Hybrid PAPR Reduction Scheme for FBMC/OQAM Systems Based on ...

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Hybrid PAPR Reduction Scheme for FBMC/OQAM Systems Based on Multi Data Block PTS and TR methods Han Wang1, Xianpeng Wang1, (Member, IEEE), Lingwei Xu2, and Wencai Du1*  Abstract—The filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM）is being studied by many researchers as a key enabler for the fifth generation (5G) air interface. In this paper, a hybrid peak-to-average power ratio (PAPR) reduction scheme is proposed for FBMC/OQAM signals by utilizing multi data block partial transmit sequence (PTS) and tone reservation (TR). In the hybrid PTS-TR scheme, the data blocks signal is divided into several segments, and the number of data blocks in each segment is determined by the overlapping factor. In each segment, we select the optimal data block to transmit and jointly consider the adjacent overlapped data block to achieve minimum signal power. Then the peak reduction tones (PRTs) are utilized to cancel the peaks of the segment FBMC/OQAM signals. Simulation results and analysis show that the proposed hybrid PTS-TR scheme could provide better PAPR reduction than conventional PTS and TR schemes in FBMC/OQAM systems. Furthermore, we propose another multi data block hybrid PTS-TR scheme by exploiting the adjacent multi overlapped data blocks, called as the Multi hybrid (M-hybrid) scheme. Simulation results show that the M-hybrid scheme can achieve about 0.2dB PAPR performance better than hybrid PTS-TR scheme. Index Terms— FBMC/OQAM, PAPR, hybrid, partial transmit sequence, tone reservation

I. INTRODUCTION Multicarrier techniques have been widely used in many communication systems for high data rate transmission and are considered a suitable candidate for future wireless systems. Orthogonal frequency division multiplexing (OFDM) technique is certainly one of the most famous and accepted type of multicarrier schemes in many digital communication systems. However, the insertion of cyclic prefix (CP) in OFDM transmission symbol sacrifices spectral efficiency. Moreover, the use of rectangular pulse shaping on each subcarrier will lead to high out of band radiation. To overcome these disadvantages This work is supported by Hainan University excellent paper cultivation plan, the National Natural Science Foundation of China (Grant No. 61561017) and the International Science and Technology Corporation Plan organized by the Ministry of Science and Technology of China, Grant No. 2015DFR10510. Han Wang, Xianpeng Wang and Wencai Du are with the College of Information Science & Technology, Hainan University, Haikou, China (e-mail: [email protected], [email protected], [email protected] ). Lingwei Xu is with the Department of Information Science & Technology, Qingdao University of Science & Technology, Qingdao, China (e-mail: [email protected]).

of OFDM systems, filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) technique has drawn increasing attentions by many researchers [1-5]. As a potential candidate multicarrier modulation scheme for the fifth generation (5G) wireless communication network [6-10], FBMC/OQAM well utilizes time frequency localization (TFL) property pulse shaping via an inverse fast Fourier transform/fast Fourier transform (IFFT/FFT) based filter bank, and staggered OQAM symbols, real symbols at twice the symbol rate of FBMC/QAM, are loaded on the subcarriers. Hence, FBMC/OQAM has a higher spectral efficiency [11, 12] in theory as well as robustness to frequency offset and Doppler spread. Besides, CP is not required in FBMC/OQAM systems, which can provide higher data rate than CP-OFDM [13,14]. The high peak-to-average power ratio (PAPR) issue is emerged in all multicarrier communication systems. A high PAPR means that, in order to avoid distortions in the transmitted signal, linear amplifiers with large input backoff need to be used. As a particular type of multicarrier communication systems, FBMC/OQAM has its root in the pioneering works of Chang [15] and Saltzberg [16] who introduced multicarrier techniques over two decades ago. Similar to OFDM systems, one of the main shortcomings for FBMC/OQAM systems is the high PAPR of transmitted FBMC/OQAM signals. Various PAPR reduction schemes for OFDM systems have been proposed during the past decade, such as clipping and filtering scheme [17], selective mapping (SLM) scheme [18], partial transmit sequence (PTS) scheme [19], and tone reservation (TR) scheme [20, 21]. However, the structure of FBMC/OQAM signal is different from that of OFDM signal. FBMC/OQAM signals are overlapped with adjacent data blocks, while the signals in OFDM systems are independent. Therefore, the conventional PAPR reduction schemes cannot be effectively utilized in FBMC/OQAM systems. In recent years, a number of PAPR reduction schemes for FBMC/OQAM systems have been studied [22-29]. In Refs. [22, 23], the authors proposed two PAPR reduction techniques based on SLM. These techniques take the overlapping nature of the FBMC/OQAM symbols into account. In Refs. [24, 25], the overlapped SLM (OSLM) and alternative signals (AS) schemes have been proposed to reduce the PAPR of FBMC/OQAM signals, and they jointly consider the current data block and the previous data blocks to acquire the optimal phase rotation

