Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) Effec of Modulaion Schemes on Performance of OFDM based Wireless Nework using Smar Anenna 1 Mr.Balaji G.Hogade, 1 Research Scholar, EXTC, SVKM s, NMIMS, MPSTME Vileparle, Mumbai, Associae Professor,Terna Engineering College,Navi Mumbai, India, E-mail: bghogade@gmail.com 2 Dr Shrikan K Bodhe 2 Principal, Pandharpur, COE, Solapur, Maharashra, India, E-mail: s_k_bodhe@yahoo.co.in 3 Mrs.Vrishali M Pail 3 Suden, ME (EXTC), Terna Engineering College, Nerul, Navi Mumbai E-mail: vmsipa10@gmail.com ABSTRACT : In his paper we have presened he effec of differen modulaion Techniques (QPSK, 16QAM and 64QAM) and number of anenna elemens a he receiver (Smar Anenna) on he performance of beamforming in OFDM based Wireless nework. The performance of he proposed echnique is esed for adapive beam forming algorih Leas Mean Square (LMS), improved LMS and convenional beamforming for differen number of anenna elemens. Proposed sysem no only has good abiliy of suppressing inerference, bu also significanly improves he bi-error rae () performance of he sysem. Simulaion resuls show ha an adapive beam forming gives he opimum performance on urban channels. SNR vs., are compared using same se of parameers. Keywords - Beamforming, LTE, OFDM, Smar Anenna, WiMAX, WLAN. I. INTRODUCTION In Wireless Communicaion sysems, capaciy and performance of nework are usually limied by wo major impairmens, mulipah and co-channel inerference. Smar anenna is one of he mos promising echnologies ha will enable a higher capaciy in wireless neworks by effecively reducing mulipah and cochannel inerference. Smar Anenna use adapive beam forming algorihms in a dynamic environmen coninuously adjusing he weigh of anenna arrays for creaing a beam o rack desired users auomaically, and minimize inerference from oher users by placing nulls in heir direcions. Proposed sysem no only has good abiliy of suppressing inerference, bu also significanly improves he bi-error rae () performance of he sysem. Orhogonal frequency division muliplexing (OFDM) sysem is a promising scheme for broadband communicaions. As wireless communicaion sysems look inenly o compose he ransiion from voice communicaion o ineracive inerne daa, achieving higher bi raes becomes boh increasingly desirable and challenging. In oday s world a large number of wireless ransmission echnologies exis. These echnologies are disribued over differen nework families depending upon he nework scale such as PAN (Personal Area Nework), WLAN (Wireless Local Area nework), WMAN (wireless Meropolian Area Nework), WAN (wireless Area Nework) and LTE (Long Term Evoluion). As he demand for daa ransmission wih higher raes changed so is he focus on he deploymen of wireless neworks. Technologies ha promise o deliver higher daa raes are aracing more and more vendors and operaors owards hem. II. LITERATURE SURVEY. Basically he hree main facors which limi ransmiing high daa rae over he wireless medium are mulipah fading, delay spread and co-channel inerference [1]. The released WiMAX sandard (802.16d) [2] repors a MAC layer and five physical layers, each suied for especial applicaion and frequency range. Wireless MAN-OFDM is one of hem [3]. The Wireless MAN-OFDM inerface can be highly limied by he presence of fading caused by mulipah propagaion and as resul he refleced signals arriving a he receiver are muliplied wih differen delays, which cause Inersymbol inerference (ISI). OFDM basically is designed o overcome his issue and for siuaions where high daa rae is o be ransmied over a channel wih a relaively large maximum delay. If he delay of he received signals is larger han he guard inerval, ISI may cause severe degradaions in ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1480
