RECENT ADVANCES in NETWORKING, VLSI and SIGNAL PROCESSING
|
|
- Vivian Bishop
- 6 years ago
- Views:
Transcription
1 SMART ANTENNA AOA ESTIMATION EMPLOYING MUSIC ALGORITHM And DIGITAL BEAMFORMING By VARIABLE STEP-SIZE LMS ALGORITHM With NOVEL MAC PROTOCOL For IEEE 82. T.S.JEYALI LASEETHA, R.SUKANESH 2,. &2. Department Of Electronics And Communication Engineering, Anna University, Chennai.Dr. Sivanthi Aditanar College Of Engineering, Tiruchendur 2.Thiagarajar College Of Engineering, Madurai &2 INDIA Abstract :- Smart antenna using multiple antennas exploring the SDMA technology has been used in wireless communication systems which provides higher spectrum efficiency, improved link quality and throughput through frequency reuse, reduction of intersymbol interference (ISI) and co-channel interference rejection (CCI)[]. Space Division Multiple Access, where multiple user signals are simultaneously transmitted and received over same conventional time and frequency channels by using multiple antennas, dramatically increases spectral efficiency. SDMA is realized with beam forming and null forming techniques which accounts for co-channel interference rejection. Channel equalization is done using adaptive equalizer to mitigate the effects of ISI. This paper discusses SDMA technology with digital beam forming with the novel idea of including the Variable step-size LMS algorithm along with MUSIC algorithm employed in MAC protocol for IEEE 82. and the results of simulation are analyzed for their performance. Key-words :- smart antenna, adaptive beamforming, intersymbol interference, variable step-size lms algorithm, adaptive equalizer, Angle of Arrival estimation(aoa), MAC protocol, MUSIC algorithm.introduction Adaptive antenna beam forming also known as Digital beam forming and Smart antenna technology has been widely used for system identification, sonar technology, image processing, wireless communications, radar and related fields[2],[3]. This technology provides wireless communication systems with improved spectral efficiency, throughput and reduced ISI and CCI. The base station can suppress the cochannel interference in the service cell. Therefore the mobile user need not bother about explicit interference rejection function. The air interface used in this paper is TDD(Time Division Duplex) /TDMA(Time Division Multiple Access), which the frame structure supports for an efficient DBF/SDMA processing. An variable step size Least Mean Square Algorithm used at the base station computes and applies reception array antenna weights upon receiving uplink channel signal from a desired user, to compensate for propagation spatial characteristics[9]-[]. Then the BS uses the reception array weights as the transmission array weights for downlink transmission. Therefore optimum beam forming is made towards the desired user while rejecting the interference from undesired mobile user. In this paper Digital beam forming technique is presented with 6 number of antenna elements at the base station as ISSN: ISBN:
2 uniform linear array. Section 2 deals with system specification with physical layer protocol. In section 3 the adaptive antenna array algorithm is discussed for array weight calculation and updating the weights using variable step size LMS algorithm. Section 4 deals with the MAC protocol with DBF/SDMA technology. The experimental simulation results are shown and discussed in section 5. The paper is concluded in section 6. 2.Digital Beamforming Using Adaptive Antenna Array System Table : System Parameters Specification required average output signal to noise ratio for a given BER with fading. The arrays can theoretically completely cancel N interferers with M antennas (M>N) and achieve an M-N fold diversity gain[]. Significant suppression of N>M interferers is also possible. However this is at the cost of requiring a receiver for each antenna and tracking the antenna weights at the fading rate (79Hz at 2Ghz and 6mph) versus switching every few seconds with the multibeam antenna. In this paper the array weights for these desired beam patterns are generated by variable step size LMS algorithm using MMSE criterion by receiving the uplink training sequence. For downlink System TDD-TDMA/SDMA Carrier frequency 2.4 GHz Symbol rate Mbps Downlink modulation BPSK Base station Number of antenna 6 elements Antenna topology Uniform Linear Array Antenna spacing λ/2 Adaptive antenna algorithm Variable step-size Least mean square Adaptive antenna processing criteria Minimum mean square error Mobile user Number of antenna element An Antenna array consists of M elements arranged in uniform linear array (ULA) fashion is employed in DBF/SDMA signal processing and is executed in baseband. The block diagram of DBF/SDMA signal processing at the Base station is shown in Fig. A base station mitigates the fading of received power of the desired signal by steering the beam in the desired mobile user s direction while there are N number of sources transmitting the signals at the base station. The base station communicates with them all but picks up or selects the desired signal while nullifying interfering signals from others. M antenna elements can provide an increased gain of M plus a diversity gain against the multipath fading which depends on the correlation of the fading the antennas. The antenna gain can be defined as the reduction in required received signal power for a given average output signal to noise ratio. The diversity gain is defined as the reduction in the Fig. Digital beamforming at the Base station transmission, the array weights which are determined by the uplink,are applied because of the reciprocity nature of TDD channel. The DBF/SDMA system reduces communication overhead and improve the user throughput in TDD operation. 3. Variable Step-Size LMS Algorithm For Array Weights Calculation Digital beam forming employing the reference signal structure and variable step-size LMS algorithm is adopted in this system to update the weights of the beam former and execute realtime tracking operation. The advantage of using an variable step-size LMS algorithm includes network compatibility, portability, mobility and ISSN: ISBN:
