Adaptive Network Resource Optimization for Heterogeneous VLC/RF Wireless Networks

2018 ◽  
Vol 66 (11) ◽  
pp. 5568-5581 ◽  
Author(s):  
Weihua Wu ◽  
Fen Zhou ◽  
Qinghai Yang
2021 ◽  
Vol 488 ◽  
pp. 126837
Author(s):  
K. Küçük ◽  
D.L. Msongaleli ◽  
O. Akbulut ◽  
A. Kavak ◽  
C. Bayılmış

2018 ◽  
Vol 67 (12) ◽  
pp. 11988-12002 ◽  
Author(s):  
Hui Wang ◽  
Minquan Cheng ◽  
Qingchun Chen ◽  
Xiaohu Tang ◽  
Qin Huang

Author(s):  
Liang Song ◽  
Petros Spachos ◽  
Dimitrios Hatzinakos

Cognitive radio has been proposed to have spectrum agility (or opportunistic spectrum access). In this chapter, the authors introduce the extended network architecture of cognitive radio network, which accesses not only spectrum resource but also wireless stations (networking nodes) and high-level application data opportunistically: the large-scale cognitive wireless networks. The developed network architecture is based upon a re-definition of wireless linkage: as functional abstraction of proximity communications among wireless stations. The operation spectrum and participating stations of such abstract wireless links are opportunistically decided based on their instantaneous availability. It is able to maximize wireless network resource utilization and achieve much higher performance in large-scale wireless networks, where the networking environment can change fast (usually in millisecond level) in terms of spectrum and wireless station availability. The authors further introduce opportunistic routing and opportunistic data aggregation under the developed network architecture, which results in an implementation of cognitive unicast and cognitive data-aggregation wireless-link modules. In both works, it is shown that network performance and energy efficiency can improve with network scale (such as including station density). The applications of large-scale cognitive wireless networks are further discussed in new (and smart) beyond-3G wireless infrastructures, including for example real-time wireless sensor networks, indoor/underground wireless tracking networks, broadband wireless networks, smart grid and utility networks, smart vehicular networks, and emergency networks. In all such applications, the cognitive wireless networks can provide the most cost-effective wireless bandwidth and the best energy efficiency.


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