LS-DN Algorithm Based User Matching and Power Minimization in NOMA Disaster Communication

Abstract

To address the limited and time delay disaster communication, a joint optimization scheme integrates the advantages of differential evolution algorithm (DE) and naked mole- rat algorithm (NMR), and proposes Lévy and sigmoidal DE-NMR, namely LS-DN. LS-DN applies the Lévy flight parameters of adaptive features and sigmoidal selection factor (λ) to the worker of NMR phase, and optimizes the crossover rate (CR) and variation parameter (F) in the DE algorithm, to obtain a balance the exploration and development capabilities. The proposed LS-DN algorithm is used to optimize the user aggregation scheme, since an effect aggregation of disaster victims can reduce power consumption and improve system performance. An value of power external function (Cfn ) is defined for each disaster victim, which is expressed as the system power consumption value for each disaster victim under different aggregation schemes. To minimize the microcell power without deteriorating the quality of service (QoS), it is demonstrated by analyzing the relevant characteristics of non-orthogonal multiple access（NOMA）disaster communication that the power consumption strongly depends on user aggregation method and power allocation. The significance of joint optimization for improving the performance of NOMA disaster communication systems is also emphasized. Simulation results show that LS-DN is able to significantly reduce the power consumption of the system. With the application of LS-DN, the throughput of NOMA system increases by 65% compared to the conventional orthogonal multiple access (OMA) system.