A

RESEARCH PROPOSAL

On

MIMO

Wireless System Technology

Submitted to

Cultural & Public Relations Department

Embassy of Japan

Submitted by

Deep Raj Bhujel

Bachelor’s Degree in Engineering

Electronics and Communication Engineering

30-May-2013

ABSTRACT

Dead spots are everywhere. They're those areas of your home or office where, no

matter how you position your router or how you point the antenna, you just can't get a

Wi-Fi signal. Almost any Wi-Fi connection, even a weak one, is sufficient to surf the

Internet or transfer data. But if distance and obstacles sap too much bandwidth from a

network, video images will start to stutter and break up. Video is what's causing this

problem on range and higher speed. The cure for the problem, is an innovation called

MIMO, short for multiple input, multiple output .The new technology, uses a number

of antennas to send multiple signals as a way to significantly increase the speed and

range of a wireless network. In tests, it is found that MIMO nearly doubled the speed

and provided superior range. Multiple-Input / Multiple Output (MIMO) technology

has emerged in the last decade as a powerful means of increasing the throughput and

performance of wireless communication systems. Research on this relatively new

technology has penetrated in a substantial way many fields, ranging from signal

processing to information / communication theory to wireless propagation. Equally

importantly, MIMO technology has made its way into current and next generation

communication standards and systems. In this paper, I will provide an overview of

MIMO systems, starting with the fundamentals of capacity, random channels, basic

transceiver architectures, diversity, space-time coding and channel estimation. I will

then review some more recent results in the areas of diversity versus multiplexing

trade-offs, input optimization / precoding, fundamental limits of coherent operation

and multi-user MIMO, including systems with interference. Finally we will cover

certain applications of MIMO techniques in current wireless systems.

TABLE OF CONTENTS

ABSTRACT ………………………………………………………………………....i

TABLE OF CONTENTS …………………………………………………………...ii

LIST OF FIGURES ………………………………………………………………..iii

LIST OF TABLES …………………………………………………………………iii

LIST OF SYMBOLS AND ABBREVIATIONS …………………………………iv

1. MOTIVATION AND OBJECTIVES …………………………………………....1

1.1 Motivation …………………………………………………………….....1

1.2 Objectives ………………………………………………………………..1

2. LITERATURE REVIEW ………………………………………………………...3

2.1 Introduction ……………………………………………………………...3

2.2 Concept of MIMO …………………………………………………….....5

2.3 Principle ……………………………………………………………….....7

2.4 How It Works ……………………………………………………………8

2.5 Channel Capacity ………………………………………………………...9

2.6 Antenna Selection ………………………………………………………..9

2.7 Outage Capacity ………………………………………………………...10

3. MIMO APPLICATIONS IN 3G WIRELESS SYSTEMS AND BEYOND ……11

3.1 Background ……………………………………………………………...11

3.2 MIMO in 3G Wireless Systems and Beyond …………………………....11

4. ACTIVITIES ……………………………………………………………………...13

4.1 MIMO testing …………………………………………………………....13

5. OUTCOMES ……………………………………………………………………..15

5.1 Applications of MIMO ………………………………………………….15

6. CONCLUSIONS AND FUTURE TRENDS …………………………………….16

7. REFERENCES …………………………………………………………………...17

LIST OF FIGURES

Figure 1 : A Multi-channel Network …………………………………………………3

Figure 2 : Understanding of SISO, SIMO, MISO and MIMO ……………………...6

Figure 3 : Working of MIMO ………………………………………………………..8

Figure 4 : MIMO channel model ……………………………………………………13

LIST OF TABLES

Table 1 : Peak Data Rates of Various MIMO Architectures ………………………..11

LIST OF SYMBOLS AND ABBREVIATIONS

MIMO …………………….Multiple Input Multiple Output

SISO ……………………...Single Input Single Output

SIMO …………………….Single Input Multiple Output

MISO …………………….Multiple Input Single Output

QoS ………………………Quality of Service

WLAN ………………..….Wireless Local Area Network

IEE ……………………….Institute of Electrical and Electronics Engineers

WiMAX ………………….Worldwide Interoperability for Microwave Access

HSDPA…………………...High-Speed Digital Packet Access

HSDPA+………………….High-Speed Digital Packet Access plus

MEAs……………………..Multiple-Element Antenna systems

ARQ ……………………...Automatic Repeat Request

3GPP ……………………..3rd Generation Partnership Project

OFDM…………………….Orthogonal Frequency Division Multiplexing

OFDMA…………………..Orthogonal Frequency Division Multiple Access

RRC……………………….Radio Resource Control

CSI………………………..Channel State Information

ITU………………………..International Telecommunication Union

BLAST ……………………Basic Local Alignment Search Tool

LTE ……………………….Long Term Evolution

PAR………………………Peak-to-Average Ratio

VSG………………………Vector Signal Generator

VSA………………………Vector Signal Analyzer

TX ………………………..Transmitter

RX ………………………..Receiver

IST-MASCOT …………...Information Society Technologies Multiple Access Space-

Time Coding Testbed

1. MOTIVATION AND OBJECTIVES

1.1 Motivation

Comprehensive broadband, integrated mobile communication will step into all mobile

