scholarly journals Ambient BackCom in Beyond 5G NOMA Networks: A Multi-Cell Resource Allocation Framework

2021 ◽  
Author(s):  
Wali Ullah Khan ◽  
Kapal Dev ◽  
Muhammad Awais Javed ◽  
Dinh-Thuan Do ◽  
Nawab Muhammad Faseeh Qureshi ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Multiple Access ◽  
Optimization Problem ◽  
Original Problem ◽  
Base Station ◽  
Joint Optimization ◽  
Theory Approach ◽  
Closed Form Solutions ◽  
Cell Network ◽  
Sum Rate

This article proposes a new resource allocation framework that uses the dual theory approach. Specifically, the sum-rate of the multi-cell network having backscatter tags and NOMA user equipments is maximized by formulating a joint optimization problem. To find the efficient base station transmit power and backscatter reflection coefficient in each cell, the original problem is first divided into two subproblems and then derived the closed-form solutions. A comparison with the orthogonal multiple access (OMA) ambient BackCom and pure NOMA transmission has been provided.

scholarly journals Ambient BackCom in Beyond 5G NOMA Networks: A Multi-Cell Resource Allocation Framework

2021 ◽  
Author(s):  
Wali Ullah Khan ◽  
Kapal Dev ◽  
Muhammad Awais Javed ◽  
Dinh-Thuan Do ◽  
Nawab Muhammad Faseeh Qureshi ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Multiple Access ◽  
Optimization Problem ◽  
Original Problem ◽  
Base Station ◽  
Joint Optimization ◽  
Theory Approach ◽  
Closed Form Solutions ◽  
Cell Network ◽  
Sum Rate

This article proposes a new resource allocation framework that uses the dual theory approach. Specifically, the sum-rate of the multi-cell network having backscatter tags and NOMA user equipments is maximized by formulating a joint optimization problem. To find the efficient base station transmit power and backscatter reflection coefficient in each cell, the original problem is first divided into two subproblems and then derived the closed-form solutions. A comparison with the orthogonal multiple access (OMA) ambient BackCom and pure NOMA transmission has been provided.

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 Backhaul-Aware Resource Allocation and Optimum Placement for UAV-Assisted Wireless Communication Network

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1397
Author(s):  
Yishi Xue ◽  
Bo Xu ◽  
Wenchao Xia ◽  
Jun Zhang ◽  
Hongbo Zhu
Keyword(s):  
Communication Network ◽  
Resource Allocation ◽  
Wireless Communication ◽  
Large Scale ◽  
Optimization Problem ◽  
Matrix Theory ◽  
Base Station ◽  
Achievable Rate ◽  
Multiple User ◽  
Wireless Communication Network

Driven by its agile maneuverability and deployment, the unmanned aerial vehicle (UAV) becomes a potential enabler of the terrestrial networks. In this paper, we consider downlink communications in a UAV-assisted wireless communication network, where a multi-antenna UAV assists the ground base station (GBS) to forward signals to multiple user equipments (UEs). The UAV is associated with the GBS through in-band wireless backhaul, which shares the spectrum resource with the access links between UEs and the UAV. The optimization problem is formulated to maximize the downlink ergodic sum-rate by jointly optimizing UAV placement, spectrum resource allocation and transmit power matrix of the UAV. The deterministic equivalents of UE’s achievable rate and backhaul capacity are first derived by utilizing large-dimensional random matrix theory, in which, only the slowly varying large-scale channel state information is required. An approximation problem of the joint optimization problem is then introduced based on the deterministic equivalents. Finally, an algorithm is proposed to obtain the optimal solution of the approximate problem. Simulation results are provided to validate the accuracy of the deterministic equivalents, and the effectiveness of the proposed method.

Resource Allocation in Orthogonal Frequency Division Multiple Access-Long Term Evaluation: Neural Network

2019 ◽  
Vol 16 (12) ◽  
pp. 5026-5031
Author(s):  
Kethavath Narender ◽  
C. Puttamadappa
Keyword(s):  
Neural Network ◽  
Resource Allocation ◽  
Communication Systems ◽  
Multiple Access ◽  
Large Scale ◽  
Cuckoo Search ◽  
Base Station ◽  
Frequency Division ◽  
Term Evaluation

