Abstract: Wireless Network coverage and capacity optimization are typically multivariable combinatorial optimization problems, and traditional exact or heuristic methods are often constrained by time complexity or accuracy during the solving process. To address this issue, a solution is proposed using the Quantum Approximate Optimization Algorithm. The network coverage and capacity optimization problem are first transformed into the maximum independent set problem, and a mathematical model is constructed to encode the true solution of the maximum independent set problem into the ground state of a target Hamiltonian. A parameterized quantum circuit is then used to approximately obtain the target ground state. Simulation results demonstrate that solving the maximum independent set problem using quantum approximate optimization algorithm yields an exact or quasi-optimal solution within the number of polynomial iteration steps, showcasing quantum advantage.

Key words: quantum approximate optimization algorithm, wireless network optimization, maximum independent set