scholarly journals Cooperative resource management and power allocation for multiuser OFDMA networks

2017 ◽  
Vol 11 (16) ◽  
pp. 2552-2559 ◽  
Author(s):  
Mohamad Yassin ◽  
Samer Lahoud ◽  
Marc Ibrahim ◽  
Kinda Khawam ◽  
Dany Mezher ◽  
...  
Keyword(s):  
Resource Management ◽  
Power Allocation ◽  
Ofdma Networks ◽  
Cooperative Resource Management

Cooperative Resource Management in Cloud-Enabled Vehicular Networks

2015 ◽  
Vol 62 (12) ◽  
pp. 7938-7951 ◽  
Author(s):  
Rong Yu ◽  
Xumin Huang ◽  
Jiawen Kang ◽  
Jiefei Ding ◽  
Sabita Maharjan ◽  
...  
Keyword(s):  
Resource Management ◽  
Vehicular Networks ◽  
Cooperative Resource Management

scholarly journals Improving Power and Resource Management in Heterogeneous Downlink OFDMA Networks

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 203
Author(s):  
Nalliyanna Goundar Veerappan Kousik ◽  
Yuvaraj Natarajan ◽  
Kallam Suresh ◽  
Rizwan Patan ◽  
Amir H. Gandomi
Keyword(s):  
Resource Management ◽  
Power Consumption ◽  
Mode Selection ◽  
Selection Method ◽  
Small Cell ◽  
Performance Model ◽  
Sleep Mode ◽  
Hybrid Technique ◽  
Communication Performance ◽  
Ofdma Networks

In the past decade, low power consumption schemes have undergone degraded communication performance, where they fail to maintain the trade-off between the resource and power consumption. In this paper, management of resource and power consumption on small cell orthogonal frequency-division multiple access (OFDMA) networks is enacted using the sleep mode selection method. The sleep mode selection method uses both power and resource management, where the former is responsible for a heterogeneous network, and the latter is managed using a deactivation algorithm. Further, to improve the communication performance during sleep mode selection, a semi-Markov sleep mode selection decision-making process is developed. Spectrum reuse maximization is achieved using a small cell deactivation strategy that potentially identifies and eliminates the sleep mode cells. The performance of this hybrid technique is evaluated and compared against benchmark techniques. The results demonstrate that the proposed hybrid performance model shows effective power and resource management with reduced computational cost compared with benchmark techniques.

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