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Probabilistic Shaping and Non-Binary Codes Joseph J. Boutros∗, Fanny Jardel†, and Cyril Me´asson‡ ∗Texas A&M University, 23874 Doha, Qatar †Nokia Bell Labs, 70435 Stuttgart, Germany ‡Nokia Bell Labs, 91620 Nozay, France [email protected], fanny.jardel,cyril.measson @nokia.com { } Abstract—Wegeneralizeprobabilisticamplitudeshaping(PAS) implementations of contemporary coding schemes that have withbinarycodes[1]tothecaseofnon-binarycodesdefinedover been proven to asymptotically achieve capacity with constant prime finite fields. Firstly, we introduce probabilistic shaping complexity per information unit [17], [21]–[23], it is then via time sharing where shaping applies to information symbols natural to combine them with efficient shaping methods. only.Then,wedesigncircularquadratureamplitudemodulations (CQAM) that allow to directly generalize PAS to prime finite Inprobabilisticshaping,forlineardigitalmodulations,thea fields with full shaping. prioriprobabilitydistributionofmodulationpointsismodified 7 1 to match a discrete Gaussian-like distribution, namely the 0 I. INTRODUCTION Maxwell-Boltzmann distribution [3]. The method aims at 2 Shaping refers to methods that adapt the signal distribu- maximizing the mutual information with respect to the same n tion to a communication channel for increased transmission modulationwhereallpointsareequallylikely.Forspecial2m- a efficiency. Shaping is eventually important for optimal infor- ASK and 2m-QAM constellations with linear binary codes, J mation transmissions [4] and various solutions starting with this method is equivalent to probabilistic amplitude shaping 7 non-linear mapping over asymmetric channel models towards (PAS) where uniformly-distributed parity bits are assigned to 2 pragmatic proposals involving shaped QAM signaling have the sign of a constellation point [1], [2]. In this paper, we ] been investigated and/or implemented over the years. generalize this method to the non-binary case. The goal is T More precisely, building upon early works on, e.g., many- to permit the use of efficient non-binary codes in order to I to-one mapping, research efforts from the 70s towards the enablelow-latencyprocessing(reducingthe needfor‘Turbo’- . s 90s derive conceptual frameworks and methods to reduce detection[17]).Also,fromanalgebraicviewpoint,acharacter- c [ the shaping gap in communication systems. Exploiting the isticp>2ofthefinitefieldFpm onwhichcodingisbuiltleads principles of coded modulation, a sequence of works [5]– to new interesting problems such as distribution matching in 1 v [12] present operational methods to reduce the shaping gap. Fpm and assigning a constellation points to elements in Fpm. 76 iCnogmgpaairnedistoaccuhbieivcacbolnesuteslilnagtiownse,llu-apdtaoptπ6eed≈si1g.n5a3lidnBg.oSfismhapple- finIend tohviesrpFap,erw, hceordeesp aisreansuopdpdosperdimtoe.bFeirsltilnye,aerxacnepdt dfoer- p 9 methods such as trellis shaping or shell mapping permit to codes with a sparse generator matrix, we show in Section II 7 recover a significant fraction of the 1.53dB figure. Exam- that parity symbols are asymptotically uniformly-distributed 0 ples of applications include the ITU V.34 modem standard over F . This fact is used to derive two new methods for . p 1 recommendations that uses shell mapping to recover 0.8dB. probabilistic shaping. Time sharing is proposed in Section III 0 While several shaping schemes are based on the structural wheresymbolsofap-arycodearemappedintop-ASKpoints. 