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American Institute of Aeronautics and Astronautics

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Adaptive Channel Coding Scheme for Rain-Fade Countermeasure inKa-Band Satellite Communications and Its Implementation

*Ji Won JungKorea Maritime University, Radio and Science Eingineering,Pusan 606-791, S. Korea([email protected],ac,kr)

Xinping HuangCommunication Research Centre Canada, Satellite System

3701 CARLING AVE., OTTAWA, ON. K2H 8S2([email protected])

Abstract An adaptive code-rate scheme for ka-band satellite syatem which adapts the level of coding to overcome rain-induced signal fade is presented. It is based on a pragmatic code, and can decode the QPSK and TC-8PSK signals using a single Viterbi decoder. The optimal parameters for implementation through computer simulations are determined. The adaptive channel coding algorithms described in this paper may be used for high-speed satellite communications to compensate the rain-attenuation.

I. INTRODUCTION

Digital transmission via Ka-band satellite can be severely affected by rain-induced signal fade. Rain-fadecountermeasure has been one important design objective of any Ka-band satellite communicationsystems, especially those offering broadband multimedia services. One possible method to achieve robust and spectrally efficient communication over a rain-faded satellite channel is to adapt the transmission scheme to the current channel characteristics using channel estimates available at the transmitter. Unlike nonadaptive systems, which are design for worst-case channel condition to achieve acceptable performance, adaptive signaling methods take advantage of favorable channel conditions by allocating power and rate efficiently. Among the adaptive systems, the adaptive channel coding receives much attention recently, and it is one of the most powerful schemes to warrant the high reliability and high spectral efficiency over the rain-fade channel.[1~4]

The adaptive channel coding scheme uses different channel coding techniques, depending on

* Ji Won Jung is currently a visiting scientist at CRC under the NSERC fellowshipCopyright 2002 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

weather conditions. For example, under clear sky, a more spectrum-efficient modulation and coding such as an 8-PSK or 16-QAM trellis-coded modulation can be used to provide a higher data rate; while under be employed to maintain an acceptable performance.

Instead of switching between several separate encoders and decoders in such an adaptive system, we can use an adaptive trellis decoding to providing a single encoder and decoder. In this paper, we present the pragmatic trellis decoder, which is based on a realization of rate n/(n+1) trellis coded scheme using a single rate 1/2 convolutional encoder/decoder in conjunction with an M-PSK mapper where M=2n+1. Compared to others, this scheme only requires a single decoder, therefore, it needs less hardware, consumes less power and reduces the receiver cost. To cope with the rain-fade, the following operation modes are offered: a QPSK modulation with coding rate of 1/2 , 2/3, 3/4, 5/6, 7/8 or a TC-8PSK modulation with coding rate of 2/3, 5/6, 8/9. These variable rate coding schemesare defined in the DVB(Digital Video Broadcasting) standard document[1]. The system shall use QPSK modulation, optionally 8PSK modulation, and concatenation of convolutional and RS codes. For 8PSK, “pragmatic” trellis coding shall be applied, optimizing the error protection of convolutional code. The convolutional code is flexiable, allowing the optimazation of the system performance for a given satellite trandponder bandwidth. So, this paper introduces a pragmatic code and established the optimal parameters for implementation through the computer simulations. We implement the pragmatic code with rate 2/3,5/6,and 8/9 by VHDL

The paper consists of the following Sections. In Section 2, we analyze the performance of adaptive channel coding scheme, and compare it with that of the conventional (non-adaptive) scheme. In Section 3, we study effects and optimal selections of various parameters in the adaptive channel coding scheme such as a number of phase sector, constellation of mapper,

20th AIAA International Communication Satellite Systems Conference and Exhibit12-15 May 2002, Montreal, Quebec, Canada

AIAA 2002-1860

Copyright © 2002 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.


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decoding depth of Viterbi decoder, and quantization. In Section 4, we present an VHDL implementation of theadaptive coding scheme. Section 5 concludes the paper.

II. ENCODER AND DECODER STRUCTURE

In this Section, we study the encoder and decoder structures of the pragmatic coding scheme. The structure is based on the rate of n/(n+1) trellis code using a single rate 1/2 encoder/decoder in conjunction with an MPSK signal. The term "pragmatic" refers to code implementation employing the widely used, best known rate 1/2 convolutional encoder and the corresponding the Viterbi decoder

2.1 Encoder Structure

The encoder structure of the pragmatic code with variable coding rates is shown in Figure 1. The signal NE of non-encoded branch shall generate, through the Symbol Sequencer, each bit to be transmitted in a modulated symbol. These bits generate parallel transition in the trellis code, and are only protected by a large Euclidean distance in the signal space. The signal E in the encoded branch shall be processed by the

convolutional encoder with a rate of nkr = . These

bits shall pass through the Symbol Sequencer, each to be transmitted in a modulated symbol.

