Performance Analysis of STBC-SM over Orthogonal STBC · Performance Analysis of STBC-SM over Orthogonal STBC International Journal of Advanced Technology and Innovative Research Volume

www.semargroup.org

ISSN 2348–2370

Vol.06,Issue.04,

June-2014,

Pages:266-275

Copyright @ 2014 SEMAR GROUPS TECHNICAL SOCIETY. All rights reserved.

Performance Analysis of STBC-SM over Orthogonal STBC SHAIK ABDUL KAREEM

1, M.RAMMOHANA REDDY

2

1PG Scholar, Dept of ECE, P.B.R.Visvodaya Institute of Technology and Sciences, Kavali, Nellore, AP, India,

Email:[email protected]. 2Asst Prof, Dept of ECE, P.B.R. Visvodaya Institute of Technology and Sciences, Kavali, Nellore, AP, India,

Email: [email protected].

Abstract: Space-time block coding (STBC) is a Multiple-Input Multiple Output (MIMO) Transmit strategy which exploits

transmits diversity and high reliability. STBC have been shown to perform well with other MIMO systems. MIMO

transmission scheme, called space-time block coded spatial modulation (STBC-SM), is compared extensively with all MIMO

transmission schemes. STBC combines spatial modulation (SM) and space-time block coding (STBC) to take advantage of the

benefits of both while avoiding their drawbacks. In the STBCSM scheme, the transmitted information symbols are expanded

not only to the space and time domains but also to the spatial (antenna) domain which corresponds to the on/off status of the

transmit antennas available at the space domain, and therefore both core STBC and antenna indices carry information. A

general technique is presented for the design of the STBC-SM scheme for any number of transmits antennas besides the high

spectral efficiency advantage provided by the antenna domain; the proposed scheme is also optimized by deriving its diversity

and coding gains to exploit the diversity advantages of STBC. The performance advantages of the STBC-SM over simple

OFDM, CDMA, BPSK, QPSK, QAM and PSK are shown by simulation results for various spectral efficiencies and number of

channels, which are supported by the comparison for the bit error probability for different time intervals. Along with above

stated MIMO techniques new version of STBC are analyzed with existing STBC-SM, like distributed STBC and Orthogonal

STBC.

Keywords: Multiple-Input Multiple-Output (MIMO), BPSK, QPSK, QAM, STBC, Spatial Modulation.

I. INTRODUCTION

MIMO technology means multiple antennas at both the

ends of a communication system, that is, at the transmitting

end and receiving end. The idea behind MIMO is that the

transmit antennas at one end and the receive antennas at the

other end are connected and combined in such a way that

the bit error rate (BER), or the data rate for each user is

improved .MIMO has the capacity of producing

independent parallel channels and transmitting multipath

data streams and thus meets the demand for high data rate

wireless transmission. This system can provide high

frequency spectral efficiency and is a promising approach

with tremendous potential. The use of multiple antennas at

both transmitter and receiver has been shown to be an

effective way to improve capacity and reliability over those

achievable with single antenna wireless systems.

Consequently, multiple-input multiple-output (MIMO)

transmission techniques have been comprehensively

studied over the past decade by numerous researchers, and

two general MIMO transmission strategies, a space-time

block coding1 (STBC) and spatial multiplexing, have been

proposed. The low-complexity sub optimum linear

decoders, such as the minimum mean square error (MMSE)

decoder, degrade the error performance of the system

significantly. On the other hand, STBCs offer an excellent

way to exploit the potential of MIMO systems because of

their implementation simplicity as well as their low

decoding complexity.

A. STBC-SM

It has been shown that the symbol rate of an OSTBC is

upper bounded by ¾ symbols per channel use (PCU) for

more than two transmit antennas. Several high rate STBCs

have been proposed in the past decade, but their ML

decoding complexity grows exponentially with the

constellation size, which makes their implementation

difficult and expensive for future wireless communication

systems. Recently, a novel concept known as spatial

modulation (SM) has been introduced to remove the ICI

completely between the transmit antennas of a MIMO link.

