Improving DVB-S2 Performance Through Constellation Shaping and Iterative Demapping

Xingyu Xiang and Matthew C. Valenti Lane Department of Computer Science and Electrical Engineering West Virginia University, Morgantown, WV, U.S.A.

Abstract—Because it is widely supported by commercial-off- constellation shaping [7]–[10]. Our strategy for APSK is based the-shelf (COTS) technology, the DVB-S2 waveform standard on that proposed by Le Goff et al. in [10] for bit-interleaved has become an attractive solution for military communication turbo-coded pulse-amplitude modulation (PAM). The strategy links. The waveform uses a combination of amplitude-phase- shift keying (APSK) modulation and low-density parity-check in [10] partitions the basic constellation into two or more (LDPC) codes. Typical DVB-S2 implementations select signals sub-constellations of increasing average energy and uses a from the APSK signal set with uniform probability. However, shaping code to select signals from the lower energy sub- information-theoretic results suggest that performance may be constellations more often than the signals from higher energy improved by selecting lower-energy signals more frequently than sub-constellations. higher-energy signals. In this paper, we propose and analyze a DVB-S2-compatible system that shapes the APSK constellation Our previous work in [6] on shaping for APSK was limited by selecting signals with a nonuniform probability. The receiver to only turbo codes. However, DVB-S2 uses LDPC codes. iterates between the APSK demapper, the shaping decoder, and Because the nature of turbo and LDPC decoders are quite the LDPC decoder. Using 32-APSK and a rate of 3 data bits per symbol, the system described in this paper achieves a gain of different, the adaptation of shaping to LDPC-coded systems over 1 dB relative to a standard DVB-S2 system (i.e. one that is not trivial. The DVB-S2 system can be considered as an does not use shaping or iterative demodulation) in additive white instance of bit-interleaved coded modulation (BICM) [11]. Gaussian noise (AWGN) at a bit-error rate of 10−5. About 0.7 Like other BICM systems, DVB-S2 can be iteratively decoded dB of the gain can be attributed to shaping, and rest of the gain using the strategy known as BICM with iterative demapping can be attributed to iterative demodulation and decoding. Lesser gains can be achieved over Rayleigh fading channels. and decoding (BICM-ID) [12]. BICM-ID has been previously considered for DVB-S2 in [13], but that paper does not I.INTRODUCTION consider shaping. Digital Video Broadcasting Satellite - Second Generation In this paper we apply a combination of BICM-ID and (DVB-S2) is the successor to the ubiquitous DVB-S satellite constellation shaping to the DVB-S2 system. On the one hand, digital video broadcasting standard [1]. DVB-S2 supports the the paper can be considered to be an extension of [6] to broadcast of standard-definition and high-definition television accommodate LDPC codes, while on the other hand, it can be (HDTV), interactive services, and data content distribution. considered an extension of [13] to accommodate shaping. At a Because of the wide availability of commercial-of-the-shelf rate of 3 data bits per APSK symbol and using 32-APSK, the (COTS) technology, DVB-S2 has become an attractive solution system in this paper achieves a gain of over 1 dB at a bit-error for military communication links [2]–[5]. Compared with the rate of 10−5 relative to a typical DVB-S2 implementation in first generation, DVB-S2 uses much stronger coding combined additive white Gaussian noise (AWGN). About 0.7 dB of the with high-order modulation. In particular, DVB-S2 uses low- gain can be attributed to shaping, and the other 0.3 dB can be density parity-check (LDPC) codes and amplitude-phase-shift attributed to iterative demapping and decoding. Lesser gains keying (APSK) modulation with constellations containing up can be achieved over Rayleigh fading channels. The gains are to 32 symbols. Together, these features achieve a 30% gain achieved without an expansion in bandwidth or a change to in transmission rate when using the same satellite transponder the standardized LDPC codes or APSK constellations. All that bandwidth and emitted signal power as DVB-S. is needed on the transmitter side is the inclusion of a shaping With APSK modulation, the signals are located on several encoder between the LDPC encoder and the APSK modulator. concentric circles, each with a different amplitude. In typ- The receiver architecture, which is disclosed in this paper, ical implementations, the APSK symbols are selected with requires iteration between the APSK demapper, the shaping uniform probability. However, as we have shown in [6], the decoder, and the LDPC decoder. performance of APSK may be improved by selecting lower- The remainder of this paper is organized as follows. A energy signals more frequently than higher-energy signals. general model for bit-interleaved LDPC-coded APSK with The strategy in [6] is an instance of the general concept of constellation shaping is provided in Section II. Section III discusses the shaping code. The BICM-ID receiver imple- The authors were sponsored by the National Science Foundation under Award No. CNS-0750821 and by the United States Army Research Laboratory mentation is discussed in Section IV. Numerical results and under Contract W911NF-10-0109. conclusions are given in Sections V and VI, respectively. d shaping c s1  buLDPC v encoder 2 z APSK x  bit s P/S encoder 1 2 modltdulator s3

