Energy efficiency of cooperative D2D communications underlaying LTE-A networks

Device-to-device (D2D) communications underlaying LTE-A networks is expected to bring significant benefits for resource utilization and energy efficiency (EE) improvement of user equipment (UE). However, the allocation of radio and power resources to D2D communications needs elaborate coordination, because of the interference between D2D communications and cellular communications. In this paper, we propose an energy-efficient cooperative D2D communication (EECD2D) technique using a power allocation algorithm, aiming at maximizing EE introduced by D2D communications in LET-A networks. Specifically, we define four D2D and cellular combinations based on distances, and analyze average EE of EECD2D and that of cooperative D2D communications without optimization. Results show that average EE of our algorithm is much higher than that without optimization, and closer D2D cooperators and distant cellular UEs whose uplink resource is reused, achieve highest average energy efficiency.

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Energy-efficient power allocation in analogue network coding based multi-hop D2D communication

Proceedings of the Conference on Research in Adaptive and Convergent Systems - RACS '19 ◽

10.1145/3338840.3355651 ◽

2019 ◽

Author(s):

Pengfei Wu ◽

Jun Huang ◽

Longyan Xu

Keyword(s):

Power Allocation ◽

Network Coding ◽

Energy Efficient ◽

D2d Communication ◽

Efficient Power ◽

Analogue Network

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

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-201412 ◽

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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