smart antennas
DESCRIPTION
TRANSCRIPT
SMART ANTENNASMART ANTENNA
OUTLINE
Introduction
Antenna and its Parameters
Smart antenna and its evolution
Adaptation algorithms
Applications
Future Scope
Conclusion
INTRODUCTION
Performance and capacity are the two major impairments in Wireless Communication.
Can be achieved by overcoming Multipath and Interference.
Smart antenna is a promising technology that ensures higher capacity in wireless networks.
Employs SDMA (Space Division Multiple Access).
ANTENNA AND ITS PARAMETERSAntenna is a device that provides a means for radiating or
receiving radio waves.
o Transmitting Antenna
o Receiving Antenna
o Radiation pattern
o Isotropic antenna
Omni-directional pattern: f (θ, φ) = f (θ)
o Pattern lobes
o Side lobe level
o Beam width- HPBW and FNBW
o Radiation intensity
o Directivity
o Radiation efficiency
o Gain
o Beam efficiency
o Antenna Impedance
o Antenna Polarization
SMART ANTENNA & ITS EVOLUTION
Omni-directional antenna: radiates and receives well in all directions.
Antenna
Top View
Directional antenna: has certain fixed preferential transmission and reception directions.
Antenna Array
Top View
OmnidirectionalOmnidirectional
ElementElementDirectionalDirectional
elementelement
GainGain LOWLOW HIGHHIGH
Frequency Frequency reuse reuse
InterferenceInterference
RejectionRejection
NONE
TYPE
LIMITATION
Antenna diversity: uses two or more antennas to improve the quality and reliability of a wireless link. Multiple versions of the same signal may be transmitted and/or received and combined in the receiver.
o Spatial diversity o Polarization diversity
o Pattern diversity
GainGain
CapacityCapacity
InterferenceInterference
RejectionRejection
DIVERSITY COMBINING SYSTEM
VERY GOOD
HIGH
LOW
TYPE
LIMITATION
Smart Antenna
An intelligent antenna system which is an antenna array that integrates the simultaneous operation of diversity schemes along with a digital signal processing capability to transmit and receive data.
“Smart” >> digital signal processing facility
Smart antenna functions
o Direction of arrival estimation
o Beam steering
Benefits of Smart antenna
o Capacity enhancement
o Coverage extension
o Increase in transmission efficiency
o Reduction of Co-channel interference (CCI) and Multipath fading
o Reduction of Bit Error Rate (BER)
o Reduction in Handoff
Smart Antenna types
Switched beam array: consists of either a number of fixed beams with one beam turned on towards the desired signal or a single beam that is steered towards the desired signal.
Coverage pattern
Antenna Array
Active Beam
Block diagram of Switched beam system
Adaptive antenna array: consists of an array of multiple antenna elements with the received signals weighted and combined to maximize the SINR.
Coverage pattern
Antenna Array
Desired User
Interfering User
Block diagram of Adaptive array system
Comparison b/n Switched beam and Adaptive array systems
CRITERIA SWITCHED BEAM ADAPTIVE ARRAYS
INTEGERATION • Easy to implement• Low cost
• Transceiver complexity• High cost• Less hardware redundancy
RANGE/COVERAGE • More coverage compared to conventional systems• Less coverage compared to adaptive array
• More coverage compared to switched beam system
INTERFERENCE REJECTION
• Difficulty in distinguishing between desired signal and interferer • Does not react to the movement of interferers.
• Focusing is narrower• Capable of nulling interfering signals
ADAPTATION ALGORITHMS
Continuous Adaptation: Automatically adjust weights as the incoming data is sampled and updates it such that it converges to an optimal solution, uses a reference signal.
E.g. The Least Mean Square algorithm (LMS), The Recursive Least Square algorithm (RLS).
Blind Adaptive algorithm: Adjustment of weights without the benefit of reference signal information.
E.g. The Constant modulus algorithm (CMA).
o LMS algorithm generates better main lobes in desired user direction but do not nullify co channel interference.
o Interference rejection is better in CMA because nulls are produced towards interfering signals. Hence nullifies co channel interference but bears maximum errors.
o RLS algorithm has better response towards co channel interference, generates better main lobe in desired direction and has faster convergence rate than LMS, hence the best of all.
