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Optics Communications 249 (2005) 79–84 www.elsevier.com/locate/optcom
Chromatic dispersion monitoring technique employing SOA spectral shift in 40 Gbit/s system Ying Shi *, Minghua Chen, Nan Ma, Shizhong Xie Department of Electronic Engineering, Tsinghua University, 11-406, East Main Building, Beijing 100084, PR China Received 13 October 2004; received in revised form 15 December 2004; accepted 14 January 2005
Abstract An all-optical online chromatic dispersion monitoring technique in 40 Gbit/s system by using of the spectral shift in the semiconductor optical amplifier (SOA) is demonstrated. Spectrum components on the long-wavelength side of 40 Gbit/s signal after passing the SOA are extracted for the dispersion monitoring. The range of monitoring can reach ±60 ps/nm, and the accuracy of monitoring is less than 5 ps/nm. Ó 2005 Elsevier B.V. All rights reserved. PACS: 42.79.S Keywords: Chromatic dispersion; Monitoring; SOA; Spectral shift
1. Introduction In 40 Gbit/s optical long haul transmission systems, the system residual dispersion varies due to the changes of environment factors, which results in system performance degradation. So, it is necessary to employ online residual dispersion monitoring and dynamic dispersion compensation in these systems. At present, online dispersion monitoring methods include vestigial sideband [1] or single sideband [2], subcarrier monitoring [3,4], clock level *
Corresponding author. Tel.: +86 010 627 92551/73197; fax: +86 010 627 88161. E-mail address: [email protected] (Y. Shi).
[5], fiber spectral broadening [6], and two-photon absorption [7,8]. The sideband, clock level and subcarrier methods involve high speed O/E units, and the fiber spectral broadening method needs high power optical amplifiers due to the weak Kerr effect in fiber. In our former work [9], a dispersion monitoring method employing SOA spectral shift in 10 Gbit/s system has been proposed and experimentally demonstrated. However, when the SOA operates at the bit rate of 40 Gbit/s, it will introduce serious pattern effect. In this paper, the performance of this method applied in 40 Gbit/s system will be investigated and the influence of the pattern effect will be analyzed. It is demonstrated that online chromatic dispersion monitoring for 40 Gbit/s
0030-4018/$ - see front matter Ó 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.optcom.2005.01.017
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Y. Shi et al. / Optics Communications 249 (2005) 79–84
carrier-suppressed return-to-zero (CSRZ) systems can be implemented by this method with proper setup.
2. Spectral shift in SOA In our method, the dispersion is measured employing the frequency shift in SOA. As shown in Fig. 1, a 223 1 pseudo random bit sequence (PRBS) in 40 Gbit/s CSRZ code is sent into a SOA. After passing through the SOA, the spectrum components of the signal are measured by an optical spectrum analyzer (OSA) or a 0.3 nm optical filter and two photodiodes. The input signal causes the gain saturation of the SOA, which results in a down chirp, thus the frequency of the output signal of the SOA shifts and the power of the long-wavelength side of the output spectrum rises. Since the saturation is mainly caused by the head of the pulse, the value of the frequency chirp depends on the shape of the rising edge of the input pulses if the input power is kept constant. When the dispersion increases, the input pulses of the SOA become flat, the gain saturation turns weak, and the frequency chirps of the corresponding output pulses are also suppressed. As a result, the power of the long wavelength side decreases. Therefore, the power of the long wavelength side can be used to monitor the dispersion. In the numerical simulation, the saturation energy of SOA is set at Esat = 2 pJ, the unsaturated gain G0 = 30 dB, and the carrier lifetime
Fig. 1. Experiment schema.
