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(IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 Performance of Iterative Concatenated Codes with GMSK over Fading Channels Labib Francis Gergis Misr Academy for Engineering and Technology Mansoura, Egypt IACSIT Senior Member, IAENG Member Abstract-Concatenated continuous phase achievable data rates obtained using codes modulation (CCPM) facilitates powerful of a manageable decoding complexity. error correction. CPM also has the However, a novel approach to error advantage of being bandwidth efficient and control coding revolutionized the area of compatible with non-linear amplifiers. coding theory. The so-called turbo codes Bandwidth efficient concatenated coded [1,2], almost completely closed the gap modulation schemes were designed for between the theoretical limit and the data communication over Additive White rate obtained using practical Gaussian noise (AWGN), and Rayleigh implementations. Turbo codes are based on fading channels. An analytical bounds on concatenated codes (CC's) separated by the performance of Serial (SCCC), and interleavers. The concatenated code can be Parallel convolutional concatenated codes decoded using a low-complexity iterative (PCCC) were derived as a base of decoding algorithm [3]. Given certain comparison with the third category known conditions, the iterative decoding algorithm as hybrid concatenated convolution codes performs close to the fundamental Shannon scheme (HCCC). An upper bound to the capacity. In general, concatenated coding soft-input, soft-output (SISO) maximum a provides longer codes yielding significant posteriori (MAP) decoding algorithm performance improvements at reasonable applied to CC's of the three schemes was complexity investments. The overall obtained. Design rules for the parallel, decoding complexity of the iterative outer, and inner codes that maximize the decoding algorithm for a concatenated code interleaver's gain were discussed. Finally, a is lower than that required for a single code low complexity iterative decoding algorithm of the corresponding performance that yields a better performance is The parallel, serial, and hybrid proposed. concatenation of codes are well established as a practical means of achieving excellent key words: Concatenated codes, continuous performance. Interest in code concatenation phase modulation, GMSK, uniform has been renewed with the introduction of interleaved coding, convolutional coding, turbo codes [4,5,6,7]. These codes perform iterative decoding well and yet have a low overall decoding complexity. CPM is a form of constant-envelope I. INTRODUCTION digital modulation and therefore of interest for use with nonlinear and/ or fading The channel capacity unfortunately only channels. The inherent bandwidth- and states what data rate is theoretically possible energy efficiency makes CPM a very to achieve, but it does not say what codes to attractive modulation scheme [8]. use in order to achieve an arbitrary low bit Furthermore, CPM signals have good error rate (BER) for this data rate. spectral properties due to their phase Therefore, there has traditionally been a continuity. Besides providing spectral gap between the theoretical limit and the economy, CPM schemes exhibit a “coding gain” when compared to PSK modulation. 76 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 This “coding gain” is due to the memory where Eb, is the energy per symbol interval, that is introduced by the phase-shaping T is the duration of the symbol interval, fc, is filter and the decoder can exploit this. CPM the carrier frequency, and Ф(t+α) is the modulation exhibits memory that resembles "phase function" responsible for mapping in many ways how a convolutionally the input sequence to a corresponding phase encoded data sequence exhibits memory - in wavefom. both cases, a “trellis” can be used to display The term α = {αi} is the input sequence the possible output signals (this is why taken from the M-ary alphabet ±l, ±3, . . . , convolutional encoders are used with CPM ± M - 1. For convenience the focus here will in this paper. be on the binary case, αi є {±1}. This paper