a spatial modulation based ber analysis of mimo system under rayleigh fading channel using stbc...

8/9/2019 A Spatial Modulation based BER analysis of MIMO System under Rayleigh Fading Channel using STBC codes and Complex Wavelet Transform

1/12

56 | International Journal of Computer Systems, ISSN-(2394-1065), Vol. 01, Issue 02, November, 2014

International Journal of Computer Systems (ISSN: 2394-1065), Volume 01 – Issue 02, November, 2014

Available at http://www.ijcsonline.com/

A Spatial Modulation based BER analysis of MIMO System under Rayleigh

Fading Channel using STBC codes and Complex Wavelet Transform

AVipul Ray Gaur,

BAshish Parikh

ȦDigital Communication Engineering, Mandsaur Institute of Technology, Mandsaur (M.P), IndiaḂElectronics & Communication Engineering, Mandsaur Institute of Technology, Mandsaur (M.P), India

Abstract

Because of the enormous capacity upsurge a MIMO systems offer; such systems gained a l ot of interest in mo bile

communication research. One indispensable problem of t he wireless channel is fading, which occurs as the s ignal

follows multiple paths between transmitter and receiver antennas. Fading can be mitigated by diversity, which means

that the infor mation is transmitted not only once but several times, hoping that at least one of the r eplicas will notundergo severe fading. There are various coding methods, a main issue in all thes e schemes is the exploitation o f

redundancy to achieve hig h reliability, high spectral efficiency and high performance gain for MIMO-OFDM systems

earlier. In this paper, w e introduce an orthogonal spatial division multiplexing in which we divide the central signal

streams into both time and fr equency. Also to increase the spatial diversity we introduce spatial modulation along withSTBC for our new MI MO-OSDM. Experimental results show that pr oposed system outperform the exis ting MIMO-

OFDM system in terms of performance measure for various modulation schemes.

Keywords: Multiple Input mu ltiple output ( MIMO) system, Orthogonal Spatial Division Multiplexing ( OSDM), Space

Time Block Coding (STBC), spatial modulation, 4G wireless communications.

I. I NTRODUCTION

High spectral efficiency and high transmissionrate are the challenging requirements of future wireless

broadband communications. In a multipath wirelesschannel environment, the use of Multiple Input MultipleOutput (MIMO) systems leads to the accomplishment ofhigh data rate transmission without escalating the totaltransmission power or bandwidth [1]. Multiple-InputMultiple-Output antenna systems are a ty pe of spatialdiversity. An effective & realistic way of approachingthe capacity of MIMO wireless channels is t o utilizespace-time block coding in which data is coded throughspace & time to improve the reliability of thetransmission, as redundant copies of the original data are

broadcasted ov er independent fading channels [2, 3].Then all th e signal copies are collected at the receiverend in a best possible way to extort as much information

from each of them as possible. In practice, wirelesscommunications channels are time varying or frequencyselective particularly for broadband & mobileapplications. To deal with these challenges, a promisingamalgamation has been exploited, namely, MIMO withOrthogonal Frequency Division Multiplexing (OFDM),MIMO-OFDM, which has previously been adopted for

present & future broadband communication standardssuch as LTE or WiMax [5-9].

OFDM can diminish the effect of frequency selectivechannel. This is because OFDM is a multi-carriertransmission scheme, which divides the existingspectrum into many carriers, each on e of them being

modulated by a low -rate data stream. One popularcombination of MIMO & OFDM is th e STBC-OFDM.

Furthermore, this work is encouraged from such STBC-OFDM system to build up an orthogonal spatial divisionmultiplexing system. In STBC coding is applied acrossmultiple OSDM blocks to improve the system

Performance inherent in MIMO-OFDM system. Thecoding allocates symbols along different transmitantennas & time slots. In this context, the STBC-OSDMsystem is one of most capable system configurations thatis adopted for 4th generation mobile systems [10].

Figure 1: Example of 4x2 MMO (Multiple InputMultiple Output)

The transmission of radio waves through theatmosphere including the ionosphere is not an easy

phenomenon to model. Atmospheric propagation canshow a wide variety of behaviours based on the aspectslike frequency, bandwidth of the signal, and types ofantennas utilized, terrain & weather conditions. Whenthere is n o fading, the channel can be supposed to beadditive. If the samples are independent of each otherthe additive noise is referred to as ‘white’ & then theyare correlated are known as ‘colored’. The

straightforward communication channel model is theAdditive White Gaussian Noise model under which the


2/12

Vipul et al A Spatial Modulation based BER analysis of MIMO System under Rayleigh Fading Channel using STBC codes andComplex Wavelet Transform

57 | International Journal of Computer Systems, ISSN-(2394-1065), Vol. 01, Issue: 02. November, 2014

signal is exaggerated only by a constant attenuation. Inwireless communication channels there will be morethan one path in which the signal can travel amid thesource & destination. The presence of these paths is dueto atmospheric reflections, refractions & scattering. In a

multipath fading environment if a lin e of sight (LOS)component is present then the channel is known as aRician channel. On the other hand if there is no LOScomponent then the channel will be referred as theRayleigh fading channel.

A. Introduction to fourth generation of communication

system

The first-generation (1G) radio systems put awayanalog communication schemes to transmit voice overradio, such as A dvanced Mobile Phone Services(AMPS), the Nordic Mobile Telephone (NMT) scheme,& the Total Access Communication System (TACS),which were developed in the 1970s & 1980s. The 2G

systems were accumulated in the 1980s & 1990s, &featured the execution of digital technology, such asGlobal System for Mobile Communications (GSM),Digital-AMPS (D-AMPS), code-division multipleaccess (CDMA), & personal digital cellular (PDC);among them GSM is th e mostly successful & widelyused 2G sy stem. 3G mobile technologies offer userswith high-data-rate mobile access, which developedrapidly in the 1990s & is still budding today.

The three main radio air limit standards for 3G arewideband CDMA (WCDMA), time-divisionsynchronous CDMA (TD-SCDMA), & CDM A 2000.The transmitted data rate of 3G is up to 144 kb/s for

high-mobility traffic, 384 kb/s for low-mobility traffic,& 2 Mb/s in good condition. However, there are tworestrictions with 3G. One is the tricky expansion to veryhigh data rates such as 100 Mb/s with CDMA due tosevere interference between services. The other is th edifficulty of providing a phase of multirate services, allwith different quality of service (QoS) & performancerequirements, due to the restrictions required on the corenetwork by the air i nterference standard.This design isencouraged by the growing demand for broadbandInternet access. The challenge for wireless broadbandaccess lies in providing an analogous quality of service(QoS) for similar cost contrasting wire line technologies.

