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  1. 1. Prof. Shivendra Singh, Prof. Vikas Gupta, Shiv kumar Yadav / International Journal ofEngineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.946-949946 | P a g ePerformance Analysis of MIMO-OFDM (802.11n System) forWLAN Channel Model*Prof. Shivendra Singh, **Prof. Vikas Gupta, ***Shiv kumar Yadav*Associate prof. T.I.T. Science Deptt. of EC**Associate prof. T.I.T. Deptt. of EC***M.Tech. DC, T.I.T. BhopalAbstractFading is a common problem for thewireless communication system especially inurban areas where a large number of buildingsreflecting the radio signals that result ininterference between the reflected signals makesthe fading effect since multiple selective nature ofthe spectrum at some specific place cancels out sothe reception signal loss any part of yourinformation in this sharply increases thecommunication system BER in slight motion ofreceiver, this paper specially analyzes the BERperformance under Rayleigh fading channelconditions of MIMO-OFDM in presence ofAWGN (Additive White Gaussian Noise) fordifferent number of Transimitting, differentnumber of users, and different path gains systemanalysis is performed by simulating the MIMO-OFDM using MATLAB program, and finally thepaper also presents a comparison betweensimulated results.Keywords: MIMO-OFDM, AWGN (AdditiveWhite Gaussian Noise), Rayleigh fading.1. IntroductionMultipath fading is not a new problem forwireless communication, but the recent growth inthe mobile communication system, attracted thedesigner to think seriously about the problem, as itis difficult to avoid this kind of problem in thetransport conditions. Because the device is on themove, can not impose restrictions on it and couldtravel to many points that correspond to selectivefading.Multipath fading in wirelesscommunication could occur by reflection of radiosignals from different objects (multipath causesinclude air ducts, the ionospheric reflection andrefraction, and reflection from water bodies andterrestrial objects such as mountains and buildings)that causes the reception of signals at different phaseangles at the receiver. Multipath effects includeconstructive and destructive interference, and phaseshifting the signal. This causes Rayleigh fading. Thestatistical model of this standard is a distributionknown as the Rayleigh distribution. Rayleigh fadingwith strong line of sight content is said to have aRician distribution. In digital radio communications(such as GSM) can cause errors and multipath affectthe quality of communications. The errors are due tointer-symbol interference (ISI). Equalizers are oftenused to correct the ISI. Alternatively, techniques canbe used such as orthogonal frequency divisionmodulation (OFDM) and RAKE receivers.2. MIMO-OFDMIn radio, multiple-input and multiple-output, or MIMO, is the use of multiple antennas atboth the transmitter and receiver to improvecommunication performance. The terms input andoutput refer to the radio channel carrying the signal,not to the devices having antennas. MIMOtechnology has attracted attention in wirelesscommunications, because it offers significantincreases in data throughput and link range withoutadditional bandwidth or increased transmit power. Itachieves this goal by spreading the same totaltransmit power over the antennas to achieve an arraygain that improves the spectral efficiency (more bitsper second per hertz of bandwidth) and/or to achievea diversity gain that improves the link reliability(reduced fading). Because of these properties,MIMO is an important part of modern wirelesscommunication standards such as IEEE 802.11n(Wi-Fi), 4G, WiMAX etc.MIMO can be sub-divided into three maincategories, precoding, spatial multiplexing or SM,and diversity coding.2.1 PrecodingPrecoding is multi-stream beamforming, inthe narrowest definition. In more general terms, it isconsidered to be all spatial processing that occurs atthe transmitter. In (single-stream) beamforming, thesame signal is emitted from each of the transmitantennas with appropriate phase and gain weightingsuch that the signal power is maximized at thereceiver input. The benefits of beamforming are toincrease the received signal gain, by making signalsemitted from different antennas add upconstructively, and to reduce the multipath fadingeffect. In line-of-sight propagation, beamformingresults in a well defined directional pattern.
