Hayar Presss5g 2014 f

Cross-Layer Design for Spectrum- and Energy-Efficient Wireless Networks

By Prof. Aawatif Hayar GREENTIC/ENSEM, University Hassan II Casablanca Morocco

SS5G Hammamet Tunisia, March 16-18 2014

Philosophy Nous n'hritons pas de la terre de nos parents, nous l'empruntons nos enfants. par

Antoine de Saint-Exupry

Dr. Aawatif HAYAR, GREENTIC, Univ Hassan II Casablanca, Morocco

GREENTIC Initiative


Context


Challenges


Opportunities


By Btechkaboss (slideshare)

1111stststst GENERATION:GENERATION:GENERATION:GENERATION:

Introduced in 1980

Analog cellular mobile,Data speed

2.4kbps

1G mobiles- AMPS,NMT,TACS

Uses FDMA technique with

30KHz

2222ndndndnd GENERATION:GENERATION:GENERATION:GENERATION:

Digital cellular systems

Digital modulation schemes-

TDMA,CDMA

Data speed in 2g is up to 64kbps

Data speed in 2.5g is up to

144kbps

GPRS, EDGE and CDMA 2000 were

2.5 technologies.

3333rdrdrdrd GENERATION:GENERATION:GENERATION:GENERATION: 3g technology is intended for true

multimedia cell phone

typically called smart phones and

features increased bandwidth and

transfer rates to accommodate

wed-based applications and

phone-based audio and video files

AdvantagesAdvantagesAdvantagesAdvantagesuniversal global roaming

multimedia (voice , data & video)

384 kbps while moving

2mbps when stationary at specific l

locations

video calling

4444thththth GENERATION:GENERATION:GENERATION:GENERATION:

high-speed data access

high quality streaming

video

combination of wi- fi and

wi-max

SDR,OFDM,OFDMA

and MIMO

WHAT IS 5G???WHAT IS 5G???WHAT IS 5G???WHAT IS 5G???

5G is a packet switched wireless system with wide area coverage and high throughput.

5G wireless uses OFDM and millimeter wireless that enables data rate of 1Gbps and frequency band of 2-8 GHz.

OBJETIVES OF 5G:OBJETIVES OF 5G:OBJETIVES OF 5G:OBJETIVES OF 5G:

5G being developed to accommodate QoS rate requirements

set by further development of existing 4G applications.

Flexible channel bandwidth between 5 and 20MHz,

optionally up to 40MHz.

Data rate of 1Gb/s between any two points in the world.

Increase system spectral efficiency of up to 3bit/s/Hz/cell

in the downlink and 2.25bit/s/Hz/cell for indoor usage.

STANDARD WIRELESS 5G:STANDARD WIRELESS 5G:STANDARD WIRELESS 5G:STANDARD WIRELESS 5G:

WiMAXWiMAXWiMAXWiMAX formed to provide conformance and interoperability of the IEEE 802.16 standard. It aims to provide wireless data over long distance from point-to-point link to cellular mobile type access.

WiBROWiBROWiBROWiBRO a part of IEEE 802.16e in process to provide collaborative and generic mobile WiMAX.

3GPP LTE 3GPP LTE 3GPP LTE 3GPP LTE a project aims to improve the mobile phone standard to cope with future requirements.

5GPP 2 UMB5GPP 2 UMB5GPP 2 UMB5GPP 2 UMB a project to improve the CDMA2000 mobile phone standard for next generation applications.

5G NETWORK REFRENCE MODEL:5G NETWORK REFRENCE MODEL:5G NETWORK REFRENCE MODEL:5G NETWORK REFRENCE MODEL:

IPv6 SUPPORT:IPv6 SUPPORT:IPv6 SUPPORT:IPv6 SUPPORT:

IPv6 increases the IP addresses size from 32bit to 128 bits, to support

more levels of addressing hierarchy and much greater number of

addressable node.

