Abin Report

8/6/2019 Abin Report

http://slidepdf.com/reader/full/abin-report 1/21

BLAST 1

MOUNT ZION COLLEGE OF ENGINEERING, KADAMMANITTA

1. INTRODUCTION

The explosive growth of both the wireless industry and the Internet is creating a

huge market opportunity for wireless data access. Limited internet access, at very low

speeds, is already available as an enhancement to some existing cellular systems. However

those systems were designed with purpose of providing voice services and at most short

messaging, but not fast data transfer. Traditional wireless technologies are not very well

suited to meet the demanding requirements of providing very high data rates with the

ubiquity, mobility and portability characteristics of cellular systems. Increased use of

antenna arrays appears to be the only means of enabling the type of data rates and

capacities needed for wireless internet and multimedia services. While the deployment of

base station arrays is becoming universal it is really the simultaneous deployment of base

station and terminal arrays that can unleash unprecedented levels of performance by

opening up multiple spatial signaling dimensions .Theoretically, user data rates as high as

2 Mb/sec will be supported in certain environments, although recent studies have shown

that approaching those might only be feasible under extremely favorable conditions-in the

vicinity of the base station and with no other users competing for band width. Some

fundamental barriers related to the nature of radio channel as well as to the limited band

width availability at the frequencies of interest stand in the way of high data rates and low

cost associated with wide access..



BLAST 2


FUNDAMENTAL LIMITATIONS IN WIRELESS

DATA ACESS

Ever since the dawn of information age, capacity has been the principal metric

used to asses the value of a communication system. Since the existing cellular system

were devised almost exclusively for telephony, user data rates low .Infact the user data

were reduced to the minimum level and traded for additional users. The value of a system

is no longer defined only by how many users it can support, but also by its ability to

provide high peak rates to individual users. Thus in the age of wireless data, user data

rates surges as an important metric.

Trying to increase the data rates by simply transmitting more; Power is extremely

costly. Furthermore it is futile in the contest of wherein an increase in everybody¶s

transmit power scales up both the desired signals as well as their mutual interference

yielding no net benefit. Increasing signal bandwidth along with the power is a more

effective way of augmenting the data rate. However radio spectrum is a scarce and very

expensive resource. Moreover increasing the signal bandwidth beyond the coherent

bandwidth of the wireless channel results in frequency selectively. Although well-

established technique such as equalization and OFDM can address this issue, their

complexity grows with the signal bandwidth. Spectral efficiency defined as the capacity

per unit bandwidth has become another key metric by which wireless systems are

measured. In the contest of FDMA and TDMA, the evolutionary path has led to

advanced forms of dynamic channel assessment that enable adaptive and more aggressive

frequency reuse.In the context of multi-user detection and interference cancellation

techniques.



BLAST 3


SPACE: THE LAST FRONTIER

As a key ingredient in the design of more spectrally efficient systems. In recent years

space has become the last frontier. The entire concept of frequency reuse on which

cellular systems are based constitutes a simple way to exploit the spatial dimension. Cell

sectorisation, a widespread procedure that reduces interference can also be regarded as a

form of spatial processing. Moreover, even though the system capacity is ultimately

bounded, the area capacity on a per base station basis. Here, base station antenna array

are the enabling tools for wide range of spatial processing techniques devised to enhance

desired to enhance desired signals and mitigate interference. Coverage can be extended

and tighter user packaging becomes possible, enabling in turn larger cell sizes and higher

capacity can be extended even beyond the point at which every unit of bandwidth is

effectively used in every sector through space division multiple access (SDMA), which

enables the reuse of the same bandwidth by multiple users within a given sector as

long as they can be spatially discriminated.



BLAST 4


LIFTING THE LIMITS WITH TRANSMIT AND

RECEIVE ARRAYS

Until recently, the deployment of antenna arrays in mobile systems was

contemplated-because of size and cost considerations-exclusively at base station sites.

The principle role of those arrays, long before interference suppression and other signal

processing advances were conceived, was to provide spatial diversity against fading.

