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Improving Spatial Reuse through Tuning Transmit Power, Carrier Sense Threshold, and Data Rate in Mul

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Title: Improving Spatial Reuse through Tuning Transmit Power, Carrier Sense Threshold, and Data Rate in Mul


1
Improving Spatial Reuse through Tuning Transmit
Power, Carrier Sense Threshold, and Data Rate in
Multi-hop Wireless Networks
  • Tae-Suk Kim
  • Hyuk Lim
  • Jennifer C. Hou
  • Dept. of Computer Science
  • UIUC
  • ACM MobiCom 2006

2
Contents
  • Background and Motivations
  • Related Works
  • Network Capacity Analysis
  • Analysis on Tuning Parameters
  • Proposed Power and Rate Control (PRC) Algorithm
  • Simulation Study
  • Conclusions

3
  • Background and Motivations
  • Related Works
  • Network Capacity Analysis
  • Analysis on Tuning Parameters
  • Proposed Power and Rate Control (PRC) Algorithm
  • Simulation Study
  • Conclusions

4
Background and Motivations
  • Multi-hop network capacity depends on
  • Achievable channel capacity at each individual
    wireless link
  • Level of spatial reuse
  • Tradeoff between the two factors
  • Increasing one factor inevitably causes
    decreasing the other
  • Physical carrier sensing employed in IEEE 802.11
    MAC
  • Carrier sense threshold
  • Determines the minimum distance, termed as the
    carrier sense range, between any pair of
    transmitters
  • The other control knob
  • Wireless medium is shared, and the shared range
    is determined by both the transmit power and the
    carrier sense threshold
  • One can control the level of spatial reuse by
    adjusting the transmit power or the carrier sense
    threshold

5
Background and Motivations (contd)
  • Two questions
  • What is the relation between the transmit power
    and the carrier sense threshold?
  • Does increasing transmit power have the same
    effect as increasing the carrier sense threshold?
  • Our contributions
  • Analytic model that expresses the network
    capacity as a function of the transmit power and
    the carrier sense threshold
  • Spatial reuse depends only on the ratio of the
    transmit power and the carrier sense threshold
  • Several advantages of tuning the transmit power
    over tuning the carrier sense threshold
  • Analyze the number of power levels required to
    achieve the same control granularity as afforded
    by tuning the carrier sense threshold
  • Localized power and rate control (PRC) algorithm
  • Each transmitter dynamically determines its
    transmit power and data rate adapting to the
    interference level that it perceives.

6
  • Background and Motivations
  • Related Works
  • Network Capacity Analysis
  • Analysis on Tuning Parameters
  • Proposed Power and Rate Control (PRC) Algorithm
  • Simulation Study
  • Conclusions

7
Related Works
  • Carrier sense threshold adjustment
  • Level of spatial reuse is controlled by varying
    the carrier sense threshold
  • Yang and Vaidya 1 is perhaps the first to
    address, with the data rate issue figured in, the
    impact of physical carrier sense on spatial reuse
    in multi-hop wireless networks. They also propose
    a heuristic algorithm, called Dynamic Spatial
    Backoff (DSB).
  • Power control
  • For the purpose of spatial reuse and capacity
    optimization (PCMA, PCDC, POWMAC, etc.)
  • Not consider the effect of carrier sense
    threshold on the network capacity
  • Analysis of the relation between the transmit
    power and the carrier sense threshold
  • Vaidya et al. 8 also analyze the relation
    between the transmit power and the carrier sense
    threshold in determining the network capacity.
  • They conclude that transmitters should keep the
    product of their transmit power and carrier sense
    threshold fixed at a constant.

