# backhaul Published articles for backhaul. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## From Connectivity to Continuity: Cisco URWB for Autonomous Work Vehicles DevFeed: [From Connectivity to Continuity: Cisco URWB for Autonomous Work Vehicles]() Original publisher: [Read original article]() Author: David Eror Published: 2026-11-07T01:14:49Z Content type: article Language: en Sources: [Cisco Blogs]() Topics: [autonomous vehicles](), [cisco networking](), [Cisco]() Tags: [ai](), [ai-platform](), [amr](), [apis](), [application-programming-interfaces](), [asset-management](), [autonomous](), [backhaul](), [cisco](), [cisco-industrial-iot-iiot](), [cisco-industrial-wireless](), [cisco-ultra-reliable-wireless-backhaul](), [connectivity](), [critical](), [environments](), [honda](), [industrial-automation](), [industrial-wireless](), [inspection](), [learn-with-cisco](), [mission](), [operations](), [outdoor](), [vehicles](), [wireless](), [wireless-and-mobility](), [wireless-networking]() ### AI overview Cisco URWB provides the wireless backbone for Honda's Autonomous Work Vehicle (AWV), which uses GPS, LiDAR and odometry to navigate off-road routes and can support airfield perimeter inspection. The text says URWB uses MPLS-over-wireless and make-before-break handoffs for roaming, with predictable low latency depending on deployment design and operating conditions. Its multipath operation (MPO) can duplicate selected packets across paths and remove duplicates at the receiver to address packet loss; the data plane is encrypted. The article contrasts this with conventional Wi-Fi's potential handoff, latency-variation and packet-loss challenges, and notes 4G and 5G as alternatives for organizations that do not require full control of their wireless infrastructure and operational data. An AWV connected through URWB can send anomaly data to Illuminex AI's InspectEx Cloud for hazard monitoring and integration with asset-management systems. ### Source excerpt Learn how Cisco Ultra-Reliable Wireless Backhaul (URWB) helps enable reliable connectivity for Honda's Autonomous Work Vehicle (AWV), supporting perimeter inspection and other mission-critical operations in demanding outdoor environments. ## QPP-Aware MCX over Tactical Edge 3D Networks in Public-Safety Communications DevFeed: [QPP-Aware MCX over Tactical Edge 3D Networks in Public-Safety Communications]() Original publisher: [Read original article]() Author: Jos\\'e Oliveira, Pedro Valente, Tiago Mendes, Andr\\'e Vasconcelos, Tiago Fernandes, Rhyan Matos, Duarte Raposo, Pedro Rito, Marco Ara\\'ujo, Susana Sargento Published: 2026-11-04T05:00:00Z Content type: article Language: en Sources: [arXiv: Networking]() Topics: [5G](), [communications](), [Critical Infrastructure]() Tags: [5g](), [architecture](), [backhaul](), [communications](), [connectivity](), [context](), [critical](), [cs-ni](), [delay](), [deployment](), [edge](), [emergency](), [evaluation](), [experimental](), [extensions](), [functions](), [management](), [mechanism](), [networks](), [public](), [safety]() ### AI overview The proposed public-safety system combines MCPTT, MCVideo, and MCData on a private 5G standalone network with non-terrestrial connectivity. Its context-aware quality, priority, and pre-emption mechanism is designed to adjust resource allocation to MCX operational state; Open5GS PCF and SMF extensions can update priority and pre-emption for existing flows without re-establishing sessions. Service and media functions can run at the tactical edge while service control remains centralized. In tests comparing terrestrial backhaul with centralized media, satellite backhaul with centralized media, and satellite backhaul with edge media, edge processing under satellite backhaul lowered 95th-percentile MCPTT audio transport delay by 60.03 ms and packet loss by 9.42 percentage points, with 95th-percentile access time of 184.52 ms. The excerpt reports experimental support for edge processing benefits, not a quantified evaluation of the QPP mechanism itself. ### Source excerpt arXiv:2611.05165v1 Announce Type: new Abstract: During disasters, public mobile networks may become unavailable, congested, or degraded, requiring deployable communication systems to support emergency operations. This article proposes a mission-critical communications system supporing Mission Critical Push-to-Talk (MCPTT), Mission Critical Video (MCVideo), and Mission Critical Data (MCData) over a private 5G standalone network with Non-Terrestrial Network (NTN) connectivity. A context-aware Quality, Priority, and Pre-emption (QPP) mechanism is proposed to dynamically adapt network resource allocation according to the operational state of Mission Critical Services (MCX). Extensions to the Open5GS Policy Control Function (PCF) and Session Management Function (SMF) enable priority and pre-emption updates for existing flows without session re-establishment. The architecture supports tactical edge deployment of service and media functions while retaining centralized service control. Experimental evaluation considers three configurations: terrestrial backhaul with centralized media processing, satellite backhaul with centralized media processing, and satellite backhaul with edge media processing. Results show that tactical edge processing reduces communication delay