Figure 1. Block diagram of the pragmatic encoder. Pragmatic coding rate R , which is changed according to r and the number of NE and E, is specified in Table 1.

Table 1. Pragmatic coding rate R

d (bits)

NE(bits)

E(bits) r R

2 1 1 1/2 2/3

5 3 2 1/2 5/6

8 6 2 2/3 8/9

The mapping rule of 8-PSK is depends on R . In the case of 32 /R = , bit mapping rule shall follow the Ungerboeck’s set partition rule[5] while the bit mapping for 65/R= and 98/R= shall comply with gray coded LSB(Least Significient Bit). [1][6]

2.2 Decoder Structure

As shown in Figure 2, the pragmatic decoder is mainly consists of a Viterbi decoder, a sector phase a quantizer, a soft decision logic and a convolutional reencoder. The Viterbi decoder used in this system accepts soft decision inputs on a scale of 0 thru 7, with a soft decision 7 indicating the strongest binary 1, and a soft decision 0 indicating the strongest binary 0. With this in mind, the signal vector space is quantized, and a pair of soft decisions (one for each code bit) are assigned to each quantization point. The sector phase quantizer is used for decoding the uncoded bits NE, and soft decision logic makes 3 quantizated bits so that Viterbi decoder can supports the soft decision decoding.

8-PSKDemodulator

SectorPhase

Quantizer

SoftDecisionLogic

Buffer

(n,k)Viterbi

Decoder

(n,k)Convolutional

Reencoder

E

UncodedBit

Decision

NE

Buffer

S/P

S/P

8-PSKDemodulator

SectorPhase

Quantizer

SoftDecisionLogic

Buffer

(n,k)Viterbi

Decoder

(n,k)Convolutional

Reencoder

E

UncodedBit

Decision

NE

Buffer

S/P

S/P

Figure 2. The structure of the pragmatic decoder

The sector phase quantizer is designed with the assumption that the in-phase and quadrature components of the received signals will be converted to q bit number. The circuit is shown in Figure 3.

Three comparators and two absolutors generate the three bits of phase information indicating one of sectors. Each of the three phase information bits gives aninformation about the location of the received vector: Ø2 and Ø3 indicate the quadrant, the remaining one bit indicates the location within the quadrant. When |I| < |Q|, Ø1 is one. This is simple logic to generate the soft decisions. Once the encoded bits have been determinedby the Viterbi decoder, it remains to determine the uncoded bit. This is accomplished by making a

P/P

P/S (n,k)Convolutional Encoder

SymbolSequencer

MPSKMapperM

d

NE

EP/P

P/S (n,k)Convolutional Encoder

SymbolSequencer

MPSKMapperM

d

NE

E


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threshold decision. Code bits E are generated by reencoding the output of the Viterbi decoder. Due to the structure of the Viterbi algorithm, every Viterbi decoder delays the data by a fixed number of symbol periods. The phase information bits must be delayed by the memory size of 3-pointer trace back unit[7] to match with the reconstructed code sequence

COMPAREI<0

COMPAREQ<0

ABSOLUTEVALUE

ABSOLUTEVALUE

COMPARE|I|<|Q|

I

Q

COMPAREI<0

COMPAREQ<0

ABSOLUTEVALUE

ABSOLUTEVALUE

COMPARE|I|<|Q|

I

Q

φ2

φ0

φ1

I & Q channelSoft Decision

COMPAREI<0

COMPAREQ<0

ABSOLUTEVALUE

ABSOLUTEVALUE

COMPARE|I|<|Q|

I

Q

COMPAREI<0

COMPAREQ<0

ABSOLUTEVALUE

ABSOLUTEVALUE

COMPARE|I|<|Q|

I

Q

φ2

φ0

φ1

I & Q channelSoft Decision

Figure 3. Sector phase quantizer and Soft decision mapping block

In the case of 65/R= and 98/R= , its decoder structure is a little different from that of 32/R= . The rest bits, except the LSB, use a buffer to adjust the formation mapped in the modulator. The decoder for rate 5/6 and 8/9 is shown in Figure 4.[5]

