In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT ), Vol.9, No.4/5, Oc obe 2019
DOI : 10.5121/ijmnc .2019.9501 1
INVESTIGATING THE PERFORMANCE OF VARIOUS
CHANNEL ESTIMATION TECHNIQUES FOR
MIMO-OFDM SYSTEMS USING MATLAB
Woud M. Abed and Raghad K. Mohammed
Depa men o Basic Science, College o Den is y
Uni e si y o Baghdad, Baghdad, I aq
ABSTRACT
This pape simula es and in es iga es he pe o mance o ou widely-used channel es ima ion echniques
o MIMO-OFDM wi eless communica ion sys ems; namely, supe imposed pilo (SIP), comb- ype, space-
ime block coding (STBC), and space- equency block coding (SFBC) echniques. The pe o mance is
e alua ed h ough a numbe o MATLab simula ions, whe e he bi -e o a e (BER) and he mean squa e
e o (MSE) a e es ima ed and compa ed o di e en le els o signal- o-noise a io (SNR). The simula ion
esul s demons a e ha he comb- ype channel es ima ion and he SIP echniques o e whelmed he
pe o mance o he STFC and STBC echniques in e ms o bo h bi -e o a e (BER) and mean squa e
e o (MSE).
KEYWORDS
MIMO-OFDM, pilo -based channel es ima ion, pilo alloca ion, SIP, comb- ype, STBC, SFBC, MATLab.
1. INTRODUCTION
One o he mos challenging opics in oday wi eless communica ion sys ems is how o
accomplish high da a ansmission a e and main ain sa is ac o y quali y-o -se ice (QoS) ha can
mee he exponen ially g owing use s and applica ions demands. This is a challenging opic
because o he limi ed spec um and he channel ading caused by mul ipa h componen s in he
wi eless channel. One o he p omising solu ions o his p oblem is o combine he concep s o
mul iple-inpu mul iple-ou pu (MIMO) wi h o hogonal equency di ision mul iplexing
(OFDM); which led o he eme gen o he new MIMO-OFDM wi eless communica ion sys ems
[1, 2].
The MIMO echnology implies he use o mul iple an ennas a he ansmi e and he ecei e
sides o he wi eless link, which signi ican ly inc eases he da a ansmission a es [3]. OFDM
implies a mul ica ie ansmission and equency di ision mul iplexing, whe e a single da a
s eam is ansmi ed o e se e al low a e subca ie s, placed o hogonal o each o he o p o ide
high da a ansmission a e wi h minimum e o , and enough obus ness o adio channel
impai men s. P ac ically, he ansmi ed signals o MIMO-OFDM sys ems bene i om he
mul i-pa h delay ole ance and immuni y o equency selec i e channel ading o MIMO, as well
as he high da a ansmission a e o OFDM[4, 5].
Channel es ima ion is one o he main equi emen s o MIMO-OFDM sys ems. The e o e, a
numbe o channels es ima ion echniques o MIMO-OFDM sys ems ha e been de eloped [6-
8].In o de o be able o selec be ween hese echniques, i is necessa y o in es iga e hei
pe o mance in di e en wo king en i onmen s. Compu e simula ion is well- ecognized as he
mos easible solu ion as p ac ical in es iga ions a e complica ed, cos ly, and ime consuming
[9,10].
In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT), Vol.9, No.4/5, Oc obe 2019
2
This pape simula es and in es iga es he pe o mance o ou di e en channel es ima ion
echniques o MIMO-OFDM sys ems; hese a e: supe imposed pilo (SIP) [11], comb- ype [12],
space- ime block coding (STBC) [13], and space- equency block coding (SFBC) [14]
echniques. The pe o mance is e alua ed h ough a numbe o MATLab simula ions, whe e he
bi -e o a e (BER) and he mean squa e e o (MSE) a e es ima ed and compa ed o di e en
le els o signal- o-noise a io (SNR) [5]. The simula ion esul s demons a e ha he comb- ype
and SIP p o ides be e pe o mance in e ms o bo h BER and MSE o e he STBC and SFBC
especially wi h SNR.
