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Abstract
As the demand for mobile Internet capacity explodes, the research on fifth-generation (5G) mobile communication systems has gradually deepened, which has stringent requirements for latency and transmission capacity, especially in the section called mobile fronthaul (MFH). Wavelength division multiplexing passive optical network (WDM-PON) is an attractive technology for 5G MFH which requires an auxiliary management and control channel (AMCC) to achieve efficient network deployment. In previous studies, more research has been done on AMCC superimposition methods and transmission performance on 10 Gbps WDN-PON systems, and the role of AMCC in wavelength management has been studied at the system level. In this paper, we realize non-linear baseband modulation of AMCC signals up to 20 Mbps in a single wavelength 25-Gbps PON system through the distributed feed-back laser and Mach-Zehnder modulator. At the receiving end, we propose a low-complexity interference cancellation method to suppress the interference caused by WDM-PON signals and significantly reduce the bit error rate of AMCC signals. The method realizes a simplified scheme to reconstruct the PON signals by analyzing the characteristics of nonlinear modulation and the reconstructed signals can be applied to the original AMCC signals through filtering and subtraction to eliminate interference. These operations have low complexity and can be easily implemented by analog circuits, thus making it an effective way to improve the quality of AMCC signals. With the help of the proposed method, AMCC transmission at 20 Mbps can be achieved with different modulation depths, which is very promising for 5G MFH.
© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
The fifth-generation (5G) mobile communication network has been commercially released in 78 countries by end of 2021, and the next 3 to 5 years will still be critical for 5G development [1]. In NTT’s White paper [2], it is shown that the applications such as Metaverse concept, 4K, 8K, other ultra-high-definition video services as well as Virtual/Augmented Reality, etc. put forward higher requirements on the capacity, delay and other characteristics of the 5G fronthaul/backhaul network. By the 2030s, network capacity will have increased by more than 100 times, and the introduction of 6G networks will result in peak network bandwidths of more than 100Gbps, end-to-end network latency of less than 1ms, and networks with features such as extreme coverage, extreme high reliability and some other characteristics. To solve these problems, wavelength division multiplexed passive optical network (WDM-PON) as one of the highly attractive candidates for 5G mobile fronthaul (MFH) [3,4] should be developed accordingly to play an important role in the future 6G system.
In the WDM-PON system, in order to effectively utilize wavelength resources and achieve stable and reliable communication, an embedded communication called Auxiliary Management and Control Channel (AMCC) is defined in the ITU-T G.989 series [5–7]. AMCC is an additional channel superimposed on the WDM-PON signals for managing wavelengths and transmitting operations management (OAM) data. The deployment of AMCC can realize flexible network management and effectively adapt to the needs of 5G MFH. The feasibility of AMCC has been confirmed and evaluated in a number of previous studies [8–16]. At the system level, NTT has experimentally confirmed the possibility of using AMCC signals to achieve wavelength control such as wavelength adjustment and wavelength shift protection in 5G networks [17,18]. In [19], a WDM-PON system managed by AMCC is proposed for ONU activation, wavelength adjustment and activity monitoring. At the signal level, in [20,21], Caballero et al. studied the problem of mutual interference between signals by co-embedding AMCC, LTE-A and OTDR signals in a single transmitter, and realized the co-transmission of AMCC, OTDR and LTE-A signals. In previous studies, AMCC signals can be superimposed on PON signals in a number of different ways, including baseband modulation schemes and radio frequency (RF) pilot schemes. The baseband over-modulation scheme modulates the AMCC signals at baseband, while the RF pilot tone scheme up converts the baseband AMCC signals to the appropriate RF frequency. Fujitsu company uses three different modulation methods PSK, FSK and ASK on SFP+ transceivers from different vendors to achieve AMCC signaling at 100Kbps [22]. We once used baseband nonlinear modulation technology to increase the AMCC transmission rate to 10Mbps in a 10-Gbps PON system while satisfying the 1dB power loss rule [15].
However, most of these studies have focused on the 10-Gbps PON system. With the accelerated expansion of 5G networks and the continuous evolution of service content, higher requirements will be placed on the capacity and delay of the transmission network. Fronthaul/backhaul PON networks will develop to 25 Gbps or even higher line rate [19]. Experiments show that using a simple DSP and SOA, 50 Gbps PAM4 TDM-PON can support a link loss budget of more than 26 dB [23]. In [24], we have proposed a method to achieve AMCC transmission up to 20 Mbps in a 50 Gbps PAM4 PON system. NTT also investigated the feasibility of adding AMCC signals in a simplified coherent system with 25 Gbps QPSK-signal [25]. AMCC will still play an important role in wavelength control and OAM transmission, while future systems may have higher requirements for AMCC, such as carrying more information, reducing power penalty and minimizing the cost brought by AMCC.
