2009031848887001

8/8/2019 2009031848887001

http://slidepdf.com/reader/full/2009031848887001 1/56

From OFDM and SC-FDE

to EST Based Modulation

Professor Geoffrey Ye Li

School of Electrical and Computer Engineering

Georgia Institute of Technology, USA

8/8/2019 2009031848887001


Contents

Overview of my Research

Orthogonal Frequency Division Multiplexing (OFDM)

S ingle-Carrier with Frequency-Domain Equalization (SC-FDE)

Energy S preading Transform (EST) based Modulation for Frequency-

Selective Channels

Why EST?

Spreading in Time and Frequency Domain

System Description (Hard/Soft Decision)

Performance Analysis Simulation Results

Extension to MIMO Systems

Extension to Doubly Selective Channels

2

8/8/2019 2009031848887001


Contents





Selective Channels

Why EST?






3

8/8/2019 2009031848887001


MIMO-OFDM

Channel estimation for MIMO-OFDM system with a large

number of transmit antennas under high mobility

environments

Signal detection for MIMO-OFDM: Complexity

performance trade-off

Transmission with partial CSI Interference avoidance and suppression

Multi-user MIMO

Various applications in current standards and systems

8/8/2019 2009031848887001


Cross-Layer Optimization

Centralized Optimization: How to perform optimization with partial CSI?

Impact of MIMO on cross-layer optimization

performance?

Interference suppression and avoidance in

cellular systems

De-centralized Optimization:

Scheduling with limited CSI

Stability region of multi-carrier networks

Energy efficiency transmission

8/8/2019 2009031848887001


Cognitive Radio

MIMO OFDM(A) based cognitive networks

Cooperative spectrum sensing for mobile networks

Dynamic spectrum allocation

Cross-Layer issues in CR nestworks

8/8/2019 2009031848887001


OFDM for Wir eless Communications:

Channel Estimation

Y. (G.) Li, L. J. Cimini, Jr., and N. R. Sollenberger, Robust channel estimation

for OFDM systems with rapid dispersive fading channels, IEEE Trans. Commun.

vol. 46, pp. 902-915, July 1998. (Google citation: 488)

Y. (G.) Li, Pilot-symbol-aided channel estimation for OFDM in wireless

systems, IEEE Trans. Veh.T ech., vol. 49, pp. 1207-1215, July 2000. (Google citation: 262)

8/8/2019 2009031848887001


OFDM for Wir eless Communications:

Co-Channel Interf er ence Suppr ession

Y. (G.) Li and N. R. Sollenberger, Adaptive antenna arrays for OFDM systems

with co-channel interference, IEEE T rans. C ommun., vol. 47, pp. 217-229, Feb.

1999. (Google citation: 142)

BASESTATION

R

D

8/8/2019 2009031848887001


MIMO-OFDM: Channel Estimation

and Tr aining Sequence Design

Y. (G.) Li, N. Seshadri, and S. Ariyavisitakul, Channel estimation for OFDM

systems with transmitter diversity in mobile wireless channels, IEEE J.

Selected Areas Commun., vol. 17, pp. 461-471, March 1999. (Google citation:

417)

Y. (G.) Li, Simplified channel estimation for OFDM systems with multiple transmit

antennas, IEEE T rans. on Wireless C ommun., vol. 1, pp. 67-75, Jan. 2002. (Google citation: 263)

First MIMO-OFDM System !!!

8/8/2019 2009031848887001


MIMO-OFDM:

Mor e Tr ansmit and Receive Antenna System

Y. (G.) Li, J. H. Winters, and N. R. Sollenberger, MIMO-OFDM for wireless

communications: signal detection with enhanced channel estimation, IEEE T rans.

C ommun., vol. 50, pp. 1471-1477, Sept. 2002. (Google citation: 262)

G. L. Stuber, J. Barry, S. McLaughlin, Y. (G.) Li, M. A. Ingram, and T. Pratt,

Broadband MIMO-OFDM wireless communications, Proc. of IEEE, vol. 92, pp.271-294,

Feb. 2004. (Google citation: 355)

8/8/2019 2009031848887001


MIMO-OFDM:

Perfor mance Improvement by Pr e-Processing

Data

Input

Demultiplexer

Modulator

Modulator

4

4

Statistical Layer Rate

Allocation

Channel

Encoder

ChannelEncoder

J. Du, Y. (G.) Li, D. Gu, A. Molisch, and J. Zhang, ³Statistical rate allocation for layered

space-time system,´ to appear in IEEE Trans. Commun., vol. 55, no. 3, pp. 489-496,

March 2007.