4G service and communication. The 4G will be the migration from the other

generation of mobile services to overcome the limitation of boundary and achieve the

integration. The 4G of mobile services aims to total wireless.

The 4G will be developed to provide high speed transmission, next generation

internet support, seamless integrated services and coverage, utilization of higher

frequency, lower system cost, seamless personal mobility, mobile multimedia,

sufficient spectrum use, quality of service (QoS), reconfigurable network and end-to-

end IP systems.

In conventional wireless communication, a single antenna is used at the source and

another antenna is used at destination. In many cases, it gives rise to problem with

multipath fading, making difficult to meet promises aim by the 4G.

The solution to multipath fading can be solved using MIMO technology. The

following paper will outline the concept of MIMO technology and why it’s superior

to present the present day technology. That is the reason I want my research on

MIMO technology exploration and advancement to make the wireless service hassle-

free and easier.

1.2 Objectives

MIMO technology promises higher data rate, higher quality of service and better

reliability by exploiting antenna array at both the transmitter and the receiver. Signals

at both sides (transmitter and receiver) are mixed such that they either generate

multiple parallel, spatial bit pipes and/or add diversity to decrease the bit-error rate.

Diversity helps in selecting the clearest signal out of many signals, resulting in lower

bit-error rate. Multiple bit pipes effectively increase the data rate (quantitative

improvement), whereas the reduced bit-error rate improve the quality of service,

throughput and reliability (qualitative improvement).

The fundamental gain in MIMO is increased data rate. Why not use more bandwidth

or complex modulation scheme to increase the data rate? The use of more bandwidth

depends upon the availability of spectrum and again the use may be difficult to meet

the spectral efficiency. All wireless devices use a particular part of radio spectrum.

Air traffic radar, for example, operates between 960 and 1215 megahertz and

cellphone between 824 to 849 megahertz. As growing number of wireless devices

enter the consumer market, the spectrum becomes congested every year. MIMO has

potential to expand radio capacity and relieve the burden on existing bandwidth.

By spreading the transmitted signal over the multiple paths, the MIMO technology

increases the chances of signal reception at receiver. It also increases the range of

operation.

Multipath fading causes the distortion by scrambling the copy of the signals reaching

the receiver via multiple paths on bouncing of the objects. Then how does the

multipath signals work in MIMO? Proper algorithms are used at both the transmitter

and receiver to analyses the signal received from different path and different antenna

of array.

Proper spacing of antenna and signal analysis via a matrix manipulation technology

that cross-correlate the signals are the requirement of MIMO technology.

2. LITERATURE REVIEW

2.1 Introduction

Multiple Input Multiple Output (MIMO) is a smart antenna technique that increases

speed, range, reliability and spectral efficiency for wireless systems. Given the

demands that applications are placing on WLANs, MIMO chipsets will figure

prominently in new access points and network interface cards.

MIMO is one technology being considered a standard for next-generation that boosts

throughput to 100 Mbit/sec. In the meantime, proprietary MIMO technology

improves performance of existing networks.

A conventional radio (or telephony) uses one antenna to transmit a DataStream as

shown in figure 1. A typical smart antenna radio, on the other hand, uses multiple

antennas. This design helps combat distortion and interference. Examples of multiple-

antenna techniques include switched antenna diversity selection, radio-frequency

beam forming, digital beam forming and adaptive diversity combining.

Figure 2 : A Multi-channel Network

These smart antenna techniques are one-dimensional, whereas MIMO is multi-

dimensional. It builds on one-dimensional smart antenna technology by

simultaneously transmitting multiple data streams through the same channel, which

increases wireless capacity.

You can think of conventional radio (or telephony) transmission as traveling on a

one-lane highway. The speed limit governs the maximum allowable flow of traffic

through that lane. Compared with conventional radios, one-dimensional smart

antenna systems help move traffic through that lane faster and more reliably so that it

travels at a rate closer to the speed limit. MIMO helps traffic move at the speed limit

and opens more lanes. The number of lanes that are opened as shown in figure 1

multiplies the rate of traffic flow.

