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Integer Frequency Offset Algorithm for Digital Radio
Mondiale System
Cheng Yan and Ming Yan Communication University of China, Beijing, China
Email: [email protected]; [email protected];
Abstract—This paper proposes one integer frequency offset
estimation algorithm for orthogonal frequency division
multiplexing (OFDM) based digital radio mondiale (DRM)
system. The algorithm exploits the correlation of frequency
pilots to construct a novel angle vector. As the power factor of
the pilots in the correlated calculation is inevitably disturbed by
the multipath and noise, the angle vector only utilizes the phase
factor of the pilots. The integer frequency offset can be obtained
by detecting the shift of the vector norm of the pilots, because
the vector norm is maximum at the position of the pilots. The
performance of the proposed algorithm is compared with that of
conventional algorithms. The simulation results show that the
proposed algorithm can effectively combat multipath and noise
with wider range and higher accuracy of the frequency offset
estimation. Index Terms—Digital radio mondiale, orthogonal frequency
division multiplexing, integer frequency offset
I. INTRODUCTION
The DRM system utilizes OFDM modulation [1].
OFDM as an orthogonal multi-carrier modulation system
is much more sensitive to carrier frequency offset than
the single-carrier system. As the carrier frequency offset
can destroy the orthogonality of sub-carriers and bring
the inter-carrier interference (ICI), the frequency
synchronization is particularly important to OFDM
system.
The carrier frequency offset (CFO) estimation is
usually divided into two parts: integer frequency offset
(IFO) [2]-[4] and fractional frequency offset (FFO) [5]-
[9]. Lots of research has been done for OFDM frequency
synchronization algorithms. Basically, they are
summarized into two categories: the training sequence
assisted and non-data assisted.
The non-data assisted algorithm, for example, ML
(maximum likelihood) based on CP (cyclic prefix). With
the help of the correlation between the CP and the back
portion of the OFDM symbol, the algorithm can complete
the symbol synchronization estimation [10]. As the
frequency offset estimation range | | 0.5 which is
normalized to the sample interval, the algorithm can’t do
integer frequency offset estimation [11].
The method based on the training sequence is the joint
estimation of time and frequency. To get accurate integer
Corresponding author email: [email protected].
frequency offset, the estimation of time-delay and the
fractional frequency offset are necessary. S&C [12] is
proposed by T. M. Schmidl and D. C. Cox, in which the
presence of peak platforms leads to the vague timing
synchronization. Minn [13] re-designs the first two
OFDM symbols, and the algorithm eliminates the flat
effect of the timing metric function. However, the method
has a large root mean square error in multipath channel,
and in a quarter of the cyclic prefix to the number of
subcarriers, the performance is not satisfactory. Park [14]
proposes one synchronization algorithm which can
produce a sharp peak. However it would be accompanied
by side peaks. Conventional synchronization algorithm
based on the correlated property of the time-domain
pseudo-noise (PN) sequence may not work well in
multipath channels. An algorithm is proposed in [15]
where the PN sequence in the frame head is considered as
a CP of the OFDM training symbol. The frequency
synchronization algorithm based on the training sequence
develops the synchronization performance by increasing
the system overhead with the low spectrum utilization
and limited estimated range.
This paper will focus on the integer frequency offset
estimation algorithm for DRM receiver [16]. Basically,
they are summarized into two categories: the time pilot
reference and frequency pilot reference. The problem of
frequency offset estimation has been widely explored, but
there is still room for a better estimator which has a wider
range and higher accuracy.
The section II mainly introduces the DRM system
model. The section III describes the conventional
frequency synchronization algorithm for DRM system.
The section IV will introduce the proposed algorithm.
Finally, the proposed algorithm is verified by simulation.
II. THE DRM SYSTEM MODEL
The DRM system utilizes the OFDM modulation. At
the transmitter, an OFDM symbol ( ), [ , 1]gx n n N N ,
is generated by performing an N-point inverse fast fourier
transform (IFFT) on the information symbol X(k) for
maxmin[ , ]k k k and adding Ng cyclic prefix samples. The
reference parameters of min
k and maxk are shown in the
Table I. The numerical values of the OFDM parameters
are shown in the table II [1].
