Femi-Jemilohun O.J, Walker S.D
School of Computer and Electronic Engineering, University of Essex, Wivenhoe Park, CO4 3SQ, United Kingdom
{ojfemi, stuwal}essex.ac.uk
Keywords: Phase shift beamformer, Minimum Variance Distortion less Response
Abstract: The allocation of 60GHz spectrum for WLAN has made the quests for gigabit data rates delivery to the end
users possible in the wireless communication domain. The peculiar propagation characteristics in the
millimetre wave can be exploited for improved system capacity. In optimizing beamforming techniques, a
weight vector that minimizes a cost function is determined. The most commonly used optimally
beamforming techniques or performance measures (cost function) are Minimum Mean Square Error
(MMSE), Maximum Signal-to-Noise ratio (MSNR), and Minimum (noise) Variance (MV). A matlab based
MVDR (Minimum Variance Distortion Response) and Phase-Shift Beamforming algorithms are proposed in
this paper as means for cognitive spatial access in the millimetre wave band to enhance the signal of interest
(SOI), with the suppression of interferences. Simulation results reveal that MVDR outperforms the Phase-
Shifts in interference limited spatial multiple access (SMA) systems.
The formidable growth rate in the wireless
technology in the recent times has resulted in new
and improved application services at lower cost.
Invariably, the increased in demand for airtime by
numerous subscribers has led to shortage in the
limited frequency spectrum. The most readily
practical solution to this problem will be in spatial
processing. According to Andrew Viterbi, “Spatial
processing remains as the most promising, if not the
last frontier, in the evolution of multiple access
systems’’(Balanis 2005).The wider range and high
quality of service required for effective wireless
communication by the users that daily increase in
exponential rate, can only be realized through the
smart antenna technology, and spatial processing is
pivotal to this technology. The exponential increase
rate of subscribers coupled with limited frequency
allocation by FCC, compel wireless system capacity
availability a corresponding growth, this has been a
huge problem to cope with in communication
industry, hence cellular radio system has evolved
several techniques through the years. Smart antenna
technology among other techniques, with its quality
of high interference rejection, will lower the BER
thereby providing a substantial system capacity
The frequency spectrum in the Millimetre wave
band has been proven to be the only candidate
capable of gigabit throughput delivery required in
the multimedia applications. This has received great
attentions in research arena for developing ultra-high
speed gigabit wireless communication systems for
both short ranges such as WPAN as well as WLAN.
(Wu, Chiu et al. 2008; Lin, Peng et al. 2011).
Nevertheless, the capability of multi-gigabit data
rate at 60GHz is faced with a very challenging
power budget, this in collision with the propagation
conditions of the channel, especially the path
loss(Herrero and Schoebel 2010). The major
technical challenge of the limited link budget due to
high path loss, reflection loss are intended to be
optimized for spatial reuse for improved wireless
system capacity and quality of service. This was
achieved by engaging high gain and high directivity
antennas to compensate for the path loss in 60GHz
transmission. The short wavelength of 60GHz radio
signal necessitates the use of large number of tiny
antennas, makes it an ideal wireless interface to
support spatial reuse while on the other hand
beamforming has emerged as an important
Femi-Jemilohun O. and Walker S.
DOI: 10.5220/0004786101190125
In Proceedings of the Second International Conference on Telecommunications and Remote Sensing (ICTRS 2013), pages 119-125
ISBN: 978-989-8565-57-0
2013 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
technology to support high directivity in 60GHz
radio transmission to provide high data rates for
local users under severe penetration and path
loss(Yin, Chiu et al. 2011). The large number of
antenna available in 60GHz will be used to serve
multiple users while the received SNR to a single
user is increased. It is obvious that as spatial reuse
in dense environment will lead to CCI among the co-
located radio links.
In this work, Optimal Adaptive Beamforming
Algorithms (OABA) for cognitive spatial access was
used to mitigate the collocated radio links
interferences. This was implemented in the digital
domain with phased antenna array antenna. A
multiple effective antenna is employed to enhance
reception to users in the SDMA system, where
different users will have different permissible
operating regions in order to maintain the SINRs for
all users in the SDMA system.
1.1 Related Work
Quite a few number of works have been done on
millimetre wave band beamforming using phased
array antenna.(Lin, Peng et al. 2011) proposed a
MMSE based switched beamforming code selection
algorithm for mixed analog/digital beamforming
structure to enhance interference mitigation and
spatial reuse capability in the presence of CCI. The
disadvantage of Switched Beam(SB) is that the
fixed beam required the user to be in the centre of
the beam for the placement of the desired signal at
the maximum of the main lobe; otherwise, an
interferer can be enhanced instead. Also SB is
unable to fully reject the interferers. Hence we chose
to use adaptive array system to customise an
appropriate radiation pattern for individual user in
simulated wireless system in our work.(Liu 2007)
Used NLMS algorithm with the replacement of the
delay-lines (TDLs) in the traditional broadband
beamforming by sensor delay-lines to determine the
effectiveness of the adaptive broadband
beamforming with spatial only information.
