Towards Smart Grid Support in 5G: Re-designing the LTE Random Access

Transcription

1 Chair of Communication Networks Department of Electrical and Computer Engineering Technical University of Munich Towards Smart Grid Support in 5G: Re-designing the LTE Random Access ITG 5.2 Workshop, Munich, Germany Mikhail Vilgelm Wolfgang Kellerer 2017 Technical University of Munich

2 Talk Outline Smart Grid Smart Grid as Machine Type Communication Cellular Networks for Smart Grid: Advantages and Challenges Random Access in LTE-Advanced Modeling & State of the Art Prioritization via Resource Separation More on Smart Grid Communications Outlook 2

3 Talk Outline Smart Grid Smart Grid as Machine Type Communication Cellular Networks for Smart Grid: Advantages and Challenges Random Access in LTE-Advanced Modeling & State of the Art Prioritization via Resource Separation More on Smart Grid Communications Outlook 3

4 Smart Grid: An Overview From: [SG1-4] Power Generation Power Transmission Power Distribution Distributed Generation / Microgrids Power Consumption 4

5 Smart Grid: An Overview From: [SG1-4] Wide Area Monitoring, Protection and Control Microgrid Management Demand Side Management Power Generation Power Transmission Power Distribution Distributed Generation / Microgrids Power Consumption Utility Monitoring and Control Advanced Metering Infrastructure Control of Distributed Power Generation Electrical Vehicle Charging 4

6 Smart Grid: An Overview From: [SG1-4] Public Networks / Internet Wide Area Network Neighborhood Area Network Field Area Network Local Utility Network Substation Network Industrial Area Network Business Area Network Home Area Network Power Generation Power Transmission Power Distribution Distributed Generation / Microgrids Power Consumption 5-20ms % ms 99.99% 500ms 99.5% 4 >1s 99%

7 Smart Grid as Machine Type Communication Data-only subscriptions no voice service required Enhanced coverage indoor and basement installations Low cost/complexity <10$ per modem MTC Massive amount of devices orders of magnitude higher than mmtc conventional devices Longer battery life up to 10 years Wide range of performance requirements umtc from smart meeting to wide area protection From: [SG1-4], [RA7] 5

8 Cellular Communication for Smart Grid/MTC + Available infrastructure coverage, mobility + Support for Quality of Service (bearer level) different performance requirements + High datarate & low latency - Indoor / basement penetration - High complexity and cost - High power consumption - Support massive connectivity EC-GSM-IoT, NB- IoT, emtc obtaining & maintaining the radio resources Part of requirements for evolution towards 5G [RA7] Our Research [RA7] ICT METIS, Deliverable 6.6 Version 1 Final report on the METIS 5G system concept and technology roadmap, Tech. Rep.,

9 Talk Outline Smart Grid Smart Grid as Machine Type Communication Cellular Networks for Smart Grid: Advantages and Challenges Random Access in LTE-Advanced Modeling & State of the Art Prioritization via Resource Separation More on Smart Grid Communications 7

10 Random Access Channel in LTE-Advanced Infrequent transmissions (smart meters) Need to obtain Random Access Procedure cannot maintain PUSCH, PUCCH... doesn t scale PRACH UE Broadcast SIB2 enodeb 6 RB MSG1: RA Preamble MSG2: RA Response MSG3: RRC Connection Request Frequency MSG4: RRC Connection Setup Time 1 subframe Multi-channel slotted ALOHA Prone to collisions Throughput ~0 under high load (mmtc) Very high access delay 8

11 LTE RACH: Modeling Non-persistent overload Persistent overload Sudden event (emergency, blackout, etc.) (Close to) synchronous request arrival Target efficient event resolution One-shot arrival or group paging Infrequent channel access from mmtc constantly high load on RACH Independent arrival Target average performance Model Delta arrivals or Beta distribution Poisson for IAT Metrics Total service time Steady-state parameters: delay, throughput, drop ratio, etc. 9

12 LTE RACH: State of the Art Roadmap * Non-persistent overload Persistent overload Performance Tree algorithms [RA4, RA5, LKN3], Distributed Queuing [RA10] Dynamic ACB [RA2], Resource reuse [RA6, LKN2], novel RA (SIC, NOMA) [RA7, RA8], connection-less access [RA8], Quality of Service Access barring (ACB, EAB) [RA2, RA3], Resource separation [RA1, RA9, LKN1], * List is non-exhaustive Today s talk 10

