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EE Times原文发布 09-01 22:27Radar 收录 09-01 23:01查看原文 ↗

链路预算在连接器处决定

The Link Budget Is Decided at the Connector
中文摘要

文章指出,扩展光学系统的链路预算由连接器和硅光子平台内部决定,最大的可恢复损耗位于连接器和硅光子平台。

原文深度解读

本文由Mixx Technologies CEO Vivek Raghuraman撰写,发布于2026年9月1日,讨论扩展光学系统中链路预算的重要性,指出连接器和硅光子平台是最大可恢复损耗所在。文章涉及硅光子、VCSEL、TFLN、微LED和磷化铟等材料,关键数字包括连接器损耗2.5-3 dB、平台损耗10-12 dB、Mixx平台实现<1 dB波导到光纤损耗和<0.5 dB光纤到光纤损耗,以及恢复约60%链路预算。与电子元器件供应链相关,强调连接器生态系统的分散性和成本影响。

  • 文章指出,扩展光学系统的链路预算由连接器和硅光子平台内部决定,最大的可恢复损耗位于连接器和硅光子平台,两者损耗分配约为60/40。
  • 作者引用Geoff Tate六月文章,称约99%的激光功率在到达接收器前损失,表明光学损耗与成本紧密相关。
  • 连接器损耗高的原因在于端到端路径由光纤制造商、连接器组装公司、连接器公司和硅光子供应商四个独立生态系统构成,每个环节按自身规格设计,导致结构性损耗约2.5-3 dB。
  • 连接器内部有三个能量损耗点:波导-透镜接口、透镜-光纤接口和波导接口,其中模式扩展锥需将光学模式扩展30倍,但行业目前仅达到3-5微米模式(约10倍扩展)。
  • Mixx的HBxIO平台通过三个向量恢复链路预算:连接器(SxC™实现<1 dB波导到光纤损耗和<0.5 dB光纤到光纤损耗,恢复约40%)、平台(亚8 dB vs 典型10-12 dB,恢复约20%)、DSP(作为前两者的下游结果),总计恢复约60%。
  • Mixx在晶圆级验证链路,集成光纤连接器并测试完整组装流程(7-8条链路),而当前没有连接器在单一晶圆级流程中集成和测试。

供应链影响

  • 连接器生态系统的分散性可能导致供应链协调成本增加,但统一设计框架可能降低整体损耗,从而影响连接器组件的采购策略。
  • 低损耗连接器和平台可能减少对超高性能激光器的需求,从而影响激光器供应链的成熟度和投资方向。
  • 晶圆级集成和测试可能改变制造流程,使连接器供应商与半导体代工厂更紧密合作,可能重塑供应链分工。
  • 恢复的链路预算可能允许使用更低功率激光器,从而降低激光器成本,但取决于良率和可靠性曲线。
  • 行业向扩展光学过渡可能推动连接器和激光器成本下降,类似DRAM而非GPU,但取决于规模化部署速度。

系统解读,仅作为判断线索,不构成备货、出货、涨价或投资建议。

正文内容 · AI翻译

作者:Vivek Raghuraman,Mixx Technologies首席执行官兼联合创始人。

2026年9月1日

0

链路预算是行业在扩展光学过渡升温时的衡量工具。最大的可恢复损耗位于连接器和硅光子平台内部。

当今每个光网络平台都由链路预算定义,它计算网络中的每个功率增益或损耗,决定信号是否足够强以到达接收器并正常工作。这仍然是评估当前竞争扩展光学材料的正确视角。硅光子、垂直腔面发射激光器(VCSEL)、薄膜铌酸锂(TFLN)、微LED和磷化铟都在评估中。演示可以证明材料能否承载信号。但链路预算仍然是衡量标准,决定它们能否以部署所需的功率、密度和成本承载信号。在扩展光学中,每恢复一个dB都成为架构余量,最终转化为经济优势。

磷化铟表现强劲。但扩展架构所需的高密度应用对其构成挑战。TFLN正在取得实际进展,历史上提供用于设备和验证工作的参考调制器。它现在转向可插拔收发器,并且今天主要仍是可插拔收发器平台。这是一条不同的采用路径,使其扩展时机不同,而非薄弱。VCSEL和微LED都在评估中,作为有前景但尚需证明的路径。

