1. Multimedia Support for Wireless W-CDMA with Dynamic Spreading
JU WANG, MEHMET ALI ELICIN and JONATHAN C.L. LIU
CNT 6885: DISTRIBUTED MULTIMEDIA SYSTEMS

2. Overview of Presentation
1. Introduction
2. Performance guaranteed call processing
3. Dynamic scheduling for multimedia integration
4. Conclusion

3. 2. Performance guarantee
Introduction
Data
Voice
Video
More number of people are interacting with
various different forms of multimedia
Wireless networks are increasing ever present from our homes to right inside airplanes.
It is integral that these wireless networks support all the emerging multimedia over this increasing wireless network.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

4. 2. Performance guarantee
Aim of the Paper
1. This paper investigates effective protocol design with dynamic spreading factors.
2. It then proposes a middle-ware solution to monitor the network load switch spreading factors
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

5. 2. Performance guarantee
Experiments performed to find how spreading factors and number of active users affect BER.
Analysis shows increasing the spreading factor decreases the BER for given number of users.
Manufacturers are e considering to bring in the dynamic capability of changing spreading factors.
SF: 64
BER:0.0008
SF: 96
BER:
62.5 % Reduction
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

6. 2. Performance guarantee1
Hardware solution did not accomplish goals 2
Novel middleware solution required
The middleware approach will monitor the traffic load
It will switch the spreading factor dynamically based on traffic 3
Protocol designed on IS-95 architecture with backward compatibility.
This scheme reduces the admission processing time by 22% and 27 %
By using multiple channel access update time component reduced by 48% and 58%
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

7. 2. Performance guarantee
Performance guaranteed call processing
Goal of admission control protocol is to support as many users as possible while still satisfying BER requirements
While accepting new calls, system will dynamically adjust spreading factors
This scheme eliminates overhead caused by terminating and reopening new connection
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

8. Admission Protocol in a mobile station1
App sends OPEN request to base station
Along with request is type of traffic and desired data rate
4 traffic types: VOICE, AUDIO, VIDEO, DATA 2
Base station receives the request and checks if request can be satisfied
Satisfaction determined on the basis of BER requirement and min data rate requirement
The min SF is calculated for that BER and then data rate is calculated 3
Decision is made by comparing calculated data rate and requested data rate
If request is denied mobile is allowed to retry after random time period
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

9. Admission Protocol in a Base station1
After new connection Protocol performs quality check for all users.
For each connection system calculates expected average BER for increased number of users
If BER is found to be high increase SF and check data rates. 2
No existing connections requires an update then destination mobile is informed of OPEN and ACK is send
If update is required UPDATE is sent and all reply with ACK 3
This allows all to adjust their spreading factors dynamically
Flexibility to switch traffic after connection made with UPDATE message.
Flexibility
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

10. A performance guaranteed system
Fixed spreading factors schemes did not guarantee the overall performance among the users.
For connections less than 5 BER was acceptable
In this proposed protocol the average BER was always below
Even with increased number of users threshold was always maintained.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

11. Analysis of Performance.
With first connection SF is 32 , BER IS and BER increases dramatically with new connections.
For 5 connections BER is 1.5 · 10-3,
At 5 constant connections with incoming connection protocol senses BER degrades below threshold , SF updated to 64 for 5 existing connections
Base Station sends UPDATE and waits for ACK from all.
After all ACK’s BER drops to 7.9 · 10-4 , allowing the new connection.
Now BER increases with new connection but still below threshold. At 6 conns and SF 64 , BER is 5·10-3
With new connection SF does not support and the steps above are repeated.
At 10 and 14 connections SF is adjusted again.
BER drops to bottom when adjustment is going on.
Improvement in BER becomes significant with increased Spreading Factor.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

12. 2. Performance guarantee
Design Tradeoffs
Even though the experimental results were promising the proposed admission control introduced two design tradeoffs.
Longer processing time at base station
Contention time for all mobile-station to acknowledge changing spreading factors
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

13. 2. Performance guarantee
1. Processing Time at Base station
Tm : Time to send request from mobile to base station using access channel
Tp : Base station processing time
Tp : Time of notifying destination, and receiving ACK from destination
Tupdate : Time for broadcasting UPDATE message, and receiving ACKs
Ta : Time for sending ACK to requesting mobile using paging channel
Ts : Time when mobile updates channel parameters and becomes ready to transmit
Mostly the process time increases at an angle because SF is large enough for existing connections.
Peaks are observed when new connections cause the base station to recompute and distribute parameters to maintain the performance.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

14. Improved schemes for reducing Tp
1. Further improvement possible in reducing admission processing time.
2. Connections belonging to same traffic type usually change to same spreading factor
3. BER not affected by type of traffic
4. All external signals from different traffic treated as noise
5. Connection with same BER use same SF
Protocol further improved by calculating 1 spreading factor for one type of traffic.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

