Wireless Communications, Coroi Mihai Master CN, An2

8/2/2019 Wireless Communications, Coroi Mihai Master CN, An2

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Ing. Coroi Alexandru-Mihai, Prof. Coord. Dr. Ing. Cornel Balint

An2, master CN .

Content:1. Introduction…………………………………………………………………………………3

2. The basics of MIMO………………………………………………………………………..5

3. MIMO formats….…………………………………………………………………………..7

4. MIMO Spatial Multiplexing………………………………………………………………10

5. MIMO Space-Time Block Coding and Alamouti Codes…………………………………13

6. MIMO Antenna Beamforming……………………………………………………………14

7. MU-MIMO Multi-User MIMO…………………………………………………………...16

8. Bibliography………………………………………………………………………………19

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1. MIMO Wireless - Introduction

In our times, the wireless networks are part of our lives. We use mobile phones, for

personal use or for work, we use wireless networks to get connected with any device, here

including cellular, ipads, laptops, tablete pc, and for future even our microwave from our

kitchen or our washing machine will be online. These are just some examples of widely used

wireless networks. However, these devices are range and data rate limited. The researching

companies did great efforts to overcome these limitations. Here we present one of the get outthe limitations, called Multiple-Input, Multiple-Output (MIMO) technology. This uses MIMO

links. The multiple antennas allows MIMO systems to perform precoding (multilayer

beamforming), diversity coding (space-time coding), and spatial multiplexing.

Beamforming consists of transmitting the same signal with different gain and phase

(called wights), over all transmit antennas such that the receiver signal is improved

(maximized). The diversity consist of transmitting a single space-time coded-stream though all

the antennas. Spatial multiplexing increases network capacity by splitting a high-rate signal

into multiple lower rate streams and transmitting them though different antennas. In spatial

multiplexing, the receiver can successfully decode each stream given, that the received signals

have sufficient spatial signatures and the receiver has enough antennas to separate the streams.

The result of using these MIMO techniques is higher data rate of longer transmit power. Here I

will present a study of diversity coding for MIMO systems. Different space-time block coding

(STBC) schemes including Alamouti’s STBC for 2 transmit antennas as well as orthogonal

STBC for 3 and 4 transmit antennas are explored. These techniques can be simulated to

simulate the performance according to their bit-error rates using BPSK, QPSK, 16-QAM, 64-

QAM modulation schemes.

It is a long time since Tesla, using Maxwell and Hertz’s work on transmission of

electromagnetic waves, demonstrated the transmission of information through a wireless

medium using radio waves. The Second World War lead to much interest in this area, giving

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way to many of the theoretical foundations of communications. Claude Shannon’s work in

1948, which provided an upper bond of the error-free data rate under the signal-to-noise (SNR)

constraint, appeared during that time. Wireless networks widely used today include: Wi-FI,

LTE (3G long term evolution) or other cellular networks, wireless mesh networks, wireless

Local Area Networks (w LAN), personal area networks (PAN), and wireless sensor networks.

The increasing demand for these networks has turned spectrum into a precious resource. For

this reason, there is always a need for methods to pack more bits (or individual users) per Hz.

MIMO technology has been developed over many years. Not only did the basic MIMO

concepts need to be formulated, but in addition to this, new technologies needed to be

developed to enable MIMO to be fully implemented. New levels of processing were needed to

allow some of the features of spatial multiplexing as well as to utilize some of the gains of

spatial diversity.

Up to 1990’s spatial diversity was often limited to systems that switched between two

antennas or combined the signals to provide the best signal. Also various forms of beam

switching were implemented, but in view of the levels of processing involved and the degrees

of processing available, the systems were generally relatively basics. However with the

additional levels of processing power that started become available, was possible to utilize both

spatial diversity and full spatial multiplexing.

The initial work on MIMO systems focused on basic spatial diversity – here the MIMO

system was used to limit the degradation caused by multipath propagation. However this was

only the first step as system was started to utilize the multipath propagation to advantage,

turning the additional signal paths into what might effectively be considered as additional

channels to carry additional data. Two researchers: Arogyaswami Paulraj and Thomas Kailath

were first to propose the use of spatial multiplexing using MIMO in 1993 and in the following

year their US patent was granted. However it fell to Bell Labs to be the first to demonstrate a

laboratory prototype of spatial multiplexing in 1998.