The pape is di ided in o 6 sec ions. This sec ion p esen s he main heme o he pape . A e iew
o some o he mos ecen and ela ed wo ks on simula ion and in es iga ion o he pe o mance
o MIMO-OFDM sys ems, using MATLab, a e gi en in Sec ion 2.Sec ion 3 explains he basic
p inciples o MIMO-OFDM and he main concep s o he pilo -based channel es ima ion
echniques s udied in his pape . The simula ed MIMO-OFDM sys em model is desc ibed in
Sec ion 4. The esul s and discussions a e gi en in Sec ion 5. Finally, in Sec ion6 some
conclusions a e p esen ed and a numbe o ecommenda ions o u u e a e poin ed-ou .
2. LITERATURE REVIEW
This sec ion p esen s a e iew o some o he mos ecen de elopmen and pe o mance
e alua ion o MIMO-OFDM sys ems using MATLab [1, 9].
Chou asiya and Sa a [6] in es iga ed he e ec o di e en modula ion echniques (e.g., BPSK,
QPSK, 16 PSK and 16 QAM)on he BER pe o mance o a 2x2 MIMO-OFDM sys em using
MATLab. Thei esul s conclude ha o he same SNR, he BER o BPSK is lowe han QPSK,
16 PSK and 16 QAM.Simila ly, using MATLab,Sha ma and Kau [7] and Jangalwa [15] showed
ha MIMO-OFDM can p o ide be e BER pe o mance han OFDM sys ems. Ka gi [8]
in es iga ed he e ec o he mul i-an enna combina ion (e.g., 2×1, 2×2, 4×1 and 4×2), and
modula ion echnique (e.g., BPSK and QPSK) on he pe o mance o MIMO-OFDM sys ems.
Rashid and Hossain [16] used MATLab o in es iga e he pe o mance o MIMO-OFDM
sys emsin5G ne wo ks, wi h he aim o achie ing he lowes and op imum BER while inc easing
he sys em capaci y. Sh i as a a and T i edi [14] implemen ed and analyzed he pe o mance o
MIMO–OFDM sys em using space- ime- equency (STF) coding and andom beam o ming
using MATLab. They ound ha combining beam o ming wi h STF coding p o ides lowe BER
o e STF alone, as well as he combined STBC-beam o ming.
Ach a e . al. [3] discussed and analyzed he BER pe o mance o MIMO-OFDM sys em wi h wo
di e en equalize s (ZF and MMSE) o a ious modula ion echniques (e.g., BPSK, QPSK, 16-
QAM, and 64-QAM) using mul ipa h ading channels, namely, addi i e whi e Gaussian noise
(AWGN) and Rayleigh and Rician channels. The simula ion esul s show ha MMSE equalize
achie es a lowe BER han ZF o a ious SNR. Simila s udy by Pandey e . al. [17] analyzed he
pe o mance o a QPSK modula ion MIMO-OFDM sys em wi h AWGN, Rayleigh, and Rician
channels. They demons a ed ha MIMO-OFDM wi h STBC using 2x2 an enna con igu a ions
and 512 FFT leng h has be e pe o mance in e ms o BER han he o he sys ems.
Se hy and Swain [18] ound ha o di e en ading channel, MIMO achie es ull di e si y using
OSTBC encode o o e come ading e ec o channel, and OFDM educes in e symbol
in e e ence (ISI) o highe da a a e and highe spec al e iciency. Based on he simula ion
esul s, he BER pe o mance o MIMO sys em is be e han ha o MIMO-OFDM sys em, bu
MIMO-OFDM sys em is spec ally mo e e icien .
In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT), Vol.9, No.4/5, Oc obe 2019
3
Reddy and Lakshmi [19] explo ed how MIMO inc eases channel capaci y using a spa ial
modula ion echnique ha combines he high mul iplexing gain p o ided by he spa ial
modula ion and ansmi -di e si y gain p o ided by he STBC echnology. They explo ed wo
di e en STBC schemes (Alamou i’s STBC and o hogonal STBC). The wo schemes
demons a e highe da a a e o longe ansmi ange wi hou equi ing addi ional bandwid h o
ansmi powe .
Pa hak and Sha ma [20] in es iga ed and compa ed he pe o mance o wo majo ypes o pilo
a angemen such as block- ype and comb- ype pilo , using he leas squa e e o (LSE) and
minimum mean squa e e o (MMSE) channel es ima o s. Pa il and Jadha [21] compa ed he
pe o mance o channel es ima ion algo i hm and highligh ed he channel es ima ion echnique
based on pilo -aided block- ype aining symbols using LS and MMSE algo i hm.