D2

D1

D0

Decision making for D2D1/B0


Viterbidecoder

Received 8PSK I

Q

ConvolutionRe-encoder

Buf

fer

B0|B

1 se

lect

or

Sect

orqu

antiz

er

D2

D1

D0



Viterbidecoder

Received 8PSK I

Q

ConvolutionRe-encoder

Buf

fer

B0|B

1 se

lect

or

Sect

orqu

antiz

er

Figure 4. The block diagram of decoder for 5/6 and 8/9

First of all, the Viterbi decoder estimates the LSB of each symbol received. Then, LSB is used in the decoding process for second and third bit except the LSB by reencoding. The reencoding process is uses the decoded bit again. The reencoded bits divide the first set partitioning of the 8-PSK constellation and provide the standard subset for deciding the rest bit. The decoding for the rest bits except the LSB bit can be achieved by the same process as the QPSK demodulation process. In order to achieve the Viterbi decoding for the LSB bits, Decoding delay is generated. Therefore, the buffer is necessary. For a transmitted signal point “001” in Figure 5, The decoding procedure can be divided into two stages. In the first stage, the decision zones shown in Figure 6 are used to decide the

LSBs, which could be either the information bit or the parity bit. Simultaneously, by using the decision zones shown in Figure 6(a) and 6(b), the first two bits of the subsets B0 and B1, are decided. This information is stored in a buffer untill the block of symbols has been received. The Viterbi decoder then estimates the LSBof each symbol. Since the LSB of the symbol indicates the subset (B0 or B1) in which the signal point locates, the first two bits can be decided in the second stage based on the estimated LSB. As shown in Figure 6, Let’s assume that the transmitted signal is A = 001. Suppose that the received signal locates at A’ . At the first stage, the decision maker outputs the first two bits D2D1 = 01/B0 and D2D1 = 00/B1, and the LSB is made as D0=0 (type I error occurs here). At the second stage, if the number of errors is less than or equal to 3 within the block, the Viterbi decoder can determine the LSB as D0=1, which indicates that the signal point locates in subset B1 to make the final decision D2D1D0 = 001. However, if there are more than three errors in the block, the Viterbi decoder may not estimate the LSB as D0=1, and the final decision may be D2D1D0 = 010 and the decision error occurs.

Region of type 1 error


Transmitted signal point

101

000

100

111 110

011

010

001



Transmitted signal point

101

000

100

111 110

011

010

001

Figure 5. Decision zones and regions of type 1 error

100

110

010

000

A’+

A

100

110

010

000

A’+

A

011

101

111

001

A’+

Transmitted signalA

011

101

111

001

A’+

Transmitted signalA

(a) Subset B0 (b) Subset B1

Figure 6. Decision zone

III. SIMULATION RESULTS AND OPTIMUM PARAMETERS

In this Section, we analyzed the BER performance of the pragmatic code in the Gaussian channel. To


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determine the optimal parameters, we investigate the effects and optimal selections of various parameters inthe adaptive channel coding scheme such as a number of phase sectors, constellation of mapper, decoding depth of Viterbi decoder, and quantization. The following subsections show the results of above considerations.

3.1 Coding Rates and Phase Sectors

Figure 7 shows the BER performance of the pragmatic code with rate 32/R= for various number of sectors. At a bit error rate of 10-5 , the pragmatic code achieves 2.5 dB coding gain over uncoded QPSK, and only 0.5 dB is sacrificed than ungerboeck TCM. It is noticed that the optimum number of phase sector is 24. Fixed on the number of sector and the Viterbi decoding parameter(for example decoding depth, 3-pointer trace back,etc.), Figure 8 shows the BER performance comparison of the three coding rates. At a bit error rate of 10-5, A pragmatic code with 32/R= can achieves 1 dB coding gain over compared to 65/R= , and 2 dB over compared to 98/R = .

16 sector24 sector32 sector64 sectorungerboeck TCMuncoded QPSK

Figure 7. BER performance for various numbers of sectors

Figure 8. BER performance comparison of 32/R= , 65/R= and 98/R =

(for 24 sectors and 64 states)

3.2 Constellation of Mapper

The system performance is affected by Euclidean distance. Figure 9 shows the Eulidean distance between symbol mapping points for two cases. In the first case, the phase of constellation starts from 0°(Figure 9(a)), the the Euclidean distanse between mapping points is the same at all the quadratures, while in the second case, starts at 22.5°(Fig. 9(b)), Euclidean distance of Q -channel is 0.765 and of I-channel is 0.542.