The basic idea of SM is an extension of two dimensional

signal constellations (such as M-ary phase shift keying (M-

PSK) and M-ary quadrature amplitude modulation (M-

QAM), where M is the constellation size) to a third

dimension, which is the spatial (antenna) dimension.

Therefore, the information is conveyed not only by the

amplitude/phase modulation (APM) techniques, but also by

the antenna indices. However, SSK modulation does not

provide any performance advantage compared to SM. In

both of the SM and SSK modulation systems, only one

transmit antenna is active during each transmission interval,

and therefore ICI is totally eliminated, where different

SHAIK ABDUL KAREEM, M.RAMMOHANA REDDY

International Journal of Advanced Technology and Innovative Research

Volume. 06, IssueNo.04, June-2014, Pages:266-275

combinations of the transmit antenna indices are used to

convey information for further design flexibility.

B. Related work

MIMO is an effective way to improve the capacity and

reliability, comparing with single antenna wireless

systems[1],[2].several MIMO techniques have been

comprehensively studied recently studied among which the

space time block code (STBC) for two transmit antennas.

Offers a low- complexity maximum likelihood (ML)

decoding due to its orthogonal structure. Based on this

property of orthogonality, orthogonal space time block

codes (OSTBCs) was presented in [3],[4].OSTBCs are

special class of space time codes which exploits the spatial

diversity and offer low complexity ML decoding. However

,rate one OSTBC exists for two transmit antennas only to

increase the data rate a new class of semi-orthogonal codes

was proposed in [5],[6] known as quasi orthogonal space

time block codes (QOSTBCs) they are all full rate codes

with pair wise decoding complexity. However, the

QOSTBCs of [5],[6] cannot achieve full diversity. To

achieve full diversity, QOSTBC in [7],[8] was proposed by

talking half of the symbols from rotated constellation. To

further reduce the decoding complexity without

compromising on the data rates, a new and distinct class of

codes were designed using the concept of co-ordinate

interleaving .these codes are popularly known as co-

ordinate interleaved orthogonal designs(CIODs) [9],[10].

The CIODs are full rate codes which achieve single-symbol

decidability.

In [9], [10] CIODs for PAM and QAM constellation are

discussed. The existing STBCs retransmit each symbol in

space and time which reduce the capacity of the system.

This reduction in capacity can be improved by using a

mapping function for 16- QAM constellation in Alamouti

STBC [2], in this M-PAM constellation and extended it to

square QAM constellations. Using this mapping function I

proposed an STBC for four transmit antennas which

achieves high coding gain and full diversity.

II. SPACE-TIME BLOCK CODED SPATIAL

MODULATION (STBC-SM)

A new MIMO transmission scheme, called STBC-SM,

is proposed, in which information is conveyed with an

STBC matrix that is transmitted from combinations of the

transmit antennas of the corresponding MIMO system. The

Alamouti code [3] is chosen as the target STBC to exploit.

As a source of information, we consider not only the two

complex information symbols embedded in Alamouti’s

STBC, but also the indices (positions) of the two transmit

antennas employed for the transmission of the Alamouti

STBC. A general technique is presented for constructing

the STBC-SM scheme for any number of transmits

antennas. A low complexity ML decoder is derived for the

proposed STBC-SM system, to decide on the transmitted

symbols as well as on the indices of the two transmits

antennas that are used in the STBC transmission. It is

shown by computer simulations that the proposed STBC-

SM scheme has significant performance advantages over

the SM with an optimal decoder, due to its diversity

advantage. A closed form expression for the union bound

on the bit error probability of the STBCSM scheme is also

derived to support our results. The derived upper bound is

shown to become very tight with increasing signal-to-noise

(SNR) ratio.

Fig1. Block Diagram of Space-Time Coding.

In the STBC-SM scheme, both STBC symbols and the

indices of the transmit antennas from which these symbols

are transmitted, carry information. We choose Alamouti’s

STBC, which transmits one symbol PCU, as the core STBC

due to its advantages in terms of spectral efficiency and

simplified ML detection. In Alamouti’s STBC, two

complex information symbols (x1 and x2) drawn from an

M-PSK or M-QAM constellation are transmitted from two

transmit antennas in two symbol intervals in an orthogonal

manner by the codeword.

