New binary particle swarm optimization on dummy sequence insertion method for nonlinear reduction in optical direct detection orthogonal frequency division multiplexing system

New binary particle swarm optimization on dummy sequence insertion method for nonlinear reduction in optical directdetection orthogonal frequency division multiplexing system Lap Maivan & Thang Nguyentrong Journal of Optics ISSN 0972-8821 J Opt DOI 10.1007/s12596-019-00512-6 23 Your article is protected by copyright and all rights are held exclusively by The Optical Society of India This e-offprint is for personal use only and shall not be self-archived in electronic repositories If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website The link must be accompanied by the following text: "The final publication is available at link.springer.com” 23 Author's personal copy J Opt https://doi.org/10.1007/s12596-019-00512-6 RESEARCH ARTICLE New binary particle swarm optimization on dummy sequence insertion method for nonlinear reduction in optical directdetection orthogonal frequency division multiplexing system Lap Maivan1 • Thang Nguyentrong2 Received: 28 June 2017 / Accepted: 22 January 2019 Ó The Optical Society of India 2019 Abstract In the paper, a novel new binary particle swarm optimization method based on dummy sequence insertion is proposed and experimentally demonstrated in the IM-DD optical orthogonal frequency division multiplexing (OOFDM) system This technique can mitigate nonlinearity of OOFDM system without any channel side information Experimental results demonstrate that compared to the original scheme, the improvement in the receiver sensitivity by the proposed scheme is 1.9 dB and 3.2 dB with launch powers of dBm and dBm, respectively, at the BER of FEC 3.8 10-3 after transmission over 100-km standard single-mode fiber At a complementary cumulative distribution function of 10-4, the PAPR of OFDM signal can be reduced about 2.8 dB by using the proposed scheme, while the receiver-side hardware is the same as the origin Keywords Particle swarm optimization (PSO) Á Dummy sequence insertion (DSI) Á Optical fiber communication Á Orthogonal frequency division multiplexing (OFDM) & Lap Maivan lapmv@hpu.edu.vn Thang Nguyentrong nguyentrongthang@tlu.edu.vn Electronic and Electrical Engineering Department, Haiphong Private University, Haiphong 180000, Vietnam Faculty of Energy Engineering, Thuyloi University, Hanoi 115070, Vietnam Introduction Recently, orthogonal frequency division multiplexing (OFDM) has been applied in optical communication system [1–5] Due to the high PAPR of OFDM, nonlinearity noise in the nonlinear optical components (such as Mach– Zehnder modulator, fiber, etc.) will cause performance degradation in optical communication system Therefore, reduction in PAPR of OFDM is very necessary in optical OFDM system Many methods have been paid more attention, such as selective mapping (SLM), partial transmitting sequence (PTS), clipping, companding transform technique, precoding, spreading codes, and dummy sequence insertion (DSI) However, the SLM [6] and the PTS [7] methods will increase the amount of computation at the transmitter and receiver The clipping [8] could be an effective technique for PAPR reduction The OFDM signal can be clipped either at the Nyquist sampling rate or at an oversampling rate Clipping the Nyquist sampled signal does not cause out-of-band noise, since all the noise generated by clipping falls in-band Clipping an oversampled signal produces less in-band noise, but the out-of-band noise will increase, it generally causes the out-of-band radiation of the clipped power, and the bandpass filter is required to suppress the out-of-band radiation The problem of this scheme is the significant PAPR regrowth due to the bandpass filtering The companding transform technique [9, 10] has the advantages of simple implementation and low computational complexity, and it has better performance than clipping method