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) sysem performance. To solve his issue muliple anenna array can be used a he receiver, which provides specral efficiency and inerference suppression [4]. Smar anenna Sysem (SAS) is an opional feaure in IEEE 802.16d sandard bu o enhance he coverage, capaciy and specral efficiency, i should be essenial for an OFDM air inerface. I has an advanage of having single anenna sysem a he subscriber saion and all he burden is on base saion [3]. An array of anenna is se up a he base saion o cu down iner-cell inerference and fading effecs by furnishing eiher beamforming or diversiy gains. When small spacing is adoped, he fading is highly correlaed and Beamforming echniques can be employed for inerference rejecion as compared o Diversiy-oriened schemes [5]. As a resul receiver can separae he desired LOS signal from he mulipah signals and nulls are formed a he inerfering signals. As specialized in he sandard, 802.16a OFDM PHY layer baseband ransmier is compiled of hree major pars: channel coding, modulaion, and OFDM ransmier. For he receiver complimenary operaions are applied in he reverse order. Channel coding cies o he class of signal ransformaions considered o improve communicaions performance by enabling he ransmied signal o beer endure he effecs of various channel deerioraions, such as noise, fading, and jamming. The goal of channel coding is o improve he bi error rae () performance of power-limied and bandwidh limied channels by adding srucured idleness o he ransmied daa [6]. Modulaion is he process of mapping he digial informaion o analog form so ha i can be ransmied over he channel. For an OFDM sysem he changing of phase and ampliude can be done bu he frequency canno change because hey have o be kep orhogonal. The modulaions used in 802.16 are QPSK, 16 QAM, and 64QAM. Smar Anenna Sysem (SAS) consis of se of radiaing elemens capable of sending and receiving signals in such a way ha radiaed signals combine ogeher o form a swichable and movable beam owards he user. However i may be noed ha he hardware of he smar anenna does no make hem smar, in fac i is he signal processing echnique ha is used o focus he beam of he radiaed signals in he desired direcion. This process of combining he signal and hen focusing he signal in paricular direcion is called Beamforming [9]. The smar anenna sysem performs he following funcions. Firs i calculaes he direcion of arrival of all incoming signals including he mulipah signal and he inerferers using he Direcion of Arrival (DOA) algorihms wih for example MUSIC and ESPIRIT [11]. This is jus wo of many used algorihms. DOA informaion is hen fed ino he weigh updaing algorihm o calculae he corresponding complex weighs. For ha adapive beamforming algorihm like Leas Mean Square (LMS), Recursive Leas Squares (RLS) or Sample Marix Inversion (SMI),Improved LMS, convenional beamforming can be used [10,11]. III. ORTHOGONAL FREQUENCY DIVISION MULTIPLEXING: WiMAX uses OFDM as he physical layer. OFDM allows large amouns of digial daa o be ransmied over a lump of specrum wih greaer efficiency han exising wireless echnologies. OFDM works by spliing he radio signal ino muliple smaller signals ha are hen ransmied simulaneously a differen frequencies o he receiver. An OFDM-based sysem is able o squeeze a 72 Mbi/s daa rae ou of 20 MHz of channel specrum under ideal condiions. The key o OFDM is ha he differen frequencies can be ransmied and received enirely independenly of each oher (his is he orhogonal propery). Typically in a wireless sysem he radio waves ravel from he ransmier o he receiver in a like mode o ligh rays some rays migh go sraigh from he ransmier o he receiver and oher will ake a hop off rees, buildings and cars [7]. These various mulipah, as hey are known, can inerfere consrucively or desrucively which causes varying signal power a he receiver. If he daa rae of he channel is low, compared o he ime difference beween he various mulipah componens, hen a fade (a reducion in he received signal srengh) can resul deep fades of up o 1000 imes (30 db) are possible in such sysems. If, however, a channel is ransmiing high raes of daa hen mulipah propagaion resuls in a frequency-selecive fading, i.e. he channel is disored in phase and ampliude. Complex equalizers are ofen used o measure he channel disorion and correc i in real ime. IV. SYSTEM MODEL A Transmier Module: A he ransmier, he inpu random daa is serial o parallel convered and hen mapped o eiher of he modulaion ypes (QPSK, 16QAM, 64QAM). The obained N samples are hen passed hrough he IFFT block. As a resul an OFDM symbol is generaed consising of a block of N samples. So he frequency domain signal consising of daa symbol, pilo symbols and virual symbols are ransformed by IFFT ino ime domain signal and hen ransmied over he radio channel. i. OFDM Symbol Descripion: The WMAN-OFDM-PHY is based on OFDM modulaion. An OFDM symbol is made up from carriers, and he FFT size is deermined by he carrier number. Three ypes of carriers are used here: Daa carriers: for daa ransmission ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1481