X= X1, X2 = X1, X2 → space

-X2∗ X1∗ ↓ time

Where columns and rows correspond to the transmit

antennas and the symbol intervals, respectively. For the

STBC SM scheme we extend the matrix in to the antenna

domain.

A. Multiple Input Multiple Output (MIMO)

MIMO system is commonly used in today’s wireless

technology, including 802.11n Wi Fi, WiMAX, LTE, etc.

Multiple antennas (and therefore multiple RF chains) are

put at both the transmitter and the receiver. A major

concern in MIMO systems is the integration of several

antennas into small handheld devices. Finding feasible

antenna configurations is an integral part of enabling the

MIMO technology.

Fig2. Block Diagram of MIMO.

Performance Analysis of STBC-SM over Orthogonal STBC



A MIMO system with same amount of antennas at both

the transmitter and the receiver in a point-to-point (PTP)

link is able to multiply the system throughput linearly with

every additional antenna. For example, a 2x2 MIMO will

double up the throughput. In radio, multiple-input and

multiple-output, or MIMO is the use of multiple antennas at

both the transmitter and receiver to improve

communication performance. It is one of several forms of

smart antenna technology. Note that the terms input and

output refer to the radio channel carrying the signal, not to

the devices having antennas. MIMO technology has

attracted attention in wireless communications, because it

offers significant increases in data throughput and link

range without additional bandwidth, though extra transmit

power is needed since multiple transmit antennas are

employed instead of only one as in SISO systems. MIMO

systems exploit the multipath structure of the propagation

channel. The antennas are adapted to the propagation

channel. For a comprehensive study, both antennas and

propagation channel have to be treated together and

described statistically to take many channel realizations of a

propagation environment into account. Correlations among

channel coefficients are influenced by the antenna

properties. As the antennas are collocated in a MIMO array,

mutual coupling effects may occur. All these effects should

be considered when designing an antenna array for MIMO

systems. In this contribution, a method will be presented for

accurately modeling both antennas and the propagation

channel.

III. STBC-SM SYSTEM MODELING

In the STBC-SM scheme, both STBC symbols and the

indices of the transmit antennas from which these symbols

are transmitted, carry information. We choose Alamouti’s

STBC, which transmits one symbol per channel use (pcu),

as the core STBC due to its advantages in terms of spectral

efficiency and simplified ML detection. In Alamouti’s

STBC, two complex information symbols (x1 and x2)

drawn from an -PSK or - QAM constellation are

transmitted from two transmit antennas in two symbol

intervals in an orthogonal manner by

(1)

Where columns and rows correspond to the transmit

antennas and the symbol intervals, respectively. For the

STBC-SM scheme we extend the matrix in (1) to the

antenna domain. Example (STBC-SM with four transmit

antennas, BPSK modulation). Consider a MIMO system

with four transmit antennas which transmit the Alamouti

STBC using one of the following four code words:

(2)

Where, , = 1, 2 are called the STBC-SM codebooks

each containing two STBC-SM codeword’s , = 1, 2

which do not interfere to each other. The resulting STBC-

SM code is A Non-interfering codeword group

having elements is defined as a group of codeword’s

satisfying that is they have

no overlapping columns. In (2), is a rotation angle to be

optimized for a given modulation format to ensure

maximum diversity and coding gain at the expense of

expansion of the signal constellation. However, if is not

considered, overlapping columns of codeword pairs from

different codebooks would reduce the transmit diversity

order to one. Assume now that we have four information

bits to be transmitted in two consecutive

symbol intervals by the STBCSM technique. The mapping

rule for 2 bits/s/Hz transmission is given by Table I for the

codebooks of (2) and for binary phase-shift keying (BPSK)

modulation, where a realization of any codeword is called a

transmission matrix.

We have four different codeword’s each having M2

different realizations. Consequently, the spectral efficiency

of the STBC-SM scheme for four transmit antennas

becomes = (1/2) log24M2 = 1 + log2 M bits/s/Hz, where the

factor 1/2 normalizes for the two channel uses spanned by

the matrices in (2). For STBCs using larger numbers of

symbol intervals such as the quasi-orthogonal STBC for

four transmit antennas which employs four symbol

intervals, the spectral efficiency will be degraded

substantially due to this normalization term since the

number of bits carried by the antenna modulation (log2c),

(where c is the total number of antenna combinations) is

normalized by the number of channel uses of the

corresponding STBC.

