Channel Statistical OFDM Transmission System Resource Allocation Algorithm

Abstract In order to achieve high spectral efficiency in OFDM transmission system, it is necessary to put forward the corresponding efficient subcarrier and power allocation algorithm. Therefore, on the basis of understanding the basic principle and system structure of OFDM, this paper analyzes the corresponding allocation algorithm according to the multi-user water injection theory, and studies the final results, so as to provide an effective scientific basis for future channel statistics research.

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System resource allocation algorithm for multi-tenant SaaS application

2011 International Conference on Cloud and Service Computing ◽

10.1109/csc.2011.6138523 ◽

2011 ◽

Author(s):

Hongyong Yu ◽

Deshuai Wang

Keyword(s):

Resource Allocation ◽

Resource Allocation Algorithm ◽

Allocation Algorithm ◽

System Resource

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An Optimal Resource Allocation Algorithm in Cloud Computing Environment

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.733.779 ◽

2015 ◽

Vol 733 ◽

pp. 779-783 ◽

Cited By ~ 1

Author(s):

Lu Dai ◽

Jian Hua Li

Keyword(s):

Resource Allocation ◽

Cloud Computing ◽

Energy Optimization ◽

Scientific Basis ◽

Computing Environment ◽

Cloud Computing Environment ◽

Resource Allocation Algorithm ◽

Allocation Algorithm ◽

Optimal Resource ◽

And Performance

Resource allocation is a key technology of cloud computing. At present, the most of studies on resource allocation mainly focus on improving the overall performance by balancing the load of data center. This paper will design the experimental platform of resource allocation algorithm, energy optimization and performance analysis, obtain original achievements in scientific research ,for the resource allocation method based on immune algorithm and energy optimization in cloud computing to provide innovative ideas and scientific basis. This research has important significance for further study on resource allocation and energy optimization in cloud computing environment.

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Greedy Based Radio Resource Allocation Algorithm with Water Filling Power Control Scheme in D2D Underlaying Communication

Journal of Measurements Electronics Communications and Systems ◽

10.25124/jmecs.v8i1.3474 ◽

2021 ◽

Author(s):

Rezha Aulia Riyanda ◽

Nachwan Mufti Adriansyah ◽

Vinsensius Sigit Widhi Prabowo

Keyword(s):

Resource Allocation ◽

Energy Efficiency ◽

Power Control ◽

Greedy Algorithm ◽

Spectral Efficiency ◽

Channel Condition ◽

Resource Allocation Algorithm ◽

Allocation Algorithm ◽

Control Scheme ◽

Water Filling

Device to Device (D2D) is communication between two devices directly without the intervention of eNodeB.This communication can improve sum-rate, spectral efficiency, and decrease the workload of eNodeBbecause using the same spectrum frequency with Cellular User Equipment (CUE). But this communicationshould use the same resource simultaneously with CUE which is called D2D underlaying. This sharingresources also causes interference and should be managed using the resource allocation algorithm. In thiswork, the resource allocation is allocated in a single cell and uplink communication using joint greedyalgorithm with water filling power control scheme. This algorithm is compared with greedy, joint greedy,and greedy algorithm with water filling power control scheme. Joint greedy algorithm works based on thecapacity of eNodeB and D2D pair. While in water filling power control, the power of the user is managedbased on the channel condition and impact to energy efficiency. After all the resource is allocated, theparameter performance of the system is calculated, such as spectral efficiency, energy efficiency, and D2Dfairness. From the simulation result, joint greedy algorithm with water filling power control scheme result29,34 bps/Hz in spectral efficiency, 0.939 x 107 bps/watt in energy efficiency, and 0,996 in D2D fairness.

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Slicing Resource Allocation for eMBB and URLLC in 5G RAN

Wireless Communications and Mobile Computing ◽

10.1155/2020/6290375 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11 ◽

Cited By ~ 1

Author(s):

Tengteng Ma ◽

Yong Zhang ◽

Fanggang Wang ◽

Dong Wang ◽

Da Guo

Keyword(s):

Resource Allocation ◽

Spectral Efficiency ◽

Original Problem ◽

Optimal Solution ◽

Base Stations ◽

Mixed Integer ◽

Integer Programming Problem ◽

Network Slicing ◽

Resource Allocation Algorithm ◽

Allocation Algorithm

This paper investigates the network slicing in the virtualized wireless network. We consider a downlink orthogonal frequency division multiple access system in which physical resources of base stations are virtualized and divided into enhanced mobile broadband (eMBB) and ultrareliable low latency communication (URLLC) slices. We take the network slicing technology to solve the problems of network spectral efficiency and URLLC reliability. A mixed-integer programming problem is formulated by maximizing the spectral efficiency of the system in the constraint of users’ requirements for two slices, i.e., the requirement of the eMBB slice and the requirement of the URLLC slice with a high probability for each user. By transforming and relaxing integer variables, the original problem is approximated to a convex optimization problem. Then, we combine the objective function and the constraint conditions through dual variables to form an augmented Lagrangian function, and the optimal solution of this function is the upper bound of the original problem. In addition, we propose a resource allocation algorithm that allocates the network slicing by applying the Powell–Hestenes–Rockafellar method and the branch and bound method, obtaining the optimal solution. The simulation results show that the proposed resource allocation algorithm can significantly improve the spectral efficiency of the system and URLLC reliability, compared with the adaptive particle swarm optimization (APSO), the equal power allocation (EPA), and the equal subcarrier allocation (ESA) algorithm. Furthermore, we analyze the spectral efficiency of the proposed algorithm with the users’ requirements change of two slices and get better spectral efficiency performance.

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