TRANSMISSION POWER CONTROL FOR AD HOC WIRELESS NETWORKS: THROUGHPUT, ENERGY AND FAIRNESS

Lujun Jia; Xin Liu; Noubir, G.; Rajaraman, R.;Wireless Communications and Networking Conference, 2005 IEEE.Presenter: Han-Tien Chang

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Outline

Introduction Network Models And Assumptions δ-PCS: A Class of Power Control Schemes Simulation Results Implementation Issues Conclusion And Future Work Comments

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Introduction

Introduce a new power control scheme Combines collision avoidance and spatial

reuse Significant improvements for network

throughput and energy efficiency simultaneously

Adhere to the single-channel, single-transceiver design rule

Solve the fairness problem

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Introduction (cont’d)

Drawbacks of IEEE 802.11 802.11 uses maximum transmission power Pmax

regardless of the distance between the transmitter and the receiver

Spatial channel reuse in IEEE 802.11 is not optimized One on-going transmission may unnecessarily block

multiple nearby sessions by transmitting at Pmax

Fairness problem IEEE 802.11 delivers more packets for short distance traffic

pairs than for long-distance traffic pairs When the network load increases, the ratio of delivered

short distance traffic to long-distance traffic increases

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Introduction (cont’d)5

Related power control schemes [13] may suffer from The scheme improves energy-efficiency but not

network throughput, or increase the throughput at the expense of energy consumption

Extra hardware and spectrum availability are required, i.e., multiple wireless channels and transceivers

Strong assumptions on MAC or physical layers are imposed, which are often difficult to implement

[13] A. Muqattash and M. Krunz. A single-channel solution for transmission power control in wireless ad hoc networks. In ACM MobiHoc, May 2004.

Introduction (cont’d)6

δ-PCS A novel transmission power function P(t)

to compute an appropriate transmission power, so that a better spatial channel reuse is achieved

Unlike POWMAC [13], no collision avoidance information is explicitly advertised in our scheme.

Instead, nodes choose a transmission power level based on its traffic distance d, and an estimate of the interference level it experiences.

Introduction (cont’d)7

[8] E.S. Jung and N.H. Vaidya. A power control MAC protocol for ad hoc networks. In ACM Mobicom, September 2002.[11] J. Monks, V. Bharghavan, and W. Hwu. A power controlled multiple access protocol for wireless packet networks. In IEEE INFOCOM, April 2001.

Network Models and Assumptions

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P(r) = c · P(t)/dα where c is a constant that depends on the

antenna gains and heights, and carrier frequency,

d is the distance that the signal travels, and α is the power attenuation factor. The typical value of α ranges from 2 to 4.

For our simulation study, we adopt the standard two-ray ground model that sets α to be 4 for long-range distances and 2 for short-range distances.

Network Models and Assumptions (cont’d)

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The bit-error rate of a transmission depends on the noise power and the interference level at the receiver Let {Xk, k ∈ T} be the set of nodes simultaneously

transmitting at any time instant. Let Xj be the receiver of a transmitter Xi ∈ T For the transmission by Xi to be successfully

received by Xj : (1) the received power P(r) at node Xj must exceed the

receiving threshold, RXth (2) the SINR at Xj must exceed the SINR threshold,

SINRth

Network Models and Assumptions (cont’d)

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We use traffic distance or traffic length to denote the distance between the transmitter and the receiver.

The transmission range of a certain power level P(t)

denotes the maximum distance at which the received signal is right above RXth

Beyond the transmission range, the signal can still be detected (but not decoded) if its strength is above the carrier sensing threshold, CSth. Typically, CSth is several dBs lower than RXth. Thus, the sensing range defined by CSth is larger

than the transmission range

δ-PCS: A Class of Power Control Schemes

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Overview of δ-PCS 1. Given the maximum transmission power

level, Pmax The corresponding maximum transmission

range dmax satisfies c · Pmax/dmaxα = RXth.

2. Given the distance d between the transmitter and receiver, the minimum necessary transmission power,

Pmin(d), for a transmission to be successful satisfies c · Pmin/dα = RXth.

Let parameter δ be any constant between 0 and α our power function is the following

By substituting RXth with c · Pmax/dmaxα

Let dT be the transmission range of P(t). By the definition of transmission range,

the received signal power at dT is equal to the receiving threshold, i.e., P(r) = c · P(t)/(dT)α = RXth.

We then have that the transmission range of P(t) is dT = dδ/αdmax

1−δ/α . Note that d ≤ dT ≤ dmax, for any δ between 0 and α.

δ-PCS: A Class of Power Control Schemes

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,δ ∈ [0, α]

δ-PCS: A Class of Power Control Schemes

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How the transmission power changes as a function of the traffic distance d, under different δ-PCS

The transmission range δ-PCS that lies between d and dmax

Main Goal: identify a ”good” δ value such that the corresponding power control scheme yields performance improvement in network throughput, energy efficiency and fairness simultaneously

δ-PCS: A Class of Power Control Schemes

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Analysis of δ-PCS analyze the fairness behavior of δ-PCS,

the fairness for different traffic distance is closely related to the aggregate throughput

Assumptions Each source node is located independently and

uniformly in the Euclidean plane For each source, its destination is located at a

distance chosen independently and uniformly at random from [0, dmax].