3 capability of single chip VLSI implementation. The VSLMS algorithm is one of the MMSE algorithms and is proposed for the channel estimator of a maximum likelihood sequence estimator (MLSE) equalizer[]. In the channel model of a L-length tapped delay line (TDL), let T denote the tap coefficient vector, which becomes the estimated channel impulse response, and let d(n) denote the channel output signal. If the training signal at time n is r(n), then x l (n) = r(n-l), x(n) = [ x (n) x 2 (n) x 3 (n)..x L (n)] () and e(n) = d(n) w(n-) H x(n) (2) The estimated value of w is obtained iteratively with the VLMS algorithm as[] w(n) = w(n-) + µ g (n)e * (n)x(n) (3) where T and H represent matrix transpose and Hermitian transpose respectively and (4) Where is a constant determined by forgetting factor of the RLS algorithm. The optimized array weights are determined using VSLMS algorithm while running Monto-Carlo Simulations for times. The weights are tabulated as shown below. Table.2. The weights for N = 6 ULA Array values weights W W i W i W i W i W i W i W i W i W i W i W i W i W i W i W i 4. Mac Protocol For Smart Antennas While using SDMA technology with directional antennas, a new MAC protocol is important[4]. Traditional MAC protocol with omni - directional antennas are not suitable for the support of new features like SDMA technology which supports IEEE 82.. The theoretical aspects of new MAC protocol suitable for smart antennas with SDMA technology is explored herewith for the proper understanding of how the interferers and desired users are being identified and separated. In the traditional method, Request to Send (RTS) and Clear to Send(CTS) packets are sent omni-directionally in order to enable the transmitter and receiver to locate each other and then sending DATA packet and ACK in direct mode. All these four frames contain information about the duration of the pending handshake, informing the neighbors to avoid starting a new transmission during this period. This is managed by a mechanism called Virtual Carrier Sense. Every station maintains a Network Allocation Vector(NAV). If NAV is zero the station can transmit otherwise if can not. NAV is initially zero. If NAV is a positive number there is a countdown until it reaches zero. When a station hears one of the four frames, it updates its NAV with the duration of the pending handshake preventing itself by transmitting until its NAV reaches zero again. With this scheme every station performs a Virtual Carrier Sense in addition to the physical carrier sense to enhance the resistance of the protocol against collisions. In this scheme, the transmitter starts transmitting its RTS in a predefined direction, assume with beam. Short afterwards it turns its transmission beam on the right sending the same RTS with beam2. It continues this procedure again and again until the transmission of RTS covers all the area around the transmitter (until it sends the RTS with beam M). The RTS contains the information about the duration of the intended four way handshake. As this information is spread around by the circular RTS, the neighbors are informed about the intended transmission. The neighbors after executing an algorithm decide if they will defer their transmission in the direction of transmitter or receiver, if this harms the ongoing transmission. The STA ie the mobile user, that is the destination of the RTS waits until the finish of the circular RTS transmission and then send a directional CTS towards the direction of the transmitter of the RTS. Then the ISSN: ISBN:
4 carrier sensing from the transmitter of the RTS in this phase is performed in an omni-directional mode. If the CTS is received during a predefined period (CTS time out) then the transmitter continues with the transmission of the data packet and the reception of ACK, in a particular direction. By using only the directional transmissions of RTS, CTS, Data and ACK we exploit the benefit of increasing the coverage area, compared with the omni-directional mode of transmission analyzed from Fig. 9 wheree only 4 weights are plotted instead of 6 weights to have a clear view. The weights get adapted within iterations but they reach the steady state after 5 iterations. The optimized adapted array weights are shown in Table.2. The SINR is determined as db. Fig:2 A node with M beams Fig 3. Spatial spectrum estimate of the arriving signal 4. Simulation And Results Analysis In this paper, an Uniform Linear Array of 6 elements is considered and the channel is estimated from the autocorrelation matrix of the incoming signal. The signals are assumed to be arriving from three different directions with the angles [4º 7º 9º]. Additive White Gaussian noise of variance (σ 2 ). is adopted with SNR of. The AOA is estimated using MUSIC and Minvariance method[] [3]. MUSIC algorithm performs better among the two. The spatial spectrum estimate is shown in Fig.3. The polar plot in Fig.4 shows the angle of arrival with the maximum signal strength for the signal coming from 4º. After estimating the angle of arrivals, the beamforming was done using Variable Step- of the Step- size LMS algorithm. The variation size (µ g ) is plotted in Fig.6. This speeds up the convergence of LMS algorithm. The signal from 4º is tracked within iterations and the same is shown in Fig.7. The same can be seen in the Fig.8 and Fig.9 also. In Fig.8 the mean square error is plotted to study the convergence performance. The adaptation of weights is Mean square error polar plot for AOA Estimation Fig 4. Polar plot for the AOA estimate Fig.5 Plot of Mean-Sqaure-error convergence for all the three arriving signals Received Signal and interferences Sample Interval 6 3 desired interferer interferer desired interferer interferer2 ISSN: ISBN:
5 variable stepsize.3.2. adaptation of weights w w2 w3 w4. value of mu weights iteration no. Fig.6 Variable step size(µ g ) Iteration no. Fig.9 Weights adaptation Desired signal Array output AF n Signals No. of Iterations Fig.7 tracking the desired signal AOA (deg) Fig. Radiation pattern for the 6 element ULA 5. Conclusion Mean square error Iteration no. Fig.8 Mean Square Error plot A 6-element smart antenna array has been developed for high data rate of Mbps for TDD- TDMA/SDMA system. A brief system design of the adaptive array using digital beamforming with AOA suitable for Novel MAC protocol is presented. Simulation results demonstrates the performance improvement in terms of BER and SINR using adaptive beamforming techniques multipath environment. Uplink Spatial Division Multiple Access (SDMA) is also demonstrated using the adaptive array system. Near-far effect can be avoided by pre-tuning the transmission power of each terminals according to desired BER performance. Better signal separation capability can be obtained using more degrees of freedom in the beamforming weight vectors, which in turn proportional to the number of antenna elements. This will enhance the system capacity and make the system highly suitable for wireless communication applications. In this environment, the variations of the channel are so ISSN: ISBN:
