下一代WIFi场景和评估准则
合集下载
- 1、下载文档前请自行甄别文档内容的完整性，平台不提供额外的编辑、内容补充、找答案等附加服务。
- 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
- 3、如文档侵犯您的权益，请联系客服反馈,我们会尽快为您处理(人工客服工作时间：9:00-18:30)。
Submission Slide 9 Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
What’s different about HEW?
• Almost all the techniques we use or in the literature are designed to optimize performance around an access point or within a BSS
Submission Slide 6 Jim Lansford, CSR Technology
Source: Aruba white paper
May 2013
doc.: IEEE 802.11-13/0558r1
MU-MIMO, beamforming, and OFDMA add additional waterfilling capability
– Current time-frequency-space optimization techniques – Some recent research
• WiFox
– In HEW, we will want to optimize
• Distribution of bits/packets across space-time-frequency-power-load • Across multiple APs
May 2013
doc.: IEEE 802.11-13/0558r1
Coexistence and Optimization of Wireless LAN: Time, Frequency, Space, Power, and Load
Authors:
Name
Jim Lansford Douglas Sicker
Ken.Baker (at) colorado.edu
Submission
Slide 1
Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
Abstract
• This presentation addresses some issues in “Technical Feasibility” in the 5C • A review of space-time-frequency waterfilling techniques
Source: Cisco white paper
Source: TU-Delft
•DL-MU-MIMO shapes the transmit stream •Beamforming can also null interference and “rogue” (nonmanaged) APs •Both are forms of spatial waterfilling
Submission Slide 5 Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
Space-frequency techniques
• With multiple antennas, we have lots of new options for space and frequency optimization
– Managed ESS is done by vendors – Non-managed “sea of APs“ like an apartment building is generally not addressed
• The lack of time-frequency-space-power-load optimization in non-managed environments is our biggest scaling problem
– Prioritizes traffic at an AP based on queue depth
Source: WiFox paper [6]
Source: WiFox paper [6]
Submission
Slide 8
Jim Lansford, CSR Technology
May 2013
Submission
• OFDMA allows fine grained frequencytime waterfilling
Slide 7 Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
Time optimization
• Numerous papers have been published on improving fairness, backoff, load balancing, and optimizing uplink-downlink traffic (see references for samples) • Most recent publication: “WiFox” from NC State [6]
– We’re trying to replicate the wired experience in a wireless environment - “Wireless is a noisy, unreliable, insecure piece of wire” – What we are trying to do is space-frequency-time-power waterfilling
– Issues of managed vs. unmanaged environments
• Technical issues in developing Feasible HEW Solutions
Submission Slide 2 Jim Lansford, CSR Technology
May 2013
2.0 1.5 1.0 0.5 0.0 0 20 40 60 Packet Error Rate (PER)
At 25% PER, a 450mW chipset consumes the same power as a 600mW with negligible PER
• Packet errors due to interference and congestion are especially catastrophic – “wasted air”
– Increases latency – Lowers delivered throughput – Increase effective power consumption of WLAN system
• An optimal solution for HEW should minimize retries
Date: 2013-05-16
Affiliations
CSR Technology University of Colorado - Boulder University of Colorado - Boulder University of Colorado - Boulder
Address
100 Stirrup Circle, Florissant, CO 80816 1111 Engineering Drive 530 UCB, ECOT 311 University of Color ado Boulder, CO 80309-0530 1111 Engineering Drive 530 UCB, ECOT 311 University of Colorado Boulder, CO 80309-0530 1111 Engineering Drive 530 UCB, ECOT 311 University of Colorado Boulder, CO 80309-0530
doc.: IEEE 802.11-13/0558r1
Robustness matters
Effective power due to retries
Number of additional retries
2.5
Effective power (times base power)
Relative Retry Latency Based on 10000 packets 16 14 12 10 8 6 4 2 0 0 10 20 30 40 50 60 Packet Error Rate
1
Not necessarily an area
Submission
Slide 4
Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
Channel impairments
• We have a lot of tools in our toolbox to combat fading in frequency and space
doc.: IEEE 802.11-13/0558r1
Technical Feasibility – Criterion 4
• 4 Technical Feasibility
For a project to be authorized, it shall be able to show its technical feasibility. At a minimum, the proposed project shall show: a) Demonstrated system feasibility. b) Proven technology, reasonable testing. c) Confidence in reliability.
• • • • Equalization Diversity techniques OFDM And of course MIMO
• MU-MIMO extends this concept
Optimally loading this 2-D space with signal energy is a waterfilling problem
Phone
+1 719 286 9277
303-492-8475
email
Jim.lansford@ieee.org
Douglas.Sicker (at) Colorado.EDU
David Reed
303-wenku.baidu.com92-8475
David.Reed (at) colorado.edu
Ken Baker
303-492-8475
• In either case, we are trying to deliver a specified bandwidth (bits/sec) to a point in space1 in the presence of passive channel impairments, interference (non802.11) and congestion (802.11), where we may care how long it takes to deliver a good packet (latency)
Submission
Slide 3
Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
What problem are we really trying to solve?