In wireless systems, radio waves do not propagate simply from transmit antenna to

receive antenna, but bounce and scatter randomly off objects in environment. This

scattering is known as multipath as it result in multiple copies of the transmitted signals

arriving at the receiver via different scattered paths. Multipath has always been regarded

as impairment, because the images arrive at the receiver at slightly different times and

thus can interfere destructively, canceling each other out. However recent advances in

information theory have shown that, with simulations use of antenna arrays at both base

station and terminal, multipath interference can be not only mitigated, but actuallyexploited to establish multiple parallel channels that operate simultaneously and in the

same frequency band. Based on this fundamental idea, a class of layered space-time

architecture was proposed and labeled BLAST. Using BLAST the scattering

characteristics of the propagation environment is used to enhance the transmission

accuracy by treating the multiplicity of the propagation environment is used to enhance



BLAST 5


the transmission accuracy by treating the multiplicity of scattering paths as separate

parallel sub channels. The original scheme D-BLAST was a wireless set up that used a

multi element antenna array at both the transmitter and receiver, as well as diagonally

layered coding sequence. The coding sequence was to be dispersed across diagonals in

space-tome. In an independent Rayleigh scattering environment, this processing structure

leads to theoretical rates that grow linearly with the number of antennas with these rates

approaching 90% of Shannon capacity. Rayleigh scattering refers to the scattering of

light off the molecules of air, and can be extended to. The original scheme D-BLAST

was a wireless set up that used a multi element antenna array a both the transmitter and

receiver, as well as diagonally layered coding sequence. The coding sequence was to be

dispersed across diagonals in space-time. In an independent Rayleigh scattering

environment, this processing structure leads to theoretical rates that grow linearly withthe number of antennas these rates approaching 90% of Shannon capacity. Rayleigh

scattering of light off the molecules of air, and an be extended to scattering from particles

up to about a tenth of the wavelength of light. Rayleigh scattering can be considered to be

elastic scattering because the energies of scattered photons do not change.

The researchers foun d that the original D-BLAST concept was tough to implement, so

they simplified it to its most current iteration vertical BLAST. The BLAST technology

essentially exploits a concept that other researchers believed was impossible. The prevailing view was that each wireless transmission needed to occupy a separate

frequency, similar to the way in which FM radio within a geographical area are allocated

separate frequencies. Otherwise, the interferences are too overwhelming for quality

communications. The BLAST researchers, however, theorized it is possible to have

several transmissions occupying the same frequency band. Each transmission uses its



BLAST 6


own transmitting antenna. Then, on the receiving end, multiple antennas again are used,

along with innovative signal processing, to separate the mutually interfering

transmissions from each other. Thus the capacity of a given frequency band increases

proportionally to the number of antennas.

The BLAST prototype, built to test this theory, uses an array of eight transmit

and 12 receive antennas. During its first weeks of operation, it achieved unprecedented

wireless capacities of at least 10 times the capacity of today¶s fixed wireless loop

systems, which are used to provide phone service in rural and remote areas. ³This new

technology represents an opportunity for future wireless systems of extraordinary

communications efficiency,´ said Bell Labs researcher Reinaldo Valenzuela, who headed

the BLAST research team. ³This experiment, which was designed to illustrate the basic principle, represents only a first step of using the new technology to achieve higher

capacities.´

The advanced signal-processing techniques used in BLAST were first developed

by researcher Gerard Foschini from a novel interpretation of the fundamental capacity

formulas of Claude Shannon¶s Information Theory, first published in 1948. while

Shannon¶s theory dealt with point-to-point communications, the theory used in BLAST

relies on ³volume-to-volume´ communications, which effectively gives Information

Theory a third, or spatial, dimension, besides frequency and time. This added dimension,

said Foshini, is important because ³when and where noise and interference turn out to be

severe, each bit (of data) is well prepared to weather such impairments.´ The technology

is eventually expected to be deployed in base station equipment and mobile devices such

as note book PCs and PDAs so that mobile operators can deliver higher data services too

substantially greater number of subscribers than is possible today using the best 3G

network technology available.



BLAST 7


OVERVIEW OF BLAST SYSTEM

V-BLAST takes single data stream and demultiplexes it in to m substreams. Each

substream is encoded into symbols and feed into separate transmitter. Transmitter 1

through M operate co channel at a symbol rate of 1/T symbols per second. Eachtransmitter utilizes QAM. QAM combines phase modulation with AM. Since all the sub

streams are transmitted in the same frequency band, spectrum is used very efficiently

Since the user¶s data is being sent in parallel over multiple antennas used. QAM is an

efficient method for transmitting data over limited bandwidth channel. It is assumed that

the same constellation is used for each sub streams and the transmission is organized in

to burst of L symbols. The power of each transmitter is proportional to 1/M and total

radiated power is constant irrespective of the number of transmitting antennas. BLAST¶s

receivers operate co channel, each receiving signals emanating from all M of the

transmitting antennas. It is assumed that the channel-time variation is negligible over the

symbol periods in a burst.