  2. 2. Prof. Shivendra Singh, Prof. Vikas Gupta, Shiv kumar Yadav / International Journal ofEngineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.946-949947 | P a g eHowever, conventional beams are not a goodanalogy in cellular networks, which are mainlycharacterized by multipath propagation. When thereceiver has multiple antennas, the transmitbeamforming cannot simultaneously maximize thesignal level at all of the receive antennas, andprecoding with multiple streams is often beneficial.Note that precoding requires knowledge of channelstate information (CSI) at the transmitter and thereceiver.Figure 1: Precoding procedure in MIMO-OFDM2.2 Spatial multiplexingSpatial multiplexing requires MIMOantenna configuration. In spatial multiplexing, ahigh rate signal is split into multiple lower ratestreams and each stream is transmitted from adifferent transmit antenna in the same frequencychannel. If these signals arrive at the receiverantenna array with sufficiently different spatialsignatures and the receiver has accurate CSI, it canseparate these streams into (almost) parallelchannels. Spatial multiplexing is a very powerfultechnique for increasing channel capacity at highersignal-to-noise ratios (SNR). The maximum numberof spatial streams is limited by the lesser of thenumber of antennas at the transmitter or receiver.Spatial multiplexing can be used without CSI at thetransmitter, but can be combined with precoding ifCSI is available. Spatial multiplexing can also beused for simultaneous transmission to multiplereceivers, known as space-division multiple accessor multi-user MIMO, in which case CSI is requiredat the transmitter.[9] The scheduling of receiverswith different spatial signatures allows goodseparability.Figure 2: Spatial multiplexing in MIMO-OFDM2.3 Diversity CodingDiversity Coding techniques are used when there isno channel knowledge at the transmitter. In diversitymethods, a single stream (unlike multiple streams inspatial multiplexing) is transmitted, but the signal iscoded using techniques called space-time coding.The signal is emitted from each of the transmitantennas with full or near orthogonal coding.Diversity coding exploits the independent fading inthe multiple antenna links to enhance signaldiversity. Because there is no channel knowledge,there is no beamforming or array gain from diversitycoding. Diversity coding can be combined withspatial multiplexing when some channel knowledgeis available at the transmitter.Figure 3: Complete Block Diagram of MIMO-OFDM System [1]3. The Rayleigh FadingRayleigh fading is a statistical model forthe effect of a propagation environment ona radio signal, such as that used by wireless devices.Rayleigh fading models assume that the magnitudeof a signal that has passed through sucha transmission medium (also calleda communications channel) will vary randomly,or fade, according to a Rayleigh distribution theradial component of the sum of twouncorrelated Gaussian random variables. Rayleighfading is viewed as a reasonable modelfor tropospheric and ionospheric signal propagationas well as the effect of heavily built-up urban environments on radio signals. Rayleighfading is most applicable when there is no dominantpropagation along a line of sight between thetransmitter and receiver.