硅光子作为高密度扩展的解决方案脱颖而出。尽管有高功耗和有限传输距离的批评,但我们需要明确:这些批评不是寻找替代方案的理由。它们是需要解决的工程问题。有用的问题不是哪种奇异材料最受青睐,而是哪种架构能在系统所需的密度下闭合端到端链路预算。探索激光功率实际去向,以及为什么最大损耗累积在那些地方,我们会发现答案贯穿系统中最不起眼的硬件(以及为什么这正是关键)。

作者:Vivek Raghuraman,Mixx Technologies首席执行官兼联合创始人。2026年9月1日

由MRPeasy 2026年9月1日

这些材料的性能很重要,但它只是更大系统中的一个方面。光源、连接器、光学引擎、平台、接收路径和电恢复都从同一功率中汲取。你不能将材料选择与围绕它的架构和工艺决策分开。这就是为什么链路预算定义了每个投入生产的平台。

对于硅光子,链路预算是我们面临的最难问题,随着共封装光学的出现似乎变得更难。激光器是分离的。因为它不能集成在同一封装上,架构增加了一个激光器必须克服的链路。更高的调制带宽增加了硅光子平台内部的损耗,但激光功率并未以相同速率扩展。工程挑战是真实的。对于硅光子,扩展的理由取决于完整路径能否实现更低损耗并作为集成链路验证。链路预算是定义性的设计因素。

更高的激光功率意味着更高的平台损耗,进而降低光信号完整性。这种退化变成电噪声,迫使使用前向纠错(FEC)。这些功率余量堆叠在链路预算中,正是FEC存在要纠正的。

在六月的一篇文章中,Geoff Tate将扩展过渡描述为由两个链路预算决定的竞赛:dB链路预算和美元链路预算。在他的分析中,他发现大约99%的激光功率在到达接收器之前损失。这清楚地展示了设计问题。你不能将光学损耗和成本视为两个独立问题,因为检测前消耗的功率成为两者的一部分。从分贝到美元的路径非常短。

点击展开

功率去向

从光源开始,跟随功率从激光器到光电二极管。一个100 mW激光器在信号链起点约为20dBm。这个数字是整个预算,但不是接收器记录的。激光器产生固定量的光功率,路径中的每个站点在光电二极管获得之前都从中提取一部分。

功率损耗从激光源本身开始,并在进入光学引擎的连接器处累积。当信号穿过硅光子平台时,调制和内部光路消耗其功率余量份额,产生更多损耗。一旦到达接收器侧,连接器路径成为另一个功率损耗站点,然后光电二极管转换剩余光信号。到那时,激光器产生的大部分功率已在途中消耗。

连接器路径和平台共同消耗了可用链路预算的绝大部分。它们之间的具体分配约为60/40。这是工程努力可以找到最多可恢复余量的地方。在检查这一点之前,必须理解更高输出功率的激光器本身并不能解决架构问题。信号必须通过平台并以足够完整性到达检测器,同时避免将过多FEC工作转移到电域。光源、光路和电恢复保持耦合。

底线:连接器和平台是可恢复余量所在。减少那里的损耗,系统可以决定如何利用恢复的预算。保留损耗,系统将在信号链的其他地方付出代价。

连接器

你可能首先问为什么连接器损耗如此之高?简单答案是没有人端到端拥有路径。连接器生态系统分布在光纤制造商、连接器组装公司、连接器公司和硅光子供应商之间。链路预算不是由任何单一节点设定;它在四个独立生态系统之间的接缝处累积。

考虑连接器必须做什么。其中有三个能量损耗点,包括波导-透镜接口、透镜-光纤接口和波导接口本身。第一个接口包括模式扩展锥,这是挑战中最难的部分。它必须以最低可能损耗将光学模式扩展30倍,然后持续保持。它是一个三角形结构,几乎像光在手电筒中扩展,模式通过锥体时逐渐打开。锥体设计与形成它的工艺紧密相关,意味着它不是购买的部件,而是制造的结构。

