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Spatial Backoff Contention Resolution for Wireless Networks

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Dynamic Spatial Backoff Algorithm ... Stability Properties. Open Problems ... Integration of temporal and spatial contention resolutions ... – PowerPoint PPT presentation

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Title: Spatial Backoff Contention Resolution for Wireless Networks


1
Spatial Backoff Contention Resolution for
Wireless Networks
  • Xue Yang and Nitin H. Vaidya
  • University of Illinois at Urbana-Champaign

2
Transmissions Compete for Space
Space occupied by A or B
A
B
3
Temporal Contention Resolution
Space
Time
  • Temporal contention resolution resolves the local
    channel contention in time dimension

4
Transmissions Compete for space
A
B
5
Spatial Contention Resolution
Space
Time
B transmits
Space
A transmits
Time
6
Hybrid Contention Resolution
S1
?
S4
S6
S5
S3
S2
7
Spatial Contention Resolution
  • Control the contending area by adapting
    transmission power/rate/carrier-sensing
  • Goal
  • In this work
  • Joint adaptation of transmission rate and
    carrier-sense (CS) threshold, assuming a fixed
    transmission power

Contending area Desired contention level
8
How CS Threshold Controls Contending Area
B
D
C
A
F
E
Signal Strength
CS Threshold
distance
9
How CS Threshold Controls Contending Area
  • Larger CS threshold leads to smaller contending
    area

B
D
C
A
F
E
Signal Strength
CS Threshold
distance
10
Transmission rate needs to be adjusted
  • Larger CS threshold leads to higher interference
  • Transmission rate depends on Signal-to-Interferenc
    e-Noise Ratio

B
D
C
A
F
E
Signal Strength
CS Threshold
distance
11
Why Smaller Contending Region?
  • Reduce the collision probability due to local
    contention
  • Smaller number of locally competing nodes
  • Reduce the rate-independent MAC overhead
  • Channel time consumed by physical layer
    convergence procedure (PLCP) preamble and header
    (192 ms in IEEE802.11b).
  • Inter-frame space (DIFS, SIFS, etc) and the
    backoff durations
  • A smaller fraction of channel capacity is wasted
    in MAC overhead, if the channel operates at a
    lower rate.

12
Optimal CS threshold and transmission rate depend
on transmission density
13
Local information leads to sub-optimal decisions
  • Using cs1, node 1 and 2 transmit alternately with
    rate R1
  • Using cs2, node 1 and 2 transmit concurrently
    with rate R2
  • Optimal CS threshold for node 1 is cs1 if R2ltR1/2
  • Using cs2, node 1 transmits with rate R2, node 2
    transmits concurrently with rate R3
  • Optimal CS threshold for node 1 is cs2 if R2R3gtR1

14
Dynamic Spatial Backoff Algorithm
  • To search the two-dimensional space defined by
    the CS threshold and the transmission rate.
  • K discrete rates RateiltRatej, if iltj,
    i,j?(1, K)
  • Smallest CS threshold CSi for Ratei
  • CSigtCSj, if iltj.
  • To search the two-dimensional space defined by
    the CS threshold and the transmission rate.
  • K discrete rates RateiltRatej, if iltj,
    i,j?(1, K)
  • Smallest CS threshold CSi for Ratei
  • CSigtCSj, if iltj.

Reduce the search space to the subspace above or
on the diagonal line
15
Search Rules
  • Rule 1 when transmission are successful
  • Increase transmission rate by one level
  • Update the CS threshold for the new rate with the
    CS threshold associated with the old rate

16
Search Rules
  • Rule 2 when transmission fail and the operating
    point is above the diagonal line
  • Keep the transmission rate
  • Decrease CS threshold by one level

17
Search Rules
  • Rule 3 when transmission fail and the operating
    point is on the diagonal line
  • Decrease transmission rate by one level
  • Apply the CS threshold previously associated with
    the new rate

18
Search Rules
  • Rule 4 To avoid starvation when probing small
    threshold, if no transmission attempts in a
    certain time period
  • Reduce transmission rate by one level
  • Apply the CS threshold previously associated with
    the new rate

19
Stability Properties
20
(No Transcript)
21
Open Problems
  • Jointly transmission power, CS threshold, and
    transmission rate adaptation
  • Search space
  • Search rules
  • Integration of temporal and spatial contention
    resolutions
  • Impact of traffic and channel variations
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