Deep reinforcement learning-based resource allocation for D2D communications in heterogeneous cellular networks

Device-to-Device(D2D)communication-enabled Heterogeneous Cellular Networks(HCNs)have been a promising technology for satisfying the growing demands of smart mobile devices in fifth-generation mobile networks.The introduction of Millimeter Wave(mm-wave)communications into D2D-enabled HCNs allows higher system capacity and user data rates to be achieved.However,interference among cellular and D2D links remains severe due to spectrum sharing.In this paper,to guarantee user Quality of Service(QoS)requirements and effectively manage the interference among users,we focus on investigating the joint optimization problem of mode selection and channel allocation in D2D-enabled HCNs with mm-wave and cellular bands.The optimization problem is formulated as the maximization of the system sum-rate under QoS constraints of both cellular and D2D users in HCNs.To solve it,a distributed multiagent deep Q-network algorithm is proposed,where the reward function is redefined according to the optimization objective.In addition,to reduce signaling overhead,a partial information sharing strategy that does not observe global information is proposed for D2D agents to select the optimal mode and channel through learning.Simulation results illustrate that the proposed joint optimization algorithm possesses good convergence and achieves better system performance compared with other existing schemes.

Is there hybridization between 2 species of the same genus in sympatry?——The genetic relationships between Anoplophora glabripennis,Anoplophora chinensis,and putative hybrids

Anoplophora glabripennis(Asian longhorn beetle,ALB)and Anoplophora chinensis(Citrus longhorn beetle,CLB)are native forest pests in China;they have become important international quarantine pests.They are found using the same Salix aureopendula host tree of Cixi,Zhejiang province,China.On this host tree,we collected additional beetles that appeared to be morphologically intermediate between ALB and CLB.By using a stereoscope,we observed that there were several bumps on the base of the elytra,which was inconsistent with ALB,which typically has a smooth elytral base,but was more like CLB,which has numerous short tubercles on the elytral base.Given their sympatry and intermediate morphology,we hypothesized that these may represent ALB×CLB hybrids.We studied the genomic profiles for 46 samples(ALB,CLB,and putative hybrids)using genotyping-by-sequencing(GBS)providing a reduced representation of the entire genome.Employing principal component analyses on the 163 GBS-derived single nucleotide polymorphism data,we found putative hybrids tightly clustered with ALB,but genetically distinct from the CLB individuals.Therefore,our initial hybrid hypothesis was not supported by genomic data.Further,while mating experiments between adult ALB and CLB were successful in 4 separate years(2017,2018,2020,and 2021),and oviposition behavior was observed,no progeny was produced.Having employed population genomic analysis and biological hybridization experiments,we conclude that the putative hybrids represent newly discovered morphological variants within ALB.Our approach further confirmed the advantage of genome-wide information for Anoplophora species assignment in certain ambiguous classification cases.