Vendor: Noesis Technologies Category: Channel Coding

Configurable Turbo Product Codec

In channel coding redundancy is inserted in the transmitted information bit-stream.

TSMC 180nm BCDG2 Silicon Proven View all specifications

Overview

In channel coding redundancy is inserted in the transmitted information bit-stream. This redundant information is used in the decoder to eliminate the channel noise. The error correction capability of a FEC system strongly depends on the amount of redundancy as well as on the coding algorithm itself. The ntTPC Turbo Product Codec IP core is consisted of the Turbo Product Encoder (ntTPE) and the Turbo Product Decoder (ntTPD) blocks. The product code C is derived from two constituent codes, namely C1 and C2. The information data is encoded in two dimensions. Every row of C is a code of C2 and every column of C is a code of C1. The ntTPC core supports both e-Hamming and Single Parity Codes as the constituent codes. The core also supports shortening. Shortening is a way of providing more powerful codes by removing information bits from the code.
The ntTPE core receives the information bits row by row from left to right and trans-mits the encoded bits in the same order. It consists of a row and column encoder. The row encoder encodes the data row-wise. The encoded data from the row encoder are stored in the encoded data memory. Concurrently, the information data are encoded column-wise by the column encoder and the column parity bits are stored in a separate memory.
The ntTPD decoder receives soft information from the channel in the 2’s complement number system and the input samples are received row by row from left to right. The ntTPD core transmits the decoded bits in the same order. The implemented decoding algorithm computes the extrinsic information for every dimension by decoding words that are near the soft-input word. These words are called test patterns and their number can be programmed.

Key features

  • Programmable data block size by adjusting codeword dimensions, i.e. number of rows and number of columns.
  • Supports shortening by adjusting number of rows and columns to be eliminated in order to create a shortened code.
  • Programmable number of soft bits in the input data.
  • 2’s complement arithmetic data format.
  • Supports extended Hamming or single parity constituent codes.
  • Supports (64,57), (32,26), (16,11) or (8,4) extended Hamming constituent codes.
  • Supports (64,63), (32,31), (16,15) or (8,7) single parity constituent codes.
  • Programmable number of algorithmic iterations.
  • Supports user selectable synchronous reset.
  • Fixed encoder and decoder latency.
  • Supports ASIC and FPGA implementation technologies.
  • Single edge, fully synchronous design.
  • Area efficient design.
  • Silicon proven in Xilinx FPGA technologies for a variety of applications.

What’s Included?

  • Fully commented synthesizable VHDL or Verilog source code or FPGA netlist.
  • VHDL or Verilog test benches and example configura-tion files.
  • C++ model.
  • Comprehensive technical documentation.
  • Technical support.

Silicon Options

Foundry Node Process Maturity
TSMC 180nm BCDG2 Silicon Proven

Specifications

Identity

Part Number
ntTPC
Vendor
Noesis Technologies
Type
Silicon IP

Files

Note: some files may require an NDA depending on provider policy.

Provider

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Frequently asked questions about Channel Coding IP cores

What is Configurable Turbo Product Codec?

Configurable Turbo Product Codec is a Channel Coding IP core from Noesis Technologies listed on Semi IP Hub. It is listed with support for tsmc Silicon Proven.

How should engineers evaluate this Channel Coding?

Engineers should review the overview, key features, supported foundries and nodes, maturity, deliverables, and provider information before shortlisting this Channel Coding IP.

Can this semiconductor IP be compared with similar products?

Yes. Buyers can compare this product with similar semiconductor IP cores or IP families based on category, provider, process options, and structured technical specifications.

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