The innovative and effective use of information and communication technologies (ICT) is becoming increasingly important to improve the economy of the world [1]. Wireless communication networks are perhaps the most critical element in the global ICT strategy, underpinning many other industries. It is one of the fastest growing and most dynamic sectors in the world. The European Mobile Observatory (EMO) reported that the mobile communication sector had total revenue of €174 billion in 2010, there- by bypassing the aerospace and pharmaceutical sectors [2]. The development of wireless technologies has greatly improved people’s ability to communicate and live in both business operations and social functions. The phenomenal success of wireless mobile communications is mirrored by a rapid pace of technology innovation. From the second generation (2G) mobile communication system debuted in 1991 to the 3G system first launched in 2001, the wireless mobile network has transformed from a pure telephony system to a network that can transport rich multimedia contents. The 4G wireless systems were designed to fulfill the requirements of International Mobile Telecommunications-Advanced (IMT-A) using IP for all services [3]. In 4G systems, an advanced radio interface is used with orthogonal frequency-division multiplexing (OFDM), multiple-input multiple-output (MIMO), and link adaptation technologies. 4G wireless networks can support data rates of up to 1 Gb/s for low mobility, such as nomadic/local wireless access, and up to 100 Mb/s for high mobility, such as mobile access. Long-Term Evolution (LTE) and its extension, LTE-Advanced systems, as practical 4G systems, have recently been deployed or soon will be deployed around the globe. However, there is still a dramatic increase in the number of users who subscribe to mobile broadband systems every year. More and more people crave faster Internet access on the move, trendier mobiles, and, in general, instant com- munication with others or access to information. More powerful smart phones and laptops are becoming more popular nowadays, demanding advanced multimedia capabilities. This has resulted in an explosion of wireless mobile devices and services. The EMO pointed out that there has been a 92 percent growth in mobile broadband per year since 2006 [2]. It has been predicted by the Wireless World Research Forum (WWRF) that 7 trillion wireless devices will serve 7 billion people by 2017; that is, the number of network-connected wireless devices will reach 1000 times the world’s population [4]. As more and more devices go wireless, many research challenges need to be addressed.

1. A HETEROGENEOUS WIRELESS BACKHAUL
NETWORKS
USING MASSIVE MIMO AND MOBILE
FEMTOCELLS
Presented by
P.SAI KIRAN KUMAR(13751D6107)
M.Tech, Communication Systems
SITAMS.

2. Agenda
 AIM
 HETEROGENEOUS NETWORKS ?
 ARCHITECTURE
 KEY 5G WIRELESS TECHNOLOGIES
 BACKHAUL TRAFFIC MODELS
 CENTRAL SOLUTIONS
 DISTRIBUTION SOLUTIONS
 ENERGY EFFICIENCY OF BACKHAUL NETWORKS
 ADVANTAGES
 AIM
 HETEROGENEOUS NETWORKS ?
 ARCHITECTURE
 KEY 5G WIRELESS TECHNOLOGIES
 BACKHAUL TRAFFIC MODELS
 CENTRAL SOLUTIONS
 DISTRIBUTION SOLUTIONS
 ENERGY EFFICIENCY OF BACKHAUL NETWORKS
 ADVANTAGES

3. AIM
 ANY-BODY
 ANY- THING
 ANY-WHERE
 ANY-TIME
 ANY-HOW
 ANY-BODY
 ANY- THING
 ANY-WHERE
 ANY-TIME
 ANY-HOW

4. HET NET ?
 Heterogeneous networks: small cells
within macro cells
 Improve user data rate near the access point
 Offload data from the macro cell to the small cell
 Reduce transmit power (terminal and BS)
 Flexible deployment in dense areas
 Heterogeneous networks: small cells
within macro cells
 Improve user data rate near the access point
 Offload data from the macro cell to the small cell
 Reduce transmit power (terminal and BS)
 Flexible deployment in dense areas
4G Backhaul
60 GHz Small
Cell

5. ARCHITECTURE

6. KEY 5G WIRELESS TECHNOLOGIES
 Based on the well-known Shannon theory
 Bi is the bandwidth of the ith channel,
 Pi is the signal power of the ith channel,
 Np denotes the noise power.
 Based on the well-known Shannon theory
 Bi is the bandwidth of the ith channel,
 Pi is the signal power of the ith channel,
 Np denotes the noise power.