N = 0 in our following derivation for simplicity

δ-PCS: A Class of Power Control Schemes

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Consider an on-going transmission from a node Xi to node Xj

For any other transmitting node Xk, k≠i, let Xk’ be the receiver.

In order for the transmission from Xi to Xj to be successful, we need SINRj to exceed SINRth.

We determine the value δ that minimizes E[1/SINRj]. We note that minimizing E[1/SINRj ] is only an

approximation for maximizing the aggregate throughput.

δ-PCS: A Class of Power Control Schemes

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Lemma 3.1:

The minimum of this equation is achieved at δOPT(dij)= 1/ (ln dmax − ln dij)−1

We can thus infer the following (1) This equation is a decreasing function of δ on

[−∞, δOPT], and an increasing function of δ on [δOPT,∞] (2) δOPT is an increasing function of dij

(3) There exist threshold distances d’, d’’ with δOPT(d’) = 0 and δOPT(d’’) = α

δ-PCS: A Class of Power Control Schemes

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Three observations ( 討論函數的增減性 ) Observation 1:

For 0 < dij ≤ d’, δOPT(dij) < 0, which implies that E[1/SINRj ] increases as δ increases from 0 to α

Thus, the throughput of the traffic pairs with 0 < dij ≤ d’decreases when δ increases from 0 to α

Observation 2: For d’<dij≤ d’’, 0 ≤ δOPT(dij) ≤ α, which implies that E[1/SINRj

] first decreases then increases when δ increases from 0 to α.

This indicates that the throughput of the traffic pairs with d’≤ dij ≤ d’’ first increases then decrease when δ increases from 0 to α.

Observation 3: For d’’< dij , δOPT(dij) > α, which implies that E[1/SINRj ]

decreases when δ increases from 0 to α. This indicates that the throughput of the traffic pairs with dij

> d’’ increases when δ increases from 0 to α.

Simulation Results18

Simulation model GloMoSim-2.03

Physical layer

Application layer CBR traffic model (pkt size: 512 bytes)

Parameter Value

Bandwidth 2Mbps

Receiving Threshold -64dBm

Carrier sensing threshold

-71dBm

Pmax 25dBm

dmax 250m

Carrier sensing range

550m

Simulation Results (cont’d)19

Topology and traffic Generate random topologies with 200 stationary

nodes distributed on a 2000 × 2000m2 area Select randomly located single-hop transmitter-

receiver pairs also referred to as traffic pairs

Select random traffic pairs from 0 to 250m Performance metrics

Aggregate and normalized throughput Energy efficiency (Mb/Joule) Throughput achieved in different destination

ranges

Simulation Results (cont’d)20

Random topologies with varying number of traffic pairs

Aggregate throughput under varying number of traffic pairs with fixed data rate of 1.0Mbps.

Normalized throughput under varying number of traffic pairs with fixed data rate of 1.0Mbps.

Simulation Results (cont’d)21

0-505-100100-150150-200200-250

Distance in m

1. The preference is slowly inversed when δ increases from 0 to 4, with 4-PCS showing a strong preference for long traffic pairs.

2. for destination range 100-150m, the achieved throughput first increases then decreases

3. for destination range 200-250m, the achieved throughput increases4. When δ is equal to 2 or 2.5, the achieved throughputs on each range

are close to the average, thus a fair allocation of the channel capacity is observed

Simulation Results (cont’d)22

Normalized bit-meter/sec measurement under varying number of traffic pairs

Data delivered per unit energy undervarying number of traffic pairs

Simulation Results (cont’d)23

Random topologies with varying data rate

Aggregate throughput under varying data rate. The total number of pairs is 30

Achieved throughput on different destination ranges (30 traffic pairs at data rate 600Kbps)

Simulation Results (cont’d)24

Normalized bit-meter/sec under varying data rate, where the total number of pairs is 30.

Data delivered per energy unit under varying data rate. The total number of pairs is 30.

Implementation Issues25

Power function implementation Within the RTS/CTS handshake protocol

the communicating nodes can estimate the channel gain. We propose to convert the distance variable of the power function into a gain variable.

RTS/CTS power level update In a mobile network the channel characteristics

change as the nodes move, therefore the transmission power levels have to be updated.

We propose to use a technique similar to the closed-loop power control used in CDMA cellular systems.

Conclusion And Future Work26

Propose δ-PCS a class of power control schemes for ad hoc

wireless networks, based on a novel transmission power function

Compared with IEEE 802.11 achieves up to 40% throughput increase improves energy efficiency by a factor of 3 shows better fairness with respect to the traffic

length distribution. Future work

plan to integrate our power control scheme within a resource efficient multi-hop routing protocols

Comments27

Experiment Discussion We should know what we want to find out

in this experiment or prove the hypothesis Analysis Experiment