Delay-Aware Dynamic Resource Allocation and ABS Configuration Algorithm in HetNets Based on Lyapunov Optimization

Tang, Lun; Wei, Yannan; Chen, Wan; Chen, Qianbin

doi:10.1109/access.2017.2761863

Cited by 10 publications

(2 citation statements)

References 15 publications

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“…In the process of merging the existing network, a large number of new problems will arise, such as the four points mentioned above. These problems will directly affect the security and stability of the network [5]. Only protocols that meet the requirements of the Internet of Things and ensure the safety and reliability of wireless sensor networks can solve these problems [6].…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Optimization Strategy of IoT Sensor Configuration Based on Genetic Algorithm‐Neural Network

Yang

2021

Journal of Sensors

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This article carries out the overall design framework of the IoT sensor data processing platform and analyzes the advantages of using the integrated construction platform. The platform is divided into two parts, a web management platform and a data communication system, and interacts with the database by integrating the business layers of the two into one. The web management platform provides configurable communication protocol customization services, equipment information, personal information, announcement information management services, and data collection information monitoring and analysis services. The collected data is analyzed by the sensor data communication service system and then provided to the web management platform for query and call. This paper discusses the theoretical basis of the combination of genetic algorithm and neural network and proposes the necessity of improving genetic algorithm. The improved level involves chromosome coding methods, fitness function selection, and genetic manipulation. We propose an improved genetic algorithm and use an improved genetic algorithm (IGA) to optimize the neural network structure. The finite element method is adopted, the finite element model is established, and the shock piezoelectric response is numerically simulated. The genetic neural network method is used to simulate the collision damage location detection problem. The piezoelectric sensor is optimized, and the optimal sensor configuration corresponding to its initial layout is obtained, which provides guidance for the optimal configuration of the actual piezoelectric sensor.

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Section: Introductionmentioning

confidence: 99%

[Retracted] Optimization Strategy of IoT Sensor Configuration Based on Genetic Algorithm‐Neural Network

Yang

2021

Journal of Sensors

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“…Wang and Huang jointly configure the parameters of ABS and discontinuous reception (DRX) to increase the energy efficiency of UEs while reducing their packet dropping ratios. Tang et al cope with both resource scheduling and ABS configuration by formulating a problem of stochastic optimization programming. They use the Lyapunov optimization technique to solve the problem, with the aim of raising the total throughput and reducing packet latency.…”

Section: Related Workmentioning

confidence: 99%

Efficient coordination of almost blank subframes with coupling macro cells in heterogeneous networks

Wang

Huang

2019

Int J Communication

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Heterogeneous networking is an inevitable trend in mobile communication systems, where macrocells and small cells coexist to provide the service of wireless access. The technique of enhanced inter-cell interference coordination (eICIC) is popularly used to mitigate signal interference among cells. A number of subframes are picked as almost blank subframes (ABSs), during which a macro-cell base station suspends data transmissions to improve signal quality of small cells that it covers. Since the throughput of macro cells drops to zero in an ABS, how to decide the number of ABSs (ie, the ABS ratio) and their positions (ie, the ABS placement) is critical. Many studies implicitly consider that every small cell resides in only one macro cell and they manage ABSs for each individual macro cell accordingly. In practice, some macro cells may cover the same small cells (called coupling macrocells) which makes the management of their ABSs depend on each other. To address this issue, the paper proposes an efficient coordination of ABS with coupling macro cells (ECO) algorithm. It divides the network into component subnetworks depending on whether macro cells are coupling or not. Then, ECO computes the ABS ratios for the macro cells in each component subnetwork based on multiple factors, including data rate, traffic demand, and quality of service (QoS) support. Moreover, ECO jointly places the ABSs of coupling macro cells to shorten packet latency. Experimental results show that the ECO algorithm not only increases the network throughput but also reduces the loss rate of real-time data. KEYWORDS almost blank subframe (ABS), coupling macro cells, heterogeneous network, interference management Int J Commun Syst. 2020;33:e4256.wileyonlinelibrary.com/journal/dac

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Energy-Efficient M2M Communications in for Industrial Automation

2020

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Delay-Aware Dynamic Resource Allocation and ABS Configuration Algorithm in HetNets Based on Lyapunov Optimization

Cited by 10 publications

References 15 publications

[Retracted] Optimization Strategy of IoT Sensor Configuration Based on Genetic Algorithm‐Neural Network

[Retracted] Optimization Strategy of IoT Sensor Configuration Based on Genetic Algorithm‐Neural Network

Efficient coordination of almost blank subframes with coupling macro cells in heterogeneous networks

Energy-Efficient M2M Communications in for Industrial Automation

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