B.

Principles of space-time (MIMO) systemsConsider the multi-antenna system diagram shown in

Figure 2. A compressed digital source in the form of a binary data s tream which is supplied to a s implifiedtransmitting block encompassing the functions of errorcontrol coding & (possibly joined with) mapping tocomplex modulation symbols (quaternary phase-shiftkeying (QPSK), M-QAM, etc.). The last producesseveral separate symbol streams which varies fromindependent to partially redundant to fully redundant.Each of them is then mapped onto one of the multipleTX antennas. Mapping can includes linear spatialweighting of the antenna elements or l inear antenna

space – time pre-coding. After upward frequencyconversion, filtering & amplification, the signals are broadcasted into the wireless channel. At the receiver,

the signals are captured perhaps by multiple antennas &demodulation & demapping operations are performed torecuperate the message. The level of intelligence,complexity, & a pr iori channel knowledge used inselecting the coding & antenna mapping algorithms can

differ a great deal depending on the application. Thisdetermines the class & performance of the multi-antennasolution that is implemented.

Simple linear antenna array combining can present a m ore reliable communications link in the presence of unfavourable propagation conditions such asmultipath fading & interference. A chief concept insmart antennas is th at of beam forming by which oneincreases the average signal-to-noise ratio (SNR)through focusing energy into desired directions, in eithertransmit mode or receiver mode. Indeed, if one estimatesthe reaction of each antenna element to a given desiredsignal, & possibly to in terference signal(s), one can

optimally mingle the elements with weights chosen as afunction of each element response. One can then exploitthe average desired signal level or diminish the level ofother components whether noise or co-channelinterference.

Another dominant effect of smart antennaslies in the concept of spatial diversity. In the existence ofrandom fading caused by multipath propagation, the

probability of losing the signal fade away exponentiallywith the number of decor related antenna elements beingused. A major concept here is th at of diversityorderwhich is defined by the number of decor related spatial

branches accessible at the transmitter or receiver end.

When combined together, leverages of smart antennasare shown to enhance the coverage range versus qualitytrade-offs offered to the wireless user.

As subscriber units (SU) are steadilyevolving to become complicated wireless Internet accessdevices rather than just pocket telephones, the stringentsize & complexity constraints are becoming somewhatmore relaxed. This constructs multiple antenna elementstransceivers a possibility at both sides of the link, eventhough pushing much of the processing & c ost to thenetwork’s side (i.e., BTS) still makes engineering sense.Clearly, in a MIMO link, the advantages of conventionalsmart antennas are reserved since the optimization of the

multi-antenna signals is carried out in a larger space,thus providing extra degrees of freedom. In particular,MIMO systems can offer a joint transmit-receivediversity gain, and array gain upon coherent combiningof the antenna elements.

Figure 2: Space-time (MIMO) systems


3/12



C. Transmission over MIMO systems

Although the information theoretical analysis can be bootstrapped to encourage receiver architectures (as wasdone, e.g., in [1], [2]), it usually carries a drawback inthat it does not reflect the performance attained by actual

transmission systems, since it on ly provides an upper bound recognized by algorithms/codes with anunlimited complexity or latency. The development ofalgorithms with a reasonable BER

performance/complexity compromise necessitatesrealizing the MIMO gains in practice. H ere, wesummarize different MIMO transmission schemes, givethe instinct behind them, and evaluate their performance.

D. General Principles

Current transmission techniques over MIMOchannels characteristically fall into two classes: data ratemaximization or diversity maximization schemes,although there has been a few effort towards unificationin recent times. The first kind focuses on enhancing theaverage capacity behaviour. For exam ple, in theexample shown in Fig, the aim is just to perform spatialmultiplexing as w e transmit as m any independentsignals as we have antennas for a specific error rate (or aspecific outage capacity [2]).

More usually, however, the individual streamsshould be encoded mutually in order to guardtransmission against errors caused by channel fading &noise and also interference. This leads to a second sort ofapproach in which one tries to cu rtail the outage

probability, or equivalently exploits the outage capacity.

E.

Structure of AssessmentThe association steps of this paper is as follows. The

Preliminary Section ends with a concise introduction ofMIMO systems & its necessity in today’scommunication. The part A,B & C in introduction showsa brief description about fourth generation ofcommunication, ideology of MIMO system &transmission over multiple input multiple output system.

Section II,explains a common review & relatedwork of different coding & multiplexing techniques inmultiple antenna system,many techniques have been

proposed for the MIMO systems which are classified inthis section.

Section III provides the information about thefundamental problem definition & proposedmethodology. This section is further sub-classified intonumerous subsections like spatial modulation, spatialdivision multiplexing, space time coding scheme.

Section IV gives information about the simulationresults; it also shows some comparative graphs which

proved that the proposed approach surmount thetraditional approach.

Section V shows the observations, discussion &tabular comparison of different researches reviewed inearlier sections & a g eneral conclusion of the paper,

regarding review is presented.

I. R ELATED WORK

With the speedy improvement in wirelesscommunications & the decreased cost of communicationdevices, wireless networks have become denser &denser while bandwidth efficiency becomes more &

more important. It is common to consider that multiplecommunication devices conduct transmission &reception jointly in a distributed process.

Employing multiple-input multiple-output (MIMO)in wireless communication systems has been proven to

present plenty of benefits in both increasing the systemcapacity and stea diness of reception in rich scatteringatmosphere [11, 12]. To take benefit of these a space-time block coding (STBC)-oriented diversity scheme has

been usually adopted in future wireless communicationstandards [13], for example 3GPP LTE, WiMax, etc.The STBC technique was originally proposed byAlamouti in [14], achieves transmit diversity exclusive

of channel information. Although Alamouti’s STBC wasinitially designed for two transmit antennas & onereceive antenna, this scheme has been generalized byTarokh in [15] & enlarged to th e system for fourtransmit antennas.

