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CHAPTER 01
INTRODUCTION
1.1 MOTIVATION
The performance of ad hoc networks is limited by mutual interference between
communicating devices. Medium access control (MAC) protocols are used to restrict
interference, and usually do so by blocking nodes from transmitting data. Our work is
motivated by the fact that interference does not necessarily have to be handled by theMAC layer. Instead, the burden of interference avoidance on the MAC layer can be
shifted towards interference handling on the physical layer. The intention behind this is
the expectation that less blocking on the MAC layer leads to increased throughput and
reduced transmission delay. To this end, multiple access schemes such as code division
multiple access (CDMA) or interleave division multiple access (IDMA) are alluring to be
used to separate simultaneous transmissions (e.g., [1][3]). Here, the primary concern
is the near-far problem which is often attempted to be combated by power control
mechanisms. However, in contrast to cellular systems, ad hoc networks provoke near-far
constellations that can generally not be solved by power control. As a solution to this
problem, multiuser detectors could be used which are able to separate user signals
without power control. The existing work on using multiuser detection (MUD) in ad hoc
networks mainly focuses on the improved detection capability as compared to
conventional receivers [4][7]. The tendency is to consider simple MAC protocols such
as slotted Aloha on top of a powerful multiuser detection in the physical layer. A MAC
protocol design involving MUD- specific features has so far been largely neglected,
although the use of MUD does not make medium access control obsolete. Motivated by
this, we propose a new technique IDMA based MUD technique which is used at a
physical layer. In our simulative analysis, we consider in particular the use of IDMA
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because IDMA has not largely been considered in the context of ad hoc networks. In this
thesis, we will thus provide an overview on the most critical issues involved.
1.2OBJETIVES
To Analyze a method to alleviate interference using physical layer exploiting multiuser
detection(MUD) in wireless Ad Hoc networks.
The objectives of this thesis are twofold:
1. Investigating the issues in wireless Ad Hoc networks.
2. Analyze a new IDMA based MUD scheme that is used at physical layer to restrict
interference and maintain QOS.
1.3MAJOR CONTRIBUTION OF THIS THESIS
Brief introduction to ad-hoc networks focusing especially on Physical layer andhow MUD concepts can be utilized at the physical layer.
Understanding some Multiuser detection concepts and different schemes used forMUD.
Solutions provided for Ad-hoc network by MUD using Interleave DivisionMultiple Access.
Generating results through simulations in AWGN environment in order to assessthe BER(physical layer) performance of IDMA based MUD schemes which make
it suitable for ad-hoc wireless networks.
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1.4 THESIS LAYOUT
This thesis is organized as follows:
In second chapter we describe the brief introduction to wireless communications; next
different types of wireless communication are discussed according to their ranges.
In third chapter we explain Ad-Hoc networks and their different types, next advantages
and disadvantages of ad-hoc networks are taken into consideration.
In fourth chapter we illustrate transmitter and receiver principles of IDMA, IDMA
features that and how we can employ multiuser detection concept in IDMA. Also
multiuser detection concepts with different types of MUD algorithms.
In fifth chapter we describe IDMA based MUD scheme simulation plots and its
discussion
In sixth chapter we have overall conclusion of this thesis and future extension.
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CHAPTER 02
WIRELES NEWTWORKS
2.1 WIRELESS COMMUNICATION
Wireless telecommunications is the transfer of information between two or more points
that are not physically connected. Distances can be short, such as a few metres for
television remote control, or as far as thousands or even millions of kilometres for deep-
space radio communications. It encompasses various types of fixed, mobile, and portable
two-way radios, cellular telephones, personal digital assistants (PDAs), and wireless
networking. Other examples of wireless technology include GPS units, Garage door
openers or garage doors, wireless computer mice, keyboards and Headset (audio),
headphones, radio receivers, satellite television, broadcast television and cordless
telephones[8].
Wireless operations permit services, such as long range communications, that are
impossible or impractical to implement with the use of wires. The term is commonly used
in the telecommunications industry to refer to telecommunications systems (e.g. radio
transmitters and receivers, remote controls, computer networks, network terminals, etc.)
which use some form of energy (e.g. radio frequency (RF),acoustic energy, etc.) to
transfer information without the use of wires [9]. Information is transferred in this
manner over short, medium and long distances.
2.2 LONG RANGE WIRELESS COMMUNICATION
It involves:
Satellite Communication Terrestrial Microwave
2.2.1 Satellite Communication
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A satellite communications system uses satellites to relay radio transmissions between
earth terminals. A passive satellite only reflects received radio signals back to earth. An
active satellite acts as a repeater; it amplifies signals received and then retransmits them
back to earth. This increases signal strength at the receiving terminal to a higher level
than would be available from a passive satellite [10].
A typical operational link involves an active satellite and two or more earth terminals.
One station transmits to the satellite on a frequency called the UP-LINK frequency. The
satellite then amplifies the signal, converts it to the DOWN-LINK frequency, and
transmits it back to earth. The signal is next picked up by the receiving terminal.
Communications satellites are ideally placed to provide telecommunications links
between different places across the globe. Traditional telecommunications links used
direct "cables" linking different areas. As a result of the cost of installation and
maintenance of these cables, satellites were seen as an ideal alternative. While still
expensive to put in place, they provided a high bandwidth and were able to operate for
many years.
Figure 2.1: Example of Satellite Communication [10]
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2.2.2 Microwave Transmission
Microwave transmission refers to the technology of transmitting information or energy
by the use of radio waves whose wavelengths are conveniently measured in small
numbers of centimetre; these are called microwaves [11]. This part of the radio spectrumranges across frequencies of roughly 1.0 gigahertz (GHz) to 30 GHz. These correspond to
wavelengths from 30 centimeters down to 1.0 cm.
2.3 Medium Range Communication
It usually involves:
Cellular Communication WIMAX
2.3.1 Cellular Network (Basic Concept)
A cellular network provides cell phones or mobile stations (MSs), to use a more general
term, with wireless access to the public switched telephone network (PSTN). The service
coverage area of a cellular network is divided into many smaller areas, referred to as
cells, each of which is served by a base station (BS). The BS is fixed, and it is connected
to the mobile telephone switching office (MTSO), also known as the mobile switching
center. An MTSO is in charge of a cluster of BSs and it is, in turn, connected to the
PSTN. With the wireless link between the BS and MS, MSs such as cell phones are able
to communicate with wireline phones in the PSTN. Both BSs and MSs are equipped with
a transceiver. Figure 1 illustrates a typical cellular network, in which a cell is represented
by a hexagon and a BS is represented by a triangle [12].
