1 / 15

Simulating The Basics Of A Cognitive Radio System

Simulating The Basics Of A Cognitive Radio System. Goal:. To Simulate Cognitive Radio System which is so effective that it can harvest more band-width in highly desired bands than is currently in use! – More than in use by cellular systems

elton
Download Presentation

Simulating The Basics Of A Cognitive Radio System

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Simulating The Basics Of A Cognitive Radio System

  2. Goal: • To Simulate Cognitive Radio System which is so effective that it can harvest more band-width • in highly desired bands than is currently in • use! • – More than in use by cellular systems • – More than in use by unlicensed bands • – More than in use by private mobile • systems • This represents a paradigm shift in technology!

  3. Why Cognitive Radio? • Today’s radio systems are not aware of their radio spectrum environment and operate in a specific frequency band. • In some locations or some times of the day, 70 percent of the allocated spectrum may be sitting idle. • New bandwidth-intensive wireless services are being offered. • Unlicensed users constrained to a few overloaded bands • Increasing number of users. • This growth requires more • spectral bandwidth to satisfy • the demand.

  4. What is a Cognitive Radio? • Intelligent radio that uses spectrum licensed to other users when they aren't using it. • – ‘Bandwidth Harvesting’ • It is a software-designed radio with cognitive software. • CR can sense the environment. • CR adapts its way of communication to minimize the caused interference. • CR coexists with the primary user (using the same frequency band) in two ways: Concurrent and Opportunistic. Figure:A four-nodes wireless sensor network scenario.

  5. When Will CR Happen? • Full Cognitive Radios do not exist at the moment and are not likely to emerge until 2030. • Requires practical implementation of fully flexible SDR technologies and the intelligence required to exploit them cognitively. • But, true cognition and fully flexible radios may not be needed. • Simple intelligence and basic reconfigurability at the physical layer could provide significant benefits over traditional types of radio. • CR prototypes to emerge within the next five years. • Some devices are already in use like WLANs

  6. Idea: • Dynamic Spectrum Access ( DSA ) • To fill the spectral holes with secondary users’ data.

  7. Our Code: Primary Users: Fc1 = 1000; Fc2 = 2000; Fc3 = 3000; Fc4 = 4000; Fc5 = 5000; Fs = 12000; x1 = cos(2*pi*1000*t); in_p = input('\nDo you want to enter first primary user Y/N: ','s'); if(in_p == 'Y' | in_p == 'y') y1 = ammod(x1,Fc1,Fs); end : : : in_p = input('Do you want to enter fifth primary user Y/N: ','s'); if(in_p == 'Y' | in_p == 'y') y5 = ammod(x1,Fc5,Fs); end y = y1 + y2 + y3 + y4 + y5; Pxx = periodogram(y); Hpsd = dspdata.psd(Pxx,'Fs',Fs); plot(Hpsd);

  8. Our Code: Secondary Users: in_p = input('\nDo you want to enter a secondary user Y/N: ','s'); if(in_p == 'Y' | in_p == 'y') chek1 = Pxx(25)*10000; chek2 = Pxx(46)*10000; chek3 = Pxx(62)*10000; Code Portion Skipped : : : else disp('all user slots in use. try again later,'); end

  9. Our Code: Emptying Slots: inp_t=input('do u want to empty a slot: ','s'); if(inp_t=='Y'|inp_t=='y') inp_t=input('which slot do u want to empty for ur entry: ','s'); switch(inp_t) case ('1') y1=0; disp('slot1 is fired'); y = y1 + y2 + y3 + y4 + y5; case('2') y2=0; disp('slot2 is fired'); y = y1 + y2 + y3 + y4 + y5; : : : otherwise disp('invalid slot entered'); end

  10. Our Code: Adding Noise & Attenuation: inp_t=input('do u want to add noise: ','s'); if(inp_t=='y'|inp_t=='Y') d = input('Enter the SNR in dB: '); figure Y = awgn(y,d); Pxx1 = periodogram(Y); Code Portion Skipped tm = 1-tem; Z = y.*tm; disp('attenuating'); grid on plot(Z);

  11. Results: Data assigned Allocated / Used Spectrum Band Un-allocated Bands / Spectrum Holes

  12. Results: Left over Spectral Gaps Spectral Gap Filled by modulating the new incoming user’s data over it

  13. Results:

  14. Applications: • Mobile multimedia downloads which require moderate data rates • Emergency communications services that require a moderate data rate and localized coverage (for example, video transmission from firemen’s’ helmets); • Broadband wireless networking (for example, using nomadic laptops), which needs high data rates, but where users may be satisfied with localized “hot spot” services; • Multimedia wireless networking services (e.g. audio/video distribution within homes) requiring high data rates.

  15. Thank You www.intcube.com/forum for requesting the complete project

More Related