A space-time block coding (STBC) scheme wasoriginally anticipated by Alamouti as an ef fectivetechnique to achieve a t ransmit diversity gain [16].Recently, increasing demands for high data rate wirelesscommunication services requires data transmissions overwideband channels. The combination of STBC alongwith OFDM is deem ed to be a promising solution forcombating frequency-selective fading [17]. For both

single carrier & multi-carrier transmission systems, theAlamouti scheme performs well if the channel is time-invariant over two successive symbol durations. Theimpact of a time-varying fading channel on the

performance of Alamouti transmit technique has beenexplored in [18] for a single-carrier system & in [19] foran OFDM sy stem. In both the papers, the spatialcorrelation amid the time-varying multipath Rayleighfading sub-channels has not been taken into account.However, it h as been revealed in [20] by simulationsthat the performance of a STBC-OFDM scheme dependsnot only on temporal correlation but also on spatialcorrelation.

Space time Block Coding is a set of realistic signaldesign techniques aimed at approaching the informationtheoretic capacity bounds of Multiple-Input Multiple-Output (MIMO) channels. Since the initial work ofAlamouti [21], space-time coding has been a r apidgrowing field of research. In the last decade, numerouscoding techniques have been proposed. These includesorthogonal (OSTBCs) [21] – [23], quasi-orthogonal(QOSTBCs) [24], [25] & non-orthogonal STBCs(NOSTBCs) [26]

The revolutionary works on the cooperative diversityaddress information-Theoretical aspects of cooperativenetworks examining achievable rate regions & outage

probabilities. The outage analysis in [2 0] relies on therandom coding argument & demonstrates that full


4/12



spatial diversity can be achieved employing such a richset of codes. Laneman et al . [27] proposes the use of“conventional” orthogonal space-time block coding(STBC) in a “distributed” manner for realisticimplementation of user cooperation. Nabar et al. [28],

[29] evaluates distributed STBC operating in anamplify-&-forward (AF) mode through the derivation of

pairwise error probability (PEP) terms. They show thatthe original design criterion for conventional STBC (i.e.,rank & determinant criteria) still apply for the design ofdistributed STBC schemes under the supposition thatappropriate power control rules are used at rel ays. Avariety of equalization schemes, which were originallydeveloped for single-input single-output (SISO) systemscan be useful for distributed STBC as well. However,uncomplicated extensions result in an excessivecomplexity mainly for higher-order modulation schemesand/or long channel memory [30]. Among theequalization schemes studied for STBC, three of these

deserve particular attention due to their low-complexity,specifically time-reversal STBC (TR-STBC) [31],single-carrier frequency-domain equalization for STBC(SC-STBC) [32], & orthogonal frequency divisionmultiplexed (OFDM)-STBC [33].

An overview & comparison of these schemes can befound in [34] – [36]. In this paper, author extend the threeabovementioned equalization schemes to a relay-assistedtransmission scenario, carefully utilizing thefundamental Orthogonality of distributed STBC. Mostof the existing literature on cooperative diversityassumes frequency-flat fading channel. Together withthe conference version of this paper [37], there have

been only a f ew sporadic results accounts on the broadband cooperative transmission techniques forfrequency-selective channels. Yatawatta et al. [38]

proposes an O FDM cooperative diversity systemassuming AF relaying & der ive upper bounds on thechannel capacity. They also examines the achievablediversity order for distributed cooperative OFDMsupposing a non-fading inter-user channel. Barbarossa etal. [39] examines the performance of a distributedOFDM-STBC technique through a sim ulation studyconsidering both AF & d ecode-and-forward (DF)relaying. Building upon their preceding work ondistributed STBC [40], Anghel et al . [41] studied the

performance of a relay-assisted uplink OFDM-STBCscheme & derive an expression for the symbol error probability assuming DF with no error propagation. Tothe best of our knowledge, the conference version of thecurrent paper [37] is the first effort to investigate TR-STBC & SC-STBC in a relay-assisted transmissionscenario (and OFDM-STBC along with the abovementioned papers [38], [39], [41]).

Fu Hong-liang et al., h as anticipated a novel cyclicspace time block code (STBC) scheme in MIMOCDMA system. In modern wireless communicationsmultiple input & multiple output (MIMO) is a v ery

promising scheme. MIMO functions are mainlydiversity, beam forming. And the diversity can beachieved by means of space-time coding (STC). STChas two ways one is space-time trellis codes (STTC) &

the other one is space-time block codes (STBC). STBC provides diversity with less encoding & decodingdifficulty. STBC employs linear processing at thereceiver side. In this cyclic STBC first the input symbolsare broken into blocks, then each block has M symbols

& these symbols are circularly encoded into M groups.Valipour et al., has projected that space-time block

codes for Multi-carrier code-division-multiple-access(MCCDMA) systems [42]. Now a day there is v astdemand for wideband wireless networks, especially forwireless sensor & adhoc networks.

Min Shi et al., has proposed permutation spreading by utilizing STBC code matrix, for MIMO-CDMAsystems. Assigning different spreading sequences fordifferent antennas is k nown as permutation spreading.The signal can be modulated with the help of BPSK orQPSK then it is sp read with the different spreadingsequences. As compared to the conventional & othermethods this method provides better performance andenhanced bit error rate [43].

II. PROPOSED MIMO SYSTEM

The figure below shows the transmitter side blockdiagram of proposed scheme

Figure 3: Shows the transmitter side model of proposed

work, we have to s end only constellation points with

respect to antenna number.

Input Data

Spatial Modulation

Data encoding using

Space time Block codes

Multiplexing using our orthogonal

spatial division multiplexing

Channel with Fading Environment

This Spatial Division is done using

Discrete Wavelet transform


5/12



Figure 4: Shows the receiver side model for the

proposed work.Perfect channel estimation is done to find best suitedchannel. Also, Channel consists with Rayleigh FadingEnvironment.

Furthermore, this paper also explains a detailed viewof technologies used in the proposed work as follow:

III. SPATIAL MODULATION

Spatial modulation (SM) is a r ecently developedtransmission technique that uses multiple antennas. The

basic idea is to map a block of information bits to twoinformation carrying units:

A symbol that was chosen f rom a co nstellationdiagram and

A unique transmit antenna number that was chosenfrom a set of transmit antennas.

The use of the transmit antenna number as aninformation-bearing unit increases the overall spectralefficiency by the base-two logarithm of the number oftransmit antennas. At the receiver, a maximum receiveratio combining algorithm is u sed to retrieve thetransmitted block of information bits. Here, we applySM to orthogonal spatial division multiplexing (OSDM)transmission.

