Link to project website: www.one5g.eu
Social media: Twitter @ONE_5G
Horizon 2020 – Call:
Type of action:
E2E-aware Optimizations and advancements for the Network Edge of 5G New Radio
ONE5G has developed numerous promising enhancements to the 5G NR RAN. These have been assessed by logical and numerical analysis as well as by simulations, leading to an extensive set of recommendations for the design of the 5G system.
Optimized RRC state handling and DRX, has been modelled and analysed. Recommendations on RRC state handling allowed to improve accessibility of service and network, reduce the latency and extend battery life (by up to 70%).
Multi-service and context aware radio resource management and optimization has addressed dynamic carrier configuration, multi-cell coordination and RAN slicing. Several scheduling solutions have been developed, addressing multi-user and multi-service resource allocation, managing the constraints from the various classes of services, such as preemptive scheduling, which minimize latency for URLLC services while minimizing the impact on eMBB services.
For CRAN architectures with their possibilities and challenges, signalling and control plane optimizations have been worked out. The introduction of device virtualization has been proposed in CRAN to get rid of constraints set by physical devices and use of compressed-sensing techniques has been recommended to limit training overhead (up to 80% reduction of training overhead).
Dynamic mechanisms for multi-link/multi-node connectivity have been developed, including an optimized usage of decoupled uplink and downlink cell associations. Multi-connectivity has been exploited, either with packet duplications or with secondary cell selection and has been shown to improve resource efficiency.
Dynamic spectrum aggregation mechanisms, including multi-band spectrum aggregation mechanisms have been studied, with specific radio allocation strategies for service mapping, to improve throughput and minimize delay. Suitability of unlicensed frequency bands for URLLLC services has been also explored, showing what can realistically be achieved as reliability targets with NR-U and MulteFire.
Furthermore, ONE5G has studied Advanced mobility optimization and fast agile load balancing mechanisms, with novel E2E and context-aware approaches. Traffic-steering mechanisms have been proposed, relying on QoE (Quality of Experience) proactive management, instead of traditional reactive load balancing schemes. Context-awareness has also been exploited through use of information from social events to forecast service degradation.
A performance analysis of interference management with D2D networks was done. D2D communication has also been studied for relaying in the case of eMBB and mMTC applications, resulting in reduction of power consumption.
For mMTC and URLLC, methods for reduced signalling overhead and higher resource efficiency were designed and evaluated. Reliable signalling schemes and low-overhead natively-secure access protocols have been designed and the benefits of grant-free access were analysed. The project proposed Radio Resource management for Grant-free access have been developed, enabling more efficient use of resources, as well as higher achievable load for URLLC services (up to 90%).
For higher cell capacity and connection density, different non-orthogonal multiple access (NOMA) schemes were designed. Different NOMA schemes have been studied to increase the supported load, particularly important for mMTC services, but NOMA has also been investigated for multi-service coexistence between eMBB and mMTC services.
A larger study on Massive MIMO targeted an optimized antenna design and a reduction of complexity and energy consumption. The impact of array shapes has been analysed and the project produced recommendation an array formatted depending on the considered deployment. Beamforming algorithms have also been considered, and enhancement have been proposed for beam management. New concepts have also been proposed such as multicast beamforming or interference-aware beamforming for wireless backhaul. Advanced pilot and feedback design helps to approach the theoretical gains of MMIMO. Several strategies has been proposed for pilot and feedback schemes for Channel state information (CSI) acquisition, reducing the overhead, such as parametric channel estimation, hierarchical sparse channel estimation or clustering the users to improve the CSI acquisition through spatial multiplexing. The different methods studied led to improved spectral efficiency thanks to overhead reduction.
Implementations with a rapidly configurable hardware, are proposed for a flexible support of multiple services. Flexible and fast reconfigurable hardware components have been developed and implemented into a proof-of-Concept. The project also studied hybrid array architectures and recommended flexible adaptation of arrays according to deployment and traffic conditions.
A study on Advanced link management solutions for interference coordination and -avoidance was done, for CRAN or DRAN deployments and optionally Massive MIMO. Multi-node schedulers have been proposed, or other scheduling methods have been proposed to manage interference and increase throughputs. Studying Efficient signalling and control for advanced connectivity, the limitations of current NR reference signals (RS) in supporting NR-CoMP were identified and designs with improved feedback overhead are provided. Channel State information being crucial for CRAN, the project proposed solutions to improve CSI acquisition and feedback, reducing the CSI feedback overhead.
Simulation and techno economic analysis
The techniques developed in the project have been individually assessed through specific simulations (link and/or system level) for a first evaluation of the gains. A subset of technologies has been integrated into a project-wide system-level simulator developed by WINGS.
A techno-economic analysis has been conducted for four main use cases:
In these four use cases, the main factors weighting on the cost (CPEX and OPEX) have been analysed. The expected costs for different CRAN split options have been compared.
Coming initially from seven individual testbeds, the partners have combined their work into five different Proof-of-Concept (PoC) activities:
Two integrated PoCs have also been produced, introducing integration and interworking between different testbeds
Exploitation and dissemination
The project impacted standardization with more than 50 contributions to 3GPP, with some features included in release 15 and other topics addressed in the various Study Items and Work Items for release 16.
The project actively disseminated the results through:
The project partners exploited the outcomes of the project through development of new competencies, as well as new software and hardware implementations.
|Alcatel-Lucent Deutschland AG (Nokia)||Germany|
|Centre National de la Recherche Scientifique||France|
|Freie Universität Berlin||Germany|
|Huawei Technologies Düsseldorf GmbH||Germany|
|Intel Deutschland GmbH||Germany|
|Samsung Electronics UK||UK|
|Universidad de Malaga||Spain|
|WINGS ICT Solutions||Greece|