15. 2. Contention time acknowledgment
Second Tradeoff is Tupdate component.
Tradeoff occurs when existing connections require a change of spreading factor.
All connections send ACK to base. These are all done common channel. This can cause collisions thus Tend is increased.
Tend dominated by by Tp and Tupdate .
Tupdate is zero when no update is required and Tend grows slowly.
When update is required Tupdate grows exponentially. This is due to ACK collisions.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

16. Improved schemes for updating Tupdate
1. A collision resolution protocol is necessary when multiple users are sending their ACK’s
2. UPDATE delays are reduced by decreasing contention period.
3. Increasing the number of access channels is the approach followed.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

17. 2. Performance guarantee
Analysis of Improved schemes for updating Tupdate
Base Station distributes users equally among access channels
A hash function is used with the mobile stations serial Number to equally distribute the users to the channels.
With two access channels Tupdate reduced 49 % independently of the number of connections.
With four access channels Tupdate reduced 48 to 58 %
However increasing the number of channels saw a tradeoff
The BER suffers with increased number of channels during the update phase.
For 4 access channels higher SF 128 or 160 is recommended
For 2 access channels SF of 32,63,96 are advisable
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

18. 2. Performance guarantee
Dynamic scheduling for Multimedia Integration
1. Dynamic scheduling algorithm proposed for systems integration of multimedia traffic.
2. Performance metric here is Ts which is the total turn around time to fulfill all the data traffics.
3. Retransmission will occur due to high packet loss due to a fixed SF.
4. A Non retransmission policy is beneficial with the transmission occurring under acceptable BER.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

19. 2. Performance guarantee
FSF Scheduling 1
Contact Base Station for current traffic load 2
Select Request r(i), check if addition of request satisfies BER requirement. 3
If BER exceeds any existing or new connection then this r(i) is not accepted. 4
Repeat cycle for other traffics otherwise wait for next time frame.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

20. Observations for FSF Algorithm
For SF = 64 Ts = 12s to 48s for diff k
For SF =128 Ts becomes 36s for 22 voice connections and one can be sent in 96 second. No after 25 users.
For SF = 260 Ts equals 15s for less than 20 users. Increase of Ts caused by decrease of data rate which becomes 25% less than SF = After k=34 BER doesn’t allow any DATA.
In FSF system throughput suffers to satisfy BER of DATA communication.
Under Light network loads longer SF(128,160) actually generate longer turn-around time than shorter SF
However longer SF have the capability to support more concurrent voice streams.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

21. Dynamic Scheduling to increase Ts1
Find min SF such that BER[SFv][k + Na] < RBER[1] and BER[SFa][k + Na] < RBER[4]. 2
If both SFv and SFa are found:
All audio requests are assigned with spreading factor of SFa.
Go to step (8) to update audio traffics. 3
If SFv cannot be found: 4
Use SFv = 160 as the voice spreading factor. 5
Locate the maximum audio traffic number N-a such that
BER[SFv][k + N]-< RBER[1]. 6
Find the minimum SFa that satisfies BER[SFa][k + N-A] < RBER[4]. 7
Decide which subset of audio traffics will be chosen if N-a < Na. This should be based on a fair strategy so that there is equal chance for all traffics. 8
For each of the selected audio traffics i:Calculate Tf as the length of time frame,
Reduce their remaining data amount AUDIO[i]− = Tf · 4.096/SFa. 9
Update array AUDIO[ ] and Na by deleting finished requests.
Audio
Image
FTP
Low BER
High BER
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

22. Observations for DSF Scheduling
Under Low load BER of satisfied with SF=64 and data rate 64 Kbps within 6 seconds.
For 4<k<7 SF=64 still provides the best time at 12 seconds
K=8 ,SF = 128 best at 12s. With k increasing k range
30 < Ts< 75 seconds
K=17 ,SF = 160 best at 12s. After k=10 SF = 64, 96 unable to support.
Dynamically changing Spreading Factor based on different system load can significantly improve system throughput. Example 8 background voice connections Ts reduced from 24 to % reduction.
Voice Connection guarantee with data traffic served no starvation in high load
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion

23. 2. Performance guarantee
Conclusion 1
New middleware solution supports different data types with different BER requirements. 2
Different data classes with guaranteed quality and maximizes number of users supported 3
Dynamic changing of SF to accommodate different number of users 4
DSF shows significant improvement in BER over fixed SF CDMA 5
Scheduling Algorithm for balanced support of different data types.
1. Introduction
2. Performance guarantee
3. Dynamic scheduling
4. Conclusion