13 Frequency Resource Separation in LTE-RACH PUSCH, PUCCH... PRACH RACH Resources: Time / Frequency / Preambles 6 RB Concept of resource separation Different QoS classes have different: RACH periodicity [RA9] Subframes / frequencies [RA9] Use different preambles [RA1, RA9] Time 1 subframe Challenge: given n QoS classes, how to determine the split of M resources into m 1, m 2, m n? Figure from [RA9] 11

14 Throughput-Maximizing Preamble Allocation (1/5) Steady-state performance: Throughput Drop ratio Delay T = λ (1 δ) M δ = (1 f) W D = f(f) Initial arrivas λ Backlog preamble choice from M succes f, delay D, throughput T NO collision? back-off drop δ YES attempts <W? Proposition: Given attempt limit W, arrival rate λ and number of resources m, maximum throughput T max is achieved with normalized arrival rate: ρ = λ m = 1 e e W From: [LKN1] M. Vilgelm, M. Gürsu, W. Kellerer, M. Reisslein, LATMAPA: Load-Adaptive Throughput-Maximizing Preamble Allocation for Prioritization in 5G Random Access, IEEE Access,

15 Throughput-Maximizing Preamble Allocation (2/5) Two QoS classes: Class I: prioritized Class II: non-prioritized Input: Arrival rates λ I, λ II Total resources M, limit W Output: Allocated preambles m I, m II Fairness controlled by prioritization factor r [0, 1] From: [LKN1] M. Vilgelm, M. Gürsu, W. Kellerer, M. Reisslein, LATMAPA: Load-Adaptive Throughput-Maximizing Preamble Allocation for Prioritization in 5G Random Access, IEEE Access,

16 Throughput-Maximizing Preamble Allocation (3/5) Performance: no fairness, strict prioritization From: [LKN1] 14

17 Throughput-Maximizing Preamble Allocation (4/5) Providing fairness: r = 1 fair split r = 0 strict prioritization Adjusting PRACH configuration: More PRACH slots per frame, if total arrival rate not supported beyond blue line From: [LKN1] 15

18 Throughput-Maximizing Preamble Allocation (5/5) Contributions: Analysed the trade-offs of preamble separation Load-Adaptive Throughput-Maximizing Preamble Allocation Perfect isolation between QoS class, and fairness support Preambles generic resources Reliable estimation / prediction of the arrival rates? Fast prioritization for non-persistent overload? Guarranteeing worst-case performance? From: [LKN1] M. Vilgelm, M. Gürsu, W. Kellerer, M. Reisslein, LATMAPA: Load-Adaptive Throughput-Maximizing Preamble Allocation for Prioritization in 5G Random Access, IEEE Access,

19 LTE RACH: State of the Art Roadmap * Non-persistent overload Persistent overload Performance Tree algorithms [RA4, RA5, LKN3], Distributed Queuing [RA10] Dynamic ACB [RA2], Resource reuse [RA6, LKN2], novel RA (SIC, NOMA) [RA7, RA8], connection-less access [RA8], Quality of Service Access barring (ACB, EAB) [RA2, RA3], Resource separation [RA1, RA9, LKN1], * List is non-exhaustive 17

20 Talk Outline Smart Grid Smart Grid as Machine Type Communication Cellular Networks for Smart Grid: Advantages and Challenges Random Access in LTE-Advanced Modeling & State of the Art Prioritization via Resource Separation More on Smart Grid Communications Outlook 18

21 More on Smart Grid Communications (1/2) Spatially re-use the resources via aggregation Fixed / dynamic assignment of clusterheads (CLH) UEs contend on the link UE-CLH Clustered mues enodeb CLH aggregates and forwards to enb mue CLH enodeb RA preamble D RA RA reply RRC Conn Request Question: how does aggregation impact the contention performance? D A RA Success Link mue- CLH Trigger RRC Connection Reply Aggregation Forwarding Aggregated Requests Analytically model and quantify the aggregation trade-offs in [LKN2] [LKN2] M. Vilgelm, W. Kellerer, Impact of Request Aggregation on Machine Type Connection Establishment in LTE-Advanced, IEEE WCNC,

22 More on Smart Grid Communications (2/2) Increasing RACH capacity with tree splitting algorithms [LKN3] Collision feedback with set of resources Throughput beyond 1/e Figure due: A. Martinez Alba, Master s Thesis Non-persistent overload [LKN3] M. Gürsu et al., Hybrid Collision Avoidance-Tree Resolution for M2M Random Access, IEEE Trans. on AES, 2017 (accepted) Underlying applications in Smart Grid: feedback control systems Cyber-Physical Networks: Joint Control/Communication design Focus on Wireless Medium Access Control DFG Project Cyber-Physical Networks Preliminary results in [LKN4] [LKN4] M. Vilgelm, M. H. Mamduhi, W. Kellerer, S. Hirche, Adaptive Decentralized MAC for Event-Triggered NCS, ACM HSCC,