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2 sequence. Nevertheless, the above four mentioned schemes need extra spectral band to transmit the phase rotation sequence as side information. In Refs. [26, 27], a sliding window tone reservation (SW-TR) technique has been proposed. The SW-TR method utilizes the peak reduction tones of several consecutive data blocks to cancel the peak power of the FBMC/OQAM signals inside a window. A multi block tone reservation (MB-TR) scheme has been proposed in [28]. The key idea of the MB-TR scheme is to exploit the overlapping structure of the FBMC/OQAM signals and jointly consider the adjacent data blocks to obtain the clipping noise. Besides, a segmental PTS (S-PTS) has been proposed in [29]. The S-PTS divides the overlapped FBMC/OQAM signal into a number of segments. However, this segmentation method is not based on FBMC/OQAM signal structure. A hybrid PAPR reduction scheme with SLM and TR for FBMC/OQAM has been proposed in [30]. But, it only combines the advantages of the two conventional PAPR reduction schemes, and the overlapping nature of the FBMC/OQAM symbols is not considered. The main contributions of this paper are listed as follows: 1. To the best of our knowledge, a union algorithm based on multi-block PTS and TR has not yet been investigated for FBMC/OQAM systems. In this paper, the two adjacent overlapped OFDM/OQAM data blocks signals are jointly considered to reduce overlapping effect, and the OFDM/OQAM signals are divided into segments to avoid the peak re-growth. The above process is designed to reduce the signal peak values caused by overlapping effect. 2. Another multi hybrid (M-hybrid) PTS-TS scheme, which jointly considers multi data blocks overlapping in each segment signal, is also proposed. While in the hybrid PTS-TR scheme, it only considers the two adjacent data blocks overlapping effect. 3. The accuracy of the analytical results under different conditions is verified through numerical simulation. The different conditions include different number of peak reduction tones, different clipping thresholds and different number of sub-blocks. Simulation results show that the proposed schemes have a better PAPR performance than conventional PTS and TR schemes. The remainder of this paper is organized as follows: Section 2 gives a brief introduction to the PAPR of FBMC/OQAM signal and the two conventional PAPR reduction schemes. Section 3 introduces our proposed hybrid schemes for the PAPR reduction of FBMC/OQAM signal. The performances of the proposed schemes associated with the conventional PTS and TR schemes are compared and simulation results are shown in Section 4. Finally, the concluding remarks are given in Section 5. II. FBMC/OQAM SIGNAL MODEL AND CONVENTIONAL PAPR REDUCTION SCHEMES A. PAPR of FBMC/OQAM Signals Figure 1 depicts the FBMC/OQAM transmitter structure, which consists of N subcarriers. The data after QAM

modulation into Am , where Am  [am,1 , am,2 ,..., am, N 1 , am, N ] , the QAM symbols then through serial to parallel, and the real and imaginary part of each symbols are transmitted on a subcarrier, respectively. After the prototype filter and phase modulation, the transmission of FBMC/OQAM data blocks can be obtained by adding all subcarrier signals. The m-th FBMC/OQAM data block signal in time domain can be expressed as [25] N

sm  t    am, n hm , n (t ) n 1

T   j      am , n  h  t  mT   j am , n  h  t  mT   e m ,n 2   n 1  1 mT  t  (m    )T (1) 2 where am , n denotes the m-th QAM symbol on the n-th N

subcarrier, {.} and {.} denote the real and imaginary parts of am , n , respectively. T denotes the symbol period, and h(t ) is the

response of the prototype filter with  T length.  is the overlapping factor, m , n is an additional phase term with 2 t   ) . sm (t ) is a single FBMC/OQAM data block T 2 signal formula, then the M consecutive data block signal is written as

m, n  n(

M

s  t    sm (t ), 0  t   M    1 2  T

(2)

m 1

 am,1   t  mT 

j am,1   t  mT   am,2    t  mT 

j am,2    t  mT 

data

QAM modulation

Am

S/P

h(t)

e

jm ,1

h(t-T/2) h(t)

e

jm ,2

h(t-T/2)

. . .

 am, N 1   t  mT  j am, N 1   t  mT   am , N    t  mT 

j am, N    t  mT 

 h(t)

e

sm  t 

jm , N 1

h(t-T/2) h(t)

e

jm , N

h(t-T/2)

Fig. 1. The FBMC/OQAM transmitter structure [25].

