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description=GAIA is an AI-based microwave network design and optimization solution delivering network-level, multi-objective optimization — topology, frequency, cost, and capacity in one workflow.;

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gaia ai based microwave network design optimization solution γαῖα home methodology features about us english magyar contact request information the gaia project ai based microwave transmission network design and optimization the first complete truly microwave network design know how with global multi objective optimization at the network level how it works methodology evolutionary design for microwave networks from chaos to gaia philosophy from chaos to gaia in greek mythology gaia was the primordial mother earth goddess who brought structure and stability to the world that emerged from chaos inspired by this narrative our approach follows a similar transformation from an unorganized network state with undefined structure to optimized network architecture where topology node positions frequency resources and capacity are designed to meet given requirements paradigm shift from link level tools to network level intelligence traditionally in microwave network design computational tools have focused primarily on individual links rather than on the network as a whole consequently key decisions regarding network formation have relied heavily on the designer s expertise and practical experience as a paradigm shift in design philosophy we have reformulated the design task as a multi objective optimization problem thereby elevating computational assistance from the link level to the network level this approach enables us to treat the network as an integrated system rather than merely as a collection of independent connections traditional gaia approach link by link design complete network design manual topology construction automated topology construction link optimal frequency allocation global frequency allocation post design cost evaluation cost embedded in optimization single solution pareto optimal solution set engineer dependent quality objective verifiable metrics process evolutionary network design process at the core of this methodology lies an evolutionary algorithm inspired by the principles of natural evolution starting from an initial population of candidate solutions the algorithm iteratively evolves network configurations through successive generations selecting and refining them according to predefined objectives 01 input data and existing network definition import current network information technical constraints equipment parameters geographic data and predefined design requirements 02 generation of initial network population produce a diverse set of candidate network designs based on available resources constraints and predefined design rules 03 performance evaluation and multi objective assessment pareto sorting and population selection evaluate each candidate network using defined fitness indicators including cost path length and other quality metrics rank candidate solutions according to multi objective performance and retain the most promising designs while eliminating dominated solutions 04 iterative optimization process repeat the generation evaluation and selection cycles until no further meaningful improvement can be expected 05 pareto front generation produce a final set of pareto optimal network designs representing different trade offs between competing objectives 06 subjective engineering selection select the preferred solution based on strategic priorities operational requirements and professional judgment features comprehensive capabilities for microwave network design and optimization features what gaia does differently every aspect of the design process from topology selection to lifecycle cost optimization is addressed within a unified optimization framework representing a fundamentally different approach from conventional network planning while the resulting design can be readily verified using standard tools the true challenge is identifying the optimal combination of network elements under multiple constraints natural handling of conflicting objectives applies domain specific multi objective optimization algorithms designed to resolve conflicting network design objectives and identify optimal trade offs across topology capacity frequency allocation dimensioning and cost performance criteria elevated step in the process extends computational intelligence beyond link level analysis to comprehensive network level design optimization generating solutions aligned with predefined technical requirements and business objectives objective performance metrics evaluates network solutions using multiple quality indicators including total cost path length efficiency capacity and reliability metrics global integrated cost optimization treats cost as an integral optimization objective enabling global trade off analysis between technical performance and economic efficiency while supporting any customer specific pricing model future proof planning simulates long term demand scenarios based on the current network state enabling lifecycle based planning and evolution analysis over a 10 12 year operational horizon data driven decision making enables business decisions based on full engineering grade network designs pareto optimized network design solutions generates a comprehensive set of pareto optimal network designs enabling engineers to select the most suitable solution based on their priorities trade offs and professional judgment cost as an optimization objective every cost component in scope from day one cost evaluation is seamlessly integrated into the network design process itself unlike traditional approaches where costs are assessed post design our methodology embeds both opex and capex along with roi directly into the optimization framework towers base stations construction and rental fees of towers and base stations equipment procurement procurement costs of equipment for existing and newly deployed microwave links software hardware interventions retuning polarization switching redirectioning and reinstallation costs dismantling reutilization dismantling and reutilization expenses antenna site rental fees depending on antenna size and location monthly opex monthly operational costs of microwave links structural maintenance structural reinforcements and periodic mandatory tower maintenance costs other costs additional non categorized costs technical specifications under the hood the optimization framework integrates elements of classical microwave network design graph theory and numerical optimization techniques enriched by a set of very advanced computational concepts network topologies supports tree ring inner or outer and mixed topologies of arbitrary complexity link configurations supports a wide range of link configurations including 1 0 2 0 cp xp 4 0 cp xp and dual band deployments integration of existing networks existing network infrastructure can be seamlessly incorporated into the optimization process interference environment accounts for arbitrarily sized external networks and complex interference environments to ensure accurate performance evaluation frequency planning utilizes an exact and highly efficient global scope algorithm for optimal polarization and frequency allocation channel frequency management supports selectable channel frequencies with optimization solutions based exclusively on available channel resources equipment sub band management equipment sub bands are handled according to a configurable priority order outage calculations provides advanced outage analysis including differential fading effects and outage correlation modeling cost framework supports flexible economic evaluation frameworks including opex capex roi and customer specific pricing policies calculation standards based on the latest industry standards including itu r p 530 19 and itu r p 452 18 coordinate system support wgs84 native raster and vector database support network scale designed to support large scale networks with more than 1 000 connections platform fully in house developed software platform enabling integration of customer specific requirements and tailored optimization functionalities contact let s talk about your network challenge get in touch whether you re planning a new network optimizing an existing one conducting a feasibility study or evaluating procurement decisions we re here to provide the expertise and answers you need email wsc wsc hu whatsapp 36 20 203 4690 address ws engineering kft diófa u 9 2330 dunaharaszti hungary web www wsc hu worldwide availability gaia supports global wgs84 based raster and vector online databases we are also capable of directly generating geographic databases for any location through ai based monocular height estimation enabling global coverage and adaptation to projects anywhere on the globe start a conversation we respond within one business day first name last name work email organization country message send message your information is used solely to respond to your inquiry ws engineering ltd does not share contact details with third parties message sent we ll be in touch within one business day ws engineering ltd 2026 all rights reserved home methodology features contact wsc wsc hu 36 20 203 4690 budapest hungary