量子近似优化算法在网络覆盖与容量优化中的应用
The Application of Quantum Approximate Optimization Algorithm in Network Coverage and Capacity Optimization
潘成康 1崔春风 1卢献 1侯帅 1李昕莹1
作者信息
摘要
无线网络覆盖与容量优化通常为多变量组合优化问题,传统精确方法或启发式方法在求解过程中往往受到时间复杂度或精度的制约.对此,提出采用量子近似优化算法进行求解.首先,将网络覆盖与容量优化问题转换为最大独立集问题,并构建数学模型将最大独立集问题的真实解编码到目标哈密顿量基态中;然后,借助含参量子线路近似生成目标基态.仿真实验结果表明,基于量子近似优化算法求解最大独立集问题能够在多项式迭代步数内给出问题的精确解或拟最优解,展现出量子优势.
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 thenumber of polynomialiterationsteps,showcasing quantum advantage.
关键词
量子近似优化算法/无线网络优化/最大独立集Key words
quantum approximate optimization algorithm/wireless network optimization/maximum independent set引用本文复制引用
出版年
2024
NETL
NSTL
万方数据