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Wireless Information Transmission System Lab. Institute of Communications Engineering National Sun Yat-sen University Peak-to-Average Power Ratio (PAPR)

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Presentation on theme: "Wireless Information Transmission System Lab. Institute of Communications Engineering National Sun Yat-sen University Peak-to-Average Power Ratio (PAPR)"— Presentation transcript:

1 Wireless Information Transmission System Lab. Institute of Communications Engineering National Sun Yat-sen University Peak-to-Average Power Ratio (PAPR) 2012/07/30 邱營棋

2 2 Multi-carrier systems ◊ The complex baseband representation of a multicarrier signal consisting of N subcarriers is given by where is the subcarrier spacing. ◊ In OFDM systems, the subcarriers are chosen to be orthogonal. (i.e., )

3 3 An example of the time-domain signals with 64 subcarriers

4 ◊ Due to the large number of sub-carriers in typical OFDM systems, the amplitude of the transmitted signal has a large dynamic range, leading to in-band distortion and out-of-band radiation when the signal is passed through the nonlinear region of power amplifier. ◊ Although the above-mentioned problem can be avoided by operating the amplifier in its linear region, this inevitably results in a reduced power efficiency. ◊ The PAPR of the transmit signal is defined as 4 The effect of high PAPR

5 5 AM/AM distortion Soft limiter

6 6 Bandwidth regrowth

7 ◊ If we sample x(t) by a sampling rate of 1/T s (the sampling period T s = T/N ), we may miss some signal peaks and get optimistic results for the PAPR. ◊ For better approximating the true PAPR in the discrete-time case, we usually oversample x(t) by a factor of L, i.e., the sampling rate is L/T s. ◊ It was shown in [15] that an oversampling factor L=4 is sufficient to approximate the true PAPR. 7 PAPR in discrete-time case

8 ◊ For an OFDM system with N sub-carriers, an oversampling rate of L can be achieved by inserting (L - 1)·N zeros in the middle of the modulated symbol vector to form a 1×LN data vector X, i.e. ◊ The PAPR computed from the L-times oversampled time-domain signal samples is given by 8 PAPR in discrete-time case

9 ◊ The cumulative distribution function (CDF) of the PAPR is one of the most frequently used performance measures for PAPR reduction techniques. In the literature, the complementary CDF (CCDF) is commonly used instead of the CDF itself. ◊ The CCDF of the PAPR denotes the probability that the PAPR of a data block exceeds a given threshold. ◊ From the central limit theorem, the real and imaginary parts of the time domain signal samples follow Gaussian distributions, assuming each distribution with a mean of zero and a variance of 0.5 for a multicarrier signal with a large number of subcarriers. 9 The CCDF of the PAPR

10 ◊ Hence, the amplitude of a multicarrier signal has a Rayleigh distribution, while the power distribution becomes a central chi- square distribution with two degrees of freedom. ◊ The CDF of the instantaneous power of a signal sample is given by ◊ The CCDF of the PAPR of a data block with Nyquist rate sampling is derived as This expression assumes that the N time domain signal samples are mutually independent and uncorrelated. 10 The CCDF of the PAPR

11 ◊ Distortion ◊ Clipping ◊ Companding ◊ Distortionless ◊ Selected Mapping (SLM) ◊ Partial Transmit Sequence (PTS) ◊ Others ◊ Active Constellation Extension (ACE) ◊ Tone Reservation (TR) 11 PAPR Reduction Methods

12 ◊ The simplest way to reduce the PAPR. ◊ The peak amplitude becomes limited to a desired level. ◊ Clipping ◊ Clipping Ratio 12 Clipping

13 ◊ By distorting the OFDM signal amplitude, a kind of self- interference introduced that degrades the BER. ◊ Nonlinear distortion increases out-of-band radiation. 13 Clipping

14 14 Companding

15 15 Companding

16 16 Selected mapping (SLM)

17 1. A set of U markedly different, distinct, pseudo-random but fixed vectors P (u) = [P 0 (u), …, P N-1 (u) ], with must be defined. 2. The subcarrier vector A is multiplied subcarrier-wise with each one of the U vectors P (u), then resulting to component 3. Then all U alternative subcarrier vectors are transformed into time domain to get and finally that transmit sequence with the lowest PAPR is chosen. ◊ For implementation, the SLM technique needs U IDFT operations, and the number of required side information bits is, denotes the smallest integer that exceed y. 17 Selected mapping (SLM)

18 18 PAPR reduction performance of SLM ◊ N = 256, L = 4, 16-QAM,

19 19 Partial transmit sequence (PTS) Partial transmit sequence (PTS)

20 1. In this scheme, the subcarrier vector A is partitioned into M pairwise disjoint subblocks All subcarrier positions in which are already represented in another subblock are set to zero, so that 2. We introduce complex-valued rotation factors, and μ is index of all phase rotation of “Peak value optimization”. Enabling a modified subcarrier vector which represents the same information as A, if the set (as side information) is known for each μ. 20 Partial transmit sequence (PTS) Partial transmit sequence (PTS)

21 3. To calculate, the linearity of the IDFT is exploited. Accordingly, the subblocks are transformed by M separate and parallel N-point IDFTs, yielding 4. Based on them a peak value optimization is performed by suitably choosing the free parameters such that the PAPR is minimized for. ◊ It should be noted, that PTS can be interpreted as a structurally modified special case of SLM. 21 Partial transmit sequence (PTS) Partial transmit sequence (PTS)

22 22 Partial transmit sequence (PTS) Partial transmit sequence (PTS) ◊ In general, the selection of the phase factors is limited to a set with a finite number of elements to reduce the search complexity. ◊ The set of allowed phase factors is written as, where W is the number of allowed phase factors. ◊ In addition, we can set without any loss of performance. ◊ Hence, sets of phase factors are searched to find the optimum set of phase factors. ◊ PTS needs M IDFT operations for each data block, and the number of required side information bits is.