Symmetrical Frequency Division Multiple Access (OFDMA) is utilized in the higher rate Wireless Communication Systems (WCSs). In the correspondence framework, a fem to cell is a little cell in building Base Station (BS), which devours less power, short range, and works in a minimal effort. The fem to cell has little separation among sender and recipient that give higher flag quality. In spite of the favorable position in fem to cell systems, there win critical difficulties in Interference Management. Specifically, impedance between the macro cell and fem to cell turns into the fundamental issue in OFDMA-Long Term Evaluation (OFDMA-LTE) framework. In this paper, the Neural Network and Hybrid Bee Colony and Cuckoo Search based Resource Allocation (NN-HBCCS-RA) in OFDMA-LTE framework is presented. The ideal power esteems are refreshed to dispense every one of the clients in the fem to cell and large scale cell. The NN-HBCCS strategy accomplished low Signal to Interference Noise Ratio (SINR), otherworldly proficiency and high throughput contrasted with customary techniques.

scholarly journals Energy-Efficient Resource Allocation for NOMA-based Backscatter Communications

2020 ◽  
Author(s):  
Yongjun Xu ◽  
Zhijin Qin ◽  
Guan Gui
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Power Efficiency ◽  
Multiple Access ◽  
Base Station ◽  
Spectrum Efficiency ◽  
Quadratic Transformation ◽  
Backscatter Communication ◽  
Efficient Resource ◽  
Energy Efficient Resource Allocation

Backscatter communication (BackCom) is a promising technique for achieving high spectrum efficiency and power efficiency in the future Internet of Things systems. The capacity of BackCom networks can be maximized by optimizing the backscatter time and the reflection coefficient (RC). However, system energy efficiency (EE) cannot be guaranteed usually. In this paper, we investigate the energy-efficient resource allocation problem of a non-orthogonal multiple access (NOMA)-based BackCom. Particularly, the base station (BS) transmits signals to two cellular users based on the NOMA protocol, meanwhile, a backscatter device backscatters the signals to users using the passive radio technology. The total EE of the considered system is maximized by jointly optimizing power allocation for each NOMA user and the RC of backscatter device where the decoding order and the quality of service (QoS) of each user are guaranteed. To solve such a non-convex problem, we develop an efficient iterative algorithm to obtain the optimal solutions by using Dinkelbach's method and the quadratic transformation approach. Numerical results show that the proposed algorithm can significantly improve the system EE compared with the orthogonal multiple access (OMA) scheme and the NOMA system without backscatter devices.

scholarly journals Price-Based Resource Allocation in Wireless Power Transfer-Enabled Massive MIMO Networks

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3298 ◽  
Author(s):  
Zhengqiang Wang ◽  
Kunhao Huang ◽  
Xiaona Yang ◽  
Xiaoyu Wan ◽  
Zifu Fan ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Convex Optimization ◽  
Optimization Problem ◽  
Wireless Power Transfer ◽  
Base Station ◽  
Power Transfer ◽  
Wireless Power ◽  
Convex Optimization Problem ◽  
Harvesting Time ◽  
Mimo Networks

This paper considers the price-based resource allocation problem for wireless power transfer (WPT)-enabled massive multiple-input multiple-output (MIMO) networks. The power beacon (PB) can transmit energy to the sensor nodes (SNs) by pricing their harvested energy. Then, the SNs transmit their data to the base station (BS) with large scale antennas by the harvesting energy. The interaction between PB and SNs is modeled as a Stackelberg game. The revenue maximization problem of the PB is transformed into the non-convex optimization problem of the transmit power and the harvesting time of the PB by backward induction. Based on the equivalent convex optimization problem, an optimal resource allocation algorithm is proposed to find the optimal price, energy harvesting time, and power allocation for the PB to maximize its revenue. Finally, simulation results show the effectiveness of the proposed algorithm.

scholarly journals A Novel Fairness-Aware Resource Allocation Scheme in Multiuser SISO-OFDMA Downlink

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Vasileios D. Papoutsis ◽  
Ioannis G. Fraimis ◽  
Stavros A. Kotsopoulos
Keyword(s):  
Resource Allocation ◽  
Multiple Access ◽  
Computational Cost ◽  
Wireless Systems ◽  
Base Station ◽  
Proportional Fairness ◽  
Allocation Scheme ◽  
Single Input Single Output ◽  
Data Rates ◽  
Resource Allocation Scheme