Tc = 300 ps. The gain saturation and the frequency shift can be clearly illustrated by the time– frequency analysis of the simulation results, as shown in Fig. 2, where the contour lines predicate the power distributed on the time–frequency plane, with the X axis denoting time and the Y axis instantaneous frequency. In Fig. 2(a), the input pulses are a set of symmetrical concentric circles, indicating non-chirp pulses. Corresponding to it, the output pulses are asymmetrical and the frequency of the pulses shifts negatively, as shown in Fig. 2(b). When the dispersion increases, the output pulses broaden and the frequency shift is weaker than that of the pulses without dispersion, as shown in Fig. 2(c). From Fig. 2, it can also be seen that the frequency chirp of the output pulses turns weak with continuous Ô1Õs and becomes strong after continuous Ô0Õs, which is caused by the pattern effect in 40 Gbit/s system. Since the time for the gain recovering, depending on the saturation depth and the carrier lifetime, is much longer than the period of the pulses, the pattern effect reduces the gain saturation of the SOA by decreasing G(0), which represents the instantaneous gain when a pulse reaches SOA and is determined by the pattern of the preceding pulses. In order to quantify the influence introduced by the pattern effect, the frequency shift of an output pulse is defined as R1 2 jH ðf Þj ðf f0 Þ df Df ¼ 1 R 1 ; ð1Þ 2 H ðf Þj df 1 j where f0 is the carrier frequency, and H(f) is the output spectral amplitude density. Without loss of generalness, we consider the case of a single pulse sent into a saturated SOA, where G(0) decreases from the unsaturated gain G0 to fully saturated gain 0 dB. The frequency shift Df corresponding to different G(0) is shown in Fig. 3. By studying Df with different dispersion and input power, shown in Figs. 3(a) and (b) respectively, we can get the following conclusions: (1) Both Figs. 3(a) and (b) indicate Df decreases as G(0) decreases, which shows the saturation of SOA. (2) In Fig. 3(a), with fixed G(0), Df decreases as dispersion increases. (3) In Fig. 3(b), with fixed G(0), Df increases as input power increases. Thus
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Fig. 2. The instantaneous frequency of: (a) input of the SOA without dispersion; (b) output of the SOA without dispersion; (c) output of the SOA with dispersion of 20 ps/nm.
when dealing with a single pulse, we can increase Df and improve the monitoring result by increasing the input power. However, when dealing with continuous pulses, Df does not keep increasing with the increasing input power, because too strong pulse causes deep saturation and suppresses the Df of the following pulses, and as a result, the average Df decreases. Therefore, Df can be maximized by optimizing the input average power. Fig. 4 represents the simulation results of the optimization with different dispersion. In Fig. 4, Df increases with the input power when the input power is relatively weak, and decreases rapidly after it reaches its maximum with the input power around +5 dBm.
3. Experiment and optimization of the filtering In the experiment, the saturation power of the SOA is 8.9 dBm. Considering both the optimization result and the simplicity of the experiment configuration, the input average power of the SOA is set at 0 dBm and kept unchanged so as to avoid the impact of the variation of the input power. The total dispersion varies from 68 to 60 ps/nm when the length of single mode fiber (SMF) and dispersion compensation fiber (DCF) changes. As the minimal length of the SMF is 0.1 km, the step of the dispersion is 1.7 ps/nm. The input power of the fiber link is set at 5 dBm to avoid the non-linearity in the fiber link.
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Fig. 3. The frequency shift of the output of the SOA as the SOA saturating: (a) with different dispersion; (b) with different power of the input pulse.
Fig. 4. The optimization of the input average power with different dispersion.
As the conclusion in part 2, the power shifts to long wavelength side after passing through the SOA and distributes over the spectrum. By contrasting the spectrum of the back–back signal and the output of the SOA without/with dispersion, as shown in Fig. 5, it can be seen that the spectrum of the output of the SOA broadens, part of energy of the output signal shifts to the long wavelength side, and the frequency shift turns weak when the dispersion increases. For the power rising of the discrete peaks are relatively insufficient, the peaks should not be included in the spectrum components for monitoring. So the long wavelength side is divided into part i, part ii and part iii by these peaks. In order to optimize the optical filtering and get optimized spectrum components, an OSA is used to measure the power of the three parts. The result of the filtering optimization is shown in Fig. 6, where the square, circle and triangle represent the normalized power of the part i, ii and iii, respectively. The power is normalized, and the corresponding maximum of the three curves are 4.68, 5.22 and 18.25 dBm. In Fig. 6, the shifted power of the output of the SOA decreases as the dispersion increases from 0 to ±60 ps/nm. The monitoring result with negative dispersion is similar with that of positive dispersion, except that the left half of the curve is slightly higher than the right half, because the negative dispersion causes the red part of the signal to transmit faster than the blue part and to accumulate in the head of the pulse where the frequency red shift is strong, thus the spectral shift is enhanced. By contrasting the curve (a), curve (b) and curve (c), it can be concluded that the monitoring accuracy increase, the monitoring range decreases and the peak power also decreases with the measured frequency components shifting toward the long wavelength side. Besides this, the range and accuracy of the monitoring are also influenced by the width of the optical filter, because it is unavoidable that some power of the center part of the spectrum is included in the output filtered power as the result of the finite isolation (20 dB in this experiment) of the optical filter, and especially when the bandwidth of the filter is very broad, the power of the center part will exert crucial effects on the
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Fig. 6. The normalized power measured by the OSA of: (a) the part i; (b) the part ii; (c) the part iii. (see Fig. 3).