达到30倍本身很难;行业今天仍在努力实现三到五微米的模式,约10倍扩展。保持这一点是更大的挑战。硅光子工艺必须一致地扩展模式,其后的每个接口必须通过不同材料系统保持它,每个系统都有自己的制造公差,直到光到达光纤。这是一个多物理问题,结合热、机械和光学。

现在考虑谁构建路径。光纤、连接器组装、连接器和硅光子接口来自不同生态系统。这些独立部件之间的损耗在路径完全组装时成为共享链路预算。每个供应商按自己的规格设计,各自承担预算份额。这些都不是任何一家公司的糟糕工作;损耗是结构性的。很容易看出为什么连接器的损耗数字最终约为2.5到3 dB的耦合损耗。

鉴于这些因素,连接器为何是杠杆就变得清晰。它位于工艺设计、光学模式控制、组装和系统余量交汇点。通过将这些部件纳入共同设计框架,它创造了回收链路预算重要部分的机会。

点击展开

三个链路预算恢复向量

我们通过Mixx的HBxIO平台将整个路径置于同一屋檐下,将端到端光信号链交付到统一设计和工艺边界。这样做,我们能够沿三个向量设计链路预算的恢复。

第一个向量是连接器,Mixx的SxC™是自上而下集成的连接器,实现端到端波导到光纤损耗<1 dB,光纤到光纤损耗<0.5 dB。这大约恢复连接器处40%的损耗。连接器将上述所有接缝视为单一链接设计问题,而非四个独立指定部件。

我们解决的第二个向量是引擎和平台,我们共同优化电子和光子,并调整CMOS工艺以实现高密度、低损耗硅光子平台。结果是亚8 dB平台,而典型为10到12 dB,进一步恢复约20%的预算。

下一个向量是DSP。恢复的光学余量意味着更少噪声到达电域,因此链路承载更少数字信号处理开销用于信号恢复。这个向量在前两个向量下游运行,是它们的结果。

由此产生的恢复约为链路预算总量的60%,为架构师提供物理红利。恢复的预算可以三种方式重新投资到架构中。一种方式是将功率分配到更多通道,通过1:4或1:8分路实现更高基数。另一种是运行更低功率激光器。或者消除对高级DSP的需求。通过在累积光学损耗变成电噪声和信号恢复工作之前恢复功率,架构在功率分配上可以更灵活。

延迟也可以用同样的红利购买,我将在未来文章中详细说明。

在晶圆级验证

恢复预算是论证的一半。另一半是链路能否制造、测试和鉴定。超大规模数据中心不会部署实验室结果;他们部署可以构建、测试和批量重复的东西。

Mixx的方法将链路优化移至晶圆级,在光路与计算芯片或交换ASIC集成之前。在那里,它集成光纤连接器;无源光纤贴装使其在半导体生态系统内可制造。然后通过完整组装流程验证和测试同一连接器:从光纤到芯片,再到电信号输出,七到八条不同链路,全部在晶圆级。这意味着测试边界遵循工作链路,而不是停在单个部件。

以前这些是来自不同生态系统供应商的零散部件,现在你有一个构建到晶圆级工艺中的单一系统。以前实际系统余量仅在系统构建时可见,现在你对连接器吸收的功率有一致、前置的理解。

今天没有连接器在单一晶圆级流程中集成和测试。

从dB到美元:恢复总成本

每恢复一个dB就是不必购买的激光功率,使工程决策归结为总拥有成本。性能是推动美元的因素,从分贝到美元的链条很短。

行业向高密度扩展光学推进引发了对超高功率激光器的需求。这类新型激光器尚处于早期,仍在开发中且未鉴定。可靠性曲线随更高功率激光器指数下降。我们的端到端链路优化推迟了对它们的需求,意味着超大规模数据中心不必等待新兴激光器类别成熟。