8
  • Background and Motivations
  • Related Works
  • Network Capacity Analysis
  • Analysis on Tuning Parameters
  • Proposed Power and Rate Control (PRC) Algorithm
  • Simulation Study
  • Conclusions

9
Interference Model
  • Assumptions
  • Nodes are randomly and uniformly distributed in
    an area U with reasonably high node density ?.
  • Distance between a transmitter and a receiver, R,
    is given
  • Path-loss radio propagation model
  • Perfect MAC protocol
  • Interference level and SINR at a receiver
  • Consider the transmission between TX0 and RX0
    that are R away from each other
  • Transmit power Ptx, Carrier sense threshold Tcs
  • Carrier sense range D nodes concurrently
    transmitting with TX0 must be at least D away
    from TX0 and each other

10
Interference Model (contd)
  • The worst-case interference, I, as perceived at
    RX0
  • Corresponding SINR at RX0

11
Network Capacity as a Function of Transmit Power
and Carrier Sense Threshold
  • Network Capacity
  • where ,
    is the area of the system, and is the area
    consumed by each transmitter (
    ).
  • where is a constant.
    From the fact that ,
  • where is a constant.

12
  • Background and Motivations
  • Related Works
  • Network Capacity Analysis
  • Analysis on Tuning Parameters
  • Proposed Power and Rate Control (PRC) Algorithm
  • Simulation Study
  • Conclusions

13
Benefits of Power Control
  • Example 1
  • Consider a transmission TX RX under the
    assumption that all node use the same transmit
    power Ptx. Let M denote the number of concurrent
    transmissions. The SINR at RX is then
  • RX may endure the decrease of its SINR while
    sustaining ri, hoping more concurrent
    transmissions can be accommodated.
  • CST tuning
  • Adjusting SINR depends on node distribution
    around the TX-RX!!!
  • The same scenario using the power control.
  • How many number of power levels are needed to
    achieve the same control granularity as tuning
    the carrier sense threshold?

14
Benefits of Power Control (contd)
  • Example 2
  • TX1 can increase its transmit power up to the
    point where it sustains a higher data rate r3
    while not depriving the other concurrent
    transmission TX2 RX2 of the data rate r2.
  • Tuning carrier sense threshold
  • TX1 can achieve the rate r3 only when TX1
    decreases Tcs to the degree that TX2 is included
    within the carrier sense range of TX1.
  • Tuning carrier sense threshold can not achieve
    the same object!

15
Benefits of Power Control (contd)
  • Granularity of Transit Power levels needed
  • Derive a lower bound on the number of power
    levels required to achieve at least the same
    control granularity as carrier sense threshold
    tuning.
  • Denote the SINR at RX as , where
    . We decrease at TX
    such that the carrier sense range increases from
    to and includes one additional
    concurrent transmitter TXc. Then, the
    interference level at RX will be decreased by
    amount of .
  • The minimum possible SINR increase

    with carrier sense tuning
  • The minimum possible SINR increase

    with power control
  • Set to Ptx/k, where k denotes the number of
    power levels available.
  • If DgtgtR, then total of five power levels should
    be sufficient!

16
  • Background and Motivations
  • Related Works
  • Network Capacity Analysis
  • Analysis on Tuning Parameters
  • Proposed Power and Rate Control (PRC) Algorithm
  • Simulation Study
  • Conclusions

17
Determining Power Range
  • PRC algorithm
  • A localized algorithm that enables each
    transmitter to adapt to the interference level
    that it perceives and determines its transmit
    power.
  • The transmit power is so determined that the
    transmitter can sustain the highest possible data
    rate, while keeping the adverse interference
    effect on the other neighboring concurrent
    transmissions minimal.
  • Transmit power range
  • Determine the minimum transmit power that ensures
    that a receiver can sustain the minimum data rate
    considering the worst-case where TX0 transmits
    with the minimum transmit power, while its six
    1st tier interfering nodes transmit with the
    maximum power level. For this purpose, the SINR
    level at RX0 should satisfy

