Smart antennas and MAC protocols in MANET

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Smart antennas and MAC protocols in MANET

• Lili Wei
• 2004-12-02

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Contents

• Smart antennas basic concepts and algorithms
• Background knowledge
• System model
• Optimum beamformer design
• Adaptive beamforming algorithms
• DOA estimation method
• Schemes using directional antennas in MAC layer
  of ad hoc network
• Vaidya scheme1
• Vaidya scheme2
• Nasipuri scheme
• Bagrodia scheme

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Part I Smart antennas-- basic concepts and
algorithms
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Background Knowledge

• Basic challenge in wireless communication
• ---- finite spectrum or bandwidth
• Multiple access schemes
• FDMA
• TDMA
• CDMA

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SDMA

• Spatial Division Multiple Access
• ---- Uses an array of antennas to provide control
  of space
• by providing virtual channels in an angle
  domain

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Directional Antennas

• Sectorised antenna

• Smart antenna

• 1) switched beam system
• Use a number of fixed beams
• Select one of several beams to enhance receive
  signals

• 2) adaptive array system
• Be able to change its antenna pattern dynamically

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System Model

• Uniform Linear Array of M elements

d
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System Model
Narrow Band array processing Assumption
Array response vector
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System Model
The Beam-former Structure
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A simple example
Design a beamformer with unit response at 600
and nulls at 00, -300, -750
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Optimum Beamformer Design

• Signal in AWGN and Interference

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Optimum Beamformer Design
Under different criterions

• Maximum SINR beamformer

• Mean-Square-Error optimum beamformer

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Optimum Beamformer Design
Under different criterion

• Minimum-Variance-Distortionless-Response
  beamformer

• Maximum Likelihood optimal beamformer

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Practical Issues
Issues

• In practice, neither R nor RIN is available to
  calculate the optimal weights of the array
• In practice, direction of arrival (DOA) is also
  unknown.

Solution

• Adaptive beamforming algorithms the weights are
  adjusted by some means using the available
  information derived from the array output, array
  signal and so on to make an estimation of the
  optimal weights
• DOA estimation methods

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Adaptive Beamforming Algorithms
Block diagram of adaptive beamforming system
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Adaptive Beamforming Algorithms

• SMI Algorithm (Sample Matrix Inverse)
• LMS Algorithm (Least Mean Square)
• RLS Algorithm (Recursive Least Square)
• CMA (Constant Modulus Algorithm)

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Adaptive Beamforming Algorithms

• 1. SMI Algorithm (Sample Matrix Inverse)

Estimate R using N samples
Use matrix inversion lemma
Then
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Adaptive Beamforming Algorithms
2. LMS Algorithm (Least Mean Square)
According to orthogonality principle (data
error) of MMSE beamformer
Solution

• Need training bits and calculate the error
  between the received signal after beamforming and
  desired signal
• The step size u decides the convergence of LMS
  algorithm
• Based on how to choose u, we have a set of LMS
  algorithm, unconstraint LMS, normalized LMS,
  constraint LMS.

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Adaptive Beamforming Algorithms
3. RLS Algorithm (Recursive Least Square)
Given n samples of received signal r(t),
consider the optimization problemminimize the
cumulative square error
Solution

• In some situation LMS algorithm will converge
  with very slow speed, and this problem can be
  solved with RLS algorithm.

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Adaptive Beamforming Algorithms
4. CMA (Constant Modulus Algorithm)
Assume the desired signal has a constant
modulus, the existence of an interference causes
fluctuation in the amplitude of the array output.
Consider the optimization problem
Solution

• This is a blind online adaptation, i.e., dont
  need training bits
• CMA is useful for eliminating correlated arrivals
  with different magnitude and is effective for
  constant modulated envelope signals such as GMSK
  and QPSK

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DOA Estimation Method

• MF Algorithm (Matched Filter)
• MVDR Algorithm
• MUSIC Algorithm (MUltiple SIgnal Classification)

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DOA Estimation Method

• MF Algorithm (Matched Filter)

The total output power of the conventional
beamformer is

• The output power is maximized when
  
• The beam is scanned over the angular region
  say,(-900,900), in discrete steps and calculate
  the output power as a function of AOA
• The output power as a function of AOA is often
  termed as the spatial spectrum
• The DOA can be estimated by locating peaks in the
  spatial spectrum
• This works well when there is only one signal
  present
• But when there is more than one signal present,
  the array output power contains contribution from
  the desired signal as well as the undesired ones
  from other directions, hence has poor resolution

