Research On Spatial-Frequency Resource Allocation For Millimeter Wave Backhaul Networks

Small cell network(SCN),which densely deploys small cell base stations(SBSs)within the coverage of traditional macro cell to provide low-power access point for users(UEs),effectively reduce coverage holes and improve spectral efficiency(SE),and consequently is considered as one of the key technologies of fifth generation mobile communication system.However,as the link between macro cell base station and SBSs,backhaul(BH)plays a decisive role in the complexity and cost of SCN deployment and UE's quality of service.Recently,millimeter wave(mm Wave)band has been regarded as the most promising wireless BH solution due to its advantages of large bandwidth,high gain,low interference and low cost.Although mm Wave BH network has many merits,with SBSs densely deployed,reasonable and effective resource allocation(RA)algorithm is still necessary to ensure the performance of the network,such as throughput,spectral efficiency,fairness,etc.For out-of-band BH(OBH)scenario,the existing RA algorithms cannot cope with the situation when huge aggregated BH traffic bursts in the mm Wave BH networks due to multi-hops.For in-band BH(IBH)scenario,in order to reduce the co-layer interference,cross-layer interference and self-interference of the network,the existing works utilize various resource division and resource reuse algorithms.However,the range of resource reuse is limited and the lake of flexibility,makes the SE of the network not high enough in these works.To solve the above problems,this paper proposes an RA algorithm based on matching theory for mm Wave OBH network,and another RA algorithm based on Markov approximation theory for mm Wave IBH network.For both mm Wave OBH network and mm Wave IBH network,this paper focuses on the problem of joint spatial-frequency domain resource allocation.On the one hand,the short range transmission characteristic of mm Wave and the narrow beam formed by beamforming technology,provide part of spatial resources for the system,which can reduce the interference of the regions where SBSs and UEs are distributed sparsely in the network.On the other hand,when SBSs and UEs are distributed intensely in the network,orthogonal sub-channels provide frequency domain resources for the system,and can effectively avoid interference among adjacent links.With the expansion of network scale,the joint allocation of spatial domain and frequency domain resources can not only avoid interference to ensure the throughput of SBSs and UEs by operating on orthogonal sub-channels,but also improve the SE of the network by reusing sub-channels.For OBH scenario,this paper first establishes the optimization problem of spatial-frequency RA for the mm Wave OBH network,which not only considers the difference of BH traffic demand(BTD)of multiple SBSs,but also the impact of multi-hops on the aggregated BTD.Since the problem can be cast as a two-sided matching problem,this paper absorbs the idea of matching theory to solve it,and proposes an RA algorithm based on matching theory.Simulation results show that the proposed algorithm can guarantee the fairness among SBSs.In addition,with the intensive deployment of SBSs and the rapid increase in the aggregated BTD,the proposed algorithm can adaptively improve the SE of the network,so as to cope with the massive aggregated BH traffic problem in the mm Wave multi-hop BH network with limited bandwidth resources.For IBH scenario,in order to maximize SE and provide flexibility for mm Wave IBH network,this paper assumes that any BH or access link can reuse the same sub-channel,and then establishes the corresponding interference model.On this basis,this paper formulates the optimization problem of spatial-frequency RA for the mm Wave in-band BH network,where the goal is to maximize the sum rate of all UEs with the constraints that the data rate of all UEs and the BH traffic demand of all SBSs can be satisfied.Since that the problem is a combinatorial 0-1 integer programming problem with inequality constraints,this paper firstly transforms the problem into an equivalent optimization problem without any inequality constraints,and then solves it through Markov approximation theory.Simulation results show that the proposed algorithm can effectively reduce the interference and improve the SE performance of the network under different network sizes.