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) Pilo carriers: for various esimaion purposes Null carriers: no ransmission a all, for guard bands and DC carrier The purpose of he guard bands is o enable he signal o decay and creae he FFT brick wall shaping [8]. This also conribues for canceling iner-channel inerference. Figure 1 shows he OFDM frequency descripion. Figure 1 OFDM frequency descripion. The ransmied signal volage o he anenna, as a funcion of ime during any OFDM symbol can be wrien as [2]: s( ) = Re{ e Nused / 2 j 2πfc ck k= Nused / 2 k 0 e j 2πkΔf ( Tg ) } (1) Where is he ime elapsed since he beginning of he OFDM symbol wih 0 < <Ts and C k is a complex number; he daa o be ransmied on he subcarrier whose frequency offse index is k during he subjec OFDM symbol. OFDM wave form is creaed by Inverse Fas Fourier ransforming: his ime duraion is referred o as useful symbol ime T b [2]. A copy of he las of he useful symbol period T g, ermed CP, is used o collec mulipah, while mainaining he orhogonaliy of he codes. Daa is sen in he form of OFDM symbols. The basic srucure of an OFDM symbol is represened in frequency domain. ii. Random Daa Generaion: The inpu daa is generaed in he form of random numbers i.e. series of ones and zeros (110000111001). The lengh of he informaion bis depends upon he ype of he modulaion scheme used o map he bis o symbols (QPSK, 16QAM, 64QAM). The generaed daa is hen passed o he Modulaion sub-module for symbol mapping. iii. Modulaion: The generaed daa is hen passed o he consellaion mapper, where depending upon is size he daa was modulaed using he following hree differen modulaion schemes: QPSK, 16QAM, and 64QAM o form an OFDM frequency-domain signal [2]. Modulaion is done by dividing he incoming bis ino groups of i bis o represen a modulaed signal. As a resul here are 2 i poins, and he oal number of poins represens a consellaion. The size of i for QPSK, 16QAM, 64QAM is, 2, 4, and 6 respecively. Random daa generaor Modulaor (QPSK, 16QAM, 64QAM) IFFT Cyclic prefix i i Figure 2: Transmier Module. iv. Pilo Modulaion: Pilo symbols allocae specific subcarriers in all OFDM daa symbols. To consiue he symbol, he pilo subcarriers are insered ino each daa burs and hey are modulaed according o heir carrier locaion wihin he OFDM symbol. For ha, pseudo random binary sequence (PRBS) generaor is used o produce a sequence w k. v. IFFT: Afer successful daa Modulaion Inverse Fas Fourier Transform was applied on he modulaed daa o conver i from frequency domain ino ime domain. IFFT is simple o use and i guaranees ha he carriers signal ready o be sen owards he receiver are orhogonal in naure. The h ime domain sample a he n h subcarrier a he oupu of IFFT is given by [12]. ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1482
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) x = N 1 n= 0 X n 2πn exp{ j } 0 N 1 (2) N Where N is he number of subcarriers and is he daa symbol on he n h subcarrier. As a resul an OFDM symbol is generaed. FFT is jus a compuaionally fas way o calculae he DFT. We can move back and forh beween he ime domain and frequency domain wihou losing informaion [13]. vi. Cyclic Prefix Inserion: Cyclic Prefix (CP) was added o he daa once he daa was convered ino ime domain and ready o be ransmied. The addiion of CP o he daa before i was acually ransmied helped he daa o caer he problems relaed o he mulipah propagaion and provided a resisance agains ISI. IEEE 802.16d allows he inserion of Cyclic Prefix of various lenghs such 1/4, 1/8, 1/16, and 1/32, here a CP of lengh 1/4 is added o he OFDM symbol before i was ransmied. The ransmied daa is hen fed ino he channel. B. Channel Module: The basic