• Robustness with high densities of APs and STAs • Two ways to view the problem:
– “Tragedy of the Commons” – Billions of devices that will never have any way to modify their behavior for HEW enhancements
May 2013
doc.: IEEE 802.11-13/0558r1
What’s different about HEW?
• Almost all the techniques we use or in the literature are designed to optimize performance around an access point or within a BSS
Submission Slide 6 Jim Lansford, CSR Technology
Source: Aruba white paper
May 2013
doc.: IEEE 802.11-13/0558r1
MU-MIMO, beamforming, and OFDMA add additional waterfilling capability
– Current time-frequency-space optimization techniques – Some recent research
• WiFox
– In HEW, we will want to optimize
• Distribution of bits/packets across space-time-frequency-power-load • Across multiple APs
May 2013
doc.: IEEE 802.11-13/0558r1
Coexistence and Optimization of Wireless LAN: Time, Frequency, Space, Power, and Load
Authors:
Name
Jim Lansford Douglas Sicker
Ken.Baker (at) colorado.edu
Submission
Slide 1
Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
Abstract
• This presentation addresses some issues in “Technical Feasibility” in the 5C • A review of space-time-frequency waterfilling techniques
Source: Cisco white paper
Source: TU-Delft
•DL-MU-MIMO shapes the transmit stream •Beamforming can also null interference and “rogue” (nonmanaged) APs •Both are forms of spatial waterfilling
Submission Slide 5 Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
Space-frequency techniques
• With multiple antennas, we have lots of new options for space and frequency optimization
– Managed ESS is done by vendors – Non-managed “sea of APs“ like an apartment building is generally not addressed
• The lack of time-frequency-space-power-load optimization in non-managed environments is our biggest scaling problem
– Prioritizes traffic at an AP based on queue depth
Source: WiFox paper [6]
Source: WiFox paper [6]
Submission
Slide 8
Jim Lansford, CSR Technology
May 2013
Submission
• OFDMA allows fine grained frequencytime waterfilling
Slide 7 Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
Time optimization
• Numerous papers have been published on improving fairness, backoff, load balancing, and optimizing uplink-downlink traffic (see references for samples) • Most recent publication: “WiFox” from NC State [6]
– We’re trying to replicate the wired experience in a wireless environment - “Wireless is a noisy, unreliable, insecure piece of wire” – What we are trying to do is space-frequency-time-power waterfilling
– Issues of managed vs. unmanaged environments
• Technical issues in developing Feasible HEW Solutions
Submission Slide 2 Jim Lansford, CSR Technology
May 2013
2.0 1.5 1.0 0.5 0.0 0 20 40 60 Packet Error Rate (PER)
At 25% PER, a 450mW chipset consumes the same power as a 600mW with negligible PER
• Packet errors due to interference and congestion are especially catastrophic – “wasted air”
– Increases latency – Lowers delivered throughput – Increase effective power consumption of WLAN system
• An optimal solution for HEW should minimize retries
Date: 2013-05-16
Affiliations
CSR Technology University of Colorado - Boulder University of Colorado - Boulder University of Colorado - Boulder
Address
100 Stirrup Circle, Florissant, CO 80816 1111 Engineering Drive 530 UCB, ECOT 311 University of Color ado Boulder, CO 80309-0530 1111 Engineering Drive 530 UCB, ECOT 311 University of Colorado Boulder, CO 80309-0530 1111 Engineering Drive 530 UCB, ECOT 311 University of Colorado Boulder, CO 80309-0530
doc.: IEEE 802.11-13/0558r1
Robustness matters
Effective power due to retries
Number of additional retries
2.5
Effective power (times base power)
Relative Retry Latency Based on 10000 packets 16 14 12 10 8 6 4 2 0 0 10 20 30 40 50 60 Packet Error Rate
1
Not necessarily an area
Submission
Slide 4
Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
Channel impairments
• We have a lot of tools in our toolbox to combat fading in frequency and space
doc.: IEEE 802.11-13/0558r1
Technical Feasibility – Criterion 4
• 4 Technical Feasibility
For a project to be authorized, it shall be able to show its technical feasibility. At a minimum, the proposed project shall show: a) Demonstrated system feasibility. b) Proven technology, reasonable testing. c) Confidence in reliability.
• • • • Equalization Diversity techniques OFDM And of course MIMO
• MU-MIMO extends this concept
Optimally loading this 2-D space with signal energy is a waterfilling problem
Phone
+1 719 286 9277
303-492-8475
Jim.lansford@ieee.org
Douglas.Sicker (at) Colorado.EDU
David Reed
303-wenku.baidu.com92-8475
David.Reed (at) colorado.edu
Ken Baker
303-492-8475
• In either case, we are trying to deliver a specified bandwidth (bits/sec) to a point in space1 in the presence of passive channel impairments, interference (non802.11) and congestion (802.11), where we may care how long it takes to deliver a good packet (latency)
Submission
Slide 3
Jim Lansford, CSR Technology
May 2013
doc.: IEEE 802.11-13/0558r1
What problem are we really trying to solve?
• Robustness with high densities of APs and STAs • Two ways to view the problem:
– “Tragedy of the Commons” – Billions of devices that will never have any way to modify their behavior for HEW enhancements