The problem of resource allocation for the downlink of wireless systems operating over a frequency-selective channel is investigated. It is assumed that both the Base Station (BS) and each user are equipped with a single antenna (Single Input Single Output-SISO case), and Orthogonal Frequency Division Multiple Access (OFDMA) is used as a multiple access scheme. The aim is to maximize the sum of the users' data rates subject to constraints on total available power and proportional fairness among users' data rates. Achieving the optimal solution has a high computational cost thereby the use of suboptimal techniques is necessary. A suboptimal, but efficient, scheme is devised, and it is shown, via simulation, that not only the proposed resource allocation scheme achieve higher sum of the users' data rates than other existing schemes but also the sum data rate is distributed fairly and flexibly among users. In addition, the proposed scheme is complexity effective and can be applied to latest-generation wireless systems that provide Quality-of-Service (QoS) guarantees.

scholarly journals Hybrid Direction of Arrival Precoding for Multiple Unmanned Aerial Vehicles Aided Non-Orthogonal Multiple Access in 6G Networks

2022 ◽  
Vol 12 (2) ◽  
pp. 895
Author(s):  
Laura Pierucci
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Multiple Access ◽  
Estimation Method ◽  
Direction Of Arrival ◽  
Base Station ◽  
Flying Height ◽  
Maximization Problem ◽  
Aerial Vehicles ◽  
Sum Rate ◽  
Hybrid Beamforming

Unmanned aerial vehicles (UAV) have attracted increasing attention in acting as a relay for effectively improving the coverage and data rate of wireless systems, and according to this vision, they will be integrated in the future sixth generation (6G) cellular network. Non-orthogonal multiple access (NOMA) and mmWave band are planned to support ubiquitous connectivity towards a massive number of users in the 6G and Internet of Things (IOT) contexts. Unfortunately, the wireless terrestrial link between the end-users and the base station (BS) can suffer severe blockage conditions. Instead, UAV relaying can establish a line-of-sight (LoS) connection with high probability due to its flying height. The present paper focuses on a multi-UAV network which supports an uplink (UL) NOMA cellular system. In particular, by operating in the mmWave band, hybrid beamforming architecture is adopted. The MUltiple SIgnal Classification (MUSIC) spectral estimation method is considered at the hybrid beamforming to detect the different direction of arrival (DoA) of each UAV. We newly design the sum-rate maximization problem of the UAV-aided NOMA 6G network specifically for the uplink mmWave transmission. Numerical results point out the better behavior obtained by the use of UAV relays and the MUSIC DoA estimation in the Hybrid mmWave beamforming in terms of achievable sum-rate in comparison to UL NOMA connections without the help of a UAV network.

scholarly journals Energy Efficient Resource Allocation in Millimeter-Wave D2D Enabled 5G Cellular Networks

2020 ◽  
Vol 10 (4) ◽  
pp. 6152-6160
Author(s):  
F. O. Ombongi ◽  
H. O. Absaloms ◽  
P. L. Kibet
Keyword(s):  
Resource Allocation ◽  
Optimization Problem ◽  
Current Trend ◽  
Traffic Density ◽  
Dual Decomposition ◽  
Resource Allocation Algorithm ◽  
Efficient Resource ◽  
Sum Rate ◽  
Resource Allocation Scheme ◽  
Energy Efficient Resource Allocation

The current trend has seen the data capacity and traffic density increase due to the increased demand for multimedia services. Since this cannot be handled successfully by the current 4G networks, there is a need to integrate the mmWave and the Device-to-Device (D2D) communication 5G technologies to meet this increased demand and traffic density. However, there is the challenge of increased interference between dense D2D users and cellular users if D2D users are allowed to reuse the resources allocated to cellular users. This degrades the performance of the D2D users in terms of achievable data rate and Energy Efficiency (EE). The paper formulates a match theoretic resource allocation scheme to maximize the achievable D2D sum rate. In addition, an EE optimization problem is formulated for D2D users by considering the rate and power constraints. The EE optimization problem is solved by the Lagrangian dual decomposition method. The algorithms were simulated in MATLAB and the results were compared to Hungarian and heuristic optimization algorithms. The results showed that the match theoretic resource allocation is on average 1.82 times better than the Hungarian algorithm. At the same time, the match theoretic resource allocation algorithm increases fairness in resource allocation as it maintains a higher sum rate for low and high-density number of users. The proposed EE optimization algorithm improved the D2D performance by 8.2% compared to the heuristic algorithm.

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.

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