READ ME File For 'Dataset for Near-Instantaneously Adaptive Multi-Set Space-Time Shift Keying for UAV-Aided Video Surveillance'
 

ReadMe Author: Yanqing Zhang, University of Southampton [https://orcid.org/0000-0003-2349-1925]

This dataset supports the publication:
AUTHORS: Yanqing Zhang, Chao Xu, Ibrahim Hemadeh, Mohammed El-Hajjar, Lajos Hanzo
TITLE: Near-Instantaneously Adaptive Multi-Set Space-Time Shift Keying for UAV-Aided Video Surveillance
JOURNAL: IEEE Transactions on Vehicular Technology
PAPER DOI IF KNOWN: 10.1109/TVT.2020.3012208


This dataset contains: 6 simulation figures


The figures are as follows:

Fig. 9  The MS-STSK(4,2,2,2,32,16)|QAM scheme's MI curve for transmission over Ricean fading channels (K = 0 dB) at the channel SNR of 6 dB 
Fig. 11  MI performance of our MS-STSK(4,2,2,4,4)|QAM under two different normalized Doppler frequencies, when K = 0 dB at a channel SNR of 7 dB
Fig. 13  PDF of the three fixed modes of operation
Fig. 14  : Video quality in Y-PSNR versus time for UEPassisted adaptive design, Mode 1, Mode 2 and Mode 3, respectively, for mobility Scenario 1 at the average channel SNR of 12 dB
Fig. 15  The comparison between the three fixed modes and the adaptive system, where the first, second and third
column represent the PLR value of the l1, the e-PLR value of l2 and the image quality (PSNR), respectively, for
mobility Scenario 1 and 3 
Fig. 16  Image quality (Y-PSNR) versus mobility scenarios for the EEP and UEP schemes
  

Related projects:
L. Hanzo would like to acknowledge the financial support of the Engineering and Physical Sciences Research Council projects EP/Noo4558/1, EP/PO34284/1, COALESCE, of the Royal Society's Global Challenges Research Fund Grant as well as of the European Research Council's Advanced Fellow Grant QuantCom

M. El-Hajjar would like to acknowledge the financial support of the
Royal academy of Engineering industrial fellow grant

Date that the file was created: July, 2020