Sushanth internet 4g discussion semianr - 4G.ppt

4g wireless technology

1. 4G-Wireless Cellular
Communications
M.SushanthBabu
Associate Prof., Dept. of ECE
VCEW, Warangal

2. Agenda
•Introduction
•3G
•W-CDMA
•HSPA
•HSPA +
•MIMO Wireless system
•Cooperative Communication

3. Text
data
Voice
Dominant services
Required data rate
Requirement for short delay
Video
services
File
transfer
Game
VerystrongFEC,
e.g.TurboCodes,
canbeapplied.
Target services
Problem:
How to support video services with limited frequency resources?
Sinceveryshortdelay
isrequired,itis
difficulttoapplystrong
FECforthisservice.

4. Evolution of Mobile standards
EDGE
GPRS
GSM
HSCSD
cdmaOne
(IS-95)
WCDMA
FDD
HSDPA/
HSUPA
cdma2000
TD-SCDMA
TDD LCR
cdma2000
1XEV -DO
cdma2000
1XEV -DV
TD-CDMA
TDD HCR
HSDPA/
HSUPA
LTE

5. 3G Supports Entire Range of IP Services
Enabled by 3G’s Integrated Quality of Service (QoS) support,
high capacity and low latency
•Video/Music
•Telco-quality VoIP
•Low-Latency Gaming
•Push to Talk / Push to Media
•Multimedia Upload/Exchange
•High-Speed Web Browsing
•Streaming/Downloads
•Video Telephony
•Service Tiering
•Multicasting

6. Channel B.W 5 MHz
Forward RF Channel StructureDirect Spread
Chip Rate 3.84 Mcps
Frame Length 10 ms (38400 chips)
No. of slots/frame 15
No. of chips/slot 2560chips (Max. 2560 bits)
Power Control Open and fast close loop (1.6
KHz)
Uplink SF 4 to 256
Downlink SF 4 to 512
WCDMA Parameters

7. WCDMA Radio Access Modes

8. 3G rel99 Architecture (UMTS) —3G
Radios
SS7
IP
BTS
BSC
MSC
VLR
HLR
AuC
GMSC
BSS
SGSN GGSN
PSTN
PSDN
CN
C
D
Gc
Gr
Gn Gi
Abis
Gs
B
H
BSS —Base Station System
BTS —Base Transceiver Station
BSC —Base Station Controller
RNS —Radio Network System
RNC —Radio Network Controller
CN —Core Network
MSC —Mobile-service Switching Controller
VLR —Visitor Location Register
HLR —Home Location Register
AuC —Authentication Server
GMSC —Gateway MSC
SGSN —Serving GPRS Support Node
GGSN —Gateway GPRS Support Node
A
E PSTN
2G MS (voice only)
2G+ MS (voice & data)
UMTS —Universal Mobile Telecommunication System
Gb
3G UE (voice & data)
Node B
RNC
RNS
Iub
IuCS
ATM
IuPS

9. Release 99 Uplink Limitations
• Large Scheduling Delays
–Slow scheduling from RNC
• Large Latency
–Transmission Time Interval (TTI) durations of
10/20/40/80 ms
–RNC based retransmissions in case of errors
• Limited Uplink Data Rate
–Deployed peak data rate is 384 kbps
• Limited Uplink Cell Capacity
–Typically about 800 kbps

10. Evolution of WCDMA/HSPA

11. STANDARDIZED Integral part of WCDMA(3GPP Rel.5/6)
REDUCED DELAY Quicker response time with interactive services
CAPACITY
3 –4 times improved system capacity Rel. 5/6
SPEED
Higher bit rates: up to 14 Mbps
Network Coverage Short time to market with existing sites
HSDPA
Improving the WCDMA downlink

12. WhyHSDPA?
Comparison Between 3G & 3.5G.
Data Rate ( 2Mbps -----> 14.2 Mbps)
Modulation ( QPSK -----> QPSK&16QAM)
TTI( 10ms ----> 2ms )

13. High Speed Downlink Packet Access
• High speed data enhancement for WCDMA/UMTS
• Peak theoretical speeds of 14.2 Mbps
• Current devices support 7.2 Mbps throughput
•Methods used by HSDPA
–High speed channels shared both in the code and time
domains
–Short transmission time interval (TTI)
–Fast scheduling and user diversity
–Higher-order modulation
–Fast link adaptation
–Fast hybrid automatic-repeat-request (HARQ)

