This document proposes iterative clipping and error filtering methods to improve the performance of UFMC systems using SLM for 5G networks. Existing SLM techniques have high complexity and reduce spectral efficiency. The proposed method uses phase offset SLM in a UFMC system without needing to transmit side information, increasing data rate. It provides advantages over OFDM like low latency, high spectral efficiency, and lower out-of-band emissions. The performance of the proposed UFMC-SLM system will be evaluated using MATLAB simulations.

1. ITERATIVE CLIPPING AND ERROR FILTERING
METHODS IN SLM FOR 5G UFMC SYSTEMS
PRESENTED BY,
Mr. K. AYAPPASAMY

2. CONTENT
 Introduction
 Objective
 Existing work
 Disadvantages of existing method
 Proposed work
 Advantages of UFMC
 Block diagram
 SLM
 Simulation tool
 Reference
2

3. INTRODUCTION
 A number of wireless applications have been growing over the
last decade.
 Frequency spectrum has already been licensed by FCC.
 Dynamic spectrum access techniques were recently proposed
to solve spectrum inefficiency problems.
 The key enabling technology of dynamic spectrum access
techniques is Orthogonal Frequency Division Multiplexing.
3

4. Contd.,
 Conventional OFDM multicarrier has high power and OOB.
 It causes ACI.
 Clipping technology is considered as a solution for OFDM.
 It is achieved by clipping a series of successive sub-carriers.
4

5. OBJECTIVE
 To improve the performance of the UFMC with SLM system
using Iterative clipping and error filtering methods in 5G
technology.
5

6. EXISTING WORK
 It investigates the performance of signal processing based
PAPR reduction.
 To increase efficiency of power amplifier used in 5G and
B-5G.
 The waveforms considered in this work are (WOLA
OFDM) Weighted Overlap and Add-OFDM.
 The reduction methods used are SLM and Tone reservation.
6

7. DISADVANTAGE OF EXISTING
SYSTEM
 High PAPR
 High computation complexity
 Reduction spectral efficiency
 Poor SNR
7

8. PROPOSED WORK
 Here, an UFMC-SLM system is presented as a novel phase
offset selected mapping (SLM) scheme is proposed to reduce
the peak-to-average power ratio (PAPR) in Alamouti coded
multi-input multi-output orthogonal frequency division
multiplexing (MIMO-UFMC) systems, and its key idea is that
different phase rotation sequences are multiplied by their
corresponding phase offsets at the transmitter.
 Therefore, the proposed SLM scheme does not need to reserve
bits for the transmission of side information, resulting in the
increase of the data rate. 8

9. ADVANTAGES OF UFMC
 Low latency
 High spectral efficiency
 Lower in-band and OOB emissions
 Low power consumption
9

10. BLOCK DIAGRAM OF
UFMC-SLM
10

11. UFMC
11

12. SLM
 The three different SLM is designed and compared with the original signal.
 The B-SLM represent the blind SLM, C-SLM is the convolution SLM and
the P-SLM is the Phase offset SLM.
 A maximum likelihood (ML) based blind SLM (B-SLM) method for
OFDM systems is evaluated which does not need the SI transmission.
 The conventional SLM (C-SLM) scheme, extra bits should be reserved for
the transmission of the phase rotation sequences as side information (SI),
resulting in the decrease of the data rate.
12

13. BLOCK DIAGRAM OF SLM

14. SIMULATION TOOL
14
MATLABR2018a

15. REFERENCES
[1] Selahattin Gokceli, Toni Levanen, Taneli Riihonen, Juha Yli-Kaakinen and Alberto Brihuega,
“Novel Iterative Clipping and Error Filtering Methods for Efficient PAPR Reduction in 5G
and Beyond.
[2] H. Wang, Z. Zhang, Y. Zhang and G. Yu, “Enhanced universal filtered multi-carrier
transmission with active interference cancellation,” in Proc. IEEE Wireless Commun. Netw.
Commun. (WCNC), 2017, pp. 1–6.
[3] C. L. I, S. Han, Z. Xu, S. Wang, Q. Sun and Y. Chen, “New paradigm of 5G wireless Internet,”
IEEE J. Sel. Areas Commun., vol. 34, no. 3, pp. 474–482, Mar. 2016.
[4] Q. Sun, I. Chin-Lin, S. Han, Z. Xu, and Z. Pan “Software defined air interface: A framework of
5G air interface,” in Proc. IEEE Wireless Commun. Netw. Conf. Workshops (WCNCW), Mar.
2015, pp. 6–11.
[5] X. Wang, T. Wild, F. Schaich and A. F. dos Santos, “Universal filtered multi-carrier with
leakage-based filter optimization,” in Proc. 20th Eur. Wireless Conf., May 2014, pp. 1–5.
15

16. REFERENCES
[6] M. Korki, J. Zhang, C. Zhang and H. Zayyani, “Block-sparse impulsive noise reduction in
ofdm systems—A novel iterative Bayesian approach,” IEEE Trans. Commun., vol. 64, no. 1,
pp. 271–284, Jan. 2016.
[7] M. Nassar, P. Schniter and B. L. Evans, “A factor graph approach to joint OFDM channel
estimation and decoding in impulsive
noise environments,” IEEE Trans. Signal Process., vol. 62, no. 6, pp. 1576–1589, Mar. 2014.
[8] H. Zhou, A. V. Malipatil and Y. F. Huang, “OFDM carrier synchronization based on time-
domain channel estimates,” IEEE Trans. Wireless Commun., vol. 7, no. 8, pp. 2988–2999,
Aug. 2008.
[9] P. Banelli, S. Buzzi, G. Colavolpe, A. Modenini, F. Rusek and A. Ugolini, “Modulation
formats and waveforms for 5G networks: Who will be the heir of OFDM?: An overview of
alternative modulation schemes for improved spectral efficiency,” IEEE Signal Process.
Mag., vol. 31, no. 6, pp. 80–93, Nov. 2014.
[10] B. Farhang-Boroujeny, “OFDM versus filter bank multicarrier,” IEEE Signal Process. Mag.,
vol. 28, no. 3, pp. 92–112, May 2011.
16

17. Thank you