论文简报
cs.IT 2605.26719v1 值得读

RIS-Assisted Survivable Backhaul Recovery in Small-Cell Systems

Zhenyu Li, Özlem Tuğfe Demir, Emil Björnson, Cicek Cavdar

发布日期：2026-05-26 08:58 相关性：1.0000 价值：0.7400 分类：cs.IT eess.SP
arXiv 摘要 PDF 原文 网页正文

摘要

The increasing densification of small-cell networks substantially expands cable-based backhaul infrastructure, creating heightened vulnerability to cable link failures. This paper proposes a reconfigurable intelligent surface (RIS)-assisted backup framework that exploits a key insight: during backhaul cable failures, base station (BS) radio components remain functional, enabling wireless backhaul traffic redistribution. Our framework maintains network connectivity by redistributing disconnected BS backhaul traffic to neighboring BSs through RIS-assisted wireless links. To maximize survivability across varying traffic conditions, we formulate a joint optimization problem that maximizes total resolvable backhaul traffic by jointly deciding BS selection, RIS phase shifts, and precoding vectors. The inherent non-convexity arising from coupling and quadratic fractional term is addressed through an alternating optimization algorithm that iteratively solves tractable convex subproblems via quadratic transformation. Comprehensive numerical evaluations demonstrate that the proposed RIS-enhanced framework significantly improves survivability from 58% to 72% under challenging high-intensity hotspot traffic conditions. Moreover, RIS provides the greatest gains for antenna-constrained systems by extending coverage to access more spare capacity of the distant BSs as well as enhancing the signal strength. Consequently, high survivability is achieved even with only two antennas per BS under moderate traffic intensity.

相关性判断

high
相关方向
wireless_communications ris network_reliability optimization
判断依据

Directly on wireless communications and cs.IT: RIS-assisted backhaul recovery, joint BS selection/precoding/phase optimization, and survivability analysis for small-cell networks.

价值判断

Highly relevant to cs.IT wireless communications with a clear survivable backhaul recovery problem and explicit joint optimization over BS selection, RIS phases, and precoding. Structure evidence indicates solid technical machinery, including mixed-integer non-convex formulation, quadratic transform, alternating optimization, and simulation-backed survivability gains. The reported 58% to 72% survivability improvement under hotspot traffic is practically meaningful, especially for antenna-constrained small-cell systems.

核心问题与主要方法

核心问题

survivable recovery of small-cell backhaul connectivity after a cable link failure

场景：single-failure small-cell cluster with cable backhaul, a disconnected BS, surviving neighboring BSs, and an RIS-assisted wireless backup link

主要方法

A disconnected BS uses decode-and-forward-style wireless redistribution to selected surviving BSs whose BBUs have spare capacity, preserving core-network connectivity through those surviving BSs. The target BS selection is constrained by spatial multiplexing: at most N parallel streams can be served, so antenna count directly limits spare-capacity accessibility. RIS phase shifts reshape the effective disconnected-BS-to-surviving-BS channels, improving reachability to farther BSs with spare capacity and strengthening signal quality. The non-convex joint problem is decomposed by fixing RIS phases while optimizing precoders, then fixing precoders while optimizing RIS phases; each subproblem is convex except for binary selection constraints. Quadratic transformation and exponential-cone-style auxiliary variables are used to make rate-related constraints tractable inside the alternating optimization loop.

关键贡献与后续阅读

关键贡献

Introduces an RIS-assisted survivable backhaul recovery framework for small-cell systems where a disconnected BS wirelessly redistributes its traffic to neighboring surviving BSs after a cable failure. Formulates survivability maximization as total resolvable backhaul traffic maximization with joint optimization over BS target selection, RIS phase-shift matrix, and multi-user precoding vectors. Models practical constraints including surviving-BS spare BBU capacity, spatial stream limit from antenna count, zero power for non-selected BSs, total redistribution power budget, and unit-modulus RIS elements. Develops an alternating optimization procedure using epigraph reformulation, auxiliary variables for binary-rate products, quadratic transform for fractional rate terms, relaxed RIS modulus handling, and branch-and-bound for integer variables. Provides numerical evidence that RIS assistance is most useful under spatially correlated hotspot traffic and antenna-constrained settings, including the reported 58% to 72% survivability gain at high traffic intensity.

研究启发

How sensitive are the gains to imperfect or delayed CSI during an actual cable-failure event? What are the cluster sizes and binary-variable counts used in simulation, and how does branch-and-bound runtime scale for denser deployments? How robust is the result if the RIS is not guaranteed LOS to all BSs or if angular attenuation is modeled? Are there baselines against conventional wireless relay/backhaul recovery without RIS but with optimized BS selection and precoding?

限制与不确定性

Novelty may be incremental if similar RIS-assisted relay/backhaul recovery optimization frameworks already exist. Evaluation appears simulation-only and depends on strong assumptions such as perfect CSI, single-link failure, RIS placement, and available spare capacity. Branch-and-bound integer handling may limit scalability beyond the studied cluster setting.

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