良率遵循同样逻辑。激光器良率随输出功率增加而下降。在更低功率下闭合链路让运营商使用更高插墙效率的激光器,这来自良率曲线中已经有效的部分。

然后规模改变成本结构。激光器和连接器是复杂组件,但大致按类似规格制造。随着规模,它们沿成本曲线下降,更像DRAM而非GPU。DR激光器生态系统已为扩展就绪。将其重用于扩展延长了成熟生态系统的寿命,并让部署摊销现有生态系统。任何你重用或延长其生命周期的东西,自动开始下降成本曲线。

光学的推理经济学将由低损耗连接器和闭合链路预算的低功率激光器定义。这就是dB预算变成美元预算的地方。更低损耗改变了系统必须承担的部署负担。

为什么超大规模数据中心现在可以承诺

正确设置链路预算允许超大规模数据中心使用他们已经信任的经济学和光学技术从扩展过渡到扩展。首批先进光学部署,包括共封装和近封装方法,正在扩展中发生。通过减少损耗,运营商可以将相同的激光器、制造工艺和网络基础设施扩展到扩展,而不是同时改变技术基础和链路架构。

这种重用降低了过渡风险,延长了成熟生态系统的寿命,允许扩展系统接近当今部署的扩展基础设施的经济性。下一步是光学进入盒子,然后是批量部署。当解决方案提供受控损耗、验证制造、熟悉的激光器技术和基于恢复链路预算的经济模型时,超大规模数据中心将承诺。

最终,解决方案的衡量标准是超大规模数据中心能否自信地大规模部署它。

了解更多

MICROLED, PHOTONICS

By
Vivek Raghuraman, CEO and co-founder of Mixx Technologies.

09.01.2026

0

The link budget is the industry’s measuring tool as the transition to scale-up optics heats up. The largest recoverable losses are found at the connector and inside the silicon photonics platform.

Every optical networking platform today has been defined by link budgets, which account for every power gain or loss within a network, determining whether a signal is strong enough to reach the receiver and function properly. That remains the right lens for the materials now contesting scale-up optics. Silicon photonics, vertical-cavity surface-emitting lasers (VCSELs), thin-film lithium niobate (TFLN), micro-LEDs, and indium phosphide are all under evaluation. Demonstrations can show whether a material can carry the signal. Still, the link budget remains the measuring stick that will determine if they can carry the signal at the power, density, and cost a deployment requires. In scale-up optics, every recovered dB becomes architectural headroom, and ultimately, economic advantage.

Indium Phosphide has made a strong showing. High-density applications demanded by scale-up architectures challenge it. TFLN is making real inroads, historically supplying the reference modulators used for equipment and validation work. It is now pivoting into pluggable transceivers, and remains largely a pluggable transceiver platform today. That is a different adoption path, making its timing for scale-up different, not weak. VCSELs and micro-LEDs are both under evaluation as promising paths that still need to be proven.

Silicon photonics stands out as a solution for high-density scale-up. Despite the knocks against it being high power and limited reach, we need to be clear: those criticisms are not a reason to look elsewhere. They are an engineering problem that has to be solved. The useful question is not which exotic material achieves the most favor, but rather which architecture can close the end-to-end link budget at the density the system requires. Exploring where the laser power actually goes, and why the largest losses accumulate where they do, we’ll find that the answer runs through the least glamorous piece of hardware in the system (and why that’s the point).

By Vivek Raghuraman, CEO and co-founder of Mixx Technologies. 09.01.2026

By MRPeasy 09.01.2026

The performance of these materials matters, but it is only one aspect in a larger system. The source, connector, optical engine, platform, receive path, and electrical recovery all draw from the same power. You can’t separate a material choice from the architecture and process decisions around it. This is why link budgets define every platform that makes it to production.

For silicon photonics, the link budget is the hardest problem that we have, and it only seems to get harder with co-packaged optics emerging. The laser is disaggregated. Because it can’t be integrated on the same package, the architecture adds a link that the laser must overcome. Higher modulation bandwidths add loss inside the silicon photonics platform, but laser power is not scaling at the same rate. The engineering challenge is real. For silicon photonics, the case for scale-up rests on whether the complete path can be made lower loss and validated as an integrated link. The link budget is the defining design factor.

Higher laser power means higher platform loss, which in turn degrades optical signal integrity. This degradation becomes electrical noise, which forces forward error correction (FEC). These power margins stacked into the link budget are what FEC exists to correct.