A characteristic of radio transmission called multipath, which had previously been

considered an impairment to radio transmission, is actually a gift of nature. Multipath

occurs when signals sent from a transmitter reflect off objects in the environment and

take multiple paths to the receiver. The researchers showed that multipath could be

exploited to multiplicatively increase the capacity of a radio system.

If each multipath route could be treated as a separate channel, it would be as if each

route were a separate virtual wire. A channel with multipath then would be like a

bundle of virtual wires.

To exploit the benefits the virtual wires offer, MIMO uses multiple, spatially

separated antennas. MIMO encodes a high-speed DataStream across multiple

antennas. Each antenna carries a separate, lower-speed stream. Multipath virtual

wires are utilized to send the lower-speed streams simultaneously.

But wireless is not as well behaved as a bundle of wires. Each signal transmitted in a

multipath environment travels multiple routes. This makes a wireless system act like

a bundle of wires with a great deal of leakage between them, causing transmitted

signals to jumble together. The MIMO receiver uses mathematical algorithms to

unravel and recover the transmitted signals.

2.2 Concept of MIMO

In radio, MIMO (commonly pronounced my-moh or me-moh), is the use of multiple

antennas at both the transmitter and receiver to improve communication performance.

It is one of several forms of smart antenna technology. Note that the terms input and

output refer to the radio channel carrying the signal, not to the devices having

antennas.

MIMO technology has attracted attention in wireless communications, because it

offers significant increases in data throughput and link range without additional

bandwidth or increased transmit power. It achieves this goal by spreading the same

total transmit power over the antennas to achieve an array gain that improves the

spectral efficiency (more bits per second per hertz of bandwidth) and/or to achieve a

diversity gain that improves the link reliability (reduced fading). Because of these

properties, MIMO is an important part of modern wireless communication standards

such as IEEE 802.11n (Wi-Fi), 4G, 3GPP Long Term Evolution, WiMAX and

HSPA+.

Wireless channels input and output modulated signals. For the purpose of modulation,

the two basic things are considered are frequency and time. The frequency plan and

time plan use ‘bits per hertz’ and ‘bits per second’ as measures for data rate

transportation.

A new dimension to upgrade the data transportation rate is spatial dimension. This is

the concept behind MIMO technology.

MIMO technology may be seen as an upgrade of SIMO and MISO. All three

technologies namely SIMO, MISO and MIMO use multipaths for increasing data

rate, throughput and reliability. Multiple paths are used by multiple transmit antenna

and multiple receiver antenna.

Multiple antennas at one end either at transmitter or at the receiver were in use long

ago. The then use of multiple antennas aimed at beam forming and spatial diversity,

which are mainly used to increase the signal to noise ratio. The improved signal to

noise ratio decreases the bit-error rate.

The use of multiple antennas adds the new dimension to digital communication

technology which forms the basis of 3G and 4G. The natural dimension of digital

technology is time. Added with that, MIMO offers a new space time axis to digital

technology. MIMO is therefore termed as ‘space time wirelesses or ‘smart antenna’.

Digital MIMO is called volume to volume wireless links as it offers parallel bit pipes

between transmitter and the receiver.

Figure 2 : Understanding of SISO, SIMO, MISO and MIMO (note that the terms

input and output refer to the radio channel carrying the signal, not to the devices

having antennas)

2.3 Principle

The increase in spectral efficiency offered by MIMO systems is based on the

utilization of space (or antenna) diversity at both the transmitter and the receiver. Due

to the utilization of space diversity, MIMO systems are also referred to as MEAs.

With a MIMO system, the data stream from a single user is de-multiplexed into nT

separate sub-streams. The number nT equals the number of transmit antennas. Each

sub-stream is then encoded into channel symbols. It is common to impose the same

data rate on all transmitters, but adaptive modulation rate can also be utilized on each

of the sub-streams. The signals are received by nR receive antennas. With this

transmission scheme, there is a linear increase in spectral efficiency compared to a

logarithmic increase in more traditional systems utilizing receive diversity or no

diversity. The high spectral efficiencies attained by a MIMO system are enabled by

the fact that in a rich scattering environment, the signals from each individual

transmitter appear highly uncorrelated at each of the receive antennas. When the

signals are conveyed through uncorrelated channels between the transmitter and

receiver, the signals corresponding to each of the individual transmit antennas have

attained different spatial signatures. The receiver can use these differences in spatial

signature to simultaneously and at the same frequency separate the signals that

originated from different transmit antennas.

