Tabu Search for Tactical Wireless Network Design in Challenging Environments

2026-04-20

AI Summary

This work addresses the challenge of deploying tactical wireless networks in infrastructure-free, complex environments by proposing a domain-knowledge–integrated tabu search framework. The approach combines multiple heuristic subroutines with a terrain-aware radio propagation model to efficiently optimize network coverage while mitigating interference. By embedding contextual awareness into the search process, the method achieves a significant improvement in solution quality without compromising computational efficiency. Empirical evaluations on synthetic scenarios demonstrate its superiority over existing algorithms, consistently yielding robust deployment configurations that exhibit high coverage, low interference, and rapid convergence—critical attributes for dynamic tactical operations.

Technology Category

• Search and Optimization: Heuristic Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Tactical wireless networks play a vital role in ensuring reliable connectivity in scenarios where conventional telecommunications infrastructure is unavailable or damaged, such as areas impacted by natural disasters. These networks are designed to operate efficiently in difficult and unpredictable environments by adapting to the unique characteristics of the terrain. This research addresses a real-world challenge from the communications industry: designing tactical wireless networks that meet the specific constraints defined by our industrial partner, with the goal of optimizing signal strength and coverage while minimizing interference. To this end, we propose two tabu search algorithms that incorporate several heuristic subroutines, enabling the efficient generation of high-quality network designs. Results from synthetic tests demonstrate that our approach produces networks rapidly and effectively, offering significant improvements over existing methods.

Problem

• tactical wireless networks
• network design
• signal coverage
• interference minimization
• challenging environments

Innovation

• Tabu Search
• tactical wireless networks
• heuristic subroutines
• network design optimization
• interference minimization