary User ◽  
Single Server ◽  
Queuing Model ◽  
Secondary Users

This article studies the strategic access of single-server retrial queue with two types of customers, where priority is given according to their category. On the basis of this concept, a cognitive-radio network was developed as retrial queue with energy harvesting. Cognitive radio allows for a secondary user to opportunistically access the idle spectrum of a primary user (PU). Upon arrival of a primary user, the service given to the secondary user by the cognitive radio is interrupted, and the PU band is available for the primary user. After completion of service for the primary user, the PU band is again available to secondary users. Performance metrics are derived to study the equilibrium strategies of secondary users. A Stackelberg game was formulated and Nash equilibrium was derived for the noncooperative strategy of the secondary user. Game-theory concepts are incorporated with queuing theory ideas to obtain the net benefit for the noncooperative strategy and social benefit for cooperative strategy. Lastly, analytical results are verified with numerical examples, and the effects of energy-harvesting rate are discussed.

Energy Harvesting in Cognitive Networks Using Feasible Channel Selection Assignment

2020 ◽  
Vol 13 (2) ◽  
pp. 173-182
Author(s):  
M. Balasubramanian ◽  
V. Rajamani
Keyword(s):  
Cognitive Radio ◽  
Energy Harvesting ◽  
Primary User ◽  
Spectrum Management ◽  
Cognitive Networks ◽  
Secondary User ◽  
Spectrum Efficiency ◽  
Cognitive Radio Systems ◽  
Token Passing ◽  
Radio Systems

Background: The importance of this paper is to achieve maximum spectrum efficiency and proper channel allotment between Primary and Secondary User. The licensed and unlicensed users gets promoted as the channel allotment is properly carried out. To improve energy capability and spectral proficiency consider energy collecting cognitive radio systems to update both energy feasibility and spectral viability. Energy Harvesting Provides possibility of sharing energy in wireless networks which improves the performance of channel capacity. Methods: In this paper an Token Passing algorithm is proposed that switches the channels between Primary User and Secondary User. The energy efficiency decision is taken according to when primary user is idle or not. When the primary user is idle the secondary user cannot harvest any energy and when the primary channel is occupied the secondary channel harvest energy from primary user so that the harvested energy will be used by the secondary user during channel allotment. This proposed algorithm provides energy harvesting and spectrum efficiency. Results: The result shows that the most extraordinary achievable throughput R (eh) of the energy harvesting cognitive radio. The State Transition will move from busy to idle and idle to busy which is represented as S0 and S1. The other parameters are Sensing Energy es, Sampling frequency fs, Primary Signal which accepts a noise SNR γp. As Token Passing Algorithm provides tokens for primary and secondary user it takes lesser time and achieves better throughput than the FDMA and suboptimal algorithm. Conclusion: This paper achieves the maximum spectrum efficiency and energy harvesting by properly allotting spectrum for both primary and secondary user. The primary user and secondary user and spectrum management perform the channel allotment efficiently through the idle and busy state and Token Passing Algorithm does energy harvesting. An efficient scheme is developed for allocating energy in energy harvesting cognitive radio systems.

scholarly journals Design an Optimum Energy Harvesting Model for Bidirectional Cognitive Radio Networks

2021 ◽  
Author(s):  
Mohammad Kamrul Kamrul Hasan ◽  
Md. Monwar Jahan Chowdhury ◽  
Shakil Ahmed ◽  
Saifur Rahman Sabuj ◽  
Jamel Nibhen ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Cognitive Radio ◽  
Energy Harvesting ◽  
Outage Probability ◽  
Network Model ◽  
Cognitive Radio Network ◽  
Primary User ◽  
Battery Life ◽  
Radio Network ◽  
Wireless Devices