aspire of wide area neworks using broadband wireless channels is o accomplish high daa raes wih sane bandwidh and power consumpion. Mainaining high coverage and qualiy of service sandard was somehing ha was considered undoable unil he arrival of WiMAX which promises o deliver high daa raes wih improved coverage. One of he main problems faced by he wireless neworks is cope wih he ecology challenges once he signal is on air from is way owards he receiver. Whenever a deploymen of a wireless communicaion sysem is considered, he firs hing ha mus be addressed properly is he design of a channel model. Once he signal is sen from he ransmier owards he receiver i has o come across several environmenal effecs or condiions. These effecs play a significan role in wireless communicaion echnology and his is where he design of he channel model comes ino play. In order o design an efficien wireless channel model following hings mus be kep in mind [14]: Mulipah delay spread, Fading characerisics, Pah loss, Doppler spread, Co-channel inerference. Addiive Whie Gaussian Noise (AWGN) Channel: This channel adds whie Gaussian noise o he ransmied signal. In his channel model fading, inerference and dispersion are no considered. The mahemaical model for he received signal passed hrough an AWGN channel is shown in figure 3 and is represened by equaion 3, () s() n() r = + (3). A. Figure 3 an AWGN channel. C Receiver Module: A he receiver an array of anennas is deployed. The differen sub modules a he receiver are now explained. a) Anenna Array Model: A general case of linear anenna array wih uniformly spaced sensors is considered as shown in figure 4. ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1483
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) Figure 4: Anenna Array Model I is assumed ha he enire signals inciden on he anenna array is composed of plane waves and he ransmied signal is in he far field of he anenna array [15] [16]. Le M be he number of anenna elemens. Usually an array has a reference elemen, here he lef mos elemens is supposed o be considered as he reference elemen. So he plane wave firs reaches he reference elemen and hen i propagaes all he way o he M h anenna elemen. There are L incoming signals due o L pahs. When he signals ravel across he array hey suffer a phase shif. The phase shif beween he signal received a he reference elemen and he same signal received a elemen m is given by [16] Δα m = kd( m 1) cosφ (4) Noe ha Δα = 1 0. Les now define he incoming signal a he array elemen 1(reference elemen) due o lh he pah by j 2πf0 sl, = xl, e (5) Where x l, is he modulaing funcion of he l pah and f 0 he frequency of he carrier signal. The incoming signal a elemen m will be in ha case r Where = x l, e j(2πf0 + Δαm ) + s l, am( ) + n n = φ (6) a m ( φ ) l e e jδαm jkd ( m 1) cosφl = = (7) Seering Vecor describes he phases of he signal received a each anenna elemen as compared o he phase of he signal a reference elemen [18]. The seering vecor can be represened as a m 1 a2( φl )... ( φ = l ) (8) am( φl )... am ( φl ) Now considering all he pahs simulaneously, he signal a he m h elemen will be r = L l= 1 x l, e j(2πf +Δ 0 αm ) + n ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1484
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) = L l= 1 s a (φ + n (9) l, m ) h Where L is he number of incoming signals, φ l is he angle of arrival of he l pah as shown in figure 4, s l, is he ransmied signal for hel h pah and n m, denoes he Mx1 vecor of he noise a he array elemens. b) Pre-FFT Beam-forming Beam-forming is used o separae he desired signal from he inerfering signals given ha hey have same frequencies bu differen spaial locaions. Inerference signals can be oher user signals or can be he signals from mulipah environmen [15]. Pre-FFT beam-forming also called ime-domain beamforming seup a receiver is illusraed in figure 4. Here beamforming is applied before he FFT operaion. Adapive beamforming involves wo seps: Firs he weigh calculaion and hen beamforming by applying he weighs o he received signal. Consider a Narrowband beam-former, where signals from each elemen are muliplied by a complex weigh and summed o form he array