Jain and Nandal [22] analyzed and compa ed he pe o mance o channel es ima ion o MIMO
communica ion sys ems using STBC, SFBC, and STFBC echniques unde a ious ading
channels. The pe o mance is e alua ed h ough a numbe simula ions using MATLab. Daoud e .
al [23] de eloped a new algo i hm o enhance he pe o mance o he speake e i ica ion o e he
communica ion sys ems based MIMO-OFDM echniques.
In conclusion, he majo ad an ages o MIMO-OFDM sys ems a e: (i) subs an ial inc ease in
channel capaci y, which immedia ely ansla es o highe da a h oughpu , (ii) signi ican
imp o emen in da a ansmission eliabili y, i.e., e y low bi e o a e (BER). These ad an ages
can be achie ed wi hou any expansion in he equi ed bandwid h o inc ease in he ansmi
powe .
3. PILOT-BASED CHANNEL ESTIMATION TECHNIQUES
High spec al e iciency and imp o ed link eliabili y a e wo o he majo challenges in wi eless
communica ions sys ems. The wi eless channel cons i u es a hos ile p opaga ion medium, which
su e s om he addi ion o des uc i e mul ipa h componen s ( ading) and in e e ence om
o he use s. Di e si y p o ides he ecei e wi h se e al eplicas o he ansmi ed signal and is
he e o e a powe ul app oach o alle ia e ading and in e e ence and he eby imp o e link
eliabili y and channel capaci y [1].
The use o spa ial (o an enna) di e si y has become e y popula in ecen yea s, which is mos ly
due o he ac ha i can be easily implemen ed in oducing any loss in spec al e iciency.
An enna di e si y can be implemen ed a he ecei ing and ansmi ing sides. The use o mul iple
an ennas a bo h ends o a wi eless link (MIMO) has a g ea po en ial o achie ing ex ao dina y
da a a es. On he o he hand, OFDM can signi ican ly educe ecei e complexi y in wi eless
sys ems. Thus, combining MIMO wi h OFDM echnologies o de elop wha is e e ed o as
MIMO-OFDM sys em seems o be an a ac i e solu ion o u u e wi eless sys ems [2].
Channel es ima ion in MIMO-OFDM sys ems is mo e complica ed in compa ison o ha in
single-inpu single-ou pu OFDM (SISO-OFDM) sys ems [25]. The e o e, he echniques ha a e
used in SISO-OFDM canno be simply ex ended and used in MIMO-OFDM, because he
supe posi ion o signals om mul iple ansmi s an ennas makes decoupling pilo signals mo e
complica ed.
The e a e a numbe o pilo -based channel es ima ion echniques ha ha e been de eloped o
MIMO-OFDM sys ems o e quasi-s a ic channel [6, 18, 19]. This sec ion discusses ou o hem,
namely: SIP, comb- ype, STBC, and SFBC channel es ima ion echniques.
In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT), Vol.9, No.4/5, Oc obe 2019
4
3.1. SIP Channel Es ima ion Technique
SIP channel es ima ion is no a s aigh o wa d app oach compa ed o he ollowing h ee
schemes, which is in lexible in he pilo alloca ion and di icul o ex end o he a bi a y numbe
o ansmi an ennas. I has been ecognized ha SIP can sa e he subca ie s occupied by he
pilo s as depic ed in Figu e 1. In o he wo ds, his me hod es ima es he MIMO-OFDM channel
wi hou employing addi ional pilo s in he equency domain, which imp o es he spec al
e iciency. Thus, he main ad an ages o his SIP based channel es ima ion a e: high spec al
e iciency, low complexi y, and no p io knowledge abou channels and noise equi ed.
Desc ip ion o he SIP based channel es ima ion echnique can be ound in [11, 26].
3.2. Comb-Type Channel Es ima ion Technique
The comb- ype channel es ima ion o MIMO-OFDM sys ems is simila o hese echniques
employed in a single an enna scena io, due o he comb s uc u e in he equency and space
domain. The diag am o such pilo alloca ion is shown in Figu e2, which elimina es he e ec s o
in e -an enna in e e ence using addi ional null subca ie s. Hence, he SISO echniques can be
ex ended o MIMO-OFDM sys ems, because he pilo pa e n o each pai o ansmi and
ecei e an enna is simila o ha o SISO-OFDM sys ems [12, 25].
