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A pilot-based blind (PBB) phase estimation method for the coherent optical orthogonal frequency-division multiplexing (CO-OFDM) system is demonstrated in this paper. Instead of inserting the pilot-subcarriers that are loaded with the already known information in the OFDM signal, the unknown and specially designed signal is used to replace the signal on the pilot subcarriers to decrease the waste of spectrum and has demonstrated good performance in the phase noise compensation. Therefore, the spectral efficiency (SE) is further improved compared with the conventional pilot-aided (PA) phase noise estimation method. Both the proposed PBB and conventional PA estimation methods are compared in a CO-OFDM transmission experiment, which is modulated by 4 quadrature amplitude modulation (4-QAM) formats and transmitted over 1760-km standard single-mode fiber (SSMF) without optical dispersion compensation. The experimental results show that the proposed PBB method can achieve the similar performance as the conventional PA method.
© 2014 Optical Society of America
1. Introduction
To meet the ever-increasing optical bandwidth demand, the optical communication system supporting 1-Tb/sand beyond per channel will soon be required. Coherent optical orthogonal frequency-division multiplexing (CO-OFDM) is a promising candidate technology for the required large capacity, long haul transmission and has been developed rapidly in recent years [1–4].However, the phase noise is still one of the main limitations for the CO-OFDM transmission performance [5–7].It is important to compensate the phase noise with a cost as low as possible for the CO-OFDM system. So far, there are two main research directions: i) non-blind-based method; ii) blind-based method. For the former scheme, many methods have been proposed and studied widely, such as pilot-aided, RF pilot-aided and pseudo pilot-aided [8–10]. But all of them need one or more pilots to transmit the already known information for the phase noise estimation, which will decrease the spectral efficiency (SE) of the system. On the contrary, the SE will be improved for the blind-based method in the phase noise estimation since none of already known data is required. By using the specially designed digital signal processing (DSP) algorithm, the phase noise can be calculated from the unknown information. So the blind methods have higher SE, which is attractive for the large capacity transmission system. Recently, a blind compensation for phase noise in OFDM systems over constant modulus modulation has been proposed [11]. Non-data-aided phase noise suppression scheme for CO-OFDM systems has also been proposed [12]. In addition, the interesting joint phase estimation method for coherent optical OFDM systems has been proposed and demonstrated [13]. Joint compensation algorithm combines two different techniques to achieve better performance than only using one technique.
In this paper, a pilot-based blind (PBB) phase estimation method for CO-OFDM system is proposed. Instead of inserting the pilot-subcarriers which are loaded with the already known information in the OFDM signal, the unknown and specially designed signals are used to replace the signals on the pilot subcarriers to improve the SE and the good performance in the phase noise compensation is demonstrated. Therefore, the SE is further improved compared with the conventional pilot-aided (PA) phase noise estimation method. We experimentally demonstrated a CO-OFDM transmission with 4 quadrature amplitude modulation (4-QAM) format over 1760-km standard single-mode fiber (SSMF), in which both the proposed PBB and conventional pilot-aided (PA) estimation methods are applied and compared. The experimental results show that the proposed PBB method can achieve the similar performance as the conventional PA method.
2. Principle of the PBB phase noise estimation method
The principle of the proposed PBB phase noise estimation method is shown in Fig. 1. Figure 1(a) shows the two-dimensional time/frequency structure of one OFDM frame by using the PBB estimation method. K subcarriers are selected for the phase estimation. Unlike transmitting the already known signal used in the conventional PA estimation method, the subcarriers are used to transmit the unknown signal with amplitude modulation (AM) format as shown in Fig. 1(b). In half of the K selected subcarriers, the amplitudes of the AM signal are 1, 3, 5, 7… and N, respectively. Then, at the receiver, all the received random values on half of the K subcarriers and the zero value are used for the linear fitting. The angle between the fitting line and Re axis is the coarse rotated phase noise ϕ as shown in Fig. 1(c). In order to increase the accuracy of linear fitting, the amplitudes of −1, −3, −5, −7… and -N in the left half of the K selected subcarriers and zero value repeat the processing. Combining the two results, we get the final coarse phase noise. Then zero value and all of the positive random values and negative random values on the K subcarriers are used for the more accurate linear fitting to implement the fine phase noise estimation. Additionally, the order of the AM signal on the selected subcarriers can be flexible adjusted along with the modulation order of the data signal on the other subcarriers to improve the transmission capacity.
Fig. 1 The principle of the proposed PBB phase noise estimation method. (a) Two-dimensional time/frequency structure of one OFDM frame by using the conventional PA estimation method; (b) The proposed amplitude modulation formats; (c) The linear fitting for phase noise estimation
Figure 2 shows the main DSP procedures of the transmission system. Pseudo-random binary sequence (PRBS) is split into two paths. The upper path is mapped to the 4-QAM signal and the lower path is mapped to the 4-AMsignal for the phase noise estimation. Then the 4-AM signal is pre-modulated to decrease peak-to-average power ratio by increasing the random by multiplying the random ± 1 or ± j, which is saved as a table for demodulation at the receiver. Then all the signals are used to generate the optical OFDM signal. After being transmitted through the optical channel, the inverse processes are required to recover the 4-QAM and 4-AM signals, respectively. The 4-AM signal is separated from the signal after the demodulation of OFDM signal (De-OFDM) for the phase estimation. As the feedback to the De-OFDM process, the output signal of the phase estimation is used to compensate the phase noise of the OFDM signal. Then the 4-QAM and 4-AM signals are de-mapped, respectively. Although both of the joint blind phase estimation method [13] and the PBB method can achieve good performance, the proposed PBB method doesn’t need the processing of demodulation and decision-feedback compared with joint blind phase estimation method [13]. Therefore, the algorithm structure of the PBB method is relatively simple.