This represents a particular solution that has caught researcher’s attention is the use of

multiple antennas at both transmitter (TX) and receiver (RX) parts.

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2. The basics of MIMO

A channel may be affected by fading and this will impact the signal to noise ratio. In

turn this will impact the error rate, assuming digital data is being transmitted. The principle of

diversity is to provide the receiver with multiple versions of the same signal. If these can be

made to be affected in different ways by the signal path, the probability that they will be

affected at the same time is reduced. Accordingly, diversity helps to stabilize a link and

improves performance, reducing error rate. Several different diversity modes are available and

provide a number of advantages:

- Time diversity: Using time diversity a message can be transmitted at different times,

for example using different timeslots and channel coding .

- Frequency diversity: This form of diversity uses different frequencies. It may be in

the form of using different channels, or technologies such as spread spectrum / OFDM .

- Space diversity: Space diversity used in the broadcast sense of the definition is used

as the basis for MIMO. It uses antennas located in different positions to take advantage of

different radio paths that exist in a typical terrestrial environment,

MIMO is effectively a radio antenna technology as it uses multiple antennas at the

transmitter and receiver to enable a variety of signal paths to carry the data, choosing separate

paths for each antenna to enable multiple signal paths to be used.

It is important to note that each antenna element on a MIMO system operates on the

same frequency and therefore does not require extra bandwidth. Also, to fair comparison, the

total power thought all antenna elements is less than or equal to that of a single antenna system,

like:

∑=

≤ N

k

k P p1

(1)

where N is the total number of antennas elements, K

p is the power allocated though the

thk antenna element, and P is the power if the system had a single antenna element.

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As a result of these multiple antennas MIMO wireless is able to considerably increase

the capacity of a given channel while still obeying Shannon’s law. By increasing the number of

receive and transmit antennas it is possible to linearly increase the throughput of the channel

with every pair of antennas added to the system. This makes MIMO wireless technology one of

the most important wireless techniques to be employed in recent years. As spectral bandwidth

is becoming an ever more valuable commodity for radio communications systems, techniques

are needed to use the available bandwidth more efficiently.

3. MIMO formats:

The different forms of antenna technology refer to a single or a multiple inputs and

outputs. These are related to the radio link. In this way the input is the transmitter as it

transmits into the link or signal path, and the output is the receiver. It is a the output of the

wireless link.

MIMO – SISO

It is the simplest form of radio link that can be defined in MIMO terms. It is effectively

a standard radio channel. There in no diversity and no additional processing required.

Fig. 2. SISO – Single Input Single Output

The SISO channel is limited in terms of performance. Interference and fading will

impact the system more than a MIMO system using some form of diversity, and the channel

bandwidth is limited by Shannon’s law – the throughput being dependent upon the dhannel

bandwidth and the signal to noise ratio.

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MIMO – SIMO

This form of Smart Antenna occurs when the transmitter has a single antenna and the

receiver has multiple antennas. This is known as receive diversity. It is often o enable a

receiver system that receives signals from a number of independent sources to combat the

Fig.3. Single Input Multiple Output.

effects of fading. It has been used for many years with short wave listening / receiving stations

to combat the effects of ionospheric fading and interference.

The advantage of SIMO is the simplicity of implementing, although it does have some

disadvantages in that the processing is required at the receiver. The use of SIMO may be quite

acceptable in many situations, and also where the receiver is located in a mobile device such as

a cellphone, the levels of processing may be limited by size, cost and battery life. Two forms of

SIMO can be used:

Switched diversity SIMO: This form of SIMO looks for the strongest signal and

switches to that antenna.

Maximum ratio combining SIMO: This form of SIMO takes both signals and sums

them to give them a combination. In this way, the signals from both antennas contribute to the

overall signal.

MIMO – MISO

In this case the same signal is transmitted redundantly from the two transmitter

antennas. The receiver is the able to receive the optimum signal, from which is extracted the

required data.