APPLICATIONS
MILITARY APPLICATION
o Makes the battlefield communication easier.
o Power consumption is reduced on high speed multimedia battle field networks due to reduction in battery drain.
o Spoofing is avoided.
o Light weight video displays with in-built smart antenna used in warfare to exchange real time maps and pictures.
SATELLITE COMMUNICATION
o SATCOM employs Space Division Multiple Access (SDMA).
o more perspective for satcom systems for low (1500km) and middle (till 10000km) orbits.
o Base stations are employed with smart antenna technology.
MOBILE COMMUNICATION
o Economical to use adaptive antenna in base station rather than at each mobile station.
o Capacity problem is overcome by using multiple adaptive antennas on mobile handsets.
o Improves call reliability.
o Suppress the interference signals.
o mitigation against dead zones
E.g. Quadrifilar helix antenna (QHA) produced by Surrey University and small solid state antenna as manufactured by Antenova
WIRELESS SENSOR NETWORKS
o Increased gain result from smart antenna which preserve connectivity in sensor network and better usage of nodes energy source.
o Increase in Network life cycle due to improvements in SNR and BER.
o Avoid sensor network resource depletion by usage of switched beam array antennas.
TERRESTRIAL TELEVISION RECEPTION
o Increase in BER would compromise with video or audio or sometimes result in no reception.
o By employing automatic mechanism can adjust antenna gain and direction without user intervention.
o Here smart antenna functions by changing relative gain and phase of internal elements.
o Offers high degree of optimization for both signal capture and interference rejection.
FUTURE SCOPEo MIMO systems employing smart antennas that fulfill IMT-advanced requirements is the core of 4G systems with 1Gbit/s data rate and freq 20-100MHz.
o MIMO systems fulfilling beyond IMT-advanced standard forms the 5G systems with more than 10 Gbit/s data rate and with a frequency of 200MHz.
o Use of multiple smart antennas in mobile handsets to achieve much better performance.
o Smart antenna based on UWB technology to detect malignant tumors.
CONCLUSION Smart antennas are the intelligent antenna systems that vastly improve the efficiency of wireless transmission.
For applications including MIMO, Software Defined Radio - SDR, and Cognitive Radio - CR requiring antenna systems to be more adaptive and provide greater levels of adaptivity Smart antenna technology is of wide use. Promising technology to resolve the traffic capacity bottlenecks in future high-speed broadband wireless access networks and reduce RF pollution.
Efficient utilization of the scarcest resource of today’s wireless communication, the RF spectrum.
REFERENCES
Jensen M and J. W. Wallance, “A review of antennas and propagation for MIMO wireless systems”, IEEE Transaction of Antennas and propagation, vol. 52, pp. 2810-2824, 2004.
R. H. Roy, “An overview of smart antenna technology and its application on wireless communication systems,” Proc. IEEE Conf. Personal Wireless Comm., 2007, pp. 234-238
Chryssomallis, M., 2008. Smart antennas, IEEE Antennas and Propagation Magazine, 42(3): 129- 136.
S.F. Shaukat, Mukhtar ul Hassan, R. Farooq, H.U. Saeed and Z.Saleem, "Sequential Studies of Beam forming Algorithms for Smart Antenna Systems", World Applied Sciences Journal, Vol. 6, no. 6, pp 754-758, 2009.
Luca Bencini, Giovanni Collodi, Divide Di Palma, Gianfranco Manes, Antonio Manes,” An Energy Efficient Cross Layer Solution based on Smart Antennas for Wireless Sensor Network Applications” ,IEEE, COMPUTER SOCIETY, SENSOR COM, Fourth International Conference on Sensor Technologies and Applications. 2010, pp 232- 237.
Sultan Budhwani, Mahasweta Sarkar and Santosh Nagaraj “A MAC Layer Protocol for Sensor Networks using Smart Antennas”, IEEE International Conference on Sensor
Networks, Ubiquitous, and Trustworthy Computing, 2010, pp 261-267.