Fig. 5. Output spectra of the SOA: (a) back–back; (b) without dispersion; (c) with dispersion of 60 ps/nm.
monitoring result. Theoretically, the monitoring sensitivity can be improved by using a filter with narrow bandwidth and high isolation, or by placing the filter far from the carrier wavelength. But too narrow bandwidth or shifting too far from
the carrier wavelength leads to weak output power, which will result in that the electrical noise of the photodiode is comparable to the filtered power. Considering the monitoring range, accuracy and the appropriate output power of the filter, in the monitoring experiment, a fiber Bragg grating (FBG) filter, whose 3 dB width is 0.3 nm and is approximately equal to 40 GHz, is used to extract the power of the part ii. As the carrier wavelength is 1557.36 nm, the center of the filter is set at 1558 nm, and its 3 dB passband exactly covers the part ii in Fig. 5. Fig. 7 illustrates the ratio of the filtered power to the total output power of the SOA, where the dots denote the experiment result and the line represents the simulation result. By extracting part of the output of the SOA and using the ratio as the monitoring result, the impact of the variation of the total output power of the SOA is reduced and the ripple of the monitoring result decreases. However, when the value of the dispersion increases beyond ±60 ps/nm, the pulses are so flat that the change of the filtered power will be too small for monitoring. Therefore, the dispersion monitoring range is limited within the range of ±60 ps/nm. In the meantime, it can be seen from Fig. 5 that the monitoring accuracy is less than 5 ps/nm. But a problem of this method is that the negative and positive dispersion cannot be distinguished. Besides this, there is a little oscillation
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ther high speed O/E units nor microwave circuit being used in this method, nor any extra modulation being added in the transmitter. Meanwhile, the required input power is greatly reduced because of the strong non-linearity in SOA. The range of monitoring can reach ±60 ps/nm, and the accuracy of monitoring is less than 5 ps/nm. Therefore, this technique is promising to be used in online chromatic dispersion monitoring in 40 Gbit/s optical communication systems.
References Fig. 7. The experiment and simulation results of the dispersion monitoring.
in the monitoring curve, which may cause the problem of local extremum. However, these problems can be solved by appropriate algorithm, which is used to control the tunable dispersion compensation (TDC) device and keep the system residual dispersion around zero dynamically.
4. Conclusion In conclusion, an all-optical dispersion monitoring technique employing frequency shift in SOA is demonstrated in this paper. There are nei-
[1] Q. Yu, L.-S. Yan, Z. Pan, A.E. Willner, OFC 2002 Techn, Dig. WE3, p. 197. [2] Akira Hirano, Shoichiro Kuwahara, Yutaka Miyamoto, OFC 2002 Techn, Dig.WE2, p. 196. [3] M.N. Petersen, Z. Pan, S. Lee, S.A. Havstad, A.E. Willner, IEEE Photon. Technol. Lett. 14 (4) (2002) 570. [4] Timothy E. Dimmick, Giammarco Rossi, Daniel J. Blumenthal, IEEE Photon. Technol. Lett. 12 (7) (2000) 900. [5] A.B. Sahin, L.-S. Yan, Qian Yu, M. Hauer, Z. Pan, A.E. Willner, ECOCÕ01 Techn. Dig. vol. 3, p. 446. [6] Paul S. Westbrook, Benjamin J. Eggleton, Gregory Raybon, Stefan Hunsche, Tsing Hua Her, IEEE Photon. Technol. Lett. 14 (3) (2002) 346. [7] J.M. Roth, C. Xu, T.E. Murphy, Opt. Lett. 27 (23) (2004) 2076. [8] S. Wielandy, M. Fishteyn, B. Zhu, J. Lightwave Technol. 22 (3) (2004) 784. [9] Ying Shi, Minghua Chen, Shizhong Xie, Opt. Commun. 230 (4-6) (2004) 297.