IPv6 support large number of wireless enabled devices.

IPv6 Extend the IP address space enough to offer a unique IP address

to any device.

IPv6 Improve support for IP Mobility.

BENEFITS OF 5G:BENEFITS OF 5G:BENEFITS OF 5G:BENEFITS OF 5G:

High speed, high capacity, and low cost per bit.

Support interactive multimedia, voice, streaming video, Internet, and other broadband services

Global access, service portability, and scalable mobile services.

The high quality services of 5G technology based on Policy to avoid error.

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects.

This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure.


Green Cellular Networks

Green cellular networks


Green cellular networks ARCHITECTURE: ENERGY SAVINGS IN BASE STATIONS:

Improvements in Power Amplifier: There are three essential parts of a BS: radio, baseband and feeder. Out of these three, radio

consumes more than 80% of a BSs energy requirement, of which power amplifier (PA) consumes almost 50%

Power Saving Protocols: Exemple: DRX and DTX

Energy-Aware Cooperative BS Power Management cell-breathing

sleep mode

Using Renewable Energy Resources: biofuels,

solar

wind energy


IT greening the world

Green IT in Smart Grids

Energy management and efficiency:

Energy as a service concept

New ICT-Based Architecture for Energy Management and Energy as a Service Concept in Smart Grids by B. Sendama, A. Hayar and S. Bouferda, ICEER2013 23

Some examples from Computer

Science fieldGoogle wins floating data center patent; April

30th, 2009Google has been awarded a U.S. patent for its floating data centers. The data

center could be powered and cooled by the ocean, and these offshore data

centers could sit 3 to 7 miles offshore.


Energy Efficient Software Design

Windows 8 Power Saving features: up to 30%

energy saving


Energy Efficient Concepts and

architecturesVirtualization:

Save Energy by Reducing Server Underutilization

Source: Sustainable Energy New Zealand, May 2007


Energy Efficient Cloud based Solutions

Cloud-Controlled Energy Saving From Google

And Ford


Green IT for Health :

Electromagnetic Field Reduction

explosive increase in the use of mobile devices, Technology advances and consumers demands have transformed mobile terminals, from simple voice call terminals, to rich multimedia applications platforms, providing various services including: internet access, video teleconferencing, GPS localization, high quality audio and video.

=> two key impacts:health effectsthe battery lifetime for mobile devices.

Therefore, minimizing the power consumption of wireless platforms becomes a great challenge, for the entire Information and Communication technologies (ICTs), at all system levels.

Motivation


Cognitive radio : CR/Users interaction

Beamforming to avoid head

Heterogeneous Networks: Switching the network in dependency of the service used by the device

can improve energy efficiency.

Power saving protocols: it minimizes energy usage while meeting delay-tolerance deadlines

specified by users.

Some proposed solution in the literature


A fundamental parameter for discussing the health risks of

electromagnetic field power absorption in the human head is the specific

absorption rate (SAR)

It also can be defined through mathematical approach as the equation

below with the units Watts per kilogram, W/kg .

SAR =E /

Health effect of electromagnetic radiation

When this limit of SAR is exceeded or only reached, it produces human

health effects that can cause :

reverse cell membrane polarity, alter brain waves, damage DNA, and leads

to cancer and memory loss.

However, mobile phones are designed with low power and operate at high frequency where the value of SAR is lower than the limit that stated by International Commission on Non-Ionization Radiation Protection (ICNIRP). So the examples given remain somewhat rare, however there are other consequences of electromagnetic radiation of mobile phones which are very frequent such as : heating, headache, fuzziness of the view, fatigue and nausea.

Health effect of electromagnetic radiation


Cognitive radio


Lets Start from the beginning...


Currently, the radio spectrum is beginning to be crowded due to the rapid growth of wireless technologies this century. However, many studies show that the major licensed bands are underutilized and some of the remaining bands are heavily used. This fact leads to spectrum wastage.

