Symbol Error Performance Analysis of OFDM … Error Performance Analysis of OFDM Receiver with Pulse...

Symbol Error Performance Analysis of OFDM Receiver

with Pulse Blanking over Frequency Selective Fading

Channel

Haitao. Liu1, Zhisheng. Yin

1, and Xuejun. Zhang

2

1 Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin 30030, China

2 College of Electronic and Information Engineering, BeiHang University, Beijing 100191, China

Email: [email protected]; [email protected]; [email protected]

Abstract—Pulse blanking is a widely used method to eliminate

impulsive interference in orthogonal frequency division

multiplexing (OFDM) receiver. To analyze the effect of Inter

Carrier Interference (ICI) caused by pulse blanking on the

performance of symbol error rate (SER) for OFDM receiver, the

analytical expression of signal to noise ratio (SNR) for OFDM

receiver with pulse blanking is derived. The SER of OFDM

receiver with pulse blanking over AWGN, Rayleigh and Ricean

fading channel are also analyzed quantitatively based on the

SNR expression. Simulation results validate the accuracy of our

derived formulas. Index Terms—OFDM, impulse interference, pulse blanking;

SNR, SER, AWGN, rayleigh, ricean

I. INTRODUCTION

Orthogonal Frequency Division Multiplexing (OFDM)

is a multicarrier modulation technique which converts a

frequency-selective channel into a parallel collection of

frequency flat subchannels. OFDM has several

advantages over single-carrier communication systems,

such as spectral efficiency, efficient implementation

based on fast Fourier transform (FFT), and simple

channel equalization. Thus OFDM transmission scheme

is widely employed in wireless and wired

communications, e.g. Digital Subscriber Lines (DSL),

Digital Video Broadcasting (DVB), Digital Audio

Broadcasting (DAB), Wireless Local Area Networks

(WLAN), Power Line Communications (PLC), Long

Term Evolution (LTE), L-band Digital Aeronautical

Communication system (L-DACS) [1].

In general, OFDM systems are often exposed to

impulsive interference, e.g. ignition noise of passing

vehicles, powerline impulsive noise, or other systems

operating in the same frequency range. Some studies have

shown that the impulse interference with high power or

frequent occurrence can significantly affect the

performance of the OFDM receiver [2]-[4]. Thus, the

interference mitigation techniques have to be

implemented.

Manuscript received September 16, 2015; revised March 9, 2016. Corresponding author email: [email protected].

doi:10.12720/jcm.11.3.325-332

To improve the reliability of OFDM receiver exposed

to impulsive noise, an interference mitigation method

based on pulse blanking is firstly proposed in [5]. An

optimal threshold of pulse blanking is presented based on

the analytical expression of SNR for OFDM receiver [6].

With maximizing signal-to-interference-and-noise ratio

criterion, adaptive blanking threshold of impulse blanking

for OFDM receiver is proposed in [7]. To eliminate the

Inter Carrier Interference (ICI) caused by pulse blanking

of OFDM receiver, an iterative reconstructing and

subtracting ICI method is proposed in [8], [9], and a

frequency-domain ICI compensation scheme based on

FIR equalizer is also proposed in [10]. Based on

Bernoulli-Gaussian impulsive noise model, the

performance analysis of multicarrier and single carrier

communication systems is given in [2], [3], furthermore,

the influence of impulse noise on the SER performance of

multicarrier and single carrier communication systems is

also presented. The analytical expression of SNR for

OFDM receiver with impulse blanking is derived in

AWGN channel [11], however, the SER performance of

OFDM receiver with pulse blanking is not presented.

Unlike the method used in [11], in this paper, a new

analytical expression of SNR for OFDM receiver with

pulse blanking is derived. The SER performance of

OFDM receiver with pulse blanking over AWGN,

Rayleigh and Ricean fading channel are also derived

based on the SNR expression. Finally, the simulation

results validate the accuracy of our derived formulas.

II. SYSTEM MODEL

A. OFDM Transmitter

The model of an OFDM transmitter is depicted in Fig.

1. Information bit sequence I is sent to modulator for

symbol mapping. The output symbol vector of the

modulator is denoted as 0 1,..., ,...,T

k KS S S S , where

K is the number of complex modulated symbols. The

modulated symbols , 0,..., 1kS k K are assumed to

be independent and identically distributed (i.i.d.) with

0kE S and 2 2

k SE S , where E denotes

expectation operator.

