5G High Mobility Wireless Communications: Challenges and Solutions

The fifth generation(5G) network is expected to support significantly large amount of mobile data traffic and huge number of wireless connections,to achieve better spectrum- and energy-efficiency,as well as quality of service(QoS) in terms of delay,reliability and security.Furthermore,the 5G network shall also incorporate high mobility requirements as an integral part,providing satisfactory service to users travelling at a speed up to 500 km/h.This paper provides a survey of potential high mobility wireless communication(HMWC) techniques for 5G network.After discussing the typical requirements and challenges of HMWC,key techniques to cope with the challenges are reviewed,including transmission techniques under the fast timevarying channels,network architecture with mobility support,and mobility management.Finally,future research directions on 5G high mobility communications are given.

PECS: Towards Personalized Edge Caching for Future Service-Centric Networks

Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of experience(QoE). Existing content distribution networks(CDN) and mobile content distribution networks(mCDN) have both latency and throughput limitations due to being multiple network hops away from end-users. Here, we first propose a new Personalized Edge Caching System(PECS) architecture that employs big data analytics and mobile edge caching to provide personalized service access at the edge of the mobile network. Based on the proposed system architecture, the edge caching strategy based on user behavior and trajectory is analyzed. Employing our proposed PECS strategies, we use data mining algorithms to analyze the personalized trajectory and service usage patterns. Our findings provide guidance on how key technologies of PECS can be employed for current and future networks. Finally, we highlight the challenges associated with realizing such a system in 5G and beyond.

Energy-Efficient Large-Scale Antenna Systems with Hybrid Digital-Analog Beamforming Structure

A large-scale antenna system(LSAS) with digital beamforming is expected to significantly increase energy efficiency(EE) and spectral efficiency(SE) in a wireless communication system. However, there are many challenging issues related to calibration, energy consumption, and cost in implementing a digital beamforming structure in an LSAS. In a practical LSAS deployment, hybrid digital-analog beamforming structures with active antennas can be used. In this paper, we investigate the optimal antenna configuration in an N × M beamforming structure, where N is the number of transceivers, M is the number of active antennas per transceiver, where analog beamforming is introduced for individual transceivers and digital beamforming is introduced across all N transceivers. We analyze the green point, which is the point of maximum EE on the EE-SE curve, and show that the log-scale EE scales linearly with SE along a slope of-lg2/N. We investigate the effect of M on EE for a given SE value in the case of fixed NM and independent N and M. In both cases, there is a unique optimal M that results in optimal EE. In the case of independent N and M, there is no optimal(N, M) combination for optimizing EE. The results of numerical simulations are provided, and these results support our analysis.

Unified Framework Towards Flexible Multiple Access Schemes for 5G

Non-orthogonal multiple access(NOMA) schemes have achieved great attention recently and been considered as a crucial component for 5G wireless networks since they can efficiently enhance the spectrum efficiency, support massive connections and potentially reduce access latency via grant free access. In this paper, we introduce the candidate NOMA solutions in 5G networks, comparing the principles, key features, application scenarios, transmitters and receivers, etc. In addition, a unified framework of these multiple access schemes are proposed to improve resource utilization, reduce the cost and support the flexible adaptation of multiple access schemes. Further, flexible multiple access schemes in 5G systems are discussed. They can support diverse deployment scenarios and traffic requirements in 5G. Challenges and future research directions are also highlighted to shed some lights for the standardization in 5G.

人工智能在5G无线网络中的标准与应用进展

论述了人工智能对5G无线网络的重要价值,指明了人工智能在5G无线网络中的重要应用场景、标准进展和典型应用方案,提出了人工智能技术在5G无线网络中的挑战及发展建议。

面向智能电力的无线光技术研究与进展

随着各种新兴信息技术与电力电网的融合进一步走向深入,依托并服务于智能电力的多种无线光技术方案先后被提出,并形成了初步的规模。分别从电力线通信与可见光通信融合的信道特性及传输方案、混合射频电力可见光通信、电力无线光室内定位与中继、高压线路无线光监测等诸多方面阐述智能电力无线光技术的主要分类与前沿进展。结合多款原型实验,介绍了目前各类智能电力无线光技术方案在传输速率、覆盖范围、定位精度、能耗水平等方面所能达到的主要技术指标水平;最后给出智能电力无线光技术所面临的主要挑战与潜在的解决途径。

Data-driven resource allocation with trac load prediction

Wireless big data is attracting extensive attention from operators,vendors and academia,which provides new freedoms in improving the performance from various levels of wireless networks.One possible way to leverage big data analysis is predictive resource allocation,which has been reported to increase spectrum and energy resource utilization eciency with the predicted user behavior including user mobility.However,few works address how the trac load prediction can be exploited to optimize the data-driven radio access.We show how to translate the predicted trac load into the essential information used for resource optimization by taking energy-saving transmission for non-real-time user as an example.By formulating and solving an energy minimizing resource allocation problem with future instantaneous bandwidth information,we not only provide a performance upper bound,but also reveal that only two key parameters are related to the future information.By exploiting the residual bandwidth probability derived from the trac volume prediction,the two parameters can be estimated accurately when the transmission delay allowed by the user is large,and the closed-form solution of global optimal resource allocation can be obtained when the delay approaches in nity.We provide a heuristic resource allocation policy to guarantee a target transmission completion probability when the delay is no-so-large.Simulation results validate our analysis,show remarkable energy-saving gain of the proposed predictive policy over non-predictive policies,and illustrate that the time granularity in predicting trac load should be identical to the delay allowed by the user.