7 propertiesoflattices[13]–[15],morerandomizedschemesalso Hence,intimesharing,probabilisticshapingisperformedonly 1 : emerge after the re-discovery of probabilistic decoding in the when information symbols are transmitted. Full probabilistic v 90s. With the adventof efficientbinarycodes,differentcoded shaping is described in Section IV where circular QAM i X modulationschemeswere proposedofferingflexible and low- (CQAM) constellations of size p2 points are introduced. This r complexsolutions[17].Inthe2000s,despitetheimportantde- second method assigns a constellation shell to a Maxwell- a velopmentofwirelesscommunications,theneedforadvanced Boltzmann-distributed information symbol and then a parity shaping methods seems to have remained marginal. From symbol selects a point within that shell. Numerical results a technological viewpoint, this may have been justified by for p-ASK-based time sharing and p2-CQAM probabilistic the high variations of the channel in wireless communication shapingareshowninSectionV.Similartothebinarycase[1], networks. From an academic viewpoint, schemes have been a gap to channel capacity of 0.1 dB or less is observed for analyzed and match the capacity-achieving distribution of a CQAM constellations. channelindifferenttheoreticalscenarios[18]–[20].Inthe last few years, industrialapplicationsofshapingmethodshavere- II. SUM OF RANDOMVARIABLES IN APRIME FIELD gainedinterest.Thisconcernsareaswherecurrenttechnologies Lemma 4.1 in [16] established the expressions of the operate close to fundamental limits. For example, different probability of a sum in F . We translate this result to a 2 methods have been experimented in optical communications prime field F = Z/pZ. Principles of this extension to the p [26], [27]. Hence, because there are already efficient VLSI non-binary case are implicit from Chapter 5 of [16] with the use of the z-transform. Nevertheless, we give here the It remains to summarize this observation in a theorem. exact expression of the probabilityof a sum of prime random Theorem 1: Let p be a prime and F = 0,1, ,p 1 p { ··· − } symbols modulo p. This expression is directly related to be the associated Galois field. Consider a sequence s ℓ ℓ≥1 Hartmann-Rudolph symbol-by-symbol probabilistic decoding of independent random symbols over F with re{spe}ctive p [24] in the special case of a single-parity check code and its probability distributions (q (0),q (1), ,q (p 1)) 1 ℓ ℓ ℓ ℓ { ··· − } ≥ generalization to characteristic p [25]. such that limsup max (q (p)) <1. Then Lemma 1: Let p be a prime and F = 0,1, ,p 1 ℓ→∞{ p ℓ } mbe itnhdeeapsesnodceianttedsyfimnbitoelsfioelvde.rCFonsinidewrhpaicsheqt{hueenℓc-eth·{·ss·yℓm}mℓb=−o1loi}sf ∀k ∈Fp, ml→im∞Pr{ m sℓ =k}= p1. (6) p ℓ=1 β F with probability X ∈ p For error-correction over a prime field, this observation is Pr sℓ =β =qℓ(β). interestingasfollows.ThelimittheoremoverFpindicatesthat { } the non-systematic symbols obtained from a linear encoder Then, for any k F , the probabilitythat the sum of the s ’s ∈ p ℓ associated with a dense generator matrix will tend to have a equals k is uniform distribution independently on the input distribution. m 1+ p−1 m p−1q (β)ωiβ−k+1 Pr s =k = i=1 ℓ=1 β=0 ℓ , III. PROBABILISTIC SHAPING VIA TIMESHARING OVER { ℓ } P Q (cid:16)Pp (cid:17) PRIME FIELDS ℓ=1 X (1) A common mapping between non-binary codes and non- binarymodulationsistoselectaconstellationandafinitefield where ω d=efexp(2π√ 1/p) indicates the p-th root of unity. of identical size. Let p be a prime integer, p > 2. Consider − Proof: Consider the enumerator function in t, the set of p points shown in Figure 1, known as p-ASK mod- m p−1 ulation. This p-ASK set = p−1,..., 1,0,1,...,p−1 Q(t)d=ef qℓ(β)tβ mod (tp 1). (2) is isomorphicto the finiteAfield{F−p (2a ring is−omorphismin2Z)}. − Symbols from F are one-to-one mapped into p-ASK points. ℓY=1(cid:16)βX=0 (cid:17) p We embed F into Z such that a symbol s F and its Observethatif this isexpandedintoa polynomialin t (where p ∈ p degreeoperationsaretakenmodp),thecoefficientoftk isthe corresponding point in A satisfy x−s=0 mod p. probability that the sum of m symbols is k, which we write m Fp={0,1,...,p−1} Pr s =k =coef[Q(t),tk]. (3) ℓ { } one to onemapping Xℓ=1 − − Let us also define for any k 0,1,2, ,p 1 the p-ASK ∈ { ··· − } function Q (t)=t−kQ(t) mod tp 1. (4) p−1 1 0 1 +p−1 k − − 2 − 2 In anidenticalmannerasforQ(t), expandingQk(t) would Fig. 1: Real p-ASK constellation isomorphic to F . p enumerate the probabilities of the sum of the s ’s. Recall ℓ that the p-th root of unity in the complex plane satisfies There are many advantages for such a simple structure p−1ωki = 0 for any k 1,2, ,p 1 . Then, for any k i=F0 , we have ∈ { ··· − } where the source is p-ary, the linear code is over Fp, and P∈ p p-ary modulation points are transmitted over the channel. m p−1 Firstly, a probabilistic detector needs no conversion between 1 Pr sℓ =k = Qk(ωi) (5) modulation points and code symbols. A channel likelihood, { } p ℓ=1 i=0 after normalization, is directly fed as a soft value to the X X because all but the constant polynomial terms are annihilated input of a probabilistic decoder. Secondly, turbo detection- from the fact that the roots of unity sum to zero. It remains decoding between the constellation and the code C is not A to evaluate the expression observing that ω0 = 1 to get the requiredasforbinarycodeswithnon-binarymodulations[17]. results. (cid:3) Remark 1: This lemma shows that, if a s is uniformly Consider a systematic linear code C over F where parity ℓ p distributedoverF ,thenthesumisalsouniformlydistributed. symbolssatisfyTheorem1,i.e.,checknodesusedforencoding p Remark 2: For any ℓ, it is straightforward from convexity have a relatively high degree. Many practical error-correcting argumentsthatthe weightedsum p−1q (β)ωiβ in the com- codes do satisfy this property, such as LDPC codes over β=0 ℓ plex plane lies inside the unit circle in the strict sense if and F . Let R = k/n be the coding rate of C, where n is p c P onlyifoneoftheprobabilitydistributionq isnotdegenerated the code length and k is the code dimension. Assume that ℓ inonesingularpoint.Therefore,assumingthatthenormtends information symbols s ,s ,...,s at the encoder input are 1 2 k to be smaller and bounded away from 1, the distribution of identically distributed according to an a priori probability the infinite sum tends to be uniform. distribution π p−1. Let P (x,ν) exp( ν x2) be a { i}i=0 MB ∝ − | | discrete Maxwell-Boltzmann distribution [3] with parameter The key idea in our new coded modulation is to assign ν 0. The a priori distribution π is taken to be the parity symbol to p modulation points with the same i ≥ { } amplitude. This is a directgeneralizationof the sign mapping π =P (0,ν) 1, (7) 0 MB ∝ to p-ary mapping. The linear p-ary code is assumed to be πi =πp−i =PMB(i,ν) exp( νi2), (8) systematic. Its information symbols become amplitude labels ∝ − in the modulation. We propose a bi-dimensionalconstellation fori=1...p−1.Theaverageenergyperpointforthep-ASK 2 withp2 points,referredtoasp2-circularquadratureamplitude constellation, denoted by E , is given by s modulation (p2-CQAM). A circle containing CQAM points (p−1)/2 of the same amplitude will be called a shell. The p2-CQAM E = P (x,ν) x2 = 2 π i2. (9) includespshellswithppointspershell.Suchabi-dimensional s MB i | | x∈A i=1 constellation is not unique. Indeed, many