Chromatic dispersion monitoring technique employing SOA spectral shift in 40 Gbit/s system Ying Shi *, Minghua Chen, Nan Ma, Shizhong Xie Department of Electronic Engineering, Tsinghua University, 11-406, East Main Building, Beijing 100084, PR China Received 13 October 2004; received in revised form 15 December 2004; accepted 14 January 2005
Abstract An all-optical online chromatic dispersion monitoring technique in 40 Gbit/s system by using of the spectral shift in the semiconductor optical amplifier (SOA) is demonstrated. Spectrum components on the long-wavelength side of 40 Gbit/s signal after passing the SOA are extracted for the dispersion monitoring. The range of monitoring can reach ±60 ps/nm, and the accuracy of monitoring is less than 5 ps/nm. Ó 2005 Elsevier B.V. All rights reserved. PACS: 42.79.S Keywords: Chromatic dispersion; Monitoring; SOA; Spectral shift
1. Introduction In 40 Gbit/s optical long haul transmission systems, the system residual dispersion varies due to the changes of environment factors, which results in system performance degradation. So, it is necessary to employ online residual dispersion monitoring and dynamic dispersion compensation in these systems. At present, online dispersion monitoring methods include vestigial sideband [1] or single sideband [2], subcarrier monitoring [3,4], clock level *
Corresponding author. Tel.: +86 010 627 92551/73197; fax: +86 010 627 88161. E-mail address: [email protected] (Y. Shi).
[5], fiber spectral broadening [6], and two-photon absorption [7,8]. The sideband, clock level and subcarrier methods involve high speed O/E units, and the fiber spectral broadening method needs high power optical amplifiers due to the weak Kerr effect in fiber. In our former work [9], a dispersion monitoring method employing SOA spectral shift in 10 Gbit/s system has been proposed and experimentally demonstrated. However, when the SOA operates at the bit rate of 40 Gbit/s, it will introduce serious pattern effect. In this paper, the performance of this method applied in 40 Gbit/s system will be investigated and the influence of the pattern effect will be analyzed. It is demonstrated that online chromatic dispersion monitoring for 40 Gbit/s
0030-4018/$ - see front matter Ó 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.optcom.2005.01.017
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Y. Shi et al. / Optics Communications 249 (2005) 79–84
carrier-suppressed return-to-zero (CSRZ) systems can be implemented by this method with proper setup.
2. Spectral shift in SOA In our method, the dispersion is measured employing the frequency shift in SOA. As shown in Fig. 1, a 223 1 pseudo random bit sequence (PRBS) in 40 Gbit/s CSRZ code is sent into a SOA. After passing through the SOA, the spectrum components of the signal are measured by an optical spectrum analyzer (OSA) or a 0.3 nm optical filter and two photodiodes. The input signal causes the gain saturation of the SOA, which results in a down chirp, thus the frequency of the output signal of the SOA shifts and the power of the long-wavelength side of the output spectrum rises. Since the saturation is mainly caused by the head of the pulse, the value of the frequency chirp depends on the shape of the rising edge of the input pulses if the input power is kept constant. When the dispersion increases, the input pulses of the SOA become flat, the gain saturation turns weak, and the frequency chirps of the corresponding output pulses are also suppressed. As a result, the power of the long wavelength side decreases. Therefore, the power of the long wavelength side can be used to monitor the dispersion. In the numerical simulation, the saturation energy of SOA is set at Esat = 2 pJ, the unsaturated gain G0 = 30 dB, and the carrier lifetime
Fig. 1. Experiment schema.
