scholarly journals Joint selection of the MCS’s and power allocation coefficients in the two-user downlink PD-NOMA system

2021 ◽  
Vol 270 ◽  
pp. 01031
Author(s):  
Yakov Kryukov ◽  
Dmitriy Pokamestov ◽  
Eugeniy Rogozhnikov
Keyword(s):  
Power Allocation ◽  
Additive White Gaussian Noise ◽  
Base Station ◽  
System Capacity ◽  
Channel State ◽  
Processing Resource ◽  
Power Domain ◽  
Capacity Maximization ◽  
Selection Of ◽  
High Computational Complexity

Power Domain Non-Orthogonal Multiple Access (PD-NOMA) is a perspective multiplexing technique for future cellular networks. Nevertheless, it is poorly studied and not applied in the existing systems due to the complexity of PD-NOMA signal processing, resource scheduling, and power allocation. The issue is that a modulation and coding scheme (MCS) selection, including power allocation, is a cooperative procedure considering the channel state information of each multiplexed user. It can be solved by enumerating all possible multiplexing combinations but at the expense of the high computational complexity. In our work, we propose a composed table with the joint MCS’s, which can be selected by the base station (BS) for the user multiplexing in a downlink PD-NOMA system based on their signal-to-noise (SNR) ratios. It allows selecting two MCS’s with two power allocation coefficients for both users and guarantees the 10% block error rate (BLER) performance in the additive white Gaussian noise (AWGN) channel. The joint MCS selection method is based on a max-rate scheduling strategy and provides system capacity maximization ignoring fairness between users. The proposed table is given in the Appendix.

scholarly journals Benefiting wireless power transfer scheme in power domain based multiple access: ergodic rate performance evaluation

2021 ◽  
Vol 10 (2) ◽  
pp. 785-792
Author(s):  
Anh-Tu Le ◽  
Minh-Sang Van Nguyen ◽  
Dinh-Thuan Do
Keyword(s):  
Power Allocation ◽  
Multiple Access ◽  
Wireless Power Transfer ◽  
Ergodic Capacity ◽  
Base Station ◽  
Power Transfer ◽  
Wireless Power ◽  
Transfer Scheme ◽  
Power Domain ◽  
Fixed Power

Power domain based multiple access scheme is introduced in this paper, namely Non-orthogonal multiple-access (NOMA). We deploy a wireless network using NOMA together with a wireless power transfer (WPT) scheme for dedicated user over Nakagami-$m$ fading channel. When combined, these promising techniques (NOMA and WPT) improve the system performance in term of ergodic performance at reasonable coefficient of harvested power. However, fixed power allocation factors for each NOMA user can be adjusted at the base station and it further provide performance improvement. We design a new signal frame to deploy a NOMA scheme in WPT which adopts a linear energy harvesting model. The ergodic capacity in such a NOMA network and power allocation factors can be updated frequently in order to achieve a fair distribution among NOMA users. The exact expressions of ergodic capacity for each user is derived. The simulation results show that an agreement between analytic performance and Monte-Carlo simulation can be achieved. 

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 Joint Optimization on Trajectory, Cache Placement, and Transmission Power for Minimum Mission Time in UAV-Aided Wireless Networks

2021 ◽  
Vol 10 (7) ◽  
pp. 426
Author(s):  
Tingting Lan ◽  
Danyang Qin ◽  
Guanyu Sun
Keyword(s):  
Wireless Communication ◽  
Power Allocation ◽  
Optimization Problems ◽  
Base Station ◽  
Optimization Techniques ◽  
Joint Optimization ◽  
Transmission Power ◽  
Wireless Backhaul ◽  
Mission Time ◽  
Cache Placement

In recent years, due to the strong mobility, easy deployment, and low cost of unmanned aerial vehicles (UAV), great interest has arisen in utilizing UAVs to assist in wireless communication, especially for on-demand deployment in emergency situations and temporary events. However, UAVs can only provide users with data transmission services through wireless backhaul links established with a ground base station, and the limited capacity of the wireless backhaul link would limit the transmission speed of UAVs. Therefore, this paper designed a UAV-assisted wireless communication system that used cache technology and realized the transmission of multi-user data by using the mobility of UAVs and wireless cache technology. Considering the limited storage space and energy of UAVs, the joint optimization problem of the UAV’s trajectory, cache placement, and transmission power was established to minimize the mission time of the UAV. Since this problem was a non-convex problem, it was decomposed into three sub-problems: trajectory optimization, cache placement optimization, and power allocation optimization. An iterative algorithm based on the successive convex approximation and alternate optimization techniques was proposed to solve these three optimization problems. Finally, in the power allocation optimization, the proposed algorithm was improved by changing the optimization objective function. Numerical results showed that the algorithm had good performance and could effectively reduce the task completion time of the UAV.

