A low-memory intensive decoding architecture for double-binary convolutional turbo code

Ming ZHAN; Liang ZHOU; Jun WU

Makale detayları

A low-memory intensive decoding architecture for double-binary convolutional turbo code

Yazarlar:

Ming ZHAN | Liang ZHOU | Jun WU

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 1, pp.202-213

Belge Tipi:

Makale

Yayın Tarihi:

5/2014

Belge Dili:

Türkçe

Document ID (Org No.):

2000743132

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

Memory accesses take a large part of the power consumption in the iterative  decoding of double-binary convolutional turbo code (DB-CTC). To deal with  this, a low-memory intensive decoding architecture is proposed for DB-CTC in  this paper. The new scheme is based on an improved maximum a posteriori  probability algorithm, where instead of storing all of the state metrics,  only a part of these state metrics is stored in the state metrics cache  (SMC), and the memory size of the SMC is thus reduced by 25%. Owing to a  compare-select--recalculate processing (CSRP) module in the proposed  decoding architecture, the unstored state metrics are recalculated by simple  operations, while maintaining near optimal decoding performance.

 

Memory accesses take a large part of the power consumption in the iterative  decoding of double-binary convolutional turbo code (DB-CTC). To deal with  this, a low-memory intensive decoding architecture is proposed for DB-CTC in  this paper. The new scheme is based on an improved maximum a posteriori  probability algorithm, where instead of storing all of the state metrics,  only a part of these state metrics is stored in the state metrics cache  (SMC), and the memory size of the SMC is thus reduced by 25%. Owing to a  compare-select--recalculate processing (CSRP) module in the proposed  decoding architecture, the unstored state metrics are recalculated by simple  operations, while maintaining near optimal decoding performance.

Makale detayları

A low-memory intensive decoding architecture for double-binary convolutional turbo code

Yazarlar: Ming ZHAN | Liang ZHOU | Jun WU

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 1, pp.202-213

Belge Tipi: Makale

Yayın Tarihi: 5/2014

Belge Dili: Türkçe

Document ID (Org No.): 2000743132

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Ming ZHAN | Liang ZHOU | Jun WU

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2014 Vol.22 Issue 1, pp.202-213

Belge Tipi:

Makale

Yayın Tarihi:

5/2014

Belge Dili:

Türkçe

Document ID (Org No.):

2000743132

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632