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
>