Hence, cognitive radio has become an important research topic in these last years since it tries to take advantage of the unused spectrum by the licensed users, while causing a minimum level of interference in the licensed bands.

Motivation


Mitola coined the term Cognitive Radio (CR) in his work published in 1998 Mitola defined CR as a radio that employs model based reasoning to

achieve a specific level of competence in radio-related domains Haykin : an intelligent wireless communication system that is aware of its

surrounding environment (i.e., outside world), and uses the methodology of understanding-by-building to learn from the environment and adapt its internal states to statistical variations in the incoming RF stimuli by making corresponding changes in certain operating parameters (e.g.,transmit-power, carrier frequency, and modulation strategy) in real-time, with two primary objectives in mind: Highly reliable communications whenever and wherever needed. Efficient utilization of the radio spectrum.

The FCC gave the following definition on cognitive radio [795]. A cognitive radio is a radio that can change its transmitter parameters based on interaction with the environment in which it operates.as radio systems that continuously perform spectrum sensing, dynamically identify unused (white) spectrum, and then operate in this spectrum at times when it is not used by incumbent radio systems.

Definition of cognitive radio


1) Radio-scene analysis, which encompasses the following: estimation of interference level of the radio environment

detection of spectrum holes.2) Channel identification, which encompasses the following:

estimation of channel-state information (CSI); prediction of channel capacity for use by the transmitter

3) Transmit-power control and dynamic spectrum management.

Cycle of cognitive radio


Temporal spectrum holes mean that there is no signal coming from primary users over the band of interest during the sensing time. So that, the secondary users can use that spectrum band while the primary signal is absent. In such a case, the secondary users are located inside the coverage area of the primary transmitters.

Spatial spectrum holes mean that spectrum band of interest is busy by the primary transmitter but only in a restricted area. In other words, this spectrum band will be able to be used by secondary users being outside of this restricted area. Nevertheless, the secondary transmission is only allowed if the signal does not interfere with the primary receivers inside the coverage area.

Frequency spectrum holes are defined as a frequency band in which a secondary user can transmit without interfering with any primary receivers across all frequencies.

Spectrum holes


1. Sensing: Efficient spectrum sensing techniques which provide continuous monitoring of the spectrum with lower sensing time.

Matched filter detection

Energy detection Cyclostationarity

2. Interference management and Resource allocation: 1. DSA methods able to adapt to the fluctuating nature of the

cognitive radio system and allocate the bandwidth accordingly.

2. Interference management

Cognitive radio main research axes


Two networks with different priorities

Primary network : owner of the spctrum

Secondary network : trying to access the spectrum in a opportubistic way

without causing harmful degradation to the PS

Requirement :

High reactivity for the sensing

Flexible Ressource allocations

CR scenarios:

Primary versus secondary networks


No one is owner of the spectrum (no licensed band )

No Secondary system

This model works with a shared spectrum among devices. All the devices have the same priority to access communication services and they must share the spectrum through techniques such as cooperation or just co-existing. According to the sharing technique it is necessary for a protocol to manage the spectrum.

Different approaches: Sensing + Ressource allocations

Interference Management + Ressource allocations

CR scenarios:

Open opportunistic access


As the performance of the primary system must fulfill always the requirements of the policies and regulatory bodies, the interference management in cognitive systems has become an important issue.

the cognitive users must be aware of the interference generated at primary receivers

Depending on the level of the generated interference, the performance of the primary system can be negatively affected. Therefore, the harmful interference should be controlled by the secondary users using different techniques.

interference management in cognitive

radio systems


when the secondary users are trying to access the primary resources they should choose which channel, QoS and which scheme to use.