18
Determining Carrier Sense Threshold
  • Objective if TX transmits with its minimum
    transmit power, then at RX, which is the maximum
    distance Rmax away from TX, the minimal date rate
    of r1 can be sustained.
  • We determine Tcs at the transmitter to ensure the
    IRX requirement is satisfied at RX. However, it
    needs global knowledge of node distribution! ?
    conservative but localized approach.
  • The most conservative scenario occurs when the
    distance between RX and the interferer closest to
    RX is minimized. This is when IRX is contributed
    by a single interfering node TXi using the
    minimum transmit power.
  • The minimum interference level perceived at TX

19
Proposed Algorithm
  • Theoretical base
  • Find the maximal transmit power such that it does
    not deprive the other concurrent transmissions of
    sustaining their data rate.? needs global
    knowledge!!!
  • Estimate the position of a hypothetical
    interfering node TXi based on the level of ITX
    under the conservative scenario. To ensure both
    TX and TXi can engage in transmission
    concurrently,
  • Decide the final transmit power
  • If the data rate ri afforded by can be
    achieved with a smaller power level, there is no
    need to transmit with to mitigate the
    interference level of other transmissions.

20
Proposed Algorithm (contd)
  • Pseudo codes of PRC
  • Concurrent transmissions may commence and
    terminate dynamically, the interference level
    perceived at the receiver fluctuates with time.
    ?Need to monitor the variation in the
    interference level.
  • Ns and Nf

21
  • Background and Motivations
  • Related Works
  • Network Capacity Analysis
  • Analysis on Tuning Parameters
  • Proposed Power and Rate Control (PRC) Algorithm
  • Simulation Study
  • Conclusions

22
Simulation Setup
  • Modified ns-2 Ver. 2.28
  • The interference perceived at a receiver is the
    collective aggregate interference from all the
    concurrent transmissions
  • Each node uses physical carrier sense to
    determine if the medium is free
  • IEEE 802.11a radios supporting 8 discrete data
    rate (6 54 Mbps)
  • Random topology
  • 3, 10, 20, 30, and 50 transmitter-receiver pairs
    are randomly generated in a 300m X 300m area, and
    represent sparsely, moderately, and densely
    populated networks, respectively,.
  • Algorithms used for evaluations
  • Static
  • Dynamic Spatial Backoff (DSB)
  • Greedy Power Control (GPC)
  • Power and Rate Control (PRC)

23
Simulation Results
  • Sparse network
  • Low effect of carrier sense range
  • PRC operates in an economical manner
  • Compared with Static
  • Higher concurrent transmissions
  • Unnecessarily high transmit power can actually
    reduces the attainable level of spatial reuse

24
Simulation Results (contd)
  • Compared with DSB
  • In spite of a smaller carrier sense range, using
    a lower transmit power leads to less
    interference, and enables more concurrent
    transmissions.
  • Comparison between DSB and Static
  • High carrier sense threshold, when combined with
    an inappropriately tuned transmit power, can
    actually impair the network throughput.
  • GPC
  • Higher power level leads to the decrease in
    spatial reuse
  • Aggregate throughput approaches to that of static
    with the size of the network

25
  • Background and Motivations
  • Related Works
  • Network Capacity Analysis
  • Analysis on Tuning Parameters
  • Proposed Power and Rate Control (PRC) Algorithm
  • Simulation Study
  • Conclusions

26
Conclusions
  • We have investigated the impact of spatial reuse
    on the network capacity
  • Derive the network capacity as a function of the
    two control knobs the transmit power and the
    carrier sense threshold
  • Show their relation (i) in the case of continuous
    data rate (i.e., the channel rate follows the
    Shannon capacity) and (ii) in the case of
    discrete data rate
  • We proposed a localized power and rate control
    (PRC) algorithm
  • Each node can adjust transmit power and data rate
    dynamically based on its signal interference
    level.
  • A transmitter determines its transmit power so
    that it can sustain the highest possible data
    rate, while keeping the adverse interference
    effect on the other neighboring concurrent
    transmissions minimal
  • PRC achieves up to 22 improvement in the
    aggregate network throughput as compared to the
    DSB algorithm
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