325

Journal of Communications Vol. 11, No. 3, March 2016

©2016 Journal of Communications

I s xS ( )x t

Infor-

mation

source

Modu-

latorIFFT

Insert

CP

RF

front-

end

D/A

Conve

-rter

Fig. 1. Model of OFDM transmitter

The modulated symbol vector S is then transformed

into time domain by K-point inverse fast Fourier

Transform (IFFT). Thus the IFFT output signal vector

0 1,..., ,...,T

n Ks s s s is given by

H s F S (1)

where IFFT matrix HF is defined by

2

,

1, , 0, , 1

k nj

H Kn k e n k K

K

F (2)

with k being the subcarrier index in the frequency domain

and n denoting the sample index in the time domain.

Considering IFFT is an unitary transformation, the

statistical property of s agrees with S . Thus

, 0,..., 1ns n K are also i.i.d. with 0nE s and

2 2

n SE s .

After inserting Kg-point cyclic prefix, the transmitted

signal vector 0 1[x ,..., x ,..., x ]g

T

n K K x can be

expressed as

in x P s (3)

where inP is the cyclic prefix insertion matrix denoted as

( )

( )

g g g

g

K K K K

in

K K K K

0 IP

I (4)

The transmitted signal vector x is converted to analog

signal ( )x t by D/A converter and then ( )x t is

transformed into RF signal by RF front-end. Finally, the

RF signal is sent to channel by transmitter antenna.

B

z yr Y

RF

front-

end

A/D

Conv-

ertor

Rem-

ove

CP

Pulse

Blank-

ing

Equal-

izerFFT

( )r t y I

Infor-

mation

source

Demo-

dulat-

or

Interf-

erence

Detec-

tor

Channel

Estimat-

ion

kH

Fig. 2. Model of OFDM receiver with pulse blanking

B. OFDM Receiver with Pulse Blanking

The model of the OFDM receiver with pulse blanking

is depicted in Fig. 2. The RF signal from receiver antenna

is converted into baseband signal by RF front-end. The

baseband signal ( )r t can be represented as

( ) ( ) ( ) ( ) ( )r t x t h t n t i t (5)

where ( )x t denotes the transmitted signal, denotes

convolution operation, ( )h t denotes the channel impulse

response, ( )n t denotes the complex Gaussian white noise

signal, and ( )i t denotes the impulsive noise.

Assuming that the symbol timing synchronization

isestablished, the A/D converter output signal vector is

denoted as r . After removing Kg-point cyclic prefix, the

received signal vector 0 1[ ,..., ,..., ]T

n Kz z z z can be

expressed as

out z P r (6)

where [ ]gout K K KP 0 I denotes the cyclic prefix

removal matrix. According to the basic theory of the

OFDM technology [12], z can be written as

z s h n i (7)

where s is given by Eq.(1), denotes circular

convolution, 0 1,..., ,...,l Lh h h h denotes discrete-time

channel impulse response with L paths, where

, 0,..., 1lh l L are assumed to be statistically

independent and that remains constant over one OFDM

symbol interval., without loss of generality, the channel

power is normalized to 1, i.e.

1

2

0

1L

l

l

E h

,0 1[ ,..., ,..., ]T

n Kn n n n denotes the

complex Gaussian white noise vector where

, 0,..., 1nn n K are i.i.d complex Gaussian random

variables of mean zeros and variance 2

n ,

0 1,..., ,...,T

n Ki i i i denotes the impulsive noise vector

where ni is a Bernoulli-Gaussian variable modeled as[10]

, 0,1,..., 1n n ni b g n K (8)

where , 1,..., 1nb n K are i.i.d. Bernoulli random

variables with probability rP 1nb p and

, 0,..., 1ng n K are i.i.d. complex Gaussian random

variables of mean zeros and variance 2

g .

Assuming that the positions of impulsive noise

occurrence are precisely detected by OFDM receiver, the

output of impulse blanking is given as

0 1[y ,..., y ,..., y ]T

n Ky

y B z (9)

where 0 1,..., ,...,n Kdiag b b b B denotes the diagonal

matrix of impulse blanking with 1n nb b .