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Figure 2.2: Typical cellular network [12]
2.3.2 WIMAX (IEEE 802.16 standard)
WiMAX(Worldwide Interoperability for Microwave Access) is a wireless
communications standard,also known as 802.16,designed to provide 30 to 40 megabit-
per-second data rates [13] with the 2011 update providing up to 1 Gbit/s for fixed stations.
It is a part of a fourth generation, or 4G, of wireless-communication technology.
WiMax far surpasses the 30-metre (100-foot) wireless range of a conventional Wi-Filocal area network (LAN), offering a metropolitan area network with a signal radius of
about 50 km (30 miles). The name "WiMAX" was created by the WiMAX Forum, which
was formed in June 2001 to promote conformity and interoperability of the standard. The
forum describes WiMAX as "a standards-based technology enabling the delivery of last
mile wireless broadband access as an alternative to cable and DSL" [14] WiMax offers
data-transfer rates that can be superior to conventional cable-modem and DSL
connections, however, the bandwidth must be split among multiple users and thus yields
lower speeds in practice [15] WiMAX, is primarily aimed at making broadband network
access widely available without the expense of stringing wires (as in cable-access
broadband) or the distance limitations of Digital Subscriber Line. WiMAX I similar to
802.11/Wi-Fi networks with the coverage and QOS (quality of service) of cellular
networks. WiMAX is intended for wireless "metropolitan area networks". WiMAX can
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provide broadband wireless access (BWA) up to 30 miles (50 km) for fixed stations, and
3 - 10 miles (5 - 15 km) for mobile stations. In contrast, the WiFi/802.11 wireless local
area network standard is limited in most cases to only 100 - 300 feet (30 - 100m).With
WiMAX, WiFi-like data rates are easily supported, but the issue of interference is
lessened. WiMAX operates on both licensed and non-licensed frequencies, providing a
regulated environment and viable economic model for wireless carriers.
2.3.2.1 A wimax system consists of
1) A WiMAX tower, similar in concept to a cell-phone tower - A single WiMAXtower can provide coverage to a very large area as big as 3,000 square miles
(~8,000 square km).
2) A WiMAX receiver - The receiver and antenna could be a small box or PersonalComputer Memory card, or they could be built into a laptop the way WiFi access
is today [16].
Figure2.3:WIMAX Tower [16] Figure 2.4:WIMAX Reciever [16]
2.4 Short Range Wireless Communications
It involves:
Wi-Fi Infrared Communication
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Bluetooth2.4.1 Wi-Fi
Wi-Fi is a popular technology that allows an electronic device to exchange datawirelessly (using radio waves) over a computer network, including high-speed Internet
connections. The Wi-Fi Alliance defines Wi-Fi as any "wireless local area network
(WLAN) products that are based on the Institute of Electrical and Electronics Engineers'
(IEEE) 802.11 standards"[13] However, since most modern WLANs are based on these
standards, the term "Wi-Fi" is used in general English as a synonym for "WLAN".
A device that can use Wi-Fi (such as a personal computer, video game console, smart
phone, tablet, or digital audio player) can connect to a network resource such as the
Internet via a wireless network access point. Such an access point (or hotspot) has a range
of about 20 meters (65 feet) indoors and a greater range outdoors. Hotspot coverage can
comprise an area as small as a single room with walls that block radio waves or as large
as many square milesthis is achieved by using multiple overlapping access points.
Wi-Fi provides short-range wireless high-speed data connections between mobile data
devices (such as laptops, PDAs or phones) and nearby Wi-Fi access points (special
hardware connected to a wired network).
The range covered by a Wi-Fi access point is from 30 to 100 meters indoors while
outdoors a single access point can cover about 650 meters. Wi-Fi has had a checkered
(both successful and unsuccessful) security history. Its earliest encryption system, WEP,
proved easy to break. Much higher quality protocols, WPA and WPA2, were added later.
However, an optional feature added in 2007, called Wi-Fi Protected Setup (WPS), has a
flaw that allows a remote attacker to recover the router's WPA or WPA2 password in a
few hours on most implementations [14]. Some manufacturers have recommended
turning off the WPS feature. The Wi-Fi Alliance has since updated its test plan and
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certification program to ensure all newly-certified devices resist brute-force AP PIN
attacks.
2.4.2 Infrared Communication
Infrared (IR) light is electromagnetic radiation with longer wavelengths than those of
visible light, extending from the nominal red edge of the visible spectrum at 0.74
micrometres (m) to 300 m. This range of wavelengths corresponds to a frequency
range of approximately 1 to 400 THz [17] and includes most of the thermal radiation
emitted by objects near room temperature. Infrared light is emitted or absorbed by
molecules when they change their rotational-vibrational movements.
Infrared light is used in industrial, scientific, and medical applications. Night-vision
devices using infrared illumination allow people or animals to be observed without the
observer being detected. In astronomy, imaging at infrared wavelengths allows
observation of objects obscured by interstellar dust. Infrared imaging cameras are used to
detect heat loss in insulated systems, observe changing blood flow in the skin, and
overheating of electrical apparatus.
2.4.3 Bluetooth
Bluetooth is a proprietary open wireless technology standard for exchanging data over
short distances (using short-wavelength radio transmissions in the ISM band from 2400
2480 MHz) from fixed and mobile devices, creating personal area networks (PANs) with
high levels of security. Created by telecoms vendor Ericsson in 1994 [18] it was
originally conceived as a wireless alternative to RS-232 data cables. It can connect
several devices, overcoming problems of synchronization.
Bluetooth uses a radio technology called frequency-hopping spread spectrum, which
chops up the data being sent and transmits chunks of it on up to 79 bands (1 MHz each;
centered from 2402 to 2480 MHz) in the range 2,4002,483.5 MHz (allowing for guard
bands). This range is in the globally unlicensed Industrial, Scientific and Medical (ISM)
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2.4 GHz short-range radio frequency band. It usually performs 800 hops per second, with
AFH enabled.