ways do exist to X X build p shells and populate each shell with p points. As a From Theorem 1 and (7)&(8), a fraction R of transmit- c consequence, we introduce a figure of merit for a constella- ted ASK points corresponding to information symbols are tion [6] and we build a specific p2-CQAM constellation that Maxwell-Boltzmann-shaped and a fraction 1 R of ASK c − maximizes this figure of merit. pointscorrespondingtoparitysymbolsisuniformlydistributed Definition 1: Consider a finite discrete QAM constellation in the constellation. We refer to this coding scheme as proba- bilistic shapingviatime sharing.The targetrate shouldbe the A ⊂ C. Assume that x∈Ax = 0. Let Es = Px∈|AA||x|2 be averageinformationrate(expressedinbitsperrealdimension) the average energy per point, assuming equiprobable points. P Rt =Rclog2(p)=RcI(Xs;Y)+(1−Rc)I(Xp;Y), (10) Lsqeutadre2EdmEinu(cAlid)e=anmdiisntaxn,xc′e∈Abe,xtw6=xe′e|nxt−hexp′o|2inbtseotfheA.mAinifimguumre of merit for is defined by the following expression: where the two random variablesXs,Xp satisfy Xs πi FM A ∈A ∼ and X 1/p. The random variable Y represents the output d2 ( ) ofareapl∼additivewhiteGaussiannoisechannel,whereadditive FM(A)= EmEin A ·log2(|A|). (13) s noise has variance σ2 = N0. For a given target rate R , 2 t Thelog ( )factorisarbitrary,itisusedintheabovedefini- the Maxwell-Boltzmann parameter ν is chosen such that the 2 |A| tiontonormalizethesquaredminimumEuclideandistanceby signal-to-noise ratio γ = E /N attaining R is minimized. s 0 t bit energy instead of point energy. This may be useful when Let γ be that minimum. We also define two signal-to-noise A comparing two constellations of different sizes. ratios γcap and γunif such that Now,we builda p2-CQAM constellation thatmaximizes A 1 ( ) by populating the p shells as follows: M R = log(1+2γ ), (11) F A t 2 cap 1) For the first shell, draw p uniformly-spaced points on and the unit circle. The points are xℓ = exp(ℓ2pπ√−1), for ℓ = 0...p 1. Here, we impose the constellation R =I(X ;Y), for γ =γ . (12) t p unif − minimum distance to be the distance between two con- Then, the gap to capacity and the shaping gain (expressed in secutive points of the first shell, decibels) are respectively given by γA(dB) γcap(dB) and π − d ( )=2sin( ). (14) γ (dB) γ (dB).Inthistimesharingscheme,probabilis- Emin unif A A p − tic shaping is made only duringa fraction R of transmission c 2) Assume that shells 1 to i 1 are already built. Let time. This method is attractive due to isomorphism between − x = ρ exp(φ √ 1) be the first point of the i-th the fieldFp andthe p-ASKconstellation.From(10), onemay shipell. Thei p 1i r−emaining points on this shell are quickly conclude that high coding rate is recommended to − x = ρ exp((φ + ℓ2π)√ 1), ℓ = 1,...p 1. approachfull-timeprobabilisticshaping.However,atRc close Liept+dℓ2 = mi in i xp −x 2 be the minim−um to 1,the mutualinformationI(X;Y), forX , approaches i ℓ=0...ip−1| ip − ℓ| ∈A distance between the first point of the current shell and its asymptote log ( ) = log (p) and the required signal-to- 2 A 2 all previously constructed points. The radius ρ and the noise ratioγ goesfar awayfromγ . Thisis clearlyshown i A cap phase shift φ are determinedby an incrementalsearch: in the numericalresults presentedin Section V. A methodfor i full probabilistic shaping is proposed in the next section. • Start with ρi =ρi−1 and increment by a step ∆ρ. • At each radius increment, vary φi from π/p to IV. PROBABILISTIC SHAPING VIAp2-CIRCULAR QAM π/p. − OVERPRIME FIELDS • Stop incrementing the radius ρi and the phase shift φ when d2 d2 ( ). Now, x is found. We proposein this section a