Power Reservation-Based Admission Control Scheme for IEEE 802.16e OFDMA Systems

1. Power Reservation-Based Admission Control Scheme for IEEE 802.16e OFDMA Systems Wireless Communications and Networking Conference, 2007.WCNC 2007. IEEE Yu, Guanding; Zhang, Zhaoyang; Qin, Chi; Jia, Huiling; Huang, Aiping

2. Outline • Introduction • System Model • Resource Allocation Algorithm • Power Reservation-Based Admission Control • Simulation Results • Conclusion

3. 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 allocation

4. Two reasons for these channel reservation schemes are not competent in IEEE 802.16e • First, in WiMAX systems with OFDMA PHY, high spectrum utilization is achieved by efficient and flexible channel and power allocation • reserving a number of channels for handoff calls will potentially result in poor spectrum utilization • Second, there exists a fundamental tradeoff between bandwidth resource and power resource. • For a mobile station (MS) with a given channel condition and a fixed data rate requirement, its total power requirement decreases with the increasing amount of bandwidth allocated to it Requirement 1M/s 4.0 bit/s/Hz 1 MHz 2.0 bit/s/Hz 2 MHz 1 unit power per channel 0.5 unit power per channel

5. 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

6. System Model • Network Model • IEEE 802.16e cellular system consisting of 19 cells • the cell radius is set to 1Km • All the MSs are uniformly distributed throughout the 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

7. Traffic Model • Only real-time services with fixed data rate requirements are considered • which ranges uniformly between 250 Kbps and 700 Kbps • Both new calls and handoff calls arrive according to a Poisson process • Call duration is exponentially distributed with the mean of 120 seconds

8. 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

9. The resource allocation problem DR requirement > QPSK 3/4 QPSK 3/4 co-channel interference The number of subchannels required by useri QAM 64 QAM 16 The required transmit power on each subchannel N denote the total number of available subchannels P denote the maximum transmit power in the BS The required power from the BS to user M active calls Ridata rate requirement of the user is (1<= i<= M ) user’s AMC level is set to MCi DR(MCi): data rate per unit of MCi ηis the thermal noise f(MCi): SINR requirement Ii denotes the co-channel interference B0 denotes the bandwidth of each subchannel Gi denotes the channel gain of the link

10. The details of this algorithm

11. Example Initializes MCi = Lmax Next lower ACM level User 1 13.5M/s Total Bandwidth 10MHz 30.6-30/34-30=0.15 4.5 bit/s/Hz 4.0 bit/s/Hz 3 MHz 3.4 MHz 30 unit power 1.0 per channel 30.6 unit power 0.9 per channel Subchannel = 0.1 MHz User 2 9M/s 23-22/23-20=0.333 2 MHz 4.5 bit/s/Hz 2.3 MHz 4.0 bit/s/Hz 22 unit power 1.1 per channel 23 unit power 1 per channel 13.2-12/12-10=0.6 User 3 4.5M/s Next lower ACM level again 4.5 bit/s/Hz 1 MHz 4.0 bit/s/Hz 3.0 bit/s/Hz 1.2 MHz 1.5 MHz 12 unit power 1.2 per channel 13.2 unit power 1.1 per channel 0.8 unit power

12. Power Reservation-Based Admission Control P’ and P’’ respectively denote the total power requirements as N subchannels and subchannels are occupied in all • 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 QoS requirements and outage may happen because of resource insufficiency • Overall reserved power in the BS

13. Determination of the Reservation Factors K and β • in view of the tradeoff between handoff dropping rate and new call blocking rate • we determine the values of the reservation factors based on the optimization of the grade of service(GoS) performance

14. 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

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

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

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

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

19. Approximate Solution vs. Optimal Solution

20. 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.

21. Thank you!!