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CHAPTER 03
INTRODUCTION TO WIRELESS AD-HOC NETWORS
3.1 WIRELESS AD-HOC NETWORKS
A wireless ad-hoc network is a decentralized type ofwireless network [19]. The network
is ad hoc because it does not rely on a preexisting infrastructure, such as routers in wired
networks or access points in managed (infrastructure) wireless networks. Instead, each
node participates in routing by forwarding data for other nodes, and so the determination
of which nodes forward data is made dynamically based on the network connectivity. In
addition to the classic routing, ad hoc networks can use flooding for forwarding the data.
Figure 3.1: Home Network Diagram of Adhoc Network [19]
An ad hoc network typically refers to any set of networks where all devices have equal
status on a network and are free to associate with any other ad hoc network devices in
link range.
The earliest wireless ad-hoc networks were the "packet radio" networks (PRNETs) from
the 1970s, sponsored by DARPA after the ALOHA net project
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In most wireless ad hoc networks, the nodes compete for access to shared wireless
medium, often resulting in collisions (interference). Using cooperative wireless
communications improves immunity to interference by having the destination node
combine self-interference and other-node interference to improve decoding of the desired
signal.
3.2 APPLICATIONS
The decentralized nature of wireless ad-hoc networks makes them suitable for a variety
of applications where central nodes can't be relied on, and may improve the scalability of
wireless ad-hoc networks compared to wireless managed networks, though theoretical
[20] and practical [21] limits to the overall capacity of such networks have been
identified.
Minimal configuration and quick deployment make ad hoc networks suitable for
emergency situations like natural disasters or military conflicts. The presence of dynamic
and adaptive routing protocols enables ad-hoc networks to be formed quickly.
3.3 TECHNICAL REQUIREMENTS
An ad-hoc network is made up of multiple nodes connected by links. Links areinfluenced by the node's resources (e.g. transmitter power, computing power and
memory) and by behavioral properties (e.g. reliability), as well as by link properties (e.g.
length-of-link and signal loss, interference and noise). Since links can be connected or
disconnected at any time, a functioning network must be able to cope with this dynamic
restructuring, preferably in a way that is timely, efficient, reliable, robust and scalable.
The network must allow any two nodes to communicate, by relaying the information via
other nodes. A path is a series of links that connects two nodes. Various routing
methods use one or two paths between any two nodes; flooding methods use all or most
of the available paths [22].
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3.4 TYPES OF AD-HOC NETWORK
3.4.1 Mobile ad-hoc networks
Figure 3.2: Mobile Adhoc Network [23]
A mobile ad-hoc network (MANET) is a self-configuring infrastructure lessnetwork of mobile devices connected by wireless links. Ad hoc is Latin and
means "for this purpose" [24,25]
Each device in a MANET is free to move independently in any direction, and willtherefore change its links to other devices frequently. Each must forward traffic
unrelated to its own use, and therefore be a router. The primary challenge in
building a MANET is equipping each device to continuously maintain the
information required to properly route traffic. Such networks may operate by
themselves or may be connected to the larger Internet.
MANETs are a kind of wireless ad-hoc networks that usually has a routablenetworking environment on top of a Link Layer ad hoc network.
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The growth of laptops and 802.11/Wi-Fi wireless networking have madeMANETs a popular research topic since the mid 1990s. Many academic papers
evaluate protocols and their abilities, assuming varying degrees of mobility within
a bounded space, usually with all nodes within a few hops of each other. Different
protocols are then evaluated based on measure such as the packet drop rate, the
overhead introduced by the routing protocol, end-to-end packet delays, network
throughput etc.
3.4.1.1 Types of MANET
3.4.1.1.1 VANET (Vehicular Ad-hoc Networks)
Figure 3.3: Vehicular Ad hoc Networks [26]
Vehicular Ad-Hoc Network (VANET) is a subset of mobile ad-hoc network,
which supports data communications among nearby vehicles and between
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vehicles and nearby fixed infrastructure, and generally represented as roadside
entities. Depending on the range of data communications, nodes in VANET
communicate among themselves in type of short-range (vehicle-to-vehicle) or
medium-range (vehicle-to-roadside) communications. We can understand
VANETs as subset of MANET and best example of VANET is Bus System of
any University which is connected. These buses are moving in different parts of
city to pick or drop students if they are connected, make a Ad hoc Network.
In addition, the major application view of VANETs includes real-time andsafety applications. Non-safety applications include real-time traffic
congestion and routing information, high-speed tolling, mobile
infotainment, traffic condition monitoring, and many others. Vehicularsafety applications include emergency, collision, car accident, and other
safety warnings. For high performance, highly robust, scalable, robust,
fault tolerant, and secure vehicular networking, several extraordinary
challenges are remained as follows:
Safety and commercial applications
Mobility and traffic models
Channel Modeling
Security and privacy
Cooperative aspects of vehicular communication
Cross-layer optimization techniques
Vehicle-to-Vehicle
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Vehicle-to-Roadside
Scalability and Availability issues in Vehicular networks
PHY, MAC, Network Layer (Routing protocols)
3.4.1.1.2 Intelligent vehicular ad hoc networks (InVANETs)
Intelligent vehicular ad hoc networks (InVANETs) are a kind of artificial
intelligence that helps vehicles to behave in intelligent manners during vehicle-to-
vehicle collisions, accidents, drunken driving etc [27].
Figure 3.4: Intelligent Design of Vehicular Networks (VANETs) [27]
In the last few years there has been an increasing interest for ad hoc networks that enable
users of different wireless technologies (bluetooth, WiFi) to interconnect without using
any third-party infrastructure. In particular, there exists an important research line
supported by a high number of projects in the whole world dedicated to the study the
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Internet Based Mobile Ad hoc Networks (iMANET) are ad hoc networks that link
mobile nodes and fixed Internet-gateway nodes. In such type of networks normal
ad hoc routing algorithms don't apply directly.
Figure 3.5: Internet Based Mobile Ad hoc Networks [28]
3.4.1.2 MANET usage areas
Military scenarios
Sensor networks Rescue operations Students on campus Free Internet connection sharing Conferences
3.4.1.3 Mechanisms required in a MANET
Multihop operation requires a routing mechanism designed for mobile nodes.
Internet access mechanisms. Self configuring networks requires an address allocation mechanism. Mechanism to detect and act on, merging of existing networks. Security mechanisms.
