1. Interference Cancellation Algorithm with Pilot in 3GPP/LTE
Technology Mongolian University of Science and Technology
School of Information and Communication
Interference Cancellation Algorithm with Pilot in 3GPP/LTE
Researchers: Professor Otgonbayar Bataa (Ph.D)
Buyanhishig Ulziinyam
Erdenebayar Lamjav

2. OUTLINE Introduction The Analysis of ICS Requirement for 3GPP/LTE
Overview of IC
Channel Estimation Techniques
IC algorithm with pilot signal
Channel Simulation
Conclusions
We give an overview of Repeater system in 3GPP/LTE. We discuss iterative algorithm with pilot signal based on channel estimation techniques. with its simulation result for it performances. Conclusion is given in the last section.

3. Introduction
The major challenges for LTE terminal implementation are efficient channel estimation (CE) method as well as equalization.
We are assuming the basic CE techniques and future direction for research in CE fields.
General interference cancellation methods work in the frequency and time domain. The algorithms use in the time domain and is used methods named LMS, LMMSE and MLSE.
Minimum LSE technique has been proposed for general MIMO-OFDM systems with pilot signal.
We proposed new algorithm of received signal with pilot design. Although repeater design need to our project, so we discuss to interference cancellation algorithm for 2x2 MIMO system with pilot in LTE. First explain to general repeater principle structure of 3GPP/LTE, next determine to our new design and algorithm. Finally we simulated our mathematic extraction of proposed new algorithm on MATLAB.

4. 1.1 The Analysis of ICS Requirement for 3GPP/LTE
This task includes following subtasks:
Applications and features of ICS repeater
Analysis of ICS requirement for 3GPP/LTE
Repeater communication is one promising candidate solution in future cellular networks because of its ability to increase throughput, data rate and coverage.
ICS repeater is one of the candidate technology in future 3GPP/LTE-A to increase capacity.

5. 1.1 The Analysis of ICS Requirement for 3GPP/LTE
Traditionally repeaters have been active continuously and perform blind forwarding without knowing the signal.
However the repeater in LTE Advanced is likely to include some advanced functionalities such as:
frequency selectivity,
gain controllability,
multi antenna ability,
advanced antenna processing,
optimum power control algorithm, etc.

6. 1.1 The Analysis of ICS Requirement for 3GPP/LTE
The ICS Repeater is a new kind of single-band RF repeater that can automatically detect and cancel the interference signals caused by oscillation of RF feedback between the Donor and Coverage Antennas in real time by adopting DSP (Digital Signal Processing) technology.
It can continuously and stably cancel the interference signals and be adapted to any changes in the surrounding RF environment (including fixed and mobile objects).

7. 1.1 The Analysis of ICS Requirement for 3GPP/LTE
A repeater consists of two antennas and a power amplifier. The antennas are identified as donor (receive) and coverage (transmit or service or sector) antennas. The two antennas are typically mounted on the same tower and are located in close proximity. The donor antenna at the repeater is adjusted to be in line of sight (LOS) transmission with the BS. A repeater that receives and transmits signals on the same frequency band is termed as an on-frequency repeater or SFN repeater. Figure 1.1 shows a general adaptive interference cancellation repeater and the terms associated with it [1].

8. 1.2 Features of ICS Repeater
High-speed, large dynamic A/D, D/A technology
The adaptive filter design based on the modern digital signal processing technology
Real-time cancellation of interference signal (incl. multi-path fading, feedback signal)
ICS function to prevent self-oscillation, enhance gain and coverage range, and reduce isolation requirement between donor antenna and coverage antenna
Highly selective digital channel selector
No interference to BTS by adopting linear amplifier with high gain and low noise
Adopting filter with highly selectivity and low insertion loss eliminates interference between uplink and downlink

9. 2.1 Overview of IC
Successive and Parallel IC can be iteratively (iterative IC) ,that is, after one iteration over all streams we can further improve the quality of the streams by cancelling the streams estimated in the first iteration.
Successive IC (SIC) processes each stream successively canceling their interference before previously decoded streams.
Parallel IC (PIC) processes all streams in parallel and cancels their interference after they have all been decoded independently.
Currently number of researchers have been proposed to develop algorithms for interference cancellation.
Successive IC (SIC)
Parallel IC (PIC)

10. 2.2.1 Channel equalization
There are three categories of equalization techniques.
Frequency-domain technique
Frequency-domain technique, which applies the conventional equalization algorithm for single-carrier MIMO systems to each subcarrier, the design complexity is rather high, and the memory required to store the equalizer coefficients is large.
Time–frequency domain technique
Time-domain technique
A time-domain equalizer, which is designed using the second-order statistics (SOS) of the shifted received OFDM symbols, is applied to partially cancel the ICI and ISI.
At first we analyzed of performance of the channel estimation using MLSE in OFDM system which, as known suffers from the time variation of the channel, using pilot insertion.

