RE: stds-802-16-tg4: Call for input - Data Encoding
Minfei,
Here is my 5 cents... (by the way, Sean, the originator of this thread, is from
AHA).
Very little of what you have written about convolutional and concatenated codes
is true. To whit:
1. convolutional codes with puncturing ususally have rates of n/(n+1). This
means that the code could be configured to have a code rate of 0.9 or higher
(compare to your statement limiting the maximum rate to 0.5)
2. the interleaving, and not the coding scheme itself, is the most dominant
factor in addressing performance in a fading environment, but the interleaver
depth must be matched to the fade duration. It isn't correct to make the
blanket statement that TPC codes are better at handling fading channel error
statistics.
3.Research at NASA JPL has shown that TPC codes are no closer to the Shannon
limit than convolutional turbo codes. See their website and publications.
4. Concatenated coding schemes (e.g., Viterbi/RS) have a decoder implementation
complexity that is less than that of TPC codes. Furthermore, any code will be
less stressed in an AWGN environment. As I noted earlier, the interleaver is
the dominant factor in addressing burst error statistics.
5. There has been a great deal of effort expended on comparing different coding
schemes by participants in TG1. See the website and examine the documents for a
wealth of useful infomation.
Mis-information is worse than no information.
John Liebetreu
Intersil Corporation
Scottsdale, Arizona
-----Original Message-----
From: Minfei Leng [mailto:Mleng@Clearwire.com]
Sent: Thursday, April 12, 2001 12:31 PM
To: Octavian Sarca; Stds-802-16-Tg4 (E-mail)
Subject: 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
>