is organized as follows. The "continuous phase" constraint in Section II briefly describes continuous CPM requires that the phase function phase modulation, using Gaussian minimum maintain a continuous amplitude. In general shift keying GMSK, and how it can be the phase function is given by separated into a finite-state machine and a memoryless signal mapper. Section III N describes in details the system model and Ф(t+α) = 2 π Σα n δn g( t – n T ) encoder structure of serial, parallel, and n=0 hybrid concatenated codes. (2) Section IV derives analytical upper where δ is the modulation index, and g(t) is bounds to the bit-error probability of the the phase pulse. The phase pulse g(t) is three concatenated codes using the concept typically specified in terms of a normalized, of uniform interleavers that decouples the time-limited frequency pulse f(t) of duration output of the outer encoder from the input LT such that: of the inner encoder, from the knowledge of the input–output weight coefficients (IOWC), Acw,h, for CC's. Acw,h is represented related to the type of 0 ; if t < 0 concatenation. The choice of decoding t algorithm and number of decoder g(t) = ∫ f(τ)dτ ; if 0 < t < LT iterations is described in section V. 0 Factors that affect the performance are discussed in section VI. Finally conclusion 1/2 ; if t > LT results for some examples described in (3) section IV have been considered in section VII. The duration term (LT) is specified in terms of the bit duration T, and identifies the number of bit durations over which the II. GMSK SYSTEM MODEL frequency pulse f (t) is non-zero, δ = 1/2, and the frequency pulse is Gaussian minimum-shift keying is a special case of a more genet-ic class of modulation schemes known as continuous f(t)= (1/2T) Q 2πB (t -τ/2)/ √ ln 2 - phase modulation (CPM). In CPM schemes, the signal envelope is kept constant and the phase varies in a continuous manner. This Q 2πB (t+τ/2)/ √ ln 2 ensures that CPM signals do not have the high-frequency components associated with (4) sharp changes in the signal envelope and B is a parameter in GMSK which controls allows for more compact spectra. CPM the amount of bandwidth used as well as the signal s(t ) can be written [8,9] severity of the intersymbol interference, the B parameter is expressed in terms of the S(t) = (√2Eb/T) cos [2πfct + Ф(t+α) ] (1) inverse of the bit duration T. 77 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 III. PERFORMANCE ANALYSIS OF It is clear from equation (8) that BER COCATENATED CODES depends on major factors like signal-to- noise ratio per bit, and the input–output weight coefficients (IOWC), Acw,h for the Consider a linear (n,k) code C with code code, Acw,h is represented related to the type rate Rc = k/n and minimum distance hm. An of concatenation. upper bound on the bit-error rate [BER] of The average IOWC for λ concatenated the code C over memoryless binary-input codes with λ -1 interleavers can be obtained channels, with coherent detection, using by averaging (5) over all over all possible maximum likelihood decoding, can be interleavers. This average is obtained by obtained as [4] replacing the actual ith interleaver (i = 1, 2, … , λ-1), that performs a permutation of the n k Ni input bits, with an abstract interleaver BER ≤ Σ Σ (w/k) Acw,h D(Rc Eb / No , h) called uniform interleaver defined as a h=dmin w=1 probabilistic device that maps a given input (5) word of weight w into all distinct Ni w where Eb/No is the signal-to-noise ratio per permutations of it with equal probability bit, and Acw,h for the code C represents the ψ = 1 / Ni . number of codewords of the code with w output weight h associated with an input sequence of weight w. Acw,h is the input– output weight coefficient (IOWC).The IV. DESIGN OF CONCATENATED function D(.) represents the pairwise error CODES probability which is a monotonic decreasing function of the signal to noise ratio and the Concatenated codes represent a more output weight h. For AWGN channels we recent development in the coding research have D(Rc Eb / No , h) = Q( √ 2Rc h Eb / No ). field [1], which has risen a large interest in For fading channels, assuming