An Adaptive Energy Saving Mechanism in the Wireless Packet Access Network

Mugen Peng and Wenbo Wang

Wireless Signal Processing & Network LabBeijing University of Posts and Telecommunications

< IEEE WCNC 2008 >

Outline

• Introduction

• Related work– ESM

• IEEE 802.16e PSM

• EESM

• Adaptive Energy Saving Mechanism (AESM)

• Performance Evaluation

• Conclusion

Introduction

• The energy saving mechanism is very important for supporting the mobility and extending the battery life in the wireless packet access network.

Sleep Mode

Type 1 …

Type 2 …

Type 3 …

Normal Operation Sleep period Listen period

Introduction

• Energy Saving Mechanism (ESM) scheme is popular and researched deeply. Furthermore, it was accepted and standardized in IEEE 802.16e PSC of Type I standard.– [3] Yang Xiao, “Energy Saving Mechanism in the IEEE 802.16e

Wireless MAN,” IEEE Communications Letters, Vol. 9, No. 7, July 2005.

• According to the definition in the standards, an adaptive energy saving mechanism (AESM) for enhancing the standardized energy saving mechanism (ESM) is proposed, in which the sleep interval is determined by both the system load and traffic properties.

Related work

• ESM in IEEE 802.16e PSC of Type I.– Initial Sleep Interval (Tmin)

– Final Sleep Interval (Tmax)

– Listening Interval (L)

SWi+1 = 2 * SWi

Related work

• Enhanced ESM for IEEE 802.16e Type I.– Junfeng Xiao, “An Enhanced Energy Saving Mechanism in IEEE

802.16e,” IEEE GLOBECOM, 2006.

– A MSS uses half of the last sleep interval when it exits from the previous sleep-mode operation as the initial sleep interval in the next sleep-mode operation.

• The main idea of EESM is to reduce the listening operation.

SWi = 1 、 2 、 4 、 8 、 16 、 32 、64 …

Adaptive Energy Saving Mechanism (AESM)

• The proposed AESM proposal, the sleep interval is adaptive to the system load and the traffic properties, in which the initial sleep interval and the period sleep interval is not in subjection with the binary exponential distribution.

SWi+1 = γ * SWi

Adaptive Energy Saving Mechanism (AESM)

• The non-real time services are further categories as the heavy-load and light-load according to the current system load (η) , which is executed in the BS.– Light-load ： η ＜ ηth

– Heavy-load ： η ＞ ηth

SWi+1 = γ * SWi

Adaptive Energy Saving Mechanism (AESM)

• The parameter γ is bigger than 2 if the system load is light and the serving traffic is non-real time.– Light-load ： η ＜ ηth

– γ = min { 2 (ηth /η) , MAX(4) }

• Otherwise, the parameter γ is not more than 2 if the system load is heavy or the traffic arrival is similar with the real-time service.– Heavy-load ： η ＞ ηth

– γ = max { 2 (ηth /η) , MIN(1) }

SWi+1 = γ * SWi

Adaptive Energy Saving Mechanism (AESM)

•

Performance Evaluation

• Simulator : OPNET

• L : 1 frame

• Tmin : 1 frame

• Tlim : 16 frames

• Tmax : 1024 frames

• ES : 1 unit per frame

• EL : 10 units per frame

Performance Evaluation

Performance of AESM in heavy load scenario

Performance Evaluation

Performance of AESM in light load scenario

Conclusion

• The sleep interval is adaptive to the system load and the traffic properties in the proposed AESM proposal.

• AESM can have a better energy saving efficiency than the ESM, especially when the system load is light.

The End

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