Beamforming algorithm with the suppression of
interference was proposed by (alias Jeyanthi and
Kabilan 2009) using matrix Inversion-Normalised
Least Mean Square adaptive beamforming with
minimum Bit Error Rate (BER). NLMS is
characterised by computational complexity and low
convergence, It also requires a reference signal.
In this paper, An empirical analysis of a typical
wireless network deployed in millimetre wave band
was conducted to determine the QoS and reliability
of the channels in a spatial multiple access (SMA)
system. We adopted Phase Shift and MVDR
adaptive beamforming techniques algorithms in a
digital domain transmission. A matlab based
simulation was implemented for digital
beamforming structure to achieve an optimal
adaptive beamforming (OAB) for an enhanced
signal of interest (SOI) and suppression of non-
signal of interest (NSOI) to improve system capacity
in a dense spatial reuse environment. Moreover, a
comparison of the two beamforming algorithms was
done for better and effective performance. Our
simulation results showed that the proposed
algorithms are able to provide interference
mitigation while the beamforming capability in the
millimetre wave is optimized in the dense spatial
reuse scenario with multiple service users for
effective utilization of frequency spectrum. The rest
of this paper is organised as follows: section two
discussed the Array Signal Processing and adaptive
beamforming, while section three discussed the
challenges in the millimetre wave frequency band,
with empirical analysis in a real world scenario.
Section four proposed and implemented the
beamforming algorithms targeting at the
optimization of cognitive spatial access system for
improved system capacity. The results of the
simulations and discussions were presented in
section five. The conclusion was presented in
section six.
This is one of the major areas of signal processing
with wide applications in radar, sonar,
communications e.t.c. The technology involves
multiple sensors at different locations in space to
process received signals arriving at different
directions. (Matsuo, Ito et al. 2011). The three major
areas of ASP are: Detecting the presence of an
imping signal and determine the signal number,
finding the direction of arrival angles of the
impinging signals, and enhancing the signal of
interest from known/unknown directions and
suppress the interfering signals(Liu and Weiss
2010).This work is based on the third category: we
developed an algorithm using the ASP technique to
mitigate co-location interference in wireless access
network for the improvement of the communication
network system.
2.1 Adaptive Beamforming
This is a technique geared towards forming a
multiple beams towards desired users while nulling
Second International Conference on Telecommunications and Remote Sensing
the interferers at the same time through the
adjustment of the beamformer’s weight vectors. It is
the process of altering the complex weight on-the-fly
to maximize the quality of the communication
channel. Smart Antenna which is pivotal in adaptive
beamforming is a system of antenna with smart
signal processing algorithms. These algorithms are
used to identify the spatial signature like direction of
arrival (DOA) of the signal as well as to determine
the beamforming vectors, which is used to track and
locate the antenna beam on the mobile terminal
(Park 2011). The figure 1 below depicts the process
involved in adaptive beamforming
Figure 1: .Block diagram of Adaptive beamforming
Figure 2: 60GHz Transmission Measurement set up
Figure 3: 60GHz Transmission at MSc Lab Beam
The peculiar characteristics of the millimetre wave
such as limited emitted power, high temperature
noise, and high oxygen absorption has confined its
propagation to within the rooms or open areas in the
Figure 4: 60GHz Transmission at MSc Lab Locked Beam
close proximity of the antennas. There is
unacceptable strong interference occurrence in these
scenarios as a result of reuse of resources which
attracts broadband mobile telecommunication. It was
shown by (Flament 1999; Flament 1999) that the
Signal-to- Interference ratio can drop from 15dB to
0dB within a few centimetres. .Likewise, a human
influence on the path of transmission can attenuate
the signal by 15dB or more, hence complete
breakage of link.(Yang and Park 2009). The
importance of antenna design in an indoor
environment at 60GHz cannot be overlooked, since
each room/small coverage area is a single cell with
its own antenna, full coverage as well as lack of
signal spill across rooms must be guaranteed. In case
of coverage areas overlap results in co-channel
interference(Voigt, Hubner et al. 1999; Xia, Qin et
al. 2007). Adaptive Beamforming is method where
antenna array are used to improve system capacity
through interference reduction and also mitigates
multipath fading. This was demonstrated in this
work through matlab simulations and the results are
depicted in the graphs.