oupu [11]. y = M m= 1 w r = w r H m (10) Where subscrip H denoes complex conjugae ransposiion of a vecor or marix and w is called he array weigh vecor. w = w, w,..., ] r [ 1 2 w M r = r ( ), r ( ),..., r ( )] [ 1 2 The oupu of he array sysem becomes T M T y = w H r (11) c) Adapive beamforming Algorihm used: There are many ypes of Adapive beamforming algorihms. The minimum mean square error (MMSE) crierion algorihms such as he leas mean squares (LMS) and recursive leas square algorihm (RLS) are ofen used for updaing weighs in adapive beamforming [15, 11]. Due o complex muliplicaions per updae for he RLS algorih he LMS algorihm is generally employed [19]. LMS which is ieraive makes use of pas informaion o minimize he compuaions required a each updae cycle is used in his simulaor [12]. The LMS algorihm is based on he seepes-decen mehod which recursively compues and updaes he sensor array weigh vecors [20]. The oupu of he array is compared wih he reference signal generaed a he receiver. Here he reference signal is assumed o be idenical o he incoming signal and have similar saisical properies as he ransmied signal. The error signal is pu ino he weigh updaing algorihm. The gradien approach which provides an ieraive updae soluion for he MMSE crieria is given by [12] w = w 1 2 j( w i 1 i i + μ (12) ) The convergence characerisic of he algorihm depends on he parameer μ. j( w) funcion j ( w) which is given by: 2 is he gradien of H j( wm ) = E[ wm ri di ] (13) The funcion j ( w) is he cos funcion. By solving he gradien of he cos funcion in above equaion and we can ge he approximaed soluion for he insananeous squared error and Sub. So he Leas Mean Square algorihm is found by [12]: w i 1 = w i μ ri ei, m (14) + + ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1485
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) Where H e i, m w iri d i = is he error beween he array oupu and reference signal. Afer applying he adapive beamforming algorihm he desired LOS signal was obained, hus filering i ou from unwaned (null and inerfering signals). The desired oupu signal from he beamformer as shown in he figure 5 i.e. Y () is hen processed in he following way so ha he original signal can be exraced. Figure 5: Receiver Module The process sars wih he removal of he cyclic prefix ha was iniially added o he ransmied signal as earlier on explained in he ransmier module. Afer cyclic prefix removal, he daa was convered back ino frequency domain from he ime domain using he FFT. Once he daa conversion is compleed he daa is passed o he De-Modulaor where he daa is De-modulaed according o modulaion schemes applied on he daa during he ransmission. The De-modulaion of he daa marks he end of he receiver module where he daa obained from De-modulaor was compared o original daa in form Bi Error Rae (). D The simulaion block diagram: Figure 6: Simulaion Block Diagram. V. SIMULATION RESULTS: The simulaions implemened in his paper are all done in MATLAB. The whole sysem was esed using Mone Carlo based simulaions [21]. The Mone Carlo simulaion is used o esimae he which he sysem can achieve. In his model he simulaion of he sysem is repeaed and he number of ransmied bis and bi errors are calculaed for each simulaion. In he end rae is esimaed as he raio of he oal number of observed errors and he oal number of ransmied bis [21]. The parameers ha can be se are: number of simulaed OFDM symbols, modulaion scheme, and number of anennas a receiver and range of SNR values. a. Performance in Urban Channel: Performance of he sysem model esed using differen modulaion schemes i.e. QPSK (quadraure phaseshif keying), 16 QAM (Quadraure Ampliude Modulaion) and 64QAM wih an urban channel. Figure 7(a-i) ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1486
