Mobile Communication Academic Assignment For B.Tech Electronics and Communication Engineering 7th Semester Index: 1. Introduction 2. Techniques 3. Schemes 4. History 5. Digital an Analog Beamforming 6. Difference between Digital and Analog Beamforming 7. Analog Beamforming Working 8. Digital Beamforming Working with receiver and transmitter 9. Digital Beamforming Challenges with receiver and transmitter 10. Solutions to the Challenges 11. For Speech Audio Source: Wikipedia, Research Papers etc

1. BEAM FORMING
A
Project Report
Submitted
By
Krati Shukla, Nandini Maheshwari, Parnika Gupta
For The Assignment Of
B.Tech[EC] 7th Semester
Submitted To:-
Ms. Vartika Kulshrestha
Submitted By:-
Krati Shukla [BTBTE16090]
Nandini Maheshwari[BTBTE16031]
Parnika Gupta [BTBTE16017]
Department of Electronics
Banasthali Vidyapith, Rajasthan 304022

2. Beam forming
Beam foming or spatial filtering is a signal processing technique used in sensor arrays for
directional signal transmission or reception. This is achieved by combining elements in an
antenna array in such a way that signals at particular angles experience constructive
interference while others experience destructive interference. Beam foming can be used at
both the transmitting and receiving ends in order to achieve spatial selectivity. The
improvement compared with omni-directional reception/transmission is known as the
directivity of the array.
In simple words, Beamforming can be explained as a radio wave technology that is written
into the next generation IEEE Wi-Fi 802.11ac standard. This technology allows the
beamformer (Router) to transmit radio signal in the direction of the beamformee (Client),
thus creating a stronger, faster and more reliable wireless communication.
Beam foming can be used for radio or sound waves. It has found numerous applications in
radar, sonar, seismology, wireless communications, radio astronomy, acoustics and
biomedicine. Adaptive beam foming is used to detect and estimate the signal of interest at the
output of a sensor array by means of optimal (e.g. least-squares) spatial filtering and
interference rejection.
Beam foming is used for directional signal transmission and reception with the versatility to
change both amplitude and phase to help regulate power needs and steer the beam in the
intended direction. Bandwidth from 6 to 100 GHz, or millimeter Wave (mmWave), is likely
an integral part of future mobile broadband as 5G communication systems are introduced in
the global market. Concepts like beam foming and analog vs. digital become part of the
discussion when the topic turns to “What’s next?” In high frequency mmWave transmission,
large path loss during signal propagation limits the transmission range; to overcome this
obstacle, directional antennas with beam foming abilities are used in transmission and

3. reception. Beam foming directs the antenna beams at the transmitter and receiver so that the
transmission rate is maximized with minimal loss.
Purpose of Beam forming Technology is-
Beam forming is a type of RF (radio frequency) management in which an
access point uses multiple antennas to send out the same signal.
Techniques
To change the directionality of the array when transmitting, a beamformer controls the phase
and relative amplitude of the signal at each transmitter, in order to create a pattern of
constructive and destructive interference in the wavefront. When receiving, information from
different sensors is combined in a way where the expected pattern of radiation is
preferentially observed.
For example, in sonar, to send a sharp pulse of underwater sound towards a ship in the
distance, simply simultaneously transmitting that sharp pulse from every sonar projector in an
array fails because the ship will first hear the pulse from the speaker that happens to be
nearest the ship, then later pulses from speakers that happen to be further from the ship. The
beam foming technique involves sending the pulse from each projector at slightly different
times (the projector closest to the ship last), so that every pulse hits the ship at exactly the
same time, producing the effect of a single strong pulse from a single powerful projector. The
same technique can be carried out in air using loudspeakers, or in radar/radio using antennas.
In passive sonar, and in reception in active sonar, the beam foming technique involves
combining delayed signals from each hydrophone at slightly different times (the hydrophone
closest to the target will be combined after the longest delay), so that every signal reaches the
output at exactly the same time, making one loud signal, as if the signal came from a single,
very sensitive hydrophone. Receive beam foming can also be used with microphones or radar
antennas.
With narrow-band systems the time delay is equivalent to a "phase shift", so in this case the
array of antennas, each one shifted a slightly different amount, is called a phased array. A
narrow band system, typical of radars, is one where the bandwidth is only a small fraction of
the centre frequency. With wide band systems this approximation no longer holds, which is
typical in sonars.
In the receive beamformer the signal from each antenna may be amplified by a different
"weight." Different weighting patterns can be used to achieve the desired sensitivity patterns.
A main lobe is produced together with nulls and sidelobes. As well as controlling the main
lobe width (beamwidth) and the sidelobe levels, the position of a null can be controlled. This
is useful to ignore noise or jammers in one particular direction, while listening for events in
other directions. A similar result can be obtained on transmission.