In general, any number of transmit antennas and anydigital modulation scheme can be used. Theconstellation diagram and th e number of transmitantennas determine the total number of bits to b etransmitted on each sub-channel at each instant.

The combination of BPSK and f our transmitantennas in this illustration in a total of three information

bits to be transmitted on each sub-channel. Instead, fourquadrature-amplitude modulation (QAM) and twotransmit antennas can be used to transmit the samenumber of information bits, as shown in Table below.The number of bits that can be transmitted on each

OSDM sub-channel for a system that uses a Q AMconstellation diagram of size M (m = log2(M)) and Nttransmit antennas.

(1)This shows that the constellation diagram and th e

number of transmit antennas can be traded off for anynumber of transmitted information bits. In addition, SMincreases the spectral efficiency by the base-twologarithm of the total number of transmit antennas.

In SM, a block of any number of information bitsis mapped into a constellation point in the signal domainand a constellation point in the spatial domain. At eachtime instant, only one transmit antenna of the set will beactive. The other antennas will transmit zero power.Therefore, ICI at th e receiver and th e need tosynchronize the transmit antennas are completelyavoided. At the receiver, maximum receive ratiocombining (MRRC) is used to estimate the transmitantenna number, after which the transmitted symbol isestimated. These two estimates are used by the spatialdemodulator to retrieve the block of information bits.

TABLE I. SM MAPPING TABLE

b/symbol/subchannel

IV. ORTHOGONAL SPATIAL DIVISION

MULTIPLEXING

In our work the spatial division multiplexing is performed using discrete wavelet transform as f astFourier transform used in orthogonal frequency division

multiplexing can split the signal into frequency signalonly. The transform of a signal is just another form ofrepresenting the signal. It does not change theinformation content present in the signal. The WaveletTransform provides a time-frequency representation ofthe signal. It was developed to overcome the shortcoming of the Short Time Fourier Transform (STFT),which can also be used to analyze non-stationary signals.While STFT gives a constant resolution at allfrequencies, the Wavelet Transform uses multi-resolution technique by which different frequencies areanalyzed with different resolutions.

A wave is an oscillating function of time or space

and is pe riodic. In contrast, wavelets are localizedwaves. They have their energy concentrated in time or

Output Data

Data decoding using

Space time Block codes

De-multiplexing using our orthogonalspatial division multiplexing

Perfect Channel Estimation Data from Channel


6/12



space and are suited to analysis of transient signals.While Fourier Transform and S TFT use waves toanalyse signals, the Wavelet Transform uses wavelets offinite energy.

The wavelet analysis is d one similar to the STFTanalysis. The signal to be analyzed is multiplied with awavelet function just as it is multiplied with a windowfunction in STFT, and then the transform is co mputedfor each segment generated. However, unlike STFT, inWavelet Transform, the width of the wavelet functionchanges with each spe ctral component. The WaveletTransform, at h igh frequencies, gives good timeresolution and poor frequency resolution, while at l owfrequencies, the Wavelet Transform gives goodfrequency resolution and poor time resolution.

OSDM is a m ulti-carrier modulation (MCM)technique. The MCM scheme as the name implies is amodulation technique in which multiple carriers are usedfor modulating the information signals. It is a su itablemodulation used for high data rate transmission and isable to mitigate the effects of inter symbol interference(ISI) and inter carrier interference (ICI). In an SFDMscheme, a huge number of orthogonal, overlapping,narrow band su b-channels, transmitted in parallelsubdividing the existing transmission bandwidth. Theoverlapping of the sub-channels do not create any

problems since the peak of one subcarrier occurs atzeroes of other subcarriers. Orthogonality between thedifferent subcarriers is achieved by using CWT. Figure6 depicts the spectrum for 5 different frequencies where, p

is the subcarrier spacing. We clearly see that for

the red and green peaks the dashed lines cross from thezero crossings of the other carriers [29].

Figure 5: Frequency-time Spectrum for 5 Orthogonal

Subcarriers.

V. TRANSCEIVER OF PROPOSED OSDM SYSTEM

The general block diagram of an OSDM transceiverhas been shown in Figure 7. The digital data if first up-converted by a modulation scheme and then the symbolsare put into parallel streams that the CWT block is goingto work on. After ICWT is taken an appropriately sized

cyclic prefix is a ppended at the end of the signal.Finally, the signal is sent into the channel. This channelis either the AWGN or the flat fading Rayleigh channel.

At the receiver the first task is to rem ove the cyclic prefix and then apply CWT. Afterwards, the parallelstreams are serialized and then the symbols put throughthe demodulator for obtaining the input source data.

Figure 6: OSDM Transmitter- Receiver Block DiagramOnce the cyclic prefix is removed taking IFFT of the

signal is e quivalent to multiplying the constellation points by sinusoids whose frequencies are equal to thefrequency of a car rier signal and th en summing these

products.

The complex wavelet transform (CWT) is acomplex-valued extension to th e standard discretewavelet transform (DWT). It is a two-dimensional wavelet transform which provides multi-resolution, sparse representation, and usefulcharacterization of the structure of an image. Further, it

purveys a h igh degree of shift-invariance in itsmagnitude. However, a drawback to th is transform is

that it is exh ibits (where is the dimension of thesignal being transformed) redundancy compared to aseparable (DWT).

VI. SPACE-TIME CODING

Space-Time Codes (STCs) have been implementedin cellular communications as well as in wireless localarea networks. Space time coding is performed in bothspatial and temporal domain introducing redundancy

between signals transmitted from various antennas atvarious time periods. It can achieve transmit diversityand antenna gain over spatially un-coded systemswithout sacrificing bandwidth. The research on STCfocuses on improving the system performance byemploying extra transmit antennas, in general, the designof STC amounts to finding transmit matrices that satisfycertain optimality criteria. Constructing STC, researcherhas to tr ade-off between three goals: simple decoding,

minimizing the error probability, and m aximizing theinformation rate. The essential question is: How can wemaximize the transmitted date rate using a simple codingand decoding algorithm at the same time as the bit error

probability is minimized?