A. System Design and Optimization

1. STBC-SM Transmitter

In this subsection, we generalize the STBC-SM scheme

for MIMO systems using Alamouti’s STBC to transmit

antennas by giving a general design technique. An important

design parameter for quasi-static Rayleigh fading channels

is the minimum coding gain distance (CGD) between two

STBC-SM codeword’s and , where is

transmitted and , is erroneously detected, is defined as

(3) Minimum CGD between two codebooks xi and xj is

defined as

(4) And the minimum CGD of an STBC-SM code is defined

by




(5)

Note that, corresponds to the determinant

criterion, since the minimum CGD between non-interfering

codeword’s of the same codebook is always greater than or

equal to the right hand side of above equation (4)

Fig3. Block diagram of the STBC-SM transmitter.

Unlike in the SM scheme, the number of transmit antennas

in the STBC-SM scheme need not be an integer power of 2,

since the pair wise combinations are chosen from

available transmit antennas for STBC transmission. This

provides design flexibility. However, the total number of

codeword combinations considered should be an integer

power of 2. In the following, we give an algorithm to design

the STBC-SM scheme:

1. Given the total number of transmit antennas ,

calculate the number of possible antenna combinations

for the transmission of Alamouti’s STBC, i.e., the total

number of STBC-SM codeword’s from

, where is a positive integer.

2. Calculate the number of codeword’s in each codebook

, from and the total

number of codebooks from . Note that the

last codebook does not need to have codeword’s, i.e.,

its cardinality is .

3. Start with the construction of which contains non

interfering codeword’s as

(6)

4. Using a similar approach, construct for

by considering the following two

important facts:

Every codebook must contain non-interfering

codeword’s chosen from pair wise combinations of

available transmit antennas.

Each codebook must be composed of codeword’s

with antenna combinations that were never used in

the construction of a previous codebook.

5. Determine the rotation angles for each

, that maximize for a

given signal constellation and antenna configuration;

that is , where .

As long as the STBC-SM codeword’s are generated by

the algorithm described above, the choice of other antenna

combinations is also possible but this would not improve the

overall system performance for uncorrelated channels. Since

we have antenna combinations, the resulting spectral

efficiency of the STBC-SM scheme can be calculated as

(7) The block diagram of the STBC-SM transmitter is shown

in Fig. 3. During each two consecutive symbol intervals, 2

bits . Enter the STBC-

SM transmitter, where the first log2 bits determine the

antenna-pair position ℓ = that is

associated with the corresponding antenna pair, while the

last bits determine the symbol pair . If

we compare the spectral efficiency (7) of the STBC-SM

scheme with that of Alamouti’s scheme , we

observe an increment of provided by the

antenna modulation. We consider two different cases for the

optimization of the STBC-SM scheme.

Case 1: : We have, in this case, two codebooks

and and only one non-zero angle, say , to be optimized.

It can be seen that is equal to the minimum

CGD between any two interfering codeword’s from and

. Without loss of generality, assume that the interfering

codeword’s are chosen as

(8)

Where is transmitted and is erroneously

detected. We calculate the minimum CGD between

from (3) as

(9)




Where . Although maximization of

with respect to is analytically possible

for BPSK and quadrature phase-shift keying (QPSK)

constellations, it becomes unmanageable for 16-QAM and

64- QAM which are essential modulation formats for the

next generation wireless standards such as LTE-advanced

and WiMAX. We compute as a function of

∈ [0, /2] for BPSK, QPSK, 16-QAM and 64-QAM signal

constellations via computer search and plot them in Fig. 2.

