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Resource Allocation Algorithms Design for 5G Wireless Networks - - PowerPoint PPT Presentation

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Resource Allocation Algorithms Design for 5G Wireless Networks Vincent Wong Department of Electrical and Computer Engineering The University of British Columbia November 5, 2016 0 5G Overview User Data Rate 1000K E2E Latency 0.1 1 Gbps

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Resource Allocation Algorithms Design for 5G Wireless Networks

Vincent Wong Department of Electrical and Computer Engineering The University of British Columbia

November 5, 2016

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5G Overview

Traffic Devices Applications

UHD 3D Video Augmented Reality Mobile Cloud M2M Devices Wearables Smart Phones Smart Home Industry e-Health Energy Transportation

User Data Rate 0.1 – 1 Gbps 1000K Connections/km2 E2E Latency < 10 ms

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3GPP Use Cases

§ Enhanced Mobile Broadband (eMBB)

Devices

  • Smart Phones
  • Tablets

Applications

  • UHD 3D Video

Streaming

  • Virtual / Augmented

Reality

  • Mobile Cloud / Cloud

Gaming

Requirements

  • Peak Data Rate

~ Tens of Gbps

  • User Data Rate

~ 0.1-1 Gbps

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3GPP Use Cases

§ Massive Machine-type Communications (mMTC)

Devices

  • Wearables
  • Smart Home

Appliances

  • Smart Traffic Signs

/ Lights

  • Sensors

Applications

  • Home Automation
  • Intelligent

Transportation Systems

  • Asset Tracking
  • Environmental

Monitoring

Requirements

  • High Connection

Density ~ 1000K Devices per km2

  • Extended Battery

Lifetime ~ 15 Years

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3GPP Use Cases

§ Ultra-Reliable Low Latency Communications (URLLC)

Devices

  • Autonomous

Vehicles

  • Health Monitoring

Devices

  • Remote Surgery

Robotics

  • Industrial Sensors

and Actuators

Applications

  • e-Health
  • Industrial

Automation

  • Autonomous

Driving

Requirements

  • High Reliability

Rate ~ 0.99999

  • Low E2E Latency

~ < 10 ms

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Key Technologies Filling the Gap

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5G Network Architecture

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Cloud Radio Access Network (C-RAN) Architecture

§ Decouple the baseband unit (BBU) and the remote radio head (RRH) § Place BBUs in a data center for centralized control and processing § Reduce CAPEX and OPEX for system upgrade and maintenance § Improve spectral efficiency via centralized interference control and coordinated multi-point transmission (CoMP)

UE RRH

  • ptical fiber

1 3 2 4 5 6 C1 C2 C3 C4 C5 C6

BBU pool

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Network Slicing

§ Enables flexible and dynamic slicing of network resources Resource Management Algorithm

Slice 1 Slice 2 Slice 3 Slice N – 2 Slice N – 1 Slice N Service Provider A Service Provider B Service Provider C Cloud Gaming E-Health UHD Video

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Slice 4 Slice 5 Environmental Monitoring V2V eMBB URLLC mMTC

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Problem Statement 1: User-Centric Resource Sharing for C-RAN

§ Goal

  • Quality of service guarantee
  • Service isolation
  • Traffic variation, user mobility

§ Given

  • Set of service providers
  • Capacity of fronthaul links

§ Variables

  • Time slot, channel allocation
  • User association

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§ Techniques

  • Mixed integer non-linear programming

§ Multi-timescale resource allocation

  • Global (local) resource allocation at longer (smaller) time scale
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Problem Statement 2: Beamforming Design in C-RAN

§ Given

  • Set of users and RRHs
  • Capacity of fronthaul links
  • Imperfect CSI

§ Variables

  • Beamforming vector for

each user § Techniques

  • Non-linear programming
  • Convex relaxation
  • Semidefinite programming

UE RRH

  • ptical fiber

1 3 2 4 5 6 C1 C2 C3 C4 C5 C6

BBU pool

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§ Goal

  • Maximize users’ satisfaction
  • SINR and power constraints
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Problem Statement 3: Non-Orthogonal Multiple Access (NOMA) for Narrowband IoT Systems

§ Goal

  • Maximize connection density

§ Given

  • Set of mMTC, URLLC devices
  • NB-IoT specification
  • Latency and power

requirement § Variables

  • Sub-carrier allocation
  • Transmit power

§ Techniques

  • Non-orthogonal multiple

access (NOMA)

  • Combinatorial optimization

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Sample Publications in Wireless Networking in 2016

§

  • B. Niu et al., “A Dynamic Resource Sharing Mechanism for Cloud Radio Access Networks,”

IEEE Trans. on Wireless Communications, 2016. §

  • Z. Wang et al., “How to Download More Data from Neighbors? A Metric for D2D Data

Offloading Opportunity,” IEEE Trans. on Mobile Computing, 2016. §

  • B. Ma et al., “Multimedia Content Delivery in Millimeter Wave Home Networks,” IEEE Trans.
  • n Wireless Communications, 2016.

§

  • S. Duan et al., “D-ACB: Adaptive Congestion Control Algorithm for Bursty M2M Traffic in LTE

Networks,” IEEE Trans. on Vehicular Technology, 2016. §

  • L. Xiang et al., “Cache-Enabled Physical-Layer Security for Video Streaming in Wireless

Networks with Limited Backhauls,” in Proc. of IEEE GLOBECOM Workshop, Dec. 2016. §

  • Z. Wang et al., “Transmit Beamforming for QoE Improvement in C-RAN with Mobile Virtual

Network Operators,” in Proc. of IEEE Int’l Conf. on Communications (ICC), May 2016. §

  • B. Ma et al., “A Matching Approach for Power Efficient Relay Selection in Full Duplex D2D

Networks,” in Proc. of IEEE Int’l Conf. on Communications (ICC), May 2016. http://www.ece.ubc.ca/~vincentw/Homepage/Publication.html

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Forthcoming Edited Book in 5G Wireless Systems WIRELESS SYSTEMS KEY TECHNOLOGIES

5G

FOR

EDITED BY: VINCENT W. S. WONG ROBERT SCHOBER DERRICK WING KWAN NG LI-CHUN WANG

§ Publisher: Cambridge University Press § Hard copy will be available in April 2017

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Questions

vincentw@ece.ubc.ca http://www.ece.ubc.ca/~vincentw

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