We present a telecom-native auction mechanism for allocating bandwidth and time slots across heterogeneous-delay networks, ranging from low-Earth-orbit (LEO) satellite constellations to delay-tolerant deep-space relays. The Lorentz-Invariant Auction (LIA) treats bids as spacetime events and reweights reported values based on the \emph{horizon slack}, a causal quantity derived from the earliest-arrival times relative to a public clearing horizon. Unlike other delay-equalization rules, LIA combines a causal-ordering formulation, a uniquely exponential slack correction implied by a semigroup-style invariance axiom, and a critical-value implementation that ensures truthful reported values once slacks are fixed by trusted infrastructure. We analyze the incentive result in the exogenous-slack regime and separately examine bounded slack-estimation error and endogenous-delay limitations. Under fixed feasible slacks, LIA is individually rational and achieves welfare at least \(e^{-λΔ}\) relative to the optimal feasible allocation, where \(Δ\) is the slack spread. We evaluate LIA on STARLINK-200, INTERNET-100, and DSN-30 across 52,500 baseline instances with market sizes \(n\in\{10,20,30,40,50\}\) and conduct additional robustness sweeps. On Starlink and Internet, LIA maintains near-efficiency while eliminating measured timing rents. However, on DSN, welfare is lower in thin markets but improves with depth. We also distinguish winner-determination time from the background cost of maintaining slack estimates and study robustness beyond independent and identically distributed (iid) noise through error-spread bounds and structured (distance-biased and subnetwork-correlated) noise models. These results suggest that causal-consistent mechanism design offers a practical non-buffering alternative to synchronized delay equalization in heterogeneous telecom infrastructures.

翻译：我们提出了一种电信原生的拍卖机制，用于在具有异构延迟的网络（从低地球轨道卫星星座到容忍延迟的深空中继）中分配带宽和时隙。洛伦兹不变拍卖 (LIA) 将出价视为时空事件，并基于因果量“地平线松弛”对报告值进行重新加权，该量是根据相对于公共清算地平线的最早到达时间推导出的。与其他延迟均衡规则不同，LIA 结合了因果排序公式、由半群式不变性公理隐含的唯一指数松弛校正，以及临界值实现机制，该机制确保一旦由可信基础设施固定松弛量，报告值即为真实值。我们分析了外生松弛机制下的激励结果，并分别研究了有界松弛估计误差和内生延迟限制。在固定可行松弛量下，LIA 是个人理性的，并且相对于最优可行分配，可实现至少 \(e^{-λΔ}\) 的福利，其中 \(Δ\) 是松弛扩散度。我们在市场规模 \(n\in\{10,20,30,40,50\}\) 的 52,500 个基线实例上，针对 STARLINK-200、INTERNET-100 和 DSN-30 评估了 LIA，并进行了额外的鲁棒性扫描。在 Starlink 和 Internet 上，LIA 保持了接近最优的效率，同时消除了测量到的时序租金。然而，在 DSN 上，福利在稀疏市场中较低，但随市场深度增加而提高。我们还区分了胜者确定时间与维护松弛估计的背景成本，并通过误差扩散界以及结构化（距离偏差和子网络相关）噪声模型，研究了超出独立同分布噪声的鲁棒性。这些结果表明，因果一致性机制设计为异构电信基础设施中的同步延迟均衡提供了一种实用的非缓冲替代方案。