Figure 3 : Working of MIMO

2.4 How It Works

The MIMO system uses multiple antennas to simultaneously transmit data, in small

pieces to the receiver, which can process the data flows and put them back together.

This process, called spatial multiplexing, proportionally boosts the data-transmission

speed by a factor equal to the number of transmitting antennas. In addition, since all

data is transmitted both in the same frequency band and with separate spatial

signatures, this technique utilizes spectrum very efficiently (Refer to figure 3)

2.5 Channel Capacity

At the input of a communication system, discrete source symbols are mapped into a

sequence of channel symbols. The channel symbols are then transmitted/ conveyed

through a wireless channel that by nature is random. In addition, random noise is

added to the channel symbols. In general, it is possible that two different input

sequences may give rise to the same output sequence, causing different input

sequences to be confusable at the output. To avoid this situation, a non-confusable

subset of input sequences must be chosen so that with a high probability, there is only

one input sequence causing a particular output. It is then possible to reconstruct all

the input sequences at the output with negligible probability of error. A measure of

how much information that can be transmitted and received with a negligible

probability of error is called the channel capacity.

2.6 Antenna Selection

The MIMO channel capacity has so far been optimized based on the assumption that

all transmit and receive antennas are used at the same time. Recently, several authors

have presented papers on MIMO systems with either transmit or receive antenna

selection. The capacity of the MIMO channel reduces with a rank deficient channel

matrix. A rank deficient channel matrix means that some columns in the channel

matrix are linearly dependent. When they are linearly dependent, they can be

expressed as a linear combination of the other Columns in the matrix. The

information within these columns is then in some way redundant and is not

contributing to the capacity of the channel. The idea of transmit antenna selection is

to improve the capacity by not using the transmit antennas that correspond to the

linearly dependent columns, but instead redistributing the power among the other

antennas. Since the total number of parallel sub channels is equal to the rank of the

channel matrix, the optimal choice is to distribute the transmit power on a subset of k

transmit antennas that maximizes the channel capacity. The optimal choice of k

transmits antennas that maximize the channel capacity results in a channel matrix that

is full rank. In, a computationally efficient, near-optimal search technique for the

optimal subset based on classical water pouring is described.

2.7 Outage Capacity

In this paper, the ergodic (mean) capacity has been used as a measure for the spectral

efficiency of the MIMO channel. The capacity under channel ergodicity is defined as

the average of the maximal value of the mutual information between the transmitted

and the received signal, where the maximization was carried out with respect to all

possible transmitter statistical distributions. Another measure of channel capacity that

is frequently used is outage capacity. With outage capacity, the channel capacity is

associated to an outage probability. Capacity is treated as a random variable, which

depends on the channel instantaneous response and remains constant during the

transmission of a .nite-length coded block of information. If the channel capacity falls

below the outage capacity, there is no possibility that the transmitted block of

information can be decoded with no errors, whichever coding scheme is employed.

The probability that the capacity is less than the outage capacity denoted by Coutage

is q. This can be expressed in mathematical terms by

Prob {C = Coutage} = q.

In this case, represents an upper bound due to fact that there is a .nite probability q

that the channel capacity is less than the outage capacity. It can also be written as a

lower bound, representing the case where there is a .nite probability (1 - q) that the

channel capacity is higher than Coutage, i.e., Prob {C > Coutage} = 1- q.

3. MIMO APPLICATIONS IN 3G WIRELESS SYSTEMS AND

BEYOND

3.1 Background

With MIMO-related research entering a maturing stage and with recent measurement

campaign results further demonstrating the benefits of MIMO channels, the

standardization of MIMO solutions in third generation wireless systems (and beyond)

has recently begun. Several techniques, seen as complementary to MIMO in

improving throughput, performance and spectrum efficiency are drawing interest,

especially as enhancements to present 3G mobile systems, e.g., HSDPA. These

include adaptive modulation and coding, hybrid ARQ, fast cell selection, transmit

diversity.

Table 1 : Peak Data Rates of Various MIMO Architectures

3.2 MIMO in 3G Wireless Systems and Beyond

There is little commercial implementation of MIMO in cellular systems as yet and

none is currently being deployed for 3G outside pure transmit diversity solutions for

MISO. Current MIMO examples include the Lucent’s BLAST chip and proprietary

systems intended for specific markets such as Iospan Wireless’ Airburst system for

fixed wireless access. The earliest lab trials of MIMO have been demonstrated by

Lucent Technologies several years ago. In the case of 3GPP, some MIMO results are

presented here.