14. Adaptive Modulation and Coding

15. HSDPA Scheduling and
Retransmissions
• Scheduling
–Done at the Node B
–No interaction with the RNC
–Based on channel quality feedback from the
UE.
• Retransmissions
–HARQ (link level retransmissions)
–Done at the Node B
–Based on UE feedback (ACK/NACK)
–Soft combining at the UE

16. Hybrid Automatic Repeat Request (HARQ)
• Scheme combining ARQ and Forward Error
Correction.
• FEC decoding based on all unsuccessful
transmissions
• Two basic schemes:
–Chase Combining
*same data block is sent at each transmission
–Incremental Redundancy (IR)
*Additional Redundant Information sent at
each retransmission

17. Chase Combining
Data Block
Retransmissions
Block
Combine
Accept
Data
Block
•Coding is applied to transmission packets
•Soft combining of original and retransmitted signals is done
at receiver before decoding
•Advantage:
self decodable, time diversity, path diversity
•Disadvantage:
wastage of bandwidth

18. Incremental Redundancy
•Advantage:
Reducing the effective data throughput/bandwidth of a user and
using this for another user
•Disadvantage:
non-self decodable
Data Block
Information from
IR database
Combine
Error
Detection
IR
Database
Accept
Data Block
Error
No Error
Deliver
To Upper
Layers

19. HARQ –Illustration

20. Higher Order Modulations (HOMS)

21. High Speed Uplink Packet Access
• 85% increase in overall cell throughput on the uplink
• Achievable rates of 5.8 Mbps on the uplink
• Reduced packet delays to as low as 30 msec
• Methods:
–An enhanced dedicated physical channel
–A short TTI, as low as 2 msec, which allows
fast responses to changing radio conditions
and error conditions
-Node B based scheduling –Fast B-scheduling, which allows the
base station to efficiently allocate radio resources
–Fast Hybrid ARQ, which improves the efficiency of error
processing

22. How are Enhancements Achieved?

23. HSUPA Features (continued)
•Rate Request
-The UE requests grant for data transmission
•Rate Control
• The UTRAN controls the grants for transmission on Uplink
–Scheduled transmissions granted by the Node B for high speed
data.
–Non-Scheduled transmissions granted by the RNC for delay-
sensitive applications
•Load Control
-The UTRAN monitors Rise-over-Thermal (RoT) noise at the Node
B receiver.
–UTRAN prevents overloading by reducing scheduled grants to UEs

24. HSUPA Features (continued)
Hybrid-ARQ
–N-channel Stop-and-Wait (SAW)
protocol, with 4 processes for 10
ms TTI and 8 processes for 20
ms TTI.
–Synchronous retransmission
–Separate HARQ feedback is
provided per Radio-Link

25. E-DPDCH with SF4 and Puncturing

26. Lower Spreading Factor SF2

27. HSUPA UE Capabilities

28. Peak Rates Over Time

29. HOM Peak Rate Performance Benefits:
DL 64-QAM & UL 16-QAM

30. Introduction
to multiple antenna systems

31. Tx Rx
+6db is required !
QPSK QPSK16QAM 16QAM256QAM 256QAM
+12db is required !
To double the data rate0 5 10 15 20 25 30
10
-6
10
-4
10
-2
10
0
SNR [dB]
BER0 5 10 15 20 25 30
10
-6
10
-4
10
-2
10
0
6dB0 5 10 15 20 25 30
10
-6
10
-4
10
-2
10
0
12dB
Ifexistingsystemuseshigherordermodulation,
unacceptablehugetransmissionpowerisrequiredto
doublethedatarate.
2bits/symbol4bits/symbol8bits/symbol

32. Four basic models

33. What is a MIMO system?
What are MIMO systems ?
A MIMO system consists of several antenna elements, plus
adaptive signal processing, at both transmitter and receiver,
the combination of which exploits the spatial dimension of
the mobile radio channel.
Benefits
•Higher spectral efficiency (bits/s/Hz):
-spectrum is expensive; number of base stations limited
•Better transmission quality
•Increased coverage
•Improved user position estimation

34. MIMO System Model
y= Hs+ n
User data stream
.
.
User data stream
.
.
.
.
Channel
Matrix H
s1
s2
sM
s
y1
y2
yM
y
Transmitted vector Received vector
.
.
h11
h12
Where H=
h11 h21 ……..
hM1 h12 h22 ……..
hM2
h1M h2M ……..
hMM
. . …….. .
MT
MR
hij is a Complex Gaussian
random variable that models
fading gain between the ith
transmit and jth receive
antenna

