scholarly journals An Efficient Resource Allocation for Massive MTC in NOMA-OFDMA Based Cellular Networks

Electronics ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 705
Author(s):  
Yali Wu ◽  
Shuang Zhang ◽  
Zhengxuan Liu ◽  
Xiaoshuang Liu ◽  
Jianfeng Li
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Power Allocation ◽  
Multiple Access ◽  
Random Access ◽  
Iterative Algorithms ◽  
Low Complexity ◽  
Access Scheme ◽  
Efficient Resource ◽  
Resource Allocation Scheme

To alleviate random access congestion and support massive-connections with less energy consumption for machine-type communications (MTC) in the 5G cellular network, we propose an efficient resource allocation for massive MTC (mMTC) with hybrid non-orthogonal multiple access (NOMA)-orthogonal frequency division multiple access (OFDMA). First, a hybrid multiple access scheme, including the NOMA-based congestion-alleviating access scheme (NCAS) and OFDMA-based congestion-alleviating access scheme (OCAS), is proposed, in which the NOMA based devices coexist with OFDMA based ones. Then, aiming at maximizing the system access capacity, a traffic-aware resource blocks (RBs) allocation is investigated to optimize RBs allocation for preamble transmission and data packets transmission, as well as to optimize the RBs allocation between NCAS and OCAS for the RBs usage efficiency improvement. Next, aiming at the problem of high computational complexity and improving energy efficiency in hybrid NOMA-OFDMA based cellular M2M communications, this paper proposes an improved low complexity power allocation algorithm. The feasibility conditions of power allocation solution under the maximum transmit power constraints and quality of service (QoS) requirements of the devices is investigated. The original non-convex optimization problem is solved under the feasibility conditions by two iterative algorithms. Finally, a device clustering scheme is proposed based on the channel gain difference and feasible condition of power allocation solution, by which NOMA based devices and OFDMA based devices can be determined. Simulation results show that compared with non-orthogonal random access and transmission (NORA-DT), the proposed resource allocation scheme for hybrid NOMA-OFDMA systems can efficiently improve the performance of access capacity and energy efficiency.

scholarly journals An Efficient Resource Allocation Algorithm for OFDM-Based NOMA in 5G Systems

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1399 ◽  
Author(s):  
Omar A. Saraereh ◽  
Amer Alsaraira ◽  
Imran Khan ◽  
Peerapong Uthansakul
Keyword(s):  
Resource Allocation ◽  
Power Allocation ◽  
Multiple Access ◽  
Low Complexity ◽  
System Capacity ◽  
Resource Allocation Algorithm ◽  
Allocation Algorithm ◽  
User Grouping ◽  
Power Domain ◽  
Efficient Resource

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.

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 Resource Management in Cloud Radio Access Networks

2021 ◽  
Author(s):  
Lilatul Ferdouse
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Resource Management ◽  
Power Allocation ◽  
Multiple Access ◽  
Optimization Problem ◽  
Sparse Code ◽  
User Association ◽  
Allocation Method ◽  
Radio Access

This thesis focuses on resource management both in communication and computing sides of the cloud radio access networks (C-RANs). Communication and computing resources are bandwidth, power, baseband unit servers, and virtual machines, which become major resource allocation elements of C-RANs. If they are not properly handled, they create congestion and overload problems in radio access network and core network part of the backbone cellular network. We study two general problems of C-RAN networks, referred to as communication and computing resource allocation problem along with user association, base band unit (BBU) and remote radio heads (RRH) mapping problems in order to improve energy efficiency, sum data rate and to minimize delay performance of C-RAN networks. In this thesis, we propose, implement, and evaluate several solution strategies, namely posterior probability based user association and power allocation method, double-sided auction based distributed resource allocation method, the energy efficient joint workload scheduling and BBU allocation and iterative resource allocation method to deal with the resource management problems in both orthogonal and non-orthogonal multiple access supported C-RAN networks. In the posterior probability based user association and power allocation method, we apply Bayes theory to solve the multi-cell association problem in the coordinated multi-point supported C-RANs. We also use queueing and auction theory to solve the joint communication and computing resource optimization problem. As the joint optimization problem, we investigate the delay and sum data rate performance of C-RANs. To improve the energy efficiency of C-RANs, we employ Dinkelbach theorem and propose an iterative resource allocation method. Our proposed methods are evaluated via simulations by considering the effect of bandwidth utilization percentage, different scheduling weight, signal-to-interference ratio threshold value and number of users. The results show that the proposed methods can be successfully implemented for 5G C-RANs. Among the various non-orthogonal multiple access schemes, we consider and implement the sparse code multiple access (SCMA) scheme to jointly optimize the codebook and power allocation in the downlink of the C-RANs, where the utilization of sparse code multiple access in C-RANs to improve energy efficiency has not been investigated in detail in the literature. To solve the NP-hard joint optimization problem, we decompose the original problem into two subproblems: codebook allocation and power allocation. Using the graph theory, we propose the throughput aware sparse code multiple access based codebook selection method, which generates a stable codebook allocation solution within a finite number of steps. For the power allocation solution, we propose the iterative level-based power allocation method, which incorporates different power allocation approaches (e.g., weighted and successive interference cancellation ) into different levels to satisfy the maximum power requirement. Simulation results show that the sum data rate and energy efficiency performance of non-orthogonal multiple access supported C-RANs significantly increases with the number of users when the successive interference cancellation aware geometric water-filling based power allocation is used.