All the cognitive users must follow some procedures to determine whether the access to some spectrum resource is feasible or not :

sensing the spectrum in order to identify available spectrum opportunities

spectrum allocation which will depend on the internal different (cognitive system itself) spectrum allocation policies as well as external (licensed service)

Interference management:

spectrum sharing techniques


spectrum access.(There must be some protocol able to manage this spectrum allocation) -> radio Resource management entity

The capability of changing the used spectrum resource quickly must be available as well, it means using another free spectrum resource preserving a minimum QoS for the unlicensed system

The current spectrum sharing techniques can be divided into different classes, according to the architecture of the cognitive system, the spectrum access technique...

Interference managment :spectrum

sharing techniques


Spectrum access technique: Interweave: the CS does not transmit overall time slot because it uses

a part of time for "spectrum sensing" to make a decision on primary

signal presence and starts transmission only when PS is absent

Underlay: SU and PU can access the spectrum simultaneously. Once

the spectrum allocation has been made, some advanced techniques

such as spread spectrum techniques can be used in order to spread

the transmitted power under the noise or at primary receivers,

avoiding then their harmful interference.

Overlay: In this approach, there is a cooperation between the primary

and the secondary systems. The CS decodes partially or totally the PS

and uses this information to transmit while avoiding interference with

the primary. The PS ca, also act as a relay for the PS

Interference management in cognitive

radio systems


Interweave

Overlay

Underlay

Source B. Kouass Theisii

Architecture :

Centralized spectrum sharing : A centralized entity controls the allocation and access procedures . The cognitive users send the information to the main entity that

Distributed spectrum sharing: The users decide by themselves when they can access the spectrum according to the policies.

Interference managment :

centralized versus distributed spectrum sharing

techniques


Spectrum sensing


General Cognitive Radio Network


Recent trends


Spectrum sensing techniques

Energy detection

Cyclostationary Feature setection

Data aided based detection

Features detection (Sub space)

Compressed sensing

Spectrum sensing goal


Model selection using Kullback-Leibler

distance


Akaike Information Criterion


Blind sensing based on dimension

using model selection toolsThe received signal, denoted by the q x1 complex vector x, can be modeled as:

Patent: A. HAYAR "Process for sensing vacant bands over the spectrum bandwidth and apparatus

for performing the same based on sub space and distributions analysis. European

patent 08368002.5, Submitted on 2007 and accepted on 2008.


using model selection tools

Because the noise is zero mean and independent of the signals, it follows that the covariance matrix of x(t) is given by:


using model selection tools

From our covariance matrix model given by equation (2), let us consider the following family of covariance matrix :

Blind sensing based on Dimension

estimation


Model selection using AIC


Dimension estimation detector (DED)


Dimension Estimation DetectorDED: Dimension Estimation Detector based on Subspace analysis and model

selection tools such as Akaike Information Criterion (AIC)

Detection rule

Detection Threshold

F2 denote the cumulative density function (CDF) for the distribution of

Tracy-Widom 62

Blind sensing based on distribution

analysis and model selection tools


Distribution analysis detector (DAD)


Distribution Analysis DetectorDAD: Based on Kullback-Leibler distance and Akaike weights

Detection rule

Detection Threshold

where G denotes the Meijer G-function

B. Zayen and A. Hayar, "Dimension estimation-based spectrum sensing for

cognitive radio" EURASIP Journal on Wireless Communications and Networking (JSAC)

2012, 2012 :64 February 2012. 67

Spectrum Discountinuities Detection using

Algebraic Method: Algebraic Detector

The sensing algorithm is based on the following steps:

Modeling the spectrum as a piecewise polynomial.

Expressing the discontinuities properties in frequency domain.

Transferring the equations to the Laplace domain

Back to the frequency domain, the problems solution is casted as a

filtering by N+1 filters.

Computing the threshold and making the decision on each sensed

sub-and.