23 23 PAPR reduction performance of PTS ◊ N = 256, L = 4, 16-QAM, exhausted research for. W=2 means [+1,-1], W=4 means [+1, -1, +1j, -1j].

24 ◊ In this technique, some of the outer signal constellation points in the data block are dynamically extended toward the outside of the original constellation such that the PAPR of the data block is reduced. 24 Active Constellation Extension (ACE) QPSK16-QAM

25 Active Constellation Extension (ACE) PAPR 25 clipping

26 ◊ N = 256, L = 4, QPSK, A = 4.86 dB. PAPR reduction performance of ACE PAPR 26

27 27 Tone Reservation (TR) ◊ The transmitter reserves a small number of unused subcarriers. These subcarriers are referred to as peak reduction carriers (PRCs). ◊ Since PRCs do not carry data, this increment induces a severe degradation of system’s power efficiency. ◊ In general, there are two approaches to reduce the PAPR in the TR technique. ◊ The first is to select the PRC indices for the TR technique to be used in reducing the PAPR. ◊ The second is to design the proper values on these PRCs to generate an optimal peak-canceling signal that minimizes the PAPR of a transmitted OFDM signal.

28 28 Tone Reservation (TR)

29 ◊ [1] S. H. Han and J. H. Lee, “An overview of peak-to-average power ratio reduction techniques for multicarrier transmission,” IEEE Wireless Commun., vol. 12, pp. 56-65, Apr. 2005. ◊ [2] T. Jiang and Y. Wu, “An overview: peak-to-average power ratio reduction techniques for OFDM signals,” IEEE Trans. Broadcast., vol. 54, no. 2, pp. 257-268, Jun. 2008. ◊ [3] J. Armstrong, “Peak-to-average reduction for OFDM by repeated clipping and frequency domain filtering,” IET Electron. Lett., vol. 38, no. 5, pp. 246–247, Feb 2002. ◊ [4] X. Li and L. J. Cimini, “Effects of clipping and filtering on the performance of OFDM,” IEEE Commun. Lett., vol. 2, no. 5, pp. 131–133, May 1998. ◊ [5] X. Huang, J. H. Lu, J. L. Zheng, K. B. Letaief, and J. Gu, “Companding transform for reduction in Peak-to-Average power ratio of OFDM signals,” IEEE Trans. Wireless Commun., vol. 3, no. 6, pp. 2030–2039, Nov. 2004. ◊ [6] T. Jiang and G. Zhu, “Nonlinear companding transform for reducing peak-to-average power ratio of OFDM signals,” IEEE Trans. Broadcast., vol. 50, no. 3, pp. 342–346, Sep. 2004. ◊ [7] S. S. Yoo, S. Yoon, S. Y. Kim, and I. Song, “A novel PAPR reduction scheme for OFDM systems: selective mapping of partial tones (SMOPT),” IEEE Trans. Consum. Electron., vol. 52, no. 1, pp. 40– 43, Feb. 2006. ◊ [8] M. Breiling, S. H. Muller, and J. B. Huber, “SLM peak-power reduction with explicit side information,” IEEE Commun. Lett., vol. 5, no. 6, pp. 239–241, June 2001. 29 Reference

30 ◊ [9] S. G. Kang, J. G. Kim, and E. K. Joo, “A novel subblock partition scheme for partial transmit sequence OFDM,” IEEE Trans. Commun., vol. 45, no. 9, pp. 333–338, Sep. 1999. ◊ [10] A. Ghassemi and T. A. Gulliver, “A low-complexity PTS-based radix FFT method for PAPR reduction in OFDM system,” IEEE Trans. Signal Process., vol. 56, no. 3, pp. 1161–1166, Mar. 2008. ◊ [11] B. S. Krongold and D. L. Jones, “PAR reduction in OFDM via active constellation extension,” IEEE Trans. Broadcast., vol. 49, no. 3, pp. 258–268, Sep. 2003. ◊ [12] A. Saul, “Generalized active constellation extension for peak reduction in OFDM systems,” in Proc. 2005 IEEE International Conference on. Communications (IEEE ICC 2005), Seoul, Korea, Sep. 2005, vol. 3, pp. 1974–1979. ◊ [13] J. Tellado, “Peak to average power reduction for multicarrier modulation,” Ph.D. dissertation, Stanford University, 2000. ◊ [14] L. Wang and C. Tellambura, “Analysis of clipping noise and tone-reservation algorithms for peak reduction in OFDM systems,” IEEE Trans. Veh. Technol., vol. 57, no. 3, pp. 1675–1694, May 2008. ◊ [15] C. Tellambura, “Computation of the continue-time PAR of an OFDM signal with BPSK subcarriers,” IEEE Commun. Lett., vol. 5, no. 5, pp. 185–187, May 2001. 30 Reference


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