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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.
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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.
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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.
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.
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=
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 distructively, 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 actually exploited 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
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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 of f
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 Rauleigh
scattering environment, this processing structure leads to theoretical rates that
grow linearly with the number of antennas these rates approaching 90% of
Shanon capacity. Rayleigh scattering of light off the molecules of air, and
can be extended to scattering from particles up to about a tenth of the
wavelength of light. Raylegh scattering can be considered to be elastic
scattering because the energies of scattered photons do not change.
An overview of radiated power
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Scattering at right angles is
half the forward intensity
for Rayleigh scattering
Rayleigh scattering
from air molecules
N= No. of Scatters
= Polarizability
R=Distance from scatter
Observer The strong wavelength depend upon
Rayleigh scattering enhances the short
Fig. 1
wave engines giving as the blue sky.
The researchers found 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
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
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fixed wireless loop systems, which are used to provide phone service in rural
and remote areas.
“This 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. “This
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 Shanon’s theory dealt with point-to-point
communications, the theory used in BLAST relies on “volume-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 “when and where noise and interference turn
out to be severe, each bit (of data) is well prepared to weather such
impaiments.”
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
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OVERVIEW OF BLAST SYSTEM
TX
RX
RX
V-BLAST
TX
RX signal
VECTOR processing
ENCODER RX
TX
RX
TX
RX
Fig.2
V-BLAST takes single data stream and demultiplexes it in to msubstreams.
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. Each transmitter 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 organised 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.
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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
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sequentially understood as the desired signal. This implies that the other sub
stream 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 components of
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 ‘a’ are assumed to be the 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 “best-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.
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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 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 26bps/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 4billion. 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
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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 “diversity” 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 1хRTT
rollout has shown. Asked about its plans for BLAST, Verizon’s reps
indicated that the discussion was premature, but that they 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 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 speed-
spectrum 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
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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
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.
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
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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.
0.9
Probability (System Capacity C)
0.8
0.7 Transmit
diversity using
a single
0.6 antenna
BLAST
0.5 M antennas per
section
0.4 4
Antennas
terminal
0.3 ¼
1/40
0.2
0.1
0
10 100 1000
M bits /section
Fig 4
There is an extraordinary growth in attainable data unleashed by the
additional signaling dimensions provided by the combined use of transmit
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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.
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BLAST technology has reportedly delivered a data reception at 19.2Mbps on
a 3G 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 “fixed” wireless
technology to rival the capabilities of today’s wired networks would connect
homes and businesses to copper-wired public telephone service providers.
DRAWBACKS
The BLAST technology is not is not well suited for mobile wireless
applications, such as hand-held and car-based cellular phones multiple
antennas—both transmitting and receiving—are needed. In addition, tracking
signal changes in mobile applications would increase the computational
complexity.
It would require manufacture to invest in the development of new multi-
antenna devices. It would also require new wireless network infrastructure.
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
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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 attempt was to “tune” the
system to the environment, or to modify the environment in anyway.
The antenna arrays consisted of λ/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 λ/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 were each 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 “block” 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.
4bits/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
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efficiency is 80% of the above, or 20.7bps/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 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.
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Single-position performance
BLER
SNR (dB)
Multiple-Position Performance
BLER and BER in 24 dB SNR vs position
BLER /BER 2.1 dB SNR
* BLER
BER
Position Number
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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.
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REFERENCES
1. IEEE Communication Magazine. September 2001
2. www.bell-labs.com/projects/blast
3. www.lucent.com/information theory
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ABSTRACT
BLAST is a wireless communications technique which uses multi-element
antennas at both transmitter and receiver to permit transmission rates far in
excess of those possible using conventional approaches.
In wireless systems, radio waves do not propagate simply from transmit
antenna to receive antenna, but bounce and scatter randomly off objects in
the environment. This scattering known as multipath, as it results in multiple
copies (“images”) of the transmitted sign arriving at the receiver via different
scattered paths. In conventional wireless system multipath represents a
significant impediment to accurate transmission, because the image arrive at
the receiver at slightly different times and can thus interfere destructively,
canceling each other out. For this reason, multipath is traditionally viewed as
a serious impairment. Using the BLAST approach however, it is possible to
exploit multipath, that is, to use the scattering characteristics of the
propagation environment to enhance, rather than degrade transmission
accuracy by treating the multiplicity of scattering paths as separate parallel
sub channels.
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ACKNOWLEDGEMENT
I extend my sincere thanks to Prof. P.V.Abdul Hameed, Head of the
Department for providing me with the guidance and facilities for the
Seminar.
I express my sincere gratitude to Seminar coordinator Mr. Berly C.J, Staff
in charge, for their cooperation and guidance for preparing and presenting
this seminar.
I also extend my sincere thanks to all other faculty members of Electronics
and Communication Department and my friends for their support and
encouragement.
BILAL ABDU
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CONTENTS
INTRODUCTION 01
FUNDAMENTAL LIMITATIONS IN WIRELESS 02
DATA ACESS
SPACE: THE LAST FRONTIER 03
LIFTING THE LIMITS WITH TRANMIT AND 03
RECEIVE ARRAYS
OVERVIEW OF BLAST SYSTEM 08
BLAST’S SIGNAL DETECTION 09
BLAST IN THE REAL WORLD 11
BLAST vs. EXISTING SYSTEMS 12
ADVANTAGES 13
DRAWBACKS 15
LABORATARY RESULS 15
CONCLUSION 19
REFERENCES 20