We show the structure of FBMC/OQAM signal in Figure 2. It can be seen that each sm (t ) consists of two parts, and they are staggered by T 2 . The length of each data block is

   1 2 T . The length of M data blocks length is    M  1 2 T . It is obvious that s1 (t ) overlaps with the next   1 data blocks. In conventional OFDM systems, each OFDM symbol length is T . Thus, there are no overlaps between adjacent symbol blocks, and the definition of peak-to-average power ratio is proposed for each individual OFDM symbol. According to the overlapping structure of FBMC/OQAM signal, the definition of PAPR in FBMC/OQAM systems should be modified. We divide s  t  into M   intervals, and each interval equal to T (the last one is T 2 ). The PAPR of

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3 each interval is written as

PAPR(dB)  10 log10

max

iT  t  ( i 1)T

s t 

elements, thus, the search complexity is reduced. One simple example is to use the binary phase factor of 1, 1 .

2

(3) 2 E  s t     2   where i  0,1,..., M    1 , E s  t  denotes the s  t    expectation. s1  t 

s1R  t 



s2R  t 



s3  t 

C. Conventional Tone Reservation Scheme for FBMC/OQAM In the TR scheme, iterative clipping filtering algorithm is usually adopted. The total N subcarriers (tones) are partitioned into R peak reduction tones (PRTs) and N  R data tones. Symbols in PRTs are chosen so that FBMC/OQAM signal in the time domain has a lower PAPR. The positions of PRTs are known by the receiver and transmitter. Usually, the PRTs are chosen with null sub-carriers [21]. The m-th data block S mn is divided into data vector Dmn and

s1I  t 

T/2 T s2  t 

s2I  t  s3R  t 

 s4  t 

s3I  t 



s4R  t 

s4I  t  .

Overlapped

. .

sMR 1  t 



sM 1  t 

sMI 1  t 

sM  t 



sMR  t  sMI  t 

Fig.2. The structure of FBMC/OQAM signal.

B. Conventional Partial Transmit Sequence Scheme for FMBC/OQAM PAPR reduction techniques are classified into several different approaches: clipping technique, coding technique, probabilistic technique, and DFT-spreading technique. The probabilistic technique is to scramble an input data block of the symbols and transmit one of them with the minimum PAPR, so that the probability of incurring high PAPR can be reduced. PTS and TR belong to this approach. Let S denote the input signal in frequency domain. S is partitioned into V sub-blocks with Smv  [S1v , S2v ,..., SMv ]T . Unlike the SLM technique in which scrambling is applied to all sub-carriers, scrambling (rotating its phase independently) is applied to each sub-block in the PTS technique. Then each partitioned sub-block is multiplied by a corresponding complex phase factor bv  e j v , v  1, 2,...,V . The time domain signal after the combination is given by V

sm  t    bv smv  t 

(4)

v 1

where smv  t  is presented as a partial transmit signal. The phase vector is chosen so that the PAPR can be minimized, which is shown as [b1 ,..., bV ]  arg min max 1 v [ b ,...,b ]

0  t T

In the PTS scheme, the phase rotation operation is used for each transmit data block signal independently. When we utilize PTS scheme to reduce PAPR in FBMC/OQAM systems, the overlapped structure debases the optimization performance. This conclusion could be verified by the simulations in Section 4.

