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doc.: IEEE 802.11-13/0545r1
Submission
May 2013
Veli-Pekka Ketonen (7signal)Slide 1
WLAN QoE, End User PerspectiveOpportunities to Improve
Date: 2013-05-15
Name Company Address Phone email Veli-Pekka Ketonen 7signal Solutions, Inc. 526 S. Main Street,
Akron, Ohio, USA +1 330 8618150 veli-pekka.ketonen
@7signal.com
Authors:
doc.: IEEE 802.11-13/0545r1
Submission
May 2013
Slide 2 Veli-Pekka Ketonen (7signal)
Abstract
Presentation for 802.11HEW SG in Hawaii May 12th-17th Interim meeting
Includes data from various anonymous networks from 7signal Sapphire automated client device QoE
measurements for performance optimization and management work
Bottlenecks in current networks and suggestions for improvements are presented as background for further
HEW SG work
doc.: IEEE 802.11-13/0545r1
Submission
The Key Challenge
May 2013
Slide 3 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
In live networks, high max performance does not translate to sufficient user experience*
• Capacity, range and end user experienced quality do not any more meet needs
• Example from University. Nw. vendor has less impact, network config. higher impact • * = these are hourly average values from an area of multiple APs/SSID over a week time
Veli-Pekka Ketonen (7signal)Slide 4
doc.: IEEE 802.11-13/0545r1
Submission
Key findings
May 2013
Slide 5 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
#1. Too aggressive rate control,average retrys often exceed 50% (1/2)
May 2013
Slide 6 Veli-Pekka Ketonen (7signal)
• With 802.11n products, regularly 30-50% of packets require at least one retry. Often even more.
Too high rate selected
A lot of retries,multiplied by MIMO-X
factor
High utilization
Lower SNR
More radio retries, up to 7 times/packet
No air time & lost packets
Capacity and TCP throughput collapse
doc.: IEEE 802.11-13/0545r1
Submission
#1. Too aggressive rate control, less aggressive has been proven better (2/2)
May 2013
Slide 7 Veli-Pekka Ketonen (7signal)
• Individual network behavior impacts also all other nearby networks
• 802.11ac has much more demanding requirements than 802.11n
• Suggestions:• Use clearly less aggressive rate control
• Make rate control dynamic, adjusting based on observed radio conditions (like continuous Bluetooth)
• 802.11 to specify proper rate control schemes, instead of leaving this to vendors
RX-level during this part of the route: -70 – -88 dBm
Original link adaptation
Optimized link adaptation
-> Reason for improvement:•Using more MCS-8 instead of MCS-9
RX-level
RX-level
Past findings from Nokia Networks EDGE link adaptation (Public, Ref [1])
Throughput
Throughput
doc.: IEEE 802.11-13/0545r1
Submission
#2 Automated channel control algorithms need clear improvements
• Automated features, like channel selection do not work properly
• Continuous channel hopping in the whole network and no stable state
• Impacts also surrounding networks
• Suggestion:• 802.11 to specify more in
more detail requirements
May 2013
Slide 8 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
#3. Already available radio settings are not utilized since their impacts are not understood
• Radio should more accurately and dynamically operate its settings, like
– Data rates; supported, default, control
– Management/control traffic data rates,
– Fragmentation process, MTU
– QoS
– Ack/block ack schemes usage
– Long/short pre-amble configuration
– RTS/CTS process
– Supported 802.11 standards
– Minimum limit for probe response
– Load balancing, etc
• Suggestions– Performance management practices
– Automated operation
– 802.11 to specify in more detail
May 2013
Slide 9 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
#4. Interference due to lacking channel coordination and Bluetooth devices
• Channel plans are almost random in public areas
– Resulting packet loss, jitter
• Proper radio operation in the mid-term still requires significantly better channel plans
• Suggestions
– Better, proven automated algorithms for channel negotiation
– Cloud based control
– Regulation for allowed channels
– Better industry defaults
– Adhoc channel selection limited/guided
May 2013
Slide 10 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
#5. Too dense beacons load air unnecessarily• In practice solely 100ms used
globally with 1 Mbit/s as mandatory rate in consumer grade APs. This congests air significantly everywhere
• In 100ms, a person walking full speed moves ~10 inches (~ 25cm). Is this dense beaconing necessary?