and packet loss. Under satellite backhaul, edge processing reduced the 95th-percentile MCPTT audio transport delay by 60.03 ms and packet loss by 9.42 percentage points, while achieving a 95th-percentile MCPTT access time of 184.52 ms. These findings demonstrate the benefits of tactical edge media processing and provide an experimental foundation for context-aware priority mechanisms in public-safety networks integrating terrestrial and non-terrestrial components. ## Band-Separated Redundant Communication for a Mars-Analog Rover DevFeed: [Band-Separated Redundant Communication for a Mars-Analog Rover]() Original publisher: [Read original article]() Author: Zamiul Rashid, Akid Anis, Tanzim Ahmed, Md. Golam Rabiul Alam, Md. Khalilur Rhaman Published: 2026-11-03T05:00:00Z Content type: article Language: en Sources: [arXiv: Networking]() Topics: [Data transmission](), [mesh networking]() Tags: [babel](), [backhaul](), [backup](), [bandwidth](), [bench](), [bridge](), [camera](), [capacity](), [challenge](), [command](), [communication](), [control](), [cs-ni](), [drive](), [edge](), [failed](), [failure](), [field](), [limit](), [link](), [mars]() ### AI overview The BRACU Mongol-Tori rover separates video and RTK corrections from command traffic to maintain bandwidth and control redundancy. Video and corrections use a 5.2 GHz bridge with a 2.4 GHz backup selected by Babel; commands are sent simultaneously over two sub-gigahertz radios, with the backup copy used when the primary falls silent. Bench tests switched traffic to backup within seconds, while a metric offset kept Babel on a primary losing 10% of packets. In a drive exceeding 1 km, the primary failed at 771 m and the backup carried video and corrections just beyond 1 km, despite line of sight ending about halfway. The field test also revealed that Babel's lost-Hello-based link judgment can retain a primary with a faulty receiver despite the backup reporting twice its capacity, and can flap near range limits. The abstract identifies antenna aiming, link metrics, and logging as lessons from the tests. ### Source excerpt arXiv:2611.02131v1 Announce Type: new Abstract: Teams in the University Rover Challenge (URC) drive their rovers remotely and often out of sight. The organizers name communication failure as the most common reason a team falls short. A rover therefore needs bandwidth for several camera views and a command path that survives the loss of one radio. We describe and field test the communication stack of the BRACU Mongol-Tori rover, which keeps vision and control on separate radios and bands. Video and RTK corrections travel over a 5.2 GHz bridge with a 2.4 GHz backup, and the Babel routing protocol chooses between them. Every command goes out on two sub-gigahertz radios at once, and the rover uses the backup copy only when the primary falls silent. We tested the backhaul on the bench with a power cut and injected packet loss. We also drove the rover more than a kilometer from the base, and line of sight ended about halfway. On the bench, traffic reached the backup within a few seconds. A metric offset kept it on a primary that lost one packet in ten. In the field, the primary failed at 771 m and the backup carried video and corrections to just over a kilometer. The drive also exposed a limit of Babel, which judges a link only by lost Hello messages. It kept traffic on a primary with a faulty receiver, although the backup reported twice the capacity, and it flapped at the edge of range. We close with lessons on antenna aiming, link metrics and logging. ## ATLAS: Expert-Guided Sustainable Satellite Backhaul for Off-Grid Wildlife Monitoring DevFeed: [ATLAS: Expert-Guided Sustainable Satellite Backhaul for Off-Grid Wildlife Monitoring]() Original publisher: [Read original article]() Author: Hao Fang, Miao Zhang, Haoyuan Zhao, Long Chen, Yi Ching Chou, Chi Xu, Cheng Pan, Jiangchuan Liu Published: 2026-10-21T04:00:00Z Content type: article Language: en Sources: [arXiv: Machine Learning]() Topics: [Reinforcement learning](), [Artificial Intelligence](), [Machine learning]() Tags: [atlas](), [backhaul](), [bandwidth](), [cameras](), [case-study](), [clip](), [cloud](), [compile](), [connectivity](), [continuous](), [cs-lg](), [cs-sy](), [downtime](), [edge](), [eess-sy](), [energy](), [filter](), [fixed](), [foundation](), [foundation-models](), [monitoring](), [satellite](), [wildlife]() ### AI overview ATLAS addresses the power and bandwidth limits of satellite backhaul for off-grid wildlife monitoring by selecting which camera clips to upload and when. It uses foundation models to translate experts' natural-language objectives into semantic scoring logic, combines relevance with environmental and energy conditions, and applies constrained reinforcement learning to schedule uploads. In a six-month deployment at 18 off-grid salmon-monitoring sites, it achieved 87.4% mean clip-selection accuracy, 26.4 percentage points above the mean baseline, and near-continuous operation during low-solar periods, when baselines had 16.0% downtime. ### Source excerpt arXiv:2610.24910v1 Announce Type: cross Abstract: Remote wildlife monitoring increasingly depends on high-fidelity cameras and sensors deployed far from grid power and terrestrial networks. Low Earth orbit satellite links can provide connectivity in these