(0,0)

(0,7)

(7,7)

(7,0)

(0,0)

(0,7)

(7,7)

(7,0)

(1)

(2)(3)

(4)

(5)

(6) (7)

(8)

(0,0)(0,1)(0,2)(0,3)(0,4)(0,5)(0,6)(0,7)

0.0883750.176750.2651250.35350.4418750.530250.618625

(0.707,0.707)

(0,0)

(0,7)

(7,7)

(7,0)

(0,0)

(0,7)

(7,7)

(7,0)

(1)

(2)(3)

(4)

(5)

(6) (7)

(8)

(0,0)(0,1)(0,2)(0,3)(0,4)(0,5)(0,6)(0,7)

0.0883750.176750.2651250.35350.4418750.530250.618625

(0.707,0.707)

(a) 8PSK constellation initiated at 0°

(0,0)

(0,0)

(0,7)(7,7)

(7,0)

(0,7)(7,7)

(7,0)

o5.22 (3,0)

(0,0)(1,0)(2,0)

(4,0)(5,0)(6,0)(7,0) -0.28725

0.28725

-0.1915

0.1915

-0.09575

0.095750.0

Q

0.765

0.542 0.3825

0.9245

(0,0)

(0,0)

(0,7)(7,7)

(7,0)

(0,7)(7,7)

(7,0)

o5.22 o5.22 (3,0)

(0,0)(1,0)(2,0)

(4,0)(5,0)(6,0)(7,0) -0.28725

0.28725

-0.1915

0.1915

-0.09575

0.095750.0

Q

0.765

0.542 0.3825

0.9245

(b) 8PSK constellation initiated at 22.5°

Figure 9. Softdecision assignment of 8PSK constellation initiated at 0° and 22.5°

To faciliate comparison, coding gain difference Gbetween two different constellations in dB defined as

805420

707010

7650

707010

2

12

2

102

2

10 .).

.(log)

.

.(logG ≅

+= (1)

This is confirmed by simulation result shown in Figure 10.

3.3 Optimum quantization bits of received signal

The BER performance can be affected by the number


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of quantized bits of the received signal. Figure 11shows the BER performance of the pragmatic code with 32/R= for different quantization levels of the received signal. As shown in Figure 11, the

2 4 s e c t o r ( 0 )3 2 s e c t o r ( 0 )6 4 s e c t o r ( 0 )2 4 s e c t o r ( 2 2 . 5 )3 2 s e c t o r ( 2 2 . 5 )6 4 s e c t o r ( 2 2 . 5 )

F i g u r e 10. B ER p e r f o r m a n c e c o m p a r i s o n b e t w e e n t w o d i f f e r e n t c o n s t e l l a t i o ns

p e r f o r m a n c e i m p r o v e s w i t h t h e i n c r e a s e o f t h e n u m b e ro f q u a n t i z a t i o n . A s t h e p e r f o r m a n c e o f 5 b i t q u a n t i z a t i o n i s a l m o s t t h e s a m e a s t h a t o f l e v e l s f l o a t y-p o i n t i m p l e m e n t e d ,w e m a y u s e t h e 5 bi t s f o r r e c e i v e d s i g n a l .

3bit4bit5bit6bitfloat

Figure 11. BER performance for different quantized levels.

3.4 Decoding Depth of the Viterbi Decoder

For 32 /R = and ][7/ 0 dBNEb = , Figure 12 shows

the BER performance of the two cases: the first case is that the Viterbi decoder searches minimum PM(Path Metric) at each states, the second case is that the Viterbi decoder doesn’t search the minimum PM. Whether Viterbi decoder searches the minimum PM or not has a great effects on the decoding speed.[6] Taking into

account the hardware, we conclude that the optimal decoding depth is approximatly 6k (k is constraint length) in the case that minimum PMs are not searched,while the optimal decoding depth is approximatly 4k in the case of searching the minimum PM.

24 sector

32 sector

64 sector

(a) Not searching the minimum PM

24 sector

32 sector

64 sector

(b) Searching the minimum PM

Figure 12. BER performance versus. decoding depth

Based on the above performance analysis, the optimum parameters for implementation are shown in Table 2. Table 2. Optimum parameters of pragmatic code for implementation

Parameters Optimum value

Integer bit assignment of received signals

5 bits

Initiated angle of 8PSK phase constellation 0°

sector number 24 sector

search for minimum PM 4kDecoding depth not search for minimum PM 6k~7k

IV VHDL SIMULATION RESULTS


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Figure 13 shows the implementate of the adaptive code-rate system. It is composed of the number of external ports and funtional blocks. The external ports are mainly composed of five ports: input data ports, clock ports, rate_sel, mod_sel ports and output pin ports. The input data ports are connected to the demodulator block. Three clock ports can be used for supporting the various coding rates, rate_sel and mod_sel port selects the various rate and the various modulation scheme. Functional blocks are mainly composed of six parts: Viterbi decoder, phase sector modul(PSM), soft decision modul(SDM), reencoder(RC), outboard decision modul(ODM) and output contiol modul(OCM). ODM decodes the uncoded bits using the phase information bits and reencoded bits.