Based on link level simulations of a combination of V-Blast and spreading code

reuse. Table 1 gives the peak data rates achieved by the down link shared channel

using MIMO techniques in the 2-GHz band with a 5-MHz carrier spacing under

conditions of flat fading. The gains in throughput that MIMO offer are for ideal

conditions and are known to be sensitive to channel conditions. In particular, the

conditions in urban channels that give rise to uncorrelated fading amongst antenna

elements are known to be suitable for MIMO. The gains of MIMO come at the

expense of increased receiver complexity both in the base station and in the handsets.

Also various factors such as incorrect channel estimation, presence of correlation

amongst antenna elements, higher Doppler frequencies, etc., will tend to degrade the

ideal system performance.

4. ACTIVITIES

Figure 4 : MIMO channel model

4.1 MIMO testing

MIMO signal testing focuses first on the transmitter/receiver system. The random

phases of the sub-carrier signals can produce instantaneous power levels that cause

the amplifier to compress, momentarily causing distortion and ultimately symbol

errors. Signals with a high PAR can cause amplifiers to compress unpredictably

during transmission. OFDM signals are very dynamic and compression problems can

be hard to detect because of their noise-like nature.

Knowing the quality of the signal channel is also critical. A channel emulator can

simulate how a device performs at the cell edge, can add noise or can simulate what

the channel looks like at speed. To fully qualify the performance of a receiver, a

calibrated transmitter, such as a VSG, and channel emulator can be used to test the

receiver under a variety of different conditions. Conversely, the transmitter's

performance under a number of different conditions can be verified using a channel

emulator and a calibrated receiver, such as a VSA.

Understanding the channel allows for manipulation of the phase and amplitude of

each transmitter in order to form a beam. To correctly form a beam, the transmitter

needs to understand the characteristics of the channel. This process is called channel

sounding or channel estimation. A known signal is sent to the mobile device that

enables it to build a picture of the channel environment. The mobile device sends

back the channel characteristics to the transmitter. The transmitter can then apply the

correct phase and amplitude adjustments to form a beam directed at the mobile

device. This is called a closed-loop MIMO system. For beamforming, it is required to

adjust the phases and amplitude of each transmitter. In a beamformer optimized for

spatial diversity or spatial multiplexing, each antenna element simultaneously

transmits a weighted combination of two data symbols.

5. OUTCOMES

5.1 Applications of MIMO

Spatial multiplexing techniques make the receivers very complex, and therefore they

are typically combined with OFDM or with OFDMA modulation, where the problems

created by a multi-path channel are handled efficiently. The IEEE 802.16e standard

incorporates MIMO-OFDMA. The IEEE 802.11n standard, released in October 2009,

recommends MIMO-OFDM.

MIMO is also planned to be used in Mobile radio telephone standards such as recent

3GPP and 3GPP2. In 3GPP, HSPA+ and LTE standards take MIMO into account.

Moreover, to fully support cellular environments, MIMO research consortia including

IST-MASCOT propose to develop advanced MIMO techniques, e.g., multi-user

MIMO (MU-MIMO).

MIMO technology can be used in non-wireless communications systems. One

example is the home networking standard ITU-T G.9963, which defines a powerline

communications system that uses MIMO techniques to transmit multiple signals over

multiple AC wires (phase, neutral and ground).

6. CONCLUSIONS AND FUTURE TRENDS

This paper reviews the major features of MIMO links for use in future wireless

networks. It is clear that the success of MIMO integration into commercial standards

such as 3G, WLAN, and beyond will rely on a fine compromise between rate

maximization (BLAST type) and diversity (space–time coding) solutions, also

including the ability to adapt to the time changing nature of the wireless channel

using some form of (at least partial) feedback. To this end more progress in modeling,

not only the MIMO channel but also its specific dynamics, will be required. As new

and more specific channel models are being proposed, it will be useful to see how

those can affect the performance tradeoffs between existing transmissions and

whether new, tailored to specific models, can be developed. Finally, upcoming trials

and performance measurements in specific deployment conditions will be key to

evaluate precisely the overall benefits of MIMO systems in real-world wireless

scenarios.

7. REFERENCES

i. http://en.wikipedia.org/wiki/MIMO

ii. http://www.nari.ee.ethz.ch/wireless/research/projects.html

iii. http://www.howstuffworks.com/

iv. www.comsoc.com

v. http://www.networkworld.com/topics/wireless.html

vi. http://www.youtube.com/watch?v=VLAgYUQCgD8

vii. George V. Tsoulos, MIMO System Technology for Wireless Communications,

CRC Press, Taylor & Francis Group, 2006

viii. http://www.swatijaininst.com/