scholarly journals Towards Communication UAV-Based: Improving Throughput By Optimum Trajectory And Power Allocation

2021 ◽  
Author(s):  
Sedighe Nasrollahi ◽  
Seyed Masoud Mirrezaei
Keyword(s):  
Power Allocation ◽  
Communication Systems ◽  
Optimization Problem ◽  
Iterative Algorithms ◽  
Telecommunication Networks ◽  
Future Generations ◽  
Communication Link ◽  
Source Power ◽  
Optimum Trajectory ◽  
Wireless Telecommunication

Abstract It is predicted that the use of unmanned aerial vehicles (UAVs) in communication systems will be more extensive in future generations of wireless telecommunication networks, due to their facilitating advantages. In this paper, a UAV-based wireless communication system is considered in which a UAV is employed as a relay to connect two ground users. These two disconnected users make a communication pair. Our aim is to maximize the minimum achievable information rate for the communication link between the transmitter and receiver, by cooperatively optimizing UAV trajectory and transmitter and source power allocation. Motivated by the above, we formulate the optimization problem. The solving process is complicated because of the non-convexity of the formulated problem. To overcome this difficulty, we convert the main problem to some sub-problems by fixing some constraints and solve them with iterative algorithms such as successive convex optimization and reach the solution for the main problem. Simulation results show the capability of the proposed algorithm.

Data and Communication Infrastructure in Smart Grids

2022 ◽  
pp. 380-407
Author(s):  
Abdelmadjid Recioui ◽  
Youcef Grainat
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Communication Systems ◽  
Data Communication ◽  
Future Generations ◽  
Wireless Communication Systems ◽  
Communication Link ◽  
Communication Infrastructure ◽  
Grid Applications ◽  
State Of Art

The communication infrastructure constitutes the key element in smart grids. There have been great advances to enhance the way data is communicated among the different smart grid applications. The aim of this chapter is to present the data communication part of the smart grid with some pioneering developments in this topic. A succinct review of the state of art projects to improve the communication link is presented. An illustrative simulation using LABVIEW is included with a proposed idea of introducing some newly technologies involved in the current and future generations of wireless communication systems.

scholarly journals Nonconvex and game theory optimization for resource allocation in wireless communications

2021 ◽  
Author(s):  
Kandasamy Illanko
Keyword(s):  
Wireless Communication ◽  
Power Allocation ◽  
Communication Systems ◽  
Optimization Problem ◽  
Polynomial Complexity ◽  
Optimization Problems ◽  
Stackelberg Game ◽  
Mathematical Optimization ◽  
Simultaneous Optimization ◽  
Theoretical Development

Designing wireless communication systems that efficiently utilize the resources frequency spectrum and electric power, leads to problems in mathematical optimization. Most of these optimization problems are difficult to solve because the objective functions are nonconvex. While some problems remain unsolved, the solutions proposed in the literature for the others are of somewhat limited use because the algorithms are either unstable or have too high a computational complexity. This dissertation presents several stable algorithms, most of which have polynomial complexity, that solve five different nonconvex optimization problems in wireless communication. Two centralized and two distributed algorithms deal with the power allocation that maximizes the throughput in the Gaussian interference channel (GIC)with various constraints. The most valuable of these algorithms, the one with the minimum rate constraints became possible after a significant theoretical development in the dissertation that proves that the throughput of the GIC has a new generalized convex structure called invexity. The fifth algorithm has linear complexity, and finds the power allocation that maximizes the energy efficiency (EE) of OFDMA transmissions, for a given subchannel assignment. Some fundamental results regarding the power allocation are then used in the genetic algorithm for determining the subchannel allocation that maximizes the EE. Pricing for channel subleasing for ad-hoc wireless networks is considered next. This involves the simultaneous optimization of many functions that are interconnected through the variables involved. A composite game, a strategic game within a Stackelberg game, is used to solve this optimization problem with polynomial complexity. For each optimization problem solved, numerical results obtained using simulations that support the analysis and demonstrate the performance of the algorithms are presented.

Data and Communication Infrastructure in Smart Grids

2021 ◽  
pp. 1-28
Author(s):  
Abdelmadjid Recioui ◽  
Youcef Grainat
Keyword(s):  
Smart Grid ◽  
Smart Grids ◽  
Communication Systems ◽  
Data Communication ◽  
Future Generations ◽  
Wireless Communication Systems ◽  
Communication Link ◽  
Communication Infrastructure ◽  
Grid Applications ◽  
State Of Art

The communication infrastructure constitutes the key element in smart grids. There have been great advances to enhance the way data is communicated among the different smart grid applications. The aim of this chapter is to present the data communication part of the smart grid with some pioneering developments in this topic. A succinct review of the state of art projects to improve the communication link is presented. An illustrative simulation using LABVIEW is included with a proposed idea of introducing some newly technologies involved in the current and future generations of wireless communication systems.

scholarly journals Nonconvex and game theory optimization for resource allocation in wireless communications

