Abstract :

Allocating Spectrum And Choosing Transmit Powers In A 6G Network Made Up Of Several Unmanned Aerial Vehicles (UAVs) Is A Coupled, Non-convex Problem. A Recent Two-stage Remedy [1] First Divides The Band With A Graphcolouring Model That Is Solved By Sequential Quadratic Programming (SQP), And Then Reduces The Transmit Powers With An M-matrix Procedure. SQP Is A Local, Gradient-driven Method: Where It Ends Up Depends On Where It Starts, And Its Iteration Count Grows As The Network Becomes Denser. In This Paper The Bandwidth Stage Is Given To A Multi-Objective Harris Hawks Optimization (MO-HHO) Algorithm, A Derivative-free, Population-based Global Search That Works Directly On The Maximal-independent-set (MIS) Space Of Bandwidth Reuse, While The M-matrix Power Stage Is Retained Unchanged. A Rule-based Natural-language-processing (NLP) Front End Is Added As Well, So That A Ground Operator Can Describe Mission Needs In Everyday English, For Example “guarantee At Least 5 Mbps For The Rescue-team Relay And Favour UAV-3”. The Module Extracts UAV Identifiers And Quality-of-service (QoS) Keywords And Turns Them Into The Minimum-rate Constraints Used By The Optimizer, Which Removes The Need To Edit Constraint Vectors By Hand. Monte Carlo Simulations For Network Densities Of 0.5, 0.8 And 1.0 And For 3–8 UAVs Report Improvements Of Up To 32.8% In Data Rate And Up To 26.1% In Energy Efficiency Over SQP, And Convergence In 2–3 Iterations Against 90–100 For SQP. Key Words—6G, Multi-UAV Networks, Harris Hawks Optimization, M-matrix Theory, Bandwidth Allocation, Power Control, Spectral Efficiency, Energy Efficiency.

Published:

12-10-2026

Issue:

Vol. 26 No. 10 (2026)

Page Nos:

32-41

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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