In a June article, Geoff Tate framed the scale-up transition as a contest decided by two link budgets: the dB link budget and the dollar link budget. In his analysis, he found that on the order of 99% of laser power is lost before hitting the receiver. This clearly demonstrates the design issue in clear terms. You cannot treat optical loss and cost as two separate problems, because the power consumed before detection becomes part of both. The path from decibels to dollars is remarkably short.

Click to expand

Where the Power Goes

Start at the source and follow the power from the laser to the photodiode. A 100 mW laser is roughly 20dBm at the start of the signal chain. That figure is the entire budget, and is not what the receiver registers. The laser produces a fixed amount of optical power, and every station in the path extracts a cut of it before the photodiode is paid.

The loss of power starts at the laser source itself, and accumulates at the connector that enters the optical engine. More loss is achieved as the signal crosses the silicon photonics platform, where modulation and the internal optical path consume their share of the power margin. Once it advances to the receiver side, the connector path becomes another station for power loss before the photodiode can convert what is remaining of the optical signal. By that time, most of what the laser has produced was spent along the way.

The connector path and the platform together consume the large majority of the available link budget. The specific split between them is about 60/40. This is where engineering effort can find the most recoverable margin. Before examining this, it must be understood that a higher-output laser does not, by itself, solve the architectural problem. The signal has to survive the platform and reach the detector with adequate integrity, while avoiding transferring excessive FEC work into the electrical domain. The source, optical path, and electrical recovery remain coupled.

The bottom line: The connector and the platform are where recoverable margin can be found. Reduce loss there, and the system can decide how to leverage the recovered budget. Leave the loss in place, and the system will pay for it elsewhere in the signal chain.

The Connector

The first question you might ask is why the connector loss is so high? The simple answer is that no one owns the path end-to-end. The connector ecosystem is distributed across the fiber maker, the connector assembly company, the connector company, and the silicon photonics provider. The link budget is not set by any single point; it accumulates across the seams between four separate ecosystems.

Consider what the connector has to do. There are three points of energy loss within it, including the waveguide-to-lens interface, the lens-to-fiber interface, and the waveguide interface itself. This first interface includes the mode-expansion taper, which is the hardest piece of this challenge. It has to expand the optical mode 30x at the lowest possible loss, and then consistently maintain it. It is a triangular structure that is almost like how light expands in a torchlight, with the mode opening gradually as it moves through the taper. The taper design is tightly tied to the process that forms it, meaning it’s not a part you buy, but a structure that you fabricate.

Getting to 30x is itself hard; the industry today is still working toward a three- to five-micron mode, an expansion on the order of 10x. Maintaining this is the bigger challenge. The silicon photonics process has to expand the mode consistently, and every interface after it has to hold it through different material systems, each with its own manufacturing tolerances, until the light reaches the fiber. It’s a multi-physics problem spanning thermal, mechanical, and optical combined.

Now consider who builds the path. The fiber, connector assembly, connector, and silicon photonics interface arrive from separate ecosystems. The loss between these separate parts becomes a shared link budget when the path is fully assembled. Each provider engineers to its own specifications, each taking its share of the budget. None of this is bad work by any one company; the loss is structural. It’s easy to see why loss figures for the connector end up being around 2.5 to 3 dB of coupling loss.

Given these factors, it becomes clear why the connector is the lever. It sits at the point where process design, optical mode control, assembly, and system margin all meet. By bringing these pieces together in a common design framework, it creates an opportunity to reclaim a significant portion of the link budget.

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Three Link Budget Recovery Vectors

We are bringing the whole path under one roof through Mixx’s HBxIO platform, delivering an end-to-end optical signal chain into a unified design and process boundary. In doing so, we’ve been able to engineer the recovery of the link budget along three vectors.

The first vector is the connector, where Mixx’s SxC™ is a top-down integrated connector achieving an end-to-end waveguide-to-fiber loss of <1 dB and Fiber to fiber loss of <0.5dB. That recovers roughly 40% at the connector. The connector treats all of the seams described above as a single linked design problem, not four separately specified pieces.

