1 / 17

DISCRETE CHANNEL SIMULATION OF BLUETOOTH PICONETS

DISCRETE CHANNEL SIMULATION OF BLUETOOTH PICONETS . Workshop on Broadband Wireless Ad-Hoc Networks and Services 12th - 13th September 2002, ETSI, Sophia Antipolis, France. Beatriz Bardón Rodríguez Matilde P. Sánchez Fernández Ana García Armada Department of Signal Theory and Communications

hester
Télécharger la présentation

DISCRETE CHANNEL SIMULATION OF BLUETOOTH PICONETS

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. DISCRETE CHANNEL SIMULATION OF BLUETOOTH PICONETS Workshop on Broadband Wireless Ad-Hoc Networks and Services 12th - 13th September 2002, ETSI, Sophia Antipolis, France Beatriz Bardón Rodríguez Matilde P. Sánchez Fernández Ana García Armada Department of Signal Theory and Communications Carlos III University of Madrid, Spain e-mail: {beatriz, mati, agarcia}@tsc.uc3m.es

  2. Worldwide availability of frequencies Bands also used by many other devices Rapid introduction to the market Degradation in throughput and quality Introduction and motivation • After the success of Wireless Local Area Networks (WLAN), Bluetooth has come out as an initiative to build Wireless Personal Area Network (WPAN) systems: • Idea: To connect every device that we are used to carry with us (cellular phones, PDAs, laptops, printers, …) • The success of Bluetooth depends on the massive use of the standard • Development of applications that respond to the user’s needs • Bluetooth devices transmit in ISM band Carlos III University of Madrid. Dept. Signal Theory and Communications

  3. Introduction and motivation (II) • The coexistence of a high number of devices in the same frequency band has a great impact in the applications • Design of Applications - two options: • Conservative to ensure a quick market introduction • Optimum in the sense of being capable of making fuller use of the possibilities of the communication • Simulation techniques • To analyse the different choices for new services • To characterise in detail every significant effect that influences the system performance Carlos III University of Madrid. Dept. Signal Theory and Communications

  4. Introduction and motivation (III) • To maintain a good characterisation of the system usually implies long simulation runs • The low bit error rates involved in the case of inclusion of some kind of channel coding imply a great computational cost in simulation • Simulations must be efficient in order to be feasible DISCRETE CHANNEL MODELS • Useful tool for simulating communication systems operating over fading channels • The bursty nature of errors generated is reproduced by means of a state diagram that avoids the simulation of the whole physical channel Carlos III University of Madrid. Dept. Signal Theory and Communications

  5. Outline • Bluetooth • Interference Inmunity and Multiple Access Scheme • Ad Hoc Networks • Discrete Channel Models for Wireless Communications • Parameters of a Markov Model • Estimating the parameters of the HMM • Discrete channel simulation of Bluetooth piconets • Conclusions Carlos III University of Madrid. Dept. Signal Theory and Communications

  6. Bluetooth • Provides ad-hoc connections via radio using portable devices characterized by • Low cost • Small size • Low power comsumption • 0 dBm for most applications • Specifications allow to transmit up to 20 dBm • This wireless technology must support both voice and data to be transmitted over a short range distance (up to 10 meters typically) Carlos III University of Madrid. Dept. Signal Theory and Communications

  7. Multiple Access Scheme • FH-CDMA (79 separate 1 MHz channels) • TDD (Time Division Duplex) A B Bluetooth: Interference Inmunity and Multiple Access Scheme • Bluetooth uses the ISM bandInterferences coming from other devices (microwave ovens, WLANs) and other Bluetooth devices • To obtain the desired interference inmunity Two options • Interference suppression DSSS • Interference avoidance FHSS Carlos III University of Madrid. Dept. Signal Theory and Communications

  8. S S M M S S S S M S M S S Bluetooth: Ad Hoc Networks • No difference between radio units (Peer communications) • One unit has the ‘master’ role governing the synchronization of the FH communication A master and one or several slaves (8 max) PICONET Two or more piconets overlapped in time and space SCATTERNET Carlos III University of Madrid. Dept. Signal Theory and Communications

  9. SCRAMBLING (whitening) SCRAMBLING (whitening) CODING DECODING • FEC 1/3 • NO CODE • FEC 1/3 • FEC 2/3 72 bits 54 bits 0-2745 bits FREQUENCY HOPPING FREQUENCY HOPPING GFSK MODULATOR ACCESS CODE HEADER HEADER PAYLOAD PAYLOAD Radio Channel GFSK DEMODULATOR BT = 0.5 0.28<h<0.35 • Multipath • Interferences (piconets, scatternets, other devices, ...) FRAME EXTRACTING Bluetooth: system block diagram FRAME CONFORMING Carlos III University of Madrid. Dept. Signal Theory and Communications