V

 bv smv t 

2

(5)

v 1

Then, the corresponding time domain signal with the lowest PAPR vector can be expressed as V

sm (t )   b v sm (t )

(6)

The selection of the phase factors bv 

is limited to a set of

v 1

V v 1

PAPR reduction vector Cmn .The input symbols in frequency domain can be expressed as  C n , n   Smn  Dmn  Cmn   nm C (7)  Dm , n   n C n Cm  0, for n   , Dm  0, for n   where   n1 , n2 ,..., nR  denotes the set of tones reserved for peak reduction, C denotes the set of data subcarriers, and C is the complement set of  in   1, 2, , N . The data tones in time domain d (t ) are generated by N point IFFT operation of Dmn . d (t ) is clipped to a threshold A as  d (t ), d (t )  A  d  t    jd   Ae , d (t )  A

(8)

where d  t   d  t  e jd , and  d is the phase of d (t ) . Then, the original clipping noise is f (t )  d  t   d (t ) ,

F, n   Cmn   (9) C 0, n   where F  FFT( f ) , f is the time domain clipping noise signal. Then, the peak reduced FBMC/OQAM signal can be written as PAPRTR (dB)  10log10

max

iT  t  ( i 1)T

s  t   c(t )

2

(10) 2 E  s t     where c(t ) is time domain peak reduction signal. By properly selecting proper peak reduction signal, the peak power of the FBMC/OQAM signal can be reduced to a certain range. However, it cannot achieve the same performance of reducing PAPR as that in OFDM systems. As we mentioned previously, OFDM signals independently select the proper peak reduction signal for each data block, because there is no overlap between the blocks. On the other hand, the FBMC/OQAM signal is overlapped by the adjacent data blocks. Therefore, the

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4 reduction of PAPR in FBMC/OQAM system has limited effect by the conventional TR scheme. III. PROPOSED HYBRID SCHEME In this section, we propose a hybrid PTS-TR PAPR reduction scheme. For simplicity, we call this scheme as “Hybrid”. Unlike existing PTS and TR schemes for OFDM systems, the proposed method exploits the overlapping signal structure. Moreover, according to the overlapping factor, the data blocks are divided into several segments. In each segment, the first data block is optimized by some sub-blocks multiplied with the phase rotation factors. While dealing with the second data block, the optimal phase rotation factors are generated by selecting the minimum power between the first and the second data blocks. It is obvious that this operation considers the adjacent data blocks overlapping effect. Then, the following data blocks are taken the same procedure. The clipping noise signal of each optimized segment is obtained by a certain clipping threshold. Moreover, another scheme called as M-hybrid is also proposed, which considers the adjacent multi data blocks overlapping influence. A. Hybrid PTS-TR Scheme The length of the prototype filter is greater than the period of FBMC/OQAM symbol, thus, there exists overlaps between adjacent FBMC/OQAM data blocks. We can clearly understand the overlapping nature of the FBMC/OQAM symbols from Figure 2. The first data block overlaps with the next   1 data blocks. We divide the data blocks into M  segments, then the iterative clipping filtering algorithm is utilized to generate the peak canceling signal for each optimized segment signal. This operation is used to get better peak canceling signal. Obviously, in FBMC/OQAM systems, this approach can provide better PAPR reduction than conventional TR, which independently cancels the peak signal of each data block. Inspired by PTS scheme, the proposed hybrid scheme optimizes every data block signal by choosing optimal phase rotation. The optimal phase rotation in proposed scheme is determined by taking the adjacent data blocks effect into account, where the data block optimal phase rotation is based on the idea of minimizing signal power between current data block and previous data block. The optimal phase rotation in the proposed approach is obtained from a different way compared with the traditional method. The Hybrid algorithm is presented below. Step 1: Firstly, divide the M data blocks into M  segments, each segment has  data blocks. Then optimize the first segment. Step 2: The first data block signal s1 (t ) in the first segment is partitioned into V disjoint sub-blocks s1v  t  for v  1, 2,...,V . The data block signal s1v  t  is multiplied with the phase rotation factor b1v  1, 1 . For simplicity, bkv  1, 1 is easily implemented. Then, the optimal phase factor combination of s1v  t  with the minimum PAPR is selected as