8/8/2019 2009031848887001


Cross-Layer Optimization for Str eaming Tr aff ic:

Theor etical Fr amework

Continuous frequency Discrete subcarriers

G.-C. Song and Y. (G.) Li, Cross-layer optimization for OFDM wireless

networks Part I and Part II, IEEE T rans. Wireless Commun., vol. 4,

no. 2, pp. 614 634, March 2005. (Google citation: 120+72)

8/8/2019 2009031848887001


Cross-Layer Optimization for Best Effor t Tr aff ic

G. Song, Y. (G.) Li, and L. J. Cimini, Jr., Joint channel- and queue-

aware scheduling for multiuser diversity in wireless multicarrier

networks, to appear in IEEE T rans. Commun.

8/8/2019 2009031848887001


Cross-Layer Optimization: Mor e

What happens if a network has different types of traffic?

G.-C. Song and Y. (G.) Li, ³Utility-based resource allocation and

scheduling in OFDM-based wireless networks,´ IEEE Commun.

Mag., vol. 43, no. 12, pp. 127 - 135, Dec. 2005.

How to evaluate performance theoretically?

G.-C. Song and Y. (G.) Li, ³Asymptotic throughput analysis for

channel-aware scheduling,´ IEEE Trans. Commun., vol. 54, no.

10, pp.1827-1834, Oct. 2006.

Stability of CSI aware random access?

G. Ganesan, Y. (G.) Li, and Frederick W. Vook, ³Stability region of

multicarrier channel aware Aloha,´ IEEE Trans. Inf. The., vol.

53, no. 9, pp. 3212-3218, Sept. 2007.

8/8/2019 2009031848887001


Cognitive Radio: Cooper ative Spectr um Sensing

: Licensed user

: Cognitive user

Cognitive users should

not cause interference

to licensed users

Primary

G. Ganesan and Y. (G.) Li, ³Cooperative spectrum sensing in cognitive radio: Part I: two

user networks,´ IEEE Trans. Wireless Commun., vol. 6, pp. 2204-2213, June 2007.

G. Ganesan and Y. (G.) Li, ³Cooperative spectrum sensing in cognitive radio: Part II:

multiuser networks,´ IEEE Trans. Wireless Commun., vol. 6, pp. 2214-2222, June 2007.

G. Ganesan, Y. (G.) Li, B. Bing, and S.-Q. Li, ³Spatial-temporal sensing in cognitive radio

networks,´ IEEE J. Selected Areas Commun., vol. 26, pp. 5 ± 12, January 2008.

8/8/2019 2009031848887001


Contents





Selective Channels

Why EST?






16

8/8/2019 2009031848887001


Principles of OFDM (I)

17

How to communicate across an ISI channel with bandwidth W?

Single Carrier : Transmit at symbol rate

Multi Carrier :

Divide band into narrow sub-channels

Transmit at symbol rate for each sub-channels

N parallel transmission with rate each

Total rate

Avoids ISI when N is large that means symbol duration is long

1/ /T W N !

/W

/W W ! v !

N

8/8/2019 2009031848887001


01

T

1 N

T

L

0 ( )G f 1

( )G f 1

( ) N G f

f

L L

Bandwidth =N

W !

Principles of OFDM (II)

Symbol duration in parallel using N subcarriers

Separation between adjacent subcarriers = (orthogonal condition)

18

1 ( ) N g t

0 ( ) g t

1( ) g t

M

8/8/2019 2009031848887001


OFDM System

IFFT is used to implement N parallel orthogonal subcarriers

Inserting cyclic prefix (CP)

avoids interference between OFDM symbols

makes the convolution of IFFT values and channel impulse response ³circular´

makes the received signal after FFT as a multiplication of channel response and

data for each subcarrier (zero-forcing equalizer)

19

8/8/2019 2009031848887001


Properties of OFDM

Pros:

Low-complexity signal detection for frequency-selective channels

potentially achieve channel capacity by adaptive modulation and power

loading according to SNR of each subcarrier [water-filling algorithm]

OFDMA: group subcarriers and allocate them to different users

Cons:

High peak-to-average power ratio (PAPR)

Sensitivity to Doppler: Channel variation within one OFDM symbol

duration incurs inter-carrier interference (ICI)

Applications: ADSL, Digital Video Broadcast (DVB), Digital Audio Broadcast (DAB),

Wireless LAN (IEEE 802.11a), Wireless MAN (WiMax IEEE 802.16),

Down-Link [base station to mobile] 3GPP LTE, etc.