separation …

sm

Fig. 1. Transmitter structure. II.SYSTEM MODEL 11100 01100 C 11000 A. Transmitter C C 11101 01000 C C 10100 10000 A block diagram of the transmitter is shown in Fig. 1. The B B 10001 10101 B 11001 k b 01101 B input to the system is a length- c vector of information C C bits, which is fed into an LDPC encoder. The LDPC encoder 00101 00100 00000 00001 A produces a length-n codeword u, which is permuted by inter- B A B c 01111 01001 C C leaver Π1 to produce the vector v.A bit separator separates v 00111 00011 B B 00110 00010 into m streams, where m = log2 M and M is the number of A A 11111 01011 C symbols in the APSK constellation. The first stream, denoted C 10111 10011 B B d, is passed through a shaping encoder to produce the shaping 10110 10010 B B codeword c, which is then permuted by interleaver Π2 to 01110 11011 C C produce the vector s . The purpose of the shaping encoder, 1 11110 01010 C 11010 C as described below, is to produce a nonuniform output with C a higher likelihood of 0’s than 1’s. The remaining streams at the output of the bit separator are denoted {s2, ..., sm} and Fig. 2. 32-APSK constellation. The shaping bit is the second from left. do not pass through the shaping encoder. The m streams si are all of equal length and pass through a parallel-to-serial the LDPC code and shaping codes rate by: converter (P/S) and into an APSK modulator. Since the si are of the same length and the shaping encoder has a rate less R = Rc [m + g(Rs − 1)] (1) than unity, it follows that the first stream d output by the bit where R is the rate of LDPC code and R = k /n is the rate separator is actually shorter than the other stream output by c s s s of shaping code. When shaping is used, g > 0 and R < 1, the bit separator. s which implies that the rate of the LDPC code Rc used by a The P/S converter assures that each APSK symbol is se- system with shaping must be higher than the R used without s s c lected using one bit from each of the i. The bit from 1 shaping if the overall system rate R is to remain fixed. In other shaping is called a bit and is used to select from among words, the loss of the system rate R caused by the shaping two subconstellations with nonequal probability. When the code must be compensated by an appropriate increase in R . shaping bit is equal to 0, the lower-energy subconstellation is c selected, while when it is 1, the higher-energy subconstellation B. Receiver is selected. The remaining m − 1 bits, which are not shaped, The receiver structure is shown in Fig 3. While Section are used to select from among the M/2 symbols within the IV describes the receiver in detail, a general description is subconstellation. An example symbol labeling map is shown provided here to provide a better understanding of the entire in Fig. 2, which is the labeled 32-APSK constellation from the system. Throughout this discussion, it is assumed that all DVB-S2 standard. To be consistent with the DVB-S2 standard, information exchanged within the decoder is in the form of the shaping bit is the second bit from the left. With this bit used log-likelihood ratios (LLRs). The notation La denotes an LLR as the shaping bit, the high-energy subconstellation is the outer input to a module (which may possibly be fed back from ring of 16 symbols, while the lower-energy subconstellation another module), while Le denotes the LLR output by a is the union of the two inner rings of symbols. module. The received symbols y, which are corrupted by the Note that in Fig. 1, there is just a single shaped bit, which channel, are passed into the APSK demodulator. The APSK corresponds to partitioning the constellation into two subcon- demodulator produces log-likelihood ratios (LLRs), which are stellations. More generally, g bits could be shaped, in which divided into m streams Le(si) by reversing the P/S operation case the constellation is partitioned into 2g subconstellations of the transmitter. The bit-separation operation is expressed as [6]. To accommodate such a possibility, we use the shorthand S/P in the diagram, and Le(s2:m) is used to represent the LLR s1:g to represent the first g streams, which have passed through of streams {s2, ..., sm}. the shaping encoder, and sg+1:m to represent the other m − g The first stream Le(s1) is de-permuted to produce La(c), streams, which do not pass through the shaping encoder. which is fed into the shaping decoder. Initially, the a priori The overall rate of the system R is the number of informa- input to the shaping decoder La(d) is set to all zeros. A tion bits per modulated symbol, and is related to the rates of parallel to serial converter combines the output of the shaping Hard decision Le(z) Le(s2:m) Le(v) L (u) y a APSK S/P P/S -1 -1 L (c) !1 Le(s1) a Le(d) !3 CND demodulator -1 _ !2 shaping VND decoder La(d) !2 La(z) Le(c) P/S La(s1) S/P ! 1" !3 La(s2:m) Le(u)