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) shows he simulaion resuls for QPSK, 16 QAM and 64QAM. In all of he figures a comparison is shown beween he simulaed for his sysem model. I has been concluded from he simulaion resuls ha simulaed for urban channel good for all Modulaion schemes and grea improvemen by increasing he number of anenna elemens a he receiver. The simulaion resuls are shown using a single anenna a he ransmier and muliple anennas a he receiver. The simulaions are performed for implemening he AAS(Adapive Anenna Sysem) using Pre-FFT beamformer in WiMAX OFDM sysem: QPSK,16 QAM and 64QAM modulaion is used in sysem and halfwavelengh spacing is employed and all he resuls are relaive o smar anenna composed by K=2,K=4, K=8 and K=16 sensors. Differen aspecs of he complee sysem model were invesigaed such as angle of arrival of he incoming signals and number of array elemens. The value of μ used is 0.001. When applying he channel condiions o adapive array fixed WiMAX (World Wide Ineroperabiliy for Micro Wave Access) syse he receiver separaed he desired LOS signal from he mulipah signals. Also he bi error rae () performances are evaluaed. So i can be seen ha he performance of he sysem improves if we increase he number of anennas a he receiver. I can be seen from he resuls ha curve is improved afer using an SAS a he receiver and he desired signal a he receiver is deeced wih low bi rae. 10 0 vs. SNR. Channel:Urban. Modulaion:QPSK. Beamforming:LMS Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 10-6 (a) ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1487
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) 10 0 vs. SNR. Channel:Urban. Modulaion:16QAM. Beamforming:LMS Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 (b) 10 0 vs. SNR. Channel:Urban. Modulaion:64QAM. Beamforming:LMS Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 (c) ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1488
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) 10 0 vs. SNR. Channel:Urban. Modulaion:QPSK. Beamforming:Improved LMS Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 10-6 (d) 10 0 vs. SNR. Channel:Urban. Modulaion:16QAM. Beamforming:Improved LMS Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 10-6 (e) ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1489
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) 10 0 vs. SNR. Channel:Urban. Modulaion:64QAM. Beamforming:Improved LMS 10-6 Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 (f) 10 0 vs. SNR. Channel:Urban. Modulaion:QPSK. Beamforming:Convenional Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 (g) ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1490
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) 10 0 vs. SNR. Channel:Urban. Modulaion:16QAM. Beamforming:Convenional Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 10-6 (h) 10 0 vs. SNR. Channel:Urban. Modulaion:64QAM. Beamforming:Convenional Anenna Elemen:2 Anenna Elemen:4 Anenna Elemen:8 Anenna Elemen:16 (i) Figure 7 (a-i) vs. SNR for differen modulaion schemes and number of anenna elemens a he receiver VI. CONCLUSION: To reduce he effec caused by fading, SAS is implemened a he receiver module by using LMS algorih improved LMS, convenional beamforming and pre-fft beamforming. The whole sysem was esed wih SAS using differen modulaion schemes. Finally performance in erms of vs. SNR has been driven. I can be concluded from he simulaion resuls ha, if here is an SAS insalled a he receiver hen performance of he sysem drasically increases as we go on increasing he number of anenna elemens a he receiver. ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1491
Mr.Balaji G.Hogade e al. / Inernaional Journal on Compuer Science and Engineering (IJCSE) REFERENCES: [1] Hidehiro Masuoka and Hiroki Shoki, Comparison of pre-fft and pos-fft processing adapive arrays for OFDM sysems in he presence of co-channel inerference. Corporae R&D Cenre. Toshiba Corporaion I Komukai-Toshiba-cho, Saiwai-ki, Kawasaki 212-8582, Japan [2] Wireless MAN Group. IEEE sandard for local and meropolian area neworks. Technical Repor IEEE Sd 802.16-2001, wirelessman.org, 2001. Par 16, Air Inerface for Fixed Broadband Wireless Access Sysems. [3] Y. Li, D. Kenyon, An Examinaion of he Processing Complexiy of an Adapive Anenna Sysem (AAS) for WiMAX. IEE 2005 Firs presened a he 2nd IEE/EURASIP DSPEnabledRadio Conference, Sepember 2005, Souhampon. [4] Daniele Borio, Laura Camoriano, Leizia Lo Presi and Marina Mondin, Beamforming and Synchronizaion Algorihms Inegraion for OFDM HAP-Based Communicaions Inernaional Journal