A Flow Level Perspective on Base Station Power Allocation in Green Networks

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.

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

EURASIP Journal on Wireless Communications and Networking ◽

10.1186/s13638-021-01960-0 ◽

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.

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

International Journal of Distributed Sensor Networks ◽

10.1177/1550147718811094 ◽

2018 ◽

Vol 14 (11) ◽

pp. 155014771881109 ◽

Cited By ~ 1

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.

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

International Journal of Electronics and Telecommunications ◽

10.1515/eletel-2017-0011 ◽

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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An Efficient IR-HARQ Power Allocation for Relay-Aided Cellular Networks

Journal of Circuits System and Computers ◽

10.1142/s0218126618501955 ◽

2018 ◽

Vol 27 (12) ◽

pp. 1850195

Author(s):

P. Mangayarkarasi ◽

J. Raja

Keyword(s):

Power Allocation ◽

Cellular Networks ◽

Channel Capacity ◽

Energy Efficient ◽

Base Station ◽

Relay Station ◽

Decode And Forward ◽

Relay Placement ◽

Cell Coverage ◽

The Impact

Energy-efficient and reliable data transmission is a challenging task in wireless relay networks (WRNs). Energy efficiency in cellular networks has received significant attention because of the present need for reduced energy consumption, thereby maintaining the profitability of networks, which in turn makes these networks “greener”. The urban cell topography needs more energy to cover the total area of the cell. The base station does not cover the entire area in a given topography and adding more number of base stations is a cost prohibitive one. Energy-efficient relay placement model which calculates the maximum cell coverage is proposed in this work that covers all sectors and also an energy-efficient incremental redundancy-hybrid automatic repeat request (IR-HARQ) power allocation scheme to improve the reliability of the network by improving the overall network throughput is proposed. An IR-HARQ power allocation method maximizes the average incremental mutual information at each round, and its throughput quickly converges to the ergodic channel capacity as the number of retransmissions increases. Simulation results show that the proposed IR-HARQ power allocation achieves full channel capacity with average transmission delay and maintains good throughput under less power consumption. Also the impact of relaying performance on node distances between relay station and base station as well as between user and relay station and relay height for line of sight conditions are analyzed using full decode and forward (FDF) and partial decode and forward (PDF) relaying schemes. Compared to FDF scheme, PDF scheme provides better performance and allows more freedom in the relay placement for an increase in cell coverage.

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Joint 3-D Positioning and Power Allocation for UAV Relay Aided by Geographic Information

10.36227/techrxiv.14843055 ◽

2021 ◽

Author(s):

Pengfei Yi ◽

Liang Zhu ◽

Lipeng Zhu ◽

Zhenyu Xiao

Keyword(s):

Power Allocation ◽

Upper Bound ◽

Three Dimensional ◽

Geographic Information ◽

Base Station ◽

Lagrangian Multipliers ◽

Loop Optimization ◽

Convex Problem ◽

Communication Links ◽

Minimum Capacity

<div>In this paper, we study to employ geographic information to address the blockage problem of air-to-ground links between UAV and terrestrial nodes. In particular, a UAV relay is deployed to establish communication links from a ground base station to multiple ground users. To improve communication capacity, we fifirst model the blockage effect caused by buildings according to the three-dimensional (3-D) geographic information. Then, an optimization problem is formulated to maximize the minimum capacity among users by jointly optimizing the 3-D position and power allocation of the UAV relay, under the constraints of link capacity, maximum transmit power, and blockage. To solve this complex non-convex problem, a two-loop optimization framework is developed based on Lagrangian relaxation. The outer-loop aims to obtain proper Lagrangian multipliers to ensure the solution of the Lagrangian problem converge to the tightest upper bound on the original problem. The inner-loop solves the Lagrangian problem by applying the block coordinate descent (BCD) and successive convex approximation (SCA) techniques, where UAV 3-D positioning and power allocation are alternately optimized in each iteration. Simulation results confifirm that the proposed solution signifificantly outperforms two benchmark schemes and achieves a performance close to the upper bound on the UAV relay system.</div>

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Power Allocation Scheme Based on Fairness for Multi-Base Station Cooperative Communication System

Journal of Software Engineering ◽

10.3923/jse.2016.138.146 ◽

2015 ◽

Vol 10 (1) ◽

pp. 138-146

Author(s):

Hu Guolong ◽

Jia Zhenghong ◽

Qin Xizhong ◽

Niu Hongmei ◽

Jiao Huadong ◽

...

