Functional Level Virtualization Prototype for 5G Core Networks: The core networks are evolving from Evolve Packet Core (EPC) in 4G to Service-Based Architecture (SBA) in 5G as that defined in 3GPP Release 15. For this evolution, we have developed RECO, a Reconfigurable Core Network for future 5G communication systems (http://reconet.org/). With RECO, a network component can use different modules at the same time or change modules at execution time for different applications or services to achieve the vision of network slicing and functional level virtualization in fine grain. This demonstration shows the prototype that we have implemented for RECO. We will demo RECO with real commercial UEs and a real commercial LTE small cell eNB. We will demonstrate the functional level virtualization technology, which is important to level up the flexibility of future 5G core networks.
‘One-click-deployment’ of a Truly Cloud-Native End-to-End cellular network solution over hybrid clouds-Infrastructure: 5G must become the ubiquitous fabric blending universal connectivity (to humans, robots, sensors…) with cloud versatility and scalability. For realizing this vision, the Platform-As-A-Service (PaaS) model is adopted.
PaaS promises to deliver network services and applications with higher agility and performance through “ancillary services” – scalability, high availability, state management, controllers, orchestrator… – provided once by the PaaS. Developers and service providers can therefore concentrate on their applications and businesses and improve time to market.
To solve the “one size does not fit all” dilemma, instead of building an “end-to-end hard-wired” solution (as it is the case now in the market) we adopt the “build-to-order” paradigm that best matches the business, latency, throughput… requirements thanks to the platform “composability”. A component is an extension of the Reusable Functional Block (RFB) abstracting various virtualization (VM, containers, unikernels) & acceleration (GPU, FPGA, packet processors) technologies. Thanks to RFB, we can ‘build-to-order’ platforms suiting targeted use-case: platforms are made of VNFs (RAN, CORE, MEC, Video application, xHAUL…) and well-selected ancillary (orchestrator, intent-based controllers, message bus…) components.
This demonstration shows a “one-click-deployment” of an end-to-end cellular network over a distributed infra-structure FRONT-END/EDGE/CENTRAL/PUBLIC clouds:
- RAN is split in two components (Central Unit/Distributed Unit) running in FRONT-END and EDGE clouds respectively,
- xHAUL connecting FRONT-END and EDGE clouds supports intent-based networking,
- CORE is split in four components running in PUBLIC cloud (Amazon Public Cloud),
- Ancillary services (orchestrator, SDN controller) are optimized to make the Platform-As-A-Service (PaaS) telco-grade.
- All components (VNF and ancillary) are deployed on-demand.
Distributed Multi-User MIMO network with multi-antenna devices using SDRs: This demonstration shows the working of a distributed MU-MIMO (D-MIMO) based Wi-Fi (802.11ac compliant) network using SDRs (USRP B210s and X310s). D-MIMO synchronizes and coordinates the transmissions from spatially separate Wi-Fi access points (APs) to facilitate multiple simultaneous transmissions in the downlink. Four USRP B210s, located in four corners of the testbed, are used as Wi-Fi APs, which are synchronized using an external octo-clock. Wi-Fi users are distributed throughout the testbed. Novel algorithms for user selection in the downlink are proposed and implemented. Experiments describe the merits of using D-MIMO compared to state-of-the-art configuration and the associated implementation challenges.
Uplink packet detection and demodulation of OFDM frames for a Massive MIMO system using CPU and GPU: This demonstration shows the demodulation of the OFDM symbols for a Massive MIMO system using GPU at the back-end. The demo contains users (B210s), which are situated on all 4 corners of the testbed, sending OFDM frames to the Massive MIMO system (16 antennas, 8 X310s), which acts as a Base Station (BS) situated in the corner of the testbed. The back-end of the BS consists of CPU and GPU. The performance of CPU and GPU for channel estimation and demodulation of OFDM symbols is compared with variation in parameters such as FFT length and number of channels.
