1. Slides adapted from Romit Roy Choudhury (Duke)
Wireless & Mobile Networking CS 752/852 - Spring 2011
Lec #7: Medium Access Control – V Data Rate Control
Tamer Nadeem
Dept. of Computer Science
Slides adapted from Romit Roy Choudhury (Duke)

2. What is Data Rate ? Number of bits that you transmit per unit time
under a fixed energy budget
Too many bits/s:
Each bit has little energy -> Hi BER
Too few bits/s:
Less BER but lower throughput

3. How do we choose the rate of modulation
Some Basics
Friss’ Equation:
Received Power
Bit error (p) for BPSK and QPSK :
Channel Bandwidth
How do we choose the rate of modulation
SNR
Varying
with time
and space
Data Rate
Floor Noise

4. 802.11b – Transmission rates

5. Static Rates SINR time # Estimate a value of SINR
# Then choose a corresponding rate that would transmit packets
correctly most of the times
# Failure in some cases of fading  live with it

6. Adaptive Rate-Control
SINR
time
# Observe the current value of SINR
# Believe that current value is indicator of near-future value
# Choose corresponding rate of modulation
# Observe next value
# Control rate if channel conditions have changed

7. Is there a tradeoff ?
Rate = 10 B C E A D

8. What about length of routes due to smaller range ?
Is there a tradeoff ?
Rate = 10 B C E A D
Rate = 20
What about length of routes due to smaller range ?

9. Will carrier sense range vary with rate
Any other tradeoff ?
Will carrier sense range vary with rate

10. Carrier sensing estimates energy in the channel.
Total interference
Rate = 10 B C E A D
Rate = 20
Carrier sensing estimates energy in the channel.
Does not vary with transmission rate

11. Bigger Picture Rate control has variety of implications
Any single MAC protocol solves part of the puzzle
Important to understand e2e implications
Does routing protocols get affected?
Does TCP get affected? …
Good to make a start at the MAC layer
RBAR
OAR
Opportunistic Rate Control

12. A Rate-Adaptive MAC Protocol for Multi-Hop Wireless Networks
Gavin Holland
HRL Labs
Nitin Vaidya Paramvir Bahl
UIUC Microsoft Research
MOBICOM’01 Rome, Italy
© Gavin Holland

13. Background Current WLAN hardware supports multiple data rates
802.11b – 1 to 11 Mbps
802.11a – 6 to 54 Mbps
Data rate determined by the modulation scheme

14. Problem Modulation schemes have different error characteristics
8 Mbps
1 Mbps
BER
But, SINR itself varies
With Space and Time
SNR (dB)

15. Large-scale variation with distance (Path loss) Mean Throughput (Kbps)
Impact
Large-scale variation with distance (Path loss)
8 Mbps
Path Loss
SNR (dB)
Mean Throughput (Kbps)
1 Mbps
Distance (m)
Distance (m)

16. Small-scale variation with time (Fading)
Impact
Small-scale variation with time (Fading)
Rayleigh Fading
SNR (dB)
2.4 GHz
2 m/s LOS
Time (ms)

17. Question Which modulation scheme to choose?
SNR (dB)
SNR (dB)
2.4 GHz
2 m/s LOS
Distance (m)
Time (ms)

18. Answer  Rate Adaptation
Dynamically choose the best modulation scheme for the channel conditions
Desired
Result
Mean Throughput (Kbps)
Distance (m)

19. How frequently must rate adaptation occur?
Design Issues
How frequently must rate adaptation occur?
Signal can vary rapidly depending on:
carrier frequency
node speed
interference
etc.
For conventional hardware at pedestrian speeds, rate adaptation is feasible on a per-packet basis
Coherence time of channel higher than transmission time

20. Adaptation  At Which Layer ?
Cellular networks
Adaptation at the physical layer
Impractical for in WLANs
For WLANs, rate adaptation best handled at MAC
Why?
RTS/CTS requires that the rate be known in advance D C B A
CTS: 8
RTS: 10 10 8
Sender
Receiver

21. Who should select the data rate?
Collision is at the receiver
Channel conditions are only known at the receiver
SS, interference, noise, BER, etc.
The receiver is best positioned to select data rate A B

22. Previous Work PRNet Pursley and Wilkins
Periodic broadcasts of link quality tables
Pursley and Wilkins
RTS/CTS feedback for power adaptation
ACK/NACK feedback for rate adaptation
Lucent WaveLAN “Autorate Fallback” (ARF)
Uses lost ACKs as link quality indicator

23. Lucent WaveLAN “Autorate Fallback” (ARF)
DATA
2 Mbps
Effective Range
1 Mbps
Sender decreases rate after
N consecutive ACKS are lost
Sender increases rate after
Y consecutive ACKS are received or
T secs have elapsed since last attempt