BLAST 8


BLAST¶S SIGNAL DETECTION

At the receiver, an array of antennas is again used to pick up the multiple

transmitted sub streams and their scattered images. Each receiver antenna sees the entire

transmitted sub streams super imposed, not separately. However, if the multipath

scattering is sufficient is sufficient, then the multiple sub streams are located at different

points in space .Using sophisticated signal processing, these slight difference in

scattering allow the sub streams to be identified and recovered. In effect the unavoidable

multipath is exploited to provide a useful spatial parallelism that is used to greatly

improve data transmission rates. Thus when using the BLAST technique, the more

multipath, the better, just the opposite of the conventional systems. The blast signal

processing algorithms used at the receiver are the heart of the technique. At the bank of

receiving antennas, high speed signal processors look at the signals from all the receiver

antennas simultaneously, first extracting the strongest signal have been removed as a

source of interference. Again the ability to separate the sub streams depends on the slight

differences in the way the different sub streams propagate through the environment. Let

us assume a signal transmitted vector symbol with symbol-synchronous receiver

sampling and ideal timing. If a= (a1, a2, a3,«. am) T is the vector transmitted symbols,

then the receiver N vector is r1=Ha+v, where H is the matrix channel transfer function

and V is a noise vector. Signal detection can be done using adaptive, antenna array

techniques, sometimes called linear combinational nulling. Each sub stream is

sequentially understood as the desired signal. This implies that the other substream will

be understood as interference. One nulls out this interference by weighting the interfering

signals they go to zero (known as zero forcing). While these linear nullings work, on

linear approaches can be used in conjunction with them for overall result. Symbol

cancellation is one such technique. Using interference from already detected componentsof interfering signals are subtracted to form the received signal vector. The end result is a

modified receiver vector with few interferes present in the matrix. Bell labs actually tried

both approaches. The result showed that adding the nonlinear to the linear yielded the

best performance and dealing with the strongest channel, first (thus removing it as and

interference) give the best overall SNR. If all components of µa¶ are assumed to be the



BLAST 9


part of the same constellation, it would be expected that the component with the smallest

SNR would dominate the overall error performance. The strongest channel then becomes

the place to start symbol cancellation. This technique has been called the ³best-first´

approach and has become the de-facto way to do signal detection from an RF stream. But

what the Bell labs guys found is that if you evaluate the SNR function at each stage of

the detection process, rather than just at the beginning, you come up with a different

ordering that is also (minmax) optimal.

As its core V-BLAST is an iterative cancellation method that depends on

computing a matrix inverse to solve the zero forcing function. The algorithm works by

detecting the strongest data stream from the received signal and repeating the process for

the remaining data streams. While the algorithm complexity is linear with the number of transmitting antennas, it suffers performance degradation through the cancellation

process. If cancellation is not perfect, it can inject more noise in to the system and

degrade detection.

The essential difference between D-BLAST and V-BLAST lies in the vector

encoding process. In D-BLAST, redundancy between the sub streams is introduced

through the use of specialized inter-sub stream block coding. In D-BLAST code blocks

are organized along diagonals in space-time. It is this coding that leads to D-BLAST¶s

higher spectral efficiencies for a given number of transmitters and receivers. In V-

BLAST, however, the vector encoding process is simply a demultiplex operation

followed by independent bit-to-symbol mapping of each sub stream. No inter-sub stream

coding, or coding of any kind, is required, though conventional coding of the individual

sub streams may certainly be applied.



BLAST 10


BLAST IN THE REAL WORLD

Two familiar factors are essential to the success of a BLAST: technology and

economics. On the technology side, scalar systems (those currently in use) are far less

spectrally efficient than BLAST ones. They can encode B bits per symbols using a single

constellation of 2B points. Vector systems can realize the same rate using M

constellation of 2B/M points each. Large spectral efficiencies (that is, a large B) are more

practical. Let¶s take an example. If you want 26 bps/Hz with a 23%roll off, you need to

have (26*1.32)=32bits/symbol.a scalar system would require 232 points, which is around