Journal of Communications Vol. 8, No. 9, September 2013
572©2013 Engineering and Technology Publishing
doi:10.12720/jcm.8.9.572-578
Manuscript received July 12, 2013; revised September 21, 2013.
max
min
2 /1( ) ( )
kj kn N
k kx n X k e
N
. (1)
TABLE I: CARRIER NUMBERS FOR EACH MODE
Robust
Mode
Carrier Spectrum occupancy patterns
0 1 2 3 4
A Kmin 2 2 -102 -114 -98
Kmax 102 114 102 114 314
B Kmin 1 1 -91 -103 -87 Kmax 91 103 91 103 279
C Kmin - - - -69 -
Kmax - - - 69 - D Kmin - - - -44 -
Kmax - - - 44 -
TABLE II: NUMERICAL VALUES OF THE OFDM PARAMETERS
Robust
Mode
Tu (ms) Tg(ms) Ts(ms)
A 24 2.6 26.66 B 21.33 5.33 26.66
C 14.66 5.33 20
D 9.33 7.33 16.66
where Ts is the OFDM symbol period, Tg is the cyclic
prefix, Tu is the useful part of OFDM symbol.
After passing over DRM channel with Nt paths, the
receiver symbol:
,
12 /
( ) ( ( ) ( )) ( )
0L t L
L L
Nt j n Nz n h n x n e w n
t
. (2)
where L is the symbol index, is the frequency offset
normalized to carrier spacing which can be divided into
two parts: IFOinteger
and FFOfraction
f ,,
( )L t
h n is the
channel impulse response of the tth path, ( )L
w n is the
contribution of the AWGN.
The receiver symbol in the frequency domain can be
expressed:
( ) ( ) ( ) ( )L L L L
Z k H k X k W k . (3)
.
12 /
( ) ( )
0L t
L
Nt j k NtH k H k e
t
. (4)
where ,
( )L t
H k : the channel frequency response of the tth
path, t :the time-delay normalized to sample interval of
the tth path , ( )LW k : the AWGN.
III. THE CONVENTIONAL FREQUENCY
SYNCHRONIZATION FOR DRM
The carrier frequency offset is usually divided into
integer part and fractional part, and it can be calculated
respectively. With the influence of the fractional
frequency offset, the accuracy of integer frequency offset
estimation will greatly decrease.
The fractional frequency offset estimation can use the
most commonly used algorithm: ML (maximum
likelihood).
Figure 1. The transmitted symbols
argm
ax
2.
22
.2
( )z n NZ
*.
(.)
(.)
.
1
2
fractionf
ML
Summation
Summation
Figure 2. The fractional frequency offset acquisition algorithm
Define two sets:
{ ,......, 1}gI N (5)
' { ,......, 1}gI N N N (6)
where I is cyclic prefix of the symbol L. According to
the features of cyclic prefix, it contains the same elements
in 'I .
2 2
s
* 2
s
- j2
+ = 0
{ (n) (n+ m)} = ,
0
w
fractionf
d d m
E z z d e m N n I
others
(7)
where 2
sd and 2
wd denote the energy of the useful symbol
and Gaussian white noise. The algorithm is shown in Fig.
2.
arg max(| ( ) | - | ( ) |)ML
(8)
-1
*( ) ( ) ( )n Ng
n
z n z n N
(9)
-11 2 2( ) ( ( ) ( ))2
n N g
n
z n z n N
(10)
symbol
L
Symbol
L-1
symbol
L+1
I
'I
Journal of Communications Vol. 8, No. 9, September 2013
573©2013 Engineering and Technology Publishing
where SNR
=SNR+1
, SNR is Signal to Noise Ratio, ML is
the estimation of time-delay. So, the fractional frequency
offset is:
1
( )2
fraction MLf
(11)
2
(n) (n) fractionj f n N
L Ly z e
(12)
where (n)L
y is the receiver symbol which eliminates
fractional frequency offset. Making FFT (Fast Fourier
Transform) operation on (n)L
y and removing the cyclic
prefix, we can get (n)L
Y .
A. The Integer Frequency Offset Estimation based on
Time Pilots
Define a TRC (time reference cell) as:
2 ( ) /1024( ) 2 j kP k e k (13)
where 2 is a pilot boost factor and 2 ( ) /1024k
denotes a predefined phase rotation of the pilot cell.
denotes the set of TRC indices. The exact position and
phase rotation of the TRCs are depicted in [1].
The traditional integer frequency synchronization
algorithm based on the time pilot exploits the correlation
of the time pilots and receiver symbol [17].