Fu he mo e, he posi ions o pilo s can be eadily placed in he equency and space domain as
compa ed o SIP alloca ion. Howe e , he comb- ype channel es ima ion o e e y equency
selec i e channels equi es mo e pilo s in he sense ha he mo e null subca ie a e employed,
which educes he spec al e iciency.
3.3. STBC Channel Es ima ion Technique
STBC is a echnique used in wi eless communica ion o ansmi mul iple copies o a da a s eam
ac oss a numbe o an ennas, o exploi he a ious ecei ed e sions o da a o imp o e he
eliabili y o da a ans e . STBC has eme ged as one o he majo echniques o exploi he
MIMO bene i . Bo h spa ial and empo al di e si ies a e achie ed in STBC, also i o e s simple
decoding wi h he use o maximum likelihood de ec ion algo i hm a he ecei e [13].
STBC can be used in he channel es ima ion o MIMO-OFDM sys ems wi h he assump ion ha
he channels emain cons an in he ime o equency domain du ing se e al OFDM symbols.
The assump ion may no be p ac ical in some scena ios, and he pe o mance will be signi ican ly
a ec ed i he channels become mo e selec i e [14].
F equency
An enna
Pilo , Da aNull
F equency
An enna
Pilo Da a
. . .
Figu e 2. The diag am o comb- ype.
Figu e 1. The diag am o SIP.
In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT), Vol.9, No.4/5, Oc obe 2019
5
3.4. SFBC Channel Es ima ion Technique
SFBC is he same as STBC is a echnique used in wi eless communica ions o ansmi mul iple
copies o a da a s eam ac oss a numbe o an ennas and o exploi he a ious ecei ed e sions
o he da a o imp o e he eliabili y o da a ans e . SFBC in ol es coding ac oss space and
equency, which is o en e e ed o as space- equency coding (SFC) [14]. A way o do SFC is
o ake he space- ime codes (STC) (e.g., Alamou i code), and apply hem in he equency
dimension ins ead o ime dimension. Tha is, ins ead o moun ing he space- ime coded symbols
on mul iple ime slo s, hey a e moun ed on mul iple OFDM subca ie s. SFBC is simila o
STBC i can be used in he channel es ima ion o MIMO-OFDM sys ems wi h he assump ion
ha he channels emain cons an in he ime o equency domain du ing se e al OFDM
symbols.
4. MIMO-OFDM SYSTEM MODEL
The sys em model ha is simula ed and in es iga ed is desc ibed as ollows: An un-coded spa ial
mul iplexing MIMO-OFDM sys em wi h Ns subca ie s, N ansmi and N ecei e an ennas,
whe e N ≤ N , as shown in Figu e3. In Figu e (3, he modula ed symbols om he modula o s
(MOD) and pilo s a e inse ed in o da a subca ie s and pilo subca ie s ia pilo alloca ion. The
ou pu o pilo alloca ion is hen passed h ough in e se as Fou ie ans o m (IFFT) and
appended wi h cyclic p e ix (CP) o ansmission. A he ecei e , he CP is emo ed and he
unca ed ecei ed signals wi hou CP a e hen passed h ough as Fou ie ans o m (FFT). The
pilo s a e used o channel es ima ion, and he de ec ion is pe o med wi h he es ima ed channels.
The ansmi ed symbols a e eco e ed h ough he demodula o s (DEMOD) wi h he ou pu o
de ec ion.
5. RESULTS AND DISCUSSIONS
In o de o compa e he pe o mance o he channel es ima ion echniques desc ibed in Sec ion 3,
a numbe o simula ions ha e been pe o med using MATLab. In hese simula ions, we conside
a 2×2 MIMO-OFDM sys em, numbe o subca ie (Ns) is 128, numbe o pilo s uni o mly
dis ibu ed (Np) is 16, channel leng h (L) is 8, no malized Dopple equency ( dTOFDM) is 10-2, and
channel gene a ion model is Jake’s model. Fo comb- ype channel es ima ion, 8 pilo s and 8 null
subca ie s a e employed o ai compa ison.
The pe o mance is e alua ed in e ms o wo widely-used pe o mance measu es; hese a e: he
bi -e o a e (BER) and he squa e mean e o (MSE). BER is he numbe o bi s ha a e
e oneously ecei ed o al e ed (due o noise, in e e ence, dis o ion o bi synch oniza ion)
di ided by he o al numbe o bi s ansmi ed o e he channel o a ce ain pe iod o ime. MSE
is he a e age o he squa e o he e o . The BER and MSE a e in es iga ed agains an in e es ing
inpu pa ame e , namely, he signal- o-noise a io (SNR), which is de ined as he a io o signal
powe o he noise powe . O en i is exp essed in decibels and calcula ed by di iding he alue o
he main signal by he alue o he noise, ake he common loga i hm o he esul , and hen
mul iply he esul by 20 [5].