23 Talk Outline Smart Grid Smart Grid as Machine Type Communication Cellular Networks for Smart Grid: Advantages and Challenges Random Access in LTE-Advanced Modeling & State of the Art Prioritization via Resource Separation More on Smart Grid Communications Outlook 21

24 Conclusions & Outlook Smart Grid multiple MTC applications with diverse requirements Smart Grid Communications future cellular networks need to support massive connectivity RA procedure re-design Resource separation for QoS provisioning Aggregation (persistent overload) increase the number of resources Tree algorithms (non-persistent) increase resource utilization Combination of the approaches? Applications to narrowband systems? (NB-IoT, emtc, ) Alternative channel access methods? (NOMA, ) 22

25 References (1/2) [LKN1] M. Vilgelm, M. Gürsu, W. Kellerer, M. Reisslein, LATMAPA: Load-Adaptive Throughput-Maximizing Preamble Allocation for Prioritization in 5G Random Access, IEEE Access, 2017 [LKN2] M. Vilgelm, W. Kellerer, Impact of Request Aggregation on Machine Type Connection Establishment in LTE- Advanced, IEEE WCNC, 2017 [LKN3] M. Gürsu, M. Vilgelm, W. Kellerer, M. Reisslein, Hybrid Collision Avoidance-Tree Resolution for M2M Random Access, IEEE Trans. on AES, 2017 (accepted) [LKN4] M. Vilgelm, M. H. Mamduhi, W. Kellerer, S. Hirche, Adaptive Decentralized MAC for Event-Triggered NCS, ACM HSCC, 2016 [RA1] K.-D. Lee, S. Kim, and B. Yi, Throughput comparison of random access methods for M2M service over LTE networks, in Proc. IEEE GLOBECOM Workshops, Dec [RA2] S. Duan, V. Shah-Mansouri, Z. Wang, and V. Wong, D-ACB: Adaptive congestion control algorithm for bursty M2M traffic in LTE networks, IEEE Trans. Veh. Technol., Dec [RA3] Study on RAN Improvements for Machine-Type Communications (Release 11) 3GPP Technical Specification Group Radio Access Network, 3GPP document , 3rd Generation Partnership Project, Sep [RA4] B. S. Tsybakov and V. A. Mikhailov, Free synchronous packet access in a broadcast channel with feedback, Problemy Peredachi Informatsii, vol. 14, no. 4, pp , [RA5] G. Madueno, S. Stefanovic, and P. Popovski, Efficient LTE access with collision resolution for massive M2M communications, in Proc. IEEE Globecom Workshops, Dec 2014, pp [RA6] K. S. Ko, M. J. Kim, K. Y. Bae, D. K. Sung, J. H. Kim, and J. Y. Ahn, A Novel Random Access for Fixed-Location Machine-to-Machine Communications in OFDMA Based Systems, IEEE Communications Letters, Sep

26 References (2/2) [RA7] ICT METIS, Deliverable 6.6 Version 1 Final report on the METIS 5G system concept and technology roadmap, Tech. Rep., [RA8] Shirvanimoghaddam, Mahyar, Mischa Dohler, and Sarah Johnson. "Massive Non-Orthogonal Multiple Access for Cellular IoT: Potentials and Limitations." arxiv preprint arxiv: (2016). [RA9] T.-M. Lin, C.-H. Lee, J.-P. Cheng, and W.-T. Chen, PRADA: prioritized random access with dynamic access barring for MTC in 3GPP LTE-A networks, IEEE Transactions on Vehicular Technology, 2014 [RA10] Laya, A., Kalalas, C., Vazquez-Gallego, F., Alonso, L., & Alonso-Zarate, J. Goodbye, aloha!. IEEE access, 2016 [SG1] Nokia, Whitepaper on Optimizing LTE for the IoT, 2014 [SG2] Siemens, Whitepaper on Smart Communications for Smart Grid, 2013 [SG3] Cheng et al, Feasibility Study of Applying LTE to Smart Grid, IEEE SmartGridComm, 2011 [SG4] Patel et al, Assessing Communications Technology Options for Smart Grid Applications, IEEE SmartGridComm,

27 Questions? 25