Jyh-Cheng Chen (S’96–M’99–SM’04–F’12) has been a Faculty Member with National Chiao Tung University (NCTU), Hsinchu, Taiwan since 2010. Prior to that, he was with Bellcore /Telcordia Technologies in New Jersey, USA, for 5 years, and National Tsing Hua University (NTHU), Hsinchu, Taiwan, for 7 years. He is also now serving as the Convener, Computer Science Program, Ministry of Science and Technology, Taiwan. Dr. Chen received numerous awards, including the Outstanding Teaching Awards from both NCTU and NTHU, the Outstanding Research Award from the Ministry of Science and Technology, the Outstanding I. T. Elite Award, Taiwan, the K. T. Li Breakthrough Award from the Institute of Information and Computing Machinery, and the Telcordia CEO Award. He is a Fellow of the IEEE and a Distinguished Member of the ACM. He was a member of the Fellows Evaluation Committee, IEEE Computer Society. He received the Ph.D. degree from the State University of New York at Buffalo, USA, in 1998.
Bessem Sayadi is a Research Manager in Nokia Bell-Labs France. He received M.Sc. (00) and Ph.D. (03) degrees in Control and Signal processing from SUPELEC with highest distinction. He worked previously as a postdoctoral fellow in the National Centre for Scientific Research (CNRS), and as a senior researcher engineer in Orange Labs. He is leading the Next Generation Platform as a Service project funded by EU in 5G-PPP Phase2. He is the technical manager of the Superfluidity project funded by EU in 5G-PPP Phase 1. He is the chair of the 5G-PPP Software Networks Working Group and member of the 5G-PPP SB/TB board. His main research interests are in Virtualization & Cloudification, 5G, Microservice Architecture. He has authored over 70 publications in journal and conference proceedings and serves as a regular reviewer for several technical journals and conferences. He holds 28 patents and has more than twenty patent applications pending in video coding and wireless communications.
Bhargav Gokalgandhi is currently a Doctoral student at the Electrical and Computer Engineering Department at Rutgers University and is a Graduate Research Assistant at Wireless Information Network Laboratory (WINLAB). He completed his under-graduate in Electronics and Telecommunication Engineering at D. J. Sanghvi College of Engineering, Mumbai University, Mumbai, India and his Diploma in Electronics and Telecommunication Engineering at St. Xavier’s Technical Institute, Mumbai, India. His interests lie in the field of Massive MIMO, Distributed MIMO, Wireless Communication, Digital Communications, Networking, and Signal Processing for Communication Systems.
Neelakantan (Neel) Nurani Krishnan is a PhD candidate and research assistant with WINLAB, Rutgers University, NJ. He obtained his bachelors in electrical engineering in 2014 from the University of Calicut, India, where he won the institute gold medal for outstanding academic achievement and holds a masters in electrical engineering from Rutgers University. He has interned with Ericsson (Piscataway, NJ), Schlumberger-Doll Research Center (Cambridge, USA), and Nokia Bell Labs (Sunnyvale, CA). His interests lie at the intersection of analytical modeling and experimental validation using hardware, particularly in the realm of distributed MIMO, massive MIMO, MU-MIMO, and wireless network design (Wi-Fi and LTE).
Ivan Seskar is an Associate Director at WINLAB, Rutgers University responsible for experimental systems and prototyping projects. He is currently the program director for the COSMOS project responsible for the New York City NSF PAWR deployment, the PI for the NSF GENI Wireless project, which resulted in campus deployments of LTE/WiMAX base stations at several US universities, and the PI for the NSF CloudLab deployment at Rutgers. He has also been the co-PI and project manager for all three phases of the NSF-supported ORBIT mid-scale testbed project at WINLAB, successfully leading technology development and operations since the testbed was released as a community resource in 2005 and for which the team received the 2008 NSF Alexander Schwarzkopf Prize for Technological Innovation. Ivan is a co-chair of the IEEE 5G Testbed Working Group, a Senior Member of the IEEE, a member of ACM and the co-founder and CTO of Upside Wireless Inc.