fix point 16 qam demapper-presentation_linked_in
TRANSCRIPT
Fixed point Software Implementation of a
Low-Complexity Soft Demapper
Presented By : Adeel Akhtar Supervised By : Imran AliPresented To : Prof. Norbert Wehn
Microelectronics Seminar
Outline Introduction
Goals
Work Description
Simulation Results
Conclusion
2
Channel Encoder
Channel
Mapper
Demapper
Channel Decoder
The received symbols are mapped to soft values:0.7,-1.3,-0.1,1.4; 3.1, -0.7, -1.1, 2.3
Error correction data is added to the message:01100110
The soft values are used to recover the original message: 1011
Message to be sent: 1011
The message is mapped to symbolsdescribing the signal.
(-1+2i, -1+2i)
Sending the signal through the channel distorts it.
(-0.76+1.3i; -1.1+2.15i)
Wireless Communication
3
Channel Encoder
Channel
Mapper
Demapper
Channel Decoder
Im
Re
0111 0110
01000101
0010 0011
00010000
1000 1001
10111010
1101 1100
11101111
Due to interference the sent signal isdeformed.
Wireless Channel
4
1.Optimal Soft DemapperChannel Encoder
Channel
Mapper
Demapper
Channel Decoder
0
2
1
00
2
||exp
||exp
log
Nxy
Nxy
LLR
i
i
Sx
Sx
i
Im
Re
0111 0110
01000101
0010 0011
00010000
1000 1001
10111010
1101 1100
11101111
Demapper Algorithms
5
Channel Encoder
Channel
Mapper
Demapper
Channel Decoder
Im
Re
0111 0110
01000101
0010 0011
00010000
1000 1001
10111010
1101 1100
11101111
2.Sub-optimal Demapper
0
2
0
2
1||min||min
N
xyxyLLR ii SxSx
i
6
Channel Encoder
Channel
Mapper
Demapper
Channel Decoder
0
20min
21min ||||
N
xyxyLLR ii
i
3.Less Complex Sub-Optimal Soft Demapper [1]
Im
Re
0111 0110
01000101
0010 0011
00010000
1000 1001
10111010
1101 1100
11101111
7
Fixed point software implementation of the algorithm in C++.
Simulation of the demapper with Duo binary Turbo Decoder.
Communication performance analysis with different bit widths and comparison with Optimal technique.
8
Goals of Seminar
Block Diagram of Algorithm
9
Received Symbol Real Img
Rounding
Distance Calculation
Magnitude to Gray Code
Closest flipped bit constellation point
Gray Code to Magnitude
Calculation of Log Likelihood Ratio (LLRs)
(-2.7,1.4)
(-3,1)
(1001)
10010011100111011001101110011000
0011( 1, 1)1101(-3,-1)1011(-1, 1)1000(-3, 3)
llro = -72.3llr1 = 29.9llr2 = 15.9llr3 = -10.4
Closest flipped bit constellation points
Flipping the bit at needed position.
…xxxxxxxxx… ...x’x1x0x0x0… The next less significant bit is set. All lesser significant bits are reset. Real and imaginary numbers are interleaved.
10
Example: symbol with four bits (1001)
Flip bit 0: xxxx → x’x1x (10010011)
Flip bit 1: xxxx → xx’x1 (10011101)
Flip bit 2: xxxx → xxx’x (10011011)
Flip bit 3: xxxx → xxxx’ (10011000)
Fixed-Point Low-Complexity Soft Demapper
11
Received Symbol Real Img
Rounding
Distance Calculation
Magnitude to Gray Code
Closest flipped bit constellation point
Gray Code to Magnitude
Calculation of Log Likelihood Ratio (LLRs)
(-906,485)
(-971,323)
(1001)
10010011100111011001101110011000
0011( 323, 323)1101(-971,-323)1011(-971, 323)1000(-971, 971)
llro = -13llr1 = 30llr2 = 16llr3 = -10
Fixed point number Q.10,8
Simulation Setup
12
Source
Statistics
Turbo encoder 16 QAM Mapper
16 QAMDe-Mapper
Turbo Decoder
Transmitter (Tx)
Receiver(Rx)
Channel
Simulation Results
13
6 6.2 6.4 6.6 6.8 7 7.210
-5
10-4
10-3
10-2
10-1
100
SNR Eb/N0 dB
FE
R
Info bits1552 total bits1864-16QAM R0.833 Turbo Decoder
Optimal Demapper
Simulation Results
14
6 6.2 6.4 6.6 6.8 7 7.210
-5
10-4
10-3
10-2
10-1
100
SNR Eb/N0 dB
FE
R
Info bits1552 total bits1864-16QAM R0.833 Turbo Decoder
Optimal Demapper
Proposed. Q10,8
Simulation Results
15
6 6.2 6.4 6.6 6.8 7 7.210
-5
10-4
10-3
10-2
10-1
100
SNR Eb/N0 dB
FE
R
Info bits1552 total bits1864-16QAM R0.833 Turbo Decoder
Optimal Demapper
Proposed. Q10,8
Proposed. Q8,6
Conclusions
1. Understanding of a less complexity sub-optimal demapper.
2. Fixed point software implementation of the proposed algorithm.
3. The performance of the algorithm is exactly similar to the optimal algorithm for 16 QAM.
4. Less number of distances computation, consequently less computation complexity in hardware.
16
17
Thank You