35. MIMO Systems
Single Input Single Output (SISO)
Tx Rx
Multiple Input Multiple Output (MIMO)
Tx Rx
Space Time Coding Spatial multiplexing
=High data rate
High spectrum
efficiency
All effects cannot be achieved at the same time.
Smart design methodis needed for each system.
MIMO transmission techniques Effects

36. ARCHITECTURE OF MIMO

37. 7/2/2024
Path Loss and Fading Challenge
Delay
Spread
Rayleigh
Fading
Path
Loss
rapid fading of 20 to 30 dB
(power varies by 100 to 1000 times
in level at rates of about 100 times per second)
path loss up to
~ 150 dB
(that is a 1 followed
by 15 zeroes)
Reflected signals
arrive spread out
over 5 to 20
microsecond

38. Training vsBlind vsSemi-Blind
Channel Estimation
•Must estimate the channel to recover the signal
•Training-based
–Use pilot symbols/tones
–Consume bandwidth, capacity loss
•Blind
–Use inherent structure of signal
–Constrained to special cases, less accurate
•Semi-blind
–Use minimal amount of known symbols w/
inherent structure of signal

39. Tx Rx
Estimated CSI
MIMO transmission
techniques Effects
Signal distribution in space
Beamforming
Spatial multiplexing
=High data rate
Array gain
MIMO systems with perfect CSIat a transmitter
Probe signals are transmitted from each antenna.
CSI is estimated at the receiver.
Estimated CSI is fedback to the transmitter.Beams are generated in both sides.
Complicatedprocedureisrequiredwhileitachievesthe
bestperformances.

40. Spatial Multiplexing Effect
Tx
Coherent
phase
+
-
Tx
Df=p
Todoublethedatarate,requiredtransmissionpower
doesnotdependonthemodulationorder.
No signal
No signal
QPSK
w
1
w
2

41. Space-Time Coding (STC)
•Jointly encodes the data streams over
antennas, and therefore aims to maximize
diversity gain.
•STBC is based on orthogonal design and
obtains full diversity gain with low decoding
complexity (Alamouti code is a special case
with double Tx antennas).

42. •STC is a new coding / signal processing framework having the
potential of improving link quality for wireless communications
with multiple transmit and multiple receive antennas.
•For an input symbol sequence, ST encoder chooses constellation
points to simultaneously transmit from all antennas so that
coding and diversity gains can be
maximized.
Space-Time Block Code (STBC)

43. Diversity Effect
-Space Time Block Coding (STBC)-AlamoutiScheme
Tx
Tx
S
1S
2
*
S
1S
2
S
2-S
1
*
h
1=1
h
2=1
T
S
1S
2
*
We can easily
decode the data.
*
S
1+ S
2-S
1+ S
2
+
2 S
2
-
2 S
1
Bydoingthisprocedure,diversityeffectcanbeexpected
evenfortransmitters.
Additionaldiversityeffectcanbeexpectedbyincreasing
antennasatthereceiver.
w

44. MIMO Increases Throughput
Shannon’s
Law
Wireless throughput scales as
more radio transmissions are
added onto the same channel
Only baseband complexity, die
size/cost, and power consumption
limits the number of simultaneous
transmissions

45. Cooperative Communications

46. Motivation
•The main advantages of cooperative
communications are:
–Higher spatial diversity
–Higher throughput/Lower delay
–Reduced interference/Lower transmitted
power
–Adaptability to network conditions
•A cross-layer research is proposed to facilitate
the cooperative communication in WLAN.

47. What’s Different Between MIMO and
Cooperation?
•Distributed nature of relays/nodes
–Different channel gain amplitudes and phases
–Each relay runs on its own timer and VCO
•Relay capabilities
–Single antenna
–Full duplex or half duplex
•Channel state information (CSI)
–Relay might not know states of other relay links

48. Cellular Cooperative Communication
System

49. D
R
S
R
broadcast
Multiple
access
Transmission Phases:
Phase I
Phase II

50. Tradeoffs
Reduces
Energy Consumption
Multipath Fading,
Shadowing
Interference.
BER
Increases:
Data Rates proportional to
diversity.
s
r
1
d
r
2
r
3
r
4
h
1d
h
4d
h
2d
h
3d
h
sd
d
s
2
s
1
Cooperative Relays
Two cooperative
sources
h
s2d
h
s1d
h
sd

