Utility-Aware Optimal Resource Allocation Protocol for UAV-Assisted Small Cells with Heterogeneous Coverage Demands
Poonam Lohan, Deepak Mishra

TL;DR
This paper introduces a utility-aware resource allocation protocol for UAV-assisted small cells that maximizes user coverage and service efficiency amid heterogeneous demands, using analytical and iterative optimization methods.
Contribution
It proposes a novel utility-aware resource allocation scheme with a closed-form rate-coverage expression and an iterative method for global optimality in UAV-assisted small cells.
Findings
60% more users served compared to benchmarks
Analytical expressions validate system performance
Key system parameters significantly impact coverage and utility
Abstract
In this paper, we consider a UAV-assisted small-cell having heterogeneous users with different data rates and coverage demands. Specifically, we propose a novel utility-aware resource-allocation protocol to maximize the utility of UAV by allowing it to simultaneously serve the highest possible number of heterogeneous users with available energy resources. In this regard, first, we derive a closed-form expression for the rate-coverage probability of a user considering Rician fading to incorporate the strong line of sight (LoS) component in UAV communication. Next, since this UAV utility maximization problem is non-convex and combinatorial, to obtain the global optimal resource allocation policy we propose an iterative feasibility checking method for fixed integers ranging from lower to upper bound on the number of users that can be served by UAV. To further reduce the complexity, we…
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