Wael Guibene, Monia Turki, Bassem Zayen, Aawatif Hayar " Spectrum sensing

for cognitive radio exploiting spectrum discontinuities detection" EURASIP Journal

on Wireless Communications and Networking (JSAC) 2012, 2012 :4 January 2012. 68

Spectrum Discountinuities Detection using

Algebraic Method: Algebraic Detector

Spectrum Discountinuities Detection

using Algebraic Method: Algebraic

Detector

Performance comparison for low

complexity Blind spectrum sensing

techniques

Probability of detection vs. SNR for the three detectors: energy detector (ED), distribution analysis

detector (DAD) and algebraic detector (AD) with PFA = 0.05 and N = (1, 3) for a DVB-T primary user

system with Rician channel.

73

Combined Compressed Sensing and

Distribution Discontinuities Detection

Approach to Wideband Spectrum Sensing

Compressive sensing makes possible the reconstruction of a sparse signal by

taking less samples than Nyquist sampling, and thus wideband spectrum sensing is

then doable.

74

Simulations


Complexity

Blind cyclostationary feature detector

Z. Khalaf, A.Nafkha et J. Palicot Blind cyclostationary feature detector based on sparsity hypotheses for cognitive radio

equipment", The 54th IEEE International Midwest Symposium on Circuits and Systems, Seoul, Korea, Aout 2011

Cognitive Orthogonal Spectrum pooling:

Principle The objective is to enhance spectral efficiency by

overlaying a new mobile radio system on an existing one

without requiring any changes to the actual licensed

system.

Idea: exploit primary system fading and operate cognitive

transmission during the voids

Spectral efficiency gain 81

Cognitive Orthogonal Spectrum

Pooling: Performance

[HHD08] Haddad, Majed ; Hayar, Aawatif ;Debbah, Merouane, "Spectral efciency

of spectrum pooling systems", IET Special Issue on Cognitive Spectrum Access,

July 2008, vol. 2, No. 6, pp. 733-741. 82

Cognitive Spectrum Sharing based on outage

probabilty criterion The objective is to maximize the total SU throughput under interference and noise

impairments, and binary power constraints while preserving the QoS of the

primary system.

Trying to transmit as much information for itself as possible,

Maintaining the primary users outage probability unaffected.

Bassem Zayen, Majed Haddad, Aawatif Hayar and Geir E. ien,"Binary

Power Allocation for Cognitive Radio Networks with Centralized and Distributed User

Selection Strategies", Phycom Journal, ELSEVIER vol.1 Issue 3, 2008. 83

Vandermonde Frequency Division

Multiplexing: VFDM

VANDERMONDE FREQUENCY DIVISION MULTIPLEXING FOR COGNITIVE RADIO by Leonardo S.Cardoso,

Mari Kobayashi, yvind Ryan and Merouane Debbah

Spatial Interweave Technique

B. Kouassi, B. Zayen, R. Knopp, F. Kaltenberger, D. Slock, I. Ghauri, F. Negro and L. Deneire. Design and Implementation of Spatial Interweave LTE-TDD Cognitive Radio Communication on an Experimental Platform. IEEE Wireless Communications

Magazine : Next Generation Cognitive Cellular Networks.

Cross Layer Design Approach


Crosslayer Design

Application

Network

Access

Link

Hardware

Delay Constraints

Rate Constraints

Energy Constraints

Adapt across design layers

Reduce uncertainty through scheduling

Provide robustness via diversity

Source Lecture from Pr A.Goldsmith

Cross layer design impacts

Technology Enhancements

Hardware: Better batteries. Better circuits/processors.

Link: Antennas, modulation, coding, adaptivity, DSP, BW.

Channel acess (MAC) : Retransmissions, delay,

Network: Dynamic resource allocation. Mobility support.

Application: Soft and adaptive QoS.