Abstract The energy efficiency and spectrum shortage problem of wireless devices has become a concern for researchers worldwide as the number of wireless devices increases at an unparalleled speed. Many new solutions have been proposed to extend mobile devices' battery life, such as wireless energy harvesting from traditional radio frequency signals to design new smart battery chips. This paper considers a cognitive radio network model where primary users have their specific licensed band, and secondary users equipped with necessary hardware required for energy harvesting can use the licensed band of the primary user by smart sensing capability. First, the expression of outage probability is theoretically derived for uplink and downlink scenarios. Moreover, maximum energy efficiency for both uplink and downlink in the cognitive radio network model subject to interference and noise is investigated here. The theoretical analysis is then evaluated. It has been observed that outage probability improves low harvested power in the downlink scenario and high harvested power in the uplink scenario. Finally, the result signifies that energy efficiency is improved using optimum power for uplink and downlink scenarios.

scholarly journals Optimum energy harvesting model for bidirectional cognitive radio networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Mohammad Kamrul Hasan ◽  
Md. Monwar J. Chowdhury ◽  
Shakil Ahmed ◽  
Saifur R. Sabuj ◽  
Jamel Nibhen ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Cognitive Radio ◽  
Energy Harvesting ◽  
Outage Probability ◽  
Primary User ◽  
Battery Life ◽  
Transmission Power ◽  
Wireless Devices ◽  
Harvesting Technique ◽  
Power And Energy

AbstractWireless devices’ energy efficiency and spectrum shortage problem has become a key concern worldwide as the number of wireless devices increases at an unparalleled speed. Wireless energy harvesting technique from traditional radio frequency signals is suitable for extending mobile devices’ battery life. This paper investigates a cognitive radio network model where primary users have their specific licensed band, and secondary users equipped with necessary hardware required for energy harvesting can use the licensed band of the primary user by smart sensing capability. Analytical expressions for considered network metrics, namely data rate, outage probability, and energy efficiency, are derived for uplink and downlink scenarios. In addition, optimal transmission power and energy harvesting power are derived for maximum energy efficiency in downlink and uplink scenarios. Numerical results show that outage probability improves high transmission power in the downlink scenario and high harvested power in the uplink scenario. Finally, the result shows that energy efficiency improves using optimum transmission power and energy harvesting power for downlink and uplink scenarios.

Joint user clustering and salp based particle swarm optimization algorithm for power allocation in MIMO-NOMA

2021 ◽  
Vol 40 (5) ◽  
pp. 9007-9019
Author(s):  
Jyotirmayee Subudhi ◽  
P. Indumathi
Keyword(s):  
Energy Efficiency ◽  
Particle Swarm Optimization ◽  
Power Allocation ◽  
Multiple Access ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Swarm Optimization ◽  
Allocation Algorithm ◽  
User Clustering ◽  
Sum Rate

Non-Orthogonal Multiple Access (NOMA) provides a positive solution for multiple access issues and meets the criteria of fifth-generation (5G) networks by improving service quality that includes vast convergence and energy efficiency. The problem is formulated for maximizing the sum rate of MIMO-NOMA by assigning power to multiple layers of users. In order to overcome these problems, two distinct evolutionary algorithms are applied. In particular, the recently implemented Salp Swarm Algorithm (SSA) and the prominent Optimization of Particle Swarm (PSO) are utilized in this process. The MIMO-NOMA model optimizes the power allocation by layered transmission using the proposed Joint User Clustering and Salp Particle Swarm Optimization (PPSO) power allocation algorithm. Also, the closed-form expression is extracted from the current Channel State Information (CSI) on the transmitter side for the achievable sum rate. The efficiency of the proposed optimal power allocation algorithm is evaluated by the spectral efficiency, achievable rate, and energy efficiency of 120.8134bits/s/Hz, 98Mbps, and 22.35bits/Joule/Hz respectively. Numerical results have shown that the proposed PSO algorithm has improved performance than the state of art techniques in optimization. The outcomes on the numeric values indicate that the proposed PSO algorithm is capable of accurately improving the initial random solutions and converging to the optimum.

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