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Channel Coding

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Overview of Channel coding. Digital Communication System. Types ... RACH. PCH. CPCH, DCH, DSCH, FACH. 1/2. Convolutional coding. BCH. Coding rate. Coding scheme ... – PowerPoint PPT presentation

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Title: Channel Coding


1
Channel Coding
  • NCU-EE VLSI/DSP Lab.
  • Freshman Training Course
  • Speaker ???
  • Advisor ??? ??

2
Outline
  • Overview of Channel coding
  • Digital Communication System
  • Types of Error Control
  • Types of Channel Coding
  • Turbo Codes
  • Introduction
  • System model
  • Log-MAP vs SOVA
  • Simulation
  • SW Memory Architectures
  • Conclusions

3
Digital Communication System
JPEG, MPEG, etc.
RS code, Turbo code,
QPSK, QAM, BPSK, etc.
rb
rc
Information
Source
Channel
Modulator
Source
Encoder
Encoder
rs
Channel
Demodu-
Channel
Source
Data Sink
lator
Decoder
Decoder
4
Channel Coding
  • Channel coding refers to the class of signal
    transformation designed to improve communication
    performance by enabling the transmitted signals
    to better withstand the effects of various
    channel impairments.
  • Channel coding can be partitioned into two areas,
    waveform (or signal design) coding and structured
    sequences (or structured redundancy.)
  • Waveform coding deals with transforming waveforms
    into better waveforms, to make the detection
    process less subject to errors.
  • Structured sequence deals with transforming data
    sequences into better sequences, having
    structured redundancy.

5
Types of Error Control
  • Before we discuss the detail of structured
    redundancy, let us describe the two basic ways
    such redundancy is used for controlling errors.
  • Error detection and retransmission, utilizes
    parity bits (redundant bits added to data) to
    detect that an error has been made and requires
    two-way link for dialogue between the transmitter
    and receiver.
  • Forward error correction (FEC), requires a one
    way link only, since in this case the parity bit
    are designed for both the detection and
    correction of errors.

6
Why Use Error-Correction Coding
  • Trade-off
  • Error Performance verse Bandwidth
  • Power verse Bandwidth
  • Data Rate verse Bandwidth
  • Capacity verse Bandwidth
  • Coded verse Uncoded Performance
  • Coding Gains
  • For a given bit-error probabilities, coding gain
    is defined as the reduction in Eb/N0 that can be
    realized through the use of code.

7
Types of Channel Coding
  • Block codes
  • Extended Golay code
  • Hamming code
  • BCH code
  • Convolutional codes
  • Recursive or Nonrecursive
  • Systematic or Nonsystematic
  • Reed-Solomon Codes
  • Interleaving and Concatenated Codes
  • Turbo Codes

8
Block Codes
  • (n,k) Block Codes
  • message k-tuple u(u1,u2,,uk)
  • code word n-tuple v(v1,v2,,vn)
  • code rate Rk/n

9
Convolustional Codes
  • (n,k,m) Convolutional Codes
  • message k-tuple u(u1,u2,,uk)
  • code word n-tuple v(v1,v2,,vn)
  • code rate Rk/n
  • memory order m
  • Constraint length Km1
  • Generator polynomials g1(x) 1xx2
    g2(x)1x2

10
Outline
  • Overview of Channel coding
  • Digital Communication System
  • Types of Error Control
  • Types of Channel Coding
  • Turbo Codes
  • Introduction
  • System model
  • Log-MAP vs SOVA
  • Simulation
  • SW Memory Architectures
  • Conclusions

11
Turbo Codes
  • Shannons channel coding theorem guarantees the
    existence of codes that can achieve arbitrary
    small probability of error if the data
    transmission rate is smaller than the channel
    capacity.

12
Applications
  • Turbo code is currently adopted as the channel
    coding schemes in many next-generation
    communication systems
  • WCDMA, CDMA2000
  • CCSDS in space communications
  • Baseband Signal compensation in Fiber
    transmission systems

13
Specifications in WCDMA
14
Specification in CDMA2000
15
Turbo Code v.s. Convolutional Code
  • Convolutional Code
  • Non-recursive
  • Non-systematic
  • Without Interleaver
  • Turbo Code
  • Recursive
  • Systematic
  • Parallel structure
  • Use Interleaver

NSC
RSC
16
Design Flow
17
System Model
18
Log-MAP vs SOVA
G7 5, Unpunctured(1/3), frame
size1024, Iteration8.
Iteration increment..
SOVA
Iteration increment..
Log_MAP
19
The SOVA algorithm
20
Log-MAP Algorithms
21
Log-MAP Algorithms
22
Sliding Window Memory Issue
  • The extrinsic and APP value are made with a
    delay, which is equal to received sequence
    length.
  • But the decoder decisions length can be reduced
    to about six times the encoder memory because of
    reliable decoding decision.

23
Simulation Results (1/3)
24
Simulation Results (2/3)
25
Simulation Results (3/3)
26
SW - Memory Architectures
  • Advantage
  • 1 Less memory size. 2. Might be Lower
    latency.
  • Disadvantage
  • 1.Read-modify-write access required for the
    memory.
  • 2.Address is hard to be controlled.

27
Timing Diagram
28
Position VS Time
A
DO
B0
B1
G
Decode output without LIFO
Decode output with LIFO
29
ACS Unit
Add-compare-select (ACS) Unit
30
Forward / Backward Processor
Trellis States
Forward Processor (A) / Backward Processor (B)
Block Diagram
Block Diagram based on Trellis States
31
Novel Turbo Code Iteration Issues
  • In high-quality channel environments, a large of
    decoding iterations are not required to obtain
    the target BER, and it is possible to terminate
    the process after a few numbers of decoding
    iterations.

Denterlever
SISO (MAP1) Decoder
SISO (MAP2) Decoder
Interlever
Threshold Detection
Hard Decision
Denterlever
32
Outline
  • Overview of Channel coding
  • Digital Communication System
  • Types of Error Control
  • Types of Channel Coding
  • Turbo Codes
  • Introduction
  • System model
  • Log-MAP vs SOVA
  • Simulation
  • SW Memory Architectures
  • Conclusions

33
Conclusions
  • We discuss some fundamentals of channel coding.
  • We discuss some basic implementation issues for
    turbo codes.
  • This study can be exploited in development of
    high performance receiver with different
    constraints of cost and throughput.
  • The novel turbo decoder can practically have
    lower iteration with the adaptive SNR channel
    estimation.
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