V

arg min v b1

max

0  t    1 2 T

 b1v s1v  t 

2

(11)

v 1

The first optimal data block signal can be expressed as (12) x1 (t )  b1v s1v  t  Step 3: Calculate the second data block optimum phase rotation factor. Be different with Step 2, taking the overlapping effect from the first data block into account, the optimal phase factor is selected as V

arg min v b2

max

T  t     3 2 T

x1 (t )   b s  t  v 1

2

v v 2 2

(13)

where formula (13) indicates that the optimal phase factor is based on the idea of minimizing signal power between the first data block signal and the second data block signal. Using this algorithm to calculate the following data block signal until to the  th data block signal, the optimal phase factor is selected as V

arg min v b

max

(  1)T  t   2  1 2 T

x 1  t    bv sv  t 

2

(14)

v 1

Then, the first segment data blocks signal can be written as 

x1  t    xm  t 

(15)

m 1

Step 4: The first segment signal is to clip the amplitude of the signal with a predefined threshold A  x1 (t ), x1 (t )  A  (16) x1  t    j x 1 Ae , x ( t )  A   where x1  t   x1  t  e j x ,  x is the phase of x1 (t ) .The expected clipping signal corresponding to (16) is

x1 (t )  A 0,  f 1 (t )   1 1 1  x  t   x (t ), x (t )  A

(17)

In order to reduce the interference of the data tones and avoid the bit error rate performance degradation, we utilize an approximate signal f 1 (t ) to reduce the peak power, which only has nonzero signal on the reserved tones. It needs several iterations to produce f 1 (t ) . In the Hybrid scheme, the FBMC/OQAM utilizes the reserved tones of several data blocks. However, the reserved tones of independent data blocks are utilized in OFDM systems. If the maximum number of iteration is reached, the iteration stops. The final peak canceling signal is  n  cm (t ), 0  t  (2   1 2)T f (t )   m 1  0, else  1

(18)

where cmn (t ) is the time domain signal corresponding to Cmn . Replace x1  t  with

x1  t   x1  t   f 1 (t )

(19)

Step 5: Go back to the Step 2, we calculate the optimal second segment data blocks signal. The first data block signal

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5 in second segment is jointly considered with the previous data block. Then, we can obtain the second segment data blocks signal as 2



x2 t  

m  1

xm  t 

x2  t   x 2 t   f 2 (t )

(21)

where x 2 . is not the square of x . , the superscript represents the number of segments. Step 6: According to Step 3 and Step 4, continue to calculate the residual segments. Finally, we can get all the optimized segment signals, the final PAPR reduction signal is M 

x

k

TABLE I SIMULATION PARAMETERS

(20)

Repeat Step 4, after peak canceling, we have

x(t ) 

distribution function (CCDF) is employed to measure the PAPR reduction performance. The detailed values of simulation parameters are listed in Table 1.

(t )

(22)

Parameters

Values

Total number of sub-carriers M data blocks Number of peak reduction tones with null sub-carriers Peak reduction tones set

64 16 4, 8

Modulation Overlapping factor Threshold (A) Number of sub-blocks (V) Number of clipping iterations

Random generation selection 4OQAM 4 2.2, 2.4, 2.6 4, 8 4

and

k 1

B. M-hybrid PTS-TR Scheme In the Hybrid scheme, we only consider the two adjacent data blocks overlapping effect. On the basis of the hybrid scheme, we investigate an approach to optimize multi data blocks together in each segment. As a complement of the Hybrid scheme, it is called as M-hybrid. The difference between the two algorithms is presented blow. Similar to Step 1 and Step 2 in Section 3.1, we obtain the first and second optimum data blocks signals. When calculate the third data block optimum phase rotation factor, we take the previous two data blocks influence into account. However, only one adjacent data block is utilized to minimize the data block signal power in Hybrid scheme. Thus, the optimal phase factor is selected as arg min v b3

max

2T  t     5 2 T

2

V

m 1

v 1

 xm (t )   b3v s3v t 

2

(23)

The  th data block phase factor is selected as  1

arg min v b

max

(  1)T  t   2  1 2T

V

 x t    b s t  v

m 1

m

v

OQAM data blocks signal

Hybrid scheme M-hybrid scheme

Dive the data blocks into M /  segments

Optimize the segment signals

Consider the two adjacent overlapped data blocks

Consider the multi adjacent overlapped data blocks

Minimize signal power between current data block and previous multi data blocks in each segment to obtain the optimal data block signal

YES Minimize signal power between current data block and previous data block in each segment to obtain the optimal data block signal