*int
| |
{| ( ) ( ) |}arg maxL Neger
kd F
Y k d P k
(14)
where ( )N is modular arithmetic, is the modulus
operation, F is the maximum allowable ofinteger
, d is
the trial value of integer
, *(.) denotes the complex
conjugation.
*
2 /2
*
( ) ( )
{ ( ) | ( ) |
( ) ( )}
L N
L
L
k
j k N
k
Y k d P k
H k P k e
W k P k
(15)
The algorithm is susceptible to multipath and noise.
The algorithm in [18] is based on the partial correlation
and splits the correlation into the B blocks ( 2 aB T , aT :
the allowed symbol time-delay error).
*int
1| |
{ | ( ) ( ) |}arg maxN
B
egerm k Bd F m
Y k d P k
.(16)
The algorithms in [17] [18] are suitable for DAB
(Digital Audio Broadcasting) system that utilizes the
block-type pilot, while they are not suitable for DRM
system because the time pilots are not uniformly
distributed. The frequency estimation algorithm in [19],
implemented by TRC partitioning for DRM systems, is
proposed. The TRC partitioning scheme is used for
weakening the effect of frequency-selective fading:
/ 2
int1 1| | ,
*{ | ( ) ( ) |}arg max
NN mc
eger Nm n k Pd F m n
Y k d P k
. (17)
where cN and / 2mN
are the numbers of pilot clusters
and sub-groups in the mth cluster, respectively, ,m nP is the
set of TRC indices, rounds the element to the nearest
integer. Note that the total number of sub-groups is
1 /2cNm mtN N [20].
B. The Integer Frequency Synchronization Algorithm
based on the Frequency Pilots
Define a FRC (frequency reference cell) as:
2 ( ) /1024( ) 2 1j kQ k e k (18)
where 2 is a pilot boost factor and 2 ( ) /1024k
denotes a predefined phase rotation of the pilot cell. 1
denotes the set of FRC indices. The exact position and
phase rotation of the FRCs are depicted in [1].
One frequency synchronization algorithm for DRM
system based on the frequency pilots is proposed by
Communications Technology Institute of Darmstadt
University. The following will introduce the algorithm
[21]:
Firstly, the algorithm should make FFT operation on
receiver symbols to estimate the power spectrum:
224 1
4
0 0
1( ( ) )( )
aver
sL
j nkNN s Ns
i naver
R k z n L i N eN
.(19)
where s gN NN , averN is the number of spectra used
for averaging. In the presence of frequency offset, the
peak of the pilot will shift .The frequency offset can be
obtained by detecting the shift of the pilots.
( ) 4 ( 1) 1g
fac
NP k k k
N (20)
int
^
( ( ))arg max4
L
k
egerd
s
s
f R d P kfacf
N (21)
where sf is the sampling rate, int
^
egerf is the estimation of
integer frequency offset.
IV. THE PROPOSED ALGORITHM
A. The Proposed Algorithm
Based on the characteristics of DRM frequency pilots,
this paper proposes one integer frequency offset
estimation algorithm for DRM. The proposed algorithm
utilizes M+1 consecutive received symbols. After the
conjugate multiplication of two adjacent symbols, the
power spectrum of corresponding carriers ( )L iPow k :
Journal of Communications Vol. 8, No. 9, September 2013
574©2013 Engineering and Technology Publishing
*
1
( ) ( ) ( )
[0, 1] [0, 1]
L i L i L i
k
Pow k Y k Y k
N i M
. (22)
where L is the index of symbols. According to (23), the
phase ( )L iPh kof ( )L iPow k
:
( ) tan( ( )) [0, 1] [0, 1]L i L iPh k ac Pow k k N i M . (23)
where tan()ac is the function of phase acquired. Define
the angle vector _Angl temp :
1
01
0
_ ( ) cos( ( ))
sin( ( ))
M
iM
i
L i
L ij
Angl temp k ph k
ph k
. (24)
where 1j . Therefore, integer frequency offset can
be obtained by (25):
int
| _ ( 1) | | _ ( 2) |arg max
| _ ( 3) |N N
N
egerd
Angl temp d k Angl temp d k
Angl temp d k
[0, 1]d N . (25)
where d is the trial value of integer
, 1, 2, 3k k k are the
position of the frequency pilots without frequency offset.
