New Approaches To Next Generation Communication: Cross

Wireless Mobile Communication and Transmission Lab. (WMCT)

New Approaches To Next Generation

Communication:

Cross Layer Design and IDMA

Xiaotian Zhou

School of Inform. Sci.& Eng.

Shandong University

Aug.24.2010

A joint work by Dongfeng Yuan, Haixia Zhang, Yanbo Ma and Xiaotian Zhou∗


Contents

Background

CLD in the Next Generation Communication

Concept of Cross Layer Design

CLD in Multi-media Sensor Network

CLD in Vehicular Communication Networks

IDMA in the Next Generation Communication

Concept of IDMA

IDMA in Cognitive Radio Network

Other Related Work


Next Generation Communication

Demands of NGC:

Broadband Transmission

Multi-media Transmission

Supporting High-speed UT

Ubiquitous Experience

Research on NGC

Novel Network Framework

Cognitive Radio, Cooperative Network, WSN, WiMAX ......

Novel Methodology or Technology

Cross Layer Design, IDMA, OFDM, Network Coding55


Contents

Background






Concept of IDMA


Other Related Work



Why Layered?

Simplify the network protocol

design

Avoid the information exchange

between different layer

Facilitate the interconnection

of different devices

Portability in different scenario Physical

Data Link

Network

Transport

Session

Presentation

Application

The original model is proposed for wired networkThe original model is proposed for wired network



Drawbacks:

Not suitable for time-varying wireless scenario

Independently optimization in one layer with respective to its

output might lead to a counterproductive results to the other layer

Example:

Packet loss due to fading effect in wireless scenario may be

incorrect treated as congestion in traditional TCP protocol

TCP Sender TCP ReceiverBase Station

Wired

Networks

TCPWireless

link

??



Top down CLD

Bottom up CLD

Composite CLD

Physical

Data Link

Network

Transport

Application

Bandwidth、、、、BER

Bottom up

Optimal Transmit

Strategy

Physical

Data Link

Network

Transport

Application

Top-down

QoS Demand

Resource

Allocation

Minimize Cost

Physical

Data Link

Network

Transport

Application

Optimization Decision

Parameter

Parameter



Cross Layer Model

Effective capacity:

describe the queuing behaviors at data link layer

characteristic the maximal arrival rate which can be supported under

guaranteed delay QoS requirements

Mathematical expression

1[ ]1

( ) lim log [ ]t

kS k

Ct

E E et

θθ

θ=

−

→∞

∑= − [ ]S k denotes the service process

θ denotes the delay QoS exponent

max

maxPr ( ) .D

D t D eθ µδ ε∗−≥ ≈ ≤

δ µ

ε

non-empty probability of the buffer at link layer

maximum delay bound violation probability

rate of source traffic flow



Cross Layer Model

Physical layer

－resource allocation

Data link Layer

－queuing

Cross Layer information

－effective capacity

QoS requirement

－QoS exponent

－delay bound violation probability



Challenge in Multi-media Sensor Network

Power constraint at nodes

Read-time transmission requirement

Scenario consideredClustered single hop network

MAC：TDMA

∗

∗ “POWER-EFFICIENT RESOURCE ALLOCATION WITH QOS GUARANTEES FOR TDMA FADING CHANNELS”

accepted by Wireless Communications and Mobile Computing



Resource Allocation

Extend network life: reducing power dissipation while

fulfilling the delay QoS requirement of multimedia flow

Improve the network capacity：increase

the network throughput with QoS requirements

Maximizing the effective capacity with given power constraints

Minimizing the average transit power while satisfying delay QoS requirements

Dual

Problem



Problem Formulation

The resource allocation is formulated as a constrained optimization

problem

Optimization objective: minimizing the average transmit power of

sensor node

Constraints

Effective capacity: delay QoS constraint

Slot constraint

( )

( )( ), ( )

(

1

(

1

)

)

(

/ )argmin E ,

1 s.t. log E , 1,..., ,

( ) 1.

( )2 1

τ h r h

h

h hh

h

k

k k

k

K

k

r

k

k

K

k

r

k

k

k

h

e E k K

τ

θ

θ

τ

τ

=

−

=

− ≥ =

−

≤

∑

∑

Objective FunctionObjective FunctionObjective FunctionObjective Function

ConstraintsConstraintsConstraintsConstraints



To minimize the power while fulfilling QoS requirements

Dual function

Dual problem：to maximize the dual

function

Subgradient iteration algorithm

Release the time constraint

Dual problem Resource allocation for each node

Subgradient iteration

algorithm

Release Qos constraints and obtain the partial lagrangian

function

Resource allocation for the given fading state

Dual decomposition

Lagrangian dual technique

Algorithm Flow Chart

Outer iterationInner iteration



Rayleigh fading channel and

The joint power and time allocation to minimize the average power while fulfilling the given delay QoS requirements

The power and time allocated to user 2 is larger than those of user 1 under the same channel conditions.