3.4.2 Wireless mesh network
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Figure 3.6: Wireless Mesh Network [29]
A wireless mesh network (WMN) is a communications networkmade up ofradio nodes
organized in a mesh topology. Wireless mesh networks often consist of mesh clients,
mesh routers and gateways. The mesh clients are often laptops, cell phones and other
wireless devices while the mesh routers forward traffic to and from the gateways which
may but need not connect to the Internet. The coverage area of the radio nodes working
as a single network is sometimes called a mesh cloud. Access to this mesh cloud is
dependent on the radio nodes working in harmony with each other to create a radio
network. A mesh network is reliable and offers redundancy. When one node can no
longer operate, the rest of the nodes can still communicate with each other, directly or
through one or more intermediate nodes [29]. The animation below illustrates how
wireless mesh networks can self form and self heal. Wireless mesh networks can be
implemented with various wireless technology including 802.11, 802.15, 802.16, cellular
technologies or combinations of more than one type.
A wireless mesh network can be seen as a special type of wireless ad-hoc network. A
wireless mesh network often has a more planned configuration, and may be deployed to
provide dynamic and cost effective connectivity over a certain geographic area. An ad-
hoc network, on the other hand, is formed ad hoc when wireless devices come within
communication range of each other. The mesh routers may be mobile, and be moved
according to specific demands arising in the network. Often the mesh routers are not
limited in terms of resources compared to other nodes in the network and thus can be
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exploited to perform more resource intensive functions. In this way, the wireless mesh
network differs from an ad-hoc network, since these nodes are often constrained by
resources.
3.4.2.1 Network Architecture
Figure 3.7: Wireless mesh network architecture [30]
It's built of peer radio devices that don't have to be cabled to a wired port like traditional
WLAN access points (AP) do. Mesh architecture sustains signal strength by breaking
long distances into a series of shorter hops. Intermediate nodes not only boost the signal,
but cooperatively make forwarding decisions based on their knowledge of the network,
i.e. perform routing. Such architecture may with careful design provide high bandwidth,
spectral efficiency, and economic advantage over the coverage area.
Wireless mesh networks have a relatively stable topology except for the occasional
failure of nodes or addition of new nodes. The path of traffic, being aggregated from a
large number of end users, changes infrequently. Practically all the traffic in an
infrastructure mesh network is either forwarded to or from a gateway, while in ad hoc
networks or client mesh networks the traffic flows between arbitrary pairs of nodes [30].
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3.4.2.2 Operation
The principle is similar to the way packets travel around the wired Internetdata will
hop from one device to another until it reaches its destination. Dynamic routing
algorithms implemented in each device allow this to happen. To implement such dynamic
routing protocols, each device needs to communicate routing information to other devices
in the network. Each device then determines what to do with the data it receiveseither
pass it on to the next device or keep it, depending on the protocol. The routing algorithm
used should attempt to always ensure that the data takes the most appropriate (fastest)
route to its destination.
3.4.2.3 Applications
Mesh networks may involve either fixed or mobile devices. The solutions are as diverse
as communication needs, for example in difficult environments such as emergency
situations, tunnels, oil rigs, battlefield surveillance, high speed mobile video applications
on board public transport or real time racing car telemetry. An important possible
application for wireless mesh networks is VoIP. By using a Quality of Service scheme,
the wireless mesh may support local telephone calls to be routed through the mesh.
3.4.3 Wirelesssensor network
Figure 3.8: Typical multi-hop wireless sensor network architecture [31]
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A wireless sensor network (WSN) consists of spatially distributed autonomous sensors to
monitor physical or environmental conditions, such as temperature, sound, vibration,
pressure, motion or pollutants and to cooperatively pass their data through the network to
a main location. The more modern networks are bi-directional, also enabling control of
sensor activity. The development of wireless sensor networks was motivated by military
applications such as battlefield surveillance; today such networks are used in many
industrial and consumer applications, such as industrial process monitoring and control,
machine health monitoring, and so on.
The WSN is built of "nodes"from a few to several hundreds or even thousands, where
each node is connected to one (or sometimes several) sensors. Each such sensor network
node has typically several parts: a radio transceiver with an internal antenna orconnection to an external antenna, a microcontroller, an electronic circuit for interfacing
with the sensors and an energy source, usually a battery or an embedded form ofenergy
harvesting. A sensor node might vary in size from that of a shoebox down to the size of a
grain of dust, although functioning "motes"(demo video) of genuine microscopic
dimensions have yet to be created. The cost of sensor nodes is similarly variable, ranging
from a few to hundreds of dollars, depending on the complexity of the individual sensor
nodes. Size and cost constraints on sensor nodes result in corresponding constraints on
resources such as energy, memory, computational speed and communications bandwidth.
The topology of the WSNs can vary from a simple star networkto an advanced multi-hop
wireless mesh network. The propagation technique between the hops of the network can
be routing or flooding [32, 33].
In computer science and telecommunications, wireless sensor networks are an active
research area with numerous workshops and conferences arranged each year.
3.4.3.1 Applications
3.4.3.1.1 Area monitoring
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Area monitoring is a common application of WSNs. In area monitoring, the WSN is
deployed over a region where some phenomenon is to be monitored. A military example
is the use of sensors to detect enemy intrusion; a civilian example is the geo-fencing of
gas or oil pipelines.
3.4.3.1.2 Environmental sensing
The term Environmental Sensor Networks [34] has evolved to cover many applications of
WSNs to earth science research. This includes sensing volcanoes [35], oceans [36],
glaciers, forests [37], etc. Some other major areas are listed below.
3.4.3.1.3 Air pollution monitoring
Wireless sensor networks have been deployed in several cities (Stockholm, London or
Brisbane) to monitor the concentration of dangerous gases for citizens. These can take
advantage of the ad-hoc wireless links rather than wired installations, which also make
them more mobile for testing readings in different areas.
3.4.3.1.4 Greenhouse monitoring
Wireless sensor networks are also used to control the temperature and humidity levelsinside commercial greenhouses. When the temperature and humidity drops below
specific levels, the greenhouse manager must be notified via e-mail or cell phone text
message, or host systems can trigger misting systems, open vents, turn on fans, or control
a wide variety of system responses.
3.4.3.1.5 Landslide detection
A landslide detection system makes use of a wireless sensor network to detect the slightmovements of soil and changes in various parameters that may occur before or during a
landslide. And through the data gathered it may be possible to know the occurrence of
landslides long before it actually happens.