6 fast that by utilizing a variable step-size factor, the system becomes more adaptive and the channel estimation will provide a more accurate estimation of the data and the use of a variable step size allows each path to be independent of every other path. References : [] J.H.Winters, Smart antennas for wireless systems, IEEE Personal Communications, vol.5, pp.23-27, Feb [2] R.Kohno, Spatial and temporal communication theory using adaptive antenna array, IEEE Personal Communications, vol.5, no., pp.28-35, Feb [3] Y.Kikuma, Adaptive signal processing with array antenna, Kagakugijutsu-Shuppan, Tokyo, 998. [4] B.Widrow and S.D.Stearns, Adaptive signal processing, Prentice Hall, Upper Saddle River, USA, 985. [5] Y.Ogawa, M.Ohmiya, and K.Itoh, An LMS adaptive array for multipath fading reduction, IEEE Trans. Aerosp. Electron. Syst., vol.aes- 23, no., pp.7-23, Jan [6] Y.Ogawa, Y.Nagashima, and K.Itoh, An adaptive antenna system for high-speed digital mobile communications, IEICE Trans. Commun., vol.e75-b, no.5, pp.43-42, May 992. [7] T.Ohgane, Spectral efficiency evaluation of adaptive array base station for land mobile cellular systems, Proc. VTC 94, pp , May 994. [8] D.M.Brady, Adaptive coherent diversity receiver for data transmission through dispersive media, Conf. Rec., IEEE Int. Conf. Commun., San Francisco, June 97. [9] J.Takada, Optimum antenna spacing in MMSE combining, Proc. First International Symposium on Wireless Personal Multimedia Communications (WPMC 98), pp , Nov [] J.H.Winters, Optimum combining in digital mobile radio with cochannel interference, IEEE J. Sel. Areas Commun., vol.sac-2, pp , July 984.\ [] H.Suzuki, Signal transmission characteristics of diversity reception with leastsquare combining, IEICE Trans., vol.j75- B-II, no.8, pp , Aug [2] J.Salz and J.H.Winters, Effect of fading correlation on adaptive arrays in digital mobile radio, IEEE Trans. Veh. Technol., vol.43, no.4, pp.49-57, Nov [3] Y.Akaiwa, Introduction to Digital Mobile Communication, John Wiley & Sons, New York, 997. [4] S.Haykin, Adaptive filter theory, 3rd ed., Prentice Hall, Upper Saddle River, USA, 996. [5] R.W.Harris and D.M.Chabries, A variable step (VS) adaptive filter algorithm, IEEE Trans. Acoust., Speech & Signal Process., vol.assp- 34, pp.39-36, April 986. [6] A.Taguchi and N.Hamada, A variable step size method for the learning identification, IEICE Trans., vol.j7-a, no.8, pp , Aug [7] R.H.Kwong and E.W.Johnston, A variable step size LMS algorithm, IEEE Trans. Signal Process., vol.4, pp , July 992. [8] E.Eweda and O.Macci, Convergence of an adaptive linear estimation algorithm, IEEE Trans. Autom. Control, vol.ac-29, no.2, pp.9-27, Feb [9] S.Ahn and P.J.Voltz, Convergence of the delayed normalized LMS algorithm with decreasing step size, IEEE Trans. Signal Process., vol.44, pp.38-36, Dec [2] S.Kozono and T.Tsuruhara, Correlation between two mobile radio base-station antennas, IEICE Trans., vol.j66-b, no.4, pp , April 983. [2] S.Denno and Y.Saito, Fast channel impulse response estimation scheme for adaptive MLSE equalizer, IEICE Trans., vol.j78-b-ii, no.4, pp.22-23, April 995. [22] J.Nagumo and A.Noda, A learning method for system identification, IEEE Trans. Autom. Control, vol.ac-2, pp , 967 ISSN: ISBN:
K.NARSING RAO(08R31A0425) DEPT OF ELECTRONICS & COMMUNICATION ENGINEERING (NOVH).
Smart Antenna K.NARSING RAO(08R31A0425) DEPT OF ELECTRONICS & COMMUNICATION ENGINEERING (NOVH). ABSTRACT:- One of the most rapidly developing areas of communications is Smart Antenna systems. This paper
More informationTHE EFFECT of multipath fading in wireless systems can
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 47, NO. 1, FEBRUARY 1998 119 The Diversity Gain of Transmit Diversity in Wireless Systems with Rayleigh Fading Jack H. Winters, Fellow, IEEE Abstract In
More informationINTERFERENCE REJECTION OF ADAPTIVE ARRAY ANTENNAS BY USING LMS AND SMI ALGORITHMS
INTERFERENCE REJECTION OF ADAPTIVE ARRAY ANTENNAS BY USING LMS AND SMI ALGORITHMS Kerim Guney Bilal Babayigit Ali Akdagli e-mail: kguney@erciyes.edu.tr e-mail: bilalb@erciyes.edu.tr e-mail: akdagli@erciyes.edu.tr
More informationSmart Antenna ABSTRACT
Smart Antenna ABSTRACT One of the most rapidly developing areas of communications is Smart Antenna systems. This paper deals with the principle and working of smart antennas and the elegance of their applications
More informationMultiple Antenna Processing for WiMAX
Multiple Antenna Processing for WiMAX Overview Wireless operators face a myriad of obstacles, but fundamental to the performance of any system are the propagation characteristics that restrict delivery
More informationAdvanced Antenna Technology
Advanced Antenna Technology Abdus Salam ICTP, February 2004 School on Digital Radio Communications for Research and Training in Developing Countries Ermanno Pietrosemoli Latin American Networking School
More informationEFFICIENT SMART ANTENNA FOR 4G COMMUNICATIONS
http:// EFFICIENT SMART ANTENNA FOR 4G COMMUNICATIONS 1 Saloni Aggarwal, 2 Neha Kaushik, 3 Deeksha Sharma 1,2,3 UG, Department of Electronics and Communication Engineering, Raj Kumar Goel Institute of
More informationComprehensive Performance Analysis of Non Blind LMS Beamforming Algorithm using a Prefilter
Research Article International Journal of Current Engineering and Technology E-ISSN 2277 4106, P-ISSN 2347-5161 2014 INPRESSCO, All Rights Reserved Available at http://inpressco.com/category/ijcet Comprehensive
More informationMITIGATING INTERFERENCE TO GPS OPERATION USING VARIABLE FORGETTING FACTOR BASED RECURSIVE LEAST SQUARES ESTIMATION
MITIGATING INTERFERENCE TO GPS OPERATION USING VARIABLE FORGETTING FACTOR BASED RECURSIVE LEAST SQUARES ESTIMATION Aseel AlRikabi and Taher AlSharabati Al-Ahliyya Amman University/Electronics and Communications
More informationPerformance Study of A Non-Blind Algorithm for Smart Antenna System
International Journal of Electronics and Communication Engineering. ISSN 0974-2166 Volume 5, Number 4 (2012), pp. 447-455 International Research Publication House http://www.irphouse.com Performance Study
More information2-2 Advanced Wireless Packet Cellular System using Multi User OFDM- SDMA/Inter-BTS Cooperation with 1.3 Gbit/s Downlink Capacity
2-2 Advanced Wireless Packet Cellular System using Multi User OFDM- SDMA/Inter-BTS Cooperation with 1.3 Gbit/s Downlink Capacity KAWAZAWA Toshio, INOUE Takashi, FUJISHIMA Kenzaburo, TAIRA Masanori, YOSHIDA
More information6 Uplink is from the mobile to the base station.