scholarly journals Resource Management in Cloud Radio Access Networks

2021 ◽  
Author(s):  
Lilatul Ferdouse
Keyword(s):  
Resource Allocation ◽  
Energy Efficiency ◽  
Resource Management ◽  
Power Allocation ◽  
Multiple Access ◽  
Optimization Problem ◽  
Sparse Code ◽  
User Association ◽  
Allocation Method ◽  
Radio Access

This thesis focuses on resource management both in communication and computing sides of the cloud radio access networks (C-RANs). Communication and computing resources are bandwidth, power, baseband unit servers, and virtual machines, which become major resource allocation elements of C-RANs. If they are not properly handled, they create congestion and overload problems in radio access network and core network part of the backbone cellular network. We study two general problems of C-RAN networks, referred to as communication and computing resource allocation problem along with user association, base band unit (BBU) and remote radio heads (RRH) mapping problems in order to improve energy efficiency, sum data rate and to minimize delay performance of C-RAN networks. In this thesis, we propose, implement, and evaluate several solution strategies, namely posterior probability based user association and power allocation method, double-sided auction based distributed resource allocation method, the energy efficient joint workload scheduling and BBU allocation and iterative resource allocation method to deal with the resource management problems in both orthogonal and non-orthogonal multiple access supported C-RAN networks. In the posterior probability based user association and power allocation method, we apply Bayes theory to solve the multi-cell association problem in the coordinated multi-point supported C-RANs. We also use queueing and auction theory to solve the joint communication and computing resource optimization problem. As the joint optimization problem, we investigate the delay and sum data rate performance of C-RANs. To improve the energy efficiency of C-RANs, we employ Dinkelbach theorem and propose an iterative resource allocation method. Our proposed methods are evaluated via simulations by considering the effect of bandwidth utilization percentage, different scheduling weight, signal-to-interference ratio threshold value and number of users. The results show that the proposed methods can be successfully implemented for 5G C-RANs. Among the various non-orthogonal multiple access schemes, we consider and implement the sparse code multiple access (SCMA) scheme to jointly optimize the codebook and power allocation in the downlink of the C-RANs, where the utilization of sparse code multiple access in C-RANs to improve energy efficiency has not been investigated in detail in the literature. To solve the NP-hard joint optimization problem, we decompose the original problem into two subproblems: codebook allocation and power allocation. Using the graph theory, we propose the throughput aware sparse code multiple access based codebook selection method, which generates a stable codebook allocation solution within a finite number of steps. For the power allocation solution, we propose the iterative level-based power allocation method, which incorporates different power allocation approaches (e.g., weighted and successive interference cancellation ) into different levels to satisfy the maximum power requirement. Simulation results show that the sum data rate and energy efficiency performance of non-orthogonal multiple access supported C-RANs significantly increases with the number of users when the successive interference cancellation aware geometric water-filling based power allocation is used.

scholarly journals On the Achievable Max-Min User Rates in Multi-Carrier Centralized NOMA-VLC Networks

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3705
Author(s):  
Omar Maraqa ◽  
Umair F. Siddiqi ◽  
Saad Al-Ahmadi ◽  
Sadiq M. Sait
Keyword(s):  
Power Allocation ◽  
Orthogonal Frequency Division Multiplexing ◽  
Multiple Access ◽  
Low Complexity ◽  
Subcarrier Allocation ◽  
Visible Light Communications ◽  
User Pairing ◽  
High Data ◽  
Access Scheme ◽  
Optimal Resource

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.

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.

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.

scholarly journals A Coordinated Direct AF/DF Relay-Aided NOMA Framework for Low Outage

2021 ◽  
Author(s):  
Anand Jee ◽  
KAMAL AGRAWAL ◽  
Shankar Prakriya
Keyword(s):  
Energy Efficiency ◽  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Outage Probability ◽  
Closed Form ◽  
Power Allocation ◽  
Multiple Access ◽  
Performance Gain ◽  
Amplify And Forward ◽  
Decode And Forward

This paper investigates the performance of a framework for low-outage downlink non-orthogonal multiple access (NOMA) signalling using a coordinated direct and relay transmission (CDRT) scheme with direct links to both the near-user (NU) and the far-user (FU). Both amplify-and-forward (AF) and decode-and-forward (DF) relaying are considered. In this framework, NU and FU combine the signals from BS and R to attain good outage performance and harness a diversity of two without any need for feedback. For the NU, this serves as an incentive to participate in NOMA signalling. For both NU and FU, expressions for outage probability and throughput are derived in closed form. High-SNR approximations to the outage probability are also presented. We demonstrate that the choice of power allocation coefficient and target rate is crucial to maximize the NU performance while ensuring a desired FU performance. We demonstrate performance gain of the proposed scheme over selective decode-and-forward (SDF) CDRT-NOMA in terms of three metrics: outage probability, sum throughput and energy efficiency. Further, we demonstrate that by choosing the target rate intelligently, the proposed CDRT NOMA scheme ensures higher energy efficiency (EE) in comparison to its orthogonal multiple access counterpart. Monte Carlo simulations validate the derived expressions.

Sign in / Sign up

Export Citation Format

Share Document