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3.4.3.2 Characteristics
The main characteristics of a WSN include
Power consumption constrains for nodes using batteries or energy harvesting
Ability to cope with node failures Mobility of nodes Dynamic network topology Communication failures Heterogeneity of nodes Scalability to large scale of deployment Ability to withstand harsh environmental conditions Ease of use Power consumption
3.5 ADVANTAGES AND DISADVANTAGES OF AD-HOC NETWORK
3.5.1 Advantages of Ad-hoc Network
There are many reasons better to use ad hoc than infrastructure. The biggest ad hocs
strength is its independency from any infrastructure. Therefore, it is possible to establish
an ad hoc network in any difficult situations. The following are the advantages of ad hoc
networks.
a). No infrastructure and lower cost: There are situations, with which a user of a
communication system cannot rely on an infrastructure[38]. Using a service from a
infrastructure can be expensive for specific applications. In an area with very low density,like desert, mountain, or isolated area it is not impossible to establish an Infrastructure.
But if we compare how often the people there are using service of infrastructure and how
many data per day transmitted with cost of installation, maintenance, and repair, it is may
be too expensive. Almost the same problem with military network. It is obviously very
useless to build an infrastructure in a battlefield. Aside from cost of installation, the
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enemy can destroy the infrastructure in short time. An independent from infrastructure
network is needed for both cases.
b. Mobility (MANET only): In the next generation of wireless communication systems,
there will be a need for the rapid deployment of independent mobile users [39]. The most
popular examples include military networks, emergency/ rescue operations, and disaster
effort. In these scenarios we cant rely on centralized connectivity. MANETs support
nodes mobility. We can still communicate with our mobile devices as long as the
destination is reachable.
c. Decentralized and robust: Another advantage of ad hoc networks is that they are
inherently very robust [40]. Imagine that for some reason one of the base stations is not
working. In this case, all users of that base station will lose connectivity to other
networks. In the ad hoc networks you can avoid such problem. If one node leaves the
network or is not working, you can still have connectivity to other nodes and maybe you
can use these nodes to multi-hop your message to the destination nodes, as long as there
is at least one way to desired node.
d. Easy to build and spontaneous infrastructure: Malfunction of a network
infrastructure is sometimes not avoidable. It is obviously difficult to repair or replace the
malfunction infrastructure in short time, while the networks existence must be
maintained all-time. Establishing an ad hoc is a good deal in such situation. The network
participants can act as ad hoc nodes and hop the messages.
3.5.2 Disadvantages of Ad-hoc Network
The wireless communication is very famous now a days, using wireless can make rooms
look better, because fewer cables are used. The weakness of wireless link impact ad hoc.
Lower data rate, security, and medium access control are common problems in thewireless communications. Ad-hoc strengths cause also some problems. The following are
the disadvantages of ad hoc networks.
a. Higher error rate: Unlike wired transmission, the wireless transmission may deal
with problem the characteristic of the electronic wave. In a free room without obstacle
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the electronic wave propagates linear independently from its frequency [38].There is
seldom such a situation. The obstacle causes shadowing, refection, scattering, fading,
refraction, diffraction of the wave. This propagation may lead to transmitted packets
being garbled and thus received in error.
b. Lower data rate: One of biggest Problem of ad hoc networks is reduced data rates.
The characteristic of wave, which is used for wireless communication, prevents wireless
communication to transmit data better than wired communication. A higher frequency
can transmit more data, but then it is more vulnerable to interference and performs well in
short range.
c. Dynamic topology and scalability: Because ad hoc networks do not allow the same
kinds of aggregation techniques that are available to standard Internet routing protocols,
they are vulnerable to scalability problem [40].
Since the MANETs nodes are mobile, the routing changes as the nodes move. Current
connectivity Information must to be propagated to all networks participant. Control
messages have to sent around the network frequently. The increased number of control
messages burdens the available bandwidth.
Therefore, the ad hoc protocols are typically designed to reduce the number of control
messages, such as by keeping the current information. A good algorithm for ad hoc
networks must be able to evaluate and compare networks relative scalability in the face
of increased number of nodes and nodes mobility. It is very important to know how many
control message is required. So we can control bandwidths usage.
d. Security: Due to dynamic distributed infrastructure less nature and lack of centralized
monitoring points, the ad hoc networks are vulnerable to various kinds of attacks [42].
Unlike wired channel, the wireless channel is accessible to both legitimate network usersand malicious attacker. Therefore, the ad hoc networks are susceptible to attacks ranging
from passive attacks such as eavesdropping to active attack such as interfering [43].
Especially for MANET, limited power consumption and computation capabilities, due to
energy limitation, causes incapability to execute computation-heavy algorithms like
public key algorithms. Passive attack means, that the attacker does not send any message.
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The attacker just listens the channel; therefore, it is almost impossible to detect this
attack. In contrast, the active attacks modifies, deletes the packets, injects packets to
invalid destination. Active attack can be detected. There are numerous security problem
issues in the ad hoc networks.
3.6 THE FOLLOWING ARE SOME OF THE SECURITY PROBLEMS OF IEEE
802.11
1) Eavesdropping (passive), a non-legitimate listening into a transmission between two
nodes.
2) Traffic analysis (passive), the attacker monitoring the transmission for patterns of
communication.
3) Masquerading (active), the attacker pretends to be an authorized user of a system in
order to gain access to it or to gain greater privileges than they are authorized for.
4) Replay (active), the attacker spies transmissions and retransmits message as the
legitimate user
5) Message modification (active), the attacker alters a original message by deleting,
adding to, modifying it.
6) Denial-of-service or interruption (active), the attacker prevents or prohibits the normal
use or management of communications facilities.
e). Energy limitation (MANET only): A MANET network allows mobile nodes to
communicate in the absence of a fixed infrastructure. Therefore, they operate with on
battery power. Because of this limitation, they must have algorithms which are energy-
efficient as well as operating with limited processing and memory resources. The usage
of available bandwidth will be limited because nodes may not be able to sacrifice the
energy consumed by operating at full link speed.