2021 ◽  
Author(s):  
Kandasamy Illanko
Keyword(s):  
Wireless Communication ◽  
Power Allocation ◽  
Communication Systems ◽  
Optimization Problem ◽  
Polynomial Complexity ◽  
Optimization Problems ◽  
Stackelberg Game ◽  
Mathematical Optimization ◽  
Simultaneous Optimization ◽  
Theoretical Development

Designing wireless communication systems that efficiently utilize the resources frequency spectrum and electric power, leads to problems in mathematical optimization. Most of these optimization problems are difficult to solve because the objective functions are nonconvex. While some problems remain unsolved, the solutions proposed in the literature for the others are of somewhat limited use because the algorithms are either unstable or have too high a computational complexity. This dissertation presents several stable algorithms, most of which have polynomial complexity, that solve five different nonconvex optimization problems in wireless communication. Two centralized and two distributed algorithms deal with the power allocation that maximizes the throughput in the Gaussian interference channel (GIC)with various constraints. The most valuable of these algorithms, the one with the minimum rate constraints became possible after a significant theoretical development in the dissertation that proves that the throughput of the GIC has a new generalized convex structure called invexity. The fifth algorithm has linear complexity, and finds the power allocation that maximizes the energy efficiency (EE) of OFDMA transmissions, for a given subchannel assignment. Some fundamental results regarding the power allocation are then used in the genetic algorithm for determining the subchannel allocation that maximizes the EE. Pricing for channel subleasing for ad-hoc wireless networks is considered next. This involves the simultaneous optimization of many functions that are interconnected through the variables involved. A composite game, a strategic game within a Stackelberg game, is used to solve this optimization problem with polynomial complexity. For each optimization problem solved, numerical results obtained using simulations that support the analysis and demonstrate the performance of the algorithms are presented.

scholarly journals Multiple Power Allocation Game Schemes for Spectrum Coexistence Model Between Multistatic MIMO Radar Sensors and MU Communication

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6216
Author(s):  
Bin He ◽  
Hongtao Su
Keyword(s):  
Power Allocation ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Iterative Algorithms ◽  
Mimo Radar ◽  
Base Station ◽  
Radar Sensors ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Study Power

The normal operations of radar systems and communication systems under the condition of spectrum coexistence are facing a huge challenge. This paper uses game theory to study power allocation problems between multistatic multiple-input multiple-output (MIMO) radars and downlink communication. In the case of spectrum coexistence, radars, base station (BS) and multi-user (MU) have the working state of receiving and transmitting signals, which can cause unnecessary interferences to different systems. Therefore, when they work together, they should try to suppress mutual interferences. Firstly, the signal from BS is considered as interference when radar detects and tracks targets. A supermodular power allocation game (PAG) model is established and the existence and uniqueness of the Nash equilibrium (NE) in this game are proved. In addition, the power allocation problem from BS to MU is also analyzed, and two Stackelberg PAG models are constructed. It is proved that the NE of each game exists and is unique. Simultaneously, two Stackelberg power allocation iterative algorithms converge to the NEs. Finally, numerical results verify the convergence of the proposed PAG algorithms.

scholarly journals Low-complexity beam-domain channel estimation and power allocation in hybrid architecture massive MIMO systems

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Xiao Chen ◽  
Zaichen Zhang ◽  
Liang Wu ◽  
Jian Dang
Keyword(s):  
Channel Estimation ◽  
Power Allocation ◽  
Spectral Efficiency ◽  
Communication Systems ◽  
Mimo Systems ◽  
Beam Steering ◽  
Estimation Method ◽  
Low Complexity ◽  
Estimation Accuracy ◽  
Hybrid Architecture

Abstract In this journal, we investigate the beam-domain channel estimation and power allocation in hybrid architecture massive multiple-input and multiple-output (MIMO) communication systems. First, we propose a low-complexity channel estimation method, which utilizes the beam steering vectors achieved from the direction-of-arrival (DOA) estimation and beam gains estimated by low-overhead pilots. Based on the estimated beam information, a purely analog precoding strategy is also designed. Then, the optimal power allocation among multiple beams is derived to maximize spectral efficiency. Finally, simulation results show that the proposed schemes can achieve high channel estimation accuracy and spectral efficiency.

Subcarrier and Power Allocation Algorithm for Spectral Efficiency Maximization in Superposition Coding OFDMA Systems

2015 ◽  
Vol 24 (05) ◽  
pp. 1550061
Author(s):  
Mateus de Paula Marques ◽  
Taufik Abrão
Keyword(s):  
Power Allocation ◽  
Spectral Efficiency ◽  
Time Complexity ◽  
Multiple Access ◽  
Optimization Problem ◽  
Frequency Division ◽  
Superposition Coding ◽  
Ofdma System ◽  
Transmission Strategy ◽  
Throughput Gain

This paper addresses the optimization problem on subcarrier and power allocation of orthogonal frequency division multiple access (OFDMA) system under spectral efficiency (SE) metric when deploying superposition coding (SC) transmission strategy. An algorithm with polynomial time complexity, of the order of (UN log 2(N)) has been proposed for sub-optimal SE maximization. Results indicate that the system SE increases with the use of SC technique. Besides, the throughput gain with SC adoption increases when the number of users (U) approaches the number of subcarriers (N) available in the system.

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