In this paper, for a single wavelength 25-Gbps WDM-PON system, we use a transmitter architecture with a Distributed Feed-Back (DFB) laser coupled with a Mach-Zehnder Modulator (MZM) to achieve nonlinear baseband modulation of AMCC by controlling the DC bias signals of the MZM. At the receiver side, we propose a low-complexity interference cancellation (IE) method for AMCC channels to suppress the interference caused by WDM-PON signals, and this method can significantly reduce the BER of AMCC signals. The method obtains the power of PON signals and AMCC signals by analyzing the statistical characteristics of the received signals, employs a simplified PON signal reconstruction method based on the characteristics of nonlinear modulation. The reconstructed PON signals are applied to the original received AMCC signals through a decimation operation between the filter and the signals to achieve improved signal-to-noise ratio (SNR) by eliminating interference. The operations mentioned above have low complexity and can be easily implemented by analog circuits, which makes the method an effective way to improve the quality of AMCC signals. It is experimentally verified that with the help of this IE method, AMCC transmission rates up to 10 Mbps and even 20 Mbps under certain conditions can be achieved using various modulation depths, which is very helpful for the application of WDM-POM in 5G MFH.
The remainder of this paper is organized as follows. In Section II, we introduce the principle of WDM-PON architecture for 5G MFH and design an IE method based on statistical signal characterization, which can greatly improve AMCC signal quality. In Section III, the proposed method is experimentally demonstrated in a 25 Gbps OOK signal transmission system. With the help of nonlinear baseband modulation and IE algorithm, we improve AMCC up to 20 Mbps rate on 25 Gbps channel. Finally, we conclude this paper in Section IV.
2. Proposed AMCC superimposition and extraction for WDM-PON
The feasibility of WDM-PON in 5G fronthaul systems has been shown in previous studies. The concept of centralized radio access network (C-RAN) has been introduced. This concept involves two types of equipment: a centralized unit/distributed unit (CU/DU) and remote unit (RU). As shown in Fig. 1, in 5G MFH, CU/DU is connected to RUs via WDM-PON, where CU/DU is connected to the upper layer of OLT. OLT and ONU are connected through the optical distribution network, and the signals at the OLT end are transmitted through the power divider. Distributed to multiple ONUs, each ONU is connected to the RU, and they together form a fronthaul network.
As a network management and control channel, AMCC transmits management and control information between the OLT and the ONU. AMCC is mixed and transmitted with PON signals in the OLT. On the ONU side, the AMCC signals are extracted and detected to manage channel parameters, such as wavelength and power. In order to superimpose AMCC, we choose the nonlinear baseband modulation method. At the receiver, the AMCC signals can be restored through a simple filter, and the signal quality can be improved through a low-complexity IE method as follows.
2.1 Non-linear baseband modulation of AMCC signal
With the promotion of 5G applications, the original 10-Gbps PON system rate has been saturated, 25-Gbps PON can significantly increase the capacity of the fronthaul network. In order to superimpose the AMCC signal into the single wavelength 25-Gbps PON signal, a DFB laser is utilized as the light source, and a LiNbO3 intensity modulator is used to superimpose the AMCC signal as a bias signal into the PON signal. Figure 2 shows the structure of AMCC superimposition based on baseband over modulation.
At the Tx side, the AMCC is modulated on the PON signals by a nonlinear baseband modulation scheme to form an optical combined signal. The figure also shows how the modulator is connected in this case. The PON signal is imported from the RF port of the modulator while the AMCC signal is imported from the bias port of the modulator.
After the superimposition operated by the modulator, the output optical signal can be formulated as:
Figure 3(a) shows the spectral relationship between the AMCC (10Mbps OOK) and PON (25Gbps OOK) signals after superimposition. Compared with the PON signal, the AMCC occupies a small frequency band, but it has a higher spectral density. To reduce the interference of AMCC signals to PON signals, we conduct pulse shaping and bandwidth limitation on AMCC signals at the transmitting side.
From Fig. 3(b), it can be further seen that in the AMCC band, the PON signal is a full-band white noise like interference. Therefore, we cannot use simple methods of spectrum separation, such as filters, to remove the interference from the PON directly. We perform a low-complexity Interference Elimination (IE) process on AMCC at the receiving end, which can improve the BER performance of AMCC signals.
Fig. 3. (a) Signal spectrum after the AMCC (10Mbps OOK) and PON (25Gbps OOK) signals are superimposed. (b) Interference caused by PON in AMCC Band.