The signal vector y is then transformed into

frequency domain by a K-point fast Fourier transform

(FFT). Thus the FFT output signal vector

0 1,..., ,...,T

k KY Y Y Y is given by

326



Y = F y (10)

where the FFT matrix F is defined by

2

,

1, , 0,..., 1

k nj

Kk n e k n K

K

F (11)

Assuming that ideal channel estimation is employed,

the output of linear forced zero equalizer is given as

0 1[ ,..., ,..., ]T

k KY Y Y Y , where kY denotes the output of

k-th subchannel, which is given by

*

2, 0,..., 1k

k k

k

HY Y k N

H (12)

The signal vector Y is sent to demodulator, finally, the

demodulator output bit sequence I is sent to the sink.

III. PERFORMANCE ANALYSIS

A. SNR for OFDM Demodulator with Pulse Blanking

Substituting Eq. (7) into Eq. (9), the output signal

vector of pulse blanking can be represented as

y B s h B n B i (13)

where 0 0 1 1diag ,..., ,...,n n K Kb i b i b i B i with the

n-th term represented as

1 , 0,1,..., 1n n n n nb i b b g n K (14)

Since nb is a Bernoulli random variable with value one

or zero, the product 1 n nb b identically equals to 0.

Thus, 0, 0,1,..., 1n nb i n K , and then B i 0 .

Given all above, Eq. (13) is further simplified as

y s h i n (15)

where i B I s h denotes the equivalent

impulse noise vector with the n-th component ni

represented as

1

mod0

K

n n m n m Km

i b s h

(16)

and n B n denotes the complex Gaussian white noise

vector at the output of pulse blanking with the n-th

component nn represented as

1n n nn b n (17)

Substituting Eq. (14) into Eq. (10) yields

Y S H F i F n (18)

where 0 1,.., ,...,k Kdiag H H H H denotes the

frequency domain channel transfer matrix where kH

denotes the frequency response of the k-th subchannel.

Expanding Eq. (18), the k-th component of Y can be

expressed as

1 12 2

0 0

1 1k n k nK Kj jK K

k k k n n

n n

Y S H i e n eK K

(19)

From Eq. (19), kY can be split into two parts. The first

part contains the desired signal of the k-th subchannel,

which is defined as kE , and the second part contains

noise and the ICI caused by pulse blanking, which is

defined as kW . kY can be further expressed as

k k kY E W (20)

where

k k kE S H (21)

1 12 2

0 0

1 1k n k nK Kj jK K

k n n

n n

W i e n eK K

(22)

The variance of kE is calculated as

2 2

ar k k SV E H (23)

According to appendix A, the variance of kW can be

calculated as

2 21ar k S nV W p p (24)

Combining Eq. (22) and Eq. (23), the instantaneous

Signal-to-Noise Ratio (SNR) of the k-th subchannel for

OFDM receiver with pulse blanking is given by

22

2 2

( )SNR

( )

, 0,..., 11

ar k

k

ar k

S

k

S n

V E

V W

H k Kp p

(25)

B. SER of OFDM Receiver with Pulse Blanking over

AWGN Channel

In terms of AWGN channel, the channel transfer

matrix 0 1diag ,.., ,...,k KH H H H is a K K

identity diagonal matrix. According to Eq.(24), the SNR

of the k-th subchannel for OFDM receiver with pulse

blanking is given by

2

/ 2 2, 0,..., 1

1

S

k B

S n

k Kp p

(26)

By using the result in [13], the SER of the k-th

subchannel for OFDM receiver with pulse blanking in

case of M-PSK modulation can be expressed as

2

1

, / 20

sin π1exp d

sin

M MMPSK

k AWGN k B

MP

(27)

And the SER of the k-th subchannel for OFDM

receiver with pulse blanking in case of M-QAM

modulation can be expressed as

327



/

,

/

314

1

311

1

MQAM k B

k AWGN

k B

MP Q

MM

MQ

MM

(28)

where Q is the Gaussian Q-function defined as [14]

2

2

20

1exp d

2sin

xQ x

(29)

Considering each subchannel of OFDM receiver has

the same SER performance, the average SER is obtained

as

1

,

0

,

1 K

AWGN k AWGN

k

k AWGN

P PK

P

(30)

where ,k AWGN is given by Eq. (27) or (28). Based on

Eq. (27), (28) and (30), the following analysis can be

observed:

(1) In the SER expressions given in Eq. (27) and

Eq.(28), the SER of the k-th subchannel is independent of

subchannel index k, which indicates that the pulse

blanking has same effect on the error performance of

each subchannel of OFDM receiver;

(2) For the special case of no interference, i.e., p 0 ,

Eq.(30) reduces to the analytical expression of SER for

conventional OFDM receiver.