settings, but their high power draw and variable bandwidth, combined with intermittent on-site solar harvesting, make continuous backhaul infeasible. Current systems therefore filter at the edge, with motion triggers that waste limited energy and bandwidth on environmental artifacts, or fixed vision models that cannot follow evolving expert objectives. We present \textsc{ATLAS}, an expert-guided edge-to-cloud system that treats satellite backhaul as a scarce resource for off-grid wildlife monitoring. \textsc{ATLAS} uses foundation models to compile natural-language expert intent into semantic scoring logic, combines semantic relevance with environmental and energy state, and uses a constrained reinforcement-learning scheduler to decide which clips to upload and when. As a representative case study, we deployed \textsc{ATLAS} for over six months across 18 off-grid salmon-monitoring river sites. \textsc{ATLAS} achieves a mean clip-selection accuracy of $87.4\%$, exceeding mean baseline accuracy by $26.4$ percentage points, while maintaining near-continuous operation through low-solar periods in which baselines incur 16.0\% downtime. ## How Rain Affects Wireless Microwave Links: 24 GHz, 60 GHz, and 80 GHz Compared DevFeed: [How Rain Affects Wireless Microwave Links: 24 GHz, 60 GHz, and 80 GHz Compared]() Original publisher: [Read original article]() Author: j2sw Published: 2026-06-15T09:47:43Z Content type: tutorial Language: en Sources: [Justin Wilson (j2sw)]() Topics: [Network](), [Network design](), [Internet](), [data centers]() Tags: [24ghz](), [60ghz](), [80ghz](), [adaptive](), [backhaul](), [capacity](), [changes](), [e-band](), [error-correction](), [fiber](), [microwave](), [network](), [network-design](), [perfomance](), [radio](), [reduction](), [rf](), [wireless](), [wireless-networking]() ### AI overview This article explains how rain fade affects wireless microwave links, with emphasis on 24 GHz, 60 GHz, and 80 GHz bands. It describes how precipitation reduces signal strength, causes adaptive modulation and throughput reductions, and can eventually cause a link to drop when fade margin is exhausted. ### Source excerpt Rain can have a major impact on wireless microwave links, especially as frequencies increase. Learn how rain fade affects 24 GHz, 60 GHz, and 80 GHz circuits, and why fade margin is critical for reliable network design. The post How Rain Affects Wireless Microwave Links: 24 GHz, 60 GHz, and 80 GHz Compared appeared first on Justin Wilson (j2sw). ## Who can light fibre in India? DevFeed: [Who can light fibre in India?]() Original publisher: [Read original article]() Published: 2026-02-21T20:49:05Z Content type: article Language: en Sources: [Personal blog of Anurag Bhatia]() Topics: [Internet](), [Cloud](), [hosting](), [data centers]() Tags: [backhaul](), [cloud](), [connectivity](), [datacenter](), [hosting](), [india](), [infrastructure](), [mpls](), [regulatory](), [routers](), [vlan]() ### AI overview The article discusses Indian telecom licensing rules for deploying, lighting, and reselling fibre outside a building. It explains that IP-1 providers may lease passive dark-fibre infrastructure but may not light it, while appropriately licensed ISPs may light fibre for end-user internet access and their own backhaul, not point-to-point connectivity. ### Source excerpt Friend and his two homes... Recently, a friend of mine mentioned his plan to procure dark fibre to connect two of his homes. His idea was straightforward - get LCO to give a dark strand between both homes and run Bidi optics over it. I ended up telling him that while his idea is technically fine, as modern optics can easily cover that sort of distance, it would be illegal as per Indian telecom laws! It wasn't just him, but numerous content players, hosting companies, and Cloud players find it a bit odd when they find this out. In this post, I will document what is allowed and what is not allowed. Advance warning: I am a technical person & do not know much about regulatory. Whatever I am sharing here is what I have learned from my friends who have expertise in the subject. Indian telecom rules are overly complex and can have a different set of interpretations, and often go into the grey area. I welcome readers to share feedback if they are aware of something which isn't correct as per the regulation. With that warning out of the way, I will proceed with the post. Understanding licensing In India, when fibre is going outside of a given building, one needs to have a license to light it. In fact, not just "lighting up a dark fibre" but to deploy and resell dark fibre, one needs a license (IP-1). Infrastructure Provider Category 1 (or IP-1) is considered an easy license which can be used to sell passive assets such as dark fibre, ducts, towers, etc. Active infra i.e lighting up fibre, is not allowed under this license, and it's expected that an IP-1 holder leases their dark fibre only to a license holder who is authorised to light the fibre. Within a building, campus, datacenter, home etc one can deploy a light fibre but as soon as it goes outside of that it becomes a bit of a grey area depending on the use case. An Internet Service Provider (ISP) holding an ISP license or Unified License with ISP authorisation can light fibre but only for two specific purposes: Offering i