11. 2.2.2 Channel Estimation Techniques
We proposed to study the performance of the two linear estimators under the effect of the channel length.
Channel estimation algorithms can be generally separated into two methods,
Pilot-based channel estimation
Non-Pilot channel estimation.
Adaptive channel estimation methods are typically used for rapidly time-varying channel.
Channel estimation is used two-dimensional time and frequency domain structure of OFDM system.
Channel estimation plays very important role in ICS.
In recent years, with the appearance of “turbo principle” [36], iterative receivers are becoming more and more popular because of their attractive performances. Different mechanisms have already been proposed and studied, for example, iterative detection, iterative MIMO equalization, etc. However, these iterative mechanisms are seriously affected by channel estimator.
Pilot-based channel estimation estimates the channel information by obtaining the impulse response from all sub-carriers by pilot.
Non-Pilot-based channel estimation uses statistical information of the received signals.

12. 2.4.1 Pilot based system architecture

13. 2.6 IC algorithm using pilot signal
For pilot based channel estimation of OFDM system, following three are required.
Firstly, suitable pilot pattern needs to be considered.
Secondly, pilot-based channel estimation algorithm with low complexity should be identified.
Thirdly, proper demodulation method toward effective channel estimation has to be developed

14. 2.6.1 How to use pilots for Channel Estimation
Methods/Estimation & Interpolation/
Channel Estimation Techniques Based on Pilot Arrangement in OFDM Systems
Based on Block type pilot arrangement
Based on Comb type pilot arrangement
LS /Least Square/ +
LMS /Least Mean Square/
MMSE /Minimum Mean Square Error /
LMMSE /Linear MMSE/ or Wiener filtering
Decision Feedback Interpolation
Linear Interpolation
Second Order Interpolation
Low Pass Interpolation
Spline Cubic Interpolation
Time Domain Interpolation
Piecewise Constant Interpolation
Channel estimation methods, 2-D or 1-D dimensional, can be characterized into two types
Generalized linear network models based on orthogonal polynomials (least-squares method)
Wiener filtering using second-order statistics of the channel (LMMSE method)

15. 2.6.2 Pilot orientation for Channel Estimation in LTE
The two basic channel estimations in OFDM systems.
Block-type pilot channel estimation, is performed by inserting pilot tones into all subcarriers of OFDM symbols with a specific period in time. The pilot symbols, because covering all frequencies, could be effective against the selective frequency fading, but more sensitive for the impact of fast fading channel. Therefore, the block-type pilot is developed under the assumption of slow fading channel. In case of same number of pilots, the performance is decided by channel change rate, known as coherent time.
Comb-type pilot channel estimation, is performed by inserting pilot tones into certain subcarriers of each OFDM symbol, where the interpolation is needed to estimate the conditions of date subcarriers.
Comb Type:
Part of the sub-carriers are always reserved as pilot for each symbol
Block Type:
All sub-carriers is used as pilot in a specific period

16. 2.6.3 Pilot for Channel Estimation
Figure 2. Pilot allocation in EUTRAN (generic frame structure, normal cyclic prefix)
Figure shows the pilot allocation in EUTRAN generic frame structure and normal cyclic prefix setup.

17. 2.6.4 Comb-type pilot channel estimation
Piecewise Constant Interpolation
Linear Interpolation
Second Order Interpolation
Cubic Spline Interpolation
These algorithms have very low complexities. However, they are not precise enough or need some presumptions (e.g. the number of channel taps, the delay spread), which limit the application of these algorithms for LTE systems.

18. 2.6.5 Block-type Channel Estimation
LSE: Least Square Estimation
The goal of the channel least square estimator is to minimize the square distance between the received signal and the original signal.
LMMSE: Linear MMSE
the LMMSE estimator always needs some a priori information of the channel, e.g. noise level and channel correlations.
In [72], another important channel estimator is also proposed: minimum mean square error (MMSE) estimator. It has a better performance than LS estimator; however, its complexity is even higher than LS estimator. In order to reduce the complexity of MMSE channel estimator, some simpler schemes are considered. In [72], only a part of taps in channel s considered for MMSE estimator. Also, the mismatched MMSE estimator and exponential mismatched MMSE estimator proposed in [74] can both reduce the complexity of MMSE; however, these simplified MMSE estimators need some a priori information of channels (delay spread and noise variance) and result in performance degradation.

19. 2.6.6 Least Square (LS) Estimator
The cost function of LS algorithm:
The purpose of LS algorithm is to minimize the cost function J without noise. For the minimization of J, let

20. 2.6.6 Least Square (LS) Estimator
Then
Then we could get

21. 2.6.6 Least Square (LS) Estimator
The LS estimators are known by its very low complexity because they not need the statistic information of channel.
The least square estimates (LS) of the channel at the pilot subcarriers given in bellow can be obtained by the following equation:
represents the least-squares (LS) estimate obtained over the pilot subcarriers.

22. Proposed signal processing technique with pilot signal for ICS

23. 2.6.6 Simulation results
Figure The symbol error rate comparison of the proposed non-pilot and pilot technique with any modulation order at the receiver
Figure The symbol error rate technique with pilot, that of a 2Tx−2Rx at the LS estimator based receiver

24. CONCLUSION AND FUTURE WORKS
Finally, in this project the Minimum LSE equalization used to pilot system, that is mainly considered as proved by any works. It would be very interesting to extend the ideas of the polynomial approach and transceiver/repeater designs to new practical system based channel interference cancellation methods.