24. Slow to adapt to channel conditions
Performance of ARF
SNR (dB)
Time (s)
Dropped Packets
Rate (Mbps)
Time (s)
Failed to Increase
Rate After Fade
Attempted to Increase
Rate During Fade
Slow to adapt to channel conditions
Choice of N, Y, T may not be best for all situations

25. Move the rate adaptation mechanism to the receiver
RBAR Approach
Move the rate adaptation mechanism to the receiver
Better channel quality information = better rate selection
Utilize the RTS/CTS exchange to:
Provide the receiver with a signal to sample (RTS)
Carry feedback (data rate) to the sender (CTS)

26. Receiver-Based Autorate (RBAR) Protocol
CTS (1)
RTS (2)
2 Mbps
1 Mbps D
DATA (1)
RTS carries sender’s estimate of best rate
CTS carries receiver’s selection of the best rate
Nodes that hear RTS/CTS calculate reservation
If rates differ, special subheader in DATA packet updates nodes that overheard RTS

27. Performance of RBAR SNR (dB) Time (s) Rate (Mbps) Time (s) Rate (Mbps)
ARF
Time (s)

28. There are two types of fading
Question to the class
There are two types of fading
Short term fading
Long term fading
Under which fading is RBAR better than ARF ?
Under which fading is RBAR comparable to ARF ?
Think of some case when RBAR may be worse than ARF

29. Implementation into

30. Implementation into
PLCP Header

31. Reservation Subheader (RSH)
Implementation into
Frame
Control
Sequence
Control
Duration DA SA
FCS
BSSID
Body
FCS
Reservation Subheader (RSH)
Encode data rate and packet length in duration field of frames
Rate can be changed by receiver
Length can be used to select rate
Reservations are calculated using encoded rate and length
New DATA frame type with Reservation Subheader (RSH)
Reservation fields protected by additional frame check sequence
RSH is sent at same rate as RTS/CTS
New frame is only needed when receiver suggests rate change
WHY

32. Performance Analysis 1E-5
Ns-2 with mobile ad hoc networking extensions
Rayleigh fading
Scenarios: single-hop, multi-hop
Protocols: RBAR and ARF
RBAR
Channel quality prediction:
SNR sample of RTS
Rate selection:
Threshold-based
Sender estimated rate:
Static (1 Mbps)
BER
1E-5
2 Mbps
Threshold
SNR (dB)
8 Mbps
Threshold

33. Performance Results Single-Hop Network

34. Mean Throughput (Kbps)
Single-Hop Scenario
Mean Throughput (Kbps)
Distance (m) A B

35. Varying Node Speed UDP Performance
RBAR
ARF
Mean Throughput (Kbps)
CBR source
Packet Size = 1460
Mean Node Speed (m/s)
RBAR performs best
Declining improvement with increase in speed
Adaptation schemes over fixed
RBAR over ARF
Some higher fixed rates perform worse than lower fixed rates
WHY?

36. Varying Node Speed TCP Performance
RBAR
ARF
Mean Throughput (Kbps)
FTP source
Packet size = 1460
Mean Node Speed (m/s)
RBAR again performs best
Overall lower throughput and sharper decline than with UDP
Caused by TCP’s sensitivity to packet loss
More higher fixed rates perform worse than lower fixed rates

37. No Mobility UDP Performance
RBAR
CBR source
Packet size = 1460
ARF
Mean Throughput (Kbps)
Mean Throughput (Kbps)
Distance (m)
Distance (m)
WHY?
RSH overhead seen at high data rates
Can be reduced using some initial rate estimation algorithm
Limitations of simple threshold-based rate selection seen
Generally, still better than ARF

38. No Mobility UDP Performance
RBAR-P
CBR source
Packet size = 1460
Mean Throughput (Kbps)
Distance (m)
RBAR-P – RBAR using a simple initial rate estimation algorithm
Previous rate used as estimated rate in RTS
Better high-rate performance
Other initial rate estimation and rate selection algorithms are a topic of future work
Why useful ?

39. RBAR Summary Modulation schemes have different error characteristics
Significant performance improvement may be achieved by MAC-level adaptive modulation
Receiver-based schemes may perform best
Proposed Receiver-Based Auto-Rate (RBAR) protocol
Implementation into
Future work
RBAR without use of RTS/CTS
RBAR based on the size of packets
Routing protocols for networks with variable rate links