3.1 Empirical Measurements Setup of
Millimetre Wave Access Networks
The setup for source and sink transceivers for the
radiation pattern measurements of 60GHz is shown
in figure 2. The SiBeam P5 HDMI reference kits
contain two host MCUs. One host is on the
SK9200DB debug board and the other host is on the
Distance (m)
0 10203040
SignalSt rength(dBm)
Optimization of Beamforming Technology for Cognitive Spatial Access in Millimetre Wave
module board. The SBAM2 (SiBeam Applications
Manager) software is installed on a PC with XP
operating system to monitor status, set configuration
and control other parameters of the WiHD
transceiver modules. The SK9200DB Boards
(Source and Sink) are connected to the PC through
the USB cable, The source is connected to the DVD
player via an HDMI cable, both source and sink are
connected to monitors separately for monitoring
signal transmitted and received.
3.2 Data Acquisition and Processing
The transmission measurement was carried out at the
MSc laboratory of the University of Essex,
Colchester campus. The total distance 30m was
covered at a step distance of 10m.The recorded
received signals at different locations were
processed through the excel software to generate the
graphs 3 and 4 above
The Normalized Least Mean Square (NLMS) and
Recursive Least Square (RLS) are the classes of
adaptive algorithms and cost functions used for
wideband beamforming when a reference signal is
available and are characterised with computational
complexity. Linearly constrained Minimum
Variance Beamforming and Minimum Variance
Distortion less Response (LCMV and MVDR)
beamforming can be better options when a reference
signal is not available but the DOA angle of the
signal of interest and the range of their bandwidth is
known. Some constraints can be imposed on the
array coefficients to adaptively minimize the
variance or power of the beamformer output such
that the SOI impinging on the array from specific
directions are preserved by a specified gain and
phase response while all other contributions from
NSOI from other directions are suppressed.(Liu and
Weiss 2010).Taken a transmitted signal with a
frequency of
and DOA angle of , then the
beamformer’s response can be expressed as follows:
is the steering vector for wideband
Beamformer with corresponding elements of
complex exponentials expressed as :
For any signal with frequency
and DOA angle
Pass through the beamformer, with a specified
response, a
Constraint is set as follows:
The power output is given by:
The LCMV beamforming problem follows equation
These constrains determines the response of the
beamformer to signal coming from specified
direction and at specified frequencies. The resultant
beamformer is called the minimum variance
distortion less response (MVDR) beamforme
Table 1: Simulations Parameters.
SOI angle 35
Interfering signals angles 45 and 55
SNR 1 4dB
SNR 2 40dB
Element number 10
Carrier Frequency 60GHz
Element spacing lambda/2
Second International Conference on Telecommunications and Remote Sensing
In this part we provided simulation results of the
proposed algorithms. There are 10 sensors aiming at
enhancing SOI at 35dgrees and adaptively suppress
two wideband interfering signals arriving at 45 and
55 degrees respectively. SNR is 4dB and 40dB.A set
of 500 channel iterations was generated using
60GHz NLOS multipath channel model.
Figure five is the magnitude plots of two
antennas out of the array of ten to depict the
transmission of the SOI and some thermal noise
modelled as complex Gaussian distributed random
numbers. Figure six depicts the output of a phase
shift beamformer used to suppress signals from all
directions other than the desired signal direction.
The SOI becomes stronger than the noise as a result
of the 10-array multiplicative power to give a gain of
10. The output response of this beamformer is
shown in figure seven, where the mainlobe of the
beamformer is pointing to the SOI direction
(35degrees) as desired. A challenging scenario for
the phase shift beamformer is depicted in figure
eight. Interference signal from neighbouring
transmitter masked antenna array and the SOI fell to
the side lobe, therefore an adaptive MVDR
Beamformer was used for the suppression of the
interference at 45 and 55 degrees. This is depicted in
figure nine; the output response of these beamformer
for comparison is depicted in figure ten. The two
nulls in the graph shows the suppression of
interfering signals. It also shows the outperformance
of the MVDR Beamformer over the phase shift
beamformer for optimization of beamforming
technology in spatial access system.
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5
Pulse at Antenna 1
Time (s)
Magnitude (V)
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5
Pulse at Antenna 2
Time (s)
Magnitude (V)
Figure 5: Magnitude plots of the first two channels.
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5
Output of Phase Shift Beamformer
Time (s)
Magnitude (V)
Figure 6: Output of the phase shift beamformer.
-80 -60 -40 -20 0 20 40 60 80
Azimuth Angle (degrees)
Power (dB)
Azimuth Cut (elevation angle = 0.0
Figure 7: Beam pattern response of the beamformer.
