Transmit Power Minimization for Downlink Multi-Cell Multi-Carrier NOMA Networks

Ni, Dadong; Li, Hao; Tran, Quang Thanh; Qian, Xiaomin

doi:10.1109/lcomm.2018.2872991

Cited by 30 publications

(19 citation statements)

References 10 publications

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“…Cui et al investigated PA in multicell multicarrier NOMA (MC-NOMA) networks by considering maximizing the sum mean opinion scores (MOSs) of users and proposed a low-complexity suboptimal approach based on successive convex approximation techniques, which attained a good computational complexityoptimality trade-off [17]. Ni et al developed a centralized minimum power control algorithm to minimize the total transmit power by considering the user data rate requirements for multicell MC-NOMA networks where the user assignment is fixed [18]. Khan et al presented an iterative local optimal solution to calculate the optimal PA and enhance the sum capacity, which considered the transmission power in sending node, the user PA, and the minimum rate requirements per user [19].…”

Section: Introductionmentioning

confidence: 99%

Optimal Power Allocation for Cooperative Pattern Division Multiple Access Systems

Zhang

Kang²,

2021

Mathematical Problems in Engineering

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This study focuses on the power allocation (PA) problem in code division multiple access (PDMA) networks with amplify-and-forward (AF) relays. We provide two wireless communication technical performance indexes, which are system throughput and outage probability. A multiobjective version of particle swarm optimization is proposed to solve Pareto-optimal solutions for optimal PA problems. A novel programming model is built based on improvement of constraint functions, and the accuracy and efficiency of solution can be improved via compact constraints. The technique for order preference by similarity to an ideal solution is proposed to balance the performance indicators, which include outage probability and system throughput. It has been calculated that the proposed approach for optimal PA is verified and performs better than a genetic algorithm approach.

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Section: Introductionmentioning

confidence: 99%

Optimal Power Allocation for Cooperative Pattern Division Multiple Access Systems

Zhang

Kang²,

2021

Mathematical Problems in Engineering

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“…In practice, wireless communications systems are usually multi-cell systems. Resource management has been addressed from different perspectives for multi-cell NOMA [ 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ]. Resource optimization was studied in [ 32 ] to achieve the optimal resource utilization by optimizing power allocation and the user pair.…”

Section: Introductionmentioning

confidence: 99%

“…The authors in [ 36 ] investigated EE in MCMC-NOMA networks using the non-cooperative auction-based game for power allocation for users and graph-based k-means clustering to mitigate the inter-cell interference. Moreover, transmit power minimization in MCMC-NOMA networks was considered in [ 37 ]. Centralized minimum power control for fixed user assignment was exploited, then the greedy user clustering and power allocation scheme was proposed.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency Maximization for Multi-Cell Multi-Carrier NOMA Networks

Adam

Wang

2020

Sensors

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As energy efficiency (EE) is a key performance indicator for the future wireless network, it has become a significant research field in communication networks. In this paper, we consider multi-cell multi-carrier non-orthogonal multiple access (MCMC-NOMA) networks and investigate the EE maximization problem. As the EE maximization is a mixed-integer nonlinear programming NP-hard problem, it is difficult to solve directly by traditional optimization such as convex optimization. To handle the EE maximization problem, we decouple it into two subproblems. The first subproblem is user association, where we design a matching-based framework to perform the user association and the subcarriers’ assignment. The second subproblem is the power allocation problem for each user to maximize the EE of the systems. Since the EE maximization problem is still non-convex with respect to the power domain, we propose a two stage quadratic transform with both a single ratio quadratic and multidimensional quadratic transform to convert it into an equivalent convex optimization problem. The power allocation is obtained by iteratively solving the convex problem. Finally, the numerical results demonstrate that the proposed method could achieve better EE compared to existing approaches for non-orthogonal multiple access (NOMA) and considerably outperforms the fractional transmit power control (FTPC) scheme for orthogonal multiple access (OMA).

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“…Resource management plays an important role to alleviate these interference [8]. For downlink communication, specifically, some work focuses on the sum rate maximization and shows higher spectral efficiency (SE) can be achieved by NOMA when considering the intercell interference [9,10,11,12]. Besides SE, energy efficiency (EE) is also a key performance metric investigated for resource allocation in NOMA-enabled HetNets [8,13,14].…”

Section: Introductionmentioning

confidence: 99%

User Association and Power Control for Energy Efficiency Maximization in M2M-Enabled Uplink Heterogeneous Networks with NOMA

Zhang

Kang

2019

Sensors

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To support a vast number of devices with less energy consumption, we propose a new user association and power control scheme for machine to machine enabled heterogeneous networks with non-orthogonal multiple access (NOMA), where a mobile user (MU) acting as a machine-type communication gateway can decode and forward both the information of machine-type communication devices and its own data to the base station (BS) directly. MU association and power control are jointly considered in the formulated as optimization problem for energy efficiency (EE) maximization under the constraints of minimum data rate requirements of MUs. A many-to-one MU association matching algorithm is firstly proposed based on the theory of matching game. By taking swap matching operations among MUs, BSs, and sub-channels, the original problem can be solved by dealing with the EE maximization for each sub-channel. Then, two power control algorithms are proposed, where the tools of sequential optimization, fractional programming, and exhaustive search have been employed. Simulation results are provided to demonstrate the optimality properties of our algorithms under different parameter settings.

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Transmit Power Minimization for Downlink Multi-Cell Multi-Carrier NOMA Networks

Cited by 30 publications

References 10 publications

Optimal Power Allocation for Cooperative Pattern Division Multiple Access Systems

Optimal Power Allocation for Cooperative Pattern Division Multiple Access Systems

Energy Efficiency Maximization for Multi-Cell Multi-Carrier NOMA Networks

User Association and Power Control for Energy Efficiency Maximization in M2M-Enabled Uplink Heterogeneous Networks with NOMA

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