These curves are denoted by for = 2, 4, 16 and

64, respectively. Values maximizing these functions can

be determined from Fig. 2 as follows:

(10)

Case 2: : In this case, the number of codebooks, ,

is greater than 2. Let the corresponding rotation angles to be

optimized be denoted in ascending order by

, where for BPSK and

for QPSK. For BPSK and QPSK signaling, choosing

(11)

For guarantees the maximization of the

minimum CGD for the STBC-SM scheme. This can be

explained as follows. For any , we have to maximize

as

(13)

Where, , for and the minimum CGD between

codebooks and is directly determined by the

difference between their rotation angles. This can be easily

verified from (9) by choosing the two interfering

codeword’s as and with the

rotation angles and , respectively. Then, to maximize

min ( ), it is sufficient to maximize the minimum CGD

between the consecutive codebooks and .

For QPSK signaling, this is accomplished by dividing the

interval into equal sub-intervals and choosing,

The resulting maximum can be evaluated from

(11) as

(14)

Similar results are obtained for BPSK signaling except

that is replaced by in (12) and (13). We obtain

the corresponding maximum as

. On the other hand, for 16-QAM

and 64-QAM signaling, the selection of s in integer

multiples of /2 would not guarantee to maximize the

minimum CGD for the STBC-SM scheme since the

behavior of the functions and for

QPSK and 16-QAM. Similarly, max is

calculated for BPSK, QPSK and 16-QAM constellations as

(15)

According to the design algorithm, the codebooks can

be constructed as follows:

(16)

B. Optimal ML Decoder for the STBC-SM System

In this subsection, we formulate the ML decoder for the

STBC-SM scheme. The system with transmit and receive

antennas is considered in the presence of a quasi-static

Rayleigh flat fading MIMO channel. The received

signal matrix Y can be expressed as

(17)

Where is the STBC-SM transmission

matrix, transmitted over two channel uses and is a

normalization factor to ensure that is the average SNR at

each receive antenna. H and N denote the

channel matrix and 2× noise matrix, respectively. The

entries of H and N are assumed to be independent and

identically distributed (i.i.d.) complex Gaussian random

variables with zero means and unit variances. We assume

that H remains constant during the transmission of a

codeword and takes independent values from one codeword

to another. We further assume that H is known at the

receiver, but not at the transmitter. Assuming transmit

antennas are employed; the STBCSM code has c

codeword’s, from which different transmission

matrices can be constructed. An ML decoder must make an




exhaustive search over all possible transmission

matrices, and decides in favor of the matrix that minimizes

the following metric:

(17) The minimization in (6) can be simplified due to the

orthogonality of Alamouti’s STBC as follows. The decoder

can extract the embedded information symbol vector from

(5), and obtain the following equivalent channel model:

(18)

Where is the equivalent channel matrix of the

Alamouti coded SM scheme, which has cdifferent

realizations according to the STBC-SM codeword’s. In (7),

y and n represent the equivalent received signal and

noise vectors, respectively. Due to the orthogonality of

Alamouti’s STBC, the columns of are orthogonal to

each other for all cases and, consequently, no ICI occurs in

our scheme as in the case of SM. Consider the STBC-SM

transmission model as described in Table I for four transmit

antennas. Since there are c = 4 STBC-SM codeword’s.

Generally, we have equivalent channel matrices

, and for the ℓth combination, the

receiver determines the ML estimates of and using

the decomposition as follows, resulting from the

orthogonality of hℓ,1 and hℓ,2: x

(19)

Where H ℓ =[ hℓ,1 hℓ,2 ] , , and

is a 2 ×1 column vector. The associated

minimum ML metrics and for and are

(20)

Since and are calculated by the ML decoder for

the ℓth combination, their summation 1

gives the total ML metric for the ℓth combination. Finally,

the receiver makes a decision by choosing the minimum

antenna combination metric as for which

. As a result, the total number of ML metric

calculations in (15) is reduced from 2 to 2 , yielding a linear

decoding complexity as is also true for the SM scheme,

whose optimal decoder requires metric calculations.

Obviously, since for , there will be a linear

increase in ML decoding complexity with STBC-SM as

compared to the SM scheme. However, as we will show in

the next section, this insignificant increase in decoding

complexity is rewarded with significant performance

improvement provided by the STBC-SM over SM. The last

step of the decoding process is the demapping operation

based on the look-up table used at the transmitter, to recover

the input bits

from the determined spatial position (combination) ˆℓ and

the information symbols ˆ 1 and ˆ 2. The block diagram of

the ML decoder described above is given in Fig. 3.

