Demystifying 5G, Massive MIMO and Challenges 5G India 2017 Ramarao Anil Head – Product Support, Development & Applications Rohde & Schwarz India Pvt. Ltd. COMPANY RESTRICTED
Demystifying 5G, Massive MIMO and Challenges
5G India 2017
Ramarao Anil Head – Product Support, Development & Applications
Rohde & Schwarz India Pvt. Ltd.
COMPANY RESTRICTED
Agenda
ı 5G Vision
ı Why Virtualization & C-RAN ?
ı Why Massive MIMO ?
ı Challenges & OTA
ı Summary
COMPANY RESTRICTED
5G Vision: A Union of Spectral & Energy Efficiency
Radio: Spectral Efficiency Virtualization: Energy Efficiency
Automotive
Public Safety
E-Health
IoT
Smart City Ecosystem
Ultra-Dense Broadband
Broadcast Mobility
Advanced test equipment bridging between radio &
virtualization
Both capacity and power consumption are critical for 5G success
BS Locations
Expenses
Revenue
Traffic
Time
Growth
Mobile data explosion
Voice dominated
Why 5G? Capacity vs. Revenue Increased Capacity, Increased OPEX
Expenses
Revenue
Traffic
Time
Growth
Mobile data explosion
Voice dominated
Optimal Network
?
Drive profit by reducing expenses (energy efficiency)
BS Locations
Low data rates
on edges
Cell Edge
Uniform
Coverage
Why 5G? Power Consumption
2G GSM
830,000 Basestations
80 GWH (96 KWH per BTx)
3G TD-SCDMA
350,000 Basestations
13 GWH (37 KWH per BTx)
WiFi Data Offloading
4.2 Million Access Points
2 GWH Power consumption
4G TD-LTE
800,000 Basestations
16 GWH (20 KWH per BTx)
Cellular Network Energy Consumption (China) Radio Access Network Energy Consumption
CAPEX OPEX
Biggest CAPEX/OPEX Expense is Air
Conditioning
Example: China Mobile Network in
2013 consumed over 15 Billion KWH
31%
7% 41%
21%
O&M
Electricity
Site
rent
Tx
46% 51%
3%
Air
conditioners
Equipment
Source: IEEE Communications Magazine, Feb 2014
CMRI, “C-RAN: The Road Towards Green RAN,” Dec. 2013
Cellular Infrastructure Evolution to 5G Passive Antennas & Separate Radio Transceivers
Active Antenna System
Antenna + Integrated TRx
Massive MIMO: Requires new T&M paradigms
Traditional: 1G & 2G Distributed: 3G & 4G Centralized: 4.5G & 5G
0.45 to 1.9 GHz 0.7 to 3.6 GHz 3.4 to 6 GHz & 20 to 60 GHz
8 dual-polarized antennas 8+ dual-polarized passive antennas 128 to 512 active antennas
Peak data rate: 114 kbps Peak data rate: 150 Mbps Peak data rate: 10 Gbps
Energy Efficiency: C-RAN & Network Virtualization
Virtual Basestation Pool (Real-time Cloud BBU)
BS1: GSM Phy/Mac
BS2: LTE Phy/Mac
BS3: 5G Phy/Mac ...
RTOS RTOS RTOS ... Hypervisor
General Purpose Processor Platform
Distributed configurable wideband RRU
High bandwidth optical transport network
Centralized Control/Processing
Centralized processing resource pool that can support 10~1000 cells
Collaborative Radio
Multi-cell joint scheduling and processing
Real-Time Cloud
Target to open IT platform
Consolidate the processing resource into a cloud
Flexible multi-standard operation and migration
Clean System Target
Less power consuming
Lower OPEX
Fast system roll-out
-15% Capital Costs
-50% Operating Costs
-70% Power Consumption
Architecture Equipment Air Con Switching Battery Transmission Total
Traditional 0.65 kW 2.0 kW 0.2 kW 0.2 kW 0.2 kW 3.45 kW
Cloud Radio 0.55 kW 0.1 kW 0.2 kW 0.1 kW 0.2 kW 0.86 kW
CMRI, “C-RAN: The Road Towards Green RAN,” Dec. 2013
Easiest way to improve energy efficiency: more virtualization
Spectral Efficiency: Why MIMO?
Signal to Noise Ratio (S/N) Signal BW (Hz)
Capacity
(bits/second)
C = W N log2(1+SNR)
Number of Channels
•Use additional frequency bands in mmWave spectrum (24
to 110 GHz) for increased signal bandwidth up to 2 GHz
• Increase SNR of 5G waveforms and multiple access
• Implement Massive MIMO with multiple channels and
beamforming to improve SNR
Solutions: mmWave & Massive MIMO
Increased Capacity, Increased OPEX
Energy Efficiency: Why Massive?
Number of Antennas = 1
Number of BS transmit
antennas (Mt) 1
Normalized output power of
antennas
Normalized output power of
base station
Improve energy efficiency: more antennas
Number of UEs: 1
120 antennas per UE
120
...
PBS = 1 PBS = 0.008
Wasted
power
Source: IEEE Signal Processing Magazine, Jan 2013
Massive MIMO Beamforming Architectures
Analog Beamforming (ABF)
PA
ABF
Phase
shifters
N = 1
Ant 1
Ant M
...