It is well known that by using the directional properties of adaptive arrays, the interference from multiple users operating on the same channel as the desired user in a time division multiple access (TDMA)
More informationAdvanced Communication Systems -Wireless Communication Technology
Advanced Communication Systems -Wireless Communication Technology Dr. Junwei Lu The School of Microelectronic Engineering Faculty of Engineering and Information Technology Outline Introduction to Wireless
More informationMIMO Systems and Applications
MIMO Systems and Applications Mário Marques da Silva marques.silva@ieee.org 1 Outline Introduction System Characterization for MIMO types Space-Time Block Coding (open loop) Selective Transmit Diversity
More informationSIMULATIONS OF ADAPTIVE ALGORITHMS FOR SPATIAL BEAMFORMING
SIMULATIONS OF ADAPTIVE ALGORITHMS FOR SPATIAL BEAMFORMING Ms Juslin F Department of Electronics and Communication, VVIET, Mysuru, India. ABSTRACT The main aim of this paper is to simulate different types
More informationSPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS
SPLIT MLSE ADAPTIVE EQUALIZATION IN SEVERELY FADED RAYLEIGH MIMO CHANNELS RASHMI SABNUAM GUPTA 1 & KANDARPA KUMAR SARMA 2 1 Department of Electronics and Communication Engineering, Tezpur University-784028,
More informationAbstract. Marío A. Bedoya-Martinez. He joined Fujitsu Europe Telecom R&D Centre (UK), where he has been working on R&D of Second-and
Abstract The adaptive antenna array is one of the advanced techniques which could be implemented in the IMT-2 mobile telecommunications systems to achieve high system capacity. In this paper, an integrated
More informationCapacity Enhancement in Wireless Networks using Directional Antennas
Capacity Enhancement in Wireless Networks using Directional Antennas Sedat Atmaca, Celal Ceken, and Ismail Erturk Abstract One of the biggest drawbacks of the wireless environment is the limited bandwidth.
More informationAnalysis of LMS and NLMS Adaptive Beamforming Algorithms
Analysis of LMS and NLMS Adaptive Beamforming Algorithms PG Student.Minal. A. Nemade Dept. of Electronics Engg. Asst. Professor D. G. Ganage Dept. of E&TC Engg. Professor & Head M. B. Mali Dept. of E&TC
More informationSNS COLLEGE OF ENGINEERING COIMBATORE DEPARTMENT OF INFORMATION TECHNOLOGY QUESTION BANK
SNS COLLEGE OF ENGINEERING COIMBATORE 641107 DEPARTMENT OF INFORMATION TECHNOLOGY QUESTION BANK EC6801 WIRELESS COMMUNICATION UNIT-I WIRELESS CHANNELS PART-A 1. What is propagation model? 2. What are the
More informationAdaptive Systems Homework Assignment 3
Signal Processing and Speech Communication Lab Graz University of Technology Adaptive Systems Homework Assignment 3 The analytical part of your homework (your calculation sheets) as well as the MATLAB
More informationVOL. 3, NO.11 Nov, 2012 ISSN Journal of Emerging Trends in Computing and Information Sciences CIS Journal. All rights reserved.
Effect of Fading Correlation on the Performance of Spatial Multiplexed MIMO systems with circular antennas M. A. Mangoud Department of Electrical and Electronics Engineering, University of Bahrain P. O.