In the OFDM system, to reduce the PAPR of an OFDM signal, the ideal case is to make the envelope of the OFDM signal constant However, it is difficult to implement the ideal case by the available companding transform techniques due to the limitation of the BER [11] In addition, precoding [5] and spreading 123 Author's personal copy J Opt codes [4] can also reduce the PAPR and improve BER performance, but at the receiver, de-precoding or despreading process must be done The DSI [12, 13] method can be used to insert dummy sequence into the transmission data block for PAPR reduction before the IFFT stage In the DSI method [12], complementary sequence and combination of the correlation sequence are considered as dummy sequence, which will be discarded at the receiver; thus, the side information is not necessary Moreover, compared with the conventional PTS or SLM method, the BER performance of the method is better in the case of the errors in the side information about the phase rotation But, the only limitation is that the computation is high In order to solve complex computation problems, various heuristic approaches have been adopted by researches, such as genetic algorithm, tabu search and PSO PSO [14, 15] is one of the optimization techniques The origin version of the PSO [14] operates in continuous space, and the binary PSO (BPSO) [15] operates on discrete binary variables The PSO technique has been used in many fields; one of them was used for PAPR reduction in wireless OFDM system [13, 16, 17] During utilization and research PSO and BPSO, some researches have shown that standard PSO and BPSO cannot converge well [18] To overcome this problem with BPSO, a novel NBPSO [18] is proposed In this paper, a novel NBPSO based on DSI method is proposed and experimentally demonstrated for PAPR reduction in the IM-DD optical OFDM system The NBPSO scheme can assign a suboptimal dummy sequence to enhance the performance of the DSI method so as to reduce the PAPR of the IM-DD OOFDM system CCDF ẳ pPAPR [ PAPR0ị: In the OFDM system, the baseband OFDM signal is given by ð1Þ The DSI method [18] can reduce the PAPR by inserting a dummy sequence in the subcarriers of the OFDM system Dummy sequence is used for only PAPR reduction without any channel information At the receiver, dummy sequence can be discarded after FFT stage It is different from the conventional PTS and SLM methods Therefore, the DSI method can greatly reduce the complexity of the receiver And it is independent of the dummy sequence error Figure illustrates the structure of the DSI data In this paper, DSI with method of Ref [13] is used, and 16QAM format is considered Here, the total number of subcarriers in the OFDM signal is M, and the number of subcarriers reserved for the dummy sequence is L; therefore, there are N = M L subcarriers available for data transmission And the number of dummy sequence bit is K = 4xL In Fig 1, after the IFFT input, the output signal can be expressed as À Á ytị ẳ IFFT ẵx st ; 4ị where y = [y1, y2,…, yM]t, x = [x1, x2,…, xN]t is the transmission data sequence and s = [s1, s2,…, sL]t is the inserted dummy sequence IFFT (z) implies the inverse fast Fourier transform of z, and [•]t is a transpose operation The PAPR of the OFDM signal with DSI method can be defined as PAPR ẳ 10 log10 maxjytịj2 n o: mean jytịj2 2ị where E{ã} denotes the expectation operation E {|s(t)|2} is equal to the variance r2, and the symbols are zero mean The statistics for the PAPR of an OFDM signal can be given in terms of its complementary cumulative distribution function (CCDF) The CCDF of PAPR is defined as Fig DSI data block using the complementary sequence 123 ð5Þ Meanwhile, Eq (5) can be written in vector form and expressed in decibels as where x is the data symbol, Df is the carrier spacing of IFFT, and N is the number of subcarriers The PAPR of the OFDM signal can be defined as maxjstịj2 o; PAPR ẳ n E jsðtÞj2 ð3Þ Dummy sequence insertion method maxjyðtÞj2 o: PAPR