Radio Resource Management in Wireless Mobile Networks

1. BS RNC Radio Resource Management in Wireless Mobile Networks Emre A. Yavuz, Ph.D. candidate Supervised by : Dr. Victor C.M. Leung Communications Lab., Elec. & Comp. Eng. University of British Columbia, UBC emrey@ece.ubc.ca

2. Motivation • To build mathematical models for Radio Resource Management and to simulate the resource allocation process • in order to look for optimum algorithms and • develop better admission and congestion control procedures. • Extra capacity that is provided to the network will result in higher end-user average bit rates, low delays and BER and lower blocking/dropping ratios. • Radio Resource Management will be the major differentiator between the overall QoS provisioning offered by different operators’ networks.

3. Agenda • What makes Wireless Mobile Networks different ? • The Radio Resource Management Methods • Resource Usage in CDMA Networks • Admission Control & Its Logical Dependencies • Congestion Control & Actions to be Taken • Traffic Types, Adaptation of Quality Indicators & Cost • Resource Management based on Utility Function Approach • Pricing Frameworks • Future Research

4. What Makes Wireless Mobile Networks Different ? • The probabilistic behaviour of the wireless channel (shadow fading, rayleigh fading, path loss) as opposed to almost deterministic behavior of the wired lines. • Soft Capacity (changes with other & own cell interference) • User - mobility (handovers, shadowing effects etc.) • Call Dropping Probability constraint besides Call Blocking Probability constraint. • Cell Coverage guarantee for each service.

5. The Radio Resource Management Methods • Admission Control • Handles new incoming traffic (new connections, handover decisions and bearer modifications) • Congestion Control • Manages the system when the load exceeds threshold • Traffic Scheduling (mostly for non-real time traffic) • Handles packet data users to initiate the packet transmissions and guarantee QoS through bit rate, BER and delay adjustments • Power Control - to maintain radio link quality

6. Pi ri BS gi*Pi RNC Resource Usage in CDMA • Uplink (Interference Limited) • Downlink (Power Limited)

7. Admission Control & Its Logical Dependencies • Estimate the load and fills the system up to the limit without having impact on coverage and quality of existing connections. • Separate admission for UL and DL. • Uses load info from Congestion Control, Traffic Scheduling, Power Control and Handover Control. • Derives the transmission bit rate, target BER, processing gain, initial link quality parameters. • Initiates the forced call release and interfrequency or intersystem handover.

8. Congestion Control & Actions to be Taken • Optimize the capacity of a cell and prevent overloading by measuring application parameters from planning and UL & DL interference. • Congestion Control takes care of the network to prevent overloading and to preserve the stability. • Consider load control actions on the network traffic. • Lower bit rates of the rate-adaptive traffic. • Lower SIR target based on the type of application. • Interact with TS and throttle back packet data traffic. • Force interfrequency or intersystem handover. • Drop calls in a controlled manner.

9. Traffic Types, Adaptation of Quality Indicators & Load • Quality of Service (QoS) Classes (Conversational, Streaming, Interactive and Background) • Main concern: Real-time and Non-real-time Traffic. (More compatible with scheduling when compared toreal-time traffic) • Regrouping the traffic • Adaptive rate and adaptive signal quality requirements. • Adaptive rate and fixed signal requirements. • Fixed rate and adaptive signal requirements. • Fixed rate and fixed signal requirements.

10. Resource Management based on Utility Function Approach • Objective: To maximize aggregate utility subject to • Available transmission power and spreading codes (at the base station) • Allowed interference (at the mobile stations) • A solution based on a pricing framework, where prices per unit power, code or load are announced by the network (RNC) in order • the users to maximize their net utilities while • the system tries to maximize the total sum of utilities and • the network tries to maximize its revenue.

11. Three Cases of Optimization • From User point of view • From System point of view • From Network point of view where λ is the price that is announced by RNC MAX where ki is a coefficient chosen for QoS or price-based class

12. How should a Utility Function for a SIR Adaptive Application be ? U(SIRi)=1/(1+exp(-(a*(SIRi -b))))

13. Cost Calculation based on Pricing Frameworks • Cost can be based on a shadow price and a constraint related load parameters like rate, BER, power etc. • Based on the rate and BER of the application Cost = Shadow price * rate * SIR • Based on the application power Cost = Shadow price * power • Shadow price will be announced by RNC for each period and be adjusted dynamically based on the network load.

14. How does the Derivative of the Utility Function Look Like ?

15. How does the Net Utility Function Look Like ?

16. How does the Radio Network Control make the Upgrade/Downgrade Decision ?

17. And What About Power ?

18. Future Research • What comes next ? To look into issues like; • Behavior of the uplink/downlink load from the channel efficiency point of view • Changes in the quality of connection with the changing mobile users’ distance from the Base station (near-far fairness). • Behavior of the rate during the whole life of a connection. • Behavior of the signal quality (BER) during the whole life of a connection. • Call Dropping and Blocking Probabilities. • Possible Applications of Adaptive Learning Techniques.

19. THANKS !