Towards the Deep Convergence of Communication and Computing in RAN: Scenarios, Architecture, Key Technologies, Challenges and Future Trends

To accommodate the diversified emerging use cases in 5G,radio access networks(RAN)is required to be more flexible,open,and versatile.It is evolving towards cloudification,intelligence and openness.By embedding computing capabilities within RAN,it helps to transform RAN into a natural cost effective radio edge computing platform,offering great opportunity to further enhance RAN agility for diversified services and improve users’quality of experience(Qo E).In this article,a logical architecture enabling deep convergence of communication and computing in RAN is proposed based on O-RAN.The scenarios and potential benefits of sharing RAN computing resources are first analyzed.Then,the requirements,design principles and logical architecture are introduced.Involved key technologies are also discussed,including heterogeneous computing infrastructure,unified computing and communication task modeling,joint communication and computing orchestration and RAN computing data routing.Followed by that,a VR use case is studied to illustrate the superiority of the joint communication and computing optimization.Finally,challenges and future trends are highlighted to provide some insights on the potential future work for researchers in this field.

Leader-following consensus protocols for formation control of multi-agent network

Two protocols are presented,which can make agents reach consensus while achieving and preserving the desired formation in fixed topology with and without communication timedelay for multi-agent network.First,the protocol without considering the communication time-delay is presented,and by using Lyapunov stability theory,the sufficient condition of stability for this multi-agent system is presented.Further,considering the communication time-delay,the effectiveness of the protocol based on Lyapunov-Krasovskii function is demonstrated.The main contribution of the proposed protocols is that,as well as the velocity consensus is considered,the formation control is concerned for multi-agent systems described as the second-order equations.Finally,numerical examples are presented to illustrate the effectiveness of the proposed protocols.

Second-order consensus in networks of dynamic agents with communication time-delays

This paper proposes second-order consensus protocols with time-delays and gives the measure of the robustness of the protocols to the time-delay existing in the network of agents with second-order dynamics. By employing a frequency domain method, it is proven that the information states and their time derivatives of all the agents in the network achieve consensus asymptotically, respectively, for appropriate communication timedelay if the topology of weighted network is connected. Particularly, a tight upper bound on the communication time-delay that can be tolerated in the dynamic network is found. The consensus protocols are distributed in the sense that each agent only needs information from its neighboring agents, which reduces the complexity of connections between neighboring agents significantly. Numerical simulation results are provided to demonstrate the effectiveness and the sharpness of the theoretical results for second-order consensus in networks in the presence of communication time-delays.

AN ADAPTIVE CDMA RAKE RECEIVER

A new adaptive RAKE receiver is proposed which uses pilot sig-nal for channel estimation in CDMA down link communications. The configuration of the system is presented and the performance is also evaluated forboth adaptive RAKE receiver and the non-adapti

Improving microwave brightness temperature predictions based on Bayesian model averaging ensemble approach

The choices of the parameterizations for each component in a microwave emission model have significant effects on the quality of brightness temperature （Tb） sim- ulation. How to reduce the uncertainty in the Tb simulation is investigated by adopting a statistical post-processing procedure with the Bayesian model averaging （BMA） ensemble approach. The simulations by the community microwave emission model （CMEM） cou- pled with the community land model version 4.5 （CLM4.5） over China's Mainland are con- ducted by the 24 configurations from four vegetation opacity parameterizations （VOPs）, three soil dielectric constant parameterizations （SDCPs）, and two soil roughness param- eterizations （SRPs）. Compared with the simple arithmetical averaging （SAA） method, the BMA reconstructions have a higher spatial correlation coefficient （larger than 0.99） than the C-band satellite observations of the advanced microwave scanning radiometer on the Earth observing system （AMSR-E） at the vertical polarization. Moreover, the BMA product performs the best among the ensemble members for all vegetation classes, with a mean root-mean-square difference （RMSD） of 4 K and a temporal correlation coefficient of 0.64.

以“科学”的眼光在大众传播领域传播科学

科学的传播发展至今,已经超越了传统的科普传播方式,步入了崭新的传播环境下的对话模式中。科学传播必须还科学的本来面目,不仅仅进行科学知识、技能的传播,还有科学方法、科学精神、科学史的传播。大众传媒在科学传播中是除学校之外最重要的一级,无论是对科学事件的报道还是日常报道中,科学传播的理念都对普通受众有具体的指导意义,网络媒体在科学传播中更具有时代性的实践意义。

Short-Term Effects of Experimental Warming and Precipitation Manipulation on Soil Microbial Biomass C and N, Community Substrate Utilization Patterns and Community Composition

Soil microorganisms are major drivers of soil carbon(C) cycling;however,the response of these microorganisms to climate change remains unclear.In the present study,we investigated how 18 months of multifactor climate treatments(warmed air temperature by 3℃ and decreased or increased precipitation manipulation by 30%) affected soil microbial biomass C and nitrogen(N),community substrate utilization patterns,and community composition.Decreased and increased precipitation significantly reduced microbial biomass C by 13.5% and 24.9% and microbial biomass N by 22.9% and 17.6% in unwarmed plots,respectively(P<0.01).Warming enhanced community substrate utilization by 89.8%,20.4%,and 141.4% in the natural,decreased,and increased precipitation plots,respectively.Particularly,warming significantly enhanced the utilization of amine and carboxylic acid substrates among all precipitation manipulation plots.Compared with the natural air temperature with natural precipitation treatment,other treatments affected fungal community richness by -0.9% to 33.6% and reduced the relative abundance of the dominant bacterial and fungal groups by 0.5% to 6.8% and 4.3% to 10.7%,respectively.The warming and/or precipitation manipulation treatments significantly altered Zygomycota abundance(P<0.05).Our results indicate that climate change drivers and their interactions may cause changes in soil microbial biomass C and N,community substrate utilization patterns,and community composition,particularly for the fungal community,and shifts in the microorganism community may further shape the ecosystems function.