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DOA Estimation Method
2. MVDR Algorithm
This technique form a beam in the desired
look direction while taking into consideration of
forming nulls in the direction of interfering
signals.
Solution

• By computing and plotting pMVDR over the whole
  angle range, the DOAs can be estimated by
  locating the peaks in the spectrum
• MVDR algorithm provides a better resolution when
  compared to MF algorithm
• MVDR algorithm requires the computation of a
  matrix inverse, which can be expensive for large
  arrays

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DOA Estimation Method
Comparison of resolution performance of MF and
MVDR algorithms
Scenario Two signals of equal power at SNR of
20dB arrive at a 6-element uniformly
spaced array at angles 90 and 100 degrees,
respectively
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DOA Estimation Method
3. MUSIC Algorithm (MUltiple SIgnal
Classification)
MUSIC is a high resolution multiple signal
classification technique based on exploiting the
eigenstructure of the input covariance matrix.
Step 1 Collect input samples and estimate the
input covariance matrix
Step 2 Perform eigen decomposition
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DOA Estimation Method
3. MUSIC Algorithm (MUltiple SIgnal
Classification)
Step 3 Estimate the number of signals based on
the fact

• The first K eigen vectors represent the signal
  subspace, while the last M-K eigen vectors
  represent the noise subspace
• The last M-K eigen values are equal and equal to
  the noise variance

find the D smallest eigen values that almost
equal to each other
Step 4 Compute the MUSIC spectrum
find the largest peaks of Pmusic to
obtain estimates of DOA
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DOA Estimation Method
Comparison of resolution performance of MVDR and
MUSIC
Scenario Two signals of equal power at SNR of
20dB arrive at a 6-element uniformly
spaced array at angles 90 and 95 degrees,
respectively
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Summary of Part I

• System model
• Optimum beamformer design
• Adaptive beamforming algorithms
• 1) SMI
• 2) LMS
• 3) RLS
• 4) CMA
• DOA estimation method
• 1) MF
• 2) MVDR
• 3) MUSIC

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Part II Schemes using directional antennas
in MAC layer of ad hoc network
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RTS/CTS mechanism in 802.11
A
B
C
D
E
RTS
RTS
CTS
CTS
DATA
DATA
ACK
ACK
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RTS/CTS mechanism in 802.11

• Nodes are assumed to transmit using
  omni-directional antennas.
• Both RTS and CTS packet contain the proposed
  duration of data transmission
• The area covered by the transmission range of
  both the sender(node B) and the receiver (node C)
  is reserved during the data transfer
• This mechanism reduce collisions due to the
  hidden terminal problem
• However, it waste a large portion of network
  capacity.

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Vaidya Scheme 1

• Assumption
• Each node knows its exact location and the
  location of its neighbors
• Each node is equipped with directional antennas
• If node X received RTS or CTS related to other
  nodes, then node X will not transmit anything in
  that direction until that other transfer is
  completed
• That direction or antenna element would be said
  to be blocked
• While one directional at some node be blocked,
  other directional at the same nodes may not be
  blocked, allowing transmission using the
  unblocked antenna

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Vaidya Scheme 1
A
B
C
D
E
DRTS
OCTS
OCTS
DRTS
OCTS
OCTS
DATA
DATA
ACK
ACK
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Vaidya Scheme 1

• Utilize a directional antenna for sending the RTS
  (DRTS), whereas CTS are transmitted in all
  directions (OCTS).
• Data and ACK packets are sent directionally.
• Any other node that hears the OCTS only blocks
  the antenna on which the OCTS was received.

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A possible scenario of collisions
A
B
C
D
DRTS
OCTS
DRTS
OCTS
DATA
DRTS
ACK
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Vaidya Scheme 2

• A node uses two types RTS packets DRTS and ORTS
  according to the following rules
• 1) if none of the directional antennas at node X
  are blocked, then node X will send ORTS
• 2) otherwise, node X will send a DRTS provided
  that the desired directional antenna is not
  blocked.