Tc = 300 ps. The gain saturation and the frequency shift can be clearly illustrated by the time– frequency analysis of the simulation results, as shown in Fig. 2, where the contour lines predicate the power distributed on the time–frequency plane, with the X axis denoting time and the Y axis instantaneous frequency. In Fig. 2(a), the input pulses are a set of symmetrical concentric circles, indicating non-chirp pulses. Corresponding to it, the output pulses are asymmetrical and the frequency of the pulses shifts negatively, as shown in Fig. 2(b). When the dispersion increases, the output pulses broaden and the frequency shift is weaker than that of the pulses without dispersion, as shown in Fig. 2(c). From Fig. 2, it can also be seen that the frequency chirp of the output pulses turns weak with continuous Ô1Õs and becomes strong after continuous Ô0Õs, which is caused by the pattern effect in 40 Gbit/s system. Since the time for the gain recovering, depending on the saturation depth and the carrier lifetime, is much longer than the period of the pulses, the pattern effect reduces the gain saturation of the SOA by decreasing G(0), which represents the instantaneous gain when a pulse reaches SOA and is determined by the pattern of the preceding pulses. In order to quantify the influence introduced by the pattern effect, the frequency shift of an output pulse is defined as R1 2 jH ðf Þj ðf f0 Þ df Df ¼ 1 R 1 ; ð1Þ 2 H ðf Þj df 1 j where f0 is the carrier frequency, and H(f) is the output spectral amplitude density. Without loss of generalness, we consider the case of a single pulse sent into a saturated SOA, where G(0) decreases from the unsaturated gain G0 to fully saturated gain 0 dB. The frequency shift Df corresponding to different G(0) is shown in Fig. 3. By studying Df with different dispersion and input power, shown in Figs. 3(a) and (b) respectively, we can get the following conclusions: (1) Both Figs. 3(a) and (b) indicate Df decreases as G(0) decreases, which shows the saturation of SOA. (2) In Fig. 3(a), with fixed G(0), Df decreases as dispersion increases. (3) In Fig. 3(b), with fixed G(0), Df increases as input power increases. Thus
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Fig. 2. The instantaneous frequency of: (a) input of the SOA without dispersion; (b) output of the SOA without dispersion; (c) output of the SOA with dispersion of 20 ps/nm.
when dealing with a single pulse, we can increase Df and improve the monitoring result by increasing the input power. However, when dealing with continuous pulses, Df does not keep increasing with the increasing input power, because too strong pulse causes deep saturation and suppresses the Df of the following pulses, and as a result, the average Df decreases. Therefore, Df can be maximized by optimizing the input average power. Fig. 4 represents the simulation results of the optimization with different dispersion. In Fig. 4, Df increases with the input power when the input power is relatively weak, and decreases rapidly after it reaches its maximum with the input power around +5 dBm.
3. Experiment and optimization of the filtering In the experiment, the saturation power of the SOA is 8.9 dBm. Considering both the optimization result and the simplicity of the experiment configuration, the input average power of the SOA is set at 0 dBm and kept unchanged so as to avoid the impact of the variation of the input power. The total dispersion varies from 68 to 60 ps/nm when the length of single mode fiber (SMF) and dispersion compensation fiber (DCF) changes. As the minimal length of the SMF is 0.1 km, the step of the dispersion is 1.7 ps/nm. The input power of the fiber link is set at 5 dBm to avoid the non-linearity in the fiber link.
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Fig. 3. The frequency shift of the output of the SOA as the SOA saturating: (a) with different dispersion; (b) with different power of the input pulse.
Fig. 4. The optimization of the input average power with different dispersion.
As the conclusion in part 2, the power shifts to long wavelength side after passing through the SOA and distributes over the spectrum. By contrasting the spectrum of the back–back signal and the output of the SOA without/with dispersion, as shown in Fig. 5, it can be seen that the spectrum of the output of the SOA broadens, part of energy of the output signal shifts to the long wavelength side, and the frequency shift turns weak when the dispersion increases. For the power rising of the discrete peaks are relatively insufficient, the peaks should not be included in the spectrum components for monitoring. So the long wavelength side is divided into part i, part ii and part iii by these peaks. In order to optimize the optical filtering and get optimized spectrum components, an OSA is used to measure the power of the three parts. The result of the filtering optimization is shown in Fig. 6, where the square, circle and triangle represent the normalized power of the part i, ii and iii, respectively. The power is normalized, and the corresponding maximum of the three curves are 4.68, 5.22 and 18.25 dBm. In Fig. 6, the shifted power of the output of the SOA decreases as the dispersion increases from 0 to ±60 ps/nm. The monitoring result with negative dispersion is similar with that of positive dispersion, except that the left half of the curve is slightly higher than the right half, because the negative dispersion causes the red part of the signal to transmit faster than the blue part and to accumulate in the head of the pulse where the frequency red shift is strong, thus the spectral shift is enhanced. By contrasting the curve (a), curve (b) and curve (c), it can be concluded that the monitoring accuracy increase, the monitoring range decreases and the peak power also decreases with the measured frequency components shifting toward the long wavelength side. Besides this, the range and accuracy of the monitoring are also influenced by the width of the optical filter, because it is unavoidable that some power of the center part of the spectrum is included in the output filtered power as the result of the finite isolation (20 dB in this experiment) of the optical filter, and especially when the bandwidth of the filter is very broad, the power of the center part will exert crucial effects on the
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Fig. 6. The normalized power measured by the OSA of: (a) the part i; (b) the part ii; (c) the part iii. (see Fig. 3).
