information theory - thecatweb.cecs.pdx.edu/~fli/class/chapter5_notes.pdf · fundamentals of...

18
1 1 5: Capacity of Wireless Channels Fundamentals of Wireless Communication, Tse&Viswanath 5. Capacity of Wireless Channels 2 5: Capacity of Wireless Channels Fundamentals of Wireless Communication, Tse&Viswanath Information Theory So far we have only looked at specific communication schemes. Information theory provides a fundamental limit to (coded) performance. It succinctly identifies the impact of channel resources on performance as well as suggests new and cool ways to communicate over the wireless channel. It provides the basis for the modern development of wireless communication.

Upload: hacong

Post on 10-Mar-2018

219 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

1

1

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

5. Capacity of Wireless Channels

2

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Information Theory

• So far we have only looked at specific communication schemes.

• Information theory provides a fundamental limit to (coded) performance.

• It succinctly identifies the impact of channel resources on performance as well as suggests new and cool ways to communicate over the wireless channel.

• It provides the basis for the modern development of wireless communication.

Page 2: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

2

3

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Capacity of AWGN Channel

Capacity of AWGN channel

If average transmit power constraint is watts and noise psd is watts/Hz,

4

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Power and Bandwidth Limited Regimes

Bandwidth limited regime capacity logarithmic in power, approximately linear in bandwidth.

Power limited regime capacity linear in power, insensitive to bandwidth.

Page 3: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

3

5

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

6

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Example 1: Impact of Frequency Reuse• Different degree of frequency reuse allows a tradeoff

between SINR and degrees of freedom per user.• Users in narrowband systems have high link SINR but

small fraction of system bandwidth.• Users in wideband systems have low link SINR but full

system bandwidth.• Capacity depends on both SINR and d.o.f. and can

provide a guideline for optimal reuse. • Optimal reuse depends on how the out-of-cell

interference fraction f(ρ) depends on the reuse factor ρ.

Page 4: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

4

7

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Numerical Examples

10 15 20 25 30

1/7

Cell edge SNR (dB)

Frequency reuse factor 1

1/20.2

50–5–10

1.4

1.2

1

0.8

0.6

0.4

0

Rate

bits /s / Hz

10 15 20 25 30

Rate

bits / s / Hz

Cell edge SNR (dB)

1/2

Frequency reuse factor 1

1/30.5

50–5–10

3

2.5

2

1.5

1

0

d

Linear cellular system Hexagonal system

8

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Example 2: CDMA Uplink Capacity• Single cell with K users.

• Capacity per user

• Cell capacity (interference-limited)

Page 5: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

5

9

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Example 2 (continued)• If out-of-cell interference is a fraction f of in-cell interference:

10

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Uplink and Downlink Capacity

• CDMA and OFDM are specific multiple access schemes.

• But information theory tells us what is the capacity of the uplink and downlink channels and the optimal multiple access schemes.

Page 6: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

6

11

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Uplink AWGN Capacity

R1

R2

C

B

A

log 1 +

P2

N0

log 1 +

P1

N0

log 1 +

P2

P1 + N0

log 1 +

P1

P2 + N0

successive cancellation:cancel 1 before 2

cancel 2 before 1conventionaldecoding

12

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Conventional CDMA vs Capacity

CDMA

R2 ( bits / s / Hz )

R1 ( bits / s /Hz )

1

5.67

6.66

C

B

0.585

0.5850.014

D

rate increase to weak user

A 20 dB power difference between 2 users

Successive cancellation allows the weak user to have a goodrate without lowering the power of the strong user.

Page 7: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

7

13

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Orthogonal vs Capacity

0.014

R2 ( bits / s / Hz )

R1 ( bits / s / Hz )

1

5.67

6.66

AC

B Sum capacityachieved here

0.065

20 dB power difference between 2 users

orthogonal

Orthogonal achieves maximum throughput but may not be fair.

14

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Downlink Capacity

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

1

2

3

4

5

6

7

Rate of user 1

Rat

e o

f u

ser

2

20 dB gain difference between 2 users

superposition coding

orthogonal

Page 8: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

8

15

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Frequency-selective Channel

's are time-invariant.