Source Lecture from Pr A.Goldsmith

3/17/2014 94

Radio interface protocol architecture

around the

physical layer FDD

L3c

o

n

t

r

o

l

c

o

n

t

r

o

l

c

o

n

t

r

o

l

c

o

n

t

r

o

l

LogicalChannels

TransportChannels

C-plane signalling U-plane information

PHY

L2/MAC

L1

RLC

DCNtGC

L2/RLC

MAC

RLCRLCRLC

RLCRLCRLCRLC

Access Stratum

BMC L2/BMC

control

PDCPPDCP L2/PDCP

RadioBearers

RRC

Non Access Stratum

Cross-layer Techniques

Adaptive techniques Link, MAC, network, and application adaptation Resource management and allocation (power control) Synergies with diversity and scheduling

Diversity techniques Link diversity (antennas, channels, etc.) Access diversity Route diversity Application diversity Content location/server diversity

Scheduling Application scheduling/data prioritization Resource reservation Access scheduling

Joint MAC and routing solution

Use the same MAC for directional antennas, but transmit RTS

over multiple hops (MMAC protocol)

If source 1 wants to communicate with node 6 transmits a forwarding RTS with the profile of node 6, using DO links

when node 6 gets the RTS, it beamforms in the direction of 1, forming a

DD link

Transmission from 1 to 9 on DD links requires only 2 hops

Performance Evaluation

CLD Routing based approach

Luigi & al.

Routing in wireless network

Shortest path approche is not always optimal

Physical channel is instable

Each transmission injects interference in the

network

Interference reduce capacity

Power management is needed

Make use of multi-rate and power control

Cross Layer approch

Maximise throughput

Gupta & Kumar

Throughput

Node number

Transmission range

Rate

To maximise throughput we have to maximise transmission rate

and reduce interference generated by each packets

Capacity Constraints

Cross-Layer Approach

SIR

Interface characteristics

Next-Hop

Data-Rate

Transmission power

Routing metricRateInterferencePacket Error Rate

Interference

Measurement: unrealistic

More neighbor => More interference

More power => More interference

Defining a interference replacement function I(P)

Minimise I(P) => Minimise Real interference

Packet Error Rate (I)Packet Error Rate (I)

Packet Error Rate (III)

Sensing tools to assist energy

consumption reduction at MAC layer


Unied Framework for Congestion and Fading

Analysis and Backo Exponent Computation in

Cognitive Green Networks

Unified Framework for Congestion and Fading Analysis and Backoff Exponent Computation in Cognitive Green Networks , Mohamed Amine Sakraoui*, Aawatif Hayar*, Mohamed Sadik*, Geir E. ien+ and Changmian Wang, IEEE ISWCS2012 Paris France


Cooperative offload strategy in

heterogeneous networks for energy

consumption reduction and capacity

optimization


Basic Power Allocation strategy

Minimization of the transmit power :

For simplicity of the analysis we will consider a basic power allocation

in which we suppose that the received power at the BSs is fixed

to.

The transmit power from the ith terminal to its BS can be expressed as

following:

=

(2)

Based on our algorithm, the system will, at each location, decide to

attach the user to the BTS with the higher channel gain. Thus, the

average transmit power is expected to decrease automatically


system model

Ub

Ub

Ub

Ub

Ub

Ua

Ua

Ua

Ua

Ua

Ua

BS(B)BS(A)

,,

,,

x

y

Figure 1 : two cells in an heterogeneous network

operating at different frequencies:


= 46.3 + 33.9 ! 13.82 ' () +44.9 6.55 ' + + CM (1)

() = 3.20 11.75 4.97

CM= 0


Channel gain model used : COST-231 Hata



Expression of the capacities of the system before cooperation

C0 = C23,0 = log7 1 + SINR3,0)=

= (3)

SINR3,0 =>?,@B?@,?

C

D >?EB?E,?CFGEHIE@

J (4)

KL = KM + KM = 2 7 1 +

L 1 + P7 (7)

CQ =RC23,Q =Rlog7 1 + SINR3,Q)=

=

(5)

TUVW, = X,YX,XC

D XZYXZ,XCF[ZHIZ\ (6)



Expression of the capacities in the cooperative system:

after classifying, according to our channel gain selection criteria, we will have 4

capacities:

CAA: the sum capacity of users from cell A which remained attached to BS A

CAB: the sum capacity of users from cell A which moved to BS B.