As a result, the total number of metric calculations in (6)

is reduced from to , yielding a linear decoding

complexity as is also true for the SM scheme, whose

optimal decoder requires metric calculations. Obviously,

since C for , there will be a linear increase in ML

decoding complexity with STBC-SM as compared to the

SM scheme. However, as we will show in the next section,

this in signisficant increase in decoding complexity is

rewarded with significant performance improvement

provided by the STBC-SM. The last step of the decoding

process is the de-mapping operation, to recover the input

bits from the determined

spatial position (combination) and the information

symbols and . The block diagram of the ML decoder

described in Fig.4.

Fig4. Block diagram of the STBC-SM receiver.

C. Performance Analysis Of The Stbc-Sm System In this section, we analyze the error performance of the

STBC-SM system, in which 2m bits are transmitted during

two consecutive symbol intervals using one of the 2 = 22

different STBC-SM transmission matrices, denoted by

X1,X2, . . . ,X here for convenience. An upper bound on the

average bit error probability (BEP) is given by the well

known union bound

(21)

Where, is the pair wise error probability (PEP) of

deciding STBC-SM matrix given that the STBC SM

matrix is transmitted, and , is the number of bits in

error between the matrices and . Under the

normalization = 1 and in (10), the

conditional PEP of the STBC-SM system is calculated as




(22)

Where, . Averaging (17) over the

channel matrix H and using the moment generating

function(MGF) approach; the unconditional PEP is

obtained as

(23) All transmission matrices have the uniform error property

due to the symmetry of STBC-SM codebooks, i.e., have the

same PEP as that of X1. Thus, we obtain a BEP upper

bound for STBC-SM as follows:

(24) We obtain the union bound on the BEP as

(25)

IV.SIMULATION RESULTS AND COMPARISONS In this section, we present simulation results for the

STBCSM system with different numbers of transmit

antennas and make comparisons with OFDM, CDMA,

BPSK, QPSK, QAM, PSK, O-STBC and DSTBC for four

transmit antennas. All performance comparisons are made

for a BER value of 10−5 and Error probability. We first

present the BER upper bound curves of the STBC-SM

scheme are evaluated from and depicted in the following

Figures. It follows that the derived upper bound becomes

very tight with increasing SNR values for all cases and can

Fig5. BER performance of STNC scheme for different

SNR, with Distributed STBC using OFDM modulation.


SNR, with Distributed STBC using CDMA modulation.


time intervals, with STBC using QAM modulation.


time intervals, with STBC using QPSK modulation.




Fig9. BER performance of STNC scheme for different,

with Distributed STBC using QPSK modulation.


time intervals STBC using BPSK modulation.


time intervals STBC using OSTBC modulation.

Fig12. The BER performance of the STBC-SM scheme

with the orthogonal STBC code scheme.

be used as a helpful tool to estimate the error performance

behavior of the STBC-SM scheme with different setups.

Also note that the BER curves for nT=3,4 and BPSK,

QPSK modulations from Fig. 5,6,7,8,9,10,11,12; are shifted

to the right while their slope remains unchanged and equal

to , with increasing spectral efficiency. We compare

the BER performance of the STBC-SM scheme with the

orthogonal STBC code scheme which is rate- 3

(transmitting four symbols in two time intervals) STBCS

for two and four transmit antennas, respectively.

Fig13. The BER performance of the STBC-SM scheme

with = 4 and QPSK.

In the above figures 12, 13, the BER curves of STBC-SM

with =4 and QPSK is evaluated for 3bits/s/Hz

transmission. We compare the BER performance of the




STBC-SM scheme with the orthogonal STBC code scheme

which are rate-3 (transmitting four symbols in two time

intervals) STBCS for four transmit antennas, and STBC

with 8-qam OSTBC with 32 QAM.

Fig14. The BER performance at 3bits for STBC-SM

scheme with the orthogonal STBC code scheme.

We compare the BER performance of the STBC-SM

scheme with the orthogonal STBC code scheme which are

rate-3 (transmitting four symbols in two time intervals)

STBCS for four transmit antennas, and STBC with 16-

QAM and OSTBC with 256 QAM.