The BER and MSE pe o mance a e gi en in Figs. (4) and (5), espec i ely. In gene al, i can be
seen om Figu e 4 ha he BER pe o mance dec eases wi h inc easing SNR o all echniques.
All echniques p o ides almos he same BER up o SNR=5 dB. Fo SNR>5 dB, SIP and comb-
ype main ain almos he same BER, whe e bo h pe o ms be e han STBC and SFBC as hey
accomplish less BER. While he STBC p o ides he wo s pe o mance as i accomplishes he
highes BER, and he BER pe o mance is wo sen wi h inc easing SNR. The SFBC almos
In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT), Vol.9, No.4/5, Oc obe 2019
6
p o ides a mode a e BER pe o mance be ween he SIP and comb- ype and he STBC. The BER
pe o mance o comb- ype channel es ima ion is sligh ly be e han ha o SIP.
Figu e 3. Block diag am o a MIMO-OFDM sys em.
Figu e5 depic s he MSE pe o mance, and once again i can be clea ly ecognized ha he MSE
dec eases as SNR inc easing o all echniques. The comb- ype and SIP echniques o e whelm
he pe o mance o STBC and SFBC especially a SNR>5 dB. The comb- ype accomplishes
sligh ly be e pe o mance han he SIP. Fu he mo e, SIP-based channel es ima ion equi es e-
design o pilo symbols o di e en ansmi an ennas and di e en subca ie s. Hence, he pilo
pa e ns o SIP channel es ima ion is no lexible compa ed o ha o comb- ype channel
es ima ion. The cu es o MSE pe o mance in Figu e 5 o STBC and SFBC almos ag ee wi h
he cu es o BER pe o mance in Figu e4, whe e SFBC pe o ms be e han STBC.
Signal Modula ion
(QPSK)
Pilo Alloca ion
IFFT
Signal
Demodula ion
(QPSK)
Inpu
Da a
Se ial- o-Pa allel
Con e e (S/P)
Analog- o-Digi al
Con e e (A/D)
Es ima e BER &
MSE
Se ial- o-Pa allel
(S/P) Con e e
Cyclic-P e ix (CP)
Addi ion
Pa allel- o-Se ial
(P/S) Con e e
Digi al- o-Analog
Con e e (D/A)
Channel Es ima ion
FFT
Pa allel- o-Se ial
(P/S) Con e e
Cyclic-P e ix (CP)
Remo al
Signal Modula ion
(QPSK)
Pilo Alloca ion
IFFT
Se ial- o-Pa allel
(S/P) Con e e
Cyclic-P e ix (CP)
Addi ion
Pa allel- o-Se ial
(P/S) Con e e
Digi al- o-Analog
Con e e (D/A)
Signal
Demodula ion
(QPSK)
Se ial- o-Pa allel
Con e e (S/P)
Analog- o-Digi al
Con e e (A/D)
Channel Es ima ion
FFT
Pa allel- o-Se ial
(P/S) Con e e
Cyclic-P e ix (CP)
Remo al
Inpu
Da a
Noisy Channel
Ou pu
Da a
Ou pu
Da a
In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT), Vol.9, No.4/5, Oc obe 2019
7
Figu e 4. BER s. SNR (L=8, dTOFDM=10−2).
Figu e 5. MSE s. SNR (L=8, dTOFDM=10−2).
6. CONCLUSIONS
The simula ion esul s demons a e ha comb- ype and SIP channel es ima ion echniques ha e
be e pe o mance in e ms o BER and MSE (lowes alues) as compa ed o SFBC and STBC
echniques o all powe ange; and SFBC echnique p o ides be e pe o mance han STBC.
In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT), Vol.9, No.4/5, Oc obe 2019
8
P ac ically, comb- ype and SIP ou pe o m bo h SFBC and STBC signi ican ly, as well as hey
a e mo e obus and p omising. Fu he mo e, comb- ype channels es ima ion wo ks be e han
SIP wi h he same numbe o pilo s, which implies hey ha e he same numbe o da a
subca ie s. Based on he simula ion esul s o BER and MSE, he ou in es iga ed echniques
can be anked as ollows: comb- ype, SIP, SFBC, and inally STBC.