20

8/8/2019 2009031848887001


Contents




Selective Channels

Why EST?



Performance Analysis

Simulation Results



21

8/8/2019 2009031848887001


SC-FDE: Characteristics

Block transmission scheme employing cyclic prefix (CP)

No IFFT at the transmitter (single carrier)

MMSE frequency-domain equalization at the receiver

IFFT after the channel equalization at the receiver

D. Falconer et al. ³ Single carrier system with frequency-domain equalization

(SC-FDE),´ IEEE Comm. Mag. Vol. 40, Apr. 2002

22

8/8/2019 2009031848887001


SC-FDE: Principle

Block diagram

23

8/8/2019 2009031848887001


Properties of SC-FDE

Pros:

Each symbol occupies whole bandwidth frequency diversity

Low complexity frequency-domain equalization at the receiver (MMSE

equalization)

Low PAPR [no IFFT at the transmitter, good for uplink] Multiple access based on single-carrier frequency-domain multiple

access (SC-FDMA)

Applications:

Uplink [Mobile to Base Station] in 3GPP LTE [due to its low PAPR]

24

8/8/2019 2009031848887001


Contents




Selective Channels

Why EST?




Simulation Results



25

8/8/2019 2009031848887001


EST Based Modulation

Block Diagram

26

8/8/2019 2009031848887001


EST Based Modulation vs. SC-FDE

Similarities:

Transmit symbols in blocks employing CP

Use low-complexity frequency-domain equalization

í For the 1st iteration, EST-Based modulation performs the same as SC-FDE

Each symbol occupies the whole frequency band

Differences:

In SC-FDE, each symbol occupies a single symbol time

In EST Based Modulation, each symbol occupies whole block time

EST Based Modulation uses iterative symbol detector at the receiver PAPR of EST Based Modulation is comparable to that of OFDM

EST Based Modulation performs close to Matched Filter Bound (MFB)

27

8/8/2019 2009031848887001


EST Based Modulation

OFDM and SC-FDE are special cases of EST based modulation

28

n x

n x~

nr ~

k R~

n xÖ

)(i

k A

)(i

nb

)(i

k

A)(i

n

b

If ³EST = IFFT´ and ³no feedback path´ It is OFDM

If ³EST = Identity´ and ³no feedback path´ It is SC-FDE

8/8/2019 2009031848887001


Properties of EST Based Modulation

Block transmission scheme like OFDM and SC-FDE

Based on EST: EST spreads the symbol energy both in frequency and time

domain:

Frequency-domain spreading obtains frequency diversity

Time-domain spreading increases the reliability of feedback signal

Iterative scheme, but independent of channel coding

Different from turbo-like schemes

Near genie-aided (interference-free) performance

29

Frequency-domain spreading Time-domain spreading

OFDM 0% 100%

SC-FDE 100% 0%

Ideal ES

T 100% 100%

Spreading Characteristics of OFDM, SC-FDE, and Ideal EST

8/8/2019 2009031848887001


Energy Spreading Transform (EST)

0 x

1 x

2 x

3 x

1 N

TIME DOMAIN

FREQUENCY

DOMAIN

Symbol vector Transform MatrixTransform

Spreading in time and frequency domain

: EST Matrix : Normalized Fourier transform matrix : Block size

8/8/2019 2009031848887001


Ideal EST

31

Ideal EST is a unitary transform that satisfies:

Time-Domain Spreading Frequency-Domain Spreading

1) Magnitude condition:

2) Phase condition:

Phase should be randomly and symmetrically distributed

8/8/2019 2009031848887001


Measures for Spreading

32

Time spreading measure: n-th time despreading factor of E

10, ee N n

10, ee N n

Range of despreading factors:

Perfect spreading No spreading

E

F

: EST matrix

(N by N )

: NormalizedFourier transfrommatrix (N by N )

N : lock sizeNotation

e

);( n s H

¡

E §

!