3. Experimental setup
The experimental setup of the CO-OFDM system using the PBB/PA phase noise estimation methods is illustrated in Fig. 3. In the experiment, an external-cavity laser (ECL) with line-width less than 100-KHz is used as the optical carrier modulated by the OFDM signal that drives I/Q modulator. An arbitrary waveform generator (AWG) running at 12-GS/s is employed to produce OFDM/4QAMbasebandsignal.The FFT size is 256, in which 164 subcarriers are loaded with OFDM/4QAM signals. The center one subcarrier is unloaded to avoid the DC influence. 4 subcarriers are selected for the phase noise estimation. For the PBB method, the 4 subcarriers are loaded with 4-AM and the proposed phase noise estimation algorithm is used. However, for the PA method, the 4 subcarriers are the pilots loaded with the already known 4-QAM signal. In this experiment, 10 TSs are periodically inserted in the front of each OFDM/4QAM frame, which is then followed by 500 payload symbols. The cyclic prefix length is the 1/8 FFT size. The data rate of OFDM signal is 13.2-Gb/s for 4-QAM loading case. The transmission link is constructed by 22 spans of 80 km SSMF with Raman amplification. In the receiver, the typical coherent receiver is used to detect the optical OFDM signal into electrical signal, and then is sampled by a digital storage oscilloscope (DSO Tektronix DSA72004B) operating at 50 GS/s. Off-line DSP is done by the MATLAB program.
4. Experimental results and Discussions
Similar to [14], the number of the selected subcarriers is one of the important issues in the proposed PBB phase noise estimation method. The Q factor versus the number of the selected subcarriers at optical back-to-back is shown in Fig. 4. Here, the Q factor is defined as the average signal-to-noise ratio of the QAM and AM signals. The Q factor of 2 subcarriers loading is 20.1-dB that is lower than the others when more than 2 subcarriers are used. Thus 2 subcarriers are not enough for the first-order fitting in the PBB estimation method. When 4 and more subcarriers are used, the Q factor states almost 21.5-dB.Thus,4 subcarriers are adequate for the phase estimation based on PBB method. As a result, only 4 subcarriers are used for phase noise estimation in the demonstration. Because the computational complexity depends on the number of linear fitting points, 5 points will not add much computational complexity. The linear fitting processing is carried out in three stages. First and second are used for coarse estimation. Each of them contains 3 points. According to [15], only 34 multiplications and 27 additions are needed. While in the third stage, 5 points are used for linear fitting. The processing in this stage consumes 76multiplications and 67additions.
From the previous analysis, 4-AM signal with the absolute amplitudes of 1, 3, 5 and 7 is used in the PBB estimation method. But the higher amplitude signal will occupy more optical power, which can decrease the performance of the signal on the other subcarriers. The absolute amplitudes of the AM signal can be adjusted to accomplish better performance. Therefore, we investigate the Q factor performance versus amplitude factor(AF) of the AM signal at optical back-to-back and over 1760-km SSMF as shown in Fig. 5.Here, the AF is defined as the absolute amplitudes of 4-AM signal divided by the uniform amplitudes of 1, 3, 5 and 7. For example, when the AF is 0.1, the absolute amplitudes of 4-AM signal are 0.1, 0.3, 0.5 and 0.7 respectively. It can be seen that the factor of 0.4is adequate for the phase estimation because the Q factor performance is barely improved beyond0.4.
From the analysis above, we then set the number and amplitude factor of the selected subcarriers are 4 and 0.4, respectively. Meanwhile, for the purpose of comparison, 4 pilot subcarriers are also used in the PA phase estimation method. The Q factor versus launched power over 1760-km SSMF with PBB and PA phase noise estimation methods are shown in Fig. 6. The optimized launched powers of the PBB and PA methods are −0.3-dBm and −0.6-dBm, respectively. The 0.3-dBmincrease is mainly caused by the optical power radio decreasing of the subcarriers with 4-QAM format signal in the whole signal. The selected 4 subcarriers for the phase noise estimation occupy more optical power of the whole signal compared with the PA method. Thus a little higher launched power is obtained in the PBB method.
We further evaluate the transmission performance of the PBB and PA phase noise estimation systems over 1760-km fiber links. Figure 7 shows the Q factor versus optical signal-to-noise (OSNR) curves of the systems. The OSNR values are almost the same (~6.0-dB) at the 1E-3 limit (Q factor = 9.8-dB) for the two phase noise estimation methods at optical B2B. After 1760-km SSMF, the required OSNR values are 7.0-dB and 6.6-dB respectively at the 1E-3 limit. There is only 0.4-dB OSNR decrease. Thus the proposed PBB method can accomplish the comparable performance with the conventional PA method.
5. Conclusion
In this paper, a PBB phase estimation method for CO-OFDM has been proposed. A 13.2-Gb/s CO-OFDM transmission experiment modulated with 4-QAM format signal over 1760-km SSMF without optical dispersion compensation is demonstrated to compare the proposed PBB method with the conventional PA estimation method. Compared to the conventional method, the similar performance of the proposed blind method is obtained.
Acknowledgments
The authors would like to acknowledge the support of National High Technology 863 Research and Development Program of China (No. 2013AA013300), (No. 2013AA013403), National Natural Science Foundation of China (NSFC) under Grant (No. 61307092, 61435006)and New Century Excellent Talents in University (NCET-12-0679).
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