Reliable Multicast Video Transmission over Cognitive Radio Networks: Equal or Unequal Loss Protection? .......................................................................... ABDELAALI CHAOUB AND ELHASSANE IBN-ELHAJ

2014 ◽  
pp. 242-265
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Video Transmission ◽  
Radio Networks ◽  
Reliable Multicast ◽  
Unequal Loss Protection

Adaptive Bitrate Video Transmission Over Cognitive Radio Networks Using Cross Layer Routing Approach

2020 ◽  
Vol 6 (3) ◽  
pp. 935-945 ◽  
Author(s):  
Amjad Ali ◽  
Sikandar Tariq ◽  
Muddesar Iqbal ◽  
Li Feng ◽  
Imran Raza ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Video Transmission ◽  
Radio Networks ◽  
Cross Layer

On Efficient Channel Modeling for Video Transmission over Cognitive Radio Networks

2016 ◽  
Vol 91 (2) ◽  
pp. 919-932 ◽  
Author(s):  
Mohamed S. Hassan ◽  
Ayah Abusara ◽  
Menatalla Shehab El Din ◽  
Mahmoud H. Ismail
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Video Transmission ◽  
Channel Modeling ◽  
Radio Networks

Per-Subcarrier Antenna Selection for H.264 MGS/CGS Video Transmission Over Cognitive Radio Networks

2012 ◽  
Vol 61 (3) ◽  
pp. 1060-1073 ◽  
Author(s):  
Mohammud Z. Bocus ◽  
Justin P. Coon ◽  
C. Nishan Canagarajah ◽  
Simon M. D. Armour ◽  
Angela Doufexi ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Video Transmission ◽  
Antenna Selection ◽  
Radio Networks ◽  
Selection For

scholarly journals Channel Allocation Based on Content Characteristics for Video Transmission in Time-Domain-Based Multichannel Cognitive Radio Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-7
Author(s):  
Md. Jalil Piran ◽  
M. Ejaz Ahmed ◽  
Amjad Ali ◽  
Ju Bin Song ◽  
Doug Young Suh
Keyword(s):  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Video Transmission ◽  
Channel Allocation ◽  
Radio Networks ◽  
Spectrum Efficiency ◽  
Superior Performance ◽  
Network Bandwidth ◽  
Transmission Interruption

This paper proposes a method for channel allocation based on video content requirements and the quality of the available channels in cognitive radio networks (CRNs). Our objective is to save network bandwidth and achieve high-quality video delivery. In this method, the content is divided into clusters based on scene complexity and PSNR. To allocate channel to the clusters over multichannel CRNs, we first need to identify the licensee’s activity and then maximize the opportunistic usage accordingly. Therefore, we classify short and long time transmission opportunities based on the licensee’s activities using a Bayesian nonparametric inference model. Furthermore, to prevent transmission interruption, we consider the underlay mode for transmission of the clusters with a lower bitrate. Next, we map the available spectrum opportunities to the content clusters according to both the quality of the channels and the requirements of the clusters. Then, a distortion optimization model is constructed according to the network transmission mechanism. Finally, to maximize the average quality of the delivered video, an optimization problem is defined to determine the best bitrate for each cluster by maximizing the sum of the logarithms of the frame rates. Our extensive simulation results prove the superior performance of the proposed method in terms of spectrum efficiency and the quality of delivered video.

scholarly journals Resource Allocation for OFDMA-Based Cognitive Radio Networks with Application to H.264 Scalable Video Transmission

2011 ◽  
Vol 2011 (1) ◽  
Author(s):  
Mohammud Z. Bocus ◽  
Justin P. Coon ◽  
C. Nishan Canagarajah ◽  
Joe P. McGeehan ◽  
Simon M. D. Armour ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Cognitive Radio ◽  
Cognitive Radio Networks ◽  
Video Transmission ◽  
Radio Networks ◽  
Scalable Video
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