Ciena has unveiled its latest generation coherent DSP-ASIC. The device, dubbed WaveLogic Ai, follows Ciena’s WaveLogic 3 family of coherent chips which was first announced in 2012. The Ai naming scheme reflects the company's belief that its latest chipset represents a significant advancement in coherent DSP-ASIC functionality.
The WaveLogic Ai is Ciena's first DSP-ASIC to support two baud rates, 35 gigabaud for fixed-grid optical networks and 56 gigabaud for flexible-grid ones. The design also uses advanced modulation schemes to optimise the data transmission over a given link.
Perhaps the most significant development, however, is the real-time network monitoring offered by the coherent DSP-ASIC. The data will allow operators to fine-tune transmissions to adapt to changing networking conditions.
“We do believe we are taking that first step towards a more automated network and even laying the foundation for the vision of a self-driving network,” says Helen Xenos, director, portfolio solutions marketing at Ciena.
All those assumptions of the past [based on static traffic] aren't holding true anymore
Network Analytics
Conservative margins are used when designing links due to a lack of accurate data regarding the optical network's status. This curtails the transmission capacity that can be sent since a relatively large link margin is used. In turn, cloud services and new applications mean networks are being exercised in increasingly dynamic ways. “The business environment has changed a little bit,” says Joe Cumello, vice president, portfolio marketing at Ciena. “All those assumptions of the past [based on static traffic] aren't holding true anymore.”
Ciena is being asked by more and more operators to provide information as to what is happening within their networks. Operators want real-time data that they can feed to analytics software to make network optimisation decisions. "Imagine a network where, instead of those rigid assumptions in place, run on manual spreadsheets, the network is making decisions on its own," says Cumello.
WaveLogic Ai performs real-time analysis, making available network measurements data every 10ms. The data can be fed through application programming interfaces to analytics software whose output is used by operators to adapt their networks.
The network parameters collected include the transmitter and receiver optical power, polarisation channel and chromatic dispersion conditions, error rates and transmission latency. In addition, the DSP-ASIC separates the linear and non-linear noise components of the signal-to-noise ratio. An operator will thus see what the network margin is and allow links to operate more closely to the limit, improving transmissions by exploiting the WaveLogic Ai's 50-gigabit transmission increments.
"Maybe there are only a few wavelengths in the network such that the capacity can be cranked up to 300 gigabits. But as more and more wavelengths are added, if you have the tools, you can tell the operator to adjust,” says Xenos. “This helps them get to the next level; something that has not been available before.”
WaveLogic Ai
The WaveLogic Ai's lower baud rate - 35 gigabaud - is a common symbol rate used by optical transmission systems today. The baud rate is suited to existing fixed-grid networks based on 50GHz-wide channels. At 35 gigabaud, the WaveLogic Ai supports data rates from 100 to 250 gigabits-per-second (Gbps).
The second, higher 56 gigabaud rate enables 400Gbps single-wavelength transmissions and supports data rates of 100 to 400Gbps in increments of 50Gbps.
Using 35 gigabaud and polarisation multiplexing, 16-ary quadrature amplitude modulation (PM-16QAM), a 200-gigabit wavelength has a reach is 1,000km.
With 35-gigabaud and 16-QAM, effectively 8 bits per symbol are sent.
In contrast, 5 bits per symbol are used with the faster 56 gigabaud symbol rate. Here, a more complex modulation scheme is used based on multi-dimensional coding. Multi-dimensional formats add additional dimensions to the four commonly used based on real and imaginary signal components and the two polarisations of light. The higher dimension formats may use more than one time slot, or sub-carriers in the frequency domain, or even use both techniques.
For the WaveLogic Ai, the 200-gigabit wavelength at 56 gigabaud achieves a reach of 3,000km, a threefold improvement compared to using a 35 gigabaud symbol rate. The additional reach occurs because fewer constellation points are required at 56 gigabaud compared to 16-QAM at 35 gigabaud, resulting in a greater Euclidean distance between the constellation points. "That means there is a higher signal-to-noise ratio and you can go a farther distance," says Xenos. "The way of getting to these different types of constellations is using a higher complexity modulation and multi-dimensional coding."
We do believe we are taking that first step towards a more automated network and even laying the foundation for the vision of a self-driving network
The increasingly sophisticated schemes used at 56 gigabaud also marks a new development whereby Ciena no longer spells out the particular modulation scheme used for a given optical channel rate. At 56 gigabaud, the symbol rate varies between 4 and 10 bits per symbol, says Ciena.
The optical channel widths at 56 gigabaud are wider than the fixed grid 50GHz. "Any time you go over 35 gigabaud, you will not fit [a wavelength] in a 50GHz band," says Xenos.
The particular channel width at 56 gigabaud depends on whether a super-channel is being sent or a mesh architecture is used whereby channels of differing widths are added and dropped at network nodes. Since wavelengths making up a super-channel go to a single destination, the channels can be packed more closely, with each channel occupying 60GHz. For the mesh architecture, guard bands are required either side of the wavelength such that a 75GHz optical channel width is used.
The WaveLogic Ai enables submarine links of 14,000km at 100Gbps, 3,000km links at 200Gbps (as detailed), 1,000km at 300Gbps and 300km at 400Gbps.
Hardware details
The WaveLogic Ai is implemented using a 28nm semiconductor process known as fully-depleted silicon-on-insulator (FD-SOI). "This has much lower power than a 16nm or 18nm FinFET CMOS process," says Xenos. (See Fully-depleted SOI vs FinFET)
Using FD-SOI more than halves the power consumption compared to Ciena’s existing WaveLogic 3 coherent devices. "We did some network modelling using either the WaveLogic 3 Extreme or the WaveLogic 3 Nano, depending on what the network requirements were," says Xenos. "Overall, it [the WaveLogic Ai] was driving down [power consumption] more than 50 percent." The WaveLogic 3 Extreme is Ciena's current flagship coherent DSP-ASIC while the Nano is tailored for 100-gigabit metro rates.
Other Ai features include support for 400 Gigabit Ethernet and Flexible Ethernet formats. Flexible Ethernet is designed to support Ethernet MAC rates independent of the Ethernet physical layer rate being used. Flexible Ethernet will enable Ciena to match the client signals as required to fill up the variable line rates.
Further information:
SOI Industry Consortium, click here
STMicroelectronics White Paper on FD-SOI, click here
Other coherent DSP-ASIC announcements in 2016
Infinera's Infinite Capacity Engine, click here
Nokia's PSE-2, click here