Finally, combined with the fractional part, the actual
frequency offset is
int
ˆfraction egerf . (26)
B. The algorithm analysis
Before the estimation of integer frequency offset, the
time-delay and fractional frequency offset have been
already compensated. The proposed algorithm exploits
the known correlation of frequency pilots.
*
1
int int
1int
*
1int
( 1 )
( 1 ) ( 1 )
( ( 1 ) ( 1 )
( 1 ) )( ( 1 )
( 1 ) ( 1 ) )
L iN
L iN L i N
L ieger N eger N
L i L iN eger N
L ieger N N
Pow k d
Y k d Y k d
H k d Q k d
W k d H k d
Q k d W k d
(27)
*
1
int int
1int
*
1int
( 2 )
( 2 ) ( 2 )
( ( 2 ) ( 2 )
( 2 ) )( ( 2 )
( 2 ) ( 2 ) )
L iN
L iN L i N
L ieger N eger N
L i L iN eger N
L ieger N N
Pow k d
Y k d Y k d
H k d Q k d
W k d H k d
Q k d W k d
(28)
*
1
int int
1int
*
1int
( 3 )
( 3 ) ( 3 )
( ( 3 ) ( 3 )
( 3 ) )( ( 3 )
( 3 ) ( 3 ) )
L iN
L iN L i N
L ieger N eger N
L i L iN eger N
L ieger N N
Pow k d
Y k d Y k d
H k d Q k d
W k d H k d
Q k d W k d
(29)
If int eger
d , according to (18):
*
int nt
2 ( 1 ) /1024int
2 ( 1 ) /1024int
( 1 ) ( 1 )i
2
2
2
eger N eger N
j k d Neger
j k d Neger
Q k d Q k d
e
e
. (30)
The ( 1 )L iN
Pow k d can be expressed as :
int
*
1 int
( 1 ) 2 ( 1 )
( 1 )
( 1 )
L i L iN eger N
L i eger N
N
Pow k d H k d
H k d
WN k d
. (31)
int
*
1int
*
1
*
1 int
*
int
( 1 ) ( 1 )
( 1 ) ( 1 )
( 1 ) ( 1 )
( 1 )
( 1 ) ( 1 )
L iN eger N
L ieger N N
L i L iN N
L i eger N
L ieger N N
WN k d H k d
Q k d W k d
W k d W k d
H k d
Q k d W k d
. (32)
According to the DRM channel parameters:
maxsT . (33)
where max is the maximum time-delay. So the DRM
channel is flat-fading in the frequency domain [22].
When the SNR is high, the ( 1 )L iN
Pow k d can be
expressed as :
2
int( 1 ) 2 | ( 1 ) |L i L i
N eger NPow k d H k d . (34)
So the ( )L iPh k at the position of the pilots can be
expressed as :
( ) 0 [ 1, 2, 3]L i N
ph k d k k k k
. (35)
1
1
2
2
1
2
1
2 2(
2 2( (1 1
| _ ( ) |
(cos( ( )) ... cos( ( )))
(sin( ( )) ... sin( ( )))
cos ( )) sin ( ( )) ...
cos ( )) sin ( ))
2cos( ( )) cos( ( ))
2sin( ( ))sin( ( )
L L
L L
L L
L L M
L L M
L M L M
Angl temp k
Ph k Ph k
Ph k Ph k
Ph k Ph k
Ph k Ph k
Ph k Ph k
Ph k Ph k
3 1
2 1
1
1
3 1
2 1
) ...
2sin( ( ))sin( ( ))
2sin( ( ))sin( ( ))
2cos( ( )) cos( ( ))
2sin( ( ))sin( ( )) ...
2sin( ( ))sin( ( ))
2sin( ( ))sin( ( ))
L M L M
L M L M
L L
L L
L M L M
L M L M
Ph k Ph k
Ph k Ph k
M Ph k Ph k
Ph k Ph k
Ph k Ph k
Ph k Ph k
. (36)
Journal of Communications Vol. 8, No. 9, September 2013
575©2013 Engineering and Technology Publishing
Finally, 2| _ ( ) |Angl temp k can be expressed as:
1
2
2
3 1
2 1
2
| _ ( ) |
2cos( ( ) ( ))
2cos( ( ) ( )) ....