Fig. 3. Receiver structure. decoder Le(d) with the LLRs of the other streams Le(s2:m) III.SHAPINGFOR 32-APSK to produce a vector L (v) of combined LLRs. The vector e Prior to encoding, the shaping encoder’s input d must be L (v) is de-permuted by Π−1, and the resulting vector L (u) e 1 a segmented into L short blocks, each of length k . The encoder is introduced as the input to the LDPC decoder. s operates on each of these blocks by mapping the k bits onto Rather than illustrating the decoder structure using a Tanner s a length-n shaping codeword based on a codeword table. or factor graph, Fig. 3 interprets the LDPC code as the serial s The L code blocks that are generated by the encoder are concatenation of an inner repetition code and outer single par- then reassembled into a length-Ln shaping codeword c. Let ity check code, i.e. as an extended irregular repeat-accumulate s p denote the probability that a particular bit in c (or s ) (eIRA) code [14]. Such a representation helps to illuminate 0 1 equals zero, and p be the probability that it equals one. p the interaction between the LDPC and shaping decoders. 1 0 should be always greater than p according to the construction The LDPC decoder is comprised of two processing blocks: 1 methodology of the shaping codeword table. A variable node decoder (VND) and a check node decoder ks The shaping codeword table C is a size 2 × ns matrix. (CND) [15]. The VND produces a posteriori messages Le(Qi) Each row of C is a length-ns codeword. Each unique length- of bits ui, which, after interleaving and subtraction by the CND output, will form the input to the CND. The interleaver, ks binary input sequence is used to select a particular row from the matrix. The codeword table C is initialized to contain the denoted by Π3 in the diagram, corresponds to the edges in the code’s Tanner graph that connect the variable and check all-zeros codeword of length ns, and codewords with higher nodes. After interleaving, the output of the CND is used as weight are recursively added to C. Suppose that C contains all the a priori input to the VND. codewords of weight w−1 or lower but the number of rows in C is still less than 2ks . Then weight-w codewords are drawn The output Le(u) of the LDPC decoder is fed back to ks the shaping decoder and APSK demodulator, also called the and added to C until the number of distinct codeword is 2 . demapper, to be used as extrinsic information during the next To assure each bit position in the codeword has approximately iteration. A second S/P converter sends the LLRs of the shaped the same value of p0, each new weight-w codeword is selected with the goal of balancing the column weights of the codeword bits into the shaping decoder as input La(d), where after the initial iteration it is used as the a priori input. Another P/S table C. converter, which is identical to the P/S in Fig. 1, combines As an example, consider the (ns, ks) = (5, 3) code. There 3 the interleaved output of the shaping decoder with the LLRs are 2 = 8 codewords in C. The number of binary codeword of weight two or less is: of the unshaped bits to create the vector La(z). The output of that P/S converter is used as the a priori input to the demapper 5 5 L (z) + = 6. after the initial iteration (prior to the first iteration, a is 0 1 initialized according to the average bit probabilities for each bit position, as described in Section IV). In addition to these six codewords, C will contain two more 5
During each receiver iteration, four information exchanges codeword of weight 2. There are 2 = 10 possible weight-2 are performed: (1) Between the demapper and LDPC decoder, codewords to chose from when creating the code table. For in- (2) Between the demapper and shaping decoder, (3) Between stance, if the last two codewords in C are {(00011), (00101)}, the LDPC decoder and shaping decoder, and (4) Between the then the column weights would be [1 1 2 2 3]. Alternatively, if VND and CND blocks inside the LDPC decoder. Notice that they are {(01100), (00011)}, then the column weights would only one iteration of LDPC decoding is executed per iteration be [1 2 2 2 2]. In the second design, the probability p0 of demapping and shaping decoding. In fact, the shaping of each bit position, which is equal to the column weight decoder is the only additional processor required for this divided by 8 (the number of rows), is nearly constant. Thus, system compared to the BICM-ID system in [13]. Although the second design is preferred over the first. This design policy the inclusion of the shaping decoder increases the complexity is corroborated by the simulation results, which demonstrate of the receiver, the additional complexity is moderate provided improved performance when the column weights are carefully that the reasonably small length of the shaping code. balanced. The 32-APSK constellation in Fig. 2 follows the DVB-S2 be expressed without subscripts. During a particular symbol standard and therefore consists of three concentric rings, with interval, the demodulator computes the LLRs Le(z) of the m 4 points in the inner ring, 12 points in the middle ring, and code bits associated with the transmitted symbol x ∈ X , where 16 points in the outer ring. When there are two equal sized X is the signal constellation. The inputs to the demodulator sub-constellations (g = 1), the shaping bit is the second bit are the received discrete-time signal y, which is produced by a of the word based on the labeling rule in Fig. 2. The first matched-filter front end, as well as the set of m a priori LLRs partition, which is selected with probability p0, contains the La(z), which is extrinsic information generated by the shaping signals in the first two rings (i.e. signals labeled A and B and LDPC decoders during the previous iteration. Prior to the 1−p0 in the diagram). The second partition, which is selected with first iteration, La(z) is initialized to La(s1) = log( ) for p0 probability p1, contains the signals in the outer ring (i.e. those the shaped bit and La(s2:m) = 0 for the unshaped bits. Since labeled C). Due to the larger number of 0’s in shaping code, the first stream s1 corresponds to the shaping code, it follows signals in the inner two rings are more likely to be selected that p0 > 1/2 and La(s1) will initially be negative. th than signals in the outer ring. Let the function zk(x) return the k bit labeling symbol x. Because the DVB-S2 standard only defines LDPC codes Using the MAP demodulator described in [10] and [16], the for a fixed set of eleven different rates from Rc = 1/4 to a posteriori probability that zk(x) = q, q ∈ {0, 1}, is

