The fast Fourier transform is first done in order to transfer the signal
into OFDM symbols. After N-point FFT, the OFDM symbols with
TO/CFO can be written as:
Yi ,k  Yi ,(kp )  Yi ,(km)  Ni ,k
A novel CRS interference cancellation
algorithm for Heterogeneous network
Hua Luo, Wei Li, Yue Zhang, Li-ke Huang, John Cosmas,
Qiang Ni
 H i(,kp ) X i(,kp ) 
N /2

e
n  N /2
2 nn
N
H i(,mk ) X i(,mk ) i  Ni ,k
(2)
( p)
where X i ,k and X i(,mk ) represent the i th symbol at k th subcarrier for desired
Heterogeneous network is introduced to improve the network capacity in
LTE Release 9 and system beyond. The potential traffic congestion due to
increased users can be alleviated by the cooperation between macro-cell
and pico-cell. However, the inter-cell interference caused by RF signal
from macro-cell will reduce the performance severely. Enhanced inter-cell
interference coordination (eICIC) is proposed in Rel. 10 to solve this
problem using almost blank subframe (ABS). Yet, the cell specific
reference signal (CRS) in ABS can still cause interference to the data
resource element (RE) from the pico-cell inevitably for non-colliding
scenario. In this letter, a novel interference cancellation (IC) algorithm is
proposed to mitigate the interference. Firstly, the timing and carrier
frequency offset of interference signal is estimated and compensated.
Secondly, the interfering channel response is estimated by utilizing the
channel statistics. Thirdly, the interference signal is reconstructed based on
the channel estimation and cancelled in the received signal in time domain.
The experiment results show that the performance of proposed IC
algorithm is robust.
( p)
signal and interference respectively; Hi ,k and H i(,mk ) are the channel
coefficients of the serving and interfering channel at k th subcarrier
respectively; i stands for the inter-carrier interference (ICI), which
arises from CFO; and n stands for the relative timing offset between the
interfering cell and serving cell.
yi (n)
TO/CFO
estimation
Interference
Reconstruction
& Cancellation
Interfering
CE
CRS
PSS/SSS
y ( p ) ( n)
CRS
Interfering
CRS Modelling
Fig. 1. Proposed IC algorithm
Introduction: Heterogeneous network (HetNet), first introduced in LTE
Release 9, is a promising network topology for achieving high special
efficiency. With the macro-cell providing basic coverage and the pico-cell
serving as a complementary cell, pico-cell can increase the off-load data
rate and network coverage of macro-cell. However, the user equipments
(UEs), served by pico-cell, will suffer from the RF signal named inter-cell
interference caused by the neighbour high power macro-cells. This issue
will become even severer if the UEs are within the coverage of macrocells. In order to solve this problem, enhanced inter-cell interference
coordination (eICIC) [1]-[2] was introduced in 3GPP Rel. 10 with two
techniques. On the one hand, the signal strength is biased to pico-cell
which can reduce the interference power. On the other hand, macro-cell
keeps silent for certain periods called almost blank subframe (ABS). In
ABS, the interference is alleviated because UEs will not receive the
physical downlink shared channel (PDSCH) from macro-cell. However,
the cell specific reference signal (CRS), paging channel (PCH), physical
broadcast channel (PBCH) and synchronization channels (PSS/SSS) can
still be received and the performance will still be degraded. Therefore, in
Release 11, further eICIC (FeICIC) was proposed to cancel the CRS
interference problem.
There are few literatures about CRS interference cancellation (IC). In [3]
and [4], the authors studied a traditional CRS IC which is realized by first
estimating the interference channel and then cancelling the interference. A
log-likelihood Ratio (LLR) muting/puncturing method was investigated in
[5], [6]. A receiver algorithm that combines IC with direct decision
channel estimation was proposed for non-colliding CRS in [7]. According
to [8], a robust equalization technique was studied which is with similar
performance to the traditional CRS IC but has lower complexity and
latency. Nevertheless, timing and frequency offset will decrease the
system performance severely for non-colliding CRS scenario. In this letter,
a CRS interference cancellation algorithm, with timing offset (TO) and
carrier frequency offset (CFO) taken into account, is studied for the noncolliding scenario. The interference signal is reconstructed and then
mitigated by using TO and CFO obtained and the estimated interference
channel response. The simulation results show that our algorithm can
achieve significant performance in different channel conditions when the
signal to interference and noise ratio (SINR) is within -3dB to 9dB.