Keyword(s):

Power Allocation ◽

Cooperative Communication ◽

Communication System ◽

Base Station ◽

Allocation Scheme

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Cooperative Admission Control with Network Coding in 5G Underlying D2D-Satellite Communication

Electronics ◽

10.3390/electronics9101601 ◽

2020 ◽

Vol 9 (10) ◽

pp. 1601

Author(s):

Asfandyar Awan ◽

Zhao Qi ◽

Shan Hu ◽

Lijiang Chen

Keyword(s):

Power Allocation ◽

Network Coding ◽

Admission Control ◽

Cooperative Communication ◽

Power Efficiency ◽

Satellite Communication ◽

Base Station ◽

User Selection ◽

Complex Solution ◽

Mode Assignment

Cooperative communication supported by device to device (D2D)-LEO earthed satellite increases the performance of the resilient network and offloads base station. Additionally, network coding in a packet-based cooperative framework provides diversity and speedy recovery of lost packets. Cooperative communication advantages are subject to effective joint admission control strengthened by network coding for multiple interfaces. Joint admission control with network coding involves multiple constraints in terms of user selection, mode assignment, power allocation, and interface-based network codewords, which is challenging to solve collectively. Sub-problematization and its heuristic solution lead to a less complex solution. First, the adaptive terrestrial satellite power sentient network (ATSPSN) algorithm is proposed based on low complex convex linearization of mix integer non-linear problem (MINLP), NP-hard. ATSPSN provides optimum power allocation, mode assignment, and user selection based on joint channel conditions. Second, a multiple access network coding algorithm (MANC) is developed underlying the D2D-satellite network, which provides novel multiple interface random linear network codewords. At the end, the bi-directional matching algorithm aiming for joint admission control with network coding, named JAMANC-stream and JAMANC-batch communication, is proposed. JAMANC algorithm leads to a less complex solution and provides improved results in terms of capacity, power efficiency, and packet completion time. The theoretical lower and upper bounds are also derived for comparative study.

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Energy consumption index minimized resource allocation in hybrid energy multiuser OFDM system with distributed antennas

ITM Web of Conferences ◽

10.1051/itmconf/20181703015 ◽

2018 ◽

Vol 17 ◽

pp. 03015

Author(s):

Huanhuan MAO ◽

Pengcheng Zhu ◽

Jiamin Li

Keyword(s):

Resource Allocation ◽

Energy Consumption ◽

Energy Harvesting ◽

Power Allocation ◽

Base Station ◽

Mixed Integer ◽

Subcarrier Allocation ◽

Ofdm System ◽

Consumption Index ◽

Distributed Antennas

Energy harvesting is one of the promising option for realization of green communication and has been a growing concern recently. In this paper, we address the downlink resource allocation in OFDM system with distributed antennas with hybrid power supply base station, where energy harvesting and non-renewable power sources are used complementarily. A joint subcarrier and power allocation problem is formulated for minimizing the net Energy Consumption Index (ECI) with system Quality of Service (QoS) and bit error rates constraint. The problem is a 0-1 mixed integer nonlinear programming problem due to the binary subcarrier allocation variable. To solve the problem, we design an algorithm based on Lagrange relaxation method and fraction programming which optimizes the power allocation and subcarrier allocation iteratively in two nests. Simulation results show that the proposed algorithm converges in a small number of iterations and can improve net ECI of system greatly.

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Energy-Efficient Power Allocation and Relay Selection Schemes for Relay-Assisted D2D Communications in 5G Wireless Networks

Sensors ◽

10.3390/s18092865 ◽

2018 ◽

Vol 18 (9) ◽

pp. 2865 ◽

Cited By ~ 10

Author(s):

Md Rahman ◽

YoungDoo Lee ◽

Insoo Koo

Keyword(s):

Wireless Networks ◽

Power Allocation ◽

Relay Selection ◽

Base Station ◽

Data Rate ◽

Transmission Power ◽

D2d Communications ◽

Long Distance ◽

Inference System ◽

Efficient Power

Device-to-device (D2D) communications allows user equipment (UE) that are in close proximity to communicate with each other directly without using a base station. Relay-assisted D2D (RA-D2D) communications in 5G networks can be applied to support long-distance users and to improve energy efficiency (EE) of the networks. In this paper, we first establish a multi-relay system model where the D2D UEs can communicate with each other by reusing only one cellular uplink resource. Then, we apply an adaptive neuro-fuzzy inference system (ANFIS) architecture to select the best D2D relay to forward D2D source information to the expected D2D destination. Efficient power allocation (PA) in the D2D source and the D2D relay are critical problems for operating such networks, since the data rate of the cellular uplink and the maximum transmission power of the system need to be satisfied. As is known, 5G wireless networks also aim for low energy consumption to better implement the Internet of Things (IoT). Consequently, in this paper, we also formulate a problem to find the optimal solutions for PA of the D2D source and the D2D relay in terms of maximizing the EE of RA-D2D communications to support applications in the emerging IoT. To solve the PA problems of RA-D2D communications, a particle swarm optimization algorithm is employed to maximize the EE of the RA-D2D communications while satisfying the transmission power constraints of the D2D users, minimum data rate of cellular uplink, and minimum signal-to-interference-plus-noise-ratio requirements of the D2D users. Simulation results reveal that the proposed relay selection and PA methods significantly improve EE more than existing schemes.

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