40. Questions?

41. Multi-rate Anomaly [Heusse03]
The question is, how severe the LA scheme on network performance. In order to answer this question, we ran a simple experiments with two nodes n1 & n2 with this simple network toplogy where n1 is fixed and connected to BS and n2 is mobile one and move from left to right
We first allowed n1 & n2 to run with 11Mbs (Red and Green), then when n1&n2 run with 1Mbs (Blue and pink). These two middle lines define the expected boundaries when nodes all run 11 MBs and when al nodes run 1Mbs.
Now, given the heterogeneous case where n1 runs 11Mbs and n2 runs 1Mbs. We get the curve for (light blue and Yellow). Comparing this curves with the expected boundaries for the homogeneous case, we can see that Fast user throughput (n1), light blue curve is severely degraded while the slow user got higher throughput than he is exepcted.
This is a well know behavior of WiFi networks first identified by Huesse in InfoCom 2003 and called this behaviour the Multi-rate Anamoly
Now the question is: How serious is it?
The SIGCOMM picture
Three scenarios:
Both nodes use 11 Mb/s
Both nodes use 1 Mb/s
n1 uses 11 Mb/s, n2 uses 1 Mb/s
Fast user’s throughput is severely degraded
whereas
Slow user achieves throughput even larger than it expects

42. OAR: An Opportunistic Auto-Rate Media Access Protocol for Ad Hoc Networks
B. Sadeghi, V. Kanodia, A. Sabharwal, E. Knightly
Rice University
Slides adapted from Shawn Smith

43. Motivation
Consider the situation below
ARF?
RBAR? A B C

44. Throughput Fairness vs Temporal Fairness
Motivation
What if A and B are both at 56Mbps, and C is often at 2Mbps?
Slowest node gets the most absolute time on channel? A B C
Timeshare A B C
Throughput Fairness vs Temporal Fairness

45. Opportunistic Scheduling
Goal
Exploit short-time-scale channel quality variations to increase throughput.
Issue
Maintaining temporal fairness (time share) of each node.
Challenge
Channel info available only upon transmission

46. Opportunistic Auto-Rate (OAR)
In multihop networks, there is intrinsic diversity
Exploiting this diversity can offer benefits
Transmit more when channel quality great
Else, free the channel quickly
RBAR does not exploit this diversity
It optimizes per-link throughput

47. OAR Idea D C A B A C Basic Idea Data Data Data Data Data Data Data
If bad channel, transmit minimum number of packets
If good channel, transmit as much as possible D C A B
Data
Data
Data
Data A
Data
Data
Data
Data C

48. Why is OAR any better ? D C A B A C
alternates between transmitters A and C
Why is that bad D C A B
Data
Data
Data
Data A
Data
Data
Data
Data C
Is this diagram correct ?

49. Why is OAR any better ? D C A B A C
Bad channel reduces SINR  increases transmit time
Fewer packets can be delivered D C A B
Data
Data A
Data
Data
Data C
Data

50. OAR Protocol Steps Transmitter estimates current channel
Can use estimation algorithms
Can use RBAR, etc.
If channel better than base rate (2 Mbps)
Transmit proportionally more packets
E.g., if channel can support 11 Mbps, transmit (11/2 ~ 5) pkts
OAR upholds temporal fairness
Each node gets same duration to transmit
Sacrifices throughput fairness  the network gains !!

51. MAC Access Delay Simulation
Back to back packets in OAR decrease the average access delay
Increase variance in time to access channel
Why?

52. OAR Protocol Rates in IEEE 802.11b: 2, 5.5, and 11 Mbps
Number of packets transmitted by OAR ~

53. Simulations Three Simulation experiments
Fully connected networks: all nodes in radio range of each other
Number of Nodes, channel condition, mobility, node location
Asymmetric topology
Random topologies
Implemented OAR and RBAR in ns-2 with extension of Ricean fading model [Punnoose et al ‘00]

54. Fully Connected Setup Every node can communicate with everyone
Each node’s traffic is at a constant rate and continuously backlogged
Channel quality is varied dynamically

55. Fully Connected Throughput Results
OAR has 42% to 56% gain over RBAR
Increase in gain as number of flows increases
Note that both RBAR and OAR are significantly better than standard (230% and 398% respectively)

56. Asymmetric Topology Results
OAR maintains time shares of IEEE
Significant gain over RBAR

57. OAR thoughts OAR does not offer benefits when
OAR may not be suitable for applications like
With TCP how can OAR get affected ?

58. OAR thoughts OAR does not offer benefits when
Neighboring nodes do not experience diverse channel conditions
Coherence time is shorter than N packets
With TCP can OAR get affected ?
Back-to-back packets can increase TCP performance
However, bottleneck bandwidth can get congested quick
Also, variance of RTT can increase

59. Multi-user Data Rate Adjustment Algorithm for Enterprise Networks
Nazif Tas, Tamer Nadeem, Ashok Agrawala
INFOCOM 2011

