Presented by: Ahmed Abdelhalim

1. Fair Resource Allocation with GuaranteedStatistical QoS for Multimedia Trafficin Wideband CDMA Cellular NetworkLiang Xu, Member, IEEE, Xuemin (Sherman) Shen, Senior Member, IEEE, andJon W. Mark, Fellow, IEEE Presented by: Ahmed Abdelhalim

2. Motivation The need of a Dynamic Fair Resource Allocation Scheme for Wideband CDMA taking into account: • The characteristics of channel fading • Intercell Interference

3. Dynamic Resource Allocation Dynamically vary the resource shares of applications according to: • Variation of traffic load • Channel Conditions Why? • To achieve efficient resource utilization • Increase network throughput

4. Problem • We have to ensure fairness while efficiently supporting QoS for multimedia traffic in Wireless networks. It is a tradeoff between wireless resourceefficiency and level of satisfaction among users

5. Conventional Time-scheduling Approach • Used in based and hybrid time-division/code-division multiple access (TD/CDMA)-based wireless networks • Requires high complexity due to intensive computation for the virtual time of each packet

6. Opportunistic Scheduling Approach • Allocates more bandwidth to MSs with good channels conditions Adv. It takes into account the channel fading conditions Dis. Lacks short-term fairness

7. A Generalized Processor Sharing Approach (GPS) • Allocates the resources according to weights assigned to the users. • The user rates are optimized for each scheduling period. • It guarantees the required minimum channel rates and adapts to the changes in channel conditions.

8. Proposed Work • a dynamic fair resource allocation scheme which efficiently support both real-time and non-real-time (multimedia) traffic with guaranteed statistical quality of service (QoS) in the uplink of a wideband code division multiple access (CDMA) cellular network. • The Scheme uses GPS to allocate channel resources taking into account the characteristic of channel fading and intercell interference

9. System Model Direct Sequence code division multiple access (DS-CDMA) • A data signal at the point of transmission is spread over a wider frequency spectrum according to the Spreading Factor • This is achieved by the MODULU-2 addition of Pseudorandom sequences to each data bit.

10. Rate-Scheduled DS-CDMA System mechanism

11. The Mechanism • Each MS generates a sequence of packets which enter a buffer after error control coding. • The packetized information sequence is then converted to a DS-CDMA signal and transmitted over the wireless channel to the base station • The BS uses a single-user Rake receiver to detect the signal from each MS. • The channel rate is dynamically allocated by the rate scheduler at the BS. • The spreading factor is adjusted according to the scheduled channel rate.

12. The Mechanism (cont.) • An SIR threshold corresponding to the target BER and the allocated channel rate is set at the receiver side. • When a new channel rate is scheduled, the SIR threshold is adjusted accordingly. • The home BS measures the received SIR and compares it with the SIR threshold. • When the actual SIR is lower (higher) than the threshold, a feedback control signal is sent to the transmitter to increase (decrease) the transmission power.

13. Channel and Traffic Models • Multi-path Fading Channel Pij = PTi rij -µ10€ij/10Xij Where: Pij :The received power at the jth BS PTi: Transmitted power of mobile i rij: the distance between the ith mobile and the jth BS µ :The loss exponent €ij: Gaussian random variable with zero mean Xij: characterizes the multipath fading between MSi and BSj

14. Traffic Model and QoS Requirements • The GPS discipline is applied in resource allocation for both real-time and non-real-time traffic. • The bandwidth requirements of all the flows are characterized by positive real numbers Ø1; Ø2; . . . ; ØN. • GPS fairness is achieved when the following inequality holds: Si(t1,t2)/Sj(t1,t2) ≥ Ø1/Ø2 Where Si(t1,t2): The amount of service received by the flow i in an interval (t1,t2)

15. Resource Allocation for Real-Time Traffic • Real-time traffic is scheduled before non-real-time traffic in each scheduling period • The resource allocation is carried out jointly via fair scheduling and admission control • The admission control assigns fixed weights to real-time traffic so that the required statistical delay bounds can be guaranteed