1

0

22

, )1

)(( N

l nl

H

N E!

);( n s F E );( n sT FE §

!

1

0

22

, )1

)(( N

l nl

N FE! !

);(),;( n sn s ¢

H

£

EE0 N

N 1e

Measure for the n-th column of FE

Measure for the n-th column of H E

8/8/2019 2009031848887001


)},({ n s E ¤

iT d E )},({ n sV H

iT d E )},({ n s E

i F d E )},({ n sV

i F d Ei

E

H FE

1!

H FPE12

!

H H FPF13

!

T4!

TP15

!

TP16

H !

0

0

0

0

0

0

0

0 0

00

41089.4 v

41089.4 v

101059.4 v

101081.5 v

11099.9 v

41089.4

v

0

101045.9 v

21054.5

v

0

31043.3 v

41089.4 v

101073.4 v

)11( ee N n

:T :F

EST Design

33

How to Construct? Concatenate permutation and special unitary matrix:

What are their spreading properties?

(Normalized) Fourier transform and Hadamard transform are good

candidates for due to their fast algorithms

8/8/2019 2009031848887001


EST: Frequency-Domain Spreading

34

ChannelFrequency Response

No Frequency Spreading

Perfect Frequency Spreading

1 H

0 H

2 H

TIME DOMAIN FREQUENCY DOMAIN

EST FFT

FFTEST

poor

good

k H

: Symbol Energy

Look at the frequency-domain operation: Multiplication

8/8/2019 2009031848887001


EST: Time-Domain Spreading

35

Look at the time-domain (feedback) filter operation: Convolution

0Ö x

1Ö x

2Ö x

3Ö x

4Ö x

1Ö

N

0

~Ö x

1

~Ö x

2

~Ö x

3

~Ö x

4

~Ö x

1

~Ö

N x

EST

EST

poor

good

No Time Spreading

Perfect Time Spreading

1b 1b1b

0bsliding

Reference time n =1

Feedback Filter: nb

21011ÖÖ xb xbq !

21011

~Ö

~Ö xb xbq !

Feedback Filter Output

= Estimated Interference

for Cancellation

: Incorrectly-decided Symbol Energy

: Correctly-decided Symbol Energy N

2

1Incorrect energy =

Incorrect energy =

N : Block size

8/8/2019 2009031848887001


Performance: Hard Decision

Asymptotic case (infinite N )

SINR for the n-th decision variable

SER (Averaged over block)

Threshold SNR: SNR at which

36

Law of large numbers:

(Independent of n)

elative frequency of error

8/8/2019 2009031848887001


Simulation Parameters

Original Scheme:

1st Iteration: MMSE equalizer without feedback

From 2nd iterations: Matched filter + ISI canceller

Improved Scheme:

Optimum filters that maximize SINR

Block Size = 2048

Channels

Proakis-B

í Proakis-C

í

37

8/8/2019 2009031848887001


Simulation: Original Scheme with Hard Decision

38

0 2 4 6 8 10 12 14 16 1810

-5

10-4

10-3

10-2

10-1

100

BER

SNR per bit (dB)

Simulation,N=2048

H FE !1

(Same as OFDM)

1st iter.

2nd iter.

3rd iter.

10th iter.

MFB

Analysis (Infinite N )

Simulation,N=2048 H

PFE !2

Simulation,N=2048

PTE !5(Hadamard)

(Fourier)

Proakis-B channel

Same as SC-FDE

8/8/2019 2009031848887001


Simulation: Original Scheme with Soft Decision

Proakis-B channel

39

0 2 4 6 8 10 12 14 16 1810

-5

10-4

10-3

10-2

10-1

100

BER

SNR per bit (dB)

Simulation,N=2048 H

PFE !2

Simulation,N=2048

PTE !5

DFE with Perfect Feedback

2nd iter.

3rd iter.

1st iter.

10th iter.

4th

iter.

MFB

MLSD

8/8/2019 2009031848887001


Simulation: Original Scheme

Proakis-C channel

40

0 5 10 15 2010

-5

10-4

10-3

10-2

10-1

100

Analysis (Infinite N ), 10th iter, Hard decision

Simulation, N=4096, 10th iter.

Hard decision

DFE with Perfect Feedback

Simulation, N=4096, 10th iter.

S oft decision

SNR per bit (dB)

BER

MFB

1st iter.

