Average Throughput Performance of Greedy Policy in Cognitive Radio Enabled Vehicular Networks

Author(s):  
Omer Melih Gul
Author(s):  
Mohammad Asif Hossain ◽  
Rafidah Md Noor ◽  
Saaidal Razalli Azzuhri ◽  
Muhammad Reza Z'aba ◽  
Ismail Ahmedy ◽  
...  

2017 ◽  
Vol 30 (18) ◽  
pp. e3371 ◽  
Author(s):  
Kuldeep Yadav ◽  
Binod Prasad ◽  
Abhijit Bhowmick ◽  
Sanjay Dhar Roy ◽  
Sumit Kundu

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.


2011 ◽  
Vol 2011 ◽  
pp. 1-9 ◽  
Author(s):  
Haroon Rasheed ◽  
Nandana Rajatheva

Recent advancement in vehicular wireless applications is also a major contributing factor in spectrum scarcity. Cognitive radio system is a mechanism which allows unlicensed cognitive users (CUs) to utilize idle unused bands. Fast and reliable detection of primary legacy user is the key component of cognitive radio networks. However, hidden terminal and low SNR problems due to shadow fading put fundamental limit to the sensing performance and practical entailments in design of the cognitive vehicular networks. Extensive modeling is being carried out to specify varying channel characteristics, particularly multipath fading and shadowing. Energy detection-(ED-) based spectrum sensing is a viable choice for many vehicle-to-vehicle (V2V) and vehicle to-road-side infrastructure (V2I) communications. This paper examines the performance of spectrum sensing using ED over Gamma-shadowed Nakagami-m composite fading channel to cater for both small-and-large scale fading. The results highlight the notable impact of shadowing spread and fading severity on detection performance. The relevant simulation results are presented to support our analytical results for average detection probability. Furthermore, these results are investigated and compared to other compound and classical channels.


2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Yuben Qu ◽  
Chao Dong ◽  
Dawei Niu ◽  
Hai Wang ◽  
Chang Tian

We study how to utilize network coding to improve the throughput of secondary users (SUs) in cognitive radio networks (CRNs) when the channel quality is unavailable at SUs. We use a two-dimensional multiarmed bandit (MAB) approach to solve the problem of SUs with network coding under unknown channel quality in CRNs. We analytically prove the asymptotical-throughput optimality of the proposed two-dimensional MAB algorithm. Simulation results show that our proposed algorithm achieves comparable throughput performance, compared to both the theoretical upper bound and the scheme assuming known channel quality information.


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