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Fig. 4. Multiple Input Single Output

The advantage of using of MISO is that the multiple antennas and the redundancy

coding / processing is moved from the receiver to the transmitter. In instances such as

cellphone this is a significant advantage in terms of space for the antennas and reducing the

level of processing required in the receiver for the redundancy coding. This has a positive

impact on size, cost and battery live as the lower level of processing requires less battery

consumption.

MIMO – MIMO

It is where there are more than one antenna at either end of the radio link . MIMO can

be used to provide improvements in both channel robustness as well as channel throughput.

Fig. 5. Multiple Input Multiple Output

In order to be able to benefit from MIMO fully it is necessary to be able to utilize

coding on the channels to separate the data from the different paths. This requires processing,

but provides additional channel robustness / data throughput capacity.

There are many formats of MIMO that can be used from SISO, through SIMO and

MISO to the full MIMO systems. These are all able to provide significant improvements of

performance, but generally at the cost of additional processing and the number of antennas

used. Balances of performance against costs, size, processing available and the resulting

battery life need to be made when choosing the correct option.

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4. MIMO Spatial Multiplexing

One of the key advantages of MIMO spatial multiplexing is the fact that it is able to

provide additional data capacity. MIMO spatial multiplexing achieves this by utilizing the

multiple paths and effectively using them as additional “channels” to carry data. The maximum

amount of data that can be carried by a radio channel is limited by the physical boundaries

defined under Shannon’s Law.

Shannon’s Law and MIMO spatial multiplexing

As with many areas of science, there a theoretical boundaries, beyond which it is not

possible to proceed. This is true for amount of data that can be passed along a specific channel

in the presence of noise. The law that governs this is called Shannon’s Law. It is named after

the man who formulated it. This is particularly important because MIMO wireless technology

provides a method not of breaking the law, but increasing data rates beyond those possible on a

single channel without its use.

Shannon’s law defines the maximum rate at which error free data can be transmitted

over a given bandwidth in the presence of noise, It is usually expressed in the form:

)/1(log2 N S W c += (2)

Where C is the channel capacity in bits per second W is the bandwidth in Hertz, and

S/N is the SNR (Signal to Noise Ratio).

From this it can be seen that there is an ultimate limit on the capacity of transmitting

data through a channel with a given bandwidth. And when this point is reached, the capacity is

also limited by the signal to noise ratio of the received signal. In view of these limits many

decisions need to be made about the way in which transmission is made. The modulation

scheme can play a major part in this. The channel capacity can be increased by using higher

order modulation schemes. Thus a balance exists between the data rate and the allowable error

rate, signal to noise ratio and power that can be transmitted.

While some improvements can be made in terms of optimizing the modulation scheme

and improving the signal to noise ratio, these improvements are not always easy or cheap to

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achieve, and they are invariably a compromise, balancing the various factors involved. It is

therefore necessary to look at other ways of improving the data throughput for individual

channels. MIMO results receive a considerable degree of interest.

MIMO spatial multiplexing

To take advantage of the additional throughput capability, MIMO utilizes several sets

of antennas. In many MIMO systems, just two are used, but there is no reason why further

antennas cannot be employed and this increases the throughput. In any case for MIMO spatial

multiplexing the number of receive antennas must be equal to or greater than the number of

transmit antennas. MIMO wireless systems utilize a mathematical matrix approach.

Fig.6. Block diagram of a MIMO system.

Data streams 1t , 2t ... nt can be transmitted from antennas 1, antennas 2, … antennas

n. These are a variety of paths that can be used to differentiate between the different data

streams it is necessary to use. These can be represented by the properties 12h , travelling from

transmit, three receive antenna system matrix can be set up:

3312211111 t ht ht hr ++=

3322221122 t ht ht hr ++=

3332231133 t ht ht hr ++=

Where 1r = signal received at antenna 1, 2r is the signal received at antenna 2 and so

forth. In matrix format we can do representation:

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][][][ T H R ×=

Where the channel have r N outputs and t N inputs is denoted as a t r N N × matrix:

=

t r r r

t

t

N N N N

N

N

hhh

hhh

hhh

H

,2,1,

,22,21,2

,12,11,1

Where each entry jih , denotes the attenuation and phase shift (transfer function)

between theth j transmitter and the th

i receiver.