of Wireless Informaion Neworks, Vol. 13, No. 1, January 2006. [5] M. Nicoli, L. Sampiero, C. Sanacesaria, U. Spagnolini, D. Archei, A. Bonfani, M. Sala, Deploymen and Design of Muli Anenna Soluions for Fixed WiMax Sysems. Dip. di Eleronica e Informazione, Poliecnico di Milano, Milano, Ialy, Siemens Neworks S.p.A., Cassina de Pecchi (Milano), Ialy [6] Juha Heiskala, John Terry, OFDM Wireless LANs: A Theoriical and Pracical Guide, Firs Ediion, Sams Publishing, December 2001. [7] Hodgkinson T: Wireless communicaions he fundamenals, BT Technol J, 25, No 2, pp 11 26 (April 2007). [8] IEEE 802.16a WMAN organizaion, Air Inerface for Fixed Broadband Wireless Access Sysems. ParA:Sysems beween 2-11 GHz, April 2003. [9] Online Educaion, Smar Anenna Sysems, Inernaional Engineering Consorium.hp://www.iec.org/online/uorials/smar_an/opic01.hml. 2003 [10] Book, Smar Anennas by Lal Chand Godara, 2004 by CRC press LLC. [11] Lal.C.Godara, Applicaion of Anenna Array o Mobile communicaions, Par II: Beam-forming and DOA consideraions, Proceedings of he IEEE, VOL NO.85, NO.8, Augus 1997. [12] Mohamed S. Heakle, Mohab A. Mangoud and Said Elnoubi, LMS Beamforming Using Pre and Pos-FFT Processing for OFDM Communicaion Sysems, 24h Naional Radio Science Conference (NRSC 2007), Faculy of Engineering, Ain shams Univ, Egyp. March 13-15, 2007 [13] Bores Signal Processing, Inroducion o DSP.hp://www.bores.com/courses/inro/index.hm [14] Book, S. Rappapor, Wireless Communicaions Principles and Pracice Second Ediion. [15] Book, Smar Anennas by Lal Chand Godara, 2004 by CRC press LLC. [16] Tom Mahes, Algorihm for Direcion of Arrival Esimaion in a Smar Anenna, Lausanne, July 2007. [17] A. A. Shishegar, N. Hojja, R. Alihemmai, G. Dadashzadeh, A. Mehrash, B. Boghrai, The Effec of he Number of Smar Anenna Elemens on he Performance of 802.11a WLAN wih Pre and Pos-FFT Mehods, Inernaional Symposium on Telecommunicaions, Sepember,10-12, 2005,Shiraz, Iran [18] Fabrizio Sellone, Fundamenals of Smar anennas For Wireless Communicaions. [19] Y. S. Cho, C. K. Ki and K. Lee, Adapive beamforming algorihm for OFDM sysems wih anenna arrays, IEEE Transacions on Consumer Elecronics, Vol. 46, No. 4, pp. 1052 1058, November 2000. [20] UOY, POLITO, EUCON, Repor on Adapive Beamforming Algorihms For Advanced Anenna Types For Aerial Plaform And Ground Terminals, Jan 2006. [21] Dr. B.P. Paris, Simulaion of Wireless Communicaion Sysems using MATLAB, fall 2007. [22] Prof.B.G. Hogade, Ms. Jyoi Chougale-Pail, Dr.Shrikan K.Bodhe, Analysis of Improved and Tradiional LMS Beamforming Algorihm for Smar Anenna, Inernaional Journal of Engineering Research and Applicaions (IJERA),ISSN: 2248-9622 Vol. 2, Issue 3, May-Jun 2012, pp.1816-1820. [23] B.G. Hogade, Ms. Sheeal Wadhe, Dr.Shrikan K.Bodhe, Miigaing he Effec of CCI and Mulipah in Mobile Communicaion using Smar Anenna, Inernaional Journal of Engineering Research and Applicaions (IJERA) ISSN: 2248-9622, (VNCET-30 Mar 12), pp 366-370. [24] Mr R.B.Waghmare,Prof B.G.Hogade,Dr S.K.Bodhe, MIMO The Nex Generaion Wireless Communicaion Syse (IJGTI ) Inernaional Journal of Global Technology Iniiaives, ISSN 2277-6591,Issue 1,March 29, 2012,ppD38-D42. [25] B. G. Hogade, Jyoi Chougale-Pail,Shrikan K.Bodhe, Performance improvemen in beamforming of Smar Anenna by using LMS algorih Inernaional Journal of Compuer Applicaions (IJCA), (NCIPET-2012)28 Th January, 2012, pp31-35. [26] Mr. Balaji G.Hogade, Dr Shrikan K Bodhe, Effec of Wideband Signals on Smar Anenna, Vol.3 No.1 ( (IJoAT ) Inernaional Journal of Advancemens in Technology, ISSN 0976-4860, (January 2012) pp 55-63. AUTHORS PROFILE Balaji G. Hogade received M.E. in Power Elecronics from Gulbarga Universiy, Karnaaka, in 1999. He is an Associae Professor in Elecronics Engineering in Terna Engineering College, And a Research Scholar in EXTC in SVKMS, NMIMS, and MPSTME Mumbai. He has guided number of projecs and hesis in graduae and pos-graduae level program. He has produced several naional and inernaional publicaions. He is a Member of BOS in Elecronics Engineering In Universiy Of Mumba.His research ineress include Wireless Nework, Smar Anenna and Power Elecronics. ISSN : 0975-3397 Vol. 4 No. 08 Aug 2012 1492