coherent the coding community. detection, and perfect Channel State information (CSI), the fading samples μi are IV. 1. Design of Parallel Concatenated i.i.d. random variables with Rayleigh Convolutional Codes ( PCCC ) density of the form f(μ)= 2μe-μ2. The conditional pairwise error probability is The first type of concatenated codes is given by parallel concatenated convolutional codes h (PCCC) whose encoder is formed by two (or D(Rc Eb No , h│μ) = Q (2Rc h Eb / No Σ μ2i ) more) constituent systematic encoders joined i=1 through one or more interleavers. The input information bits feed the first encoder and, (6) after having been scrambled by the where Q function can be defined as interleaver, they enter the second encoder. A codeword of a parallel concatenated code Q(x) ≤ (1/2) e – x2 / 2 (7) consists of the input bits to the first encoder followed by the parity check bits of both By averaging the conditional bit error encoders. As shown in Fig. 1, the structure rate over fading using (5), (6), and (7). The of PCCC consists of convolutional code C1 upper bound for BER is represented by with rate R1p = p/q1 , and convolutional code n k C2 with rate R2p = p/q2, where the BER ≤ 0.5 Σ Σ (w/k) A c w,h . constituent code inputs are joined by an h=hm w=1 interleaver of length N, generating a PCCC, Cp, with total rate Rp. The output codeword [1/(1+Rc Eb / No)]h length n = n1 + n2 [4]. (8) 78 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 input data nM C1 n1 Acw,h ≈ Σ ( Nj / j! p! ) Acw,h,j j=1 to Modulator interleaver (12) Length = N Inserting (12) into (9), we obtain the input–output weight coefficients (IOWC), C2 n2 Acpw,h, for PCCC as [4] N/p N /p Fig. 1. Parallel Concatenated nmax nmax n1 n2 Convolutional Code ( PCCC ) A cp w,h ≈ Σ Σ N : n1=1 n2 =1 w The input–output weight coefficients c1 c2 (IOWC), Acpw,h, for PCCC can be defined as .A w,h,n1 A w,h,n2 [3] nmax nmax A c1 w,h1 x A c2 w,h2 ≈ Σ Σ w! Acpw,h = Σ Acpw,h1,h2 = Σ n1=1 n2 =1 N pn1+n2 n1! . n2 ! h1,h2 : h1,h2 : w h1+h2=h h1+h2=h (9 ) . Nn1+n2-w . Ac w,h,n Ac w,h,n 1 1 2 2 (13) where Acpw,h1,h2 is the number of codeword of the PCCC with output weights h1, and h2 associated with an input sequence of weight w. IV. 2. Design of Serially Concatenated Let Acw,h.j be the IOWC given that the Convolutional Codes ( SCCC ) convolutional code generates j error events with total input w, and output weight h. The Another equally powerful code Acw,h.j actually represents the number of configuration with comparable performance sequences of weight h, input weight w, and to parallel concatenated codes is serially the number of concatenated error events j concatenated convolutional codes (SCCC). without any gap between them, starting at The structure of a serially concatenated the beginning of the code. For N much convolutional code (SCCC) is shown in Fig. larger than the memory of the convolutional 2. It refers to the case of two convolutional code, the coefficient of the equivalent code CCs, the outer code Co with rate Roc = k/p, can be approximated by and the inner code Ci with rate Ric = p/n, joined by an interleaver length N bits, nM N/p generating an SCCC with rate Rc = k/n. A w,h ≈ c Σ j Acw,h,j j=1 outer Code interleaver inner Code (10) Ci length = N Co where nM, the largest number of error events concatenated in a codeword of weight Fig. 2. Serially Concatenated h and generated by a weight w input Convolutional Code ( SCCC ) sequence, is a function of h and w that depends on the decoder. From the knowledge of the IOWC of outer and inner codes, which called Aco(w,L) N and Aci(l,H). Exploit the properties of the j ≈ Nj / j! (11) uniform interleaver, which transforms a codeword of weight l at the output of the Substitution of this approximation in (10) outer encoder into all its distinct N Yields permutations. l 79 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 As a consequence, each codeword of the outer code Co of weight l, through the action of the uniform interleaver, enters the inner encoder generating N codewords of Interleaver π1 Parallel n1 the inner code Ci. l length = N1 Encoder Thus, the IOWC of the SCCC scheme, TO CHANNEL Acsw,h ,of codewords