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Smart antennas and MAC protocols in MANET

- Lili Wei
- 2004-12-02

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

Part I Smart antennas-- basic concepts and

algorithms

Background Knowledge

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

SDMA

- Spatial Division Multiple Access
- ---- Uses an array of antennas to provide control

of space - by providing virtual channels in an angle

domain

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

System Model

- Uniform Linear Array of M elements

d

System Model

Narrow Band array processing Assumption

Array response vector

System Model

The Beam-former Structure

A simple example

Design a beamformer with unit response at 600

and nulls at 00, -300, -750

Optimum Beamformer Design

- Signal in AWGN and Interference

Optimum Beamformer Design

Under different criterions

- Maximum SINR beamformer

- Mean-Square-Error optimum beamformer

Optimum Beamformer Design

Under different criterion

- Minimum-Variance-Distortionless-Response

beamformer

- Maximum Likelihood optimal beamformer

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

Adaptive Beamforming Algorithms

Block diagram of adaptive beamforming system

Adaptive Beamforming Algorithms

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

Adaptive Beamforming Algorithms

- 1. SMI Algorithm (Sample Matrix Inverse)

Estimate R using N samples

Use matrix inversion lemma

Then

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.

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.

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

DOA Estimation Method

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

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

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

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

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

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

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

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

Part II Schemes using directional antennas

in MAC layer of ad hoc network

RTS/CTS mechanism in 802.11

A

B

C

D

E

RTS

RTS

CTS

CTS

DATA

DATA

ACK

ACK

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.

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

Vaidya Scheme 1

A

B

C

D

E

DRTS

OCTS

OCTS

DRTS

OCTS

OCTS

DATA

DATA

ACK

ACK

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.

A possible scenario of collisions

A

B

C

D

DRTS

OCTS

DRTS

OCTS

DATA

DRTS

ACK

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.

Vaidya Scheme 2

A

B

C

D

F

ORTS

ORTS

OCTS

DRTS

OCTS

DATA

ACK

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)

But what if we have no location information ?

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.

Nasipuri Scheme

CTS

CTS

4

3

B

1

2

CTS

CTS

RTS

RTS

Data

4

3

A

1

2

RTS

RTS

Nasipuri Scheme

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)

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.

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.

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

Bagrodia Scheme

- A network situation where DVCS can improve the

network capacity with DNAVs

A

C

F

E

B

D

Bagrodia Scheme

- Performance

Summary of Part II

- Comparison of four schemes

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

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)