May 2013
Slide 11 Veli-Pekka Ketonen (7signal)
• Suggestions
• Define default beacon intervals longer, ~300ms
• Dynamic/adaptive beaconing, beacon interval automatically dependent on the observed time between roaming.
• Consider add few % variance to beacon intervals to avoid continuously repeating collisions (compare to spread spectrum CPU clocking for EMI reduction)
• Consider impact to power save functionality
doc.: IEEE 802.11-13/0545r1
Submission
#6. Mobile networks interfere 2.4 GHz band WLANs through 3rd harmonic distortion
• When cellular network indoor antennas are near (30ft/10m) to WLAN APs and/or clients, they may saturate the receiver with off band signals and receiver generates distortion product that lands in the 2.4 GHz band
• Suggestion– Add mandatory RF band-pass filtering to WLAN radios
– Receiver blocking test to FCC approval
May 2013
Slide 12 Veli-Pekka Ketonen (7signal)
2.4 GHz2.3 GHz2.2 GHz 2.5 GHz 2.6 GHz2.1 GHz2.0 GHz1.9 GHz1.8 GHz1.7 GHz
DCS-1800(EUR, US)
PCS-1900 (EUR)UMTS-1900 (US)
UMTS-2100 (EUR)UMTS-1700 (US)
Distance appr. 300MHz=> Harmonic distortionlands at 300MHzdistance from source
WLAN
WLAN signal
High powermobile base station signal
High powermobile base station signal
Ghost signal(noise)
=> Signal-to-noise ratiodegrades in WLAN receiverand data transfer suffers
Verified to happen in live network conditions
doc.: IEEE 802.11-13/0545r1
Submission
#7. Support for legacy devices (802.11b/a) seriously degrades benefits of new standards
• Protection mode is “contagious” and highly inefficient
• Benefits of new standards are limited if legacy devices are overprotected. Important especially in consumer grade equipment.
• Suggestions
– Better industry defaults• 802.11b not supported
• 802.11a not supported
– Improvements to protection mode
– Prevent/limit protection mode spreading with required minimum signal levels
May 2013
Slide 13 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
#8. Lacking interoperability may take down whole network performance
• Introduction of new radio devices increased average retry rates to about 70%. Max network capacity came down at least 50%
May 2013
Slide 14 Veli-Pekka Ketonen (7signal)
• Suggestions– More exact requirements needed for
client-AP interoperability– Live network performance
management capabilities need to improve. All scenarios cannot ever be tested upfront.
doc.: IEEE 802.11-13/0545r1
Submission
#9. Modest access point antenna solutions• Omni-antennas with significant vertical coverage are widely used
• RF energy goes where it should not go and antennas try to receive it from directions where are no clients
• Lacking antenna sophistication
– More gain towards users would benefit uplink quality
– Lack of antenna directivity creates more interference
• Suggestions
– Down-tilt beam patterns
• Fixed, “normal” antennas
• Electrically adjustable, like in mobile networks
– Wider use of beam steering
May 2013
Slide 15 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
#10. Performance Management is completely missing
• With WLAN networks, commonly accepted fact is that:
“It is not necessary to continuously know what kind of service end users get from the network.
If we manage to make it work once, there is no need to look after performance for several months/a year. It will take care of itself automatically. We will troubleshoot when end users complain”
• This approach fundamentally prevents WLAN becoming a reliable media
• Mobile operators/telecom industry are used to manage networks based on Meaningful Key Performance Indicators, KPIs, that accurately indicate and predict User Experience (L1-L7) in the network. These are covered also in standards. This is a good practice that should be brought to WLAN
• Beyond technology providing the required solutions, data and services, even bigger change is required in attitudes.
