The analysis of coverage probability,ASE and EE in heterogeneous ultra-dense networks with power control

The ultra-dense network is a promising technology to increase the network capacity in the forthcoming fifthgeneration(5G)mobile communication networks by deploying lots of low power Small Base Stations(SBSs)which overlap with Macro Base Stations(MBSs).The interference and energy consumption increase rapidly with the number of SBSs although each SBS transmits with small power.In this paper,we model a downlink heterogeneous ultra-dense network where a lot of SBSs are randomly deployed with MBSs based on the Poisson point process.We derive the coverage probability and its variance,and analyze the area spectral efficiency and energy efficiency of the network considering three Fractional Power Control(FPC)strategies.The numerical results and Monte Carlo simulation results show that power control can mitigate the interference and balance the performances of inner-user and edge-user equipments.Especially,a great improvement of energy efficiency is archived with a little loss of area spectral efficiency when FPC is adopted.Finally,we analyze the effect of base stations’(BSs’)sleeping on the performance of the network when it is partially loaded.

UAV Assisted Heterogeneous Wireless Networks:Potentials and Challenges

By fully exploiting the spatial resources, unmanned aerial vehicles （UAVs） are expected to serve as an efficient complementary to terrestrial wireless communication system to provide enhanced coverage and reliable connectivity to ground users. With the growing deployment of units such as small cell base stations （BSs）, however, the incurred severe interference may hinder the potential benefits of the integration of UAVs. In this paper, we first discuss the intrinsic features and potential benefits of UAVs and introduce the architecture of multi-layer heterogeneous wireless network （MHetNet）, in which traditional wireless network is assisted by UAVs. Then, an explicit discussion on the factors that limit the performance of MHetNet is presented, including the UAV topology, UAV density, and spectrum sharing of UAV and terrestrial networks. We use simulation results to investigate the performance of MHetNet in terms of spatial throughput （ST）. It is shown that, together with the densities of UAV and terI＇estrial networks, the altitude of UAV is a limiting factor that should be optimized to improve the ST of MHetNet.

Load Distribution of Base Stations in User-Centric Heterogeneous UDN

In ultra-dense networks(UDN),multiple association can be regarded as a user-centric pattern in which a user can be served by multiple base stations(BSs).The data rate and quality of service can be improved.However,BSs in user-centric paradigm are required to serve more users due to this multiple association scheme.The improvement of system performance may be limited by the improving load of BSs.In this letter,we develope an analytical framework for the load distribution of BSs in heterogeneous user-centric UDN.Based on open loop power control(OLPC),a user-centric scheme is considered in which the clustered serving BSs can provide given signal to interference plus noise ratio(SINR)for any typical user.As for any BS in different tiers,by leveraging stochastic geometry,we derive the Probability Mass Function(PMF)of the number of the served users,the Cumulative Distribution Function(CDF)of total power consumption,and the CDF bounds of downlink sum data rate.The accuracy of the theoretical analysis is validated by numerical simulations,and the effect the system parameters on the load of BSs is also presented.

NOMA-MEC系统中基于改进遗传算法的协作式计算卸载与资源管理

为平衡网络负载与充分利用网络资源,针对超密集异构的多用户和多任务边缘计算网络,在用户时延约束下,该文构造了协作式计算任务卸载与无线资源管理的联合优化问题以最小化系统能耗。问题建模时,为应对基站超密集部署导致的严重干扰问题,该文采用了频带划分机制,并引入了非正交多址技术(NOMA)以提升上行频谱利用率。鉴于该目标优化问题具备非线性混合整数的形式,根据多样性引导变异的自适应遗传算法(AGADGM),设计出了协作式计算卸载与资源分配算法。仿真结果表明,在严格满足时延约束条件下,该算法能获取较其他算法更低的系统能耗。