基于能效优化的异构网络资源分配算法设计

An Energy-Efficient Resource Allocation Algorithm in Heterogeneous Network

Macro/Femtocell作为新一代的异构网络,在用于增加网络覆盖量和提高吞吐量以及保证用户服务需求上有很大的优势,然而大规模的部署Femtocell会导致功率消耗显著增加,同时网络的能量效率也会明显下降。除此之外,为了提高频谱利用率,Macro/Femtocell之间通常采用共享频谱方案,这会导致Macro基站和Femtocell用户之间的跨层干扰,从而明显地降低异构网络的性能。针对上述问题,通过对多目标遗传算法的研究,提出基于能效优化的异构网络资源分配算法。该算法以能量效率为优化目标,在跨层干扰和功率限制等限制条件下,进行子载波信道和功率的联合资源分配。其中,采用多目标遗传算法中的非支配排序遗传算法(Non-dominated Sorting Genetic Algorithm,NSGA-II)进行优化的子载波分配和功率分配方案的求解。仿真结果表明,本文提出的算法在节约能耗方面相比于不考虑干扰限制的算法有很大提升。

Macro/Femtocell network, as a new generation of heterogeneous network, enjoys great superiority in raising network coverage and capacity and ensuring the user＇s service needs, and however, largescale deployment of Femtocells would considerably increase power consumption and decrease energy effi- ciency of the networks. In addition, Macro/Femtocell network usually adopts spectrum-sharing strategy, thus to improve spectral efficiency, and this would lead to cross-layer interference of between Macro and Femtocell users, and clearly decrease the performance of heterogeneous network. Aiming at the above problems and based on the research of multiple objective genetic algorithms, a new energy-efficient re- source allocation algorithm in heterogeneous network is proposed. This algorithm, with energy efficiency as the optimization target, achieves joint resource allocation of subcarrier channel and power under the restricted condition of cross-layer interference and power limitation, of which, NSGA-II （ Non-dominated Sorting Genetic Algorithm） algorithm is adopted to seek the optimized solution of the joint allocation problem of subcarrier and power. Simulation result shows that the proposed algorithm could achieves a better improvement in terms of energy savings compared to the algorithm that considers no interference limitation.