implementation of fade mitigation techniques in satellite...

Implementation of Fade Mitigation Techniques in Satellite

Communication

Contents

Introduction

Fade mitigation techniques

Implementation of FMT

Block diagram of system

Block diagram of simulator

Results

Introduction

Challenges in Satellite communication

1. Saturated conventional(C, Ku) bands

2. Higher capacity-cost efficiency-good availability

The possible solutions could beGoing for higher frequency bands

1. Larger bandwidth

2. Reduced equipment size

3. Severe propagation impairments

4. Limited cost availability

Multibeam coverage with large number of narrow beams

Fade Mitigation Techniques

Fade mitigation techniques

Power Control : Transmitting power level changed in accordance with propagation impairments

Adaptive waveform : Fade compensated by a more efficient modulation and coding scheme

Diversity : Fade avoided by the use of another less impaired link

Layer 2 : Coping with the temporal dynamics of the fade

Different FMTs

POWER CONTROL: Four types of Power Control FMT can be considered :1. Up-Link Power Control (ULPC)2. End-to-End Power Control(EEPC)3. Down-Link Power Control (DLPC)4. On-Board Beam Shaping (OBBS).

ADAPTIVE WAVEFORM: These FMTs could be split into 1. Adaptive Coding (AC)2. Adaptive Modulation (AM)3. Data Rate Reduction (DRR).

DIVERSITY: Three types of diversity techniques can be considered: 1. site diversity2. satellite diversity3. frequency diversity

LAYER 2: Two different techniques can be envisaged at layer 2 1. Automatic Repeat Request (ARQ) 2. Time Diversity (TD).

Implementation of fade mitigation techniques

FMT activation

FMT no active

FMT active level 1

FMT active level 2

FMT active level n

Detection DecisionMonitored signal

FMT control logic

Block diagram of the system

DATA BITS

MODEM MODEM

Earth station

Earth station

Satellite

TX Processing

RX Processing

Block diagram of the system

DATA BITS

MODEM MODEM

Earth station

Earth station

Satellite

TX Processing

RX Processing

PER EstimationSNR EstimationFade Prediction

Data Rate Selection

Modem Interfacing

Tx-Stn Control Cmd.

Modem Interfacing

Block diagram of the system

DATA BITS

MODEM MODEM

Earth station

Earth station

Satellite

TX Processing

RX Processing

TX-Modem Interfacing

RX-Stn.Interfacing

PER EstimationSNR EstimationFade Prediction

Data Rate Selection

Modem Interfacing

Tx-Stn Control Cmd.

Modem Interfacing

TX

Block diagram of the simulator

DATA BITS

CRC

CODING

Y=1/h

M and C SELECTION

MODULATION

DEMODULATION

DECODING

CRC CHECK

PER Estimation

RECEIVED DATA BITS

SNR Estimation

X

h

X*h

N(h)

Y=X*h+n

INPUT BITS OUTPUT BITS

HPA

Prediction of Fade

Margin Correction

Rain Fade Model

RX

Interim RESULTS

PER versus SNR curves for different modulation schemes

0 5 10 15 20 25

10-2

10-1

100

PER performance for different ACM schemes

SNR (in dB)

PE

R

QPSK simulatedQPSK-1/2 simulatedQPSK-1/3 simulatedQPSK theoretical16-QAM simulated16-QAM-1/2 simulated16-QAM-1/3 simulated16-QAM theoretical64-QAM simulated64-QAM-1/2 simulated64-QAM-1/3 simulated64-QAM theoretical

Switching between different ACM schemes with time

0 10 20 30 40 50 60 70 80 90 100-4

-2

0

2

4

6

8

10

12

14

16

timeiunit=10sec

SN

R c

alcu

late

d in

dB

SNR calculatedSNR estimatedPER decision storedata rate M/C

Switching between different ACM schemes with time

0 50 100 150 200 250 300 350 400-4

-2

0

2

4

6

8

10

12

14

16

timeiunit=10sec

PE

R d

ecis

ion

PER decision storeSNR calculatedSNR estimateddata rate M/C

Module Wise Status Update

System Model (Framework) development (75%) Most of components already considered as described

To include HPA effects

Modem Specifications necessary for system design

Simulation Framework development (75%) Channel Model parameters necessary for algorithm design Modem-abstraction model simulation complete

Receiver noise as a function of attenuation implemented.

Fade Mitigation modules developed. Needs refinement

Synchronization to be included (need Modem specs)

Future Work Plan w.r.t. modules

TX

DATA BITS

CRC

CODING

Y=1/h

Data rate SELECTION

MODULATION

DEMODULATION

DECODING

CRC CHECK

PER Estimation

RECEIVED DATA BITS

SNR Estimation

X

h

X*h

N(h)

Y=X*h+n

INPUT BITS OUTPUT BITS

HPA

Prediction of Fade

Margin Correction

Rain Fade Model

RX

Future Work Plan w.r.t. modules

TX

DATA BITS

CRC

CODING

Y=1/h

Data rate SELECTION

MODULATION

DEMODULATION

DECODING

CRC CHECK

PER Estimation

RECEIVED DATA BITS

SNR Estimation

X

h

X*h

N(h)

Y=X*h+n

INPUT BITS OUTPUT BITS

HPA

Prediction of Fade

Margin Correction

Rain Fade Model

RX

Future Work Plan

Development of Fade detection algorithm (Channel Model parameters)

Modem interfacing and control logic (Modem Specs)

Refinement of Channel Model

PER Estimation

SNR Estimation

Data rate selection

Y=1/h

DEMODULATION

DECODING

RECEIVED DATA BITS

h N(h)

Y=X*h+n

OUTPUT BITS

RX

Budget

As per discussion in last meeting at IIT Kgp Rs 5 Lacs in total for each year.

Recruit one more personnel.

Status update (in details)

Earlier, for deciding the optimum ACM scheme, the channel attenuation value was assumed to be known at transmitter at every instant. This assumption has been relaxed now and a SNR detection module has been added to the system which uses CRC32 for estimating the SNR.

Channel attenuation not only influences the signal level but also influences the system noise temperature which increases the noise power. This was not considered in earlier simulator.

Future work (in details)

Increasing the accuracy of SNR estimation using betterSNR search algorithms

Increasing the accuracy of the channel model

Incorporating intelligence into the decision module forprevention of frequent switching between ACM schemes

Addition of the ability for short-term prediction of thechannel condition for further accuracy in choice of theoptimum ACM scheme

Faster SNR estimation for compensation of the delayassociated with the FMT loop

THANK YOU