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Transcript of Tech
A Seminar on
Evaluation of the Efficacy of Forward Error Correction Coding
ByB.Divya
(09B91A0511)
AGENDA
1. Abstract2. Introduction 3. System architecture4. Existing system5. proposed system6. Modules7. Modules Description8. Advantages9. Experimental Setup10. Conclusion11. References
ABSTRACT
We propose a model-based analytic approach for evaluating the overall efficacy of
FEC coding combined with interleaving in combating packet losses in IP networks.
The loss of various packets during the data transmission can be reduced by using
FEC coding.
In this , we are going to evaluate the efficacy of FEC coding. Particularly modeling
the network path in terms of a single bottleneck node.
We develop a recursive procedure for the exact evaluation of the packet-loss
statistics for general arrival processes, based on a framework.
We study both single-session and multiple-session scenarios, and provide a simple
algorithm for the more complicated multiple-session scenario.
INTRODUCTION
THE packet transport service provided by representative packet-switched
networks, including IP networks, is not reliable and the quality-of-service (QoS)
cannot be guaranteed.
Packets may be lost due to buffer overflow in switching nodes, be discarded due to
excessive bit errors and failure to pass the cyclic redundancy check (CRC) at the
link layer,.
Forward error correction (FEC) coding has often been proposed for end-to-end
recovery from such packet losses.
However, the use of FEC in this application provides a double-edged sword.
From an end user’s perspective, FEC can help recover the lost packets in a timely
fashion through the use of redundant packets.
SYSTEM ARCHITECTURE
EXISTING SYSTEM
For analysis purposes the packet-loss process resulting from the single-multiplexer model was assumed to be independent and, consequently, the simulation results provided show that this simplified analysis considerably overestimates the performance of FEC.
In existing system a recursive algorithm to compute the packet-loss statistics (block error density), through which the exact residual packet-loss rate after decoding was computed.
Surprisingly, all numerical results given indicates that the resulting residual packet-loss rates with coding are always greater than without coding, i.e., FEC is ineffective in this application.
The increase in the redundant packets added to the data will increase the performance, but it will also make the data large and it will also lead to increase in data loss.
PROPOSED SYSTEM
We propose a model-based analytic approach for evaluating the overall efficacy of
FEC coding more accurately than any existing system.
We study both single-session and multiple-session scenarios, and we reduce the
complexity in multiple-session scenario.
Our model has great potential in recovering the packet losses caused by
congestion at a bottleneck node of a packet-switched network, provided that the
coding rate and other coding parameters are appropriately chosen.
We show that the unified approach provides an integrated framework for exploring
the tradeoffs between the key coding parameters: specifically, Interleaving depths,
channel coding rates and block lengths.
MODULES OF THE FEC
FEC Encoder
Interleaver
Implementation of the Queue
De-Interleaver
FEC Decoder
Performance Evaluation
MODULE DESCRIPTION
FEC Encoder:
FEC is a system of error control for data transmission, where the sender adds
redundant data to its messages. This allows the receiver to detect and correct errors
(within some bounds) without the need to ask the sender for additional data. In this
module we add redundant data to the given input data, known as FEC Encoding.
Interleaver:
Interleaving is a way of arranging data in a non-contiguous way in order to
increase performance. It is used in data transmission to protest against burst errors. In
this module we arrange the data (shuffling) to avoid burst errors which is useful to
increase the performance of FEC Encoding.
MODULE DESCRIPTION
FEC Decoder:
In this module we recover the original data after the process of De-
Interleaving by extracting the original data from the lost packets.
Performance Evaluation:
In this module we calculate the overall performance of FEC Coding in
recovering the packet losses.
Implementation of the Queue:
In this module we receive the data from the sender and voluntarily
creating the packet loss in order to evaluate the performance of the FEC. Then we
transfer the data to the receiver.
De-Interleaver:
In this module we rearrange the data back to its original order
before Interleaving. This is known as the process of De-Interleaving
MODULE DESCRIPTION
IMAGES
IMAGES
IMAGES
IMAGES
ADVANTAGES
Forward Error Correction (FEC) enables a system to achieve a high degree of data
reliability, even with the presence of noise in the communications channel.
In systems where improvement using any other means (such as increased transmit
power or components that generate less noise) is very costly or impractical, FEC
can offer significant error control and performance gains.
In systems with satisfactory data integrity, designers may be able to implement
FEC to reduce the costs of the system without affecting the existing performance..
The introduction of the Per FEC line of FEC encoders and decoders makes
powerful FEC implementation a realistic goal for most digital communication and
storage systems. More than ever before, FEC is available for a wide range of
applications.
EXPERIMENTAL SETUP
Hardware:
PROCESSOR : PENTIUM IV 2.6 GHz
RAM : 512 MB
MONITOR : 15”
HARD DISK : 20 GB
CDDRIVE : 52X
KEYBOARD : STANDARD 102 KEYS
MOUSE : 3 BUTTONS
Software:
FRONT END : JAVA, SWING
TOOLS USED : JFRAME BUILDER
OPERATING SYSTEM: WINDOWS XP
CONCLUSION
FEC has great potential in recovering the packet losses caused by congestion at a
bottleneck node of a packet-switched network.
We developed a model to implement interleaving to improve the FEC performance
and determined how much interleaving depth is required for FEC to approach the
optimum performance.
We derived an upper bound on the end-to-end performance using FEC based on an
information-theoretic methodology, which is useful in predicting source rates that can
be supported with arbitrarily high reliability.