A. Space-Time Coded Systems

Let us consider a space-time coded communicationsystem with nt transmit antennas and nr receiveantennas. The transmitted data are encoded by a space-time encoder. At each time slot, a block of m· n t binaryinformation symbols

(2)

Demodulation

DigitaModultion ICW

AWGN/ Rayleigh Fading Channel

CPR CW P/S

S/P CPSourceInfo


7/12



are fed into the space-time encoder. The encodermaps the block of m binary data in to ntmodulationsymbols from a signal set of constellation M = 2

m points.

After serial-to-parallel (SP) conversion, the nt symbols

(3)

are transmitted simultaneously during the slot t from

nt transmit antennas. Symbol

g

, istransmitted from antenna i and al l transmitted symbolshave the same duration of T sec. The vector in equationabove is called a space-time symbol and by arrangingthe transmitted sequence in an array a of nt × N s pace-time code-word matrix.

(4)Can be defined as The i-th row

is th e data sequence transmitted

from the ith transmit antenna and the jthcolumn is the space-time symbol

transmitted at time j,1 to N.

As already explained, the received signal vector can be calculated as

Y = HS + N (5)The MIMO channel matrix H co rresponding to

nttransmit antennas and nr receive antennas can be

represented by an nr × nt matrix:

(6)Where the ji-th element denoted by h

t j,i, is the fading

gain coefficient for the path from transmit antenna i toreceive antenna j. W e assume perfect channelknowledge at the receiver side and the transmitter has noinformation about the channel available at thetransmitter side. At the receiver, the decision metric is

computed based on the squared Euclidian distance between all hypothesized receive sequences and theactual received sequence:

(7)

Given the receive matrix YS with smallest Euclidiandistance d

2 H .

There are several distributions used to m odel thefading statistics. The most commonly used distributionfunctions for the fading envelopes are Rice, Rayleighand Nakagami-m. Rayleigh is a sp ecial case of

Nakagami-m, when m equals one. The fading models

are related to some physical conditions that determinewhat distribution that best describe the channel.

The Rayleigh distribution assumes that there are asufficiently large number of equal powermultipath components with different andindependent phase.

The Nakagami one distribution equals the Rayleigh

distribution above. It is a general observationthat an increased m value corresponds to alesser amount of fading and a str onger direct

path.

In Figure 8, a MIMO 4x4 system with AlamoutiSTBC algorithm is sh own. The MIMO channels areshown in four colors to split them into four groups. Thechoice of a 4x4 MIMO instead of usual 2x1 or 2x2 ismotivated by the necessity of increasing diversity in thespace domain (and th erefore robustness against fadingeffects) together with the spectral efficiency. Nowadays,a 4-element MIMO array can be implemented withaffordable cost and th e yielded performanceimprovement in terms of spectral efficiency may justifysuch an additional (non-prohibitive) cost.

Figure 7: The 4x4 MIMO-STBC system

VII. R ESULTS & DISCUSSION

In this section we will be p resenting the link level performance of STBC and SM coded OSDM u singeither BPSK or QPSK modulation. All simulations have

been carried out using the readily available MATLAB platform and w riting dedicated functions for different parts. The simulation results obtained have been presented in four parts. The first part provides the biterror rate performance for BP SK modulated datatransmitted over a Rayleigh fading channel. This is thenfollowed by a performance analysis of OFDM over theAWGN channel using either BPSK or QPSK

modulation. Third part demonstrates the BER vs. SNRfor Alamouti STBC and Spatial modulation coded datatransmitted over a Rayleigh fading channel withoutusing OSDM. Finally, part four will provide STBC andSM coded OFDM performance when BPSK and QPSKare the preferred modulation and the channel is again theRayleigh fading channel.

Simulations are c arried out in MATLAB R2013b(Version 8.2.0.703), graphical user interface is createdfor the simulation of proposed work on MIMO systems.When there is a direct path between the transmitter andreceiver the channel is usually referred to as the Ricianchannel and when LOS component is missing it will be

referred to as the Rayleigh fading channel. In thissection we demonstrate the BER performance of BPSKmodulated data over a sin gle path Rayleigh fading


8/12



channel. The analytical expression for the BER forBPSK modulated data in a Rayleigh fading channel is

(8)

And for the AWGN channel P bis defined as:

(9)The advantage in multiple antenna schemes is th at

they use a n ew dimension called space in addition totime. Multiplexing gain, antenna gain and diversity gainare three main benefits of MISO and MIMO typesystems. Alamouti scheme is known as the first STBC.It uses two transmit antennas and N r receive antennas.

Alamouti STBC has a u nity rate an d can attain adiversity order of 2* Nr . Spatial modulation (SM) is arecently developed transmission technique that usesmultiple antennas. The basic idea is to m ap a block ofinformation bits to two information carrying units:Asymbol that was chosen f rom a co nstellation diagramandA unique transmit antenna number that was chosenfrom a set of transmit antennas.

SM is g enerally used when no information isavailable about the channel. In SM since two successivetransmitted symbols are encoded into phase differences,then it is p ossible for the receiver to recover thetransmitted information by comparing the phase of thecurrent symbol with that of the previously receivedsymbols.

This section will provide BER analysis for AlamoutiSTBC and SM over slow fading Rayleigh channels. For

both schemes the simulations have been carried outusing two transmit and one receive antenna.

2 4 6 8 10 12 14 1610

-3

10-2

10-1

100

SNR, [dB]

S y m b o l E r r o r P r o b a b i l i t y

Nt=4 QAM

2 4 6 8 10 12 14 1610

-4

10-2

100

SNR, [dB]

B i t E r r o r P r o b a b i l i t y

Nt=4 QAM

Figure 8: Comparison of Bit error probability and

symbol error probability with respect to signal to noise

ratio in case of 4 a ntenna quadrature amplitudemodulation.

2 4 6 8 10 12 14 1610

-3

10-2

10-1

100

SNR, [dB]


Nt=2 QAM

2 4 6 8 10 12 14 1610

-3

10-2

10-1

SNR, [dB]


Nt=2 QAM



ratio in case of 2 a ntenna quadrature amplitude

modulation.

2 4 6 8 10 12 14 1610

-3

10-2

10-1

100

SNR, [dB]


Nt=4 BPSK

2 4 6 8 10 12 14 1610

-3

10-2

10-1

100

SNR, [dB]


Nt=4 BPSK



ratio in case of 4 a ntenna binary phase shift keying

modulation.