CBB: the sum capacity of users from cell B which remained attached to BS B

CBA: the sum capacity of users from cell B which moved to BS A.

The new capacities of cell A and cell B will then be expressed as following:



CNA= CAA+ CAB

= 7 1 +

]^^F]X^_ F\C+ 7 1 +

]XXF]^X_ F\C

(8)

CNB= CBB+ CBA

= 1 +

]XXF]^X_ F\C+ 1 +

]^^F]X^_ F\C

(9)

K`L = K` + K`


Introduction to game theory:

Game theory is the study of strategic decision making.

It helps understand situations in which decision-makers interact in a complex

environment according to a set of rule [6].

Game theory is mainly used in economics, political science, and psychology, as

well as logic and biology.

Power Allocation Strategy using Game Theory tools


a formal game model for the power control can be defined as follows:

Players : are the users present in the cell.

Actions : called also as the decisions, and are defined by the transmission power allocation strategy.

Utility function: represents the value of the observed quality-of-service (QoS) for a player.

Power allocation algorithm using a game theory frameworkPower Allocation Strategy using Game Theroy tools


Utility function of the game proposed :

utility function = payoff function + price function

Payoff function : function of the transmit power level and the signal-to-noise

and interference ratio (SINR). The players SINR is a function of its own

transmit power and the transmit powers of the other players in the cell

The price function : represents the interference constraint

Power Allocation Strategy using Game Theroy tools


Capacity of the victim user k:

Where:

Capacity of the interfering users:

Where:



The interference power experienced to the mth user :

The transmit power from user m :



The protection for the victim user k:

Interference level

Power allocation algorithm using a game theory framework

is the maximum interference level that user m can generate to user k

Power Allocation Strategy using Game Theroy tools


maximisation of the utility function :



Expression of the SINR as a solution of the maximisation of the utility function:



power cell A Power cell B

Simulations


136

capacity cell A capacity cell B

Simulations


Energy efficiency and interference

management in femtocells networks


Wide coverage Short range wireless System: femtocells scenario

Isolated

terminals, link

to the nearest

femto cell

Ad hoc

cluster

Short

range

Directive

transmission

Wide range

CH

CH

Isolated

terminals,

link to the

macro cell

Femto

cell short

range

Directive

transmission

Wide range

Relaying and

cooperative

comm

Cell range

extension

138

A.HAYAR, B.ZAYEN, S.BOUFERDA, Interference Management Strategy for deploying Energy

Efficient Femtocells Network CROWNCOM 2012 Sweden.

S.BOUFERDA, A.HAYAR, B.ZAYEN, M .RIFI, Multiuser Diversity Based Energy Efficiency Optimization for Heterogeneous Wireless Mobile

Networks . RMT (Mediterranean telecommunications journal) September 2012

Secure HeNB Network Management Based VPN IPSec , A. Laguidi, A. HAYAR and M. Wetterwald NGNS 2012 Portugal

New planning approach based on Femto cells concept

Femtocells are low-power cellular base stations that operate in licensed spectrum. They are typically deployed indoors to improve coverage and provide excellent user

experience, including high data rates. Cellular operators benefit from reduced infrastructure and operational expenses for capacity

upgrades and coverage improvements. Although Femtocells may cause some interference to other users in the network.


Energy Efficiency and Interference in Femtocells

Network

Figure : N co-located femtocells (HNB) operating in the same band

We propose to combine the

cooperative protocol with

cognitive radio (CR) and

game theory approaches to

mitigate interference and

improve performance at the

same time

The Protection for primary users is ensured in a cognitive manner by the following

constraints


Average transmit power in

the femtocells networkAverage capacity in the

femtocells network

Simulations


Hayar Presss5g 2014 f

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