The LTE receiver IC algorithm is briefly shown in Fig. 1. For LTE
downlink, the received signal yi (n) for the i th symbol can be modelled as:
yi (n)  yi( p ) (n)  yi( m ) (n)  ni
FFT
Proposed IC algorithm: The IC algorithm proposed mainly consists the
following three steps. Firstly, the relative timing and frequency offset
between the interfering cell and serving cell are estimated by using
PSS/SSS generated in the interfering CRS modelling. Secondly, the
interfering channel estimation is done based on the signal after TO/CFO
compensation. Thirdly, the interfering signal is reconstructed according to
previous interfering CE and then cancelled from the received LTE signal.
The details of these three steps are shown below from step A to step C.
A. TO/CFO estimation: Most of the timing and frequency synchronization
algorithms existed utilize the periodic nature of time domain signal by
using cyclic prefix (CP) [12] or pilot data [13]. However, in ABS, the data
REs of the macro-cell are zero which reduces the power of CP
significantly. The low SNR of CP makes it hard for timing and frequency
synchronization. Yet, the PSS/SSS signal, located at the last and secondlast symbol in slot 0 and slot 10, can be used for synchronization as well.
The TO/CFO can be estimate by utilizing the cross-correlation of
PSS/SSS symbol in time domain [9]:
n, f   arg max  C  n, f  
n , f
(3)
where
M
C  n, f    si* (m)r (n  m)e
2fn
N
(4)
m 1
r (n) and si (n) are the received and locally generated symbol that contain
PSS/SSS respectively, and the correlation length M could be multiple
times of PSS/SSS symbols when SNR is low.
After TO/CFO estimation, the interference signal can be synchronized and
the interference channel response can be estimated.
B. Interfering CE: In order to reconstruct interfering signal, it’s important
to estimate the interfering channel response at first. For the sake of
decreasing compute complexity, the Least Square (LS) channel estimation
algorithm is chosen. According to (2), the interfering channel estimation
can be written as:
Hi(,mk )  Yi ,k / Pi ,(km)  Hi(,mk )  Hi(,kp ) Di(,kp ) / Pi ,(km)  Ni ,k / Pi ,(km)
Here, the interference signal X
(1)
( m)
i ,k
(5)
(m)
is replaced by the interfering CRS Pi ,k
because we only care for interfering CRS signal from the macro-cell.
( p)
According to (5), the data REs of serving cell Di ,k become interference
with relative higher power. Therefore, the estimation in (5) is not accurate.
Many studies, such as [10], show that the distribution of the interference
signal is close to Gaussian for large size RB and non-Gaussian for small
( p)
(m)
where yi (n) and yi ( n) denote the desired and interference signal
respectively; ni is the additive Gaussian noise.
1
size RB. And the mean of the distribution converges to 0. So the
expectation of (5) can be derived as:
 E  H i(,mk ) 
10
MCS 20; SIMO
0
BLER without IC
BLER with IC
BLER without Interference
-1
(6)
BLER
E H i(,mk )   E  H i(,mk )   E H i(,kp ) Di(,kp ) / Pi ,(km )   E  Ni ,k / Pi ,(km ) 
10
The mean value of the interfering channel can be estimated by utilizing
(m)
moving average window in time domain. Then H i ,k can be approximated
10
10
by E H i ,k  when the moving average window length M is within the
coherence time of the channel.
-2
-3
(m)
10
C. Interfering signal reconstruction and cancellation: After TO/CFO and
interfering CE estimation, the interference signal can be reconstructed
based on the local CRS in time domain. As the relative timing offset n
is larger than the duration of CP potentially which will cause intersymbol
interference (ISI) within the OFDM window of desired signal, the
interference signal is reconstructed in time domain and subtracted from
the received signal directly:
y ( p ) (n)  y (n)  x ( m ) (n  n)e
where  is circular convolution and x
reconstructed and
( m)
j 2fn
N
 hl
(7)
(8)
BLER without IC
BLER with IC
BLER without Interference
BLER
0.6
0.5
0.4
0.3
0.2
0.1
1000
2000
3000
4000 5000
CFO (Hz)
6000
7000
8000
Fig. 2. BLER Performance vs. Frequency Offset
0.9
0.8
0.7
BLER without IC
BLER with IC
BLER without Interference
BLER
0.6
0.5
0.4
0.3
0.2
0.1
0
0
20
40
60
80
100
Timing Offset (Samples)
120
140
10
SNR (dB)
11
12
13
1. Heli, Z., et al.: ‘Interference management for heterogeneous networks with
spectral efficiency improvement’, IEEE Wireless Comm. Mag., Apr. 2015,
22, pp. 101-107
2. S. Deb, P. Monogioudis, J. Miernik, J.P. Seymour: ‘Algorithms for
Enhanced Inter-Cell Interference Coordination (eICIC) in LTE HetNets’,
IEEE/ACM Trans. Networking, Feb. 2014, 22, pp. 137- 150
3. A. Tyrrell and H. Schoeneich: ‘Advanced receiver signal processing
techniques: Evaluation and characterization’, ARTIST4G D2.2 Deliverable,
June 2011
4. T. Yoo, et al: ‘Dynamic switching between common reference signal
interference cancellation & resource element puncturing in a co-channel
heteregoneous network’, Patent US2012/0087261 A1, Apr. 2012
5. Qualcomm Inc.: ‘Enabling communication in harsh interference scenarios’,
R4-102350, 3GPP-RAN WG4 AH#10-03, Bratislava, July 2010.