To recover the transmitted data-stream at the receiver it is necessary to perform aconsiderable amount of signal processing. First the MIMO system decoder must estimate the

individual channel transfer characteristic jih , to determine the channel transfer matrix. Once

all of this can be estimated, then the matrix [H] has been produced and the transmitted data

streams can be reconstructed by multiplying the received vector with the inverse of the transfer

matrix.

][][][ 1 R H T ×=−

This process can be likened to the solving of a set of N linear simultaneous equations to

reveal the values of N variables.

In reality the situation is little more complicated, because the propagation is never quite

this straightforward, and in addition to this each variable consists of an ongoing data stream,

this nevertheless demonstrates the basic principle behind MIMO wireless systems.

5. MIMO Space Time Block Coding and Alamouti Codes

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MIMO Alamouti coding

A particularly elegant scheme for MIMO coding was developed by Alamouti. The

associated codes are often called MIMO Alamouti codes or just Alamouti codes.

The MIMO Alamouti scheme is an ingenious transmit diversity scheme for two

transmit antennas that does not require transmit channel knowledge. The MIMO Alamouti

code is a simple space time block code that he developed in 1998.

Differential space time block code

Differential space time block coding is a form of space time block coding that does not need to

know the channel impairments in order for the signal to be decoded. The differential space

time block codes are normally based upon the more standard space-time block codes. One

block-code is transmitted from a set in response to a change in the input signal. This enables

the system to work because the differences among the blocks in the set are designed to allow

the receiver to extract the data with good reliability.

6. MIMO Antenna Beamforming

The MIMO antenna technologies used are key to the overall MIMO performance.

Additionally MIMO beamforming is an option that is coming to the fore.

As various forms of technology improve the MIMO antenna technology can be pushed further

allowing techniques like MIMO beamforming to be considered.

MIMO antenna & MIMO beamforming development

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For many years antenna technology has been used to improve the performance of

systems. Directive antennas have been used for very many years to improve signal levels and

reduce interference.

Directive antenna systems have, for example, been used to improve the capacity of

cellular telecommunications systems. By splitting a cell site into sector where each antenna

illuminates 60° or 120° the capacity can be greatly increased - tripled when using 120°

antennas.

With the development of more adaptive systems and greater levels of processing

power, it is possible to utilise antenna beamforming techniques with systems such as MIMO.

MIMO beamforming smart antennas

Beamforming techniques can be used with any antenna system - not just on MIMO

systems. They are used to create a certain required antenna directive pattern to give the

required performance under the given conditions.

Smart antennas are normally used - these are antennas that can be controlled automatically

according the required performance and the prevailing conditions.

Smart antennas can be divided into two groups:

- Phased array systems: Phased array systems are switched and have a number of pre-

defined patterns - the required one being switched according to the direction required.- Adaptive array systems (AAS): This type of antenna uses what is termed adaptive

beamforming and it has an infinite number of patterns and can be adjusted to the requirements

in real time.

MIMO beamforming using phased array systems requires the overall system to determine the

direction of arrival of the incoming signal and then switch in the most appropriate beam. This

is something of a compromise because the fixed beam is unlikely to exactly match the required

direction.

Adaptive array systems are able to direct the beam in the exact direction needed, and

also move the beam in real time - this is a particular advantage for moving systems - a factor

that often happens with mobile telecommunications. However the cost is the considerable extra

complexity required.

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7. MU-MIMO Multi-User MIMO

MU-MIMO is an enhanced form of MIMO technology that is gaining acceptance. MU-

MIMO, Multi-user MIMO enables multiple independent radio terminals to access a system

enhancing the communication capabilities of each individual terminal.

MU-MIMO exploits the maximum system capacity by scheduling multiple users to be

able to simultaneously access the same channel using the spatial degrees of freedom offered by

MIMO.

To enable MU-MIMO to be used there are several approaches that can be adopted, and

a number of applications / versions that are available.

MU-MIMO basics

MU-MIMO provides a methodology whereby spatial sharing of channels can be

achieved. This can be achieved at the cost of additional hardware - filters and antennas - but

the incorporation does not come at the expense of additional bandwidth as is the case when

technologies such as FDMA, TDMA or CDMA are used.

When using spatial multiplexing, MU-MIMO, the interference between the different

users on the same channel is accommodated by the use of additional antennas, and additional

processing when enable the spatial separation of the different users.