codedmodulationscheme that i i ≥ Emin A ip allows full probabilistic shaping of all transmitted symbols 3) Repeat the second construction step until completing withanon-binarylinearcodeoverF .Probabilisticamplitude the p-th shell of the p2-CQAM constellation. p shaping with binary codes maps uniformly-distributed parity bits into the sign of an ASK point [1]. This sign mapping is Thep2-CQAMobtainedwiththeconstructiondescribedabove not valid with a prime finite field F , p>2. has the circular symmetry required by PAS over F . p p 3 3 3 2 2 2 1 1 1 0 0 0 -1 -1 -1 -2 -2 -2 -3 -3 -3 -3 -2 -1 0 1 2 3 -3 -2 -1 0 1 2 3 -3 -2 -1 0 1 2 3 Fig. 2: Bi-dimensional p2-CQAM constellation for p=5,7,11 from left to right. Examples of circular QAM modulations for probabilistic Given the a priori distribution π p−1 of symbols in the amplitude shaping are shown in Figure 2, for p = 5,7,11 finite field F , the linear code C{[ni},ik=]0 and the p2-CQAM p p respectively. Points are drawn as small circles in red. Blue constellation should be combined together as illustrated in segments connect points located at minimum Euclidean Figure 3. Suppose that R = 1/2 and say that s F c 1 p distance. By the given construction, the inner radius of the is an information symbol (encoder input) and p F∈is a 1 p ∈ p2-CQAM is ρ = 1, p. The outer radius ρ varies paritysymbol.Then,s shouldbebeshapedbythedistribution in out 1 slightly with p but lim ∀ρ =ρ ( ) 3.6. This limit matcher (DM) according to π p−1 [2]. The symbol s will p→∞ out out ∞ ≈ { i}i=0 1 exists because the sequence ρ (p) is increasing with p and be used to select a shell in the p2-CQAM and the parity out bounded from above by 1 + (p 1)d ( ) 1 + 2π. symbolp willuniformlyselectapointonthatshell.Similarly, Emin 1 − A ≤ The limitation of the Maxwell-Boltzmann probability mass supposethatR =2/3andconsiderfourinformationsymbols c function to amplitudes between ρ = 1 and ρ ( ) s ,s ,s ,s and two parity symbols p ,p . The DM shall in out 1 2 3 4 1 2 is a major drawback. This short interval [1,ρ ( )[∞is generate s ,s ,s according to the distribution π p−1 and out ∞ 1 2 3 { i}i=0 shifted away from the origin and is not large enough to select the shell of three p2-CQAM points. The symbol s 4 yield a good Gaussian-like discrete distribution. In the is read directly from a uniform i.i.d p-ary source. Given the next section, the shells radii are modified to get a wider shellsofthreepoints,uniformly-distributedsymbolss ,p ,p 4 1 2 amplituderange,thep2-CQAMphaseshiftsarekeptinvariant. constitute the pointsindicesinside those shells. In the general case,n/2symbolsinF withprobabilitydistribution π are p i { } Lets ,s ,...,s bei.i.d.informationsymbolswithapriori read from the DM and mapped into a shell number for n/2 1 2 k probability distribution π p−1, as in the previous section. CQAM points. The probabilistic shaping is due to these n/2 { i}i=0 Then, for points x , i,ℓ = 0...p 1, the prior symbols On the other hand, k n/2 uniformly-distributed ip+ℓ ∈ A − − distribution becomes symbols are directly read from the source. Together with n k parity symbols, i.e., a total of n/2 symbols, uniformly- π P (x ,ν) π(xip+ℓ)= pi = MB |pip| . (15) di−stributed symbols in Fp determine the phase of CQAM points within constellation shells. In presence of the above distribution, the signal-to-noise ratio should be defined with an average energy per point Etpu2sa-lC=iQnPfAoMrpim=−01faatπicoiil|nix.taiTpte|h2se.tFhgueernntehuremarlmeeroxicrpear,leteshvseiaolcnuiracotiufolnIar(oXsfy;amYvme)reawtgrieythmofpu2a- DM s1,...,sn2Encoder select psMh2el-alCppQerAM n2 points integraltermsreducestoptermsonly.Themutualinformation