scholarly journals Novel Resource Allocation Techniques for Downlink Non-Orthogonal Multiple Access Systems

2020 ◽  
Vol 10 (17) ◽  
pp. 5892 ◽  
Author(s):  
Zuhura J. Ali ◽  
Nor K. Noordin ◽  
Aduwati Sali ◽  
Fazirulhisyam Hashim ◽  
Mohammed Balfaqih
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Power Allocation ◽  
Multiple Access ◽  
High Capacity ◽  
Kkt Conditions ◽  
Optimal Power Allocation ◽  
User Pairing ◽  
Optimal Power ◽  
Sum Rate

Non-orthogonal multiple access (NOMA) plays an important role in achieving high capacity for fifth-generation (5G) networks. Efficient resource allocation is vital for NOMA system performance to maximize the sum rate and energy efficiency. In this context, this paper proposes optimal solutions for user pairing and power allocation to maximize the system sum rate and energy efficiency performance. We identify the power allocation problem as a nonconvex constrained problem for energy efficiency maximization. The closed-form solutions are derived using Karush–Kuhn–Tucker (KKT) conditions for maximizing the system sum rate and the Dinkelbach (DKL) algorithm for maximizing system energy efficiency. Moreover, the Hungarian (HNG) algorithm is utilized for pairing two users with different channel condition circumstances. The results show that with 20 users, the sum rate of the proposed NOMA with optimal power allocation using KKT conditions and HNG (NOMA-PKKT-HNG) is 6.7% higher than that of NOMA with difference of convex programming (NOMA-DC). The energy efficiency with optimal power allocation using DKL and HNG (NOMA-PDKL-HNG) is 66% higher than when using NOMA-DC.

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.

Sum rate capacity of non-orthogonal multiple access scheme with optimal power allocation

2021 ◽  
pp. 154851292098353
Author(s):  
Lokesh Bhardwaj ◽  
Ritesh Kumar Mishra ◽  
Ravi Shankar
Keyword(s):  
Power Allocation ◽  
Multiple Access ◽  
Signal To Noise Ratio ◽  
Optimal Power Allocation ◽  
Cumulative Density Function ◽  
Optimal Power ◽  
Power Domain ◽  
Access Scheme ◽  
Rate Capacity ◽  
Sum Rate

In this work, the performance of the downlink non-orthogonal multiple access (NOMA) technique is investigated for two users considering optimal power allocation factors. The power domain NOMA differentiates the users based on channel gains by providing different power levels and it is demonstrated that optimal power allocation is only possible when the gain ratio is maximum. Further, the range of optimal power levels is derived for the strong user having better channel conditions. Furthermore, the outage probability (OP) has been derived for ordered NOMA in the downlink through the cumulative density function-based approach. The simulation results demonstrate the improvement in sum rate capacity for optimal power allocation as compared to random power allocation, and the OP reduces with the signal-to-noise ratio more sharply for the stronger user.

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.

Optimal Power Allocation for Intersatellite Visible Light Communication Based on Nonorthogonal Multiple Access

2021 ◽  
Vol 48 (7) ◽  
pp. 0706002
Author(s):  
郝少伟 Hao Shaowei ◽  
李勇军 Li Yongjun ◽  
赵尚弘 Zhao Shanghong ◽  
宋鑫康 Song Xinkang
Keyword(s):  
Visible Light ◽  
Power Allocation ◽  
Multiple Access ◽  
Visible Light Communication ◽  
Optimal Power Allocation ◽  
Optimal Power

An Optimal Power Allocation for the Two-Way Relay System Using Physical-Layer Network Coding

2014 ◽  
Vol 986-987 ◽  
pp. 2041-2047
Author(s):  
Ren Gang Yuan ◽  
Li Li Chu ◽  
Chuang Li ◽  
Ling Li Cao
Keyword(s):  
Power Allocation ◽  
Network Coding ◽  
Physical Layer ◽  
Optimal Power Allocation ◽  
Relay Channel ◽  
Allocation Scheme ◽  
Relay System ◽  
Physical Layer Network Coding ◽  
Optimal Power ◽  
Sum Rate

In this letter, an optimal power allocation in the two-way relay channel of four transmission nodes employing the physical-layer network coding (PNC) protocol is proposed to improve the network sum-rate of the two-way relay system. The optimal power allocation is obtained by maximizing the network sum-rate of the PNC protocol under a sum-power constraint in a Rayleigh fading channel environment. Analytical and simulation results show that the proposed power allocation can improve the network sum-rate. Furthermore, compared with the equal power allocation scheme, the proposed power allocation scheme can achieve much higher network sum-rate performance.

Optimal Power Allocation for Maximizing Energy Efficiency in DAS-Based IoT Network

2020 ◽  
pp. 1-7
Author(s):  
Zaki Masood ◽  
Hosung Park ◽  
Han Seung Jang ◽  
Sunyong Yoo ◽  
Sokhee P. Jung ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Optimal Power Allocation ◽  
Optimal Power
Sign in / Sign up

Export Citation Format

Share Document