Rc = 9/10, then according to equation (1), the possible choice m−1 0 ezj (x )La(zj ) of shaping code rates Rs is limited if the overall rate R is to X 0 Y P (zk(x) = q|y) = p(y|x ) (2) La(zj ) remain constant for the shaped and unshaped systems. We 0 z 1 + e x ∈Xk j=0 found that using a rate Rs = 1/2 shaping code provides good j6=k shaping gain, while allowing shaped and unshaped systems q where X is the subset of X containing those signals whose to be compared at a constant R. If the R of the shaped k kth bit positions are labeled with q. system is not required to match that of an unshaped system, For the given channel, the conditional probability of y given then the optimization procedures discussed in [6] could be x is used to pick the optimal rate of the shaping code, which 2 1 − (y−ax) may be a value other than Rs = 1/2. When the rate of p(y|x) = √ e 2σ2 (3) 2 the shaping code is limited to Rs = 1/2, there are still 2πσ 2 several choices of the shaping code, i.e. {ns, ks}: {2, 1}, where σ = N0/2 is the noise variance, N0 is the one-sided {4, 2}, {6, 3}, {8, 4}, etc. In general, as ks increases, so does power spectral density of the white Gaussian noise, and a is the complexity of the shaping decoder (which is exponential the fading coefficient (equal to 1 in an AWGN channel). in ks). The simulation results analyzes the different rate-1/2 The demodulator output may be expressed as an LLR by shaping codes to determine the preferred choices. combining (2) with (3) and performing some simplifications,

