DISCRETE CHANNEL SIMULATION OF BLUETOOTH PICONETS

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_at_tsc.uc3m.es

2
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
  users needs
• Bluetooth devices transmit in ISM band

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

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

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

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)

7
Bluetooth Interference Inmunity and Multiple
Access Scheme

• Bluetooth uses the ISM band Interferences
  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

8
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

9
Bluetooth system block diagram
FRAME CONFORMING
10
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

11
Modelling the behaviour of the black box
How is the finite state channel model obtained?
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 t1
• 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)

13
Parameters of a Markov Model (II)
Transition probabilities
Two states
Input to output transition probabilities
14
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

15
Discrete channel simulation of Bluetooth piconets
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)

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.