  10. b b a a DCM 2 DCM 2 b a physical channel physical channel signals (t) signals (t) b a symbols Demodulator Demodulator a’ a’ b’ b’ symbols symbols physical channel signals (t) LEVEL 2 LEVEL 2 Applications a’ a a a a b’ Deinterleaver, Interleaver, Deinterleaver, Interleaver, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Filters, Demodulator Modulator Modulator Modulator Modulator Modulator Modulator Modulator Modulator equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... equalizers, ... decoder,... encoder,... encoder,... decoder,... voice, symbols symbols symbols a’ physical channel physical channel physical channel physical channel signals (t) signals (t) signals (t) signals (t) b’ multimedia, ... LEVEL 2 Demodulator Demodulator Demodulator Demodulator LEVEL 1 LEVEL 1 LEVEL 1 LEVEL 1 LEVEL 1 LEVEL 1 a’ a’ a’ a’ Discrete Channel Model DCM 1 DCM 1 Discrete Channel Model Discrete Channel Model Generate symbols sequences with the same bursty characteristics Generate symbols sequences with the same bursty characteristics Generate symbols sequences with the same bursty characteristics physical channel signals (t) Demodulator Discrete Channel Models for Wireless Communications • Idea: To reproduce, by means of a state diagram, the bursty nature of errors generated in that type of channels • In order to obtain efficient models the simulation is structured in several levels Carlos III University of Madrid. Dept. Signal Theory and Communications

  11. b a Interleaver, encoder,... Deinterleaver, decoder,... a’ Simple cases Derived analytically from the models of the underlying components between a-a’ LEVEL 1 b’ Applications Filters, Filters, Modulator LEVEL 2 equalizers, ... equalizers, ... voice, multimedia, ... Channel state Describes the behaviour of the channel (a-a’) along time physical channel • Good conditions • Fading • Noise • Jamming, .., Demodulator Most cases Derived from simulated or measured error patterns between a-a’ Hidden Markov Models (HMM) Finite state channel We visualize the channel as being in one of a set of limited and identifiable conditions or states Modelling the behaviour of the black box How is the finite state channel model obtained? Carlos III University of Madrid. Dept. Signal Theory and Communications

  12. Parameters of a Markov Model • Set of states {1, 2, ...N} • State at time t: St • Set of state probabilities: Pi(t) = probability of being in state i at time t • Set of state transition probabilities: aij(t) = probability of going from state i at time t to state j at time t+1 • Set of input to output transition probabilities for each state: bi(ek) = probability of obtaining the error symbol ek when St = i (from the possible ones {e1, e2, ..., eM}) Carlos III University of Madrid. Dept. Signal Theory and Communications

  13. agb 0.3 0.9 0 0 1 1 0 0 1 1 0.7 0.1 0.7 0.1 0.3 0.9 abb agg abg bg0 = 0.9 bb0 = 0.3 Error symbols = { 0, 1 } bb1 = 0.7 bg1 = 0.1 Parameters of a Markov Model (II) Transition probabilities Two states Input to output transition probabilities Carlos III University of Madrid. Dept. Signal Theory and Communications

  14. State transition matrix Input to output transition probabilities matrix Estimating the parameters of the HMM • Under certain conditions all the parameters can be inferred from the estimation of two matrices • Problem to solve Estimate A and B • Data to start Error sequence obtained from the lowest level of simulation • Tool to use Well-known iterative procedure Baum-Welch algorithm • A pair of matrices A, B that generate error sequences with the same characteristics that the one used to train the algorithms are obtained Carlos III University of Madrid. Dept. Signal Theory and Communications

  15. SCRAMBLING (whitening) FRAME CONFORMING CODING GFSK MOD Error sequence to train the algorithm 1 = Erroneous decision 0 = Correct decision • Multipath (Channel models for HIPERLAN/2 in different indoor scenarios) • Interferences ( scatternets, microwave ovens, ...) Simulations with different coding schemes SCRAMBLING (whitening) FRAME EXTRACTING DECODING GFSK DEMOD Radio Channel GFSK signal Discrete channel simulation of Bluetooth piconets Carlos III University of Madrid. Dept. Signal Theory and Communications

  16. Discrete channel simulation of Bluetooth piconets (II) • The direct application of the Baum-Welch algorithm requires great amount of computations, specially when the error sequence contains long chains of identical symbols • K. S. Shanmugan et al. have proposed a modified version of the BW algorithm that involves great saving in computation • Once the parameters (A,B matrices) have been obtained it is indispensable to validate them for ensuring the use of the discrete channel model in upper levels of simulation • Comparison between the error sequence arising from the original physical layer and the one generated by our HMM • Cross-correlation between the two sequences • Histograms characterising error free intervals for the different guard times are obtained and compared (chi-square goodnes-of-fit test) Carlos III University of Madrid. Dept. Signal Theory and Communications

  17. Conclusions • A Discrete Channel simulation method for the efficient evaluation of Bluetooth radio system has been proposed . • Structuring the simulation in several levels and modelling them by means of Hidden Markov Models allows a great saving in computational resources. • It will be very useful to obtain models for different design options and environments. Need for standardisation: It would be very convenient to have these Discrete Channel Models standardised for WPAN (as it has been done with GSM) in order to be able to evaluate the performance of new applications. Carlos III University of Madrid. Dept. Signal Theory and Communications

More Related