4 billion. No wireless system will put up 4 billon transmitters. Ever. This means the

vector is the approach is the only one that one can ever hope to fulfill such a bit-per-

second rate. On the economic side, BLAST calls for an infrastructure that will take

considerable resource to develop. Cell antennas will have to be redesigned to evolve with

the increase in data rates. The first change will have to occur at the cell towers, and then

at the receiver. The cell tower will have to go from a switched-beam (phase-swept and

the like) to a steered-beam configuration. On the plus side, much of the development can

be gradual. Older ³diversity´ antennas will most likely retained as a fallback for the

worst-case channel environment (which means single path flat-fading at low mobile

speeds), so new antennas can be added gradually .A carrier could go from one to two

four transmit path per sector, upping the cost of service with each incremental

performance gain. Proceeding with a hardware-based migration will yield balanced gains

in the forward and reverse links. Carriers are very sensitive to the costs, however

incremental, of deploying new systems. Since CDMA systems will upgrade faster than

GSM systems. This means that CDMA carriers will be first to market with higher

bandwidth systems, as Verizon¶s recent 2.5G 1RTT rollout has shown. Asked about its

plans for BLAST, Verizon¶s reps indicated that the discussion was premature, but thatthey might have more to say about it in the first quarter of 2003. That seems enough of a

nom-denial to indicate that BLAST is part of the company¶s long range planning.



BLAST 11


BLAST vs. EXISTING SYSTEMS

What makes BLAST different from any other single-user that uses multiple

transmitters? After all, we can always drive all the transmitters using a single user¶s data,

even if it is sub streams. Well, unlike code-division or a speedspectrum approach, the

total bandwidth those QAM systems require. Unlike a Frequency Division Multiple

Access (FDMA) approach, each transmitted signals occupies the entire signal bandwidth.

And finally, unlike Time Division Multiple Access (TDMA), the entire system

bandwidth is used simultaneously by all of the transmitters all of the time .BLAST can be

best used in CDMA such as Verizon or Sprint, rather than a gem system such as AT&T.

The BLAST system does not impose orthonalization ot transmitted signals. The reason

for this is simple, obvious, and rather elegant. The Blast propagation environment of the

real world provides significant multipath latencies one receiver. Rather than fight against

these latencies, BLAST exploits them to provide the signal decor relation necessary to

separate the co-channel signals blast uses the same effect that cause ghosting in TV

pictures as a sort of clock to allow the various signals to be extracted.



BLAST 12


LABORATARY RESULS

A laboratory prototype of a V-BLAST system has-been constructed for the

purpose of demonstrating the feasibility of the BLAST approach. The prototype operates

at a carrier frequency of 1.9 GHz and a symbol/sec, in a bandwidth of 30 KHz. The

system was operated and characterized in the actual laboratory/office environment not a

test range, with transmitter and receiver separations up to about 12 meters. This

environment is relatively benign in that the delay spread is negligible, the fading rates are

low and there is significant near-field scattering from near by equipment and office

furniture. Nevertheless, it is a representative indoor lab/office situation, and no attemptwas to ³tune´ the system to the environment, or to modify the environment in anyway.

The antenna arrays consisted of /2 wire dipoles mounted in various arrangements. For

the results shown below, the receive dipoles were mounted on the surface of a metallic

hemisphere approximately 20cm in diameter, and transmit dipoles were mounted on a

flat sheet, in a roughly rectangular array with about /2 inter-element spacing. In general,

the system performance was found to be nearly independent of small details of the array

geometry. Figure 6 shows the results obtained with the prototype system, using M=8

transmitters and N=12 receivers. In this experiment, the transmit and receive arrays wereeach placed at a single representative position within the environment, and the

performance characterized. The horizontal axis is spatially averaged receiver SNR. The

vertical axis is the block error rate, where a ³block´ is defined as a single transmission

burst. In this case, the burst length L is 100 symbol duration of which is used for training.

In this experiment, each of the eight sub streams utilized uncoded 16-QAM, i.e.

4 bits/symbol/transmitter, so that the payload block size is 8*4*80=2560 bits. The spectral

efficiency of this configuration is 25.9bps/Hz and the payload efficiency is 80% of the

above, or 20.7 bps/Hz, corresponding to a payload data rate of 621 Kbps in 30 KHz

bandwidth.