The main ecommenda ions o u u e wo k a e o in es iga e he e ec s o he numbe o
subca ie (Ns), numbe o pilo s (Np), channel leng h (L), and no malized Dopple equency
( dTOFDM) on he pe o mance o hese echniques. Fu he mo e, i is also aluable o compa e he
pe o mance o hese echniques agains o he channel es ima ion echniques in a ious wi eless
communica ion en i onmen s and sys em condi ions.
REFERENCES
[1] Yong Soo Cho, Jaekwon Kim, Won Young Yang, Chung G. Kang. MIMO-OFDM Wi eless
Communica ions wi h MATLab, John Wiley & Sons, Augus 2010.
[2] Sunho Pa k, Byonghyo Shim, and Jun Won Choi. I e a i e Channel Es ima ion Using Vi ual Pilo
Signals o MIMO-OFDM Sys ems. IEEE T ansac ions on Signal P ocessing, Vol. 63, Issue: 12, pp.
3032 - 3045, June 2015.
[3] Nisha Ach a, Ga ima Ma hu , R. P. Yada . Pe o mance Analysis o MIMO-OFDM Sys em o
Di e en Modula ion Schemes unde Va ious Fading Channels. In e na ional Jou nal o Ad anced
Resea ch in Compu e and Communica ion Enginee ing, Vol. 2, Issue 5, May 2013.
[5] V. Si anaga aju and P. Siddaaih. Comp ehensi e Analysis o BER and SNR in OFDM Sys ems.
In e na ional Jou nal o Inno a i e Resea ch in Compu e and Communica ion Enginee ing
(IJIRCCE), Volume 2, Issue 2, Feb ua y 2014.
[6] Ni in Kuma Chou asiya and Aman Sa a . A Re iew Channel Es ima ion Technique o MIMO-
OFDM Wi eless Sys ems. In e na ional Jou nal on Eme ging Technologies, Vol. 8, No. 1, pp. 20-24,
2017.
[7] Vishal Sha ma and Ha leen Kau . On BER E alua ion o MIMO-OFDM Inco po a ed Wi eless
Sys em. In e na ional Jou nal o Ligh and Elec on Op ics, Vol. 127, Issue 1, pp. 203-205, Janua y
2016.
[8] Vijaykuma Ka gi. Compa ison o MIMO OFDM Sys em wi h BPSK and QPSK Modula ion.
In e na ional Jou nal on Eme ging Technologies, Vol. 6, No. 2, pp. 188-192, 2015.
[9] Sha ie Nas Abdel-Razeq, A eej Salah Al-Azzeh, Rawan Youse Ayyoub. S udy o QPSK Modula o
and Demodula o in Wi eless Communica ion Sys em Using MATLab. In e na ional Jou nal o
In e ac i e Mobile Technologies (iJIM), Vol. 7, No. 2, pp. 4-8, 2013.
h p://dx.doi.o g/10.3991/ijim. 7i2.2239.
[10] Ma hu ana han Viswana han. Digi al Modula ions using MATLab: Build Simula ion Models om
Sc a ch. E-book, June, 2017.
[11] Saga Somasheka , Na een K.D. Venka egowda, and Adi ya K.Jaganna ham. Bandwid h E icien
Op imal Supe imposed Pilo Design o Channel Es ima ion in OSTBC-Based MIMO–OFDM
Sys ems. Jou nal o Physical Communica ion, Vol. 26, pp. 185-195, Feb ua y 2018.
[12] Umesha G B and M N Shanmukha Swamy. Comb-Type Pilo A angemen Based Channel Es ima ion
o Spa ial Mul iplexing MIMO-OFDM Sys ems. In e na ional Resea ch Jou nal o Enginee ing and
Technology (IRJET), Vol. 5, Issue 2, pp. 641-645, Feb ua y 2018.
In e na ional Jou nal o Mobile Ne wo k Communica ions & Telema ics ( IJMNCT), Vol.9, No.4/5, Oc obe 2019
9
[13] Gau a Mau ya and P amod Pa el. An Ex ensi e Re iew on STBC o MIMO-OFDM Sys em.
In e na ional Jou nal o Eme ging Technology and Ad anced Enginee ing (IJETAE), Vol. 4, Issue-8,
pp. 352-357, Augus 2014.