May 2013
Veli-Pekka Ketonen (7signal)Slide 16
doc.: IEEE 802.11-13/0545r1
Submission
2-10x improvement available with these alreadyResults: Controller Automation vrs First Manual Optimization Round
• University campus, dense WLAN network• 2.4 GHz downlink throughput improvement Improvement
– Area 1 7Mbit/s vrs. 25Mbit/s (+250%)– Area 2 5Mbit/s vrs. 15Mbit/s (+200%)– Area 3 8Mbit/s vrs. 16Mbit/s (+100%)
• 2.4 GHz uplink throughput improvement– Area 1 7Mbit/s vrs. 20Mbit/s (+180%)– Area 2 10Mbit/s vrs. 25Mbit/s (+150%)– Area 3 12Mbit/s vrs. 20Mbit/s (+65%)
• 2.4 GHz downlink Voice Quality (MOS grade, max 4.0) improvement– Area 1 2.6Mbit/s vrs. 3.5Mbit/s (+0.9 MOS) – Area 2 2.9Mbit/s vrs. 3.8Mbit/s (+0.9 MOS) – Area 3 2.5Mbit/s vrs. 3.5Mbit/s (+1.0 MOS)
• 2.4 GHz uplink Voice Quality (MOS grade, max 4.0) improvement– Area 1 3.5Mbit/s vrs. 3.8Mbit/s (+0.3 MOS) – Area 2 3.5Mbit/s vrs. 3.9Mbit/s (+0.4 MOS) – Area 3 2.5Mbit/s vrs. 3.5Mbit/s (+1.0 MOS)
• 2.4 GHz jitter daily averages before vrs. after– Area 1 9% vrs. 1% (- 89%) – Area 2 9% vrs. <<1% (> -90%) – Area 3 7% vrs. 1% (-85%)
• Hourly minimum measured downlink throughput values increase 10X– Area1, Area 3 0.2 Mbit/s vrs. 2.5 Mbit/s (~1100%)
17 Veli-Pekka Ketonen (7signal.)Slide 17
doc.: IEEE 802.11-13/0545r1
Submission
May 2013
Slide 18
Areas looking for improvements based on data from current installations
1. Too aggressive rate control
2. Automated channel control algorithms need clear improvements
3. Already available radio settings are not utilized since their impacts are not understood
4. Interference due to lacking channel coordination and Bluetooth devices
5. Too dense beacons load air unnecessarily
6. Mobile networks interfere 2.4 GHz band WLAN’s through 3rd harmonic distortion
7. Support for legacy devices (802.11b/a) seriously degrades benefits of new standards
8. Lacking interoperability may take down whole network performance
9. Modest access point antenna solutions
10. Performance Management is completely missing
Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
References
[1] Nokia Networks/Jussi Nervola: Optimization of EGPRS Link Adaptation, 2007/01/16– M.Sc. Thesis seminar presentation– http://www.netlab.tkk.fi/opetus/s38310/06-07/Kalvot%2006-07/nervola_160107.ppt
Network statistics from 7signal network optimization and performance assurance reports
May 2013
Slide 19 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
ADDITIONAL SUGGESTIONS
May 2013
Slide 20 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
Other input for SG work
May 2013
Veli-Pekka Ketonen (7signal)Slide 21
Topic Description
Client power control In dense networks AP’s have often lower power levels than clients. High amount of high power clients with a lot of traffic (data, control or management) take a lot of air time and cause unnecessary interference.
Prevent hiding SSID’s Hidings SSID’s increases utilization. All beacons are anyway sent, just without SSID name. Without SSID names in beacons, Clients need to probe continuously. Remote possibility of hiding SSID names as it provides so little value. Alternatively implement so that beacons are not sent at all is SSID is hidden.