MLSD

8/8/2019 2009031848887001


Effects of Block Size N

Proakis-B channel, SNR = 10 dB

41

1 2 3 4 5 6 7 8 9 1010

-5

10-4

10-3

10-2

10-1

100

N=128

N=256

N=512

N=1024

N=2048

N=4096

BER

Iteration

8/8/2019 2009031848887001


Simulation: Improved Scheme with Hard Decision

Proakis-C channel

42

0 5 10 15 2010

-5

10-4

10-3

10-2

10-1

100

BER

SNR per bit (dB)

MFB

10th iter.

3rd iter.

2nd iter.

1st iter.

2nd iter.3rd iter.10th iter.

Original equalization(Simulation)

Improved equalization(Simulation)

Improved equalization(Analysis)

8/8/2019 2009031848887001


0 5 10 15 2010

-5

10-4

10-3

10-2

10-1

100

Proakis-C channel

Simulation: Improved Scheme with Soft Decision

43

BER

SNR per bit (dB)

MFB

1st iter.

2nd iter.

3rd iter.

10th iter.

MLSD

Original equalization

(Simulation)

Improved equalization(Simulation)

8/8/2019 2009031848887001


Contents




Selective Channels

Why EST? Spreading in Time and Frequency Domain



Simulation Results



44

8/8/2019 2009031848887001


MIMO Signal DetectionMIMO Signal Detection

Multiple-Input Multiple-Output (MIMO) system increases reliability and data

transmission rate for wireless communications

But, it introduces interference among different antennas

Therefore, low complexity receiver that resolve those interference is

necessaryDesired signal + interference + noise

nnn nHxr !

Transmitter

T n

R eceiver

Rn

]1[ v Rn ][ T R nn v ]1[ vT

n ]1[ v R

nk n ,)(H )

1,0(

T n

N ~

8/8/2019 2009031848887001


EST Based MIMO Detection: Flat fading channels

Decision

S/P EST

Receiver

IEST: Inverse Energy Spreading TransformEST: Energy Spreading Transform

IESTP/S

S/P: Serial to Parallel Converter P/S: Parallel to Serial Converter

Transmitter

S/PEST

.

.

.

)(Ö i

nx

.

.

.

delay

: Forward Matrix : Feedback Matrix

1T

n

0

n x

n x~

0

R

n 1T

n

T n

T n

T n

T n

(i)A

(i)B

(i)A

(i)B

(i)D

0

1

.

.

.

)1(Ö i

nx

Hard or

Soft decision

8/8/2019 2009031848887001


Performance Analysis (HardPerformance Analysis (Hard--Decision, Infinite N)Decision, Infinite N)

Iteration = 1: MMSE detector

¹¹ º

¸©©ª

¨¹

¹ º

¸©©ª

¨

¹¹ º

¸©©ª

¨

!

§§§

§

!

!

{

!

1

0

,

221

0

12

,

2

21

0

,

2

(1)

)|(|1

|)(|1

)(1

SINR

1 12

21

T T T

T

n

l

l l

T

n

n

l

n

l l

l l

T

x

n

l

l l

T

x

nn

n

(1)AM

M

W W

W

Iteration 2: Matched filter + Interference canceller u

nExpect ti:

err r -ecisi n

decisi n

sizeBl ck:

r tinoisetosi nal

r ationoiseceinterf er entosi nalI

otation

}{

:Ö

:Ö

:

:

2

2

!

!

!

nnn

n

n

x

x x

x

N

HAM(1)

§ §

!

{

!

1

0

1

2

,

2

,

1 1211

21

)(

|)(|1 T T n

l

n

l l l l

l l

T

H n

K G

G

}naterror symbol|{1

)(2

2

)(

n

x

¥

N

N

W

O !: Average decision-error power

normalized by signal power

§

!

!1

0,)(

11 T n

l l l T

H n

QG

SNR )(

1SI NR

)1()1(

(i)

H ¦ ¦

H

Q p p K

!

O

)SINR ()()( ii

p =!