[14] Nee aj Sh i as a a and Adi ya T i edi. Combined Beam o ming wi h Space-Time-F equency Coding
o MIMO–OFDM Sys ems. AEU - In e na ional Jou nal o Elec onics and Communica ions, Vol.
69, Issue 6, pp. 878-883, June 2015.
[15] Madh i Jangalwa. Pe o mance Analysis o MIMO-OFDM sys em wi h Ze o Fo cing Recei e .
In e na ional Jou nal o Mul idisciplina y and Cu en Resea ch, Sep embe -Oc obe Issue, 2013.
[16] Mamunu Rashid and Saddam Hossain. A Po en MIMO–OFDM Sys em Designed o Op imum BER
and i s Pe o mance Analysis in AWGN Channel. In e na ional Jou nal o Enginee ing Science
In en ion (IJESI), Vol. 4, Issue 8, pp. 44-50, Augus 2015.
[17] A ul Kuma Pandey, San osh Sha ma, and Nee u Sika wa . Imp o emen o BER wi h The Help o
MIMO-OFDM using STBC Code S uc u e. In e na ional Jou nal o Enginee ing Resea ch &
Technology (IJERT), Vol. 2, Issue 5, May 2013.
[18] Niha ika Se hy and Subhakan a Swain. BER Analysis o MIMO-OFDM Sys em in Di e en Fading
Channe. In e na ional Jou nal o Applica ion o Inno a ion in Enginee ing and Managemen , Vol. 2,
Issue 4, pp. 405-409, Ap il 2013.
[19] B. Si a Kuma Reddy and B. Lakshmi. BER Analysis wi h Adap i e Modula ion Coding in MIMO-
OFDM o WiMAX using GNU Radio. In e na ional Jou nal Wi eless and Mic owa e Technologies,
No embe 2014.
[20] S ish ansh Pa hak and Himanshu Sha ma. Channel Es ima ion in OFDM Sys ems. In e na ional
Jou nal o Ad anced Resea ch in Compu e Science and So wa e Enginee ing (IJARCSSE), Vol.3,
No.3, pp. 312-327, 2013.
[21] S. Pa il and A. N. Jadha . Channel Es ima ion Using LS and MMSE Es ima o s. KIET In e na ional
Jou nal o Communica ions & Elec onics, Vol. 2, No.1, pp. 51-55, Ap il 2014.
[22] Himanshi Jain and Vikas Nandal. A Compa ison o Va ious Channel Es ima ion Techniques o
Imp o e Fading E ec s in MIMO o e Di e en Fading Channels. In e na ional Jou nal o Cu en
Enginee ing and Technology (IJCET), Vol. 6, No. 4, pp. 1382-1386, 2016.
[23] Oma Daoud, Qad i Hama sheh, and Wael Al-Sawalmeh. MIMO-OFDM Sys ems Pe o mance
Enhancemen Based Peaks De ec ion Algo i hm. In e na ional Jou nal o In e ac i e Mobile
Technologies (iJIM), Vol. 7, No. 3, pp. 4-8, 2013. h p://dx.doi.o g/10.3991/ijim. 7i3.2302.
[24] Oma Daoud and Oma Alani. Robo ic Mobile Sys em's Pe o mance-Based MIMO-OFDM
Technology. In e na ional Jou nal o In e ac i e Mobile Technologies (iJIM), Vol. 3, pp.12-17, 2009.
h p://online-jou nals.o g/index.php/i-jim/a icle/ iew/923.
[25] Nimay Ch. Gi i, Anwesha Sahoo, J. R. Swain, P. Kuma , A. Nayak, P. Debogoswami. Capaci y and
Pe o mance Compa ison o SISO and MIMO Sys em o Nex Gene a ion Ne wo k (NGN).
In e na ional Jou nal o Ad anced Resea ch in Compu e Enginee ing & Technology (IJARCET),
Vol. 3, Issue 9, pp. 30131-3035, 2014.
[26] O. Longo ia-Ganda a, R. Pa a-Michel, R.Ca asco-Al a ez, and E. Rome o-Agui e. I e a i e MIMO
De ec ion and Channel Es ima ion Using Join Supe imposed and Pilo -Aided T aining. Jou nal o
Mobile In o ma ion Sys ems, Vol. 2016, A icle ID 3723862, 2016.
