PAPR Reduction in LTE-Advanced Carrier

Aggregation Using Low-Complexity Joint

Interleaving Technique

Abdel-karim Ajami, Hassan A. Artail, Mohammad M. Mansour

Department of Electrical and Computer Engineering

American University of Beirut

Beirut, Lebanon

Emails: {asa72, ha27, mmansour} @aub.edu.lb

Abstract—The demand for high data rates in both the uplink

and the downlink has motivated the use of carrier aggregation

(CA) of several portions of the spectrum up to 100 MHz in LTE-

Advanced, while maintaining backward compatibility with LTE

release 8. One of the main practical challenges that comes with CA

is the severe increase of peak-to-average-power-ratio (PAPR) of

the corresponding generated time-domain OFDM signal, thus

affecting the power amplifier (PA) efficiency, and hence the

transmission coverage. This paper proposes a low-complexity joint

interleaving technique to reduce the PAPR of carrier aggregated

signals. Several CA scenarios were analyzed using our proposed

technique. Simulation results demonstrate that our proposed

technique can achieve the same PAPR reduction performance as

that of the partial selective mapping (PSLM) technique with 66%

reduction in terms of real multiplication and addition operations for the case of three aggregated component carriers (CCs).

Keywords—Carrier aggregation; LTE-Advanced; PAPR; OFDMA; SC-FDMA

I. INTRODUCTION AND RELATED WORK

The evolution of multimedia applications and services requires the support of high peak data rates. In order to fulfill

this requirement, the next generation International Mobile

Telecommunications-Advanced (IMT-Advanced) system has

specified peak data rates of 1 Gbps in the downlink and 500

Mbps in the uplink [1][2]. The 3rd Generation Partnership

Project (3GPP) Long Term Evolution – Advanced (LTE-

Advanced) aims to achieve these peak data rates using a

maximum bandwidth of 100 MHz to be allocated to a certain

user. However, such large portions of contiguous spectrum are

rare in practice. As a result, the key enabling solution that was

adopted by LTE-Advanced to this feature is Carrier

Aggregation (CA) of multiple LTE Release 8 CCs [3]. Since LTE Release 8 supports CCs with maximum bandwidth of 20

MHz, LTE-Advanced allows carrier aggregation of up to five

20 MHz CCs using either Frequency Division Duplexing

(FDD) or Time Division Duplexing (TDD). In CA the allocated

CCs to a certain user may be contiguous or non-contiguous,

within the same frequency band (Intra-band) or across multiple

frequency bands (Inter-band).

Consequently, different scenarios of carrier aggregation

impose several challenges such as the increase of the PAPR of

time domain signals when a single Radio Frequency (RF) chain

with one PA is used at the transmitter side [4], as shown in

Fig. 1. The increase in PAPR is a serious issue for both the

uplink and the downlink in LTE-Advanced systems with CA.

The PAPR increase is caused by the existence of the same

Reference Signal (RS) pattern in addition to the data across the

CCs, thus adding constructively as the number of aggregated

CCs increases [5].

The reason for the same RS pattern is due to use of the same

Cell ID across aggregated CCs. Fig. 2 shows the RS distribution

pattern in the time-frequency plane. It should be noted that

although for the downlink, where Orthogonal Frequency

Division Multiplexing (OFDM) is used, the eNodeB may be

able to afford the PAPR increase caused by multiple CCs [5],

this increase is not desired since in [6] 3GPP has launched a

work item on energy savings management that targets

decreasing the transmission power in order to protect the

environment of future wireless systems. On the other hand, for

the uplink this issue is more critical due to the sensitivity of the

User Equipment (UE) to the PAPR property, where the Single Carrier - Frequency Division Multiple Access (SC-FDMA)’s

low PAPR characteristic is broken with the aggregation of

multiple CCs. Because of this, the N-x-SC-FDMA access

scheme was proposed [3]. The high PAPR problem may reduce

the performance of the uplink transmissions significantly and

result in interference with other systems, reduced cell coverage,

and system capacity loss. This is due to nonlinear distortions

that affect a signal with high PAPR at the transmitter PA.

There are several proposed PAPR reduction techniques in

the literature which can be divided into two parts. The first part

[7] considers only typical OFDM systems and not carrier-aggregated ones such as clipping and filtering technique, tone

injection, selective mapping (SLM), coding techniques, etc.