(3) For p 0 , in the limiting case S nSNR 2 2

approaches infinity, /lim 1k BSNR

p

, the SER in Eq.(30)

is determined only by the parameter p, therefore, there

will be an error floor for the SER performance curve.

C. SER of OFDM Receiver with Pulse Blanking over

Rayleigh Fading Channel

For the Rayleigh fading channel, the discrete-time

channel impulse response , 0,..., 1lh l L are

assumed to be i.i.d. complex Gaussian random variables,

i.e., 2~ 0, , 0,..., 1l lh l L and

12

0

1L

l

l

.

Hence, the frequency response of the k-th subchannel

1 2

0

klL jK

k l

l

H h e

is distributed according to complex

Gaussian of mean zeros and variance one. Furthermore, 2| |kH is distributed according to 2 with 2 degrees of

freedom and 2| | 1kE H .

According to Eq. (25), the instantaneous SNR of the k-

th subchannel for OFDM receiver with pulse blanking

over Rayleigh fading channel can be expressed as

22

/ 2 2, 0,..., 1

1

S

k B k

S n

H k Kp p

(31)

Considering 2 2 21S S np p is a constant

when the probability of impulsive noise occurrence p is

given, /k B is also distributed according to 2 with 2

degrees of freedom as well as 2| |kH . Then the average

SNR of the k-th subchannel for OFDM receiver with

pulse blanking can be obtained as

2

/ 2 2, 0,..., 1

1

S

k B

S n

k Kp p

(32)

By using the result in [13], the probability density

function of /k B is given by

/

/

/ /

/

1, 0

k B

k B

k B k B

k B

p e

(33)



case of M-PSK modulation over Rayleigh fading channel

can be expressed as

/

,

/

1 /

/

11

1 1 π

πtan cot

2 1

MPSK k B

k Rayleigh

k B

k B

k B

aM MP

M a M

a

a M

(34)

where 2sina M . The SER of the k-th subchannel

for OFDM receiver with pulse blanking in case of M-

QAM modulation over Rayleigh fading channel can be

expressed as

,

2

1

12 1

1 41 tan 1

π

MQAM

k Rayleigh

MP

M

M

M

(35)

where /

/

1.5

1 1.5

k B

k BM

.Thus the average SER is

obtained as

1

,

0

,

1 K

Rayleigh k Rayleigh

k

k Rayleigh

P PK

P

(36)

where ,k RayleighP is given by Eq. (34) or (35). We can

observe that the SER expresses given in Eq. (34~36)

support the analysis presented in section 3.2.

D. SER of OFDM Receiver with Pulse Blanking over

Ricean Fading Channel

For the Ricean fading channel, 0h is assumed to be

non-zero mean complex Gaussian random variable, i.e.,

328



~ , ,h u u 20 0 0 , , 1,..., 1lh l L are assumed

to be complex Gaussian random variables, i.e.,

2~ 0, , 1,..., 1l lh l L . The channel power is

normalized to 1, i.e.,

12 2

0

1L

l

l

u

, and the Ricean

factor is defined as

12 2

0

L

rice l

l

K u

. Hence, the

frequency response of the k-th subchannel kH is

distributed according to complex Gaussian with mean u

and variance

122

0

L

l

l

u

. Furthermore, 2| |kH is

distributed according to noncentral 2 with 2 degrees of

freedom and 2| | 1kE H .

