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Turbo-NFSK: Iterative Estimation, Noncoherent Demodulation, and Decoding for Fast Fading Channels

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BER of 16-ary NFSK in Rayleigh Fading Channel with Different Block Size BER of NFSK in Rayleigh Fading Channel with Different Alphabet Size BER of 16-ary NFSK in ... – PowerPoint PPT presentation

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Title: Turbo-NFSK: Iterative Estimation, Noncoherent Demodulation, and Decoding for Fast Fading Channels


1
Turbo-NFSK Iterative Estimation, Noncoherent
Demodulation, and Decoding for Fast Fading
Channels
  • Shi Cheng and Matthew C. Valenti
  • West Virginia University
  • Don Torrieri
  • U.S. Army Research Laboratory
  • This work sponsored by the Xenotran Corporation,
    Glen Burnie, MD

2
Outline
  • Iterative M-ary NFSK demodulation and decoding
  • ML estimator using EM algorithm
  • Performance of iterative estimation, NFSK
    demodulation and decoding
  • Methods to reduce the complexity of the estimator
  • Conclusions

3
BICM-ID Bit Interleaved Coded Modulation with
Iterative Decoding
Binary to M-ary mapping
Binary Encoder
Bitwise Interleaver
M-ary- modulator
Complex flat-fading
AWGN
Soft-In Binary Decoder
LLR Bit Metric Calculation
Receiver front end
Bitwise Deinterleaver
Bitwise Interleaver
Soft-Output Estimates of Coded Bits
4
Noncoherent M-FSK Using A Priori Probabilities
  • Bit LLRs are calculated based on the channel
    observation and the extrinsic information
    feedback from the decoder
  • Where

5
BICM ID and CM Capacity
BICM ID Performance using CDMA2000 length 6138
codeword 20 iterations, BER 10-4
Reference M.C.Valenti and S. Cheng, Iterative
demodulation and decoding of turbo coded M-ary
noncoherent orthogonal modulation IEEE Journal
on Selected Areas in Communications, Sept. 2005.
Minimum Eb/No (in dB)
Code Rate R
6
Block Fading Channel
  • Fading coefficient is fixed within one block.
  • Independent fading from block to block

2
192
3
1
...
0
767
4
8
N
4
1
2
96
...
0
767
8
N
8
CDMA 2000 turbo codeword rate ½ length 1530 with
16-NFSK
7
Estimation of One Block
  • Channel state information is needed to calculate
    bit LLRs
  • Perform estimation of A and B independently block
    by block, where

Soft-In Binary Decoder
LLR Bit Metric Calculation
Bitwise Deinterleaver
Channel Estimator
Bitwise Interleaver
8
Channel Estimator with Known Transmitted Sequence
  • Form the log-likelihood function based on the
    known sequence d d0,d1,,dN-1 of
  • Solving A and B to maximize L
  • Where

9
ML Estimator with A Priori Information of the
Sequence
  • The sequence d is never known.
  • Form log-likelihood function based on the a
    priori information of d
  • Too complex to find the solution to maximize this
    function. We resort to EM algorithm.

10
ML Estimator using EM Algorithm
  • 0. Select
  • 1.
  • 2.
  • 3.

Normalization factor
Outer Iteration
Inner Iteration
11
BER of 16-ary NFSK in Rayleigh Fading Channel
with Different Block Size
0
10
N32
CDMA2000 Turbo Code, Rate ½, Length
1530 Independent Block Fading Iteration 20
N16
N8
-1
N4
10
N1
-2
10
BER
-3
10
Estimator
-4
Perfect CSI
10
5
5.5
6
6.5
7
7.5
8
8.5
9
9.5
10
Eb/No (dB)
12
BER of NFSK in Rayleigh Fading Channel with
Different Alphabet Size
0
10
CDMA2000 Turbo Code, Rate ½, Length 1530 Data
Rate 24bits/ block
M2
M4
M16
Iteration 20
-1
M64
10
Estimator
-2
10
BER
Perfect CSI
-3
10
-4
10
4
5
6
7
8
9
10
11
12
Eb/No (dB)
13
BER of 16-ary NFSK in Rician Fading Channel
(K10dB)
Estimator
BER
Perfect CSI
CDMA2000 Turbo Code, Rate ½, Length
1530 Independent Block Fading
Iteration 20
Eb/No (dB)
14
Methods to Reduce the Complexity of the Estimator
  • 0. Select
  • 1.
  • 2.
  • 3.

Making hard decision
Outer Iteration
Normalization factor
Inner Iteration
Linear approximation of F
15
Methods to Reduce the Complexity of the Estimator
  • 0. Select
  • 1.
  • 2.
  • 3.

Making hard decision
Outer Iteration
Linear approximation of F
16
Linear Approximation of F
17
Complexity of Different Estimators
7
x 10
3
EM estimator
2.5
CPU Cycles/BICMID iteration
16-ary NFSK, CDMA2000 turbo codeword with rate ½
and length 1530. N4 symbols per block
independent Rayleigh fading

2
Decoder
1.5
Hard Linear EM
Demodulator
1
Linear EM
0.5
0
5.6
5.8
6
6.2
6.4
6.6
6.8
7
Eb/No (dB)
18
BER Performance of Low Complexity Estimators
16-ary NFSK, CDMA2000 turbo codeword with rate ½
and length 1530. N4 symbols per block,
independent Rayleigh fading, iteration 20
BER
Eb/No (dB)
19
Conclusions
  • Robust noncoherent channel estimator, dealing
    with severe channel conditions.
  • The estimator works without needing to know the
    fading statistics model. The only requirement is
    the coherence time of the fading amplitude is
    larger than 4 symbols.
  • Although the estimator using the exact EM
    algorithm is complex, linear approximation of
    F(x) I1(x)/I0(x) and hard decision of can
    be used to reduce the comlexity.
  • For 16-NFSK, when fading block size is larger
    than 4 symbols per block, the system has
    acceptable BER performance.
  • When there are 4 symbols per block, the BER of
    the iterative estimation, demodulation and
    decoding is about 0.60.8dB away from the one
    with perfect CSI.
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