2.2. Proposed IE method for AMCC extraction
The nonlinear modulation scheme allows the AMCC signal to affect only upper eyelid of the PON signal eye diagram. At the Rx side, the emitted combined signal is fed into a photodiode (PD) for photoelectric conversion. The converted electrical signal (received combined signal) is then split into two paths by a splitter. One of the paths is used for PON signal detection and the other is used for AMCC signal detection. The signal used for AMCC extraction passes through an interference elimination (IE) module, whose workflow is shown in Fig. 4.
The IE module includes two main parts, AMCC Signal Extraction and Interference Signal Extraction. In the part of AMCC Signal Extraction, a low-pass filter which matches the bandwidth of the AMCC signal is used. The output signal of this filter will contains the AMCC signal and the low-frequency part of the PON signal mixed together. In the part of Interference Signal Extraction, the signal first passes through a Signal Statistical Characterization module for analyzing the energy probability density function (PDF) of the signal. According to the principle of nonlinear modulation described in Eq. (1), when the output signal is low-level, regardless of whether the AMCC is superimposed, the change in signal amplitude is very small, even smaller than the amplitude of the noise introduced in the channel. The amplitude change caused by the superposition of AMCC signals cannot be observed in the corresponding time domain waveform, and there is only one peak in the power distribution at this time. Oppositely, when the output signal is high-level, it is obvious that the AMCC signal is superimposed on the PON signal. It makes the original high level of the PON signal split into two different amplitudes, and there should be two peaks in the power distribution. This can be seen by the transmit signal waveform in Fig. 2. Therefore, ideally the synthesized signal can be approximated as a three-level signal, where the three levels are defined as PNoise, PPON, PCombined. PPON and PCombined satisfy the following condition:
where PAMCC is the estimated power level of the AMCC signal. After transmission, the waveforms of the received signals and their corresponding PDF curves are shown in Fig. 5.From Fig. 5(a) we can see that the signal waveform at the receiver side still maintains the characteristics of the transmitter side. Figure 5(b) shows the PDF curve corresponding to the received signal. Obtaining PDF from the received signal is a statistical process. At the receiver, the received signal is sampled. Then the amplitude of each sample is recorded and compared with the pre-defined thresholds of different amplitude bins. Different bins cover different signal samples determined by the corresponding amplitude thresholds. By counting the sample numbers of different bins, the PDF of the received signal can be derived. Although the PDF is broadened due to noise, we can still capture three peaks in the curve, and we have marked these peaks in the figure. In the case of nonlinear modulation, the power distribution has only one peak if the signal of the transmitter is at low-level. Thus the peak on the left corresponds to PNoise. The two peaks on the right side correspond to the two values of the transmitter at high-level, PPON and PCombined. The difference between the two peaks is the amplitude of the superimposed AMCC signal, which is the PAMCC in Eq. (2). Once the AMCC amplitude is obtained, the PON signal can be reconstructed by removing it. Thereafter we use PPON as a threshold to reconstruct the PON signal by using it to limit the signal amplitude, and the reconstructed PON signal is then used for IE operation of the AMCC signal. More specifically, we feed the original received signal into a low-pass filter, whose bandwidth should be set so that the AMCC signal can pass through and minimize the energy of the PON signal. For the OOK signal, the low-pass filter bandwidth is usually set to 0.7 to 1 times of the signal rate. At the same time, the reconstructed PON signal is fed into a module named Interference Extraction, this module contains a low-pass filter with the same parameters as the AMCC Signal Extraction module, and the output is the interference generated by the PON in the AMCC band. Finally, we will operate the output signal of the two filters, which can perform a simple subtraction operation to eliminate the AMCC in-band noise generated by the PON signal, and the calculated signal is the final output signal of the IE module. In the process, the reconstructed PON signal can also be obtained using limiting amplifier (LA) and clock & data recovery (CDR). However, for this method, the PON signal passes through one more LA than the directly extracted AMCC signal. Then, the signal low-pass filtered laterly contains not only the interference of the PON in the AMCC band, but also the additional interference brought by the LA in its band.
In this scheme, we superimpose AMCC onto the PON signal by nonlinear-baseband modulation using an MZM. At the receiver side, based on the fact that the AMCC signal only exhibits this nonlinear baseband modulation when the PON signal is high, we reconstruct the PON signal by power distribution characteristics. At the receiver side, the reconstructed signal is then applied to the directly extracted AMCC signal by filtering and subtracting to eliminate interference. With a low complexity of these operations, which can be easily implemented by analog circuits, this method is an effective way to improve the quality of AMCC signals.