with weight h associated with an input word of weight w is given by Outer Interleaver π2 Inner n2 Encoder length = N2 Encoder N i/p Acsw,h = Σ Acow,l Χ Acil,h Fig. 3. Hybrid Concatenated l=0 Convolutional Code ( HCCC ) N l (14) Using the previous result of (12) with j=ni for the inner code, and the analogus one, j=no, for the outer code. composed of three concatenated codes, the parallel code Cp with rate Rpc = kp/np, the no M N/p outer code Co with rate Roc = ko/po, and the Acow,l ≈ Σ o no Aow,l,no inner code Ci with rate Ric = pi/ni , with two interleavers N1 and N2 bits long. Generating n =1 (15) an HCCC CH with overall rate RH. For Substituting (15) into (14) defines Acsw,h for simplicity, assuming kp = ko and po = pi = p, SCCC in the form then RH = ko / ( np + ni ). N/p N/p Since the HCCC has two outputs, the N nmax nmax n1 n2 upper bounds on the bit error probability in (8) can be modified to Acs w,h ≈ Σ Σ Σ N :l=dof no=1 ni=1 l n1 n2 k o i BER ≤ Σ Σ Σ (w/k) . ACHw,h1,h2 . A w,l,no A l,h,ni h=h p h= h i w=wm (16) where dof is the free distance of the outer . Q [ √ 2RH (h1 + h2 ) (Eb / No) ] code. Inserting the approximation (11) in (16) yields (18) N nom nim where ACHw,h1,h2 for the HCCC code Acsw,h ≈ Σ Σ Σ l! represents the number of codewords with l=dof no=1 ni=1 output weight h1 for the parallel code and pno+ni . no ! . ni ! output weight h2 for the inner code, associated with an input sequence of weight . Nno+ni . Aow,l,n Ail,h,n o i w, ACHw,h1,h2 is the IOWC for HCCC, wm is the (17) minimum weight of an input sequence generating the error events of the parallel code and the outer code, hp is the minimum IV. 3. Design of Hybrid Concatenated weight of the codewords of Cp, and hi is the minimum weight of the codewords of Ci . Convolutional Codes ( HCCC ) With knowledge of the IOWC ACpw,h1 for the constituent parallel code, the IOWC ACow,l for the constituent outer code, and the The structure of a hybrid concatenated IOWC ACil,h2 for the constituent inner code, convolutional code is shown in Fig. 3. It is 80 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 using the concept of the uniform interleaver, and Rayleigh fading channels with GMSK the ACHw,h1,h2 for HCCC can be obtained. modulation scheme, using interleaver of lengths N = 100, 1000, and 2000 bits. N2 Acpw,h1 x Acow,l x Acil,h2 ACHw,h1,h2 = Σ 1.e-1 l=0 N1 N1 1.e-2 w l 1.e-3 (19) 1.e-4 1.e-5 ACHw,h can be obtained by summing ACHw,h1,h2 overall h1, and h2 such that 1.e-6 BER Co h1+h2=h. A w,l is the number of codewords 1.e-7 of Co of weight l given by the input 1.e-8 sequences of weight w. Analogous 1.e-9 definitions apply for Acpw,h1 and Acil,h2. 1.e-10 N = 100 1.e-11 N = 1000 1.e-12 N = 2000 V. EXAMPLES CONFIRMING THE DESIGN OF CONCATENATED 1.e-13 1 2 3 4 5 6 7 8 9 CODES RULES Eb / No dB To obtain the design rules obtained Fig. 4. Analytical bounds for PCCC with asymptotically, for different signal-to-noise GMSK Modulation Scheme through different ratios and large interleaver lengths, N, the interleaver lengths upper bounds for (8) to BER for several types of the concatenated codes were evaluated, with different interleaver lengths, 2. Serially Concatenated and compare their performances with those Convolutional Codes (SCCC) predicted by the design guidelines. Consider a rate 1/3 SCCC using as outer 1. Parallel Concatenated code a convolutional encoder Co with rate Convolutional Codes (PCCC) Roc = 1/2, and the inner code Ci with rate Ric = 2/3, joined by an uniform interleaver of length N = 100, 1000, and 2000 bits, as Consider a PCCC with overall rate = 1/3, shown in Fig. 2. Using the previously formed by two convolutional codes, C1, and analysis for SCCC that defined in (8), and C2, have equal rate = 1/2, linked through an (17), we obtained the bit-error probability uniform interleaver with length N, and bounds illustrated in Fig. 5. The whose encoder is shown in Fig. 1. We have performance was obtained over AWGN, constructed different PCCCs through and Rayleigh fading channels with GMSK interleavers of various lengths, and passed modulation scheme. through the previous steps to evaluate their performance with GMSK modulator. Upper bounds to