4. For the full mathematics on directing beams using amplitude and phase shifts, see the
mathematical section in phased array.
Beam foming techniques can be broadly divided into two categories:
 conventional (fixed or switched beam) beamformers
 adaptive beamformers or phased array
o Desired signal maximization mode
o Interference signal minimization or cancellation mode
Conventional beamformers, such as the Butler matrix, use a fixed set of weightings and time-
delays (or phasings) to combine the signals from the sensors in the array, primarily using only
information about the location of the sensors in space and the wave directions of interest.
Adaptive beam foming techniques (e.g., MUSIC, SAMV) generally combine this information
with properties of the signals actually received by the array, typically to improve rejection of
unwanted signals from other directions. This process may be carried out in either the time or
the frequency domain. It is able to automatically adapt its response to different situations.
Some criterion has to be set up to allow the adaptation to proceed such as minimizing the
total noise output. Because of the variation of noise with frequency, in wide band systems it
may be desirable to carry out the process in the frequency domain.
Sonar phased array has a data rate low enough that it can be processed in real-time in
software, which is flexible enough to transmit or receive in several directions at once.
In contrast, radar phased array has a data rate so high that it usually requires dedicated
hardware processing, which is hard-wired to transmit or receive in only one direction at a
time.
However, newer field programmable gate arrays are fast enough to handle radar data in real-
time, and can be quickly re-programmed like software, blurring the hardware/software
distinction.
Schemes
 A conventional beamformer
It can be a simple beamformer also known as delay-and-sum beamformer. All the
weights of the antenna elements can have equal magnitudes. The beamformer is
steered to a specified direction only by selecting appropriate phases for each antenna.
If the noise is uncorrelated and there are no directional interferences, the signal-to-
noise ratio of a beamformer with antennas receiving a signal of power .
 Null-steering beamformer/ Zero-forcing precoding

5. Zero-forcing (or null-steering) precoding is a method of spatial signal processing by
which the multiple antenna transmitter can null multiuser interference signals in
wireless communications. Regularized zero-forcing precoding is enhanced processing
to consider the impact on a background noise and unknown user interference, where
the background noise and the unknown user interference can be emphasized in the
result of (known) interference signal nulling.
In particular, null-steering is a method of beam foming for narrowband signals where
we want to have a simple way of compensating delays of receiving signals from a
specific source at different elements of the antenna array. In general to make better
use of the antenna arrays, we sum and average the signals coming to different
elements, but this is only possible when delays are equal. Otherwise, we first need to
compensate the delays and then sum them up. To reach this goal, we may only add the
weighted version of the signals with appropriate weight values. We do this in such a
way that the frequency domain output of this weighted sum produces a zero result.
This method is called null steering. The generated weights are of course related to
each other and this relation is a function of delay and central working frequency of the
source.
History in wireless communication standards
Beam foming techniques used in cellular phone standards have advanced through the
generations to make use of more complex systems to achieve higher density cells, with higher
throughput.
 Passive mode: (almost) non-standardized solutions
o Wideband Code Division Multiple Access (WCDMA) supports direction of
arrival (DOA) based beam foming.
 Active mode: mandatory standardized solutions
o 2G — Transmit antenna selection as an elementary beam foming
o 3G — WCDMA: Transmit antenna array (TxAA) beam foming
o 3G evolution — LTE/UMB: Multiple-input multiple-output (MIMO)
precoding based beam foming with partial Space-Division Multiple Access
(SDMA)
o Beyond 3G (4G, 5G, …) — More advanced beam foming solutions to support
Space-division multiple access (SDMA) such as closed loop beam foming and
multi-dimensional beam foming are expected
An increasing number of consumer 802.11ac Wi-Fi devices with MIMO capability can
support beam foming to boost data communication rates.

6. Digital and Analog Beam foming
Analog vs. Digital
When working with electronics, both analog and digital signals have to be understood and
integrated in meaningful ways in order for our electronic systems have perform as intended.
While analog signals may be limited to a range of maximum and minimum values, there are
an infinite number of possible values within that range. The waves of a time-versus-voltage
graph of an analog signal are smooth and continuous. Conversely, digital signals have a finite
set of possible values and are one of two values such as either 0V or 5V, for example, and
timing graphs of these signals look like square waves. To identify whether a signal is analog
or digital, compare how the signal appears; a time-versus-voltage graph of an analog signal
should be smooth and continuous while digital waves are stepping, square, and discrete. Most
basic electronic components like resistors, capacitors, inductors, diodes, transistors, and
amplifiers are analog. Digital circuits use digital, discrete signals using a combination of
transistors, logic gates, and microcontrollers. An analog to digital converter (ADC) allows a
microcontroller to connect to an analog sensor to read in an analog voltage. A digital to
analog converter (DAC) allows a microcontroller to produce analog voltages. A digital down
converter (DDC) preserves information in the original signal and is often used to convert
analog radio frequency or intermediate frequency down to a complex baseband signal.
 Analog Beamforming
In analog beam foming, a single signal is fed to each antenna element in the array by
passing through analog phase-shifters where the signal is amplified and directed to the
desired receiver. The amplitude/phase variation is applied to the analog signal at
transmit end where the signals from different antennas are added before the ADC
conversion. At present, analogue beam foming is the most cost-effective way to build
a beam foming array but it can manage and generate only one signal beam.

