Power Reservation-Based Admission Control Scheme for

IEEE 802.16e OFDMA Systems

Wireless Communications and Networking Conference, 2007.WCNC 2007. IEEEYu, Guanding; Zhang, Zhaoyang; Qin, Chi; Jia, Huiling;

Huang, Aiping

Outline

Introduction System Model Resource Allocation Algorithm Power Reservation-Based Admission

Control Simulation Results Conclusion

Introduction

In IEEE 802.16e MSs may change their serving cells several times handoff droppings

Call admission control (CAC)limiting the amount of radio resource a

llocation

Two reasons for these channel reservation schemes are not competent in IEEE 802.16e First, in WiMAX systems with OFDMA PHY, high spect

rum utilization is achieved by efficient and flexible channel and power allocation reserving a number of channels for handoff calls will p

otentially result in poor spectrum utilization Second, there exists a fundamental tradeoff between b

andwidth resource and power resource. For a mobile station (MS) with a given channel conditi

on and a fixed data rate requirement, its total power requirement decreases with the increasing amount of bandwidth allocated to it

1 MHz2 MHz

4.0 bit/s/Hz

1 unit powerper channel

2.0 bit/s/Hz

0.5 unit powerper channel

Requirement1M/s

Motivation

Reduce the co-channel interference to the neighbor cells & Improve the downlink system capacity to minimize the overall transmit power of

each base station (BS) by making full use of the total available bandwidth

The transmit power of the BS serves as indicator of the traffic load A novel admission control scheme based on

reservation of the power resource in each BS

System Model

Network Model IEEE 802.16e cellular system consisting of 1

9 cells• the cell radius is set to 1Km• All the MSs are uniformly distributed throughout th

e whole system topology• The frequency reuse factor of 3 is adopted• The center frequency ( cf ) is 3.5GHz• The total bandwidth in each cell ( tB ) is 10MHz• The technique of adaptive modulation and coding

(AMC) is used

Traffic Model

Only real-time services with fixed data rate requirements are considered which ranges uniformly between 250

Kbps and 700 KbpsBoth new calls and handoff calls arrive

according to a Poisson processCall duration is exponentially

distributed with the mean of 120 seconds

Resource Allocation Algorithm

For simplicity, only downlink real-time traffic with strict data rate requirement is considered

The optimization objective of this resource allocation problem is to minimize the overall transmit power of the BS while guarantee the data rate requirements of all users

The resource allocation problem

QAM 64

DR requirement

QPSK 3/4QPSK 3/4

>

The number of subchannels required by user

i

The required transmit power on each subchannel

The required power from the BS to user

N denote the total number of available subchannelsP denote the maximum transmit power in the BSM active calls

Ri data rate requirement of the user is (1<= i<= M )user’s AMC level is set to MCi

DR(MCi): data rate per unit of MCif(MCi): SINR requirementB0 denotes the bandwidth of each subchannel

ηis the thermal noiseIi denotes the co-channel interferenceGi denotes the channel gain of the link

QAM 16

co-channel interference

The details of this algorithm

Example

3 MHz

2 MHz

4.5 bit/s/Hz

30 unit power1.0 per channel

4.5 bit/s/Hz

22 unit power1.1 per channel

TotalBandwidth10MHz

1 MHz 4.5 bit/s/Hz

12 unit power1.2 per channel

Initializes MCi = Lmax Next lower ACM level

3.4 MHz

2.3 MHz

4.0 bit/s/Hz

30.6 unit power0.9 per channel

4.0 bit/s/Hz

23 unit power1 per channel

1.2 MHz 4.0 bit/s/Hz

13.2 unit power1.1 per channel

User 1

User 2

User 3

30.6-30/34-30=0.15

Subchannel = 0.1 MHz 23-22/23-20=0.333

13.2-12/12-10=0.6Next lower ACM level again

1.5 MHz 3.0 bit/s/Hz

0.8 unit power

13.5M/s

9M/s

4.5M/s

Power Reservation-Based Admission Control two kinds of handoffs

Inter-cell handoff• Dropping occurs

• no sufficient resource for the incoming handoff request in the target cell

Intra-cell handoff • resource reassignment to maintain the Qo

S requirements and outage may happen because of resource insufficiency

Overall reserved power in the BS

P’ and P’’ respectively denote the total power requirements as N subchannels and

subchannels are occupied in all

Determination of the Reservation Factors K and β

in view of the tradeoff between handoff dropping rate and new call blocking ratewe determine the values of the reserv

ation factors based on the optimization of the grade of service(GoS) performance

Simulation Results

the total number of subchannels in each cell is set to 150

the overall transmit power of each BS is restricted to 100W

the thermal noise is -90dBm The random walk mobility model is adopted

to each MS, with an average velocity of 120km/h

The traffic load is configuredρset to 0.6, 0.65, 0.7

Forced termination probability of inter-cell handoff and new call blocking probability versus K

GoS versus K at traffic load 0.6, 0.65 and 0.7 (β=0)

Forced termination probability of intra-cell handoff and new call blocking probability versus β

GoS versus β at traffic load 0.6, 0.65 and 0.7 (K=0)

Approximate Solution vs. Optimal Solution

Conclusion

A new call admission control strategy based on power reservation

In order to balance the handoff call dropping rate and new call blocking rate, we introduce an optimization model to find the optimal and based on GoS metric

Simulation results show that the suboptimal solution is close to the optimal solution.

Thank you!!