Get the segment clipping noise by clipping the segment signal to a threshold

2

(24)

v 1

The following operations are the same as in Hybrid scheme. In fact, in Hybrid scheme, the third data block is compared with the second data block to obtain a joint minimum signal power, although the second data block signal has already been jointly considered with the first data block signal. The M-hybrid repeatedly utilizes the previous overlapping data blocks to make the current data block signal with lower peak power. The flow chart of the two hybrid schemes is shown in Figure 3. IV. SIMULATION RESULTS In this section, we present some simulation results to verify our analysis. PAPR reduction performances of the proposed hybrid schemes versus the conventional PTS and TR schemes are discussed. The square root raise cosine filter is employed in this paper, the rolloff factor of the filter is 1, the length of the filter L h(t ) is chosen to 4T , where   4 . When h at least equal to T 4, the sampling signal PAPR can approach well to the consecutive signal PAPR [24]. The complementary cumulative

Add all the optimized and clipped segment signals

PAPR reduction signal

Fig.3. The flow chart of the Hybrid scheme and M-hybrid scheme.

Figure 4 shows the peak canceling signal of the Hybrid scheme, conventional PTS scheme, TR scheme and original signal. Peak powers of the signal appear in a few points, and most points have lower powers. It can be found that compared with two conventional PTS and TR schemes, the Hybrid scheme can efficiently reduce the peak powers of the signal. In Figure 5, we plot the CCDF curves for the M-hybrid, Hybrid and TR schemes with V  4 , peak reduction tones c  8 and A  2.4 . The curve “original” is the performance of FBMC/OQAM signal without any PAPR reduction processing. When CCDF= 103 , it is observed that the PAPR could be reduced by about 1.3 dB with the conventional PTS scheme, by 1.3 dB with the conventional TR scheme, by 2.8 dB with the

2169-3536 (c) 2016 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

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6 PAPR reduction. In the following simulations, A is chosen as 2.4. 0

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Hybrid scheme, and by 3 dB with the M-hybrid scheme, respectively. The two conventional schemes obtain the same PAPR reduction performance in FBMC/OQAM systems, and the PAPR reductions are both 1.3 dB. It is obvious that the two conventional schemes cannot effectively reduce the PAPR in FBMC/OQAM systems. The Hybrid scheme outperforms 1.5 dB than the PTS and TR schemes. The M-hybrid scheme only obtains 0.2 dB PAPR improvement than the Hybrid scheme. This indicates that the two hybrid schemes based on the consideration of the adjacent data blocks overlapping effect can offer significant PAPR reduction. In the following simulations, we focus on the performance of two hybrid schemes with different thresholds, different number of sub-blocks and different number of Peak reduction tones.

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Fig.6. PAPR reductions of the Hybrid and M-hybrid schemes with different thresholds.

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Fig. 4. Peak canceling signal of the Hybrid scheme, conventional PTS and TR schemes and original signal.

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Fig.7. PAPR reductions of the proposed schemes and the PTS scheme with V=4,8, respectively.

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Original Hybrid(A=2.2) Hybrid(A=2.4) Hybrid(A=2.6) M-hybrid(A=2.2) M-hybrid(A=2.4) M-hybrid(A=2.6)

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Fig.5. PAPR reductions for different schemes with V=4,c=8 and A=2.4.

In Figure 6, we show the PAPR reductions of the Hybrid and M-hybrid schemes with different clipping thresholds with V  4, c  8 . A is selected as A  2.2 , A  2.4 , A  2.6 . When CCDF= 103 , the PAPR reductions of the Hybrid scheme are 2.9 dB, 2.9 dB and 2.8 dB with A  2.2, 2.4, 2.6 , respectively, and the PAPR reductions of the M-hybrid scheme are 3.0 dB, 3.1 dB and 3.0 dB with A  2.2, 2.4, 2.6 , respectively. Obviously, when choose A  2.4 , it can achieve the highest

Figure 7 depicts the PAPR reduction of the proposed schemes with V  4 and V  8 , respectively. The number of sub-blocks for the PTS scheme and the proposed schemes is 4 and 8, respectively. It can be seen from Figure 7 that the PAPR could be reduced by 2.9 dB and 4.0 dB at CCDF= 103 for Hybrid scheme, with V  4 and V  8 , respectively. M-hybrid scheme can obtain about 0.2 dB performance gain better than Hybrid scheme. Increasing the number of sub-blocks could significantly improve the PAPR performance. The Hybrid scheme with V  8 outperforms the conventional PTS and TR schemes about 2.7 dB. The Hybrid scheme with V  8 achieves 1.9 dB more than it with V  4 . Different number of peak reduction tones for PAPR reductions of the proposed schemes is considered in Figure 8. When the number of peak reduction tones is 4, it can be found that the PAPR reduction performance degrades. Compared with the original signal at CCDF= 103 , the PAPR reduction gains of TR scheme are 0.7 dB and 1.4 dB when c  4, 8 ,