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Vaidya Scheme 2
A
B
C
D
F
ORTS
ORTS
OCTS
DRTS
OCTS
DATA
ACK
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Performance
5
10
15
20
25
4
9
14
19
24
3
8
13
18
23
2
7
12
17
22
1
6
11
16
21

• Simulation mesh Topology (5X5)

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But what if we have no location information ?
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Nasipuri Scheme

• Node A that wishes to send a data packet to B
  first sends an omni-directional RTS packet
• Node B receives RTS correctly and responds by
  transmitting a CTS packet, again on all
  directions.
• In the meanwhile, B can do DOA estimation from
  receiving RTS packet
• Similarly, node A estimates the direction of B
  while receiving the CTS packet.
• Then node A will proceed to transmit the data
  packets on the antenna facing the direction of B.

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Nasipuri Scheme
CTS
CTS
4
3
B
1
2
CTS
CTS
RTS
RTS
Data
4
3
A
1
2
RTS
RTS
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Nasipuri Scheme
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Bagrodia Scheme

• Directional Virtual Carrier Sensing(DVCS)
• Three primary capabilities are added to original
  802.11 MAC protocol for directional communication
  with DVCS
• 1) caching the Angle of Arrival (AOA)
• 2) beam locking and unlocking
• 3) the use of Directional Network Allocation
  Vector (DNAV)

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Bagrodia Scheme

• 1. AOA caching
• Each node caches estimated AOAs from neighboring
  nodes whenever it hears any signal, regardless of
  whether the signal is sent to it or not
• When node X has data to send, it searches its
  cache for the AOA information, if the AOA is
  found, the node will send a directional RTS,
  otherwise, the RTS is send omni-directionally.
• The node updates its AOA information each time it
  receives a newer signal from the same neighbor.
• It also invalidates the cache in case if it fails
  to get the CTS after 4 directional RTS
  transmission.

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Bagrodia Scheme

• 2. Beam locking and unlocking

(2)CTS
(3)Data
A
B
(4)ACK
B
(1)RTS

• When a node gets an RTS, it locks its beam
  pattern towards the source to transmit CTS
• The source locks the beam pattern after it
  receives CTS .
• The beam patterns at both sides are used for both
  transmission and reception, and are unlocked
  after ACK is completed.

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Bagrodia Scheme

• 3. DNAV setting
• DNAV is a directional version of NAV(used in the
  original 802.11 MAC), which reserves the channel
  for others only in a range of directions.

• In the fig
• Three DNAVs are set up towards 300, 750 and 3000
  with 600 width.
• Until the expiration of these DNAVs, this mode
  cannot transmit any signals with direction
  between 0-1050 or 270-3300 , but is allowed to
  transmit signals towards 105-2700 and 330-3600

Available directions for transmission
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Bagrodia Scheme

• A network situation where DVCS can improve the
  network capacity with DNAVs

A
C
F
E
B
D
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Bagrodia Scheme

• Performance

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Summary of Part II

• Comparison of four schemes

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Conclusion

• smart antenna is a technology for wireless
  systems that use a set of antenna elements in an
  array. The signal from these antenna elements are
  combined to form a movable beam pattern that can
  be steered to a desired direction
• smart antennas enable spatial reuse and they
  increase the communication range because of the
  directivity of the antennas
• smart antennas can be beneficial for wireless ad
  hoc networks to enhance the capacity of the
  network
• To best utilize directional antennas, a suitable
  MAC protocol must be designed
• If the locations are unknown , DOA estimation may
  be needed before sending directional signals

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reference

• J.C.Liberti, T.S.Rappaport, Smart antennas for
  wireless communications IS-95 and third
  generation CDMA applications
• L.C.Godara, Application of antenna arrays to
  mobile communicaitions, part I performance
  improvement, feasiblility, and system
  considerations
• L.C.Godara, Application of antenna arrays to
  mobile communications, part II beam-forming and
  direction-of-arrival considerations
• Y.b Ko, V.Shankarkumar and N.Vaidya, Medium
  access control protocols using directional
  antennas in ad hoc networks
• A.Nasipuri, S.Ye, J.You and R.Hiromoto, A MAC
  protocol for mobile ad hoc networks using
  directional antennas
• M.Takai, J.Martin, A.Ren and R.Bagrodia,
  Directional virtual carrier sensing for
  directional antennas in mobile ad hoc networks
• S.Bellofiore, J.Foutz, etc.. Smart antenna
  system analysis, integration and performance for
  mobile ad-hoc networks (MANETs)