Interference cancellation operations introduce additional delay to AMCC demodulation, mainly from the operation of obtaining PDF. The sampled signal should contain all levels of AMCC signal. For example, at least 2 AMCC symbols are needed to obtain the PDF containing effective information for two-level modulation. In order to obtain more precise PDF, the sampling window should cover 8 or more AMCC symbols. In the WDM-PON system, the ONU has to communicate with the OLT via AMCC to determine the uplink/downlink wavelength. By employing the proposed method, transmit rate of AMCC is increased largely and the overall registration time for ONU is not going to be worse. The detailed analysis is presented in the next section.
3. Experimental results and discussions
3.1. Experimental configuration
Figure 6 illustrates the block diagram of the experimental setup. The shaped and bandwidth limited electrical AMCC signal (10 Mbps and 20 Mbps) is generated from a signal generator (Rigol DG992, 250 MSa/s). The 25 Gbps OOK PON signal is generated by an arbitrary waveform generator (AWG, Keysight M8195A, 65 GSa/s). The two signals are combined in a LiNbO3 intensity modulator (Ixblue MXAN-LN series), in which the optical output power is approximately 5 dBm. The optical signal is transmitted via 10 km standard single mode fiber (SSMF). A variable optical attenuator (VOA) is used to control the received optical power (ROP). After Photon Diode (PD, Thorlabs DXM30BF) and an electrical amplifier (EA, SHF S807 C), the detected signal is sent to a real-time oscilloscope (Keysight DSAX96204Q, 63 GHz bandwidth). The channel is sampled at 80 GSa/s. The sampled signal is divided into two paths. One is for PON BER calculation, and the other is sent to the IE Module. The proposed IE Module is used to improve the AMCC signal quality. The detected PON and AMCC signals are outputted separately. The waveform of received signal, which contains 25 Gbps OOK PON signal and 10 Mbps AMCC signal is also shown in the figure.
According to Eq. (1) of nonlinear baseband modulation, a set of parameters is determined in the experiment so that it satisfies the condition that the low and high level PON signals behave differently after superimposing AMCC signals. And the superimposed effect of AMCC can be reflected on only one of the levels. For example, When the value of modulation index is ${V_\pi }$/30, We can get the corresponding signal power and calculate the modulation index as:
In Eq. (3), P00 and P01 refer to the cases that the PON single is modulated as “0” while the AMCC signal is modulated as “0” and “1” respectively. P10 and P11 refer to the cases that the PON single is modulated as “1” while the AMCC signal is modulated as “0” and “1” respectively. In this case, we can observe that the AMCC signal is superimposed on the signal waveform at high levels, as shown in the Waveform in Fig. 2. Similarly, the AMCC can be superimposed on the PON signal with different amplitudes by adjusting the bias voltage of the MZM. AMCC signal rate is up to 20Mbps in our experiments which has an analog bandwidth of 12 MHz. The bias port of the MZM is chosen to match this bandwidth requirement.
3.2. Results and analysis
3.2.1. AMCC usability analysis
According to the relevant standards, the impact of superimposed AMCC on PON performance is limited. That is, when AMCC is superimposed, the power budget penalty @BER = 10−5 at the receiving end cannot exceed 1 dB. Therefore, we first evaluate the BER of the PON signal after superimposing AMCC to determine the range of parameters used for the AMCC signal, such as rate and modulation depth. Figure 7 shows the BER curves of the PON signal after superimposing AMCC with different parameters. It indicates that when the AMCC rates are 10Mbps and 20Mbp, a modulation depth of 5% or 10% can satisfy the 1dB penalty of PON, and this condition cannot be satisfied when the modulation depth reaches 15%. Therefore, the modulation depth needs to be controlled at 10% or lower in the experiment of testing AMCC signals.
Fig. 7. PON signal BER curve with different AMCC signals: (a) 10 Mbps AMCC Superimposed; (b) 20 Mbps AMCC Superimposed.
3.2.2. AMCC performance analysis
In this section, AMCC performance will be analyzed. We will see that the BER performance of AMCC has been improved by using the proposed IE module. As shown in Fig. 8(a), the combined signal is displayed as the blue curve, and the green one represents the reconstructed PON signal. After removing the AMCC from the combined signal, the reconstructed PON signal hardly contains any information of AMCC and can be used for further processing. Then the reconstructed PON signal passes through the interference extraction process which contains a low-pass filter, and its output contains only the interference in the AMCC signal band.