8/8/2019 2009031848887001


0 1 2 3 4 5 60

0.01

0.02

0.03

0.04

0.05

0.06

0.07

nT=n

R=16

nT=n

R=8

nT=n

R=4

nT=n

R=2

0 1 2 3 4 5 60

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.05

nT=n

R=16

nT=nR=8

nT=n

R=4

nT=n

R=2

Characteristics of Rayleigh Fading ChannelsCharacteristics of Rayleigh Fading Channels

Distributions of K H

We can show that as :

1...

p s sm

H K 1...

p s s§

H Q

gp! RT nn

denotes convergence in mean square sense (MSS) p ... s s

and

Performance of the proposed receiver depends on and :

For a channel with high and/or threshold SNR will be high

H K H Q

H K H Q

Distributions of QH

8/8/2019 2009031848887001


Simulation Results: Hard DecisionSimulation Results: Hard Decision

Number of transmit and receive antennas: 16!! RT

nn

Block Size: for simulation, for analysis1

! PFE EST:

2048! N g! N

Legend

EST-genie: genie-aided receiver

with ideal ST-EST.

F : (Normalized) Fourier transform matrix

-10 -5 0 5 10 1510

-4

10-3

10-2

10-1

100

Simulation

Anaysis

BER

SNR per bit (dB)

EST-genie

5th iter.

1st iter.

2nd iter.

8/8/2019 2009031848887001


-10 -5 0 5 10 1510

-4

10-3

10-2

10-1

100

Simulation Results: Soft DecisionSimulation Results: Soft Decision

Number of transmit and receive antennas: 16!! RT

nn

Block Size: 1

! PFE EST:2048! N

Legend

- CONV-MMSE: conventional MMSEreceiver without an EST

- CONV-ODF: conventional ordereddecision-feedback receiver without anEST

- CONV-genie: conventional genie-aidedreceiver without an EST

- EST-genie: genie-aided receiver with the ideal ST-EST.

EST-genie

CONV-genie

CONV-MMSE

CONV-ODF

1st iter.2nd ± 5th iter.

BER

SNR per bit (dB)

8/8/2019 2009031848887001


-5

0

5

10

15

20

25

30

C O N V - O D F

Ha rd decision (5th iter.)

Soft decision (5th iter.)

EST-gen ie

Simulation Results: Performance versus number of antennasSimulation Results: Performance versus number of antennas

410

R equires SNR/bit/antenna to achieve BER = for different number of antennas

Number of antennas, RT nn !

Required

SNR/bit/antenna

(dB)

42 8 16

8/8/2019 2009031848887001


Contents




Selective Channels

Why EST? Spreading in Time and Frequency Domain



Simulation Results



52

8/8/2019 2009031848887001



Selective both in time and frequency

Matrix form:

53

Channel response at time n and lag l

8/8/2019 2009031848887001


Doubly Selective Channels

Frequency domain:

Time domain:

54

Diagonal Off-diagonal

Circulant Matrix

Inter-carrier Interference (ICI)

(d-k)th Doppler freq. component

0th Doppler freq. component

Off-diagonal Matrix

Inter-symbol Interference (ISI)

8/8/2019 2009031848887001


Summary

OFDM has perfect spreading in time, but no spreading in frequency

SC-FDE has perfect spreading in frequency, but no spreading in

time

For uncoded systems, the BER performance is in the order of

EST Based Modulation > SC-FDE > OFDM

EST based modulation spreads the symbol energy in both time- and

frequency domain

Increases reliability of feedback signal

Enables iterative signal detection without employing channel

coding

Performs close to MFB

Can be extended to doubly selected and MIMO channels55

8/8/2019 2009031848887001


References

T. Hwang and Y. (G.) Li, Novel iterative equalization based on energy spreading transform, IEEE Trans. Signal Processing vol. 54, no. 1, pp. 1

90-203, Jan. 2006.

T. Hwang and Y. (G.) Li, Energy spreading transform based iterative

signal detection for MIMO fading channels, IEEE Trans. Wireless

C ommunications , vol. 5, no. 7, pp. 1746-1756, July 2006.

T. Hwang and Y. (G.) Li, Optimum filtering for energy spreading

transform based equalization, IEEE Trans. Signal Processing, vol. 55,

no. 3, pp. 1182-1187, March 2007.

T. Hwang, Y. (G.) Li, and Y. Yuan-Wu, Energy spreading transform for

down-link MC -C DMA, IEEE Trans. Wireless C ommun., vol. 7, no. 5, pp.

1522-1526, May 2008.

Date post:	10-Apr-2018
Category:	Documents
Upload:	bebiboo
View:	218 times
Download:	0 times

2009031848887001

Documents