2 4 6 8 10 12 14 1610

-3

10-2

10-1

100

SNR, [dB]


Nt=2 BPSK

2 4 6 8 10 12 14 1610

-3

10-2

10-1

100

SNR, [dB]


Nt=2 BPSK



ratio in case of 2 a ntenna binary phase shift keying

modulation.


9/12



2 4 6 8 10 12 14 1610

-3

10-2

10-1

100

SNR, [dB]

S y m

b o l E r r o r P r o b a b i l i t y

Nt=4 QAM

Nt=2 QAM

Nt=4 BPSK

Nt=2 BPSK

2 4 6 8 10 12 14 1610

-3

10-2

10-1

100

SNR, [dB]


Nt=4 QAM

Nt=2 QAM

Nt=4 BPSK

Nt=2 BPSK

Figure 12: Overall Comparison of proposed SM-

STBC-OSDM system for different modulation

schemes and antenna numbers.

I. CONCLUSION& DISCUSSION

In this paper, we first compared the BER performance of 4×1 and 2×1 transmit diversity STBCdata transmission over a Rayleigh fading channel using

both BPSK and QPSK modulation. The communicationsystem used spatial modulation to encode random datasignal to a chieve a h igher transmit diversity. The

proposed multiplexing system using complex wavelettransform we named it as orthogonal spatial divisionmultiplexing which is motivated from orthogonalfrequency division multiplexing performs better inmultiple input multiple output system. Results with

BPSK modulation indicate that using two antennas at thereceiver instead of one will bring approximately an extragain of 9dB at a BER value of 10-4.

Also comparison between 2×1 STBC usingBPSK and 2×1 STBC using QPSK indicate that STBCwith BPSK modulation would be ~4.2 dB better than the2×1 STBC with QPSK for BER value of 10-3. Theseresults indicate that to get a better performance over aRayleigh fading channel MIMO approach would be

better than MISO case and low level modulation should be preferred.

In the second phase of the simulations,transmission of data encoded using STBC and spatialmodulation over a Rayleigh fading channel wascompared. Since the STBC scheme makes use of achannel estimate and spatial modulation does not for

both BPSK and QPSK modulations, the BER performance for STBC was better using spatialmodulated encoded data. This however does not meanthat spatial modulation should not be considered. In factwhen there is high mobility and the channel conditionsare fluctuating rapidly it m ay be d ifficult to obtainestimates for the channel and the detection oftransmitted.

In the third phase of the simulations the transmitdiversity schemes were combined with the proposed

OSDM scheme and STBC-OSDM vs. SM-STBC-OSDM BER performance was obtained over a Rayleigh

fading channel. The usage of a multi-carrier modulationtechnique was seen to further improve the BER resultsobtained when data w as transmitted after encoding bySTBC or SM. For both BPSK and QPSK modulationsthe boost introduced to the BER performance by

combining OSDM with the chosen transmit-diversitytechnique would become more significant after 6dB. Ata BER of 10-3 this difference in gain is around 4.5dB forSTBC OSDM using BPSK and ~6dB for STBC OSDMusing QPSK modulation. Then 2×1 DSTBC and OSDMis used back to back similar behavior is experiencedhowever the BER performances are higher due to thefact that detection is done incoherently.

The improvement in BER performance when OSDMis used mainly comes due to the use of the guardinterval. When the duration of the guard interval isselected larger than the maximum excess delay time ofthe radio channel this will help reduce the inter-symbol

interference in a fading environment and help improvethe BER results. Secondly since OSDM splits a

broadband channel into multiple sub-channels thischanges the behavior of each sub-channel to be flatfading and hence better performance can be observed.

I. FUTURE WORK

The work described herein mainly concentrated onMIMO-OSDM based systems for 4G. However thehigher Generation communication systems must adoptOSDMA, a multi user version of OSDM as th e IMT-Advanced standard dictates. Therefore the future work

will involve simulating OSDMA physical layer alongwith MIMO transmit and receive diversity techniques.

Also some effective channel coding schemes like

Convolutional Coding (CC), Turbo Coding (TC) or

Low Density Parity Check (LDPC) coding could be

employed for providing the flexibility of detecting and

correcting errors that may occur during transmission. Ininformation theory, TCs are a class of high-performance

forward error correction (FEC) codes developed by

Berrou in 1993. Via the use of these TCs performances

that approach the channel capacity are possible. TCs

have found use in 3G mobile communications and

(deep space) satellite co mmunications as well as other

applications where designers seek to ac hieve reliable

information transfer over bandwidth- or latenc y-

constrained communication links in the presence of

data-corrupting noise. A good competitor of TCs is the

LDPC codes, which provide similar performance


10/12

Vipul et al A Spatial Modulation based BER analysis of MIMO System under Rayleigh Fading Channel using STBC codes and

Complex Wavelet Transform


.

TABLE II. TABULAR COMPARIOSON ON SOME SURVEYED LITERATURE

Author Title Summary

ChristophStuder

Energy-Efficient Spectrum Sensing forCognitive Radio Networks

Author investigate an orthogonal frequency-division multiplexing(OFDM)-based downlink transmission scheme for large-scale multi-user(MU) multiple-input multiple-output (MIMO) wireless systems. The use

of OFDM cau ses a h igh peakto- average (power) ratio (PAR), whichnecessitates expensive and power-inefficient radio-frequency (RF)components at the base station. In this paper, author present a noveldownlink transmission scheme, which exploits the massive degrees-of-

freedom available in large-scale MU-MIMO-OFDM systems to achievelow PAR.

Bang Hun Park

Efficient spectrum sensing in cognitive

Radio using energy detection method withnew threshold formulation

In this paper, author propose the Channel sounding scheme which is

made for ideal communication between some application as well as the

short distance of high speed data transmission in MIMO-OFDM system

for Wireless PAN.

Linglong Dai

An energy efficient cooperative spectrumsensing scheme for cognitive radionetworks

In this paper, author propose the time-frequency training OFDM (TFT-

OFDM) transmission scheme for large scale MIMO systems, where eachTFT-OFDM symbol without cyclic prefix adopts the time-domaintraining sequence (TS) and the frequency-domain orthogonal grouped

pilots as the time frequency training information.

The-Hanh Pham”

Energy-efficient spectrum sensing by

optimal periodic scheduling in cognitive

radio networks

In this paper authors consider two-way relaying systems consisting oftwo end users, N1 and N2, which exchange their information with thehelp of a rela y, R. T he three terminals are eq uipped with multiple

antennas.