scholarly journals Actor-critic learning-based energy optimization for UAV access and backhaul networks

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yaxiong Yuan ◽  
Lei Lei ◽  
Thang X. Vu ◽  
Symeon Chatzinotas ◽  
Sumei Sun ◽  
...  
Keyword(s):  
Power Allocation ◽  
Heuristic Algorithms ◽  
Piecewise Linear ◽  
Access Network ◽  
Computation Time ◽  
Combinatorial Problem ◽  
Base Station ◽  
Piecewise Linear Approximation ◽  
Group Scheduling ◽  
User Group

AbstractIn unmanned aerial vehicle (UAV)-assisted networks, UAV acts as an aerial base station which acquires the requested data via backhaul link and then serves ground users (GUs) through an access network. In this paper, we investigate an energy minimization problem with a limited power supply for both backhaul and access links. The difficulties for solving such a non-convex and combinatorial problem lie at the high computational complexity/time. In solution development, we consider the approaches from both actor-critic deep reinforcement learning (AC-DRL) and optimization perspectives. First, two offline non-learning algorithms, i.e., an optimal and a heuristic algorithms, based on piecewise linear approximation and relaxation are developed as benchmarks. Second, toward real-time decision-making, we improve the conventional AC-DRL and propose two learning schemes: AC-based user group scheduling and backhaul power allocation (ACGP), and joint AC-based user group scheduling and optimization-based backhaul power allocation (ACGOP). Numerical results show that the computation time of both ACGP and ACGOP is reduced tenfold to hundredfold compared to the offline approaches, and ACGOP is better than ACGP in energy savings. The results also verify the superiority of proposed learning solutions in terms of guaranteeing the feasibility and minimizing the system energy compared to the conventional AC-DRL.

scholarly journals Energy-Efficient Dual-Iteration Power Allocation for Two-Phase Relay System with Massive Antennas

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Long Zhao ◽  
Wei Xiang ◽  
Jie Mei ◽  
Hui Zhao ◽  
Hang Long ◽  
...  
Keyword(s):  
Power Allocation ◽  
Relay Node ◽  
Spectrum Efficiency ◽  
Amplify And Forward ◽  
Zero Forcing ◽  
Channel State ◽  
Relay System ◽  
Two Phase ◽  
Massive Antennas ◽  
Equal Power Allocation

This paper considers the scenario where multiple source nodes communicate with multiple destination nodes simultaneously with the aid of an amplify-and-forward relay equipped with massive antennas. In order to achieve optimal energy efficiency (EE) of the entire relay system, this paper investigates the power allocation problem for the multiple pairs of nodes at both the source nodes and the relay node, where the relay employs the backward and forward zero-forcing filters. Since the EE optimization problem cannot be solved analytically, we propose a two-phase power allocation method. Given power allocation of one phase, the optimal power allocation is derived for the other phase. Furthermore, two dual-iteration power allocation (DIPA) algorithms with performance approaching that of optimal EE are developed based on the instantaneous and statistic channel state information, respectively. Numerical results show that the proposed DIPA algorithms can greatly improve EE while guaranteeing spectrum efficiency (SE) when compared with the equal power allocation algorithm. Moreover, both algorithms suggest that deploying a rational number of antennas at the relay node and multiplexing a reasonable number of node pairs can improve on the EE and SE.