2cos( ( ) ( ))
2cos( ( ) ( ))
[0, 1]
L L
L L
L M L M
L M L M
Angl temp k
M Ph k Ph k
Ph k Ph k
Ph k Ph k
Ph k Ph k
M k N
. (37)
The equation (36) (37) is monotone decreasing in the
range [0, ]2
. When
1 2 1( ) - ( ) ... ( ) - ( ) 0
L L L M L MPh k Ph k Ph k Ph k
,
the value of 2| _ ( ) |Angl temp n is equal to 2M . Due to the
correlation, 1 2 1| ( ) - ( ) | ... | ( ) - ( ) |L L L M L MPh k Ph k Ph k Ph k
of frequency pilots tend to 0 to its fullest extent, while
1 2 1| ( ) - ( ) | ... | ( ) - ( ) |L L L M L MPh k Ph k Ph k Ph k of other
carriers are much more than 0 .
The conventional algorithms mainly exploit the power
factor of the pilots in the correlated calculation. As the
power factor of the pilots is inevitably disturbed by the
noise and multipath, the correlated peak may be
weakened. The proposed algorithm gets rid of the power
factor of the pilots in correlated calculation and only
retains the phase factor of the pilots. Because the DRM
channel is flat-fading in the frequency domain, the phase-
difference 1 2 1| ( ) - ( ) | ... | ( ) - ( ) |L L L M L MPh k Ph k Ph k Ph k
can efficiently weaken the impact of the noise and
multipath. In addition, superposition of pilots and a set of
consecutive received symbols can be used to combat the
noise. Consider the complexity and accuracy of the
proposed algorithm, 10 consecutive symbols are selected.
V. SIMULATION
The channel bandwidth is 10Hz and the Robust mode
B is selected in this paper. The DRM channel parameters
are shown in the Table III. Ts is 26.66 ms, Tg is 5.33 ms,
the carrier spacing is 7 /846 Hz.
TABLE III: THE CHANNEL PARAMETERS
Channel 1 Path 1 Path 2 Path 3 Path 4
gain 1
delay 0 ms
Df 0 Hz Dp 0 Hz
Channel 2 Path 1 Path 2 Path 3 Path 4
gain 1 0.5 delay 0 ms 1 ms
Df 0 Hz 0 Hz
Dp 0 Hz 0.1 Hz Channel 3 Path 1 Path 2 Path 3 Path 4
gain 1 0.7 0.5 0.25
delay 0 ms 0.7 ms 1.5 ms 2.2 ms Df 0.1 Hz 0.2 Hz 0.5 Hz 1 Hz
Dp 0.1 Hz 0.5 Hz 1 Hz 2 Hz
Channel 4 Path 1 Path 2 Path 3 Path 4 gain 1 1
delay 0 ms 2 ms
Df 0 Hz 0 Hz
Dp 1 Hz 1 Hz
Channel 5 Path 1 Path 2 Path 3 Path 4
gain 1 1 delay 0 ms 4 ms
Df 0 Hz 0 Hz
Dp 2 Hz 2 Hz Channel 6 Path 1 Path 2 Path 3 Path 4
gain 0.5 1 0.25 0.00625
delay 0 ms 2 ms 4 ms 6 ms Df 0 Hz 1.2 Hz 2.4 Hz 3.6 Hz
Dp 0.1 Hz 2.4 Hz 4.8 Hz 7.2 Hz
* Df is doppler shift; Dp is doppler spread.
Fig. 3 shows the integer frequency offset estimation of
the proposed algorithm in the channel 6. Set the
frequency offset to 1200.64 Hz. The peak is at position of
the 26th sampling point, and the estimated frequency
offset is 1200.58 Hz according to (24), (25), (26).
Simulation test shows that the proposed algorithm meets
the requirements of the DRM system.
0 50 100 150 200 250 3000
5
10
15
20
25
30
the sampling points
Energ
y
the integer frequency offset estimate
SNR=10dB
Figure 3. Integer frequency offset estimation.
-1500 -1000 -500 0 500 1000 1500-10
-8
-6
-4
-2
0
2
4
6
8
10
Frequency offset
the m
ean e
rror
of
frequency o
ffset
estim
ation
Figure 4. Frequency offset estimation range.
Define mean error of Frequency Synchronization:
=ˆ ˆ( ) [ ]M E . (38)
where is the actual frequency offset, ̂ is the
estimation of frequency offset. Fig.4 shows the mean
error of frequency offset estimation. Set the range of the
Journal of Communications Vol. 8, No. 9, September 2013
576©2013 Engineering and Technology Publishing
frequency offset from -1600 to 1600. The SNR is 10 dB.