7. TO INCREASE CSUM (SYSTEM
CAPACITY)
 NETWORK COVERAGE
 HETEROGENEOUS
NETWORKS
 MACRO CELLS,
MICROCELLS
 SMALL CELLS
 RELAYS
 MFEMTOCELL
 NUMBER OF SUB CHANNELS
 MASSIVE MIMO
 SPATIAL MODULATION
[SM]
 COOPERATIVE MIMO
 DAS
 NETWORK COVERAGE
 HETEROGENEOUS
NETWORKS
 MACRO CELLS,
MICROCELLS
 SMALL CELLS
 RELAYS
 MFEMTOCELL
 NUMBER OF SUB CHANNELS
 MASSIVE MIMO
 SPATIAL MODULATION
[SM]
 COOPERATIVE MIMO
 DAS
 BANDWIDTH
 CR NETWORKS
 MM-WAVE
COMMUNICATIONS
 VLC
POWER (ENERGY-EFFICIENT OR GREEN COMMUNICATIONS).

8. MASSIVE MIMO
 Massive MIMO (also known as “Large-Scale
Antenna Systems”, “Very Large MIMO”,
“Hyper MIMO”, “Full-Dimension MIMO” and
“ARGOS”)
 In massive MIMO systems, the transmitter
and/or receiver are equipped with a large
number of antenna elements (typically tens or
even hundreds).
 Massive MIMO (also known as “Large-Scale
Antenna Systems”, “Very Large MIMO”,
“Hyper MIMO”, “Full-Dimension MIMO” and
“ARGOS”)
 In massive MIMO systems, the transmitter
and/or receiver are equipped with a large
number of antenna elements (typically tens or
even hundreds).

9. Massive MIMO can increase the capacity 10 times or
more
 The capacity increase results from the
aggressive spatial multiplexing used in
massive MIMO
Massive MIMO increases data rate
 the more antennas, the more independent
data streams can be send simultaneously.
Massive MIMO can increase the capacity 10 times or
more
 The capacity increase results from the
aggressive spatial multiplexing used in
massive MIMO
Massive MIMO increases data rate
 the more antennas, the more independent
data streams can be send simultaneously.

10. Massive MIMO can be built with inexpensive, low-
power components
 With massive MIMO, expensive, ultra-linear 50 Watt
amplifiers used in conventional systems are replaced
by hundreds of low-cost amplifiers with output power
in the milli-Watt range
 Furthermore, in massive MIMO systems, the effects of
noise and fast fading vanish, and intracell interference
can be mitigated using simple linear precoding and
detection methods
Massive MIMO can be built with inexpensive, low-
power components
 With massive MIMO, expensive, ultra-linear 50 Watt
amplifiers used in conventional systems are replaced
by hundreds of low-cost amplifiers with output power
in the milli-Watt range
 Furthermore, in massive MIMO systems, the effects of
noise and fast fading vanish, and intracell interference
can be mitigated using simple linear precoding and
detection methods

11. Improved energy efficiency
 Because the base station can focus its emitted
energy into the spatial directions where it
knows that the terminals are located
Improved energy efficiency
 Because the base station can focus its emitted
energy into the spatial directions where it
knows that the terminals are located

12. SPATIAL MODULATION
 Spatial modulation, as first proposed by haas etal ..,
 SM encodes part of the data to be transmitted onto the spatial
position of each transmit antenna in the antenna array
 signal constellation spatial constellation
to increase the data rate
INFORMATION BITS
Log2(nb) log2(m) bits
 NB = number of transmit antennas
 M = size of the complex signal constellation diagram
 Spatial modulation, as first proposed by haas etal ..,
 SM encodes part of the data to be transmitted onto the spatial
position of each transmit antenna in the antenna array
 signal constellation spatial constellation
to increase the data rate
INFORMATION BITS
Log2(nb) log2(m) bits
 NB = number of transmit antennas
 M = size of the complex signal constellation diagram

13.  SM is a combination of space shift keying (SSK) and
amplitude/phase modulation
 The receiver can then employ optimal maximum likelihood (ML)
detection to decode the received signal
 Spatial modulation can mitigate inter-channel interference,
 inter-antenna synchronization,
 and multiple RF chains
 Multi-user SM can be considered as a new research direction to
be considered in 5G wireless communication systems
 SM is a combination of space shift keying (SSK) and
amplitude/phase modulation
 The receiver can then employ optimal maximum likelihood (ML)
detection to decode the received signal
 Spatial modulation can mitigate inter-channel interference,
 inter-antenna synchronization,
 and multiple RF chains
 Multi-user SM can be considered as a new research direction to
be considered in 5G wireless communication systems

14. CR NETWORKS
 The CR network is an software defined
radio technique
 In CR networks, a secondary system can
share spectrum bands with the licensed
primary system
 either on an interference free basis or on
an interference-tolerant basis
 The CR network is an software defined
radio technique
 In CR networks, a secondary system can
share spectrum bands with the licensed
primary system
 either on an interference free basis or on
an interference-tolerant basis

