QoS provisioning scheduling with joint optimization of base station and relay power allocation in cooperative OFDMA systems

2013 ◽  
Author(s):  
Xiao Zhang ◽  
Xiaoming Tao ◽  
Yang Li ◽  
Jianhua Lu
Keyword(s):  
Power Allocation ◽  
Base Station ◽  
Joint Optimization ◽  
Qos Provisioning

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 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 Joint optimization of beamforming and power allocation for DAJ-based untrusted relay networks

ETRI Journal ◽  
2018 ◽  
Vol 40 (6) ◽  
pp. 714-725
Author(s):  
Rugui Yao ◽  
Yanan Lu ◽  
Tamer Mekkawy ◽  
Fei Xu ◽  
Xiaoya Zuo
Keyword(s):  
Power Allocation ◽  
Relay Networks ◽  
Joint Optimization ◽  
Untrusted Relay

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.

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

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.

scholarly journals A Joint Optimization Scheme of Resource Allocation in Downlink NOMA with Statistical Channel State Information

2020 ◽  
Author(s):  
Lei Xu ◽  
Jing Yi Yao ◽  
Jing Cai ◽  
Yu Hong Fang ◽  
Hui Xiao Li
Keyword(s):  
Power Allocation ◽  
Channel State Information ◽  
Communication Systems ◽  
Multiple Access ◽  
Joint Optimization ◽  
System Throughput ◽  
Optimization Scheme ◽  
Channel State ◽  
State Information ◽  
User Grouping

Abstract In a real communication scenario, it is very difficult to obtain the real-time Channel State Information(CSI) accurately, so the communication systems with statistical CSI have been researched. In order to maximize the throughput of the downlink Non-Orthogonal Multiple Access (NOMA) system with statistical CSI, the formula of system throughput is derived at first. Then, according to the combinatorial characteristics of the original optimization problem, it is divided into two subproblems, that is user grouping and power allocation. At last, a joint optimization scheme is proposed. In which, Genetic algorithm is introduced to solve the subproblem of power allocation, and Hungarian algorithm is introduced to solve the subproblem of user grouping. By comparing the ergodic date rate of NOMA users with statistical CSI and perfect CSI, the effectiveness of the statistical CSI sorting is verified. Compared with the Orthogonal Multiple Access (OMA) scheme, the NOMA scheme with the fixed user grouping scheme and the random user grouping scheme, the proposed scheme can effectively improve the system throughput.

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