Improve DFS implementation DFS operation is commonly reported to be overly sensitive and prevents using DFS channels in many areas. This needs to change with .ac and .hew to allow efficient use of 5 GHz band.
Improve client roaming behavior Some clients use excessive off channel scanning. This sometimes results as QoS Null frame flood that takes air time and increase congestion.
Use adaptive beaconing When there are no relevant clients nearby for a longer time, transmit beacons less often. This reduces overall spectrum load in the surrounding areas remarkably. Currently APs beaconing (usually 1 Mbit/rate & 100ms interval) consume a lot of spectrum day and night for no good purpose. Consider ways to work around the power save mode operation.
Use dynamic fragmentation Client traffic could start with a smaller packets (with fragmentation) at higher data rate (less airtime, less interference). Once rate control has a good grip of proper rates for that client packet flow, fragmentation could be gradually removed. Rate control is slow and needs some time to adapt. In addition to lowering retries, utilization and interference, this would allow some time for rate control to work better.
Beacons and probes should use higher data rates
Beacons (and probes/probe responses) should not be transmitted with the low data rates. By using higher data rate there, the nearby clients (the only ones relevant to beaconing process) can receive them and the devices further away not. Rate control still should be able to move to lower data rates when really needed. This would be easy way to reduce utilization further away from AP.
Cloud control:Radio Link Test and Radio Link Control interfaces to APs
For automated central coordination of a large group of individual APs, there should be two new functionalities in APs. Radio Link Test interface: Without authenticating to AP/network, an authorized (password) wireless device should be able to run some basic active measurements against the AP. These include at least FTP, UDP and ICMP traffic flows. Radio Link Control interface: Without authenticating to AP/network, an authorized (password) wireless device should be able to control basic Radio settings in AP. These include at least radio channel and power level. Cloud control: With these interfaces, especially dense consumer AP installations (& SMB) could be centrally controlled and managed to provide optimum quality for everyone.
Improved radio MAC based device type classification
Current MAC address based device identification should be expanded. Currently only manufacturer names are recorded. This would allow developing better automated/by-default-on QoS control algorithms to infrastructure.
Automated “closed loop” radio network control, adaptive/SON
Optimally, wireless network should reconfigure automatically (SON, Self Organizing Networks). So far in WLAN results are modest. Channel change algorithms degrade performance, rather than improve it. Networks have to make decisions and learn from impact of changes continuously. Accurate data of end user experience is needed for this to work properly. Comprehensive data collection and analytics should drive this process.
doc.: IEEE 802.11-13/0545r1
Submission
DATA COLLECTION BACKGROUND
May 2013
Slide 22 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
Background• 7signal utilizes its products to optimize and operate critical
WLANs (hospitals, universities, enterprises, manufacturing)
• This process includes continuous collection and analysis of large amount of performance data, consisting of over 600 different metrics. Optimization takes place by reconfiguration and pre-emptive changes on network based on the data.