More informationEigenvalues and Eigenvectors in Array Antennas. Optimization of Array Antennas for High Performance. Self-introduction
Short Course @ISAP2010 in MACAO Eigenvalues and Eigenvectors in Array Antennas Optimization of Array Antennas for High Performance Nobuyoshi Kikuma Nagoya Institute of Technology, Japan 1 Self-introduction
More informationWireless Networked Systems
Wireless Networked Systems CS 795/895 - Spring 2013 Lec #4: Medium Access Control Power/CarrierSense Control, Multi-Channel, Directional Antenna Tamer Nadeem Dept. of Computer Science Power & Carrier Sense
More informationAdaptive Beamforming for Multi-path Mitigation in GPS
EE608: Adaptive Signal Processing Course Instructor: Prof. U.B.Desai Course Project Report Adaptive Beamforming for Multi-path Mitigation in GPS By Ravindra.S.Kashyap (06307923) Rahul Bhide (0630795) Vijay
More informationAn HARQ scheme with antenna switching for V-BLAST system
An HARQ scheme with antenna switching for V-BLAST system Bonghoe Kim* and Donghee Shim* *Standardization & System Research Gr., Mobile Communication Technology Research LAB., LG Electronics Inc., 533,
More informationWeight Tracking Method for OFDM Adaptive Array in Time Variant Fading Channel
Weight Tracking Method for OFDM Adaptive Array in Time Variant Fading Channel Tomohiro Hiramoto, Atsushi Mizuki, Masaki Shibahara, Takeo Fujii and Iwao Sasase Dept. of Information & Computer Science, Keio
More informationSmart antenna technology
Smart antenna technology In mobile communication systems, capacity and performance are usually limited by two major impairments. They are multipath and co-channel interference [5]. Multipath is a condition
More informationPerformance of a Base Station Feedback-Type Adaptive Array Antenna with Mobile Station Diversity Reception in FDD/DS-CDMA System
Performance of a Base Station Feedback-Type Adaptive Array Antenna with Mobile Station Diversity Reception in FDD/DS-CDMA System S. Gamal El-Dean 1, M. Shokair 2, M. I. Dessouki 3 and N. Elfishawy 4 Faculty
More informationPerformance Comparison of ZF, LMS and RLS Algorithms for Linear Adaptive Equalizer
Advance in Electronic and Electric Engineering. ISSN 2231-1297, Volume 4, Number 6 (2014), pp. 587-592 Research India Publications http://www.ripublication.com/aeee.htm Performance Comparison of ZF, LMS
More informationAnalysis and Improvements of Linear Multi-user user MIMO Precoding Techniques
1 Analysis and Improvements of Linear Multi-user user MIMO Precoding Techniques Bin Song and Martin Haardt Outline 2 Multi-user user MIMO System (main topic in phase I and phase II) critical problem Downlink
More informationCHAPTER 10 CONCLUSIONS AND FUTURE WORK 10.1 Conclusions
CHAPTER 10 CONCLUSIONS AND FUTURE WORK 10.1 Conclusions This dissertation reported results of an investigation into the performance of antenna arrays that can be mounted on handheld radios. Handheld arrays
More informationPerformance Analysis of LMS and NLMS Algorithms for a Smart Antenna System
International Journal of Computer Applications (975 8887) Volume 4 No.9, August 21 Performance Analysis of LMS and NLMS Algorithms for a Smart Antenna System M. Yasin Research Scholar Dr. Pervez Akhtar
More informationCAPACITY ENHANCEMENT IN AERONAUTICAL CHANNELS WITH MIMO TECHNOLOGY
CAPACITY ENHANCEMENT IN AERONAUTICAL CHANNELS WITH MIMO TECHNOLOGY Author: Farzad Moazzami Advisor: Dr. A. Cole-Rhodes Morgan State University ABSTRACT This paper shows how the application of MIMO (multiple-input
More informationMultiple Antennas. Mats Bengtsson, Björn Ottersten. Basic Transmission Schemes 1 September 8, Presentation Outline
Multiple Antennas Capacity and Basic Transmission Schemes Mats Bengtsson, Björn Ottersten Basic Transmission Schemes 1 September 8, 2005 Presentation Outline Channel capacity Some fine details and misconceptions
More informationSmart Antenna Techniques and Their Application to Wireless Ad Hoc Networks
Smart Antenna Techniques and Their Application to Wireless Ad Hoc Networks Jack H. Winters May 31, 2004 jwinters@motia.com 12/05/03 Slide 1 Outline Service Limitations Smart Antennas Ad Hoc Networks Smart
More informationPerformance improvement in beamforming of Smart Antenna by using LMS algorithm
Performance improvement in beamforming of Smart Antenna by using LMS algorithm B. G. Hogade Jyoti Chougale-Patil Shrikant K.Bodhe Research scholar, Student, ME(ELX), Principal, SVKM S NMIMS,. Terna Engineering
More informationADAPTIVE BEAMFORMING USING LMS ALGORITHM
ADAPTIVE BEAMFORMING USING LMS ALGORITHM Revati Joshi 1, Ashwinikumar Dhande 2 1 Student, E&Tc Department, Pune Institute of Computer Technology, Maharashtra, India 2 Professor, E&Tc Department, Pune Institute
More informationAn Advanced Wireless System with MIMO Spatial Scheduling
An Advanced Wireless System with MIMO Spatial Scheduling Jan., 00 What is the key actor or G mobile? ) Coverage High requency band has small diraction & large propagation loss ) s transmit power Higher
More informationFig(1). Basic diagram of smart antenna
Volume 5, Issue 4, 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com A LMS and NLMS Algorithm
More informationSmart antenna for doa using music and esprit
IOSR Journal of Electronics and Communication Engineering (IOSRJECE) ISSN : 2278-2834 Volume 1, Issue 1 (May-June 2012), PP 12-17 Smart antenna for doa using music and esprit SURAYA MUBEEN 1, DR.A.M.PRASAD
More informationKeywords: Adaptive Antennas, Beam forming Algorithm, Signal Nulling, Performance Evaluation.