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4.3 IDMA TRANSMITTER AND RECEIVER
Figure 4.2: IDMA Transmitter and Receiver [45]
4.3.1 Transmitter
The upper part of Fig.4.2 shows the transmitter structure of an IDMA system with K
simultaneous users. The input data sequence dkof user-k is encoded based on a low-rate
code C. The encoder block produce a coded sequence c(K)= {c(K) , j=1,2, J},where J
is the frame length. The coded sequence then interleaved by a chip-level interleaver k ,
producing xk= [xk(1),..., xk(j),.,xk(J)]T, we call the elements in xk as chips also each
encoded and interleaved sequence xkis referred as to as layer. Due to interleaving, the
layer may be interpreted astypical sequenceas defined by Shannon.
The key principle of IDAM is that the interleavers {k} should be different for different
users. The interleavers are generated independently and randomly. These interleavers
disperse the coded sequence so that the adjacent chips are approximately uncorrelated,
which facilitates the simple chip-by-chip detection at receiver side [45].
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4.4 FEATURES OF IDMA
4.4.1 Flexible rate adaption
The multi-code technique can be used for a rate/power adaption. A large variety of date
rates can be supported. As opposed to conventional adaptive modulation/channel coding
technique, the modulation scheme is fixed and the same channel code is used for all
layers. Power adaption/savings are particularly useful for the uplink [47].
4.4.2 Low complexity receiver
In IDMA, a possible low complexity receiver is used to cancel any type of interference
(multilayer interference, multi-user interference, multi antenna interference, intersymbol
interference, etc.) jointly. The receiver is based on the Gaussian assumption (joint
Gaussian detector) and turbo processing in conjunction with the low -rate encoder. Its
complexity is linear with respect to the number of layers, number of chips/layer, number
of users, number of receive antennas, number of channel taps, and the number of
iterations [47].
4.4.3 Soft-information
The mentioned receiver inherently delivers reliable soft-output information, which is
useful for rate adaption and cross-layer optimization [47].
4.4.4 Resource allocation
Resource allocation is greatly simplified since the same interleaver set is used at all
times[47].
4.4.5 Low delay
Due to chip-by-chip interleaving the block size can optionally be reduced compared to
conventional DS-CDMA [47].
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4.4.6 Scalable bandwidth
Since the frequency bins allocated to 4G system are not known yet, it is supposed to
divide the 40 MHz suggested in [48] into multiple of5 MHz. That could be 220 MHz,
but also an inhomogeneous allocation as shown in Fig.4.3. Dynamic bandwidth allocation
may be considered.
Figure 4.3: Possible Spectrum Allocation for IDMA-based 4G Services [47]
4.4.7 Quality of Service
The quality of service (QoS) is mainly defined by a maximum bit error rate, a minimum
date rate, and a maximum delay. These parameters are highly dependent on the
application, e.g. text message, voice transmission or video transmission.
IDMA-based systems can be highly adaptive in order to guarantee a certain QoS level by
applying soft link adaption strategy to guarantee a certain bit error for a layer or group of
layers allocated to user or application [47]. On the other hand, we keep the transmission
power as low as possible for longer battery life and less emitted radiation.
4.4.8 Multi user gain (MUG)
From information theory, allowing multiuser to transmit simultaneously can lead to
significantly power reduction. This advantage is referred to as multi-user gain. [49]
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Figure 4.4: MUG in Fading Channels [49]
The advantages of IDMA become more prominent in fading channels. This is shown in
Fig.4.4(b) using a convolutionally coded IDMA system with different numbers of users K
over a single-cell fading channel containing path loss, lognormal fading and Raleigh
fading. The performance of TDMA system with trellis coded modulation (TCM) andtheir corresponding channel capacities are also plotted for reference. From Fig.4.4 (b) we
can see that performance of optimized IDMA system can be very close to the fading
channel capacity (with a gap caused by the non-ideal convolutional code used) and can be
improved by increasing the number of users K. When K is large, IDMA can significantly
outperform TDMA. This advantage is referred to as multi-user gain [44].
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constraints of choosing spreading sequences with good correlation properties at a cost of
increased receiver complexity. The practical application of this approach is limited by the
complexity of the detector [51], which requires a search on a trellis with exponential
complexity according to the number of users. Furthermore, this detector requires perfect
knowledge of all spreading sequences, timing, phase, and frequency offset of all users.
Single user detection is optimal only when spreading sequences are perfectly orthogonal
and the transmission channel does not compromise this feature.
4.7 MULTIPLE ACCESS INTERFERENCE
Imperfect cross-correlation characteristics of the spreading codes Multi-path fading contributes to MAI Causes severe degradation in the performance of the system Capacity is interference limited MAI is a function of:
Number of Users Cross-Correlation between users Amplitude of Interfering Signals
MAI is due to non-orthogonality between usersMAI can be mitigated by employing multiuser detection algorithms.
4.8 MULTIUSER DETECTION (MUD)
The primary idea of Multi User Detection (MUD) techniques is to cancel the interferencecaused by other users. This is done by exploiting the available side information of the
interfering users, rather than ignoring the presence of other users like in Single User
Detection (SUD) techniques. The idea of MUD was proposed by Sergio Verdu in the
early 1980s.
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where n(j) is a noise sample. For a particular user k, we rewrite Eq. 1 as
r(j) = hk zk(j) + k(j), (4.4)
where k(j) is the distortion (including both interference and additive noise) contained in
r(j) with respect toxk(j). The ESE
operations listed in Table 1(given below) can be applied to estimate xk(j).The principles
are rather straightforward.
Step 1. Estimate the mean and variance ofr(j) using Eq. 4.3.
Step 2. Estimate the mean and variance ofk(j) using Eq. 4.4.
Step 3. Estimatexk(j) based on r(j) using Eq. 4.4.
where k(j) is the distortion (including both interference and additive noise) contained in
r(j) with respect toxk(j). The ESE operations listed in Table 1 can be applied to estimate
xk(j). The principles are rather straightforward. The distortion component k(j) in Eq. 4.4
is the summation of the received signals from other K1 users (except user k) plus noise.
Assume that these signals are random and independent of each other. Then according to
the central limit theorem, k(j) can be approximated by a Gaussian random variable for a
large K. Assume that the means and variances of all k(j) are available.(We come back to
r(j)) in step 1
is the summation of E(hk xk(j)) over all k. From Eq. 2, E(xk(j)) in step 2 is the difference
between E(r(j)) and E(hk xk(j)). The variances ofr(j) and k(j) can be obtained similarly.