7. Analog Beamforming Transmitter
The baseband signal to be transmitted is modulated first. This radio signal is split
using power divider and passed through the beamformer which has provision to
change amplitude (ak) and phase (θk) of the signals in each of the paths going towards
stack of antennas. Power divider depends on number of antennas used in antenna
array for example 4 ways power divider is needed to address the need of 4 antenna
array.

8. As shown in the receiver block diagram, complex weight is applied to the signal from
each antenna in the array. Complex weight consists of both amplitude and phase.
After these are done, signals are combined into one output.
 Digital Beamforming
In digital beam foming, the conversion of the RF signal at each antenna element into
two streams of binary baseband signals cos and sin, are used to recover both the
amplitudes and phases of the signals received at each element of the array. The goal
of this technology is the accurate translation of the analog signal into the digital
realm. Matching receivers is a complex calibration process with each antenna having
its own transceiver and data converters that generate multiple beams simultaneously
from one array. The amplitude/phase variation is applied to digital signal before DAC
conversion at transmit end. The received signals from antennas pass from ADC
converters and DDC converters.

9. Digital beam foming consists of RF translators, A/D converters, DDCs, complex
weight multiplication and summation operation.
• RF Translator converts higher RF signal frequency to lower IF signal frequency.
This is done using RF mixer. LO signal is fed to the RF mixer in order to perform RF
to IF conversion. Appropriate filters (bandpass and lowpass) are used at the input and
output of the RF mixer.
• This IF signal is converted to digital equivalent using A/D converter using
appropriate sampling clock.
• The digitized IF signal is passed to the DDC (Digital Down Converter).
• Complex weights are being applied to these baseband signals (s(t)).
• The results from these antenna elements are summed up to produce baseband signal
with desired directional pattern.
• The signal after summation is given to demodulator to retrive the information from
radio signal.

10. Digital Beamfoming Challenges
 Amount of data generated – The data rate out of the ADC effects the digital interface
and processing power requirements and the question becomes how to handle the data
when electronic systems want increased resolution and higher sampling rate for
increased bandwidth.
 Power consumption – Processors require lots and lots of power. Because of the
limitation in data bandwidth, there is a practical limit on the number of elements in
the array which requires waveform generators at each element.
 Loss – The losses high frequency mmWave transmission incur include high free space
path loss, absorption from atmospheric gases and rainfall, and non-line of sight
propagation
 Expense – The overall expensive of implementing digital beam foming systems
includes but is not limited to the physical size of the electronics and the high cost of a
large number of ADCs operating at high sampling frequencies.
Solutions to the Challenges
Possible solutions for some of these challenges in 5G mobile communications are
forthcoming in the research and tend to dominate discussions on the future of beam foming. It
appears that, at present, digital beam foming is the future in communication systems but not
without its challenges. To mitigate these challenges, it appears evident that the first 5G
mobile systems will integrate a combination of analogue and digital beam foming systems.
For receive (but not transmit), there is a distinction between analog and digital beam foming.
For example, if there are 100 sensor elements, the "digital beam foming" approach entails
that each of the 100 signals passes through an analog-to-digital converter to create 100 digital
data streams. Then these data streams are added up digitally, with appropriate scale-factors or
phase-shifts, to get the composite signals. By contrast, the "analog beam foming" approach
entails taking the 100 analog signals, scaling or phase-shifting them using analog methods,
summing them, and then usually digitizing the single output data stream.
Digital beam foming has the advantage that the digital data streams (100 in this example) can
be manipulated and combined in many possible ways in parallel, to get many different output
signals in parallel. The signals from every direction can be measured simultaneously, and the
signals can be integrated for a longer time when studying far-off objects and simultaneously
integrated for a shorter time to study fast-moving close objects, and so on. This cannot be
done as effectively for analog beam foming, not only because each parallel signal
combination requires its own circuitry, but more fundamentally because digital data can be
copied perfectly but analog data cannot. (There is only so much analog power available, and
amplification adds noise.) Therefore, if the received analog signal is split up and sent into a
large number of different signal combination circuits, it can reduce the signal-to-noise ratio of
each.

11. For speech audio
Beam foming can be used to try to extract sound sources in a room, such as multiple speakers
in the cocktail party problem. This requires the locations of the speakers to be known in
advance, for example by using the time of arrival from the sources to mics in the array, and
inferring the locations from the distances.
Compared to carrier-wave telecommunications, natural audio contains a variety of
frequencies. It is advantageous to separate frequency bands prior to beam foming because
different frequencies have different optimal beamform filters (and hence can be treated as
separate problems, in parallel, and then recombined afterward). Properly isolating these bands
involves specialized non-standard filter banks. In contrast, for example, the standard fast
Fourier transform (FFT) band-filters implicitly assume that the only frequencies present in
the signal are exact harmonics; frequencies which lie between these harmonics will typically
activate all of the FFT channels (which is not what is wanted in a beamform analysis).
Instead, filters can be designed in which only local frequencies are detected by each channel
(while retaining the recombination property to be able to reconstruct the original signal), and
these are typically non-orthogonal unlike the FFT basis.