Yuansheng Jin

Energy-Efficient Distributed SpectrumSensing for Wireless Cognitive Radio

Networks

In this paper, a new interference nulling based channel independent pr ecoding for MIMO-OFDM systems of nt transmit and nr receiveantennas with insufficient cyclic prefix (CP) is proposed.

KarthikMuralidhar

Energy-Efficient Cooperative Spectrum

Sensing by Optimal Scheduling inSensor-Aided Cognitive Radio Networks

In this letter, au thor present the VSSO Kalman channel estimator for

doubly-selective multiple-input multiple-output OFDM (DS -MIMO-OFDM) systems. Unlike the VSSO estimator in a DS -OFDM system,where all the pilot symbols had the same value, the pilot symbols need to

be designed in a sp ecific way to enable the feasibility of a VSSOestimator for a DS-MIMO-OFDM system.

Pierluigi Salvo Rossi

Energy-Efficient Spectrum Sensing and

Access for Cognitive Radio Networks

This paper proposes two low-complexity two-dimensional channel

estimators for MIMO- OFDM systems derived from a joint time – frequency channel estimator. The estimators exploit both time andfrequency correlations of the wireless channel via use of Slepian- basis

expansions. The computational saving comes from replacing a two-dimensional Slepian-basis expansion with two serially concatenated one-dimensional Slepian-basis expansions

Johannes Georg

Klotz

Energy and throughput efficient strategies

for cooperative spectrum sensing incognitive radios

In this paper, author consider a multiple-input-multiple-output –

orthogonal frequency division multiplexing (MIMO-OFDM) downlinkscenario, where each receiving mobile station has quality of servicerequirements, namely minimum rate requirements. For this problem

author propose three heuristic resource allocation algorithms, which havea much lower complexity than the existing optimal solution (opt).

Y. Mlayeh

Cluster-Based Energy Efficient

Cooperative Spectrum Sensing inCognitive Radios

This paper proposes an advanced OFDM-MIMO reconfigurable

architecture that uses an adaptive switching algorithm between diversityand spatial multiplexing. The transmitter blocs’ specifications such as theMIMO technique and the modulation scheme are adjusted according to

the channel state, w hich gives a p ractical cognitive radio strategy. The


11/12




II.

R EFERENCES & ALLUSIONS

[1]

I.E.Telatar, “Capacity of Multi-Antenna Gaussian Channels”,

AT&T Bell Labs,

http://mars.belllabs.com/cm/ms/what/mars/papers/proof, 1995.

[2] G. J. Foschini, M. J. Gans, “On Limits of Wireless

Communications in Fading Environments when Using Multiple

Antennas”, Wireless Personal Communications, vol. 6, pp. 311-

335, March 1998.

[3]

V. Tarokh, N. Seshadri, A. R. Calderbank, “Space-Time

Codes for High Data Rate Wireless Communication: Performance

Criterion and Code Construction”, IEEE Trans. Inform. Theory,

vol. 44, no. 2, pp. 744-765, March 1998.

[4]

Z. Liu, G. B. Giannakis, S. Zhou, B. Muquet, ”Space -time

coding for boradband wireless communications”, WirelessCommunications and Moblie Computing, vol. 1, no. 1. pp. 35-53,

Jan. 2001.

[5]

J. H. Winters, ”On the capacity of radio communication

systems with diversity in a Rayleigh fading environment”, IEEE

Journal on Selected Areas in Communications, pp. 871-878, June

1987.

[6] A. Wittneben, ”A new bandwidth efficient transmit antenna

modulation diversity scheme for linear digital modulation”, IEEE

Int. Conference on Com., vol. 3, pp. 1630 - 1634, Geneva, May

1993.

[7]

V. Tarokh, N. Seshadri, A. R. Calderbank, “Combined Array

Processing and Space-Time Coding”, IEEE Trans. Inform. Theory,

vol. 45, no. 5, pp. 1121 - 1128, May 1999.

[8]

A. Hottinen, O. Tirkkonen, R. Wichman, ”Multi-Antenna

Transceiver Techniques for 3G and Beyond”, John Wiley and Son

Ltd. 2003.

[9]

M. K. Simon, M.-S. Alouini, Digital Communication over

Fading Channel: A Unified Approach to Performance Analysis,

John Wiley &Sohn, 2000.

[10]

T. S. Rappapot, Wireless Communications: Principles and

Practice, Prentice Hall, 1996.

[11]

IE Telatal, Capacity of multiple-antenna Gaussian

channel. European Trans Telecommunication .10.585595 (1999).

doi:10.1002/ett.4460100604

[12]

GJ Foschini, MJ Gans, on limits of wireless

communications in a fading environment when using multiple

antennas. Wireless Personal Communication. 6(3), 311 – 335

(1998). Doi: 10.1023/a: 1008889222784

[13]

3rd Generation Partnership Project, TS36.211 Physical

Channels and Modulation. (2009)

[14] SM Alamouti, A simple transmit diversity technique for

wireless communications. IEEE J S el Areas Communication.

16(8), 1451 – 1458 (1998). doi:10.1109/49.730453

[15]

V Tarokh, H Jafarkhani, AR Calderbank, Space-time

block codes from orthogonal designs.

[16] S. M. Alamouti, “A simple transmit diversity technique

for wireless communications,” IEEE Journal on Select Areas in

Communications, vol. 16, no. 8, pp. 1451 – 1458, Oct. 1998.

[17]

S. Mudulodu and A. Paulraj, “A transmit diversity

scheme for frequency selective fading channels,” in Proc. IEEEGlobal Telecommunications Conference 2000, GLOBECOM

2000, vol. 2. San Francisco, USA, Nov. 2000, pp. 1089 – 1093.

[18]

A. Vielmon, Y. Li, and J. R. Barry, “Performance of

Alamouti transmit diversity over time – varying Rayleigh – fading

channels,” IEEE Trans. On Wire. Communication. vol. 3, no. 5,

pp. 1369 – 1373, Sept. 2004.

[19] D. B. Lin, P. H. Ch iang, and H. J. Li, “Performance

analysis of two – branch transmit diversity block – coded OFDM

systems in time – varying multipath Rayleigh –fading channels,”

IEEE Trans. on Veh. Technol., vol. 54, no. 1, pp. 136 – 148, Jan.

2005.