Once the mean and variance ofk(j) are obtained, step 3 is straightforward following the
assumption that k(j) is Gaussian. (For detailed discussion see [61]. Similar methods were
also studied in [56, 60].) The outputs of the ESE are noisy initially since they are
estimated using only one chip observation. An iterative technique is applied to improve
the estimation. The global process starts from the ESE. At the beginning, if no a priori
information is available, we set the means and variances of all of the transmitted chips to
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zero and one, respectively. This simply says that each chip takes +1 and -1 with equal
probability (assuming binary signaling over {+1, 1}). The ESE then produces coarse
estimates as described above and delivers them to the DECs. The DECs calculate (based
on the FEC coding constraint) the a posteriori probability (APP) of each transmitted chip
being +1 and 1 [54], and update its mean and variance[61], which are fed back to the
ESE for the next iteration.The above iterative process heavily relies on the DECs to
provide improved APP estimation. Codes of relatively low rate are necessary when Kis
large. Note that even simple repetition codes (without any coding gain) can efficiently
suppress the MAI induced distortion, which is related to the processing gain [53].
However, if the FEC code is properly designed to exploit the advantage of reduced rate,
improved coding gain comes as a bonus, which is vital if we want to converge toward
capacity.The complexity of step 1 in Table 1 is very low, only involving a summation
over all Kusers who share the results and also the cost. The cost of step 1 per user is only
several additions and multiplications. Steps 2 and 3 are very simple [61]. Overall, steps
13 together cost only several arithmetic operations per chip per user per iteration. No
matrix operation is necessary. The complexity is independent ofK. When Kreduces, the
Gaussian approximation for the interference component becomes less valid, but then the
benefit of less interference generally offsets the problem due to interference modeling.
3.7 MULTIUSER DETECTION TECHNIQUES IN OUR CONSIDERATION
1) Minimum Mean Square Error (MMSE)
2) MRC (Maximal Ratio Combining)
3) LLR combining (LLRC)
4.12.1 Minimum Mean Square Error (MMSE)
The minimum mean-squared error (MMSE) detector [61] is a linear detector which takes
into account the background noise and utilizes knowledge of the received signal powers.
This detector implements the linear mapping which minimizes E [|d - Ly |2], the mean-
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squared error between the actual data and the soft output of the conventional detector.
This results in [63, 65]
LMMSE = [R+ (No/2)A
-2
]
-1 (4.5)
Thus, the soft estimate of the MMSE detector is simply
dMMSE = LMMSE y (4.6)
As can be seen, the MMSE detector implements a partial or modified inverse of the
correlation matrix. The amount of modification is directly proportional to the backgroundnoise; the higher the noise level, the less complete and inversion of R can be done
without noise enhancement causing performance degradation. Thus, the MMSE detector
balances the desire to decouple the users (and completely eliminate MAI) with the desire
to not enhance the background noise. (Additional explanation can be found in [64].) This
multi-user detector is exactly analogous to the MMSE linear equalizer used to combat
IS1 [66].
Because it takes the background noise into account, the MMSE detector generally
provides better probability of error performance than the decorrelating detector. As the
background noise goes to zero, the MMSE detector converges in performance to the
decorrelating detector.[67]
An important disadvantage of this detector is that, unlike the decorrelating detector, it
requires estimation of the received amplitudes. Another disadvantage is that its
performance depends on the powers of the interfering users [63].
Therefore, there is some loss of resistance to the near-far problem as compared to the
decorrelating detector. Like the decorrelating detector, the MMSE detector faces the task
of implementing matrix inversion. Thus, most of the suboptimal techniques for
implementing the decorrelating detector are applicable to this detector as well [62]
The complexity involved (mainly for solving a size K Kcorrelation matrix) is O(K2)per
user by the well-known iterative minimum mean square error (MMSE) technique.
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() ./ j (4.9b)
() ()()
ESE function for multipath channel: Now consider multipath fading channels. In the
presence of ISI, a transmitted chip xk( j) is observed on L successive samples {r( j), r(
j+1), . . . , r( j+L-1)} in the received signal. Again, we consider BPSK signaling and real
fading coefficients.
With MRC [69], the received signal is passed through an MRC filter matched to the L
tap-coefficients for a particular user. For user-k, the output of the MRC filter is
Chip detection (similar to that given in (4.10)) is then applied to zk( j) to generate eESE(xk(
j)). Since K different L-tap matched filters are used for K users (see (4.11)), the
calculations of the mean and variance of zk( j)are different for each user. These
computations cannot be shared by different users as in (4.9). Consequently the
normalized complexity is O (KL) [69].
3.5.5 LLR combining (LLRC)
With LLRC, the output of the ESE is calculated as
()
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CHAPTER# 05
SIMULATION AND RESULTS
5.1 INTRODUCTION AND DISCUSSION
In this section comparison results of varying number of users are presented that confirm
IDMA based MUD scheme to be an excellent accessing technique for Ad-Hoc network
applications.
Due to chip level interleaving, the error performance at high loads is better for IDMA
which can be seen in the following figures where Monte-Carlo simulation results are
presented for IDMA with various number users and number of iterations on the AWGN
channel.
5.2 SYSTEM MODEL
For the system model we consider different scenarios for AD-Hoc networks while
varying the number of nodes to access the performance of IDMA based MUD scheme
with the increasing number of users. Note that all the nodes are considered as static. We
use MATLAB for performing simulations. MATLAB (short for MATrix LABoratory) is
a special-purpose computer program optimized to perform engineering and scientific
calculations. The use of MATLAB version 7.5 for this thesis enables the development of
simulations, which compute the complicated mathematical formulas and display the
simulation results in a graphical for analysis.
The mathematical formulas include calculation of the LLR algorithm, activity measure
and the processing of the information signal in a simulated IDMA communications
environment, with the presence of AWGN. Results such as the SNR performance and bit
errors are examined.
A Graphics User Interface (GUI) is created to aid users in developing an easy-to-use and
friendly environment. Users are able to enter various design parameters and compare the
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output results. The following sections will discuss about the functionality of the
simulation models and the operation of the GUI.
Case 1:
First of all we will take into consideration the case when there are 4 nodes in an ad-hoc
network;2 nodes are transmitting and remaining 2 are receiving data.
