With AI model size doubling every four months, the size of AI compute clusters is growing rapidly to keep up. Traditional data center front-end networks rely on optical interconnect for data movement with Terabits per second of connectivity and have been doubling data rate every 4 years. As the models grow it is also expected that the back-end GPU networks expand beyond the confines of the rack. Optical interconnects will be needed at distances of tens of meters with 10Tb/s data transfer rates and doubling every 2 years will be expected. How should optical interconnects best achieve this bandwidth increase and what is the best performance axis to push next? In this panel discussion we pose the question - “Is it better to scale with more wavelengths or by adding more fibers?” Join us to see if any of the panelists can convince you they have the right approach.

In order to overcome the capacity limitations of current lightwave systems based on the single-mode optical fiber, massively parallel transmission in the spatial domain [space-division multiplexing (SDM)] supported by extended parallelism in the frequency domain (ultrawideband (UWB) systems) must be used. This article reviews key aspects of parallel transmission systems as the only significant capacity scaling option going forward and discusses the various tradeoffs on an architectural level and a hardware integration level. In doing so, this article also serves as an introduction to the more detailed accounts of fiber-optic systems and their future scaling within this Special Issue of the Proceedings of the IEEE.

With joint contributions from academia and industry, this special issue provides a balanced overview of the area of fiber-optic network capacity scaling.

In this paper, we examine the information-theoretic security of multiple-input-multiple-output space-division multiplexed (MIMO-SDM) fiber-optic communication systems in the presence of multiple eavesdroppers. In particular, we analyze the achievable secrecy rate for the two special cases that reflect different capabilities of the eavesdroppers: independent eavesdroppers who do not share received information and colluding (cooperating) eavesdroppers who can combine and jointly process the received signals. Our results show that MIMO-SDM systems are robust against multiple independent tapping attacks, in the sense that the average achievable secrecy rate is strictly positive even with an infinite number of eavesdroppers. Though extremely difficult to implement in practice, if all the eavesdroppers could cooperate coherently, the average secrecy rate decreases quickly with the number of eavesdroppers. As such, to counter the colluding eavesdroppers, a combination of much higher SNR for the legitimate receiver and higher mode-dependent loss (MDL) for the eavesdroppers is needed.

Space-division multiplexed (SDM) fiber optic transmission systems can not only increase system capacity, but also achieve physical-layer security against fiber tapping attacks. In this paper, we examine the information-theoretic security of optical multiple-input-multiple-output (MIMO) SDM by evaluating the tradeoff between the achievable information rate and the confidentiality for different channel dynamics. In particular, we provide problem formulations for secure communication over these channels and study three types of secrecy capacities: 1) guaranteed capacity; 2) outage capacity; and 3) average capacity, each serving as a performance metric for a coding strategy tailored to a specific type of MIMO-SDM channel. We also assess the impact of key system parameters, such as the number of modes, the mode-dependent loss (MDL), and the signal-to-noise ratio (SNR), on the various secrecy capacities. Our results indicate that, with a proper design of channel codes that balance information rate and security, an SDM system has the potential of offering confidential data transmission at a rate that could be orders of magnitude higher than what can be achieved through other means of encryption. Moreover, we show that MDL, unavoidably induced by fiber tapping, can allow information-theoretic security even if the SNR of the eavesdropper's receiver is better than that of the legitimate receiver.

We study a class of robust network design problems motivated by the need to scale core networks to meet increasingly dynamic capacity demands. Past work has focused on one of two models. First, design the network for the known point-to-point peak demands. Second, design the network to support all hose matrices (all matrices not exceeding marginal bounds at the nodes). Both models may be too conservative if additional information on traffic patterns is available. We introduce a capped hose model to explore a range of traffic scenarios, which includes the above two as special cases. It is known that optimal network designs for the hose model are always determined by single-hub routing, and for the fixed-demand model are based on shortest-path routing. We demonstrate that a wider variety of routing templates is required to address the broader spectrum of capped hose matrices. We propose the use of hierarchical multihub routing templates, a generalization of hub and tree routing. Our empirical analysis is based on a heuristic for the resulting robust network design problem. These lead to two important findings: 1) designs based on multihub routing are often preferable to both hub and shortest path; 2) it may be possible for a carrier to sample their traffic in order to determine which type of routing is most cost-effective for their network.