According to (24), the instantaneous SNR of the k-th

subchannel for OFDM receiver with pulse blanking over

Ricean fading channel can be expressed as

22

/ 2 2, 0,..., 1

1

S

k B k

S n

H k Kp p

(37)

Considering 2 2 21S S np p is a constant

when the probability of impulsive noise occurrence p is

given, /k B is also distributed according to noncentral

2 with 2 degrees of freedom as well as 2| |kH . Then

the average SNR of the k-th subchannel for OFDM

receiver with pulse blanking /k B can be obtained as

2

/ 2 2, 0,..., 1

1

S

k B

S n

k Kp p

(38)

By using the result in [13], the probability density

function of /k Blank is given by

/

/

1

/

/

/

0

/

1

12

rice k B

k B

K

K

rice

k B

k B

rice rice k B

k B

K e ep

K KI

/, 0k B (39)

where 0I is the zero-order modified Bessel function of

the first kind. The Moment Generating Function (MGF)

of /k Blank is the Laplace transform of /k Bp with the

exponent reversed in sign, which can be obtained as

/

/ / /

0

/

/ /

1exp

1 1

k B

k B

s

k B k B

rice rice k B

rice k B rice k B

M s p e d

K K s

K s K s

(40)



case of M-PSK modulation over Ricean fading channel

can be expressed as

/

2

1 /M

, 20

πsin ( )

1= d

sink B

MMPSK

k RiceanMP M

(41)

the SER of the k-th subchannel for OFDM receiver with

pulse blanking in case of M-QAM modulation over

Ricean fading channel can be expressed as

/

/

/2

, 20

2

/4

20

4 1 3d

2 1 sinπ

4 1 3d

π 2 1 sin

k B

k B

MQAM

k Ricean

MP M

MM

MM

M M

(42)

Thus the average SER is obtained as

1

,

0

,

1 K

Ricean k Ricean

k

k Ricean

P PK

P

(43)

where ,k RiceanP is given by Eq. (40) or (41). We can

observe that the SER expressions given in Eq. (41~43)

also support the analysis presented in section 3.2.

IV. NUMERICAL RESULTS

A. System and Channel Parameters

TABLE I: SYSTEM AND CHANNEL PARAMETERS

Parameter name Value

System parameters

Modulator BPSK,16QAM

Signal bandwidth 8.192MHz

Subcarrier number 512

Data subcarrier number 512

Subcarrier interval 16KHz

Sample interval 0.122us

Cyclic prefix 16

Channel parameters

Channel models

AWGN,

Rayleigh (10 gains),

Ricean (10 gains), Krice = 5,10,15,20 dB

Impulsive noise model Bernoulli-Gaussian

Probability of interference Occurrence

P (shown in figs)

Receiver parameters

Channel estimation Ideal channel estimation

Channel equalization ZF-equalization

329



B. Symbol Error Performance Curves

In this section, we present some simulation results of

symbol error performance for AWGN, Rayleigh and

Ricean fading channels. Fig. 3-Fig. 8 show the theoretical

and simulated SER vs. SNR performance curves of

OFDM receiver with pulse blanking, where the SNR is

defined as log S nSNR 2 21010 . The theoretical

curves are obtained as follows: first, using the given

parameter p and input SNR, the average SNR of the k-th

subchannel for OFDM receiver with pulse blanking can

be obtained based on Eq. (26), (32) and (38), then, the

average SER can be obtained by using the average SNR

and Eq. (30), (36) and (43), finally, the theoretical SER

vs. SNR curves are plotted.

0 5 10 15 20 25 30 35 4010

-5

10-4

10-3

10-2

10-1

100

SNR(dB)

SE

R

theory,p=0

simulation,p=0

theory,p=0.01

simulation,p=0.01

theory,p=0.015

simulation,p=0.015

theory,p=0.02

simulation,p=0.02

Fig. 3. Symbol Error Ratio of OFDM receiver with pulse blanking (AWGN channel, 16QAM)

Fig. 3 shows the symbol error performance of OFDM

receiver with pulse blanking in case of 16QAM

modulation over AWGN channel. The figure contains

four pairs curves, which show the theoretical and

simulated SER of OFDM receiver with pulse blanking at

different p values. Based on the above observations, we

see that and simulation results show a good agreement

with theoretical calculation.