Fig. 5. Output spectra of the SOA: (a) back–back; (b) without dispersion; (c) with dispersion of 60 ps/nm.
monitoring result. Theoretically, the monitoring sensitivity can be improved by using a filter with narrow bandwidth and high isolation, or by placing the filter far from the carrier wavelength. But too narrow bandwidth or shifting too far from
the carrier wavelength leads to weak output power, which will result in that the electrical noise of the photodiode is comparable to the filtered power. Considering the monitoring range, accuracy and the appropriate output power of the filter, in the monitoring experiment, a fiber Bragg grating (FBG) filter, whose 3 dB width is 0.3 nm and is approximately equal to 40 GHz, is used to extract the power of the part ii. As the carrier wavelength is 1557.36 nm, the center of the filter is set at 1558 nm, and its 3 dB passband exactly covers the part ii in Fig. 5. Fig. 7 illustrates the ratio of the filtered power to the total output power of the SOA, where the dots denote the experiment result and the line represents the simulation result. By extracting part of the output of the SOA and using the ratio as the monitoring result, the impact of the variation of the total output power of the SOA is reduced and the ripple of the monitoring result decreases. However, when the value of the dispersion increases beyond ±60 ps/nm, the pulses are so flat that the change of the filtered power will be too small for monitoring. Therefore, the dispersion monitoring range is limited within the range of ±60 ps/nm. In the meantime, it can be seen from Fig. 5 that the monitoring accuracy is less than 5 ps/nm. But a problem of this method is that the negative and positive dispersion cannot be distinguished. Besides this, there is a little oscillation
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Y. Shi et al. / Optics Communications 249 (2005) 79–84
ther high speed O/E units nor microwave circuit being used in this method, nor any extra modulation being added in the transmitter. Meanwhile, the required input power is greatly reduced because of the strong non-linearity in SOA. The range of monitoring can reach ±60 ps/nm, and the accuracy of monitoring is less than 5 ps/nm. Therefore, this technique is promising to be used in online chromatic dispersion monitoring in 40 Gbit/s optical communication systems.
References Fig. 7. The experiment and simulation results of the dispersion monitoring.
in the monitoring curve, which may cause the problem of local extremum. However, these problems can be solved by appropriate algorithm, which is used to control the tunable dispersion compensation (TDC) device and keep the system residual dispersion around zero dynamically.
4. Conclusion In conclusion, an all-optical dispersion monitoring technique employing frequency shift in SOA is demonstrated in this paper. There are nei-
[1] Q. Yu, L.-S. Yan, Z. Pan, A.E. Willner, OFC 2002 Techn, Dig. WE3, p. 197. [2] Akira Hirano, Shoichiro Kuwahara, Yutaka Miyamoto, OFC 2002 Techn, Dig.WE2, p. 196. [3] M.N. Petersen, Z. Pan, S. Lee, S.A. Havstad, A.E. Willner, IEEE Photon. Technol. Lett. 14 (4) (2002) 570. [4] Timothy E. Dimmick, Giammarco Rossi, Daniel J. Blumenthal, IEEE Photon. Technol. Lett. 12 (7) (2000) 900. [5] A.B. Sahin, L.-S. Yan, Qian Yu, M. Hauer, Z. Pan, A.E. Willner, ECOCÕ01 Techn. Dig. vol. 3, p. 446. [6] Paul S. Westbrook, Benjamin J. Eggleton, Gregory Raybon, Stefan Hunsche, Tsing Hua Her, IEEE Photon. Technol. Lett. 14 (3) (2002) 346. [7] J.M. Roth, C. Xu, T.E. Murphy, Opt. Lett. 27 (23) (2004) 2076. [8] S. Wielandy, M. Fishteyn, B. Zhu, J. Lightwave Technol. 22 (3) (2004) 784. [9] Ying Shi, Minghua Chen, Shizhong Xie, Opt. Commun. 230 (4-6) (2004) 297.