ẳ n E jytịj2 System model N X N 1 X stị ẳ p xkị ej2p:i:Df :tị ; N kẳ0 iẳ0 the probability that the PAPR of the OFDM symbols exceeds a given threshold PAPR0 The CCDF for an OFDM signal is expressed as ð6Þ Author's personal copy J Opt The DSI method is used to search out the dummy sequence that minimizes the PAPR of an OFDM signal Based on Eq (6), the PAPR reduction using DSI method can be modeled as a constrained optimization problem It is given by Minimize PAPR subject to s; PL ð7Þ where PL is the total power limitation for the inserted dummy sequence Meanwhile, to search out the global optimal dummy sequence so as to minimize the PAPR of the optical OFDM signal, the NBPSO scheme is adopted in the optical OFDM system The fitness function in this case can be shown in Eq (7), and it can be expressed as f sị ẳ 10 log10 maxjytịj2 n o: mean jyðtÞj2 ð8Þ The NBPSO scheme based on DSI method is shown in Fig It will be described in detail as follows: Step Initialization state Firstly, the iteration counter t is reset, i.e., t = 0, and P particles are randomly generated as [Zj(0), j = 1, 2,…, P], where Zj(0) = [zj,1(0), zj,1(0),…, zj,K(0)]t, and zj,k(0) denotes the kth bit of jth particle at t = A vector of K bits represents the position of a particle and signifies a probably desired dummy sequence Then, the initial velocities of all particles are set to zero, such as [Vj(0), j = 1, 2,…, P] = 0, where Vj(0) = [vj,1(0), vj,2(0),…, vj,K(0)]t Secondly, modulate and evaluate the fitness function of each particle in the initial population based on Eq (8), and we set p_bestj = Zj(0) and Ffnj = Fj(0), j = 1, 2,…, P, where p_bestj = (p_bestj1, p_bestj2,…, p_bestjK) and Ffnj register the individual best position for the jth particle and its fitness value of the jth particle at t = Thirdly, we find the best fitness value Fbestfn= min([Ffnj, j = 1, 2,…, P]) registering the fitness values of all initial particles, and set the particle of Fbestfn as the global best g_best, which has an fitness value Fbestfn Finally, set the initial values of the inertia weight w and constants c1 and c2, which are used in velocity updating Step Iteration counter updating state Update the generation counter as t = t?1 Step Velocity updating state In the NBPSO scheme, each vjk represents the probability of bit zjk taking the value 1, and vjk must be constrained to the interval [0.0, 1.0] By defining a function S(vjk) of the kth element in the jth particle, it is updated according to the following equation: À À Á À Á Á S vjk ẳ 2x sigmoid vjk 0:5 ; 9ị with Sigmoidvjk ị ẳ 1ỵe1vjk , and vjk (t ? 1) = w.vjk(t) ? c1.rand().(p_bestjk – zjk) ? c2.rand().(g_bestk – zjk), where c1 and c2 are positive constants, rand() is a quasirandom number selected from a uniform distribution in [0.1, 1.0], w is the inertia weight, and vjk is limited in the range of [- vmax, vmax] Step Position updating state Based on the updated velocities, the position of each particle will be changed by the following equation: À Á If randị\S vjk t ỵ1ị then zjk t ỵ 1ị ẳ exchange zjk tị elsezjk t ỵ 1ị ¼ zjk ðtÞ: ð10Þ Step Individual best updating state Each particle is evaluated by fitness function on the renewed position If there is Fj(t) \ Ffnj, j = 1, 2,…, P, update individual best as P_bestj = Zj(t) and Ffnj = Fj(t) and go to the global best updating state Step Global best updating state Search for the minimum fitness value Fmin from Ffnj, j = 1, 2,,…, P, where is the index of particle with minimum fitness, i.e., {1, 2,…, P} If Fmin \ Fbestfn, then the global best is updated as g_best = Zmin(t) and Fbestfn = Fmin Step Stop criteria checking state If the stop criteria are satisfied, the procedure comes to a stop, or else goes to the Step In this paper, the use of global model in NBPSO is considered, and the parameters in Eq (9) are set as the same as Ref [18] Usually, vmax is set to be 6, c1 = c2 = 2, and the weight w is decreasing linearly from 0.6 to 0.2 The number of particle (NP) is 20, and the