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Tae-Suk Kim, Hyuk Lim, and Jennifer C. Hou Dept. of Computer Science UIUC ACM MobiCom 2006

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### Improving Spatial Reuse through Tuning Transmit Power, Carrier Sense Threshold, and Data Rate in Multi-hop Wireless Networks

Tae-Suk Kim, Hyuk Lim, and Jennifer C. Hou

Dept. of Computer Science

UIUC

ACM MobiCom 2006

of concurrent

transmissions

- MAC layer

the number of bits

that can be transported

simultaneously in the network

Signal-to-Interference-and-Noise-Ratio (SINR)

- PHY layer

Network Capacity in Ad-hoc Networks

Link Capacity=

X

Network Capacity

Spatial Reuse

Understanding PHY/MAC Control Knobs

- To mitigate interference and maximize the network capacity, there are several control knobs:
- Power control (a.k.a. topology control)
- Adjusting carrier sense threshold trade-off between spatial reuse and interference level
- Spatial diversity scheduling consecutive transmission for interference-free connections
- Channel diversity use of non-overlapping channels

Power Control

- Definition: Each node adjusts its transmission power so as to meet the SINR constraint, while keeping the adverse interference effect on the other neighboring concurrent transmissions minimal.

B

D

C

A

F

E

Signal Strength

CS Threshold

distance

Capacity Optimization Through Controlling CS Threshold- The contending area can also be adapted through tuningthe carrier-sensing threshold

D

C

A

F

E

Signal Strength

distance

CS Threshold

How CS Threshold Controls Contending Area- Larger CS threshold leads to
- Smaller contending area
- Less contending nodes within the contending area
- More concurrent transmission
- Higher interference
- Contending area depends on
- Transmit Power
- CS Threshold
- Level of spatial reuse
- Size of Contending area
- Link Capacity

Tradeoff between Spatial Reuse and Achievable Data Rates

- Higher spatial reuse can be achieved at the cost of higher interference level and lower transmission rate

- What is the optimal contending area?

- How does it relate to the transmit power and CS threshold?

Low rate links

High rate links

Our contributions

- The relationship between Network Capacity and the parameters: PTx and TCS
- spatial reuse depends only on the ratio of the transmit power and the carrier sense threshold

- The advantages of tuning the transmit power over tuning the carrier sense threshold
- 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.

Interference Model

- Assumptions
- Nodes are randomly and uniformly distributed in an area U with reasonably high node density λ.
- Distance between a transmitter and a receiver, R, is given
- Path-loss radio propagation model:
- Perfect MAC protocol
- Under the interference model
- Consider the transmission between TxandRxthat are R away from each other
- Transmit power PTx, Carrier sense threshold Tcs
- Carrier sense range D: nodes concurrently transmitting with Tx must be at least D away from Tx and each other

Link Capacity

Network Capacity as a Function of Transmit Power and Carrier Sense ThresholdD

Increasing Function

Constants

for Power Control

D

Tx

Rx

Control Factor

for CST tuning

Benefits of Power ControlHow many power levels are needed to achieve the same control granularity as tuning the carrier sense threshold?

Benefits of Power Control (cont’d)

CST tuning

Increase the carrier sense range from D to D+ΔD such that one additional concurrent transmitter is included.

Interference level at Rx is decreased by ΔI

Power Control

R

D

D+ΔD

Number of power levels

For the better granularity,

In the case of D>>R,

Total of five levels should be sufficient!!!

Benefits of Power Control (cont’d)

- Example 2
- TX1 can increase its transmit power up to the point where it sustains a higher data rate r[3] while not depriving the other concurrent transmission TX2 – RX2 of the data rate r[2].
- Tuning carrier sense threshold
- RX1 can achieve the rate r[3] only when TX2 is included within the carrier sense range of TX1 so that TX2 should be silent when TX1 is transmitting.
- Tuning carrier sense threshold can not achieve the same object!

Power and Rate Control (PRC) Algorithm

- Characteristics:
- 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 theadverse interference effect on the other neighboring concurrent transmissions minimal.

Determining the minimum transmit power level

Target Min Power level: Rx can sustain the minimum data rate.

D-R/2

D+R/2

D-R

D

R

D-R

D+R

D

Rmax

Rx

Tx

Determining Carrier Sense ThresholdTarget CST level: Each node sets its carrier sense threshold s.t. if a transmitter transmits with Pmin at a distance R, the minimum data rate can be substained.

Conservative Scenario is assumed.

Minimum interference level perceived at TX

Power Control in PRC

From the received signal strength level at Tx, the distance, L, to a hypothetical interfering node I is estimated.

From

DI

I

L

The final Transmit Power

Tx

Rx

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)

Simulation Results

Unnecessarily high transmit power and CS Threshold not properly tuned can actually reduce the attainable level of spatial reuse !!!

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
- Fuemmeler et al. [2] 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.

[1] X. Yang and N. H. Vaidya. On the Physical Carrier Sense in Wireless Ad Hoc Networks. In Proceedings of IEEE INFOCOM, 2005.

[2] J. Fuemmeler, N. H. Vaidya, and V. V. Veeravalli. Selecting transmit powers and carrier sense thresholds for csma protocols. Technical Report, Univ. of Illinois at Urbana Champaign, 2004.

Conclusions

- We have investigated the impact of spatial reuse on the network capacity
- Identify 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.
- PRC uses a lower transmit power, which in turn induces low interference and enables better spatial reuse and achievable data rates.
- PRC achieves up to 22% improvement in the aggregate network throughput as compared to the DSB algorithm.

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