51. Analysis of Basic 3 Node Scenario
Performance metrics
•Outage
•Power consumption
•Diversity
•BER (Coded/Uncoded)
d
s
2
Two sources
s
1
h
1d
h
2d
h
12
S
1transmits S
2transmits
d receives d receives
Conventional
model
Tx
Rx
S
1tx S
2repeats S
2tx S
1repeats
d, S
2rx d rx d,S
1rx d rx
Cooperative
source model
Tx
Rx
[Laneman & Wornell, IEEE Trans. on Inf. Theory, 2004]
[Stefanov, Erkip, IEEE Trans. on Communications, 2004]

52. Cooperative Communication Schemes
•Amplify and forward
•Decode and forward
Possibilities:
•Orthogonal / Non-orthogonal cooperation
•Coded / Uncoded cooperation

53. Amplify and Forward Method
• The user (relay) receives a noisy version of the signal transmitted by the
partner (source).
• The noisy signal is simply amplified and retransmitted.

54. Outage Analysis: Amplify and Forward[1][1]
[2] [2]
sd dd
d rd sr rd r d
hwy
x
y h h h w w
   
   
        2
0
r
sr s
P
h P N

 22
2
22
SNR SNR
log 1 SNR
SNR SNR
sr rd sr rd
AF sd sd
sr sr rd sr
hh
Ih
hh

  



d
r
s
h
sd
h
rd
h
sr
x
y
d
y
r = h
srx + w
r 
 
2
222
2 2 2 2
211
( , ) Pr
2 SNR
sr
sd sr
R
rd
out AF
rd
P SNR R I R

  

  
Relay power
constraint:
Tx. rate
Outage prob.
Diversity order = 2

55. Decode and Forward Method
• The user (relay) attempts to detect the partner’s bits (source)
and then retransmits the detected bits.
• The partner has to be assigned mutually by the base station.
• Different partnership topologies may be used.

56. Outage Analysis: Decode and Forward
Case 1: Destination can decode only if relay
decodes ˆ
r
xx ˆ
d rd d
y h x w   
2 2 21
min log 1 ,log 1
2
DF sr sd rd
I SNR h SNR h SNR h

   
  
2
2
1 2 1
( , ) Pr
R
out DF
sr
P SNR R I R
SNR

  
(Assume codeword level decoding)
Diversity order = 1

57. Outline
•Various cooperation
schemes
•Cooperation in ad hoc
networks
•Cooperation in
infrastructure-based
networks
•Cross-layer issues
•Other interesting topics

58. Trade-offs
How to avoid
interference?
How can
capacity be
increased?
Why use indoor
antennas?
How much BW is till
required?
What about
the future?
Continous
Conectivity

59. References
•[1] 3GPP, TSG, RAN, Physical Layer Aspects of UTRA High Speed DownlinkPacket
Access, 3GPP TR 25.848, V4.0.0, 2001.
•[2] J. Kawamoto, T. Asai, K. Higuchi, and M.Sawahashi ,“Independent Turbo Coding
and Common Interleaving Method among Transmitter Branches Achieving Peak
Throughput of 1Gbps in OFCDM MIMO Multiplexing,” ETRI J., vol.26,
no.5,Oct.2004, pp.375-383.
•[3] S. Liu and J. W. Chong, “An Efficient Scheme to Achieve Differential Unitary
Space-Time Modulation on MIMO-OFDM Systems,” ETRI J., vol.26, no.6, Dec.
2004, pp.565-574.
•[4] I. Sohn and J. Y. Ahn, “Joint Processing of ZF Detection and MAP Decoding for
MIMO-OFDM System,” ETRI J., Vol .26,no.5, Oct. 2004, pp.384-390.
•[5] A.Goldsmith,”Wireless Communications”,Cambridge University Press, 2005.
•[6] J.F. Cardoso, “Source separation using higher ordered moments,” in Proc.
ICASSP-1989, 1989, vol.4, pp.2109–2112.
•[7] P. Comon, “Independent component analysis: A new concept?” Signal
Processing, vol.36, no.3, pp.287–314, 1994.
•[8] C.-Y. Chi, C.-Y. Chen, C.-H. Chen and C.-C. Feng, “Batch processing algorithms for
blind equalization using higher-order statistics,” IEEE Signal Processing
Magazine,vol. 20, no.1, pp.25–49, 2003.
•[ 9] C-Q. Chang, S.F. Yau, P. Kwok, F.K. Lam and F.H.Y. Chan, “Sequential approach to
blind source separation using second order statistics,” in Proc. 1st Int. Conf.
information, Communication, ans Signal Processing, Sept. 9-12, 1997, vol.3,
pp.1608–1612.

60. DSCE: 08641D0607
Vaagdevi College of Engineering