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RE: stds-802-16-tg4: Call for input - Data Encoding



Octavian,

Here is my two cents on the error correction schemes.

Of the four methods suggested, I think block turbo codes provide the best
performance/price ratio.  I don't know much about convolutional turbo codes
- method 4, but in my opinion TPC is better than Convolutional or
Concatnated RS & Convolutional.  TPC is very good at handling burst noise,
which is typical of HUMAN environment; and its block structure lends well to
the TDD scheme.  TPC has the highest potential for performance -- closest to
Shannon limit, and has seen a lot of R&D works recently.  The other methods
either don't have as good performance, or are better suited for a different
noise environment, like AWGN or different applications, like streaming data.

I do want to suggest another method: RS with Eraser.  You basically
determine which block has error before correcting the data.  The advantage
is obvious.  I am no expert in it, but maybe someone else from 16.4 can
voice their opinions.

Talking about evaluating FEC schemes, I wonder if any 16.4 subscriber is
from AHA.  I gained most of my FEC knowledge from their products and
literature.  They have products in all kinds of FEC and therefore should
have the expertise to evaluate different technologies with a relatively
unbiased opinion.

I made up a table comparing the pros and cons of the 5 methods in
performance, implementation, and future growth.  I will try to copy and
paste below.  I have been told the reflector doesn't support attachments.
So I have to be a little creative.

Coding schemes		Convolutional
Examples			Viterbi
Applications		VOIP, video streaming
Performance: Pro		decent performance
Performance: Con		low code rate (typical 0.5); 
Implementation:Pro	easy implementation, cheap chip; 
Implementation:Con	sharp increase in complexity with increasing memory,
better suited for streaming data
Future Development	haven't seen much

Coding schemes		Concatnated RS & Convolutional
Examples			encode: RS + Viterbi; decode: Viterbi + RS
Applications		DSL?
Performance: Pro		high code rate (typical 0.93);     
Performance: Con		not as good performance as TPC, better for
AWGN than burst noise
Implementation:Pro	serial concatnation, less complex than TPC;
Implementation:Con	expensive chip
Future Development	haven't seen much

Coding schemes		Block Turbo 
Examples			Turbo Product Code
Applications		wireless MAN
Performance: Pro		good for burst error, highest potential for
performance; closest to Shannon limit; 
Performance: Con		output is not hard decision; CR used to be
<0.8, now 0.9 or higher
Implementation:Pro	block intrisically fits TDD
Implementation:Con	parallel concatnation more complex to implement;  
Future Development	much development recently

Coding schemes		Convolutional Turbo
Examples			don't know
Applications		don't know
Performance: Pro		slightly better performance than TPC for
higher BER; 
Performance: Con		probably lower code rate;  BER performance
floor
Implementation:Pro	don't know
Implementation:Con	better suited for streaming data
Future Development	don't know

Coding schemes		RS with Eraser
Examples			don't know
Applications		wireless LAN
Performance: Pro		high CR, good for burst error
Performance: Con		not as good as TPC, similar to Viterbi
Implementation:Pro	less complex than TPC
Implementation:Con	complex algorithm to determine bad block to erase
Future Development	don't know
--------------------------------------------------------------------------
Minfei Leng
Phone: (716)631-4584; Fax: (716)631-6080
Clearwire Technologies
P.O.Box 850
Buffalo, NY 14225-0850
www.clearwire.com


> -----Original Message-----
> From: Octavian Sarca [mailto:osarca@redlinecommunications.com]
> Sent: Monday, April 09, 2001 7:49 PM
> To: Stds-802-16-Tg4 (E-mail)
> Subject: stds-802-16-tg4: Call for input - Data Encoding
> 
> 
> Dear Colleagues,
> 
> I would like to receive input on the Data Encoding ASAP. As we
> discussed, this section contains:
> 1. Data randomizer (scrambler)
> 2. FEC
> 3. Interleaving
> Since we did not reach an agreement on these choices and 
> based on Sanjay
> recommendation, we have to include all the proposed/discussed 
> methods in
> this section. Since FEC and interleaving are strongly related each
> other, I would suggest organizing the section as follows:
> 
> 4. Data Encoding
> 4.1. Data randomizer
> 4.1.1. Method 1 - As in 802.11a
> 4.1.2. Method 2 - As in DVB
> 4.2. Encoding and interleaving
> 4.2.1. Method 1 - Convolutional
> 4.2.1.1. Convolutional encoder
> 4.2.1.2. Interleaving
> 4.2.2. Method 2 - Concatenated RS and convolutional w/ tail biting 
> 4.2.2.1. RS encoder
> 4.2.2.2. Convolutional encoder
> 4.2.2.3. Interleaving
> 4.2.3. Method 3 - Block turbo codes
> 4.2.3.1. Block turbo encoder
> 4.2.3.2. Interleaving
> 4.2.4. Method 4 - Convolutional turbo codes
> 4.2.4.1. Convolutional turbo encoder
> 4.2.4.2. Interleaving
> 
> I can review the randomizer (4.1.1.) and the convolutional part (i.e.
> 4.2.1) which unfortunately are the only ones present in the current
> draft) but I would need submissions on the other topics.
> 
> I am especially interested in getting detailed input from people that
> proposed the methods (i.e. Yossi and Brian) but other people can also
> submit.
> 
> Thank you very much in advance,
> 
> Octavian Sarca
> Redline Communications Inc.
> 90 Tiverton Crt. #102
> Markham, ON, L3R 9V2
> E-mail: osarca@redlinecommunications.com
>