[20] Y. Ma and M. P¨atzold, “Performance comparison of

space-time coded MIMO-OFDM systems using different wideband

MIMO channel models,” in Proc. 4th IEEE International

Symposium on W ireless Communication Systems, ISWCS 2007.

Trondheim, Norway, Dec. 2007, pp.762 – 766.

[21] S. Alamouti, “A simple transmit diversity technique for

wireless communication, "IEEE J. Sel. Areas Commun., vol. 16,

no. 8, pp. 1451-1458, 1998.

[22]

V. Tarokh, H. Jafarkhani, and A. Calderbank, “Space time

block codes from orthogonal designs," IEEE Trans. Inf. Theory,

vol. 45, no. 5, pp. 744-765, 1999.

[23] G. Ganesan and P. Stoica, “Space-time block codes: a

maximum SNR approach," IEEE Trans. Inf. Theory, vol. 47, no. 4,

pp. 1650-1656, 2001.

system cost- efficiency is performed by the application of the SoftwareDefined Radio (SDR) technology. Based on t he Demmel condition

number criterion, an indicator bit exchange between the transmitter andthe receiver allows selecting the adapted MIMO configuration andimproving the whole system performances.

Md. MasudRana

Energy-efficient cooperative spectrum

sensing with relay switching based ondecision variables for cognitive radio

Author compare the performance of least mean square (LMS) and

recursive least square (RLS) channel estimation (CE) algorithm forMIMO orthogonal frequency division multiplexing (OFDM) systems.The simulation results show that the RLS has better mean square error

(MSE) performance compared with LMS algorithm. The RLS CEalgorithm has better anti-noise as well as tracking ability. But the RLSCE algorithm suffers from higher complexity than LMS CE algorithm.


12/12




[24]

H. Jafarkhani, “A quasi-orthogonal space-time block

code," IEEE Trans. Commun., vol. 49, no. 1, pp. 1-4, 2001.

[25]

A. Boarui and D. Ionescu, “A class of nonorthogonal rate-

one spacetime block codes with controlled interference," IEEE

Trans. Wireless Commun., vol. 2, no. 2, pp. 270-276, 2003.

[26]

H. Jafarkhani, Space-Time Coding: Theory and Practice.

Cambridge University Press, 2005.

[27]

J. N. Laneman and G. W.Wornell, “Distributed space-

time-coded protocols for e xploiting cooperative diversity in

wireless networks,” IEEE Trans. Inf. Theory, vol. 49, no. 10, pp.

2415 – 2425, Oct. 2003.

[28]

R. U. Nabar, H. Boelcskei, and F. W. Kneubhueler,

“Fading relay channels: performance limits and space-time signal

design,” IEEE J. Sel. Areas Commun., vol. 22, pp. 1099– 1109,

Aug. 2004.

[29] R. U. Nabar and H. Boelcskei, “Space-time signal design

for fading relay channels,” in IEEE GLOBECOM, San Francisco,

CA, Dec. 2003.

[30]

A. F. Naguib and N. Seshadri, “MLSE and equalization of

space-time coded signals,” in IEEE Vehicular Technology Conf.

(VTC’00)— Springer, May 2000.

[31]

E. Lindskog and A. Paulraj, “A transmit diversity scheme

for channels with intersymbol inter ference,” in Proc. Int. Conf.

Commun., New Orleans, LA, Jun. 2002.

[32] N. Al-Dhahir, “Single carrier frequency domain

equalization for s pace time block coded transmissions over

frequency selective fading channels,” IEEE Commun. Lett., vol. 5,

no. 7, pp. 304 – 306, Jul. 2001.

[33]

Z. Liu, G. B. Giannakis, A. Scaglione, and S. Barbarossa,

“Block precoding and transmit-antenna diversity for decoding and

equalization of unknown multipath channels,” in Proc. 33rd

Asilomar Conf. Signals, Syst., Comput., Pacific Grove, CA, Nov.

1999.

[34]

N. Al-Dhahir, “Overview and comparison of equalization

schemes for space-time coded signals with application to EDGE,”

IEEE Trans. Signal Process., vol. 50, no. 10, Oct. 2002.

[35] N. Al-Dhahir, M. Uysal, and C. N. Georghiades, “Three

space-time block coding schemes for frequency-selective fading

channels with application to EDGE,” in Proc. IEEE Vehicular

Technology Conf. (VTC’01)— Fall, Oct. 2001, pp. 1834 – 1838.

[36] H. Mheidat, M. Uysal, and N. Al-Dhahir, “Comparative

analysis of equalization techniques for STBC with application to

EDGE,” in Proc. IEEE Vehicular Technology Conf. (VTC’04)—

Spring, Milan, Italy, May 2004.

[37]

H. Mheidat and M. Uysal, “Equalization techniques for

space-time coded cooperative systems,” in Proc. IEEE Vehicular

Technology Conf. (VTC’04) — Fall, Los Angeles, CA, Sep. 2004.

[38] S.Yatawatta and A. P. Petropulu,

“AmultiuserOFDMsystem with user cooperation,” in 38thAsilomar

Conf. Signals, Syst., Comput,, Pacific Grove, CA, Nov. 2004.

[39]

S. Barbarossa and G. Scutari, “Distributed space-time

coding f or multihop networks communications,” in IEEE Int.

Conf. Communications (ICC), Paris, France, Jun. 2004.

[40]

P. A. Anghel and M. Kaveh, “Exact symbol error

probability of a co operative network in a Rayleigh-fading

environment,” IEEE Trans. Wireless Commun., vol. 3, no. 5, pp.

1416 – 1421, Sep. 2004.

[41] PA Anghe, “Relay assisted uplink communication over

frequency-selective channels,” in IEEE Int. Workshop Signal

Processing Advances for Wireless Communications (SPAWC)

2003, New York, Jun. 15 – 18, 2003.

[42] Volipour M., S hafiee H., “Performance of MC-CDMA

Systems with space-time block codes in frequency selective fading

channels”, Int. Conf. on Communications Systems (ICCS 04), Sept

2004, pp. 645-649.

[43]

Min Shi, Claude D. amours, “MIMO-CDMA Systems

Using STBC-Based Permutation Spreading”, Proc. VTC-2010,

Sept 2010, pp. 1-5.

a spatial modulation based ber analysis of mimo system under rayleigh fading channel using stbc...

Documents