R1
T1
Signature#1
R2 T2
Signature#2
Figure 5.1: Using iterative MUD in a wireless ad hoc network with 4 nodes
Figure illustrates an ad-hoc network where a transmitter T1 and a transmitter T2 use
different IDMA signatures. The two transmissions can occur simultaneously if the
receivers R1 and R2 apply MUD. Signature knowledge is the requirement for multiuser
detection at receiving nodes.Looking, by way of example, at the receiver R1, it decodes
the received signal using two decoding branches in its MUD receiver. Only the signal
component coded with signature #1 is a desired signal. The component coded with
signature #2,which is interference for the receiver R1, can also be decoded, subtracted
from the received signal, and discarded.Complete transmitter and receiver design have
been given in preceding chapter(IDMA Systems)
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Case 2:
In this case we have depicted the scenario for the ad-hoc network containing 4 nodes.
T1 R1
R2 T2
R3 T3
T4 R4
Figure 5.2: Typical ad-hoc network with 8 nodes.
Case 3:
Figure 5.3: Typical ad-hoc network with 8 nodes.
Simulations and comparisons are given in the following sections for all these cases.
5.3 SIMULATIONS AND RESULTS
Following the assumptions described above, Monte Carlo simulations were implemented
to examine the performance of IDMA with respect to their BER with increasing number
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of users. Following figures shows the BER performance graphs versus Eb/No for a
system In a AWGN channel, where Eb is the transmitted energy per bit per user and No
is the power spectral density of the noise.
From the graphical results obtained, it is proved that there is graceful degradation in the
BER slope of IDMA with the increase of Eb/No values. IDMA is observed to be an
efficient accessing technique since it can achieve near single user performance in
situations with very large numbers of nodes in ad-hoc network while maintaining very
low receiver complexity.
5.3.1 Variation of Number of Nodes (users):
Following graphs are obtained with the variation of number of users and number of
iterations while keeping all other parameters constant.
For Nodes=2 and 4
Figure 5.4: Multiuser Detection Performance Of IDMA in AWGN channel forNumber of Nodes=2,4
0 1 2 3 4 5 6 710
-4
10-3
10-2
10-1
Eb/No /dB
BER
BER OF the SYSTEM
Nodes=2
Nodes=4
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BER versus Eb/No plot as shown in Figure: 5.4 for spreading length=16 symbols, Data
Length=128 bits, Block Length=128 and Number of iterations=20, at Eb/No=0db the
BER for 4 nodes is slightly greater than BER (just below 10-1
) obtained when number of
nodes are 2. It can be clearly seen that even if the number of nodes are doubled the BER
is only slightly increased. Furthermore at Eb/No=7db the BER becomes exactly the same.
For Nodes 4 and 8
Figure 5.5: Multiuser Detection Performance Of IDMA in AWGN channel for
Number of Nodes=4,8
BER versus Eb/No plot as shown in Figure: 5.5 for Number of iterations=30 at
Eb/No=0db the BER for 8 nodes is only slightly greater than BER (just below 10-1
)
obtained when number of nodes are 4. It can be clearly seen that even if the number of
0 1 2 3 4 5 6 7 810
-4
10-3
10-2
10-1
100
Eb/No /dB
BER
BER OF the SYSTEM
Nodes=4
Nodes=8
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nodes are doubled the BER is only slightly increased. Furthermore at Eb/No=8db the
BER becomes exactly the same (at approximately 10-4
)
For Nodes 8 and 16
Figure 5.6: Multiuser Detection Performance Of IDMA in AWGN
channel for Number of Nodes=8,16
BER versus Eb/No plot as shown in Figure: 5.6 for Number of iterations=20,at
Eb/No=0db the BER for 16 nodes is only slightly greater than BER(just above 10-1
)obtained when number of nodes are 8. It can be clearly seen that even if the number of
nodes are doubled the BER is only slightly increased. Even though the there is a notable
difference between the BER curves for Nodes=8 and 16 we can see that this difference is
becoming smaller as the Eb/No is increased. When Eb/No is increased to 7db the BER
becomes exactly the same.
Hence it is proved from the plots that there is graceful degradation in the BER slope of
IDMA with the increase of Eb/No values. IDMA is observed to be an efficient accessing
0 1 2 3 4 5 6 710
-4
10-3
10-2
10-1
100
Eb/No /dB
BER
BER OF the SYSTEM
Nodes=8
Nodes=16
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technique since it can achieve near single user performance in situations with very large
numbers of nodes in ad-hoc network while maintaining very low receiver complexity.
Performance also improves with increasing number of iterations.
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CHAPTER 06
CONCLUSIONS AND FUTURE WORK
6.1 CONCLUSIONS
The focus of this thesis has been concentrated on Multiuser detection performance of
IDMA with respect to BER analysis in Ad-Hoc networks, where the performance is
limited due to multiple access interference (MAI).
To reduce the complexity of multiuser detection and improve system performance, we
have proposed in Chapter 4 the IDMA scheme by introducing the chip-level interleavers
to conventional CDMA. We have demonstrated that this simple iterative CBC detectionalgorithm is very effective to suppress multiple MAI. It can support a large number of
nodes in wireless Ad-Hoc networks and this complexity is much lower than that of the
MMSE based detectors for conventional CDMA system.
In terms of performance analysis, we have presented BER analysis and evolution for
IDMA. This approach can accurately characterize the system performance as in Chapter
5 we have shown that the error performance of IDMA is better even when the number of
nodes is increasing due to chip interleaving. Simulation results have been provided to
confirm our analysis in AWGN channel.
In short, the proposed IDMA based MUD scheme provides an efficient and effective
solution to high rate multiuser wireless communications. The low complexity and high-
performance properties make the IDMA scheme a competitive candidate for wireless ad-
hoc networks.
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6.2 FUTURE WORK
There is much work for future study as suggested in order:
This thesis focuses on deployment of IDMA based MUD scheme in AD-HOC networks
where nodes are considered as static. In future, studies need to be carried out regarding
the employment of IDMA in Ad-Hoc networks where nodes would be considered as
mobile.
Furthermore, a simple complexity reduction technique for IDMA and a design of
multiple user distinct interleavers need to be examined. We believe that these aspects are
important to bring the potential of IDMA into ad hoc networks while keeping in mind
that not all receivers are likely to afford the full complexity. There are still many aspects
which need studies that include: synchronization of nodes to some extent, channel
estimations, and a design of MAC protocol for network nodes with different capabilities
of interference handling. Multiple interleavers need to be designed so as to minimize
memory requirements and signaling overhead by deriving multiple interleavers from one
common interleaver.
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