IV. BICM-ID RECEIVER STRUCTURE m−1 X 0 Y 0 This section provides a more detailed description of the p(y|x ) exp (zj(x )La(zj)) x0∈X 1 j=0 receiver than the one given in Section II-B. The section k j6=k L (z ) = ln consists of three subsections, describing the demodulator, e k m−1 shaping decoder, and LDPC decoder, respectively. Because X 0 Y 0 p(y|x ) exp (zj(x )La(zj)) information is exchanged among all these components, the 0 0 j=0 x ∈Xk notion of an “iteration” may be ambiguous. In the following j6=k discussion, one full iteration is specifically meant to include   m−1 an iteration of the shaping decoder, an iteration of the LDPC 0 2 P  (y−ax ) X 0  exp − + zj(x )La(zj) decoder (one iteration of each of the variable-node decoder  N0  x0∈X 1   and check-node decoder), and, for the case of BICM-ID, one k j=0 j6=k iteration of symbol demapping. For the BICM system, the = ln  . (4) symbol demapper is only executed once, and information is m−1 P  (y−ax0)2 X 0  not fed back to the demapper. Note that in [10], it is shown that exp − + zj(x )La(zj)  N0  0 0   feeding back information to the demapper provides little gain x ∈Xk j=0 when gray-mapped PAM or QAM is used. However, since the j6=k present system uses APSK, a gray mapping is not possible, and The above computation is facilitated by the use of the max-star BICM-ID is beneficial, as demonstrated for unshaped systems P xi operator in place of ln( i e ) [16]. in [13] and for shaped systems in Section V. B. The Shaping Decoder A. The Demodulator The first LLR stream Le(s1) is de-interleaved and fed in to The demodulator is implemented on a symbol by symbol the shaping decoder as La(c). The shaping decoder outputs the basis. For ease of exposition, we drop the dependence on extrinsic LLRs Le(d) and Le(c) based on the input from the the symbol interval in this subsection, so that symbols may demodulator and the extrinsic information fed back from the LDPC decoder. The implementation of the shaping decoder is A variable node that connects to du check nodes processes similar to that of the demodulator, but the summations are information coming in from all connected check nodes and now over subsets of the shaping code rather than subsets from the decoder input (du + 1 input messages, in total). The of the signal constellation. The exponent of the transition VND simply performs the summation probabilities are found by taking the inner product of the ns bit X LLRs with the candidate codeword. Taking into account these Le(Qi) = La(ui) + La(rji) (7) differences, the output of the MAP decoder for the shaping where L (r ) is the a priori LLR coming in from the jth code is a ji check node, the summation is over the incoming edges, and L (u ) is the LLR of code bit u at the input of the LDPC L (d ) = a i i e j decoder. L (Q ) is a LLR that represents the a posteriori   e i ith u ns ks probability of the bit i of the LDPC codeword. During X X 0 X 0  each iteration, a hard decision is made on L (Q) to produce exp  cn(d )La(cn) + d La(d`) e  `  0 1 n=1 `=1 an estimate of the codeword and the corresponding message. d ∈Dj `6=j Decoding can halt once a correct codeword has been found ln (5)   The input to the jth check node is the extrinsic information, ns ks X X 0 X 0  which may be found by subtracting the message coming in exp  cn(d )La(cn) + d`La(d`)   from check node j from the LLR Le(Qi), 0 0 n=1 `=1 d ∈Dj `6=j Le(qij) = Le(Qi) − La(rji) t th X where Dj denotes the set of messages d whose j bit position = La(ui) + La(rj0i) (8) th is labeled with t, t ∈ {0, 1}, and cn(d) is the n bit in the j06=j codeword associated with message d. where L (q ) is the extrinsic information that is passed from The extrinsic information L (c) produced by the shaping e ij e the ith variable node to the jth check node and the summation