6. Qualcomm Inc: ‘Link level simulations for FeICIC with 9dB cell range
expansion’, R4-123313, 3GPP-RAN WG4 #63, Prague, May 2012.
7. M. Huang and W. Xu: ‘Macro-femto inter-cell interference mitigation for
3GPP LTE-A downlink’, IEEE Wireless Comm. and Net. Conf, Apr. 2012,
pp. 75-80
8. B.E.Priyanto, S. Kant, F. Rusek, S. Hu, J. Chen. C. Wugenshi: ‘Robust UE
Receiver with Interference Cancellation in LTE Advanced Heterogeneous
Network’, IEEE Vehicular Technology Conf. , Las Vegas, Sept. 2013, pp.
1-7
9. Yao-Hsien Tsai and Tzu-Hsien Sang: ‘A new timing synchronization and
cell search procedure resistant to carrier frequency offsets for 3GPP-LTE
downlink’, IEEE International Conf. on Comm. in China (ICCC) , Beijing,
Aug. 2012, pp. 334–338
10. Cheng Feng, Hongyu Cui, Meng Ma, Bingli Jiao, “On Statistical Properties
of Co-channel Interference in OFDM Systems”, IEEE Comm. Letters, Oct.
2013, 17, pp. 2328–2331
11. 3GPP TS 36.101: ‘Evolved universal terrestrial radio access (E-UTRA),
user equipment (UE) radio transmission and reception’, Jul. 2013
12. Scheme, Basic Transmission: ‘LTE: the evolution of mobile
broadband’, IEEE Comm. Mag., Apr. 2009, 45
13. Filippi, A., Serbetli, S.: ‘OFDM symbol synchronization using frequency
domain pilots in time domain’, IEEE Trans. on Wireless Comm., June 2009,
8, (6), pp.3240,3248
1
0
0
9
References
0.9
0.7
8
Conclusion: In this letter, a novel IC algorithm is proposed for HetNet
receiver based on the interference signal reconstruction. First, the
TO/CFO compensation and interfering channel estimation are applied for
reconstructing the interfering CRS. Finally, the interference is cancelled in
time domain after reconstruction by subtracting it from the received signal.
The performance shown in the simulation results indicate that the IC
algorithm can achieve very good performance in different channel
conditions.
Hua Luo, Yue Zhang (Institute for Research in Applicable Computing,
University of Bedfordshire, Luton, LU1 3JU, United Kingdom)
Hua.luo@study.beds.ac.uk
Wei Li (Received his PhD degree of University of Bedfordshire at June
2015)
Li-ke Huang (Cobham Wireless, Stevenage, SG1 2AN, United Kingdom)
John Cosmas (Brunel University, London, UB8 3PH, United Kingdom)
Qiang Ni (Lancaster University, Lancaster, LA1 4YW, United Kingdom)
Results: The performance of the proposed IC algorithm is evaluated via
Monte Carlo simulation. With different modulation and coding schemes
(MCS) to deliver the service, the serving cell is set to work with 10MHz
bandwidth. The neighbour interfering cell transmits ABS with bandwidth
of 5MHz. The CRS from the interfering cell overlaps the data REs of the
serving cell. The signal with desired data and interference pass through a
fading channel with a delay spread smaller than CP duration. In this
simulation, the AWGN channel model is used. In addition, Different CFO
and arriving time are applied to the interfering signal to evaluate its effect.
The effect of CFO and TO on BLER performance is shown in Fig. 2
and Fig. 3 respectively. The performance without IC is shown as a
comparison. It can be seen that our proposed IC achieves good
performance both for CFO and TO.
0.8
7
Fig.4. BLER performance vs. different Doppler frequency and SNR
(n) is the interference CRS
hl  IFFT  H i(,mk ) 
-4
160
Fig. 3. BLER Performance vs. Timing Offset
The BLER performance of the proposed IC algorithm for different
Doppler frequency and SNR is shown Fig. 4 below. The system
performance is significantly improved and therefore the robustness of this
method can be proved.
2