the error probability based on the union bound described in(8), and (13) present a divergence at low values of signal-to-noise ratio. Fig. 4. shows the bit error probability of a PCCC over AWGN, 81 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 1.e-1 1.e-1 1.e-2 1.e-2 1.e-3 1.e-3 1.e-4 1.e-4 1.e-5 1.e-5 1.e-6 1.e-7 1.e-6 1.e-8 1.e-7 1.e-9 BER 1.e-10 1.e-8 BER 1.e-11 1.e-9 1.e-12 1.e-13 1.e-10 1.e-14 1.e-11 1.e-15 1.e-16 1.e-12 N = 100 1.e-17 1.e-13 N = 1000 1.e-18 N = 100 1.e-14 1.e-19 N = 1000 N = 2000 1.e-20 N = 2000 1.e-15 1.e-21 1 2 3 4 5 6 7 8 1 2 3 4 5 6 7 8 Eb / No dB Eb / No dB Fig. 5. Analytical bounds for SCCC with Fig. 6. Analytical bounds for HCCC with GMSK Modulation Scheme through GMSK Modulation Scheme through different interleaver lengths different interleaver lengths 3. Hybrid Concatenated VI. ITERATIVE DECODING OF Convolutional Codes (HCCC) CONCATENATED CODES Maximum-likelihood (ML) decoding of SCCC, Consider a rate 1/4 HCCC formed by a PCCC, and HCCC with large N is an almost parallel systematic convolutional code with rate complex and impossible achievement. To acquire 1/2, an outer four convolutional code with rate a practical significance, an iterative algorithm 1/2, and an inner convolutional code with rate consists of a soft-input, soft-output (SISO) 2/3, joined by two uniform interleavers of maximum a posteriori (MAP) decoding algorithm length N1 = N and N2 = 2N, where N=100, 1000, applied to CC's [10], [11], and [12]. A functional and 2000 bits, as shown in Fig. 3. Using (8), and diagram of the iterative decoding algorithm for (18) we have obtained the bit error probability PCCC, SCCC, and HCTC are illustrated in curves over AWGN, and Rayleigh fading figures 7, 8, and 9, respectively. channels with GMSK modulation scheme, shown in Fig. 6. from Demodulator MAP not used SISO C1 π MAP SISO C2 π-1 Fig. 7. Iterative decoding algorithm for PCCC 82 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 from Demodulator 1.e-1 MAP not used to Decision 1.e-2 N = 1000 SISO 1.e-3 inner Ci π-1 MAP 1.e-4 SISO 1.e-5 outer Co 1.e-6 1.e-7 1.e-8 1.e-9 1.e-10 BER π 1.e-11 1.e-12 Fig. 8. Iterative decoding algorithm for 1.e-13 SCCC 1.e-14 1.e-15 No iteration from Demodulator 1.e-16 iteration = 2 1.e-17 iteration = 3 1.e-18 iteration = 4 MAP SISO 1.e-19 iteration = 5 inner π2-1 1.e-20 MAP 1 2 3 4 5 6 7 8 SISO Eb / No dB outer Fig. 10. Analysis of Iterative decoding algorithm π2 for 1/3 PCCC with different No of to decision iterations 1.e-1 MAP 1.e-2 N = 1000 SISO 1.e-3 π1 parallel π1-1 1.e-4 1.e-5 1.e-6 1.e-7 1.e-8 Fig. 9. Iterative decoding algorithm for 1.e-9 1.e-10 HCCC 1.e-11 1.e-12 BER 1.e-13 VI . THE EFFECT OF VARIOUS 1.e-14 PARAMETERS ON THE 1.e-15 1.e-16 PERFORMANCE OF 1.e-17 CONCATENATED CODES 1.e-18 No iteration 1.e-19 1.e-20 iteration = 2 1.e-21 The performances of concatenated codes 1.e-22 iteration = 3 were evaluated and analyzed in the previous 1.e-23 iteration = 4 sections. There are many parameters which 1.e-24 iteration = 5 1.e-25 affect the performance of CC's when 1 2 3 4 5 6 7 8 decoded with iterative decoder over AWGN Eb / No dB and Rayleigh fading channels. It is shown, briefly, the effect of the interleavers lengths, and the number of decoding iterations. Fig. 11. Analysis of Iterative decoding algorithm for 1/3 SCCC with different No of iterations 83 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 1.e-1 1.e-2 1.e-3 N = 1000 VII . CONCLUSIONS 1.e-4 1.e-5 1.e-6 1.e-7 A construction of concatenated codes 1.e-8 1.e-9 CC's have presented and constructed in this 1.e-10 paper with three main basic schemes: 1.e-11 1.e-12 PCCC, SCCC, and HCCC, over AWGN 1.e-13 and Rayleigh fading channels. The effects of BER 1.e-14 1.e-15 various parameters on the performance of 1.e-16 CC's, using an upper bound to the soft- 1.e-17 input, soft-output (SISO) maximum a 1.e-18 1.e-19 posteriori (MAP) decoding algorithm are 1.e-20 investigated. These parameters are : the 1.e-21 No iteration 1.e-22 iteration = 2 interleaver length, and the number of 1.e-23 iterations. The analytical results showed 1.e-24 iteration = 3 1.e-25 iteration = 4 that coding gain was improved by 1.e-26 iteration = 5 increasing the interleaver length, and the 1.e-27 number of iterations. 