The upper curve in fig. 6 shows performance obtained when conventional nulling

is used. The lower curve shows performance using nulling and optimally-ordered



BLAST 13


cancellation. The average difference is about 4 db, which corresponds to a raw spectral

efficiency differential (for this configuration) of around 10 bps/Hz. Figure 7 shows

performance results obtained using the same BLAST system configuration ( M=8, N=12,

16-QAM) when the receive array was left fixed and the transmit array was located at

different positions throughout the environment. In each case, the transmit power was

adjusted so that large received SNR was 24+/-0.5db. Nulling with optimized cancellation

was used. It can be seen that operation at this spectra efficiency is reasonably robust with

respect to antenna position. In all positions, the system had at least 2 orders of magnitude

margin relative to 10^-2 BER. For a completely uncoded system, these are entirely

reasonable error rates, and application of ordinary error correcting codes would

significantly reduce this. At 34 db SNR, spectral efficiencies as high as 40bps/hz have

been demonstrated at similar error rates, though with less robust performance.



BLAST 14


ADVANTAGES

Since the entire sub streams are transmitted in the same frequency band, spectrum

is used efficiently. Spectrally efficiency of 30-40 bps/Hz is achieved at SNR of 24 db.

This is possible due to use of multiple antennas at the transmitter and receiver at SNR of

24 db. To achieve 40bps/Hz a conventional single antenna system would require a

constellation with 10^12 points. Furthermore a constellation with such density of points

would require in excess of 100db operating at any reasonable error rate. A critical feature

of BLAST is that the total radiated power is held constant irrespective of the number of

transmitting antennas. Hence there is no increase in the amount interference caused to

users. Figure 5 displays cumulative distributions of system capacity (in megabits per

second per sector) over all locations with transmit arrays only as well as with transmit

and receive arrays. These curves can also be interpreted as user peaks rates, that is user

data rates (in megabits per second) when the entire capacity of every sector is allocated to

an individual user. With transmit arrays only; the benefit appears significant only in the

lower tail of the distribution, corresponding to users in the most detrimental location. The

improvements in average and peak systems capacities are negligible. Moreover, the gains

saturate rapidly as additional transmit antennas are added. With frequency diversity taken

into account, those gains would be reduced even further. The combined use of transmit

and receive arrays, on the other hand , dramatically shifts the curves offering multifold

improvements in data rate at all levels. Notice that, without receive arrays, the peak data

rate that can be supported in 90 per-cent of the systems locations-with a single user per

sector ±is only on the order of 500kb/s with no transmit diversity and just over 1Mb/s

there-with.



BLAST 15


There is an extraordinary growth in attainable data unleashed by the additional

signaling dimensions provided by the combined use of transmit and receive arrays. With

only M=N=8 antennas, the single user data can be increased by an order of magnitude.

Furthermore, the growth does not saturate as long as additional uncorrelated antennas can

be incorporated into the arrays. Figure 5depicts single-user data rate supported in 90%

location Vs range with transmit and receive arrays. M is the terminal; transmit power

PT=10w; bandwidth B=5MHZ. BLAST technology has reportedly delivered a data

reception at 19.2Mbps on a3G network. With BLAST downloading a song would take

3s, not 30 via cable or DSL.20 novels can be downloaded in a second and HDTV can be

watched on a telephone. This innovation, known as BLAST, may allow so-called ³fixed´

wireless technology to rival the capabilities of today¶s wired networks would connect

homes and businesses to copper-wired public telephone service providers



BLAST 16


DISADVANTAGES

The BLAST technology is not is not well suited for mobile wireless applications,

such as hand-held and car-based cellular phones multiple antennas²both transmitting

and receiving²are needed. In addition, tracking signal changes in mobile applicationswould increase the computational complexity.

It would require manufacture to invest in the development of new multiantennadevices. It would also require new wireless network infrastructure.



BLAST 17


CONCLUSION

Under widely used theoretical assumption of independent Rayleigh scattering

theoretical capacity of the BLAST architecture grows roughly, linearly with the number

of antennas even when the total transmitted power is held constant. In the real world

ofcourse scattering will be less favorable than the independent Raleigh¶s assumption ant

it remains to be seen how much capacity is actually available in various propagation

environments. Nevertheless, even in relatively poor scattering environment, BLAST

should be able to provide significantly higher capacities than conventional architectures.



BLAST 18


REFERENCES

1. IEEE Communication Magazine. September 2001

2. www.bell-labs.com/projects/blast

3. www.lucent.com/information theory



BLAST 19




BLAST 20




BLAST 21


Abin Report

Documents

Transcript of Abin Report