60. Data Rate Adjustment Mechanisms
Previous Work
Data Rate Adjustment Mechanisms
Agreement between sender and the transmitter on rate to use.
Sender-based: statistical.
Easy, resource efficient.
ARF, AARF, CARA, AMRR…
Receiver-based: receiver chooses data rate and notifies the sender.
More accurate, unnecessary resource usage.
RBAR
Multi-rate Anomaly Solutions
Infrastructure-based solutions
AP selection, traffic scheduling, etc
[Wang, Ji, Im04, …]
MAC Layer modifications
Packet bursting, minimum CW adjustment, etc
[Mai09, Yah-hong07, …]
Higher Layer adjustments
TCP window adjustment, traffic slow down
[Yoo08, Kashibuchi09, …]
Requires holistic view of the system
Requires modifications in the standards
Time fairness?
OAR, Cwmin adjustment, scheduling etc.
But, they propose to change the standard or assume global view of the system
NOT realistic. Can we do it without modification and holistic view.
This requires a good analysis of Multi-rate anomaly
Requires non-seamless cross layer support
Can we lessen the effects of Multi-Rate anomaly efficiently in a distributed & seamless manner with no modifications in the standards?

61. Binary Exponential Backoff (BEB)
IEEE BEB
Binary Exponential Backoff (BEB)
IEEE DCF
CSMA/CA: carrier sensing
Binary Exponential Backoff

62. Baseline Fairness Criteria
: throughput seen by data rate d users in a network with ns number of slow users and nf number of fast users.
[Tan04]
Multi-rate Anomaly
Why is multi-rate anomaly bad?
Baseline Fairness Criteria
Fast
Slow

63. Bianchi Model with Retry Limit
Can we use arbitrary limits to mitigate Multi-rate Anomaly?
k: retry limit
Our extension supports arbitrary retry limits per user groups
For data rate di,

64. Multi-user Data Rate Adjustment Algorithm (MORAL)
Observe
Automatically adjust the retry limits of each user such that
Improve fairness: Take the fair throughput share without hurting others.
Distributed computation: No centralized decision making.
Standard Coherence: No packet modification, restructuring or protocol alteration. LA
MAC
Decide
Act
Two step operation:
Collect information about the overall network.
Adjust the retry limit accordingly
“The first thing to note is that [happiness] is a relative quality. We experience it differently according to our circumstances. What makes one person glad may be a source of suffering to another”

65. MORAL Details: Heuristic Principles
After each transmission cycle, we have two pieces of information:
ccurrent: number of transmissions this cycle for the current node
Successful transmission (ccurrent =1)
Failed transmission(ccurrent =0)
ccalculated: Fair number of transmissions for the current node

66. Experiments I 60% 61.3% 1 Mb/s 11 Mb/s MORAL
11, 1 Mb/s – 20 Users Each
60%
Default
MORAL
Balanced Static
1 Mb/s
61.3%
11 Mb/s

67. Experiments II 43.0% 31.8% 11, 5.5, 2, 1 Mb/s– 10 Users Each Default
MORAL
43.0%
Balanced Static
31.8%

68. Experiments III 48.0% 20.8% 93.8% 30 1 Mb/s, 10 11 Mb/s Default 1 Mb/s
MORAL
11 Mb/s
20.8%
93.8%
1 Mb/s

69. Experiments IV
40.2%
23.9%
11, 1 Mb/s – 20 Users Each

70. Summary
MORAL is an effective MAC layer link adaptation mechanism which lessens the effects of multi-rate anomaly and promises
- Better fairness
- Increased throughput
MORAL is
Fully compatible with the current standards
Totally distributed
Highly adaptable
Easily deployable in any IEEE compliant devices

71. Other Ideas
(Briefly)

72. Exploiting Diversity in Rate Adaptation
Yet another idea exploits multiple user diversity
Among many intermediate nodes, who has best channel
Use that node as forwarding node
Forwarding node can change with time
Due to channel fluctuations at different time and space
Channel Conditions
SNR
WLAN AP
TIME
USERS

73. MAD using Packet Concatenation (PAC)
The Protocol Overview
MAD using Packet Concatenation (PAC)
DIFS
SIFS
SIFS
SIFS
SIFS
sender
GRTS
DATA 0
DATA 1
DATA 2 SF
user 1
CTS 1
CTS k
CTS 2 …
user 2
ACK 0~2
user k
Since at least one intermediate node is likely to have good channel
condition, transmitter can transmit at a high data rate or concatenate
Multiple packets
Choosing subset of neighbor-group is important
Coherence time of channel must be greater than packet chain
Group needs to really have independent channel gain
Correlated channel gains can lead to performance hit.

74. Routing based on rate-control
What lies ahead ?
Routing based on rate-control
Choosing routes that contain high-rate links
ETX metric proposed from MIT accomodates link character
Opportunistic routing from MIT again – takes neighbor diversity into account (best paper Sigcomm 2005)
Fertile area for a project …
Dual of rate-control is power control
One might be better than the other
Decision often depends on the scenario  open problem
Directional antennas for DD link for data/ack
Rate control can be introduced  Not been studied yet
… many many more

75. Questions ?