1. Optimal Sequence Allocation and Multi-rate CDMA Systems
Krishna Kiran Mukkavilli, Sridhar Rajagopal, Tarik Muharemovic, Vikram Kanodia

2. Motivation 3rd Generation Comm. Systems Multi-Rate Detection
Multimedia(Data, Voice, Video)
Multiple Rate Comm.
Multi-Rate Detection
Users entering/leaving the system
Optimal Sequence Allocation to achieve Capacity.

3. Outline Conventional CDMA multiuser system
Discussion of multirate systems
Methods of multirate CDMA access
Performance of multiuser detectors
Interference avoidance
Application to variable number of users

4. Multi-rate CDMA systems
Multi code access (MC)
Give more Codes
Variable spreading length (VSL)
Change Spreading Length
Variable chip rate(VCR)
Change Chip Frequency

5. Multi code (MC) Higher Rate users assigned more codes
Data transmitted in parallel
“Virtual User” Concept
Same Spreading for all users.

6. Multi Code
Code 1
Code 2
User Rate R
User Rate 2R T
Code 3

7. Variable spreading length(VSL)
Higher Rate Users allocated smaller spreading lengths
For detection, rate of slowest user is considered.
More bits of higher rate users detected per bit of lower rate users
For detection, put 0’s

8. Variable Spreading Length
User Rate R T
User Rate 2R 2T

9. Variable Chip Rate(VCR)
User allocated different chip rates
Larger Bandwidth required
Requires more RF hardware
Oscillators
Not practical for implementation

10. Variable Chip Rate
User Rate R T
User Rate 2R 2T

11. Implementation Aspects
VSL and VCR have a sparse correlation matrix
VCR requires larger bandwidth
MC requires more codes
VSL proposed for next generation systems

12. Multiuser Detectors Maximum likelihood detector (MLD)
Conventional single user detector (SUD)
MMSE detector
Decorrelating detector

13. Simulations Four users Random Codes Spread length 32 for low rate user
2 users at rate R
2 users at rate 2R
Random Codes
Spread length 32 for low rate user
10000 bits
Channels
AWGN
Fading - Jakes Model

14. Investigate... Performance of multiuser detectors
Near far problem in detectors
Performance of high rate and low rate users in MC and VSL systems
All users with equal power
Users with unequal power

15. BER comparison for different detectors in multi code system 10 MLD 10
MLD
MMSE
Decorrelator
Single user detector -1 10 -2
BER 10 -3 10 -4 10 2 3 4 5 6 7 8 9 10 11 12
SNR

16. BER comparison for detectors with unequal powers 10 MLD Equal Power 10
MLD Equal Power
MLD Unequal Power
SUD Equal Power
SUD Unequal Power -1 10 -2
BER 10 -3 10 -4 10 2 3 4 5 6 7 8 9 10 11 12
SNR

17. Comparison of Different Rate Users in MC and VSL 10 High rate MC 10
High rate MC
High rate VSL
Low rate MC
Low rate VSL -1 10 -2
BER 10 -3 10 -4 10 2 3 4 5 6 7 8 9 10 11 12
SNR

18. VSL System Virtual user from high rate user High rate user
lower spreading length
lower interference (other virtual users are orthogonal)
High rate user
interference from same number of virtual users with lower spread length

19. Variable Spreading Length
User Rate R T
User Rate 2R 2T

20. Near Far effect for Different Rate Users in MC and VSL 10 Low rate MC 10
Low rate MC
Low rate VSL
High rate MC
High rate VSL -1 10 -2
BER 10 -3 10 -4 10 2 3 4 5 6 7 8 9 10 11 12
SNR

21. Results
Multi Code
High rate and low rate users have same performance (both BER and NFR)
VSL
Low rate users have bad BER and NFR
High rate users’ performance is similar to multicode access system.

22. Interference Avoidance in Wireless Multiuser Systems
Interference Avoidance  send where there is less noise
Fixed modulation - traditional approach
TDMA
FDMA
CDMA
CWMA
Future wireless systems - dynamically adapt to the changing interference pattern

23. Preliminaries for Multiuser Systems
(class notes pg. 5-12)
System model:
Capacity region:  X1 XM N Y R1 R2

24. Total Square Correlation vs Iteration Number 9.5
Optimum Lower Bound 9
8.5
Total Square Correlation 8
7.5 7 1
1.5 2
2.5 3
3.5 4
4.5 5
5.5 6
Iteration Number

25. Preliminaries for Multiuser Systems
(class notes pg. 5-12)
Sum Capacity:
W : channel bandwidth
Pi : power of i-th user
N0 : noise power spectrum

26. Multiuser Spread Spectrum Systems
System model Y sM  X1 XM N  s1

27. Multiuser Spread Spectrum Systems
Sum Capacity:
Optimum sequences maximize Sum Capacity
Total Square Correlation (TSC):
Max. Sum Capacity  Min. TSC

28. Eigen-Algorithm Iterative reduction of TSC
User k updates his spreading sequence
Rayleigh quotient
Choose sk to be eigenvector with smallest eigenvalue

29. Performance comparison of optimal codes with random codes 1010
Random Code Allocation
Optimal Code Allocation -1 10 -2
BER 10 -3 10 -4 10 8 10 12 14 16 18 20 22
SNR

30. BER Performance with an Incoming User 10 Random Code to new user 10
Random Code to new user
Iteration for new user only
Optimal Code Allocation -1 10
BER -2 10 -3 10 6 7 8 9 10 11 12 13 14 15 16
SNR

31. Conclusions Significant improvement in performance with optimal codes
Iterative algorithm compatible with user dynamics
Good sub-optimal schemes for user addition
Can be combined with the multi-rate schemes