length of bit in each particle (P) is 32 The number of iteration (T) is considered to be 30, which is the stopping criteria ” NBPSO scheme based on the DSI method Fig NBPSO scheme based on the DSI method 123 Author's personal copy J Opt Figure shows the experimental setup of the NBPSO based on DSI method in the IM-DD optical OFDM system In this experiment, three types of signal are used, such as the original OFDM signal, the DSI method signal, and the NBPSO based on the DSI signal The number of OFDM subcarriers is 256 Among these subcarriers, 184 are used for data and 16 for dummy sequence insertion The length of CP is 1/8 of OFDM symbol duration corresponding to 32 samples in each OFDM symbol In the experiment, the number of OFDM symbols per frame is 256 and training sequence per OFDM frame is The pseudo-random binary sequence (PRBS) is converted into parallel data by S/P converter, and then the NBPSO based on DSI method is processed for PAPR reduction The algorithm of NBPSO includes a loop: a dummy sequence is added to the end of the each parallel data, and then they are mapped onto 16QAM After that, GI and Hermitian constraints are added Then, the data symbol is passed through the IFFT, and PAPR is calculated After the NBPSO method implemented, the signal with lowest PAPR is obtained A complex-valued time-domain waveform is produced; meanwhile, the CP is added to mitigate the ISI In addition, a training sequence (TS) can be used for channel estimation and symbol synchronization The electrical baseband OFDM signals are generated by offline MATLAB and uploaded into a commercial arbitrary waveform generator (AWG) A continuous-wave generated by an external cavity laser (ECL) at 1556.26 nm is fed into a MZM biased at 2.4 V, and the OFDM signals generated by an AWG are injected into the MZM to generate optical OFDM signals The PRBS length is 94208 The sampling rate of the AWG is G samples/s, and the peak-to-peak Fig Experimental setup for the IM-DD OFDM system with the NBPSO based on DSI method AWG arbitrary waveform generator, VOA variable optical attenuator, ECL external cavity laser, PC polarization controller, MZM Mach–Zehnder modulator, EDFA Erbium-doped fiber amplifier, PD photodiode, TDS real-time/digital storage oscilloscope, and LPF low-pass filter Experimental setup and results Experimental setup 123 Author's personal copy J Opt voltage of the signals is V The half-wave voltage of the MZM is V The driving amplitude (Vpp) of OFDM signals is V, and the output power of the ECL is 14.5 dBm The output power of optical OFDM signals is dBm The optical OFDM signals are amplified by the first EDFA (EDFA-1) before transmitting over 100-km SMF After transmission over 100-km SSMF, the second EDFA (EDFA-2) and a variable optical attenuator (VOA) are adopted for controlling the received power The optical OFDM signals are converted into electrical wave signals via a PIN photodiode with a dB bandwidth of 10 GHz, and then passed through the LPF with dB bandwidth of GHz The electrical OFDM signal is captured by a 20 G samples/s real-time digital storage oscilloscope (TDS6804B) The waveform recorded by TDS is processed by offline MATLAB as the same as the original OOFDM system The channel estimation and the symbol synchronization are realized by using training sequence (TS) The TS is similar to Park’s method [19] The symbol synchronization is realized by Chen et al [20], and the channel estimation is calculated by linear interpolation [21] Finally, BER performances of the received signals are calculated Experiment results and discussion The net bit rate of data signal is 6.36 Gbps, and the net bit rate of DSI signal is 0.55 Gbps In this way, the transmission efficiency is calculated as follows: subcarriers for data/(subcarriers for DSI ? subcarriers for data) (%) = 92/ (8 ? 