1 2 3 4 5 6 7 8 Eb / No dB Fig. 12. Analysis of Iterative decoding algorithm REFERENCES for 1/4 HCCC with different No of iterations [1] N. Sven, " Coding and A. The effect of interleaver length Modulation for Spectral Efficient Transmission ", PhD dissertation .. It is well known that a good interleaving Institute of Telecommunications of the affects the CC's error performance University of Stuttgart, 2010. considerably. Figures 4, 5, and 6 represent [2] Z. Chance, and D. Love, " the BER of PCCC, SCCC, and HCCC, Concatenated Coding for the AWGN respectively, versus the interleaving length, Channel with Noise Feedback ", N. From these figures, it is shown that BER School of Electrical and Computer improve with increasing the length of Engineering, Purdue University, West interleaver. Lafayette, USA, 2010. [3] E. Lo, and K. Lataief, " Cooperative Concatenated Coding for Wireless B. The effect of number of decoder Systems", Proceeding of IEEE iterations Communication Society, 2007. [4] B. Cristea, " Viterbi Algorithm for The choice of decoding algorithm and Iterative Decoding of Parallel number of decoder iterations also influences Concatenated Convolutional Codes ", 18th performance. A functional diagrams of the European Signal Processing (EUSIPCO), iterative decoding algorithm for CC's were Aalborg, Denmark, August 2010. presented in figures 7, 8, and 9 for PCCC, [5] R. Maunder, and L. Hanzo, " Iterative SCCC, and HCCC, respectively. It could be Decoding Convergence and Termination observed, from figures 10, 11, and 12, that of Serially Concatenated Codes ", IEEE the slope of curves and coding gain are Transactions on Vehicular Technology, improved by increasing the number of VOL. 59, NO. 1, January 2010. iterations. 84 http://sites.google.com/site/ijcsis/ ISSN 1947-5500 (IJCSIS) International Journal of Computer Science and Information Security, Vol. 9, No. 1, January 2011 [6] C. Koller, A. Amat, Kliewer, F. Vatta, and D. Costello, " Hybrid Concatenated Codes with Asymptotically Good Distance Growth ", Proceeding of 5th International Symposium on Turbo Codes and Related Topics, 2008. [7] N. Wahab, I. Ibrahim, S. Sarnin, and N. Isa, Performance of Hybrid Automatic Repeat Request Scheme with Turbo Codes ", Proceeding of the International Multi Conference of Engineering and Computer Scientists (IMECS), VOL. II, Hong Kong, March 2010. [8] K. Damodaran, " Serially Concatenated Coded Continuous Phase Modulation for Aeronautical Telemetry ", Master of Science thesis, Department of Electrical Engineering, Faculty of the Graduate School of the University of Kansas. August 2008. [9] A. Perotti, P. Remlein, and S. Benedetto , " Adaptive Coded Continuous-Phase Modulations for Frequency-Division Multiuser Systems ", Advances in Electronics and Telecommunications, VOL. 1, NO. 1, April 2010. [10] M. Lahmer, and M. Belkasmi, " A New Iterative Threshold Decoding Algorithm for one Step Majority Logic Decodable Block Codes ", International Journal of Computer Applications, Volume 7, No. 7, October 2010. [11] F. Ayoub, M. Lahmer, M. Belkasmi, and E. Bouyakhf, " Impact of the Decoder Connection Schemes on Iterative Decoding of GPCB Codes ", International Journal of Information and Communication Engineering, VOL. 6, No. 3, 2010. [12] A. Farchane, and M. Belkasmi , " Generalized Serially Concatenated Codes; Construction and Iterative Decoding ", International Journal of Mathematical and Computer Sciences, VOL. 6, No. 2, 2010. 85 http://sites.google.com/site/ijcsis/ ISSN 1947-5500

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The International Journal of Computer Science and Information Security (IJCSIS) is a reputable venue for publishing novel ideas, state-of-the-art research results and fundamental advances in all aspects of computer science and information & communication security. IJCSIS is a peer reviewed international journal with a key objective to provide the academic and industrial community a medium for presenting original research and applications related to Computer Science and Information Security.
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