Analysis of Retrial Queues for Cognitive Wireless Networks with Sensing Time of Secondary Users

2019 ◽  
pp. 77-91
Author(s):  
Kohei Akutsu ◽  
Tuan Phung-Duc
Keyword(s):  
Wireless Networks ◽  
Retrial Queues ◽  
Secondary Users ◽  
Cognitive Wireless Networks ◽  
Sensing Time

Queueing models for cognitive wireless networks with sensing time of secondary users

2021 ◽  
Author(s):  
Tuan Phung-Duc ◽  
Kohei Akutsu ◽  
Ken’ichi Kawanishi ◽  
Osama Salameh ◽  
Sabine Wittevrongel
Keyword(s):  
Wireless Networks ◽  
Queueing Models ◽  
Secondary Users ◽  
Cognitive Wireless Networks ◽  
Sensing Time

scholarly journals Multi-Band Spectrum Allocation Algorithm Based on First-Price Sealed Auction

2017 ◽  
Vol 17 (1) ◽  
pp. 104-112 ◽  
Author(s):  
Zijuan Shi ◽  
Gaofeng Luo
Keyword(s):  
Wireless Networks ◽  
Wireless Network ◽  
Economic Efficiency ◽  
Low Complexity ◽  
Spectrum Allocation ◽  
Band Spectrum ◽  
Auction Mechanism ◽  
Allocation Algorithm ◽  
Cognitive Wireless Networks ◽  
Allocation Process

Abstract Auction is often applied in cognitive wireless networks due to its fairness properties and efficiency. To solve the allocation issues of cognitive wireless network inamulti-band spectrum, multi-item auction mechanism and models were discussed in depth. Multi-item highest price sealed auction was designed for cognitive wireless networks’multi-band spectrum allocation algorithm. This algorithm divided the spectrum allocation process into several stages which was along with low complexity. Experiments show that the algorithm improves the utilization of spectrum frequency, because it takes into account the spectrum owner’s economic efficiency and the users’equity.

Spectrum access strategy for cognitive wireless networks sensing part of channels

2017 ◽  
Vol 77 (6) ◽  
pp. 7703-7716
Author(s):  
Xiaoli He ◽  
Hong Jiang ◽  
Yu Song
Keyword(s):  
Wireless Networks ◽  
Spectrum Access ◽  
Cognitive Wireless Networks

Large Scale Cognitive Wireless Networks

2013 ◽  
pp. 26-52
Author(s):  
Liang Song ◽  
Petros Spachos ◽  
Dimitrios Hatzinakos
Keyword(s):  
Energy Efficiency ◽  
Wireless Networks ◽  
Cognitive Radio ◽  
Data Aggregation ◽  
Network Architecture ◽  
Large Scale ◽  
Vehicular Networks ◽  
Network Resource ◽  
Cognitive Wireless Networks ◽  
Definition Of

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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