Fig15. The BER performance at 6bits for STBC-SM

scheme with the orthogonal STBC code scheme.

In Fig. 14, 15 the BER curves of STBC-SM with = 4

and QPSK is evaluated for 3 bits/s/Hz transmission. Table-I,

clearly explains the overall comparison with respect to the

loss of signal at the receiver and by calculating the

percentage of loss, the loss less communication will be

QAM,QPSK and BPSK schemes over OFDM and CDMA.

To select the appropriate Modulation Technique we want to

simulate for, coding flexibility is provided and comparative

values are clearly exhibited, by the MATLAB program.

TABLE I: Comparison With Respect To the Loss Of

Signal

V. CONCLUSION In this paper, we have compared a novel high-rate, low

complexity MIMO transmission scheme, called STBC-SM,

with an alternative to existing techniques such as orthogonal

STBC and DSTBC. A general technique has been presented

for the construction of the STBC-SM scheme for any

number of transmit antennas in which the STBC-SM system

was optimized by deriving its diversity to reach optimum

performance. The proposed new transmission scheme

employs both APM techniques and antenna indices to

convey information and exploits the transmit diversity

potential of MIMO channels. From a practical

implementation point of view, the RF (radio frequency)

front-end of the system should be able to switch between

different transmit antennas similar to the classical SM

scheme. It has been shown by a theoretical and practical

analysis that the STBC-SM offers significant improvements

in BER performance compared to OSTBC and DSTBC

systems and other standard communication systems

(approximately 3-5 dB depending on the spectral efficiency)

with an acceptable linear increase in decoding complexity.

On the other hand, unlike DSTBC in which all antennas are

employed to transmit simultaneously, the number of

required RF chains is only two in our scheme, and the

synchronization of all transmit antennas would not be

required. We conclude that the STBC-SM scheme can be

useful for high-rate, low complexity, emerging wireless

communication systems.

VI. REFERENCES [1] S. M. Alamouti, “A simple transmit diversity technique

for wireless communications,” IEEE J. Sel. Areas

Commun., vol. 16, pp. 1451–1458, Oct. 1988.

[2] P. Wolniansky, G. Foschini, G. Golden, and

R.Valenzuela, “ an architecture for realizing very high data

rates over the rich-scattering wireless channel,” in Proc.

1998 International Symp. Signals, Syst.,Electron., pp. 295–

300.

[3] H. Jafarkhani, Space-Time Coding, Theory and Practive.

Cambridg University Press, 2005.

[4] V. Tarokh, H. Jafarkhani, and A. R. Calderbank, “Space

time block codes from orthogonal designs,” IEEE Trans.

Inf. Theory, vol. 45, no. 5,pp. 1456–1467, July 1999.




[5] E.Biglieri, Y. Hong, and E. Viterbo, “On fast-decodable

space-time block codes,” IEEE Trans. Inf. Theory, vol. 55,

no. 2, pp. 524–530, Feb. 2009.

[6] E. Ba¸ar and Ümit Aygölü, “High-rate full-diveristy

space-time blocks codes for three and four transmit

antennas,” IET Commun., vol. 3, no. 8 pp. 1371–1378, Aug,

2009.

[7] “Full-rate full-diversity STBCS for three and four

transmit antennas,” Electron. Lett. vol. 44, no. 18, pp. 1076–

1077, Aug. 2008.

[8] D. Tse and P. Viswanath, Fundamentals of Wireless

Communication Cambridge University Press, 2005.

[9] J. Jeganathan, A. Ghrayeb, L. Szczecinski, and A.

Ceron, “Space shift keying modulation for MIMO

channels,” IEEE Trans. Wireless ommun., vol. 12, pp.

3692–3703, July 2009.

[10] R. Mesleh, H. Haas, S. Sinaovic, C. W. Ahn, and S.

Yun, “Spatial modulation,” IEEE Trans. Veh. Technol.,

vol. 57, no. 4, pp. 2228–2241, July 2008.

Documents

Performance Analysis of STBC-SM over Orthogonal STBC · Performance Analysis of STBC-SM over Orthogonal STBC International Journal of Advanced Technology and Innovative Research Volume