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5
Output of Phase Shift Beamformer With Interference
Time (s)
Magnitude (V)
Figure 8: Response of the Phase shift beamformer with
Optimization of Beamforming Technology for Cognitive Spatial Access in Millimetre Wave
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5
Output of MVDR Beamformer With Presence of Interference
Time (s)
Magnitude (V)
Figure 9: Response of the MVDR beamformer in the
presence of interference.
-80 -60 -40 -20 0 20 40 60 80
Azimuth Angle (degrees)
Power (dB)
Azimuth Cut (elevation angle = 0.0
Figure 10: Beam pattern response of the beamformers.
5.1 Discussion
Fig 6 shows the desired signal is stronger than the
noise. The SNR here is 10 better than for the single
antenna shown in fig 5. Fig 7 shows the beam
pattern response of the beamformer with the applied
weights. The main beam of the beamformer is
pointing to the set desired direction for the received
signal (35). While fig8 shows the response of the
beamformer when interference was introduced. The
SNR is increased to 40dB to reflect the presence of
interference. The interring signals are set to arrive at
angles 45 and 55 degrees. It is obvious that phase
shift beamformer cannot handle the challenge of
interference; hence another beamformer called
MVDR was used to retrieve the desired signal in this
condition as depicted in fig 9. Fig. 10 shows the
beam pattern response of the beamformers. While
the phase shift fails to null the interferences; the
MVDR does totally suppress the interferences and
enhances the signal of interest.
Considering the effects of oxygen absorption and
related technical challenges in 60GHz, it is obvious
that the availability of large chunk of spectrum in it
may not satiate the quest for high throughput as well
as quality of service with high reliability required in
the wireless network and multimedia applications.
The confinement of transmission to a small area
requires many access points to reasonably provide a
wider coverage for users in the SMA systems, and
consequently, a co-located interference is inevitable.
An MVDR and Phase Shift beamforming algorithms
are proposed to achieve improved system capacity
and quality of service through interference
suppression and enhanced SOI in a spatially dense
transmission scenario. The simulation results
demonstrated effective gigabits throughputs in the
MMW band.
alias Jeyanthi, K. M. and A. Kabilan 200). "A Simple
Adaptive Beamforming Algorithm with
interference suppression." International Journal
of Engineering and Technology
1(1): 1793-8236.
Balanis, C. A. 2005. Antenna Theory. Analysis and
Design. New Jersey, John Wiley & Sons, INC,
Flament, M. (999. Propagation and Interference
Issues in a 60 GHz Mobile Network. Proc. of the
2nd Personal Computing and Communications
Workshop, Citeseer.
Herrero, P. and J. Schoebel 2010. Planar antennas
and beamforming devices for a multi gigabit 60
GHz demonstrator with Quality of Service.
Antennas and Propagation (EuCAP), 2010
Proceedings of the Fourth European Conference
on, IEEE.
Lin, Z., X. Peng, et al. 2011. Enhanced beamforming
for 60GHz OFDM system with co-channel
interference mitigation. Ultra-Wideband
(ICUWB), 2011 IEEE International Conference
on, IEEE.
Liu, W. 2007. Adaptive broadband beamforming
with spatial-only information. Digital Signal
Processing, 2007 15th International Conference
on, IEEE.
Liu, W. and S. Weiss 2010. Wideband beamforming:
concepts and techniques, Wiley.
Matsuo, M., R. Ito, et al. 2011. Wireless
transmission of JPEG 2000 compressed video,
Second International Conference on Telecommunications and Remote Sensing
Park, M. 2011. IEEE 802.11 ac: Dynamic
Bandwidth Channel Access, IEEE.
Voigt, J., J. Hubner, et al. 1999. Design pattern for a
single frequency TDMA-system in a typical office
environment at 60 GHz, IEEE.
Wu, S. H., L. K. Chiu, et al. 2008. Planar arrays
hybrid beamforming for SDMA in millimeter
wave applications. Personal, Indoor and Mobile
Radio Communications, 2008. PIMRC 2008.
IEEE 19th International Symposium on, IEEE.
Xia, P., X. Qin, et al. 2007. Short range gigabit
wireless communications systems: potentials,
challenges and techniques, IEEE.
Yang, L. L. and M. Park 2009. "Multi-band Gigabit
Mesh Networks: Opportunities and Challenges."
International Journal On Advances in Networks
and Services 2(1): 88-99.
Yin, Y. S., L. K. Chiu, et al. 2011. A space-time
precoded hybrid beamforming architecture for
broadband transmissions in 60GHz radio.
Personal Indoor and Mobile Radio
Communications (PIMRC), 2011 IEEE 22nd
International Symposium on, IEEE.
Optimization of Beamforming Technology for Cognitive Spatial Access in Millimetre Wave