1 22, 3θ θ= =

(a) (b)



The average total power versus delay QoS exponent

The average total power increase with QoS exponent

Symmetry

1 2 , θ θ



21( ) log (1 ( )/ ( ))

( ), ( )

1

1argmax log E ,

s.t. E[ ( )] , 1,..., ,

( ) 1.

h h h

τ h p h

h

h

K

k k k kkh p

k k

K

k

k

e

p Q k K

θ τ τ

θ

τ

=− +

=

∑− ≤ =

≤∑

Problem FormulationThe resource allocation is formulated as a constrained

optimization problem

Optimization objective: maximizing the effective capacity of

network

Constraints Power constraint of each node

Objective FunctionObjective FunctionObjective FunctionObjective Function

ConstraintsConstraintsConstraintsConstraints



To maximize the effective capacity power while fulfilling power

constraints

Dual function

Dual problem：to maximize

the dual function

Subgradient iteration algorithmRelease the time constraint

and obtain the partial lagrangian function

The optimal power and slot allocation

Release Qos constraints and obtain

the partial lagrangian function

Resource allocation for the

given fading state

Lagrangian dual technique

Outer iterationInner iteration



Rayleigh fading channel

The effective capacity versus QoS exponent

The effective capacity converges to a nonnegative constant



Network scenario

downlink channel of V2I communications

Physical layer：OFDM/OFDMA

Resource allocation

allocate sub-carriers to minimize the total power

consumption while still satisfying the given delay

aware QoS constraints of specified application.

∗

∗ “Quality-of-Service Driven Power, Bit and Subcarrier Allocation Policy for Vehicular Communication Networks”,

accepted by IEEE Journal on Selected Areas in Communications (JSAC)



Cross-layer framework



Problem formulation

The resource allocation is formulated as a constrained

optimization problem

Optimization objective: minimizing the transmit power of basestation

Constraints

QoS requirements; Subcarrier

( )

,

,

,

,1 ,

,

1 2

1min E 2 1 ,

1 s.t. log E , ,

0, , ,

... 1, 2,..., ,

,

k n

k k nk

k f k nn k

KC

Ck n k n

T B Ck

c

k

k n

K

i j

e E k

C k n

i j

θ

α

θ∈Ω

Ω= ∈Ω

−

−

∑ − ≥ ∀

≥ ∀

Ω Ω Ω ⊆

Ω Ω ∅ ≠

∑∑

U U U

I = .

0-1 integer programming problem



Time-sharing

Time-sharing: release the integer variable

With two new variables the problem is converted into a

convex optimization problem,

,

, ,

,

,

, 1 1 ,

K

k,n

k=1

,

,

argmin E 2 1 ,

s.t. E ,

1, ,

0, , ,

0 ,

k n

k n

k n k n

fkk k nn k k c

RK

k n

R k n k n

T BC

E

k n

k n

e e

n

R k n

k n

ρ

ρ

θ θ

ρ

α

ρ

ρ

∈Ω

= =

− −

−

∑ ≤

= ∀

≥ ∀

≤ ≤ ∀

∑∑

∑

1, .

Time-sharing：

• Time sharing factor

•

,k nρ

, , ,k n k n k nR Cρ=



,

,

,

K,

, , , k,n

1 1 1 k=1,

, ,

1 1 1

( , , , , ) 2 1 1

,

k n

k n

fkk k nn k k c

RK

k n

k n k n k n k n n

k n nk n

T BK K CE

k k n k n

k k n

L R E

E e e R

ρ

θ θ

ρρ λ µ ξ µ ρ

α

λ ξ∈Ω

= = =

− −

= = =

= − − −

∑ + − −

∑∑ ∑ ∑

∑ ∑∑

To minimize the power while fulfilling

QoS requirements

Release Qos constraints and obtain

the lagrangian function

Sub-carrier Allocation Algorithm

, , ,

,

( , , , , )0. (1)

k n k n k n k n

k n

L R

R

ρ λ µ ξ∗

∂=

∂

,, , ,

, ,

0, if (0,1)( , , , , ). (2)

0, if 1

k nk n k n k n k n

k n k n

L R ρρ λ µ ξρ ρ

∗

∗ ∗

= ∈∂

∂ < =

KKT optimality conditions

The optimal power policy

KKT (1)

KKT (2)



Minimized power versus the delay QoS exponentt

The performance gain in power efficiency increases with the QoS

exponent

Subcarrier ，user

Subcarrier bandwidth

32 = 2K =

10 kHz, 2 ms fB T= =



The performance gain in power efficiency increases with the QoS

exponent

10-5

10-4

10-3

10-2

10-5

10-4

10-3

10-2

20

20.5

21

21.5

22

θ1

θ2

Min

imiz

ed P

ow

er (dB

)