There are two scenarios associated with MU-MIMO, Multi-user MIMO:

- Uplink - Multiple Access Channel, MAC: The development of the MIMO-MAC is

based on the known single user MIMO concepts broadened out to account for multiple users.

- Downlink - Broadcast Channel, BC : The MIMO-BC is the more challenging

scenario. The optimum strategy involves pre-interference cancellation techniques known as

"Dirty Paper Coding", DPC - see below. This is complemented by implicit user scheduling and

a power loading algorithm.

MU-MIMO Multi-User MIMO advantages

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MU-MIMO, Multi-user MIMO offers some significant advantages over other

techniques:

- MU-MIMO systems enable a level of direct gain to be obtained in a multiple access

capacity arising from the multi-user multiplexing schemes. This is proportional to the number

of base station antennas employed.

- MU-MIMO appears to be affected less by some propagation issues that affect single

user MIMO systems. These include channel rank loss and antenna correlation - although

channel correlation still affects diversity on a per user basis, it is not a major issue for multi-

user diversity.

- MU-MIMO allows spatial multiplexing gain to be achieved at the base station without

the need for multiple antennas at the UE. This allows for the production of cheap remote

terminals - the intelligence and cost is included within the base station.

The advantages of using multi-user MIMO, MU-MIMO come at a cost of additional

hardware - antennas and processing - and also obtaining the channel state information which

requires the use of the available bandwidth.

MIMO-MAC

This form of MU-MIMO is used for a multiple access channel - hence MIMO and it is

used in uplink scenarios.

For the MIMO-MAC the receiver performs much of the processing - here the receiver

needs to know the channel state and uses Channel Sate Information at the Receiver, CSIR.

Determining CSIR is generally easier than determining CSIT, but it requires significant levels

of uplink capacity to transmit the dedicated pilots from each user. However MIMO MAC

systems outperform point-to-point MIMO particularly if the number of receiver antennas is

greater than the number of transmit antennas at each user.

MIMO-BC

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This form of MU-MIMO is used for the MIMO broadcast channels, i.e. the downlink.

Of the two channels, BC and MAC, it is the broadcast channel that is the more challenging

within MU-MIMO.

Transmit processing is required for this and it is typically in the form of pre-coding and

SDMA, Space Division Multiple Access based downlink user scheduling. For this the

transmitter has to know the Channel State Information at the Transmitter, CSIT. This enables

significant throughput improvements over that of ordinary point to point MIMO systems,

especially when the number of transmit antennas exceeds that of the antennas at each receiver.

Dirty Paper Coding, DPC

Dirty Paper Coding, DPC is a technique used within telecommunications scenarios,

particularly wireless communications to provide efficient transmission of digital data through a

channel that is subject to interference, the nature of which is known to the transmitter.

The Dirty Paper Coding, DPC, technique consists of precoding the data so the

interference data can be read in the presence of the interference. The pre-coding normally uses

the Channel State Information.

To explain Dirty Paper Coding, DPC, an analogy of writing on dirty paper can be used.

Normally black ink would be used, but if the paper is dirty, i.e. black, then the writing cannot

be read. However if the writing was in white, although it could not be read on white paper, it

would be perfectly legible on black, or dirty paper. The same technique is used on the data

transmission, although the nature of the interference must be known so that the pre-coding can

be incorporated to counter the effect of the interference.

Multi-user MIMO is still in its infancy, and many developments are underway to

determine the optimum formats for its use. Coding types as well as levels of channel state

indication are being determined as these use up valuable resource and can detract from the

overall data throughput available. However the significant gains that can be made by using

MU-MIMO, multi-user MIMO mean that it will be introduced in the foreseeable future.

Bibliography:

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[1]. Luis Miguel Cortés Pena, “MIMO Space-Time Block Coding (STBC): Simulations and

Results”, [2009].

[2]. Branka Vucetik, Jinhong Yuan, “Space-Time Coding”, University of Sydney, [2003]. [3].

www.wikipedia.com

[4]. www.radio-electronics.com

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http://www.wikipedia.com/

http://www.radio-electronics.com/


http://www.wikipedia.com/


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Wireless Communications, Coroi Mihai Master CN, An2