Modeling the effect of transmit power and physical carrier sense in multi hop wireless networks
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Modeling the Effect of Transmit Power and Physical Carrier Sense in Multi-hop Wireless Networks. Yong Yang , Jennifer C. Hou and Lu-chuan Kung Department of Computer Science University of Illinois at Urbana-Champaign. Carrier Sensing Range d cs. Carrier Sensing Range d cs. Motivation.

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Modeling the Effect of Transmit Power and Physical Carrier Sense in Multi-hop Wireless Networks

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Modeling the effect of transmit power and physical carrier sense in multi hop wireless networks

Modeling the Effect of Transmit Power and Physical Carrier Sense in Multi-hop Wireless Networks

Yong Yang, Jennifer C. Hou and Lu-chuan Kung

Department of Computer Science

University of Illinois at Urbana-Champaign

Y. Yang, J. Hou and L.-C. Kung


Motivation

Carrier Sensing Rangedcs

Carrier Sensing Range dcs

Motivation

  • Single-hop / Single-cell wireless networks

s1

r1

s2

r2

Y. Yang, J. Hou and L.-C. Kung


Motivation1

Interfernce Range din

Motivation

  • Single-hop / Single-cell wireless networks

s1

r1

s2

r2

Y. Yang, J. Hou and L.-C. Kung


Motivation2

dcsdind

Tx Power, CS Threshold

Motivation

  • Single-hop / Single-cell wireless networks

  • Multi-hop / Multi-cell wireless networks

s1

r1

s2

r2

  • Objective: study the effect of Transmit Power and Carrier Sensing on Network Throughput

Y. Yang, J. Hou and L.-C. Kung


Contributions

s1

r1

s2

r2

s3

Contributions

  • Model IEEE 802.11 based multi-hop networks

    • Incorporate important MAC/PHY attributes

      • Transmit Power, Carrier Sense Threshold

    • Consider accumulated signal effect

  • Analyze the effect of MAC/PHY attributes on network throughput

Y. Yang, J. Hou and L.-C. Kung


Outline

Outline

  • Motivation

  • Contributions

  • Accumulated Signal Effect

  • Analytical Model

  • Effect of Tx. Power and Carrier Sensing

  • Conclusions and Future Work

Y. Yang, J. Hou and L.-C. Kung


Accumulated signal effect

  • Consider a thin ring Ri outside dcs of width Dr:

    • Inner radius:

    • Signal level at s:

    • node together can make s sense busy

    • Effective contenting nodes

ri

Accumulated Signal Effect

  • Accumulated signals outside dcs may exceed CSth

  • Assumptions

    • Nodes are distributed by a Poisson point process with d

    • Nodes always have packet to transmit

  • Effective number of contenting nodes within dcs :

s

dcs

Y. Yang, J. Hou and L.-C. Kung


Accumulated signal effect contd

Accumulated Signal Effect (contd.)

  • Thus, the total effective contenting nodes:

  • Equivalently, we can use an effective carrier sense threshold

  • Similarly, we can obtain the effective SIR threshold

s

dcs

Y. Yang, J. Hou and L.-C. Kung


Model overview

Idle

Busy

Collision

Success

Model Overview

  • The MAC layer throughput of each sender s:

  • Tv: expected length of a slot

    • Four types of activities in a slot with respective to s

  • Pa: transmission attempt probability in a slot

  • Pc: collision probability given a transmission attempt

Y. Yang, J. Hou and L.-C. Kung


Model transmission attempt prob

Model: Transmission Attempt Prob.

  • Bianchi models the back-off process of a node as a discrete-time Markov process

    • The unit of time is the virtual slot time

    • The key assumption: for each transmission attempt, it incurs a collision with a constant and independently probability Pc

  • This can be applied to multi-hop networks

    • The only different is the virtual slot time

Y. Yang, J. Hou and L.-C. Kung


Model virtual slot time

Model: Virtual Slot Time

  • A virtual slot could be

    • Successful transmission:

      • Sender s transmits, and no collision

    • Collision:

      • Sender s transmits, but runs into a collision

    • Idle:

      • No node in CSsU{s} attempts to transmit

    • Busy:

      • Sender s is backing off, while at least one in CSs transmit

  • Expected length of a virtual slot

Tsucc, Tcol, Tidleand Tbusy can be determined given MAC/PHY parameters

Y. Yang, J. Hou and L.-C. Kung


Model collision probability

s

r

Model: Collision Probability

Tp

  • A transmission is corrupted if

    • Any node in CSs INrstarts to transmit at the beginning of the transmission

    • Any node in INr \ CSsstarts to transmit at or even after the beginning of the transmission

  • The collision probability:

t

CSs

INr

d

din

dcs

Y. Yang, J. Hou and L.-C. Kung


Fixed point analysis

Fixed Point Analysis

  • A set of fixed point equations:

  • We prove that a unique solution exists to this equations

  • But hard to find explicit formulas

Y. Yang, J. Hou and L.-C. Kung


Effect of tx power

Area

1000m1000m

Payload

2048B

Rate

36Mbps

4

Effect of Tx Power

  • The per-node throughput S decreases with the increase of d

  • Adjust transmit power to control d

    • Subject to connectivity constraint

Y. Yang, J. Hou and L.-C. Kung


Effect of carrier sense

d

din

dcs

s

r

Effect of Carrier Sense

  • When dcs > d + din, the per-node throughput S decreases with the increase of dcs

  • The optimal dcs* exists in [0, d + din]

Y. Yang, J. Hou and L.-C. Kung


Conclusions and future work

Conclusions and Future Work

  • Model IEEE 802.11 based multi-hop networks

  • Analysis and simulation show

    • Use power control to decrease d to improve MAC layer throughput

    • Adjust carrier sensing threshold s.t. dcs < d + din

  • Future Work

    • Online power control algorithm joint with carrier sense threshold adjustment

    • End-to-end throughput

Y. Yang, J. Hou and L.-C. Kung


Thank you and questions

Thank You and Questions?

Y. Yang, J. Hou and L.-C. Kung


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