10-5

10-4

10-3

10-2

10-5

10-4

10-3

10-2

20.2

20.3

20.4

20.5

20.6

20.7

θ1 θ

2M

inim

ized

Pow

er (dB

)

S NRmax

b as ed O P A P ro p o s ed A lgo rithm


Contents

Background






Concept of IDMA


Other Related Work


Concept of IDMA

Interleave Division Multiple Access

Interleaver is the mean to distinguish different user

Low cost detection based on Gaussian approximation

SCM & High spectral/power efficiency


Gaussian Approximated Detection

Estimate:

Decode:

Concept of IDMA

1

( ) ( ) ( ) ( )K

k k k k k

k

r j h x j n h x j jζ=

= + = +∑

( ) ( ( ))( ) 2

( ( ))

kESE k

k

r j E je j h

Var j

ζζ

−= ⋅

Gaussian

Approximation

1( ( )) ( ( ( ))) ( ( ))DEC ESE ESEe x j C x j x jλ λ−= −


IDMA in Cognitive Radio

Cognitive Radio Scenario

Overlay

Underlay:Primary User (PU) and Secondary User (SU) cannot coexist on

the same frequency

Challenges

There exists certain interference period due to the

delay of sensing

SU link is easily interrupted by the re-appearance of

PU

∗ “A Novel IDM-CORVUS Model in Cognitive Radio”, proc. of IEEE International Symposium on Communication and

Information Technology (ISCIT), Sep.28-30 2009

∗

“A Novel IDM-CORVUS Model in Cognitive Radio”, proc. of IEEE International Symposium on Communication and

Information Technology (ISCIT), Sep.28-30 2009



CORVUS Model Sub-channel of one SU link should be scattered among different F-bands

Save redundant sub-channels to keep the maintenance of SU link



Drawbacks of CORVUS

Heavily loaded scenario: no longer effective to

alleviate the mutual interference

Spectrum waste: Reserving redundant sub-channels

The Narrow bandwidth of sub-channels

Orthogonal MA Scheme Non-orthogonal MA SchemeOrthogonal MA Scheme Non-orthogonal MA Scheme



IDM-CORVUS Broadband property of IDMA: the secondary user enjoys the whole

bandwidth of these F-bands

Reserving redundant interleavers: keep the SUL maintenance during PU

reappearance without introducing the spectrum waste



SU link:

Each SU is equipped with L interleavers, where L is the number of

available F-bands.

: the number of redundant interleavers.

: modulation factor due to the l-th F-band

redL

1

( ) ( ) exp( )redL L

k l l

l

x j x j iθ−

=

= ⋅∑

exp( )liθ



Tradeoff between Reliability and Throughput

: Multiplexing factor

Reliability: Sending same data stream through M layers

Throughput: Sending different data through N layers

( )

1 ( ) 1

( ) ( ) exp( ) ( ) exp( )red red

red

L L L L

k m m n n

m n L L

x j x j i x j iα

α

θ θ− −

= = − +

= ⋅ + ⋅∑ ∑

α



Simulation Results Rate of repetition

code=1/32

Iteration number 15

Equal power allocation

3 interleavers per user

1 redundant interleaver

per user


Contents

Background






Concept of IDMA


Other Related Work


Other Related Works

Books:

“Cross Layer Design: From Theory to Application”

(Chinese Version), published by posts & Telecom

Press.

Papers:Game theoretic CLD in Multi-media Sensor Network

"Optimal and Fair Resource Allocation for Multiuser Wireless Multimedia Transmissions," EURASIP Journal on Wireless Communications and etworking, 2009.

“Co-opetition Strategy for Collaborative Multiuser Multimedia Resource Allocation,”EEE ICC2009, Dresden, Germany, June 2009.

“Novel Coopetition Paradigm Based on Bargaining Theory for Collaborative Multimedia Resource Management,” IEEE PIMRC 2008，Cannes，France

“A Cross-Layer Transmission Scheduling Scheme for Wireless Sensor Networks”,Computer Communications, 21 June 2007


Other Related Work

Papers: CLD in Cognitive Radio

“Co-opetition Strategy Based on Kalai-Smorodinsky Bargaining Solution for

Spectrum Sharing in Multicarrier Cognitive Radio Systems ,“ submitted to IEEE

Trans. on Vehicular Technology

IDMA in Cooperative Network “A Multi-source Cooperative Scheme based on IDMA aided Superposition

Modulation”, submitted

IDMA in Common Frequency Network

Inter-cell interference cancellation


Thanks

For Your Attention!

Contact info.:

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WMCT.Lab Website http://202.194.20.8/

Documents

New Approaches To Next Generation Communication: Cross