15. Interference-free CR networks
 In interference-free CR networks, CR
users are allowed to borrow spectrum
resources only when licensed users do
not use them
 CR receivers should first monitor and
allocate the unused spectrums via
spectrum sensing and feed this
information back to the CR transmitter
 In interference-free CR networks, CR
users are allowed to borrow spectrum
resources only when licensed users do
not use them
 CR receivers should first monitor and
allocate the unused spectrums via
spectrum sensing and feed this
information back to the CR transmitter

16. Interference-tolerant CR networks
 In interference tolerant CR networks, CR
users can share the spectrum resource
with a licensed system while keeping the
interference below a threshold
 In interference-tolerant CR networks can
achieve enhanced spectrum utilization
the radio spectrum
 Better spectral and energy efficiency.
 In interference tolerant CR networks, CR
users can share the spectrum resource
with a licensed system while keeping the
interference below a threshold
 In interference-tolerant CR networks can
achieve enhanced spectrum utilization
the radio spectrum
 Better spectral and energy efficiency.

18. MOBILE FEMTOCELL
 It combines the mobile relay concept (moving network)
with femtocell technology
 An MFemtocell is a small cell that can move around
and dynamically change its connection to an
operator’s core network.
 public transport buses, trains, and even private cars.
 MFemtocells can improve the spectral efficiency of the
entire network.
 MFemtocells can contribute to signaling overhead
reduction of the network.
 the energy consumption of users inside an MFemtocell
can be reduced
 It combines the mobile relay concept (moving network)
with femtocell technology
 An MFemtocell is a small cell that can move around
and dynamically change its connection to an
operator’s core network.
 public transport buses, trains, and even private cars.
 MFemtocells can improve the spectral efficiency of the
entire network.
 MFemtocells can contribute to signaling overhead
reduction of the network.
 the energy consumption of users inside an MFemtocell
can be reduced

20. VISIBLE LIGHT
COMMUNICATION
Office
Lounge
BedRoom
Indoor Freespace Optics
and/or Radio
Home
Gateway
PLC
cellular
ADSL
FTTH
RL
L
B ridge
(Mesh)
radio
Office
Lounge
BedRoom
Indoor Freespace Optics
and/or Radio
Home
Gateway
PLC
cellular
ADSL
FTTH
RL
L
B ridge
(Mesh)
radio

21. GREEN COMMUNICATIONS
 The increase of energy consumption in
wireless communication systems causes an
increase of CO2 emission indirectly
 The indoor communication technologies are
promising deployment strategies to get better
energy efficiency
 VLC and mm-wave technologies can also be
considered as energy efficient wireless
communication
 The increase of energy consumption in
wireless communication systems causes an
increase of CO2 emission indirectly
 The indoor communication technologies are
promising deployment strategies to get better
energy efficiency
 VLC and mm-wave technologies can also be
considered as energy efficient wireless
communication

22. BACKHAUL TRAFFIC MODELS
 BACKHAUL TRAFFIC MODEL IN CENTRAL
SOLUTIONS
 BACKHAUL TRAFFIC MODEL IN CENTRAL
SOLUTIONS

23. central solution
 S1 serves as a feeder for user data from the
advance gateway to the MBS
 X2 enables mutual information exchange
among small cells
 the aggregated backhaul traffic at the MBS is
forwarded to the core network by fiber to the
cell (FTTC) links
 S1 serves as a feeder for user data from the
advance gateway to the MBS
 X2 enables mutual information exchange
among small cells
 the aggregated backhaul traffic at the MBS is
forwarded to the core network by fiber to the
cell (FTTC) links

24.  Uplink throughput of small cell
THcentra small-up= 0.04 .Bsc centra . Ssc
centra
 Down link throughput of small cell:
THcentra small-down = (1 + 0.1 + 0.04) . Bsc centra . Ssc centra
Bsc centra is the bandwidth of a small cell
Ssc centra is the average spectrum efficiency of a smallcell
 Uplink throughput of small cell
THcentra small-up= 0.04 .Bsc centra . Ssc
centra
 Down link throughput of small cell:
THcentra small-down = (1 + 0.1 + 0.04) . Bsc centra . Ssc centra
Bsc centra is the bandwidth of a small cell
Ssc centra is the average spectrum efficiency of a smallcell

25. Uplink throughput of a macrocell
THcentra macro-up = 0.04 . Bmc centra . Smc centra,
Downlink throughput of a macrocell
THcentra macro-down = (1 + 0.1 + 0.04) . Bmc centra . Smc centra,
Bmc centra is the macrocell bandwidth
Smc centra is the average spectrum efficiency of a
macrocell
Total backhaul throughput
THsum centra = THcentra sum-up + THcentra sum-down.
Uplink throughput of a macrocell
THcentra macro-up = 0.04 . Bmc centra . Smc centra,
Downlink throughput of a macrocell
THcentra macro-down = (1 + 0.1 + 0.04) . Bmc centra . Smc centra,
Bmc centra is the macrocell bandwidth
Smc centra is the average spectrum efficiency of a
macrocell
Total backhaul throughput
THsum centra = THcentra sum-up + THcentra sum-down.