  3. 3. Prof. Shivendra Singh, Prof. Vikas Gupta, Shiv kumar Yadav / International Journal ofEngineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.946-949948 | P a g eRayleigh fading is a reasonable model when thereare many objects in the environment that scatter theradio signal before it arrives at the receiver.The central limit theorem holds that, if there issufficiently much scatter, the channel impulseresponse will be well-modelled as a Gaussianprocess irrespective of the distribution of theindividual components. If there is no dominantcomponent to the scatter, then such a process willhave zero mean and phase evenly distributedbetween 0 and 2π radians. The envelope of thechannel response will therefore be Rayleighdistributed.Calling this random variable R, it will havea probability density function:𝑝 𝑅 𝑟 =2𝑟𝛺𝑒−𝑟2/𝛺, 𝑟 ≥ 0Were Ω = E(R2).Often, the gain and phase elements of a channelsdistortion are conveniently represented as a complexnumber. In this case, Rayleigh fading is exhibited bythe assumption that the real and imaginary parts ofthe response are modeled by independent andidentically distributed zero-mean Gaussianprocesses so that the amplitude of the response is thesum of two such processes [9].4. Performance SimulationComputer simulations are done to simulateSNR vs. BER performance of MIMO-OFDM fordifferent fading channels and noise conditions,different number of subcarriers and to analyze theeffect of number of users in BER. To make theresults more useful, the results are generated forvarying number of users and for different number ofsubcarriers. Throughout the simulation, theinformation symbol is BPSK modulated at thetransmitters and detected by using the maximumlikelihood method in the demodulation at thereceiver. A cyclic prefix is added to protect thesymbol. Walsh codes are chosen as the spreadingcodes of the system. The simulation codes arewritten for MATLAB, and simulated on Pentiumclass processor.5. Simulated ResultsAll results are calculated for 104bits oftransmission, the length of spreading code is sameas number of sub-carriers and results are collectedfor each SNR step changing from 1 to 50 dB with astep size of 1 dB. For the Rayleigh channel fourpaths are considered.Figure 4.1: SNR Vs BER for two user 4 sub-carriers.Figure 5.2: SNR vs BER for two users 8 sub-carriers.Figure 5.2: SNR vs BER for two users 16 sub-carriers.6. ConclusionSimulation results shows that the increasein sub-carriers increases the effects of multipathfading, as the comparison in figure 5.1 resultssignificant reduction on BER curve with higher sub-carriers (from 4 to 16). The results of Matlabsimulation show the performance of 802.11nwireless system in Raleigh channel environment.So the simulated of this paper can be applied to
  4. 4. Prof. Shivendra Singh, Prof. Vikas Gupta, Shiv kumar Yadav / International Journal ofEngineering Research and Applications (IJERA) ISSN: 2248-9622 www.ijera.comVol. 3, Issue 3, May-Jun 2013, pp.946-949949 | P a g eanalyze many systems in the advanced wirelesscommunication.References[1] Yoon Hyun Kim and Jin Young Kim“Performance Comparison of 802.11nSystem with WLAN Channel Model”,Communications and InformationTechnology, 2009. ISCIT 2009. 9thInternational Symposium on 28-30 Sept.2009.[2] D. Love, R. Heath, V. Lau, D. Gesbert, B.Rao and M. Andrews, An overview oflimited feedback in wirelesscommunication systems, IEEE Journal onSelected Areas Communications, vol 26,pp. 1341–1365, 2008.[3] L. Zheng and D. N. C. Tse (May 2003)."Diversity and multiplexing: Afundamental tradeoff in multiple-antennachannels". IEEE Trans. Inf. Th. 49 (5):1073–1096.[4] F. Adachi, D. Garg, S. Takaoka, and K.Takeda, “Broadband CDMA techniques,”Wireless Communications, IEEE [see alsoIEEE Personal Communications], vol. 12,no. 2, pp. 8–18, April 2005.[5] A. Jamalipour, T. Wada, and T. Yamazato,“A tutorial on multiple access technologiesfor beyond 3G mobile networks,”CommunicationsMagazine, IEEE, vol. 43,no. 2, pp. 110–117, Feb. 2005.[6] S. Zhou, G. B. Giannakis, and C. L.Martret, “Chip-interleaved block-spreadcode division multiple access,”Communications, IEEE Transactions on,vol. 50, no. 2, pp. 235–248, Feb 2002.[7] M. Ma, Y. Yang, H. Cheng, and B. Jiao,“A capacity comparison between MIMO-OFDMand CP-CDMA,” VehicularTechnology Conference, 2006. VTC-2006Fall. 2006 IEEE 64th, pp. 1–4, Sept.2006.[8] D. Gesbert, M. Kountouris, R. W. Heath,Jr., C.-B. Chae, and T. Sälzer, “Shifting theMIMO Paradigm: From Single User toMultiuser Communications,” IEEE SignalProcessing Magazine, vol. 24, no. 5, pp.36–46, Oct. 2007[9] http://en.wikipedia.org/