1 / 5

Multi User Detection for CDMA

Multi User Detection for CDMA. Group Members: -Bhushan G. Jagyasi -Himanshu Soni. Multiple Access Interference(MAI). Conventional Detector. Modula- tion. Modula- tion. b 1 (.). b^ 1 (.). Decision. AWGN. g1. g1. b^ 2 (.). b 2 (.). Decision. g2. g2. r(t).

griggsv
Télécharger la présentation

Multi User Detection for CDMA

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. Multi User Detection for CDMA Group Members: -Bhushan G. Jagyasi -Himanshu Soni

  2. Multiple Access Interference(MAI) • Conventional Detector Modula- tion Modula- tion b1(.) b^1(.) Decision AWGN g1 g1 b^2(.) b2(.) Decision g2 g2 r(t) Noisy Channel b^n(.) Decision bn(.) gn gn Reciever / Detector Received signal , r(t) = b1g1f1+ b2g2f2+ ……bngnfn + n(t) After detector y(t)=b^1(t) = b1.g1.g1. f1+ b2.g2.g1.f2+ ……bn.gn.g1.fn + no.g1 y(t) = b1 f1 + MAI + zk

  3. Actual Problem y(t) = b1. f1 + MAI + zk • Total Interference (Includes interference due to other cells also) I = IMAI + f IMAI where f= Ratio of other cell MAI / IMAI • Near Far Problem in CDMA • Difficulty to implement more sophisticated algo at receiver because of limitations of size, cost, weight of handset. • Solutions to all such problems is Multi-user detection 0

  4. Genre of Multi-user detctors • NonBlind Multiuser detection algorithm • Detectors Available • Linear Detector (LMS based) • Subtractive interference canceller • Requires following information • Spreading waveform of desired signal • Spreading waveform of interfering signal • Timing (pd) of desired signal • Timing (pd) of interfering signal • Training data for every active user • Drawback • More Computational complexity. • Requires much more information.

  5. Genre of Multi-user detctors • Blind multiuser detection algorithm • Detectors Available • Kalman based • Requires following information • Spreading waveform of desired signal • Timing (pd) of desired signal • Turbo MUD: • Joint channel decoding and MUD using iterative exchange of information between two processes.

More Related