A Simple Comparative Evaluation of Adaptive Beam forming Algorithms G.C Nwalozie, V.N Okorogu, S.S Maduadichie, A. Adenola Abstract- Adaptive Antennas can be used to increase the capacity, the link quality
More informationMIMO-OFDM adaptive array using short preamble signals
MIMO-OFDM adaptive array using short preamble signals Kentaro Nishimori 1a), Takefumi Hiraguri 2, Ryochi Kataoka 1, and Hideo Makino 1 1 Graduate School of Science and Technology, Niigata University 8050
More informationComparison of Beamforming Techniques for W-CDMA Communication Systems
752 IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 52, NO. 4, JULY 2003 Comparison of Beamforming Techniques for W-CDMA Communication Systems Hsueh-Jyh Li and Ta-Yung Liu Abstract In this paper, different
More informationOn Using Channel Prediction in Adaptive Beamforming Systems
On Using Channel rediction in Adaptive Beamforming Systems T. R. Ramya and Srikrishna Bhashyam Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai - 600 036, India. Email:
More informationELEC E7210: Communication Theory. Lecture 11: MIMO Systems and Space-time Communications
ELEC E7210: Communication Theory Lecture 11: MIMO Systems and Space-time Communications Overview of the last lecture MIMO systems -parallel decomposition; - beamforming; - MIMO channel capacity MIMO Key
More informationPerformance Optimization in Wireless Channel Using Adaptive Fractional Space CMA
Communication Technology, Vol 3, Issue 9, September - ISSN (Online) 78-58 ISSN (Print) 3-556 Performance Optimization in Wireless Channel Using Adaptive Fractional Space CMA Pradyumna Ku. Mohapatra, Prabhat
More informationUniversity of Bristol - Explore Bristol Research. Link to published version (if available): /VTCF
Bian, Y. Q., & Nix, A. R. (2006). Throughput and coverage analysis of a multi-element broadband fixed wireless access (BFWA) system in the presence of co-channel interference. In IEEE 64th Vehicular Technology
More informationAdaptive Beamforming Approach with Robust Interference Suppression
International Journal of Current Engineering and Technology E-ISSN 2277 46, P-ISSN 2347 56 25 INPRESSCO, All Rights Reserved Available at http://inpressco.com/category/ijcet Research Article Adaptive Beamforming
More informationA MAC protocol for full exploitation of Directional Antennas in Ad-hoc Wireless Networks
A MAC protocol for full exploitation of Directional Antennas in Ad-hoc Wireless Networks Thanasis Korakis Gentian Jakllari Leandros Tassiulas Computer Engineering and Telecommunications Department University
More informationA LITERATURE REVIEW IN METHODS TO REDUCE MULTIPLE ACCESS INTERFERENCE, INTER-SYMBOL INTERFERENCE AND CO-CHANNEL INTERFERENCE
Ninth LACCEI Latin American and Caribbean Conference (LACCEI 2011), Engineering for a Smart Planet, Innovation, Information Technology and Computational Tools for Sustainable Development, August 3-5, 2011,
More informationChannel Estimation in Multipath fading Environment using Combined Equalizer and Diversity Techniques
International Journal of Scientific & Engineering Research Volume3, Issue 1, January 2012 1 Channel Estimation in Multipath fading Environment using Combined Equalizer and Diversity Techniques Deepmala
More information3G Evolution. Outline. Chapter: Multi-antenna configurations. Introduction. Introduction. Multi-antenna techniques. Multiple receiver antennas, SIMO
Chapter: 3G Evolution 6 Outline Introduction Multi-antenna configurations Multi-antenna t techniques Vanja Plicanic vanja.plicanic@eit.lth.se lth Multi-antenna techniques Multiple transmitter antennas,
More informationAnalysis of maximal-ratio transmit and combining spatial diversity
This article has been accepted and published on J-STAGE in advance of copyediting. Content is final as presented. Analysis of maximal-ratio transmit and combining spatial diversity Fumiyuki Adachi a),
More informationDesign of Analog and Digital Beamformer for 60GHz MIMO Frequency Selective Channel through Second Order Cone Programming
IOSR Journal of VLSI and Signal Processing (IOSR-JVSP) Volume 5, Issue 6, Ver. II (Nov -Dec. 2015), PP 91-97 e-issn: 2319 4200, p-issn No. : 2319 4197 www.iosrjournals.org Design of Analog and Digital
More informationDirection of Arrival Estimation in Smart Antenna for Marine Communication. Deepthy M Vijayan, Sreedevi K Menon /16/$31.
International Conference on Communication and Signal Processing, April 6-8, 2016, India Direction of Arrival Estimation in Smart Antenna for Marine Communication Deepthy M Vijayan, Sreedevi K Menon Abstract
More informationStudy of Turbo Coded OFDM over Fading Channel
International Journal of Engineering Research and Development e-issn: 2278-067X, p-issn: 2278-800X, www.ijerd.com Volume 3, Issue 2 (August 2012), PP. 54-58 Study of Turbo Coded OFDM over Fading Channel
More informationSpatial Correlation Effects on Channel Estimation of UCA-MIMO Receivers
11 International Conference on Communication Engineering and Networks IPCSIT vol.19 (11) (11) IACSIT Press, Singapore Spatial Correlation Effects on Channel Estimation of UCA-MIMO Receivers M. A. Mangoud
More informationRake-based multiuser detection for quasi-synchronous SDMA systems
Title Rake-bed multiuser detection for qui-synchronous SDMA systems Author(s) Ma, S; Zeng, Y; Ng, TS Citation Ieee Transactions On Communications, 2007, v. 55 n. 3, p. 394-397 Issued Date 2007 URL http://hdl.handle.net/10722/57442
More informationADVANCED WIRELESS TECHNOLOGIES. Aditya K. Jagannatham Indian Institute of Technology Kanpur
ADVANCED WIRELESS TECHNOLOGIES Aditya K. Jagannatham Indian Institute of Technology Kanpur Wireless Signal Fast Fading The wireless signal can reach the receiver via direct and scattered paths. As a result,
More informationSmart Antenna Techniques and Their Application to Wireless Ad Hoc Networks. Plenary Talk at: Jack H. Winters. September 13, 2005
Smart Antenna Techniques and Their Application to Wireless Ad Hoc Networks Plenary Talk at: Jack H. Winters September 13, 2005 jwinters@motia.com 12/05/03 Slide 1 1 Outline Service Limitations Smart Antennas
More informationG.T. Hill.