16. The Delay Bound • Each traffic source is shaped by a Leaky-Bucket regulator. i.e. Permits are generated at a fixed rate Packets are only released in the network when a permit is available • It is specified by a unique 5-tuple(Rm,i, σi, Di, Li) Where ρi: Permits rate Rm,i: constraint on the peak rate σ i: token buffer size Di: Required delay bound Li: losses due to transmission errors and excessive queuing delay • The QoS requirement is: P{τi (t) > Di } < Li where τi (t) is the actual delay for user I traffic arrived at time t

17. Static-weight code division GPS Scheme (SW-CDGPS) • The scheduler checks the total bandwidths requests from all MSs. • If it doesn’t exceed the channel capacity then each user is granted the requested BW. Otherwise the resource allocation vector (S1, S2 ,…….,Sn) is computed iteratively • Remaining capacity = channel capacity – Total BWs granted in the previous iteration • A fair share of the remaining capacity is calculated for each MS whose requested bandwidth has not been granted, according to its GPS weight

18. SW-CDGPS (cont.) • For the user whose requested bandwidth is less than its fair share of the remaining capacity computed in any iteration, its request will be fully granted; otherwise, the user’s Sv;i will be determined in a later iteration. • In the final iteration, each remaining MS will be given a fair share of the remaining capacity, but no more than its requested bandwidth.

19. Fairness Indes • For non-real-time traffic we define the Fairness index Fim Fim =|Si(t1,t2)/Ød,i - Sm(t1,t2)/ Ød,m| Si(t1,t2)/ Ød,i • The fairness index indicates the difference between the services (normalized by weights) received by the two MSs. • A Fairness bound Ø is guaranteed with probability Θ P{Fim > Ø} < Θ

20. Dynamic-weight code division GPS Scheme (DW-CDGPS) • For non-real-time traffic without stringent delay requirements, throughput can be made beneficial by dynamically adjusting the assigned weights according to channel conditions. • The amount of change in the variable weight possible per operation varies directly with the parameter Ψ • The larger the Ψ the looser the statistical bound can be guaranteed

21. Simulation • The target cell and its 18 neighboring cells in the first and second tiers are simulated • MSs are uniformly distributed in the service area. • Each Rayleigh fading channel with a maximum Doppler shift of 5Hz is generated using the Jake’s simulator

22. Hexagonal layout of cells

23. Performance Parameters: • Delay • Throughput • GPS Fairness

24. Simulation 1 • each cell has 12 homogeneous greedy data users. • Three cases, where Ψ=1; 10; 100,respectively, are simulated for the DW-CDGPS scheme, compared to the SW-CDGPS scheme with static weight. • The fairness index Fim is measured once every 20 slots in the simulation run for a total of 30,000 slots

25. Results 1

26. Comments • It can be seen that the statistical fairness bound can be regulated effectively by adjusting Ψ • When Ψ=0 the scheme reduces to the static weight scheduling scheme

27. Simulation 2 • 12 homogeneous Poisson data traffic flows are simulated • delay and throughput performances of users in cell 0 are compared. • For theDW-CDGPS, Ψ is set to be 100, corresponding to a largefairness bound • The traffic load is defined to be the sum of average arrival rates of all data flows. The • Throughput and traffic load are normalized by the maximal achievable throughput under SW-CDGPS when traffic load is high.

28. Results

29. Comments • It is shown that the DW-CDGPS scheme can improve the maximal uplink throughput significantly compared to the SW-CDGPS scheme • The throughput gain is seen only when traffic load is high since when the traffic load is low, the throughput equals to the total traffic arrival rate.

30. Results

31. Comments • It can be seen that, when the traffic load is high (around 1), the average delay can be reduced up to 70 percent, by DW-CDGPS as compared to the SW-CDGPS. • This implies that the short-term unfairness introduced by the DW-CDGPS can actually benefit the delay performance in the uplink when traffic load is high due to a high throughput that can be achieve • When traffic load is low, the delay performance can still be improved slightly

32. Conclusions • An efficient dynamic fair resource allocation scheme has been proposed for supporting multimedia traffic in the uplink of wideband CDMA cellular networks with QoS satisfaction. • The proposed scheme guarantees a statistical delay bound for real-time traffic and a statistical fairness bound for non-real-time users • The proposed scheme allows for a flexible trade-off between the generalized processor sharing (GPS) fairness and efficiency in resource allocation and is an effective way to maximize the radio resource utilization under the fairness and QoS constraints.