92)% = 92% Fig Complementary cumulative distribution function (CCDF) versus peak-to-average power ratio (PAPR) of OFDM signals Figure shows the CCDF versus PAPR of OFDM signal, NBPSO based on DSI signal, and DSI signal with the threshold of 12 dB At the CCDF of 10-4, the PAPR of the OFDM signal with the NBPSO based on DSI method is reduced by 2.8 dB and 1.4 dB, compared with that of the original OFDM and the DSI method with PAPR threshold of 12 dB, respectively The BER performance of original OFDM signal, DSI signal, and NBPSO based on DSI signal with dBm of fiber launch power after transmission over 100-km SMF is shown in Fig At the BER of FEC 3.8 10-3, the received optical power is about - 4.8 dBm for that with NBPSO based on DSI method, - 3.7 dBm for that with the DSI method, and - 2.9 dBm for original OFDM signal The received sensitivity of OFDM signal with the NBPSO based on DSI method can be improved by 1.1 dB and 1.9 dB when compared with that of the DSI method and original OFDM, respectively The BER performance of OFDM signals with received power is shown in Fig At the BER of FEC 3.8 10-3, the received optical power of NBPSO based on DSI signal, the DSI signal, and original signal is about - 6.8, - 4.8, and - 3.6 dBm, respectively The received sensitivity with NBPSO based on DSI method can be improved by dB and 3.2 dB when compared with the case of DSI method and original OFDM, respectively Figure shows BESR via launch power of optical OFDM signals at received optical power of - dBm after transmission over 100-km SMF At the same launch power, BER performance of the proposed technique is the best and BER performance of original is the worst As the launch power increases from to dBm, BER of all optical Fig BER curves of OFDM signals at dBm launch power after transmission over 100-km SMF 123 Author's personal copy J Opt Conclusion Fig BER curves of OFDM signals at dBm launch power after transmission over 100-km SMF To sum up, this paper has proposed and experimentally demonstrated a novel NBPSO based on DSI method in the IM-DD-OOFDM system The novel proposed technique is used to reduce the fiber nonlinear effect through reducing the PAPR of the OFDM signal The experimental results show that at the launch power of dBm, the received sensitivity with NBPSO based on DSI method can be improved by dB and 3.2 dB when compared with that of DSI method and original OFDM, respectively Meanwhile, at the CCDF of 10-4, the PAPR of OFDM signal with the proposed technique is reduced by 1.4 and 2.8 dB, compared with that of the DSI method and the original OFDM, respectively At a BER of FEC limitation 3.8 10-3, the received power with proposed technique is more sensitive than that of the original OFDM Thus, by using the proposed technique, it can reduce the fiber nonlinear effect efficiently, while the receiver-side hardware remains as similar as the origin References Fig BER via launch power of OFDM signals after transmission over 100-km SMF OFDM signal is decreasing Meanwhile, the BER of the proposed technique decreases faster than that of the other techniques The BER of all optical OFDM signal is the value as the launch power is about dBm, so that the launch power of dBm is the optimal launch power Moreover, with the launch power increasing from to 11 dBm, the BER of all optical OFDM signal is improving, but the BER performance of the proposed technique is better than that of the other techniques The experimental results indicate that the proposed technique can resist nonlinear and it is better than other techniques 123 W Shieh, X Yi, Y Ma, Y Tang, Theoretical and experimental study on PMD supported transmission using polarization diversity in coherent optical OFDM systems Opt Express 15, 9936–9947 (2007) W Shieh, H Bao, Y Tang, Coherent optical OFDM: theory and design Opt Express 16, 841–859 (2008) B.J.C Schmidt, A.J Lowery, J Armstrong, Experimental demonstrations of electronic dispersion compensation for longhaul transmission using direct-detection optical OFDM J Lightwave Technol 26, 196–203 (2008) L Maivan, J He, M Chen, F Mangone, L Chen, New hybrid peak-to-average power ratio