sn2+1,...,sk overFp p1,...,pn−k Merge sweiltehcitn p sohienltl I(X;Y) is given by Fig. 3: Full probabilistic amplitude shaping with p2-CQAM. p−1 p(y x ) ip π p(y x )log | dy. Xi=0 iZy∈C | ip 2 ℓp=2−01π(xℓ)p(y|xℓ)! Ourp-arycodedmodulationsuitedforprobabilisticshaping The Maxwell-Boltzmann paramPeter ν in (15) is chosen such assumes that Rc 1/2, i.e., k n/2. Coding rates in the ≥ ≥ that 2R = 2R log (p) = I(X;Y) at a minimal value of interval [0,1/2[ are less attractive for probabilistic amplitude t c 2 signal-to-noiseratio E /N =γ , where R is the targetrate shaping because, for small R , a constellation with equiprob- s 0 A t c per real dimension. The gap to capacity is determined by the able points already shows a rate that is too close to channel differenceγ γ withγ satisfying2R =log (1+γ ). capacity in terms of signal-to-noise ratio. A− cap cap t 2 cap V. NUMERICAL RESULTS [3] F.R.KschischangandS.Pasupathy, “Optimalnonuniform signaling for Gaussianchannels,”IEEETrans.Inf.Theory,vol.39,no.3,pp.913–929, Two typical values of p are considered in this section, May1993. namely p=7 and p=13. The target rate herein is expressed [4] R. G. Gallager, Information theory and reliable communication. New in bits per real dimension for both real and complex York:Wiley,1968. [5] A. R. Calderbank and N. J. A. Sloane, “New trellis codes based on constellations. Gaps and gains are expressed in decibels. lattices and cosets,” IEEE Trans. Inf. Theory, vol. 33, no. 2, pp. 177– 195,Mar.1987. [6] G. D. Forney and L.-F. Wei, “Multidimensional constellations – Part I: Size Coding Target Potential Gap Effective Introduction,figuresofmerit,andgeneralizedcrossconstellations, IEEE p Rate Rate Gain tocap. Gain J.Sel.AreasCommun.,vol.7,no.6,pp.877–892,Aug.1989. 7 2/3 1.871 0.817 0.331 0.485 [7] G. D. Forney, “Multidimensional constellations – Part II: Voronoi con- 7 3/4 2.105 0.982 0.428 0.553 stellations,” IEEE J. Sel. Areas Commun., vol. 7, no. 6, pp. 941–958, 7 4/5 2.245 1.105 0.546 0.559 Aug.1989. 7 17/20 2.386 1.283 0.753 0.530 [8] A.R.CalderbankandL.H.Ozarow,“Non-equiprobablesignalingonthe 7 9/10 2.526 1.588 1.133 0.455 Gaussianchannel,”IEEETrans.Inf.Theory,vol.36,no.4,pp.726-740, 7 19/20 2.666 2.232 1.916 0.316 Jul.1990. 13 2/3 2.466 0.997 0.346 0.651 [9] P.Fortier,A.Ruiz,andJ.M.Cioffi,“Multidimensionalsignalsetsthrough 13 3/4 2.775 1.129 0.376 0.753 the shell construction for parallel channels,” IEEE Trans. Commun., 13 4/5 2.960 1.214 0.443 0.771 vol.40,no.3,pp.500–512, Mar.1992. 13 17/20 3.145 1.328 0.593 0.735 [10] G.D.Forney,“Trellisshaping,”IEEETrans.Inf.Theory,vol.38,no.2, 13 9/10 3.330 1.549 0.915 0.633 pp.281–300, Mar.1992. 13 19/20 3.515 2.096 1.658 0.438 [11] A.K.KhandaniandP.Kabal,“Shapingmultidimensionalsignalspaces – Part 1. Optimum shaping, shell mapping,” IEEE Trans. Inf. Theory, vol.39,no.6,pp.1799–1808, Nov.1993. TABLE I: Signal-to-noise ratio gain (dB) of probabilistic [12] R. Laroia, N. Farvardin, and S. A. Tretter, “On optimal shaping of shaping via time sharing for 7-ASK and 13-ASK. multi-dimensionalconstellations,”IEEETrans.Inf.Theory,vol.40,no.4, pp.1044–1056, Jul.1994. [13] G. D.Forney, M. D.Trott, andS.