• Data includes– Automated client device tests, providing L1-L7 data
– Passive L1-L2 packet statistics of all 802.11 air traffic
– RF environment data
– Spectrum analysis data
May 2013
Slide 23 Veli-Pekka Ketonen (7signal)
doc.: IEEE 802.11-13/0545r1
Submission
7signal Sapphire consists of three elements
• Monitor
• Measure
• Record
• Report
• Alarm
• Analyze
• Troubleshoot
• Verify
Sonar test servers are located in in close proximity to application servers
Centrally located Carat manages Eyes, provides reports and alarms. Includes Analyzer software
One Eye unit manages 4-7access points (indoors)
Radio analysis, radio packet capture and end-to-end application measurement
Slide 24
doc.: IEEE 802.11-13/0545r1
Submission
7signal Sapphire data covers all layers 1-7
Synthetic tests (L1-L7)•FTP, PING, HTTP, DHCP, SIP, VOIP•Association/authentication/IP address/test success rates, delays, throughput, latency, jitter, packet loss, MOS, data rates, failure codes•60 performance indicators, separately for each AP/SSID/Sonar pair
Synthetic tests (L1-L7)•FTP, PING, HTTP, DHCP, SIP, VOIP•Association/authentication/IP address/test success rates, delays, throughput, latency, jitter, packet loss, MOS, data rates, failure codes•60 performance indicators, separately for each AP/SSID/Sonar pair
RF analysis (L1-L2)•Access point settings and capabilities, signal levels, channels, noise levels•40 performance indicators, separately for each AP, channel, antenna beam
RF analysis (L1-L2)•Access point settings and capabilities, signal levels, channels, noise levels•40 performance indicators, separately for each AP, channel, antenna beam
Traffic analysis (L2)•Radio frame header analysis for traffic flow between clients and access points•Data rates, retry rates, air congestion, roaming, frame size, device vendor, statistics for all 802.11 frame types, reason codes and status codes•500 performance indicators, separately for each client, SSID, AP, band, antenna beam
Traffic analysis (L2)•Radio frame header analysis for traffic flow between clients and access points•Data rates, retry rates, air congestion, roaming, frame size, device vendor, statistics for all 802.11 frame types, reason codes and status codes•500 performance indicators, separately for each client, SSID, AP, band, antenna beam
Spectrum analysis (L1)•High resolution (280kHz) spectrum analysis for ISM band•Historical data over months, interference source analysis with beam steering, compass direction data on beams
Spectrum analysis (L1)•High resolution (280kHz) spectrum analysis for ISM band•Historical data over months, interference source analysis with beam steering, compass direction data on beams
Troubleshooting tests (L1-L7)•Remote, manual process for troubleshooting purposes•Full array of tests may be scheduled manually to each Eye•Eyes may be assigned to perform the additional tests without interrupting automated monitoring process
Troubleshooting tests (L1-L7)•Remote, manual process for troubleshooting purposes•Full array of tests may be scheduled manually to each Eye•Eyes may be assigned to perform the additional tests without interrupting automated monitoring process
Full packet capture (L1-L2)•Remote, manual process for troubleshooting•Full blown remote packet capture and easy export to packet level analyzer like Wireshark, in case individual radio packet header content information is needed •Eyes may be assigned to perform the test without interrupting automated monitoring process
Full packet capture (L1-L2)•Remote, manual process for troubleshooting•Full blown remote packet capture and easy export to packet level analyzer like Wireshark, in case individual radio packet header content information is needed •Eyes may be assigned to perform the test without interrupting automated monitoring process
Slide 25
doc.: IEEE 802.11-13/0545r1
Submission
7signal Sapphire Eye, the data collection device• A “turbo charged” client device
• At times active like end users, at times fully passive• Beam steering technology with low noise amplifiers• Integrated compass• 802.11 a/b/g/n support• High resolution ISM band spectrum analyzer• High RF performance design; maximized coverage,
minimized quantity, typically 4-7 AP’s per unit• Standard PoE• Neutral design and white color• Attaches easily to ceiling grid, alternatively wall or pole• Indoor and outdoor versions• Data analyzed at device, only key results to database• Minimal load to network, small test packets at
determined intervals
Slide 26
doc.: IEEE 802.11-13/0545r1
Submission
7signal view on QoS, similar to end users
300x
200x
200x
100x
100x
WLAN radio Network
900x
5x
Access Point
WLAN controller
LANwired network
Core switchingnetwork
100x
Core Router100x
Applicationservers
Sitebroadbandconnection
LAN switch
2x
8x
Core switch Server racks
Servers
10x
End user terminals
7signal Sonar software
7signal Eyes
Active end-to-end quality of service assessment from end user perspective
End user device quality of service in radio network
Radio network and spectrum analysis
Slide 27
doc.: IEEE 802.11-13/0545r1
Submission
Network Optimization Flow
Slide 28