Simulation test shows that approximately within the
range [-1500, 1500], the accuracy of the proposed
algorithm can fulfill the requirements of the DRM system.
Define MSE (Mean Squared Error) of Frequency
Synchronization:
2ˆ ˆ( )J E
. (39)
5 10 15 20 2510
-6
10-5
10-4
10-3
10-2
SNR/dB
MS
E
Channel 2
the proposed algorithm
Reference 19
Reference 21
Reference 18
Reference 17
Figure 5. MSE of the traditional algorithms and the proposed
algorithm versus SNR in channel 2
5 10 15 20 2510
-6
10-5
10-4
10-3
10-2
10-1
100
101
Channel 6
SNR/dB
MS
E
the proposed algorithm
Reference 19
Reference 21
Reference 18
Reference 17
Figure 6. MSE of the traditional algorithms and the proposed
algorithm versus SNR in channel 6.
The mean square error (MSE) of normalized frequency
offset is used to measure the performance of the
algorithm. Fig. 5 shows that the MSE of the proposed
algorithm and traditional algorithms versus SNR in the
channel 2. Set the frequency offset to 150.24 Hz. From
MSE curves, it is clear that the proposed algorithm has a
small variance than traditional algorithms. Moreover,
under the same MSE conditions, the performance of the
proposed algorithm is about 2-4 dB higher than the
traditional algorithms.
Fig. 6 shows that the MSE of the proposed algorithm
and traditional algorithms versus SNR in the channel 6.
Set the frequency offset to 220.24 Hz. There are only
minor changes for the MSE cure of the proposed
algorithm with respect to Fig.5, while the algorithms in
[17], [18], [21] can no longer meet the requirements of
frequency offset estimation with large MSE. Compared
with Fig.5, the performance of the algorithm in [19] is
about 6 dB smaller. As the fading caused by multipath
channel makes the symbol power spectrum ups and
downs, the accuracy of the algorithm in [21] can’t be
guaranteed. The algorithms in [17], [18] must satisfy the
condition that time pilots are uniformly distributed, are
not suitable to the DRM system.
Fig. 7 shows the MSE of the proposed algorithm
versus SNR in DRM channels. Channel 1 is the AWGN
channel, while channel 6 is multi-path channel.
Compared with channel 6, the MSE of channel 1 is about
1dB smaller
5 10 15 20 2510
-6
10-5
10-4
10-3
SNR/dB
MS
E
channel 1
channel 2
channel 3
channel 4
channel 5
channel 6
Figure 7. MSE of the proposed algorithm versus SNR.
VI. CONCLUSION
Based on the characteristic of the frequency pilots, one
integer frequency offset estimation method is proposed
for DRM system. The proposed algorithm gets rid of the
power factor of the pilots in correlated calculation and
only retains the phase factor of the pilots. The structure of
the angle vector is beneficial to weaken the impact of the
noise and multipath. Simulation results show that the
proposed algorithm improves the range and accuracy of
the frequency offset estimation.
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Cheng Yan received his B.S. degree from the
School of Electronic Information and Control Engineering at Shandong Polytechnic University
Jinan, China, in 2011. He is currently pursuing a
M.S. degree at Communication University of China. His research interests include signal
processing, mobile multimedia and wireless
communication.
Yan Ming received his B.S. in communication engineering from the Nanjing University of Posts
and Telecommunications (NJUPT) in 2002 and
his M.S. in signal and information processing from the Communication University of China
(CUC) in 2006. He received his Ph.D. in
communication and information system from
CUC in 2012. In January 2012, Dr. Yan Ming joined the GxSOC Research Institute at CUC as a
Research Assistant.
Dr. Yan Ming leads the China Mobil Multimedia Broadcasting (CMMB) Research Group at Communication University of China,
whose mission is to conduct tracking research of mobile multimedia
broadcast technology and the related support services in China. He also participates with the Team for Research in broadband multimedia
communication at the Institute of Microelectronics of the Chinese
Academy of Sciences (IMECAS). In addition to his research activities,
Dr. Yan Ming serves as the Administrator of Postgraduate Studies in
GxSOC Research Institute. Dr. Yan Ming is an Expert Member of both the Next Generation
Broadcasting (NGB) workgroup and the Audio Video Standard (AVS)
workgroup.
Journal of Communications Vol. 8, No. 9, September 2013
578©2013 Engineering and Technology Publishing