Making Wi-Fi Suck Less with Dynamic Beamforming G.T. Hill Director, Technical Marketing www.ruckuswireless.com What We ll Cover 802.11n overview and primer Beamforming basics Implementation Lot of Questions
More informationChannel Modelling for Beamforming in Cellular Systems
Channel Modelling for Beamforming in Cellular Systems Salman Durrani Department of Engineering, The Australian National University, Canberra. Email: salman.durrani@anu.edu.au DERF June 26 Outline Introduction
More informationChapter 4: Directional and Smart Antennas. Prof. Yuh-Shyan Chen Department of CSIE National Taipei University
Chapter 4: Directional and Smart Antennas Prof. Yuh-Shyan Chen Department of CSIE National Taipei University 1 Outline Antennas background Directional antennas MAC and communication problems Using Directional
More informationComparison of MIMO OFDM System with BPSK and QPSK Modulation
e t International Journal on Emerging Technologies (Special Issue on NCRIET-2015) 6(2): 188-192(2015) ISSN No. (Print) : 0975-8364 ISSN No. (Online) : 2249-3255 Comparison of MIMO OFDM System with BPSK
More informationAdaptive beamforming using pipelined transform domain filters
Adaptive beamforming using pipelined transform domain filters GEORGE-OTHON GLENTIS Technological Education Institute of Crete, Branch at Chania, Department of Electronics, 3, Romanou Str, Chalepa, 73133
More informationEE360: Lecture 6 Outline MUD/MIMO in Cellular Systems
EE360: Lecture 6 Outline MUD/MIMO in Cellular Systems Announcements Project proposals due today Makeup lecture tomorrow Feb 2, 5-6:15, Gates 100 Multiuser Detection in cellular MIMO in Cellular Multiuser
More informationPERFORMANCE ANALYSIS OF AN UPLINK MISO-CDMA SYSTEM USING MULTISTAGE MULTI-USER DETECTION SCHEME WITH V-BLAST SIGNAL DETECTION ALGORITHMS
PERFORMANCE ANALYSIS OF AN UPLINK MISO-CDMA SYSTEM USING MULTISTAGE MULTI-USER DETECTION SCHEME WITH V-BLAST SIGNAL DETECTION ALGORITHMS 1 G.VAIRAVEL, 2 K.R.SHANKAR KUMAR 1 Associate Professor, ECE Department,
More informationLecture 8 Mul+user Systems
Wireless Communications Lecture 8 Mul+user Systems Prof. Chun-Hung Liu Dept. of Electrical and Computer Engineering National Chiao Tung University Fall 2014 Outline Multiuser Systems (Chapter 14 of Goldsmith
More informationFirst generation mobile communication systems (e.g. NMT and AMPS) are based on analog transmission techniques, whereas second generation systems
1 First generation mobile communication systems (e.g. NMT and AMPS) are based on analog transmission techniques, whereas second generation systems (e.g. GSM and D-AMPS) are digital. In digital systems,
More informationPerformance Analysis of the LMS Adaptive Algorithm for Adaptive Beamforming
Performance Analysis of the LMS Adaptive Algorithm for Adaptive Beamforming Joseph Paulin Nafack Azebaze 1*, Elijah Mwangi 2, Dominic B.O. Konditi 3 1 Department of Electrical Engineering, Pan African
More information3 RANGE INCREASE OF ADAPTIVE AND PHASED ARRAYS IN THE PRESENCE OF INTERFERERS
3 RANGE INCREASE OF ADAPTIVE AND PHASED ARRAYS IN THE PRESENCE OF INTERFERERS A higher directive gain at the base station will result in an increased signal level at the mobile receiver, allowing longer
More informationPERFORMANCE ANALYSIS OF DOWNLINK POWER CONTROL IN WCDMA SYSTEM
PERFORMANCE ANALYSIS OF DOWNLINK POWER CONTROL IN WCDMA SYSTEM Dr. M. Mahbubur Rahman, Md. Khairul Islam, Tarek Hassan-Al-Mahmud, A. R. Mahmud Abstract: WCDMA (Wideband Code Division Multiple Access) plays
More informationA Review on Beamforming Techniques in Wireless Communication
A Review on Beamforming Techniques in Wireless Communication Hemant Kumar Vijayvergia 1, Garima Saini 2 1Assistant Professor, ECE, Govt. Mahila Engineering College Ajmer, Rajasthan, India 2Assistant Professor,
More informationSpatial Reuse through Adaptive Interference Cancellation in Multi-Antenna Wireless Networks
Spatial Reuse through Adaptive Interference Cancellation in Multi-Antenna Wireless Networks A. Singh, P. Ramanathan and B. Van Veen Department of Electrical and Computer Engineering University of Wisconsin-Madison
More informationJoint Transmitter-Receiver Adaptive Forward-Link DS-CDMA System
# - Joint Transmitter-Receiver Adaptive orward-link D-CDMA ystem Li Gao and Tan. Wong Department of Electrical & Computer Engineering University of lorida Gainesville lorida 3-3 Abstract A joint transmitter-receiver
More informationDYNAMIC POWER ALLOCATION SCHEME USING LOAD MATRIX TO CONTROL INTERFERENCE IN 4G MOBILE COMMUNICATION SYSTEMS
DYNAMIC POWER ALLOCATION SCHEME USING LOAD MATRIX TO CONTROL INTERFERENCE IN 4G MOBILE COMMUNICATION SYSTEMS Srinivas karedla 1, Dr. Ch. Santhi Rani 2 1 Assistant Professor, Department of Electronics and
More informationAll Beamforming Solutions Are Not Equal
White Paper All Beamforming Solutions Are Not Equal Executive Summary This white paper compares and contrasts the two major implementations of beamforming found in the market today: Switched array beamforming
More informationFrequency-Domain Channel Estimation for Single- Carrier Transmission in Fast Fading Channels
Wireless Signal Processing & Networking Workshop Advanced Wireless Technologies II @Tohoku University 18 February, 2013 Frequency-Domain Channel Estimation for Single- Carrier Transmission in Fast Fading
More informationAdaptive Array Beamforming using LMS Algorithm
Adaptive Array Beamforming using LMS Algorithm S.C.Upadhyay ME (Digital System) MIT, Pune P. M. Mainkar Associate Professor MIT, Pune Abstract Array processing involves manipulation of signals induced
More informationAdaptive Beamforming Applied for Signals Estimated with MUSIC Algorithm
Buletinul Ştiinţific al Universităţii "Politehnica" din Timişoara Seria ELECTRONICĂ şi TELECOMUNICAŢII TRANSACTIONS on ELECTRONICS and COMMUNICATIONS Tom 57(71), Fascicola 2, 2012 Adaptive Beamforming
