scholarly journals Low‐complexity user pairing and power allocation algorithm for 5G cellular network non‐orthogonal multiple access

2017 ◽  
Vol 53 (9) ◽  
pp. 626-627 ◽  
Author(s):  
J. He ◽  
Z. Tang
Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1399 ◽  
Author(s):  
Omar A. Saraereh ◽  
Amer Alsaraira ◽  
Imran Khan ◽  
Peerapong Uthansakul

Non-orthogonal multiple access (NOMA) has become the key technology in the future 5G wireless networks. It can achieve multi-user multiplexing in the transmit power domain by allocating different power, which can effectively improve the system capacity and spectral efficiency. Aiming at the problem of high computational complexity and improving system capacity in non-orthogonal multiple access (NOMA) based on orthogonal frequency division multiple access (OFDMA) for 5G wireless cellular networks, this paper proposes an improved low complexity radio resource allocation algorithm for user grouping and power allocation optimization. The optimization model is established with the goal of maximizing system capacity. Through the step-by-step optimization idea, the complex non-convex optimization problem is decomposed into two sub-problems to be solved separately. Firstly, all users are grouped based on the greedy method, and then the power allocation is performed on the sub-carriers of the fixed group. Simulation results show that the proposed algorithm has better system capacity than the existing state-of-the-art algorithms and reduced complexity performance.


Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3705
Author(s):  
Omar Maraqa ◽  
Umair F. Siddiqi ◽  
Saad Al-Ahmadi ◽  
Sadiq M. Sait

Visible light communications (VLC) is gaining interest as one of the enablers of short-distance, high-data-rate applications, in future beyond 5G networks. Moreover, non-orthogonal multiple-access (NOMA)-enabled schemes have recently emerged as a promising multiple-access scheme for these networks that would allow realization of the target spectral efficiency and user fairness requirements. The integration of NOMA in the widely adopted orthogonal frequency-division multiplexing (OFDM)-based VLC networks would require an optimal resource allocation for the pair or the cluster of users sharing the same subcarrier(s). In this paper, the max-min rate of a multi-cell indoor centralized VLC network is maximized through optimizing user pairing, subcarrier allocation, and power allocation. The joint complex optimization problem is tackled using a low-complexity solution. At first, the user pairing is assumed to follow the divide-and-next-largest-difference user-pairing algorithm (D-NLUPA) that can ensure fairness among the different clusters. Then, subcarrier allocation and power allocation are solved iteratively through both the Simulated Annealing (SA) meta-heuristic algorithm and the bisection method. The obtained results quantify the achievable max-min user rates for the different relevant variants of NOMA-enabled schemes and shed new light on both the performance and design of multi-user multi-carrier NOMA-enabled centralized VLC networks.


2021 ◽  
Vol 40 (5) ◽  
pp. 9007-9019
Author(s):  
Jyotirmayee Subudhi ◽  
P. Indumathi

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.


Author(s):  
Jingrui Guo ◽  
Xiangyang Wang ◽  
Jingwen Yang ◽  
Jianhai Zheng ◽  
Bingqiang Zhao

2020 ◽  
Vol 10 (17) ◽  
pp. 5892 ◽  
Author(s):  
Zuhura J. Ali ◽  
Nor K. Noordin ◽  
Aduwati Sali ◽  
Fazirulhisyam Hashim ◽  
Mohammed Balfaqih

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.


Algorithms ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
Su Zhao ◽  
Gang Huang ◽  
Qi Zhu

For an energy-harvesting wireless transmission system, considering that a transmitter which can harvest energy from nature has two kinds of extra energy consumption, circuit consumption and storage losses, the optimization models are set up in this paper for the purpose of maximizing the average throughput of the system within a certain period of time for both a time-invariant channel and time-varying channel. Convex optimization methods such as the Lagrange multiplier method and the KKT (Karush–Kuhn–Tucker) condition are used to solve the optimization problem; then, an optimal offline power allocation algorithm which has a three-threshold structure is proposed. In the three-threshold algorithm, two thresholds can be achieved by using a linear search method while the third threshold is calculated according to the channel state information and energy losses; then, the offline power allocation is based on the three thresholds and energy arrivals. Furthermore, inspired by the optimal offline algorithm, a low-complexity online algorithm with adaptive thresholds is derived. Finally, the simulation results show that the offline power allocation algorithms proposed in this paper are better than other algorithms, the performance of the online algorithm proposed is close to the offline one, and these algorithms can help improve the average throughput of the system.


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