A Novel User Grouping Algorithm for Downlink NOMA

2021 ◽  
Author(s):  
Navideh Ghafouri Jeshvaghani ◽  
Naser Movahhedinia ◽  
Mohammad Reza Khayyambashi
Keyword(s):  
Interference Cancellation ◽  
Multiple Access ◽  
Spectrum Efficiency ◽  
System Capacity ◽  
Substantial Impact ◽  
User Grouping ◽  
Radio Access ◽  
Power Domain ◽  
Rate Maximization ◽  
Sum Rate

Abstract Non-orthogonal multiple access (NOMA) is one of the promising radio access techniques for resource allocation improvement in the 5th generation of cellular networks. Compared to orthogonal multiple access techniques (OMA), NOMA offers extra benefits, including greater spectrum efficiency which is provided through multiplexing users in the transmission power domain while using the same spectrum resources non-orthogonally. Even though NOMA uses Successive Interference Cancellation (SIC) to repeal the interference among users, user grouping has shown to have a substantial impact on its performance. This prformance improvement can appear in different parameters such as system capacity, rate, or the power consumption. In this paper, we propose a novel user grouping scheme for sum-rate maximization which increases the sum-rate up to 25 percent in comparison with two authenticated recent works. In addition to being matrix-based and having a polynomial time complexity, the proposed method is also able to cope with users experiencing different channel gains and powers in different sub-bands.

scholarly journals Joint power allocation and subcarrier assignment for device to device in 5G time division duplex networks

2018 ◽  
Vol 14 (11) ◽  
pp. 155014771881109 ◽  
Author(s):  
Pan Zhao ◽  
Lei Feng ◽  
Peng Yu ◽  
Wenjing Li ◽  
Xuesong Qiu
Keyword(s):  
Quality Of Service ◽  
Power Allocation ◽  
Base Station ◽  
Joint Power ◽  
Time Division Duplex ◽  
Device To Device ◽  
Minlp Problem ◽  
Device To Device Communication ◽  
Time Division

The explosive demands for mobile broadband service bring a major challenge to 5G wireless networks. Device-to-device communication, adopting side links for user-direct communication, is regarded as a main technical source for offloading large volume of mobile traffic from cellular base station. This article investigates the joint power and subcarrier allocation scheme for device-to-device communication in 5G time division duplex systems. In time division duplex system, instead of utilizing an exclusive portion of the precious cellular spectrum, device-to-device pairs reuse the subcarriers occupied by cellular users, thus producing harmful interference to cellular users in both uplink and downlink communication, and strongly limiting the spectrum efficiency of the system. To this end, we focus on the maximization of device-to-device throughput while guaranteeing both uplink and downlink channel quality of service of cellular users as well as device-to-device pairs. The problem is formulated as a mixed integer non-linear programming (MINLP) problem. To make it tractable, we separate the original MINLP problem into two sub problems: power allocation and sub-carrier reusing. The former is to develop optimal power allocation for each device-to-device pair and each cellular user, with the constraints of maximum power and quality of service. It is solved by geometric programming technique in convex optimization method. The latter is derived as a one-to-many matching problem for scheduling multiple subcarriers occupied by cellulars to device-to-device pairs. It is solved by Hungarian method. Simulation results show that the proposed scheme significantly improves system capacity of the device-to-device underlay network, with quality of service of both device-to-device users and cellular users guaranteed.

scholarly journals Improved Water-Filling Power Allocation for Energy-Efficient Massive MIMO Downlink Transmissions

2017 ◽  
Vol 63 (1) ◽  
pp. 79-84
Author(s):  
M. K Noor Shahida ◽  
Rosdiadee Nordin ◽  
Mahamod Ismail
Keyword(s):  
Power Allocation ◽  
Network Architecture ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Downlink Transmission ◽  
Allocation Algorithm ◽  
Mimo Antenna ◽  
Water Filling ◽  
Water Filling Algorithm

Abstract Energy Efficiency (EE) is becoming increasingly important for wireless communications and has caught more attention due to steadily rising energy costs and environmental concerns. Recently, a new network architecture known as Massive Multiple-Input Multiple-Output (MIMO) has been proposed with the remarkable potential to achieve huge gains in EE with simple linear processing. In this paper, a power allocation algorithm is proposed for EE to achieve the optimal EE in Massive MIMO. Based on the simplified expression, we develop a new algorithm to compute the optimal power allocation algorithm and it has been compared with the existing scheme from the previous literature. An improved water filling algorithm is proposed and embedded in the power allocation algorithm to maximize EE and Spectral Efficiency (SE). The numerical analysis of the simulation results indicates an improvement of 40% in EE and 50% in SE at the downlink transmission, compared to the other existing schemes. Furthermore, the results revealed that SE does not influence the EE enhancement after using the proposed algorithm as the number of Massive MIMO antenna at the Base Station (BS) increases.

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