Dynamic Coordination of Multi- Radio Platforms in Dense Spectrum - - PowerPoint PPT Presentation

Dynamic Coordination of Multi- Radio Platforms in Dense Spectrum Environments

Xiangpeng Jing and D. Raychaudhuri

December 3, 2007

IAB Meeting

Outline

Project overview Multi-radio co-existence problems CSCC etiquette protocol applied to the multi-radio

scenarios

Advanced rate-backoff algorithm for WiFi/Bluetooth

Identifying co-existing region from measurements Cooperative service rate control for better co-existence

Initial results for simplified rate algorithm using ORBIT

multi-radio nodes

On-going and future work

Motivations

Spectrum resource is very scarce

Current spectrum utilization is inefficient

Anecdotal evidence of WLAN spectrum congestion

Unlicensed systems need to scale and manage user “QoS”

Density of wireless devices (including multi-radio

devices) will continue to increase

~10x with home gadgets, ~100x with sensors/pervasive computing

Mobile device is becoming smaller and smaller

Limited space for multiple antennas results in in-band and adjacent-band

interference

Interoperability between proliferating radio standards

Project Goals

High spectrum efficiency in multi-radio scenarios

Spectrum sensing, reactive algorithms and etiquette protocol 802.11a/b/g/n, Bluetooth, Zigbee, WiMax, and UWB

Improve end-to-end performance via multi-radio relays

Distributed protocols for ad hoc network formation and multi-radio forwarding Algorithms for “always best connected” operation

Experimental prototyping and validation

Realistic dense usage scenarios emulated on ORBIT radio grid Measure spectrum efficiency at different levels of application performance

Radio Technology Typical Range

• Max. Output Power

Frequency Occupied

• Max. Bitrate

Supported Typical Usage 802.11a/b/g/n (WIFI) 150-300 feet 17 dBm 2.4 GHz ISM, 5 Ghz UNII up to 248 Mbits/s WLAN point-to-multipoint, Mixed web, file and streaming traffic. 802.16 (WiMAX) 3-5 miles (12 miles) 22 dBm (handheld), 26 dBm BS 2.300-2.400 GHz, 2.496-2.690 Ghz, 3.300-3.800 GHz 4 Mbits/s (70 Mbits/s) WMAN broadband, Mixed web, voice traffic. 802.15.1 (Bluetooth) 150-300 feet (Class 1), 15- 30 feet (Class 2), 3- 4inch (Class 3) 20 dBm (Class 1), 4 dBm (Class 2), 0 dBm (Class 3) 2.4 ISM 3 Mbits/s (EDR) WPAN, low speed peripheral communications and voice/audio. UWB/Wireless USB 30-100 feet

• 41dBm/Hz

3.1-10.6 GHz 500 Mbits/s WPAN, high-speed peripheral communications 802.15.4 (ZIGBEE) 33-246 feet 3 dBm (current implementations) 868 MHz (EU), 915 MHz (US), 2.4GHz ISM 20-250Kbits/s WPAN, very low rate, intermittent traffic for sensors

Multi-radio Platforms

802.11b

Microwave Oven

Cordless Phone Bluetooth

Frequency (2.412-2.483GHz) Power

ZigBee 802.11g/n

Typical Scenario - SOHO

Devices: Multi-radio laptops, handheld, Bluetooth headset, sensors, etc. Clustered distribution in conference rooms Dominate traffic:

Periodical WiFi data (web, email, file, VoIP, etc.)

CBR/VBR Bluetooth voice/audio sessions

Co-existence Problems/Solutions

Interference of co-located radios on the

same platform

Close proximity of heterogeneous radios will have major impact Antenna placement/sharing for multi-radios Other on-platform interference such as wideband LCD noise

Physical separation/insulation In-platform local scheduling

Interference due to proximity of radios

High radio density in typical co-existing scenarios Hybrid-type traffic over the air Different interference range for different radios

Simple LBT or reactive frequency/rate/power control Spectrum etiquette protocol for explicit spectrum negotiation and coordination

Hidden-node Problem

Should care the receivers

Local channel scanning has limitation in detecting absence of

receivers rather than transmitters

Interference is fundamentally a receiver property Need explicit coordination protocols for mutual observations

CSCC Approach

Explicit coordinate spectrum and operating parameters using

Common Spectrum Coordination Channel for mutual observability

Periodical message exchange using a common signaling approach Execute coordination algorithms based on the information collected Implementation: extra control radio OR re-use a common data radio

Separate control and data

WiFi-g/Bluetooth Measurements

5 10 15 20

30 20 10 1 64 256 512 1024

A c h i e v e d W i F i t h r

• u

g h p u t ( M b p s ) WiFi loading rate (kbps) BT loading rate (kbps)

200 400 600 800 1000

1024 512 256 64 30 20 10 1

A c h i e v e d B T t h r

• u

g h p u t ( k b p s )

BT loading rate (kbps) WiFi loading rate (Mbps)

Plot measured throughput vs. loading rate (2 nodes)

Good operating regions WiFi Throughput Bluetooth Throughput

A Denser 12-node Scenario

In co-existing region both

systems can achieve mostly what they expect if they control their transmit rate cooperatively

200 400 600 800

WiFi loading Rate (Mbps) M e a s u r e d A v e r a g e W i F i T h r

• u

g h p u t ( K b p s ) 10 5 1 0.1 1024 512 256 64 BT loading Rate (Kbps)

50 100 150 200 250 300 350 400 450

64 256 512 1024 BT loading Rate (Kbps) 10 5 0.1 WiFi loading Rate (Mbps)

Measured Average BT Throughput (Kbps)

Guidance for Algorithm Design

Study a network with reasonable load condition Both systems should control their loading rates QoS can be addressed by demanding a minimum rate Avoid transmit more than required/achieved Adapt transmit rate cooperatively to approaching the optimal

• perating bound

How to identify this region? Need instant receiving throughput

feedback.