We study a class of robust network design problems motivated by the need to scale core networks to meet increasingly dynamic capacity demands. Past work has focused on designing the network to support all hose matrices (all matrices not exceeding marginal bounds at the nodes). This model may be too conservative if additional information on traffic patterns is available. Another extreme is the fixed demand model, where one designs the network to support peak point-to-point demands. We introduce a capped hose model to explore a broader range of traffic matrices which includes the above two as special cases. It is known that optimal designs for the hose model are always determined by single-hub routing, and for the fixed-demand model are based on shortest-path routing. We shed light on the wider space of capped hose matrices in order to see which traffic models are more shortest path-like as opposed to hub-like. To address the space in between, we use hierarchical multi-hub routing templates, a generalization of hub and tree routing. In particular, we show that by adding peak capacities into the hose model, the single-hub tree-routing template is no longer cost-effective. This initiates the study of a class of robust network design (RND) problems restricted to these templates. Our empirical analysis is based on a heuristic for this new hierarchical RND problem. We also propose that it is possible to define a routing indicator that accounts for the strengths of the marginals and peak demands and use this information to choose the appropriate routing template. We benchmark our approach against other well-known routing templates, using representative carrier networks and a variety of different capped hose traffic demands, parameterized by the relative importance of their marginals as opposed to their point-to-point peak demands. This study also reveals conditions under which multi-hub routing gives improvements over single-hub and shortest-path routings.

The mutual information between a complex-valued channel input and its complex-valued output is decomposed into four parts based on polar coordinates: an amplitude term, a phase term, and two mixed terms. Numerical results for the additive white Gaussian noise (AWGN) channel with various inputs show that, at high signal-to-noise ratio (SNR), the amplitude and phase terms dominate the mixed terms. For the AWGN channel with a Gaussian input, analytical expressions are derived for high SNR. The decomposition method is applied to partially coherent channels and a property of such channels called “spectral loss” is developed. Spectral loss occurs in nonlinear fiber-optic channels and it may be one effect that needs to be taken into account to explain the behavior of the capacity of nonlinear fiber-optic channels.

Valiant's concept of randomized load balancing (RLB), also promoted under the name 'two-phase routing', has previously been shown to provide a cost-effective way of implementing overlay networks that are robust to dynamically changing demand patterns. RLB is accomplished in two steps; in the first step, traffic is randomly distributed across the network, and in the second step traffic is routed to the final destination. One of the benefits of RLB is that packets experience only a single stage of routing, thus reducing queueing delays associated with multi-hop architectures. In this paper, we study the queuing performance of RLB, both through analytical methods and packet-level simulations using ns2 on three representative carrier networks. We show that purely random traffic splitting in the randomization step of RLB leads to higher queuing delays than pseudo-random splitting using, e.g., a round-robin schedule. Furthermore, we show that, for pseudo-random scheduling, queuing delays depend significantly on the degree of uniformity of the offered demand patterns, with uniform demand matrices representing a provably worst-case scenario. These results are independent of whether RLB employs priority mechanisms between traffic from step one over step two. A comparison with multi-hop shortest-path routing reveals that RLB eliminates the occurrence of demand-specific hot spots in the network.

Fiber-optic communication systems form the high-capacity transport infrastructure that enables global broadband data services and advanced Internet applications. The desire for higher per-fiber transport capacities and, at the same time, the drive for lower costs per end-to-end transmitted information bit has led to optically routed networks with high spectral efficiencies. Among other enabling technologies, advanced optical modulation formats have become key to the design of modern wavelength division multiplexed (WDM) fiber systems. In this paper, we review optical modulation formats in the broader context of optically routed WDM networks. We discuss the generation and detection of multigigabit/s intensity- and phase-modulated formats, and highlight their resilience to key impairments found in optical networking, such as optical amplifier noise, multipath interference, chromatic dispersion, polarization-mode dispersion, WDM crosstalk, concatenated optical filtering, and fiber nonlinearity