The second vector that we address is the engine and the platform, where we co-optimize the electronics and photonics and tune the CMOS processing for a high-density, low-loss silicon photonics platform. The result is a sub-8 dB platform compared to a typical 10 to 12 dB draw, recovering roughly a further 20% of the budget.

The next vector is the DSP. Recovered optical margin means less noise reaches the electrical domain, so the link carries less digital signal processing overhead for signal recovery. This vector runs downstream of the previous two and is a consequence of them.

The resulting recovery is roughly 60% of the link budget total, producing a physics dividend for architects to engineer with. That recovered budget can be reinvested into the architecture in three ways. One way is to split the power across more channels, across one-to-four or one-to-eight splits for higher radix. Another is to run a lower power laser. Or eliminate the need for an advanced DSP. By recovering power before the accumulated optical loss becomes electrical noise and signal recovery work, the architecture can become more flexible in how that power is allocated.

Latency can also be bought with the same dividend, which I will unpack in a future piece.

Validated at the Wafer Level

Recovering the budget is half the argument. The other half is whether the link can be manufactured, tested, and qualified. Hyperscalers aren’t deploying lab results; they deploy what can be built, tested, and repeated at volume.

Mixx’s approach moves link optimization to the wafer level, before the optical path is integrated with the compute chip or the switch ASIC. There, it integrates the fiber connector; passive fiber attach is what makes this manufacturable within the semiconductor ecosystem. The same connector is then validated and tested through the complete assembly flow: from the fiber to the chip and through to the electrical signal going out, seven or eight distinct chains, all at the wafer level. That means the test boundary follows the operating link rather than stopping at an individual piece part.

Where previously these were piecemeal parts from different ecosystem vendors, now you have a single system constructed into a wafer-level process. Where previously the actual system margins became visible only when the system is constructed, now you have a consistent, up-front understanding of the power being absorbed at the connector.

No connector today is integrated and tested in a single wafer-level flow.

From dB to Dollars: Recovering Total Cost

Every dB recovered is laser power that does not have to be bought, making the engineering decision resolve into the total cost of ownership. Performance is what moves the dollar, and the chain from decibels to dollars is short.

The industry’s push toward high-density scale-up optics has created a call for ultra-high-power lasers. It is early days for this new class of lasers, which are still in development and not yet qualified. The reliability curve drops exponentially with higher-power lasers. Our end-to-end link optimization pushes out the need for them, meaning that hyperscalers don’t have to wait for a fledgling laser class to mature.

The yield follows the same logic. Laser yield falls as output power rises. Closing the link at lower power lets the operator use a laser with higher wall-plug efficiency, which is drawn from the part of the yield curve that already works.

Volume then changes the cost structure. Lasers and connectors are complex components, but are broadly made to similar specifications. With volume, they ride the cost curve down, acting more like DRAM than GPU. The DR laser ecosystem is already ready for scale-out. Reusing it for scale-up extends the life of a mature ecosystem and lets the deployment amortize the ecosystem already in place. Anything that you reuse, or whose life cycle you extend, automatically starts to drop the cost curve.

Inference economics for optics will be defined by the low-loss connector and the low-power laser that closes the link budget. This is where the dB budget becomes the dollar budget. Lower loss changes the deployment burden that the system must carry.

Why Hyperscalers can commit now

Getting the link budget right allows hyperscalers to move from scale-out to scale-up using economics and optical technology they already trust. The first advanced optical deployments, including co-packaged and near-packaged approaches, are occurring at scale-out. By reducing loss, operators can extend the same lasers, manufacturing processes, and network infrastructure into scale-up rather than changing both the technology foundation and the link architecture at once.

That reuse lowers transition risk and extends the life of a mature ecosystem, allowing scale-up systems to approach the economics of today’s deployed scale-out infrastructure. The next step is optics moving into the box, followed by volume deployment. Hyperscalers will commit when the solution offers controlled loss, validated manufacturing, familiar laser technology, and an economic model grounded in the recovered link budget.

Ultimately, the measure of a solution is whether a hyperscaler can confidently deploy it at scale.

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MICROLED, PHOTONICS

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