10 15 20 25 30 35 40 4510

-6

10-5

10-4

10-3

10-2

10-1

SNR(dB)

SE

R

theory,p=0

simulation,=0

theory,p=0.001

simulation,p=0.001

theory,p=0.005

simulation,p=0.005

theory,p=0.01

simulation,p=0.01

Fig. 4. Symbol Error Ratio of OFDM receiver with pulse blanking (Rayleigh channel, BPSK)

Fig. 4 and Fig. 5 show the symbol error performance

of OFDM receiver with pulse blanking in case of BPSK

and 16QAM modulation over Rayleigh fading channel.

Each figure contains four pairs curves, which show the

theoretical and simulated SER of OFDM receiver with

pulse blanking at different p values. we see that

simulation results correspond well with theoretical

calculation.

Fig. 6 show the symbol error performance of OFDM

receiver with pulse blanking in case of 16QAM

modulation over Ricean fading channel. The figure

contains four pairs curves, which show the theoretical and

simulated SER of OFDM receiver with pulse blanking for

different Ricean factor at a fixed p value. From the results,

we can observe that theoretical calculation and simulation

results coincide well.

10 15 20 25 30 35 4010

-4

10-3

10-2

10-1

100

SNR(dB)

SE

R

theory,p=0

simulation,p=0

theory,p=0.001

simulation,p=0.001

theory,p=0.005

simulation,p=0.005

theory,p=0.01

simulation,p=0.01

Fig. 5. Symbol Error Ratio of OFDM receiver with pulse blanking (Rayleigh channel, 16QAM)

10 15 20 25 30 35 4010

-6

10-5

10-4

10-3

10-2

10-1

100

theory,Krice

=20dB

simulatiion,Krice

=20dB

theory,Krice

=15dB

simulation,Krice

=15dB

theory,Krice

=10dB

simulation,Krice

=10dB

theory,Krice

=5dB

simulation,Krice

=5dB

Fig. 6. Symbol Error Ratio of OFDM receiver with pulse blanking

(Ricean channel, p=0.005, 16QAM)

V. CONCLUSIONS

In this paper, we studied the symbol error performance

of OFDM receiver with blanking. The closed-form

expression of SNR for OFDM receiver with pulse

blanking is derived. The SER of OFDM receiver with

pulse blanking over AWGN, Rayleigh and Ricean fading

channels are given. The simulation results validate the

accuracy of our derived formulas. The following

conclusions are obtained: (i) the pulse blanking has same

effect on the error performance of each subchannel of

OFDM receiver; (ii) the error floor for the SER

performance is observed for OFDM receiver with pulse

blanking and the error floor depends on the probability of

impulsive noise occurrence.

330



A

From Eq. (21), the variance of interference noise term

can be calculated as

22

ar k k kV W E W E W (A-1)

Considering that ni and nn are statistically

independent, the first term of (A-1) is reduced to

2 21 12 22

0 0

2 2

1 1k n k nK Kj jK K

k n n

n n

n n

E W E i e E n eK K

E i E n

(A-2)

By using Eq. (15) and considering mb , ms and

modn m Kh

are statistically independent, the first term of

(A-2) can be expressed as

21

2

mod0

1 22 2

mod0

12 2 2

0

2

K

n n m n m Km

K

n m n m Km

L

n m l

l

S

E i E b s h

E b E s E h

E b E s E h

p

(A-3)

Taking into account that nb is independent of nn , the

second term of (A-2) can be expressed as

22

2 2

2

1

1

1

n n n

n n

n

E n E b n

E b E n

p

(A-4)

By using Eq.(15) and (16), and keeping 0mE s

and 0nE n in mind, it is easy to find 0nE i and

0nE n . Further, the second term of (A-1) can be

calculated as 2

0kE W . Finally, the variance of the

interference noise term kW can be obtained as

2 21ar k S nV W p p (A-5)

ACKNOWLEDGMENT

This work was supported in part by National Natural

Science Foundation of China under Grants

(No.U1233117, No.61271404), and Open Fund of Tianjin

Key Laboratory for Advanced Signal Processing Program

(No.2015AFS04).

REFERENCES

[1] N. Neji, A. Azoulay, and T. Letertre, “Survey on the future

aeronautical communication system and its development

for continental communications,” IEEE Trans. on

Vehicular Technology, vol. 62, pp. 182-191, Jan. 2013.

