1 / 25

Lecture 12

Lecture 12. Time Division Multiplexing Statistical Time Division Multiplexing Statistical Multiplexing Gains Wave Division Multiplexing Code Division Multiplexing. Many Lines. Fewer Trunks. Statistical Multiplexing. Many input lines are multiplexed into a few trunks

ami
Download Presentation

Lecture 12

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. Lecture 12 • Time Division Multiplexing • Statistical Time Division Multiplexing • Statistical Multiplexing Gains • Wave Division Multiplexing • Code Division Multiplexing ECS 152A Computer Networks

  2. Many Lines Fewer Trunks Statistical Multiplexing • Many input lines are multiplexed into a few trunks • Exploit the fact that not all users are making calls all the time • When a new call arrives and all the trunks are busy, the call is blocked (lost) • Key design issue • Given a demand, detemine the number of trunks that will maintain the blocking probability below a certain value ECS 152A Computer Networks

  3. N(t) all trunks busy t 1 2 trunk # 3 4 5 6 7 Blocking Model • An new arriving call is assigned a free trunk • A call uses the trunk for a call holding time • When all the trunks are busy, a new incoming call is blocked (“all circuits busy” message) ECS 152A Computer Networks

  4. l l l l l 1 2 C 0 3 k cm m 2m 3m km Computing the Blocking Probability • State of the system: number of active calls • Call arrival rate = l calls/second (Possion Process) • Call holding time = 1/m second (negative exponential) • Offered load a = l/m Erlangs • Blocking probability = ECS 152A Computer Networks

  5. Statistical Multiplexing Gain ECS 152A Computer Networks

  6. Optical MUX Optical deMUX 1 1 2 1 2 2. m Optical fiber m m Wave Division Multiplexing • Optical-domain version of FDM • Different information signals are modulated to different wavelengths and the combined signals sent through the fiber • Prism and difffraction gratings are used to combine/split signals ECS 152A Computer Networks

  7. (a) WDM chain network c b d a WDM Based Networks (b) WDM ring network a 3 ADMs b c ECS 152A Computer Networks

  8. Spread Spectrum • Analog or digital data • Analog signal • Spread data over wide bandwidth • Makes jamming and interception harder • Frequency hoping • Signal broadcast over seemingly random series of frequencies • Direct Sequence • Each bit is represented by multiple bits in transmitted signal • Chipping code ECS 152A Computer Networks

  9. Spread Spectrum Concept • Input fed into channel encoder • Produces narrow bandwidth analog signal around central frequency • Signal modulated using sequence of digits • Spreading code/sequence • Typically generated by pseudonoise/pseudorandom number generator • Increases bandwidth significantly • Spreads spectrum • Receiver uses same sequence to demodulate signal • Demodulated signal fed into channel decoder ECS 152A Computer Networks

  10. General Model of Spread Spectrum System ECS 152A Computer Networks

  11. Advantages • Immunity from various noise and multipath distortion • Including jamming • Can hide/encrypt signals • Only receiver who knows spreading code can retrieve signal • Several users can share same higher bandwidth with little interference • Cellular telephones • Code division multiplexing (CDM) • Code division multiple access (CDMA) ECS 152A Computer Networks

  12. Pseudorandom Numbers • Generated by algorithm using initial seed • Deterministic algorithm • Not actually random • If algorithm good, results pass reasonable tests of randomness • Need to know algorithm and seed to predict sequence ECS 152A Computer Networks

  13. Frequency Hopping Spread Spectrum (FHSS) • Signal broadcast over seemingly random series of frequencies • Receiver hops between frequencies in sync with transmitter • Eavesdroppers hear unintelligible blips • Jamming on one frequency affects only a few bits ECS 152A Computer Networks

  14. Basic Operation • Typically 2k carriers frequencies forming 2k channels • Channel spacing corresponds with bandwidth of input • Each channel used for fixed interval • 300 ms in IEEE 802.11 • Some number of bits transmitted using some encoding scheme • May be fractions of bit (see later) • Sequence dictated by spreading code ECS 152A Computer Networks

  15. Frequency Hopping Example ECS 152A Computer Networks

  16. Direct Sequence Spread Spectrum (DSSS) • Each bit represented by multiple bits using spreading code • Spreading code spreads signal across wider frequency band • In proportion to number of bits used • 10 bit spreading code spreads signal across 10 times bandwidth of 1 bit code • One method: • Combine input with spreading code using XOR • Input bit 1 inverts spreading code bit • Input zero bit doesn’t alter spreading code bit • Data rate equal to original spreading code • Performance similar to FHSS ECS 152A Computer Networks

  17. Direct Sequence Spread Spectrum Example ECS 152A Computer Networks

  18. Approximate Spectrum of DSSS Signal ECS 152A Computer Networks

  19. Code Division Multiple Access (CDMA) • Multiplexing Technique used with spread spectrum • Start with data signal rate D • Called bit data rate • Break each bit into k chips according to fixed pattern specific to each user • User’s code • New channel has chip data rate kD chips per second • E.g. k=6, three users (A,B,C) communicating with base receiver R • Code for A = <1,-1,-1,1,-1,1> • Code for B = <1,1,-1,-1,1,1> • Code for C = <1,1,-1,1,1,-1> ECS 152A Computer Networks

  20. CDMA Example ECS 152A Computer Networks

  21. CDMA Explanation • Consider A communicating with base • Base knows A’s code • Assume communication already synchronized • A wants to send a 1 • Send chip pattern <1,-1,-1,1,-1,1> • A’s code • A wants to send 0 • Send chip[ pattern <-1,1,1,-1,1,-1> • Complement of A’s code • Decoder ignores other sources when using A’s code to decode • Orthogonal codes ECS 152A Computer Networks

  22. CDMA for DSSS • n users each using different orthogonal PN sequence • Modulate each users data stream • Using BPSK • Multiply by spreading code of user ECS 152A Computer Networks

  23. Seven Channel CDMA Encoding and Decoding ECS 152A Computer Networks

  24. CDMA Example ECS 152A Computer Networks

  25. CDMA Example ECS 152A Computer Networks

More Related