reduction technique based on carrier interferometry codes and companding technique for optical direct-detection orthogonal frequency division multiplexing system Opt Eng 53, 086104 (2014) W.A.N.G Zhong-peng, C.H.E.N Fang-ni, W.U Ming-wei, C.H.E.N Ming, T.A.N.G Jin, C.H.E.N Lin, Experimental evaluation of the BER performance in optical OFDM system based on discrete Hartley transform precoding Optoelectron Lett 10, 224–227 (2014) R.W Baăuml, R.F.H Fisher, J.B Huber, Reducing the peak-toaverage power ratio of multicarrier modulation by selected mapping Electron Lett 32, 2056–2057 (1996) L.J Cimini, N.R Sollenberger, Peak-to-average power ratio reduction of an OFDM signal using partial transmit sequences IEEE Commun Lett 4, 86–88 (2000) D Kim, G.L Stuber, Clipping noise mitigation for OFDM by decision-aided reconstruction IEEE Commun Lett 3, 4–6 (1999) X.B Wang, T.T Tjhung, C.S Ng, Reduction of peak-to-average power ratio of OFDM system using a companding technique IEEETrans Broadcast 45, 303–307 (1999) 10 X.B Wang, T.T Tjhung, C.S Ng, Reply to the comments on ‘reduction of peak-to-average power ratio of OFDM system using Author's personal copy J Opt 11 12 13 14 15 16 a companding technique’’ IEEE Trans Broadcast 45, 420–422 (1999) G Ren, H Zhang, Y Chang, H Zhang, in International Conference on Communications, Circuits and Systems Proceedings (ICCCAS) A self companding transform to reduce peak-to-average power ratio in OFDM based WLANs, Guilin, China, 2006, pp 1142–1146 H.-G Ryu, J.-E Lee, J.-S Park, Dummy sequence insertion (DSI) for PAPR reduction in the OFDM communication system IEEE Trans Consum Electron 50, 89–94 (2004) S.W Kim, H.S Byeon, J.K Kim, H.G Ryu, in Fifth International Conference on Information, Communication and Signal Processing An SLM-based real-time PAPR reduction method using dummy sequence insertion in the OFDM communication, Bangkok, Thailand, 2005, pp 258–262 J Kennedy, R.C Eberhart, in Proceedings of IEEE International Conference on Neural Networks Particle Swarm Optimization, Perth, WA, 1995, pp 1942–1948 J Kennedy, R.C Eberhart, in IEEE International Conference on Computational Cybernetics and Simulation A discrete binary version of the particle swarm algorithm, Orlando, FL, 1997, pp 4104–4108 S.H Lee, H.-L Hung, in International Conference on Broadband, Wireless Computing, Communication and Applications 17 18 19 20 21 (BWCCA) Particle swarm optimization on DSI method for PAPR reduction in OFDM systems, Fukuoka, 2010, pp 639–642 J Taghipour, A.A Parandoosh, V.T Vakili, in 20th Telecommunications Forum TELFOR An agent based particle swarm optimization for PAPR reduction of OFDM systems, Serbia, Belgrade, 2012, pp 839–842 H Nezamabadi-pour, M Rostami-shahrbabaki, M.M Farsangi, Binary particle swarm optimization: challenges and new solutions J Comput Soc Iran Comput Sci Eng 6, 21–32 (2008) B Park, H Cheon, C Kang, D Hong, A novel timing estimation method for OFDM systems IEEE Commun Lett 7, 239–241 (2003) M Chen, J He, Z Cao, J Tang, L Chen, W Xian, Symbol synchronization and sampling frequency synchronization techniques in real-time DDO-OFDM systems Opt Commun 326, 80–87 (2014) M Chen, J He, L Chen, Real-time optical OFDM long-reach PON system over 100 km SSMF using a directly modulated DFB laser J Opt Commun Netw 6, 18–25 (2014) Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations 123 ... link.springer.com” 23 Author's personal copy J Opt https://doi.org/10.1007/s12596-019-00512-6 RESEARCH ARTICLE New binary particle swarm optimization on dummy sequence insertion method for nonlinear. .. of India 2019 Abstract In the paper, a novel new binary particle swarm optimization method based on dummy sequence insertion is proposed and experimentally demonstrated in the IM-DD optical orthogonal. .. Vietnam Introduction Recently, orthogonal frequency division multiplexing (OFDM) has been applied in optical communication system [1–5] Due to the high PAPR of OFDM, nonlinearity noise in the nonlinear