[2] M. Ghosh, L. Philips, M. Briarcliff, et al., “Analysis of the

effect of impulsive noise on multicarrier and single carrier

QAM systems,” IEEE Trans. on Communications, vol. 44,

pp. 145–147, Feb. 1996.

[3] Y. H. Ma, P. L. SO, and E. Gunawan, “Performance

analysis of OFDM systems for broadband power line

communications under impulsive noise and multipath

effects,” IEEE Trans. on Power Delivery, vol. 20, pp. 674-

682, April 2005.

[4] K. M. Rabie and E. Alsusa, “Effective noise cancellation

using single-carrier FDMA transmission in PLC,” IEEE

Trans. on Power Delivery, vol. 29, pp. 2110-2117, Oct.

2014.

[5] P. Haffenden, “Detection and removal of clipping in

multicarrier receivers,” Eur. Patent 1043874, Oct. 2000.

[6] S. V. Zhidkov, “Performance analysis and optimization of

OFDM receiver with blanking nonlinearity in impulsive

noise environment,” IEEE Trans. on Vehicular Technology,

vol. 55, pp. 234-242, Jan. 2006.

[7] U. Epple and M. Schnell, “Adaptive threshold

optimization for a blanking nonlinearity in OFDM

Receivers,” in Proc. GLOBECOM, Anaheim, CA, 2012,

pp. 3661-3666.

[8] S. Brandes, U. Epple, and M. Schnell, “Compensation of

the impact of interference mitigation by pulse blanking in

OFDM systems,” presented at the IEEE Global

Telecommunications Conference, Honolulu, HI, Nov. 1-6,

2009.

[9] Y. Chi-Hsiao, “Iterative interference cancellation for

OFDM signals with blanking nonlinearity in impulsive

noise channels,” IEEE Signal Processing Letters, vol. 19,

pp. 147-150, March 2012.

[10] D. Darsena, G. Gelli, F. Melito, et al., “ICI-Free

Equalization in OFDM Systems with Blanking Pre

processing at the receiver for impulsive noise mitigation,”

IEEE Signal Processing Letters, vol. 22, pp. 1321-1325,

Sept. 2015.

[11] U. Epple, K. Shibli, and M. Schnell, “Investigation of

blanking nonlinearity in OFDM systems,” presented at the

IEEE International Conference, Kyoto, June 1-5, 2011.

[12] Y. Li and G. Stuber, Orthogonal Frequency Division

Multiplexing for Wireless Communications, NY: Springer,

2006, ch. 2, pp. 19-45.

[13] J. G. Proakis, Digital Communications, 4st ed. Beijing:

Publishing House of Electronics Industry, 2011, ch. 5, pp.

231-313.

[14] K. M. Simon and M. S. Alouini, Digital Communications

Over Fading Channels, 2st ed. New York: John Wiley &

Sons, 2005, ch. 8-9, pp. 193-432.

Hai-Tao Liu received his B.E. degree

from Xidian University, China in 1988,

his M.S. degree from Beijing University

of Aeronautics & Astronautics, China in

1997, and his Ph.D. degree from Beijing

University of Post and

Telecommunications, China in 2006.

From 2006 to 2008, He was a

331



PPENDIX A

postdoctoral fellow in Potevio Information Technology Co. Ltd.

China. He is a Professor in the School of Electronic and

Information Engineering in Civil Aviation University of

China ， His research interests include aviation mobile

communications system and broadband mobile communication

system. The corresponding author. Email: [email protected].

Zhi-Sheng Yin was born in 1990. He is

currently a M.S. candidate in School of

Electronic and Information Engineering

in Civil Aviation University of China.

His recent research interests include

aviation mobile communications system.

Xue-Jun Zhang received his Ph.D.

degree from Beijing University of

Aeronautics & Astronautics, china in

2000. He is a Professor in the School of

Electronic and Information Engineering

in Beihang University. His research

interests include aviation mobile

communication systems and modern air

traffic management technology.

332



mailto:[email protected]

Date post:	07-Sep-2018
Category:	Documents
Upload:	phamminh
View:	257 times
Download:	0 times

Symbol Error Performance Analysis of OFDM … Error Performance Analysis of OFDM Receiver with Pulse...

Documents