OFDM converts it into a parallel channel:

where is the waterfilling allocation:

with λ chosen to meet the power constraint.

Can be achieved with separate coding for each sub-carrier.

16

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Waterfilling in Frequency Domain

Page 9: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

9

17

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Slow Fading Channel

h random.

There is no definite capacity.

Outage probability:

−outage capacity:

18

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Outage for Rayleigh Channel

Pdf of log(1+|h|2SNR) Outage cap. as fraction of AWGN cap.

Page 10: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

10

19

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Receive Diversity

Diversity plus power gain.

20

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Transmit DiversityTransmit beamforming:

Alamouti (2 Tx):

Diversity but no power gain.

Page 11: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

11

21

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Repetition vs Alamouti

Repetition:

Alamouti:

Loss in degrees of freedom under repetition.

22

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Time Diversity (I)

Coding done over L coherence blocks, each of many symbols.

This is a parallel channel. If transmitter knows the channel, can do waterfilling.

Can achieve:

Page 12: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

12

23

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Time Diversity (II)

Without channel knowledge,

Rate allocation cannot be done.

Coding across sub-channels becomes now necessary.

24

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Fast Fading Channel

Channel with L-fold time diversity:

As

Fast fading channel has a definite capacity:

Tolerable delay >> coherence time.

Page 13: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

13

25

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Capacity with Full CSI

Suppose now transmitter has full channel knowledge.

What is the capacity of the channel?

26

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Fading Channel with Full CSIThis is a parallel channel, with a sub-channel for each fading state.

is the waterfilling power allocation as a function of the fading state, and λ is chosen to satisfy the average power constraint.

where

Can be achieved with separate coding for each fading state.

Page 14: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

14

27

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Transmit More when Channel is Good

28

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Performance

At high SNR, waterfilling does not provide any gain.But transmitter knowledge allows rate adaptation and simplifies coding.

Page 15: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

15

29

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Performance: Low SNR

Waterfilling povides a significant power gain at low SNR.

30

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Waterfilling vs Channel Inversion• Waterfilling and rate adaptation maximize long-term

throughput but incur significant delay.

• Channel inversion (“perfect” power control in CDMA jargon) is power-inefficient but maintains the same data rate at all channel states.

• Channel inversion achieves a delay-limited capacity.

Page 16: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

16

31

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Example of Rate Adaptation:1xEV-DO Downlink

Multiple access is TDMA via scheduling. (More on this tomorrow.)

Each user is rate-controlled rather than power-controlled. (But no waterfilling.)

32

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Rate ControlMobile measures the channel based on the pilot and predicts the SINR to request a rate.

Page 17: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

17

33

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

SINR Prediction Uncertainty

prediction

t

lag

prediction

SINR

(a)

t

lag

SINR

(b)

prediction

t

lag

SINR

(c)

conservative

3 km/hr 30 km/hr 120 km/hr

accurate prediction of instantaneousSINR.

conservative prediction of SINR.

accurate predictionof average SINR fora fast fading channel

34

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Incremental ARQ• A conservative prediction leads to a lower requested rate.• At such rates, data is repeated over multiple slots.• If channel is better than predicted, the number of

repeated slots may be an overkill.• This inefficiency can be reduced by an incremental ARQ

protocol.• The receiver can stop transmission when it has enough

information to decode. • Incremental ARQ also reduces the power control

accuracy requirement in the reverse link in Rev A.

Page 18: Information Theory - TheCATweb.cecs.pdx.edu/~fli/class/Chapter5_notes.pdf · Fundamentals of Wireless Communication, Tse&Viswanath 6 5: Capacity of Wireless Channels Fundamentals

18

35

5: Capacity of Wireless Channels

Fundamentals of Wireless Communication, Tse&Viswanath

Summary• A slow fading channel is a source of unreliability: very

poor outage capacity. Diversity is needed.• A fast fading channel with only receiver CSI has a

capacity close to that of the AWGN channel. Delay is long compared to channel coherence time.

• A fast fading channel with full CSI can have a capacity greater than that of the AWGN channel: fading now provides more opportunities for performance boost.

• The idea of opportunistic communication is even more powerful in multiuser situations, as we will see.