-Y. Chung, “Sphere-bound-achieving For probabilistic amplitude shaping via time sharing, cosetcodesandmultilevelcosetcodes,”IEEETrans.Inf.Theory,vol.46, signal-to-noise ratio gaps and gains are presented in Table I no.3,pp.820–850,May2000. [14] U.Erez,S.Litsyn,andR.Zamir,“Latticeswhicharegoodfor(almost) for different values of the coding rate R . As discussed in c everything,” IEEE Trans. Inf. Theory, vol. 51, no. 10, pp. 3401-3416, Section III, the effective gain due to shaping decreases at Oct.2005. very high rate. A coding rate around 4/5 yields the highest [15] N. di Pietro and J. Boutros, “Leech constellations of construction-A lattices,” Sub. to IEEETrans. Commun., Jan. 2017, [Online]. Available: effective gain. One of our perspectives is to analytically http://arxiv.org/pdf/1611.04417v2.pdf. determine the optimal coding rate (or its range) from (10). [16] R.G.Gallager,Low-DensityParity-Checkcodes.Cambridge,MA:MIT Tables II includes results for CQAM shaping. As suggested Press,1963. [17] T.RichardsonandR.Urbanke,Moderncodingtheory.Cambridge,U.K: in the previoussection, CQAM radii are stretched to improve CambridgeUniv.Press,2008. the range forPMB(ν,x). Here, radiusρi of shell i is taken to [18] C. Ling and J. C. Belfiore, “Achieving AWGN channel capacity with be 1+(ρ 1)((i 1)/(p 1))β where ρ >ρ ( ). lattice Gaussian coding,” IEEE Trans. Inf. Theory, vol. 60, no. 10, max max out − − − ∞ pp.5918–5929, Oct.2014. At R = 2/3, optimized parameters are ρ = 4.8 and c max [19] M. Mondelli, S. H. Hassani, and R. Urbanke, “How to achieve the β = 0.76 for 72-CQAM and ρmax = 6.0 and β = 0.80 for capacityofasymmetricchannels,”inProc.AllertonConf.Commun.Con- 132-CQAM. Square (p-ASK)2 constellations are not valid trolComput.,Oct.2014,pp.789796. [20] G. Kramer, “Probabilistic amplitude shaping applied to fiber-optic for full PAS because they require time sharing, however we communication systems,” in Proc. Int. Symp. on Turbo Codes and It- added them for comparisonpurpose.Shaping with 72-CQAM erative Inf.Proc.,Oct.2016. and 132-CQAM is about 0.1 dB from the additive white [21] M. Lentmaier, A. Sridharan, D. J. Costello, and K. S. Zigangirov, “Iterative decoding threshold analysis for LDPC convolutional codes,” Gaussian noise channel capacity. IEEETrans.Inf.Theory,vol.56,no.10,pp.5274–5289, Oct.2010. [22] E. Arikan, “Channel polarization: a method for constructing capacity- achievingcodesforsymmetricbinary-inputmemorylesschannels,”IEEE Constellation TargetRate Pot.Gain Gap Fullshaping Trans.Inf.Theory,vol.57,no.7,pp.3051–3073, Jul.2009. (7-ASK)2 1.871 0.817 0.098 No [23] S. Kudekar, T. Richardson and R. Urbanke, “Spatially coupled en- 72-CQAM 1.871 0.744 0.101 Yes sembles universally achieve capacity under belief propagation,” IEEE (13-ASK)2 2.466 0.998 0.036 No Trans.Inf.Theory,vol.59,no.12,pp.7761–7813, Dec.2013. 132-CQAM 2.466 1.092 0.088 Yes [24] C.R.P. Hartmann and L.D. Rudolph, “An optimum symbol-by-symbol decoding ruleforlinear codes,”IEEETrans.Inf.Theory,vol.22,no.5, pp.514-517,Sep.1976. TABLEII: Gain(dB)offullprobabilisticshapingforcircular [25] J. Boutros, A. Ghaith, and Y. Yuan-Wu, “Non-binary adaptive LDPC constellations 72-CQAM and 132-CQAM at R =2/3. codes for frequency selective channels: code construction and iterative c decoding,” inProc.IEEEInf.TheoryWorkshop, pp.184-188, Chengdu, Oct.2006. [26] M.P. Yankov, D. Zibar, K.J.Larsen, L.P.B.Christensen, and S. Forch- REFERENCES hammer,“ConstellationShapingforFiber-OpticChannelswithQAMand High Spectral Efficiency,” IEEEPhoton. Technol. Lett., vol. 26, no. 23, [1] G. Bo¨cherer, F. Steiner, and P. Schulte, “Bandwidth efficient and pp.2407–2410, Dec.2014. rate-matched Low-Density Parity-Check coded modulation,” IEEE [27] F. Buchali, G. Bo¨cherer, W. Idler, L. Schmalen, P. Schulte, F. Steiner, Trans.Commun.,vol.63,no.12,pp.4651–4665, Dec.2015. “Experimental Demonstration ofCapacity Increase andRate-Adaptation [2] P.SchulteandG.Bo¨cherer,“Constantcompositiondistributionmatching,” byProbabilistically Shaped64-QAM,”inProc.ECOC,Aug.2015. IEEETrans.Inf.Theory,vol.62,no.1,pp.430–434, Jan.2016.

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