N = 1, M antennas
Ant 1
...
Ant p
Ant q
...
Ant M
Digital Beamforming (DBF)
N TRx = M antennas
TRx 1 Ant 1
Ant M
DBF
Base-
band
beam-
forming
TRx N
Hybrid Beamforming (HBF)
N < M
From Analog .... ... To Digital
p
Probe
gm Cm
mth antenna circulator or switch
Measurement
equipment
Receive RF chain
Transmit RF chain Tn
Rn
nth TRx module Single Transceiver + Antenna
... To Hybrid
x(t)
x1(t)
xN(t)
TRx 1
DBF
Base-
band
beam-
forming
TRx N
x1(t)
xN(t)
ABF
1
ABF
N
Hardware Perspective: Massive MIMO = Beamforming + MIMO
M =
4 T
ransc
eiver
s x3(t)
x1(t)
x2(t)
x4(t)
MIMO Array: M Data Streams Beamforming Array: 1 Data Stream
x1(t) TRx +
Multi-User MIMO Increase SINR and capacity for each user
i.e. UE1: 16 ant BF with 16x2 MIMO
UE2: 32 ant BF with 8x2 MIMO
Massive arrays of 128 to 1024 active antenna elements
Massive MIMO: Combine Beamforming + MIMO = MU-MIMO with M antennas >> # of UEs
Massive MIMO Challenges
Data
Bottleneck
Calibration Mutual
Coupling Irregular
Arrays
Reduced MU-MIMO Reduced Capacity Grating Lobes Increased Costs
CPRI Bottleneck
Complexity
Increased Costs
RFIC
FPGA
Digital IQ
TR
x
RFIC
Active Antenna Arrays: The Calibration Problem
Phase/Magnitude/Frequency Tolerances (Static & Dynamic)
RFIC RFIC
LO FPGA
Digital IQ
RF Feeding Network
Dynamic Thermal Effects in PAs
Timing Errors in ADCs
Frequency Drift Between Modules
General
Manufacturing Tolerances of
Components & Thermal Effects
Phase Shifter Tolerances
Group Delay Variations
Mutual Coupling vs. Network Capacity Solution: Measurement with multi-port VNA
Up to 288 elements
0.4λ 1.2λ
Source: Signal Processing Magazine, IEEE, Jan 2013
In order to maintain capacity, square antenna arrays require
more spacing to reduce antenna mutual coupling
R&S®ZNBT
All S-parameters
0 to 8.5 GHz
Problem: Antenna mutual coupling reduces capacity
True simultaneous 24-port measurement
+ R&S®ZN-Z84
Massive MIMO = Complex Basestations
Wideband: PA
and Filter Banks
Mutual Coupling
Isolation
Adaptive Self-
Calibration
Fiber Multiplexing
mmWave = Non-
CMOS components
Beamforming
Architecture
128 element AAS prototypes: Complexity increased by 8 times
LO FPGA
Digital IQ
RFIC
Heat
Dissipation
Clock
Synchronization
Fiber
Transceivers
Receiver +
DSP/FPGA
RFIC
Passive vs. Active Antennas: Why OTA?
Passive Antenna Active Antenna
Outer enclosure: Radome
Antenna + Feeding Network
Outer enclosure
RF I/O ports
Outer enclosure: Radome
Antenna + Feeding Network
Outer enclosure
RF Transceiver Boards + Filters
Shielding + Heatsink
CPRI + FPGA Board
Input/Output: Radiated Signal
Input/Output: RF Signal Input/Output: Digital IQ BB Data
Input/Output: Radiated Signal
Front Radome
Rear Radome/Heatsink
Basestation Field Distributions
Basestation 8 Element Array at 2.69 GHz
Near-field region
phase & magnitude
Required chamber size for far-field
AUT size (D) Frequency Chamber size
0.5 meters 6 GHz 10 meters
0.5 meters 30 GHz 50 meters
1.0 meter 6 GHz 40 meters
Very near-field
region (< 0.6m)
Near: Phase + Magnitude Far: Magnitude
Far-field vs. near-field
Far field
magnitude
2D2 / λ = 4.1 m
OTA Measurements for 5G Active & Passive Antennas
Reference
Antenna
Measurement
Antenna
Active
Antenna
System
DUT
Phase Shifter
φ = [0, ± π/2, π]
Frequency range: 0.4 to 110 GHz
Passive Antenna
Measurements Active
Antennas
R&S®ZVA
R&S®SMW200A
R&S®ZVA
Measurement Setup for 3D Antenna Pattern: 24 GHz DUT
Shielded Chamber
R&S®DST200
R&S®FSW Signal and
Spectrum Analyzer
Measurement Equipment
R&S®AMS32
Measurement SW
Measurement Scenarios
OTA measurements for R&D and sample testing in production
Benchtop Beamforming
Measurements: R&S®TS7124
Shielded chamber
(R&S®TS7124)
Vivaldi probe
27.5 to 75 GHz
Measurement Equipment
Measurement Scenarios
60 GHz (and mmWave) will not have antenna connectors
OTA measurements will be mandatory for production
R&S®NRPM
2D Beam-Steering 3D Beam-Steering
R&S®TS7124
RF antenna array
beam forming/
electronic sector
selection
“If you want to go fast, go alone.
If you want to go far, go together!” African proverb