Figure 13. Decoder structure of adaptive code-rate system

The OCM block can be used for rescheduling the output datas for different coding rates. Based on the Figure 13 and Table 2, we implemented the adaptive coding scheme using VHDL.

The MAXPLUS II compiler of Altera cooperation is used for VHDL timing simulation. Figure 14 shows VHDL timing simulation results for pragmatic code with ,/R 32= 65 /R = and ./R 98= Various signals in Figure 14 are explained in the following. In the case of ,/R 32= the signals of data_I and the data_Q indicate in-phase and quadrature data respectively. The signal of data_Q is coded by convolutional encoder. The ENCODER and the MODULATION signalsindicate the process of convolutional encoder and 8-PSK modulation based on Ungerboeck's setpartition rule. The PHASE_INF and the QUANTIZATION signals indicate the process of 24-sector phase quantizer and soft decision logic, and the VITERBI signal indicates the output of Viterbi decoder. The TB signal indicates the current states using the 3-point trace back of the Viterbi decoder. And the output signals of REENCODER block and 24-SECTOR PHASE QUANTIZER block are simultaneouslyinputted to the OUTBOARD DECISION LOGIC block. The signal of UNCODED_BIT and CODE_BIT are final outputs of pragmatic code. The clock period is 47.2 [ns] and the decoding delay is about 6.9 [us].Figure 14(b) and (c) are VHDL timing simulation result of 65 /R = and ./R 98= respectively. It is more complex than ,/R 32= in implementing. We can check the error between source symbols and decoded symbols by using the signal “DIFF”. If error is occurred, “DIFF” port indicates high. otherwize it indicates low. Since the signal “diff”are always low, therefore, we confirmed that the decoder implemeted by VHDL is very accurate

,/R 32=


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V. CONCLUSION

As a one of the adaptive channel coding schemes, we described the pragmatic coding for Ka-band satellite communication and present some simulation results. Based on the results, the pragmatic code with ,/R 32=

65 /R = and 98 /R = was implemented by FPGA. In the case of ,/R 32= , its decoding speed reachs up to 42.36 [Mbps]. If we will implement the decoder by an ASIC, the decoding speed would be 5 times faster than FPGA. Therefore, pragmatic coding scheme presented in this paper can be used a satellite with 200 [MHz] transponder bandwidth in order to compensate for rain-attenuation.

In the furture, we will integrate the prgmatic code with various coding rates into a single FPGA chip or ASIC.

REFERENCES

[1] “Digital Video Broadcasting(DVB): Framing Structure, Channel Coding and Modulation for Digital Satellite News Gathering(DSNG) and Other Contribution Applications by Satellite”, ETSI EN 301 210 :European Standard.

[2] Carden Frank, "A Quantized Euclideans soft Decision Maximum Likelihood Sequence Decoder: A Concept for Spectrally Efficient TM Systems", Proceedings of the International Telemetering

65 /R =

(c) 98 /R =

Figure 14 VHDL timing simulation results


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Conference, Vol. XXIV, pp. 375-384, OCT., 1988.

[3] Carden, Frank, and Brian Kopp, "A Quantized Euclidean Soft Decision Maximum Likelihood Sequence Decoder of TCM", IEEE Military Communications Conference, Vol. 2, pp. 279-682, OCT., 1988.

[4] Shigeo Nakajima, "Adaptive Coding Rate Trellis-coded 8PSK System", IEICE Trans. FUND-AMENTALS, VOL. E80-A, NO. 7, JULY 1997.

[5] G.Ungerboeck, “Channel coding with multilevel /phase signals”, IEEE Trans. on Information Theory, vol.IT-28, No. 1, Jan. 1982.

[6] Jian Liu, Subhash C. Kwatra and Jungwan Kim, “LSB Coded 8PSK Signals”, IEEE Transaction on Communications. Vol. 43, No. 2/3/4. February/March/April. 1995.

[7] G. Fettweis and H.Meyr, "High-Speed Viterbi Processor: A Systolic Array Solution," IEEE Journal on Selected Area in Commun., vol SAC-8, pp. 1520-1534, OCT.,1990.

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