Advanced Rate-Backoff Algorithm

Buffer data-type traffic for opportunistic transmission Set higher priority for satisfying QoS requirement (e.g., min

rate/delay for streaming traffic)

Try to max rate in the co-existing region (max-min)

Increase loading rate when channel is not saturated Reduce loading rate when channel is saturated

Rtx

Integrated with CSCC-based Protocol

Each node periodically reports its self-state at control

channel, and collects other’s state information

Target transmitter calculates instant operating rate based

• n the algorithm, considering the states of hidden

heterogeneous receivers nearby

j i

Simplified Coordination Algorithms

For proof-of-concept by ORBIT experiments Low-rate BT avoids to high-rate WiFi (1) Simple BT-Rate Adaptation

Adjust BT streaming service levels when WiFi receivers detected In-platform WiFi receiver active? BT reduces to lowest 64kbps Nearby WiFi receiver active? BT lowers service rate by one level No hidden-receivers detected? Increase to the highest rate

(2) Simple BT-DeferTransfer

Any nearby WiFi receivers active? BT turns off its radio

Experiment goal:

Help study different interference impact on overall network performance from

different system

Break down the benefit by self-adaptation for the advanced algorithm design

16

ORBIT Experiment Parameters

Data Radio Service PHY Type IEEE 802.11g (Atheros AR5212) Bluetooth (Belkin and IOgear USB Dongle) Frequency 2427-2447MHz 2402-2483.5MHz Modulation OFDM (256 FFT) QAM GFSK + FHSS (DQPSK for EDR) Transmit Power 18dBm 4dBm (~20m) (class 2) 20dBm (~100m) (class 1) PHY Rate Up to 54Mbps AutoRate Upto 1Mbps Upto 2.1Mbps (w/ EDR) Data session Random ON/OFF CBR: 5 sec random session Constant audio streaming (64, 128, 320, 512, 1024kbps)

Preliminary Results – 14 Nodes

Wifi Throughput Percentage of improvement: Bluetooth Throughput Average Network Throughput

1 M 5 M 1 0 M 1 5 M 1 2 3 4

W iF i o ffe re d lo a d (b p s ) B T lo a d 1 M b p s

N o C o o rd in a tio n B T R a te A d a p t B T B a c ko ff A d a p t WiFi Average Session Throughput (Mbps)

1 M 5 M 1 0 M 1 5 M 5 0 0 0 0 1 0 0 0 0 0 1 5 0 0 0 0 2 0 0 0 0 0 2 5 0 0 0 0

W iF i o ffe re d lo a d (b p s ) B T lo a d 1 M b p s N o C o o rd in a tio n B T R a te A d a p t B T B a c k o ff A d a p t

Bluetooth Session Throughput (kbps) 1M 5M 10M 15M

• 50

50 100

WiFi offered load (bps) BT load 1Mbps Wifi (BT-Rate) Wifi (BT-BO) BT (BT-Rate) BT (BT-BO) Total (BT-Rate) Total (BT-BO)

Throughput Improvement (%)

1 M 5 M 1 0 M 1 5 M 0 .0 0 .5 1 .0 1 .5 2 .0 2 .5 3 .0 3 .5 4 .0

W iF i o ffe re d lo a d (b p s ) B T lo a d 1 M b p s N o C o o rd in a tio n B T R a te A d a p t B T B a c k o ff A d a p t

Average Total Network Throughput (Mbps)

Preliminary Results – Comparison

Percentage of improvement

• ffered load: Wifi 5Mbps BT 1Mbps

Simple rate algorithms favour

WiFi and sacrifice BT due to WiFi’s intermittent traffic type

Trade-off between how much

WiFi can gain but how much BT degrade

With 20% BT service

degradation, WiFi can gain 80%

The next version – advanced

rate-backoff algorithm can balance both systems with QoS

Conclusion

Proliferating of multi-radio devices will cause both in-

platform and close-proximity radio interference severe

CSCC protocol allows explicit spectrum coordination

between multi-radio platforms

Coordination algorithms in WiFi/Bluetooth case

Advanced rate-backoff algorithm helps both systems to approach optimal

• perating regions by cooperatively controlling their rates

Simplified rate algorithm favours WiFi over Bluetooth

Proof-of-concept experiments using ORBIT multi-radio

nodes

Simplified algorithm can significantly improve WiFi performance by lowering

Bluetooth service quality

On-going and Future Work

Improve the design and evaluate advanced rate-backoff

algorithm

Introduce ZigBee and WiMax ESG to the multi-radio

platform

Emulate WiMax DL signal with varying duty-cycles

Collaborative multi-radio relay network

Design “best-path-selection” algorithm Achieve always best connected to improve end-to-end experience

Thank you!