decoder can be implemented in a similar manner, is over all edges except for the one connecting the variable node to the jth check node, i.e. all incoming edges j0 6= j. The Le(cj) =   subtraction operation in the first line of (8) is shown in Fig. ks ns 3. The CND essentially decodes the single parity-check code X X 0 X 0  exp  dn(c )La(dn) + c La(c`) associated with each row of the parity-check equation. While  `  0 1 n=1 `=1 there are several ways to formulate the CND decoder, we use c ∈Cj `6=j a formulation described in [17] which is not be discussed here. ln   (6) ks ns V. NUMERICAL RESULTS X X 0 X 0  exp  dn(c )La(dn) + c La(c`)  `  In this section, we compare the bit-error performance of 0 0 n=1 `=1 c ∈Cj `6=j bit-interleaved LDPC coded APSK both with and without shaping. The APSK modulation and LDPC coding are as spec- t th where Cj denotes the shaping codewords c whose j bit ified in the DVB-S2 standard [1], with 32-APSK modulation position is labeled with t, t ∈ {0, 1}, and dn(c) is the used along with the length n = 64, 800 LDPC code. The th c n bit in the message associated with codeword d. Note amplitudes of the 32-APSK constellation are selected such that, because there are more zeros than ones in the shaping that the middle ring’s radius is 2.64 times the inner ring’s 0 1 codewords, |Cj | > |Cj |, and therefore there are more terms radius, and the outer ring’s radius is 4.64 times the inner in the denominator of (6) than in the numerator. This is in ring’s radius. The system uses only one shaping bit (g = 1) contrast with (5), which has the same number of terms in the which we previously showed to strike a balance between numerator and denominator since the message bits are equally performance and system complexity [6]. The overall system likely to be 0 or 1. rate is 3 bits/symbol (R = 3), in which case it is easy to identify shaping codes whose rates R are compatible with C. The LDPC decoder s the limited LDPC rates Rc defined in the standard. To ensure The decoder can be divided into two parts, a variable node R = 3 both with and without shaping, Rc = 3/5 is used for decoder (VND) and a check node decoder (CND). An edge the uniform (unshaped) system, and Rs = 1/2 and Rc = 2/3 interleaver connects the the VND with the CND. As shown in are used for the shaped system. Fig. 3, iterative decoding is performed by passing interleaved The bit-error rates for both AWGN and ergodic (fully- messages between the VND and the CND until the correct interleaved) Rayleigh fading channels are shown in Figs. 4 codeword is found or the maximum number of iterations is and 5, respectively. By comparing the two curves on the right reached. Each check node in the CND represents one parity- of Fig. 4, it is clear that BICM-ID provides a gain of about check equation; all parity check equations should be satisfied 0.3 dB over BICM in an AWGN channel without shaping. when the codeword is correctly decoded. Comparing the curve for unshaped BICM-ID (second from 0 10 and other communication links. By incorporating constellation BICM Uniform BICM-ID Uniform -1 shaping along with iterative demodulation and decoding, an 10 Shaping (4,2) Shaping (6,3) additional decibel of coding gain can be readily attained at a Shaping (12,6) rate of 3 bits per symbol over an AWGN channel. Gains can -2 10 also be achieved over Rayleigh fading channels and at other transmission rates. Due to the inclusion of a nonlinear shaping 10-3 code and its corresponding decoder, the proposed system has BER a higher per-iteration complexity than a standard DVB-S2

10-4 system. However, by carefully chosing parameters, a shaping code that provides a good tradeoff between performance and

-5 complexity can be identified. 10 REFERENCES

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