Fig. 8. (a) The measured one path of the combined signal and the reconstructed PON signal at the receiver. (b) The measured one path of the combined signal and the reconstructed PON signal at the receiver. (c) Eye of AMCC with in-band PON signal. (d) Eye of AMCC after Interference elimination.
Figure 8(b) shows the waveform of three different signals, where the blue curve represents the result of the combined signal after LPF processing and the green one is the result of the reconstructed PON signal after LPF processing. The output signal after IE is obtained by subtracting the above two waveforms, which is marked in black. Traditional AMCC extraction uses the blue curve as the received AMCC signal. As can be seen from the previous spectrogram, the AMCC frequency band contains a large number of PON signal components, which cannot be removed by LPF filtering, resulting in the situation that the signal is still strongly interfered by the PON signal. Accordingly, we add a reconstructed PON signal to assist in the interference cancellation. The reconstructed PON signal is filtered by a LPF which has the same bandwidth with AMCC, to obtain the interference signal in the AMCC frequency band, and then this part of the signal is removed from the conventional received AMCC signal. As shown in Fig. 8(b), the signal obtained by the proposed method (black curve) has much less fluctuation than that obtained by the traditional method (blue one), which indicates that the interference of the signal is reduced and the BER is further decreased. This improvement can be observed more visually in the eye diagrams, which are shown in Figs. 8(c) and (d) for the blue and black waveforms, and it is clear from the comparison of the two images that the signal SNR has improved significantly after the IE operation.
In Fig. 9, we can see that IE brings a certain improvement to the AMCC with different parameters. The figure shows the eye diagram of the received AMCC signal with or without IE, where the data rate of the AMCC signal is 10 Mbps and the ROP is -10 dBm. The modulation index is set to 5% and 10%, separately. In both cases, the eyelids are significantly thinner after IE, and larger eyes are observed. These improvements show that the IE method performs well in improving the quality of the received AMCC signal.
Fig. 9. Eye-diagram of the AMCC signal with the ROP of -10 dBm: (a) 10 Mbps-5% modulation index w/o IE, (b) 10 Mbps-5% modulation index w/ IE, (c) 10 Mbps-10% modulation index w/o IE, (d) 10 Mbps-10% modulation index w/ IE.
Figure 10 shows the relationship between BER and ROP for AMCC signals when the modulation index is set to 5% and 10%. The rate is set to 10 Mbps, and 20 Mbps, respectively. All of these settings can satisfy the 1 dB optical power penalty of the PON signal. As can be seen from the figure, the AMCC signal with a lower rate has more advantages in BER performance, because considering the interference caused by the PON signal, the AMCC signal with a high data rate will be affected by more in-band interference. The IE module extracts and removes the interference components by analyzing the signal characteristics. With the help of IE module, the BER performance of AMCC has been greatly improved.
Fig. 10. BER of the detected AMCC signal with different modulation index in different data rates: (a) 10 Mbps 5%, (b) 10 Mbps 10%, (c) 20 Mbps 5%, and (d) 20 Mbps 10%.
Higher modulation index can help improve the AMCC signal quality, but it will bring more interference to PON signal. In order to limit the power penalty within 1 dB, the AMCC modulation index cannot exceed 10%, so the higher modulation index has to be given up for our experimental setup. As shown in Fig. 10(b), the BER of AMCC can be lower than the black line, that means, by using 20% soft-decision forward error correction (SD-FEC), AMCC signal can achieve to 20 Mbps at 10% modulation index. And at lower communication rates, such as a rate of 10 Mbps and a modulation index of 10%, the BER can be lower than the gray line, thus a more efficient 7% HD-FEC can be used to improve communication efficiency.
4. Conclusion
In this paper, we propose a nonlinear baseband modulated AMCC superimposition method using MZM in 25-Gbps PON system, and realize a low-complexity IE method with signal statistical characteristics to extract the AMCC. We first tested the 25-Gbps PON signal with AMCC superimposed, and by evaluating the BER curve, we determined the limit of AMCC rate and modulation depth that can match the system penalty requirement. And then we further analyzed the transmission performance of AMCC. By eliminating the interference of the PON signal, the quality of the AMCC signal is greatly improved, and the bit error rate of the signal transmission is reduced. With the proposed method, the BER of 10 Mbps and 20 Mbps AMCC signals can be lower than the FEC threshold, while the penalty of the system can meet the requirements. The system has low complexity and is easy to implement, which increases the feasibility for the application of WDM-PON in 5G MFH. The higher transmission rate will bring a wider range of application scenarios for AMCC.
Funding
National Key Research and Development Program of China (2019YFB1802904); National Natural Science Foundation of China (U21A20454).
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.
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