2169-3536 (c) 2016 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2016.2605008, IEEE Access

7 respectively. While the Hybrid scheme could provide PAPR reduction gains of 2.1 dB and 2.9 dB, and the M-hybrid scheme could provide PAPR reduction gains of 3.0 dB and 3.1 dB, when c  4, 8 , respectively. Obviously, increasing the number of peak reduction tones could significantly improve the PAPR reduction performance for the TR scheme and Hybrid scheme. However, it has limited influence to the M-hybrid scheme.

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Fig.8. PAPR reductions of the proposed schemes and the TR scheme with different number of peak reduction tones.

As show in the simulation results, it can be verified that the proposed hybrid schemes have improved PAPR reduction performance when compared with the two conventional schemes in FBMC/OQAM systems. V. CONCLUSIONS In this paper, we propose novel hybrid schemes for the PAPR reduction of FBMC/OQAM signals. The data blocks are divided into several segments to avoid the peak re-growth from the overlapped data blocks signal. The adjacent data blocks are utilized to obtain minimum power data block signal. Simulation results and analysis show that the Hybrid scheme is an efficient PAPR reduction method in FBMC/OQAM systems, and it can provide better PAPR reduction performance than the conventional PTS and TR schemes. By exploiting the Hybrid scheme, multi adjacent data blocks are jointly considered in the M-hybrid scheme. It has been verified that, under the same conditions, the M-hybrid scheme can achieve 0.2 dB better PAPR performance than the Hybrid scheme. ACKNOWLEDGMENT

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This work is supported by Hainan University excellent paper cultivation plan, the National Natural Science Foundation of China (Grant No. 61561017), the International Science and Technology Corporation Plan organized by the Ministry of Science and Technology of China, Grant No. 2015DFR10510. The authors would like to thank the editor and the anonymous reviewers for their valuable comments.

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2169-3536 (c) 2016 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.

This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2016.2605008, IEEE Access

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Han Wang received his B.S. degree in electrical engineering from Hubei University of Nationalities, China, in 2009 and the M.S. degree in information and communication system from Hainan University, Haikou, China, in 2013. He has worked in China Mobile Jiangxi branch as a network engineer for one year. Now, he is pursuing the Ph.D. degree with the Department of College of Information Science & Technology in Hainan University. His research interests include maritime communications and information theory.

Lingwei Xu was born in Shandong Province, China, in 1987. He received his M.E. degree in Electronics and Communication Engineering from Ocean University of China, China in 2013, and his Ph.D. degree from Ocean University of China in 2016. Now, he is a lecturer in Qingdao University of Science & Technology. His research interests include ultra-wideband radio systems, MIMO wireless systems, and M2M wireless communications.

Wencai Du received the B.S. degree from Peking University, China, two M.S. degrees from ITC, The Netherlands, and Hohai University, China, respectively, and Ph.D. degree from South Australia University, Australia. He was a Post-doctor Fellow in Israel Institute of Technology (IIT), Haifa, Israel. He is Dean of College of Information Science & Technology at Hainan University and Director of Maritime Communication and Engineering of Hainan province. He has authored or coauthored 18 books and more than 80 science publications. He is currently members of the Editorial Board of Inverts Journal of Science and Technology, India. He has taken services on many professional conferences, including Conference chair of IEEE/ACIS ICIS 2011, Conference Co-Chair of IEEE/ACIS SNPD 2010, London, Conference Chair of IEEE/ACIS SERA 2009, and Program Chair of IEEE/ACIS SNPD 2009, Daegu, Korea. His research interests include several aspects of Information Technology and Communication (ITC), including computer network and maritime communications.

Xianpeng Wang was born in 1986. He received his M.S. degree and Ph.D. degree in the College of Automation from Harbin Engineering University (HEU), Harbin, China, in 2012 and 2015, respectively. He was a Postdoctoral Research Fellow in the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, from 2015 to 2016. He is a faculty in the College of Information Science & Technology at Hainan University. He is the author of over 40 papers published in related journals and international conference proceedings, and has served as a reviewer of over ten journals. His major research interests include communication system, array signal processing, radar signal processing, compressed sensing and its applications.

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