26. BACKHAUL TRAFFIC MODEL IN
DISTRIBUTION SOLUTIONS

27. DISTRIBUTION SOLUTIONS
 the number of adjacent small cells in a
cluster is assumed to be K.
Spectrum efficiency
Ssc
Comp = (K – 1)Ssc
dist
Ssc dist is the spectrum efficiency of the
small cell in the cooperative cluster
 the number of adjacent small cells in a
cluster is assumed to be K.
Spectrum efficiency
Ssc
Comp = (K – 1)Ssc
dist
Ssc dist is the spectrum efficiency of the
small cell in the cooperative cluster

28. uplink throughput of a cooperativesmall cell
THdist
small-up = 1.14 . Bsc
dist . Ssc
dist
downlink throughput of a cooperative small cell
THdist
small-down = 1.14 . Bsc
dist . (Ssc
dist + Ssc
comp).
Bsc
dist is the bandwidth of the small cell
Total backhaul throughput
THsum dist = K . (THdist
small-up + THdist
small-down).
uplink throughput of a cooperativesmall cell
THdist
small-up = 1.14 . Bsc
dist . Ssc
dist
downlink throughput of a cooperative small cell
THdist
small-down = 1.14 . Bsc
dist . (Ssc
dist + Ssc
comp).
Bsc
dist is the bandwidth of the small cell
Total backhaul throughput
THsum dist = K . (THdist
small-up + THdist
small-down).

29. ENERGY EFFICIENCY OF 5G WIRELESS
BACKHAUL NETWORKS
 The energy consumption of cellular networks should
include the operating energy and the embodied energy
EOP = POP . Tlifetime
POP is the BS operating power
Tlifetime is the BS lifetime.
BS transmission power PTX
POP = a . PTX + b, a > 0 and b > 0.
 The energy consumption of cellular networks should
include the operating energy and the embodied energy
EOP = POP . Tlifetime
POP is the BS operating power
Tlifetime is the BS lifetime.
BS transmission power PTX
POP = a . PTX + b, a > 0 and b > 0.

30. Simple model derivation
 The MBS transmission power is normalized as
P0 = 40 W radius r0 = 1 km.
 The MBS transmission power with coverage radius r is
denoted by
PTX = P0 . (r/r0)α
α is the path loss coefficient.
 BS operating power with coverage radius r is expressed as
POP = a . P0 . (r/r0)α + b.
BS embodied energy = the initial energy + maintenance Energy,
EEM = EEMinit + EEMmaint.
 The MBS transmission power is normalized as
P0 = 40 W radius r0 = 1 km.
 The MBS transmission power with coverage radius r is
denoted by
PTX = P0 . (r/r0)α
α is the path loss coefficient.
 BS operating power with coverage radius r is expressed as
POP = a . P0 . (r/r0)α + b.
BS embodied energy = the initial energy + maintenance Energy,
EEM = EEMinit + EEMmaint.

31. In Central Solution The System Energy
Consumption Is
 the energy efficiency of the central solution is
defined as
ηcentra = THsum centra /Ecentra system.
 the energy efficiency of the central solution is
defined as
ηcentra = THsum centra /Ecentra system.

32. In the distribution solution, the system
energy consumption
 the energy efficiency of the distribution solution is
defined as
ηdist = THsum centra /Ecentra system.
 the energy efficiency of the distribution solution is
defined as
ηdist = THsum centra /Ecentra system.

33. Default parameters

34. Throughput of wireless backhaul
networks

35. Energy efficiency of wireless
backhaul networks

36. Energy efficiency of wireless backhaul networks
with respect to the path loss coefficient

37. CONCLUSIONS
 5G networks are expected to satisfy
rapid wireless traffic growth.
 Massive MIMO, millimeter wave
communications, and small cell
technologies are presented to achieve
gigabit transmission rates in 5G
networks.
 5G networks are expected to satisfy
rapid wireless traffic growth.
 Massive MIMO, millimeter wave
communications, and small cell
technologies are presented to achieve
gigabit transmission rates in 5G
networks.

38. THANK YOU