协作D2D异构网络的联合资源分配和功率控制

针对下行协作D2D(Device-to-Device)异构网络中复用蜂窝用户的联合资源分配和功率控制问题,提出了一种量子珊瑚礁优化算法(Quantum Coral Reef Optimization Algorithm,QCROA)。首先,构建异构网络模型并推导得到整个网络总吞吐量的数学表达式;其次,基于QCROA算法分析全局最优量子珊瑚的测量状态,提出最优联合资源分配和功率控制方案;最后,通过仿真验证QCROA算法的优越性。实验结果表明,在不同网络通信场景下,QCROA算法均表现出良好的适应性,其收敛速度和种群多样性均优于其他基于智能优化算法的方案,在迭代次数达到1 500次时即可获得吞吐量最高的全局最优。

Joint resource allocation and power control for cooperative D2D heterogeneous networks

For the problem of joint resource allocation and power control for multiplexing cellular users in a downlink cooperative device-to-device(D2D) heterogeneous network,a quantum coral reef optimization algorithm(QCROA) is proposed.First,a heterogeneous network model is constructed,and the mathematical expression of the total throughput of the entire network is derived.Second,based on the QCROA algorithm,the global optimal quantum coral measurement status is analyzed,and an optimal joint resource allocation and power control scheme is proposed.Finally,the superiority of QCROA algorithm is verified through simulation.The experimental results show that the QCROA algorithm exhibits good adaptability under different network communication scenarios,and its convergence speed and population diversity are superior to those of other intelligent optimization algorithm-based solutions,and the global optimum with the highest throughput can be obtained when the number of iterations reaches 1 500.