More informationEnergy Harvested and Achievable Rate of Massive MIMO under Channel Reciprocity Error
Energy Harvested and Achievable Rate of Massive MIMO under Channel Reciprocity Error Abhishek Thakur 1 1Student, Dept. of Electronics & Communication Engineering, IIIT Manipur ---------------------------------------------------------------------***---------------------------------------------------------------------
More informationChapter 2 Overview. Duplexing, Multiple Access - 1 -
Chapter 2 Overview Part 1 (2 weeks ago) Digital Transmission System Frequencies, Spectrum Allocation Radio Propagation and Radio Channels Part 2 (last week) Modulation, Coding, Error Correction Part 3
More informationCoordinated and Distributed MIMO turning wireless networks on their heads? Gerard Borg
Coordinated and Distributed MIMO turning wireless networks on their heads? Gerard Borg 1 Coordinated and Distributed MIMO Outline Orientation: Coordinated and distributed MIMO vs SISO Theory: Capacity
More informationPerformance of Smart Antennas with Adaptive Combining at Handsets for the 3GPP WCDMA System
Performance of Smart Antennas with Adaptive Combining at Handsets for the 3GPP WCDMA System Suk Won Kim, Dong Sam Ha, Jeong Ho Kim, and Jung Hwan Kim 3 VTVT (Virginia Tech VLSI for Telecommunications)
More informationPerformance Analysis of MUSIC and LMS Algorithms for Smart Antenna Systems
nternational Journal of Electronics Engineering, 2 (2), 200, pp. 27 275 Performance Analysis of USC and LS Algorithms for Smart Antenna Systems d. Bakhar, Vani R.. and P.V. unagund 2 Department of E and
More informationTHROUGHPUT AND CHANNEL CAPACITY OF MULTI-HOP VIRTUAL CELLULAR NETWORK
The th International Symposium on Wireless Personal Multimedia Communications (MC 9) THOUGHPUT AND CHANNEL CAPACITY OF MULTI-HOP VITUAL CELLULA NETWO Eisuke udoh Tohoku University Sendai, Japan Fumiyuki
More informationON THE USE OF MULTI-DIMENSIONAL CHANNEL SOUNDING FIELD MEASUREMENT DATA FOR SYSTEM- LEVEL PERFORMANCE EVALUATIONS
EUROPEAN COOPERATION IN THE FIELD OF SCIENTIFIC AND TECHNICAL RESEARCH COST 273 TD(02) 164 Lisbon, Portugal 2002/Sep/19-20 EURO-COST SOURCE: University of Oulu, Finland ON THE USE OF MULTI-DIMENSIONAL
More informationInterference Reduction in Wireless Communication Using Adaptive Beam Forming Algorithm and Windows
Volume 117 No. 21 2017, 789-797 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu ijpam.eu Interference Reduction in Wireless Communication Using Adaptive Beam
More informationIEEE Working Group on Mobile Broadband Wireless Access <http://grouper.ieee.org/groups/802/20/>
00-0- Project Title Date Submitted Source(s) Re: Abstract Purpose Notice Release Patent Policy IEEE 0.0 Working Group on Mobile Broadband Wireless Access IEEE C0.0-/0
More informationLow-Complexity Beam Allocation for Switched-Beam Based Multiuser Massive MIMO Systems
Low-Complexity Beam Allocation for Switched-Beam Based Multiuser Massive MIMO Systems Jiangzhou Wang University of Kent 1 / 31 Best Wishes to Professor Fumiyuki Adachi, Father of Wideband CDMA [1]. [1]
More informationIF ONE OR MORE of the antennas in a wireless communication
1976 IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION, VOL. 52, NO. 8, AUGUST 2004 Adaptive Crossed Dipole Antennas Using a Genetic Algorithm Randy L. Haupt, Fellow, IEEE Abstract Antenna misalignment in
More informationORTHOGONAL frequency division multiplexing (OFDM)
144 IEEE TRANSACTIONS ON BROADCASTING, VOL. 51, NO. 1, MARCH 2005 Performance Analysis for OFDM-CDMA With Joint Frequency-Time Spreading Kan Zheng, Student Member, IEEE, Guoyan Zeng, and Wenbo Wang, Member,
More informationPerformance Evaluation of Nonlinear Equalizer based on Multilayer Perceptron for OFDM Power- Line Communication
International Journal of Electrical Engineering. ISSN 974-2158 Volume 4, Number 8 (211), pp. 929-938 International Research Publication House http://www.irphouse.com Performance Evaluation of Nonlinear
More informationOptimum Rate Allocation for Two-Class Services in CDMA Smart Antenna Systems
810 IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 51, NO. 5, MAY 2003 Optimum Rate Allocation for Two-Class Services in CDMA Smart Antenna Systems Il-Min Kim, Member, IEEE, Hyung-Myung Kim, Senior Member,
More informationREMOTE CONTROL OF TRANSMIT BEAMFORMING IN TDD/MIMO SYSTEMS
The 7th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 6) REMOTE CONTROL OF TRANSMIT BEAMFORMING IN TDD/MIMO SYSTEMS Yoshitaa Hara Kazuyoshi Oshima Mitsubishi
More informationJaswant 1, Sanjeev Dhull 2 1 Research Scholar, Electronics and Communication, GJUS & T, Hisar, Haryana, India; is the corr-esponding author.
Performance Analysis of Constant Modulus Algorithm and Multi Modulus Algorithm for Quadrature Amplitude Modulation Jaswant 1, Sanjeev Dhull 2 1 Research Scholar, Electronics and Communication, GJUS & T,
More informationUplink and Downlink Beamforming for Fading Channels. Mats Bengtsson and Björn Ottersten
Uplink and Downlink Beamforming for Fading Channels Mats Bengtsson and Björn Ottersten 999-02-7 In Proceedings of 2nd IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications,
More informationPerformance Evaluation of different α value for OFDM System
Performance Evaluation of different α value for OFDM System Dr. K.Elangovan Dept. of Computer Science & Engineering Bharathidasan University richirappalli Abstract: Orthogonal Frequency Division Multiplexing
More informationAdaptive Kalman Filter based Channel Equalizer
Adaptive Kalman Filter based Bharti Kaushal, Agya Mishra Department of Electronics & Communication Jabalpur Engineering College, Jabalpur (M.P.), India Abstract- Equalization is a necessity of the communication
More information