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