The allocation of minimum power with guarantee of minimum rate in passive optical network optical code division multiple access (PON-OCDMA) networks is analyzed considering heuristic optimization methods such as Particle Swarm Optimization (PSO) and four variants. The base of the power-rate adaptive PON-OCDMA is the multi-length 2-D wavelength-hopping/time-spreading code called multiple-length extended wavelength-hopping prime code (MLEWHPC) to support the services of different media in accordance with the bit-rate and quality of service (QoS). The Halton-Chaos-$\beta$-PSO (HC-PSO) algorithm is proposed for solving the optimal power and rate allocation in order to maximize the EE of the optical system, subject to QoS restrictions based on the signal-to-interference plus-noise ratio (SINR) in each class of optical user and minimum required power. The proposed HC-PSO and the analytical–iterative–heuristic approach based on the augmented Lagrangian and PSO (ALPSO) method demonstrate promising performance-complexity trade-off, specially for high dimensionality OCDMA systems. The proposed hybrid analytical-evolutionary resource allocation method is corroborated by numerical simulation results, considering the tuning of heuristic evolutionary input parameters, which have demonstrated to improve the EE of the optical system when the power-rate allocation procedure is deployed dynamically in real time applications.

考虑粒子群优化(PSO)和四种变体等启发式优化方法，分析了无源光网络光码分多址(PON-OCDMA)网络中保证最小速率的最小功率分配。功率速率自适应 PON-OCDMA 的基础是称为多长度扩展波长跳跃素码 (MLEWHPC) 的多长度二维波长跳跃/时间扩展码，以支持不同媒体的业务。比特率和服务质量 (QoS)。Halton-Chaos-$\beta$-PSO (HC-PSO) 算法被提出用于解决最优功率和速率分配，以最大化光学系统的 EE，受到基于每个信号干扰加噪声比 (SINR) 的 QoS 限制光学用户等级和最低要求功率。所提出的 HC-PSO 和基于增强拉格朗日和 PSO (ALPSO) 方法的分析-迭代-启发式方法展示了有希望的性能-复杂性权衡，特别是对于高维 OCDMA 系统。考虑到启发式进化输入参数的调整，所提出的混合解析进化资源分配方法得到了数值模拟结果的证实，这已证明当功率率分配程序在实时应用中动态部署时可以提高光学系统的 EE .