The second part considers carrier-aggregated systems, as in the

Multiplex 1

BB IFFT D/A

PA

L1

Multiplex 2

BB IFFT D/A

L2

Fig. 1 Transmitter architecture for CA

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case of LTE-Advanced. In [8] [9], the authors proposed a

combined method of frequency domain spectrum shaping using

a root raised cosine (RRC) filter and post IFFT time domain

random phase rotation using a set of phase masks such as {-1, -

j, 1, j}. Where as in [10], the authors proposed a method to

modify the generation of the downlink LTE-Release 8 RS sequence thus avoiding the same RS pattern across different

CCs but preventing backward compatibility with LTE-Release

8. In addition, this method only targets the RS effect on PAPR

and not the effect of aggregated data. In [11], the authors

proposed a precoding method based on polyphase constant

amplitude zero auto-correlation (CAZAC) sequence where

modulation symbols of each CC are multiplied by the

corresponding element in the generated sequence before IFFT

processing. In [12], the authors proposed a Codeword Mixing

(CW) technique where the symbols of different codewords

coming from different CCs are mixed via a certain pattern

before the DFT block. In [13], the authors proposed a PSLM technique which reduces the complexity of the SLM technique

by dividing the subcarriers of each CC into groups and

multiplying small number of these groups by vectors of phases

of size H thus resulting in H iterations. Then the signal with the

smallest PAPR is chosen for transmission. Finally in [14], the

authors proposed a technique based on two stages of noise

shaping where in the first stage the generated baseband OFDM

signal of each CC is clipped to a certain threshold A1 while in

the second stage the overall carrier aggregated passband signal

is further clipped to a wanted threshold A2.

Fig. 2 RS distribution in frequency-time plane [1]

In this paper we address the severe increase of PAPR in LTE-

Advanced CA systems due to both data and RS pattern where

we propose a low complexity data randomization technique

based on the interleaving concept [15]-[17].

Our contributions can be summarized as follows:

We propose a joint interleaving PAPR reduction technique for LTE-Advanced systems with CA.

The proposed method is backward compatible with

LTE-release 8.

We derive the computational complexity of our

proposed technique and we show a significant reduction

in the computational complexity as compared to PSLM

when both have the same PAPR performance.

The remainder of this paper is organized as follows. Section II shows the system model. Section III decribes our proposed

low complexity joint interleaving technique. Section IV

presents the derived computational complexities of our

proposed technique and that of PSLM. Section V discusses the

simulation results. Finally, section VI concludes the paper.

II. LTE-ADVANCED SYSTEM MODEL

For CA, the Orthogonal Frequency Division Multiple Access (OFDMA) scheme is used in the downlink, whereas in the uplink the N x SC-FDMA system is used. In LTE-Advanced, several LTE Release 8 CCs are aggregated to allow for higher peak data rates while keeping backward compatibility with LTE Release 8 users.

A. Downlink System Model

The LTE-Advanced downlink system model is summarized

in Fig. 3 (a) for the case of one CC, where every incoming bit

stream corresponding to one of the transport blocks is converted

from serial to parallel and then QAM modulated. We Let xi,λ,k

represent the QAM symbol at the λth OFDMA symbol and kth

subcarrier index of the ith CC, and let Nsymb denote the number

of OFDMA symbols in each subframe, where xi,λ,k is mapped to the (k, λ) element of the resource grid. In addition we define

fi to be the difference of the center frequency of the ith CC and

the first CC (i = 1) e.g. f1 = 0, where i ∈ { 1, 2, ... CCnb } and

CCnb denotes the number of aggregated CCs. As a result, the

complex baseband discrete-time signal corresponding to the λth

OFDMA symbol of the ith CC in a certain subframe is given by:

N

kf

niffλλ

,j2π

1N

0k

nj2πk,i,

DLi, eex(n)S

N

1 (1)

where n = 0, 1 …, N – 1 and λ = 0, 1 … Nsymb -1, with N corresponding to the Inverse Fast Fourier Transform (IFFT)

size. After the RRC pulse shaping, the complex passband signal

can be expressed by:

1N

0n

DLi,

2πDLi, nT)(n).r(tSe(t)S λ

tiλ

Fj (2)

where 0 ≤ t ≤ NT, T is the sample duration. Fi is the passband

frequency of the corresponding ith CC. The RRC pulse shaping

filter with roll-off factor 0 ≤ α ≤ 1 can be defined as follows:

2

22

T

t16α1

T

πt

α)(1T

πtcos

T

t4αα)(1

T

πtsin

r(t)

(3)

B. Uplink System Model

For the case of the LTE-Advanced uplink system model we consider the case of a user that is assigned with M subcarriers

over Nsymb SC-FDMA symbols per subframe of each CC. In this

case, the serial data stream of each CC is converted into parallel

data stream and then QAM modulated.

(a)

Bit

Stream

Coding

ModulationSubcarrier

MappingN-IFFT

Pulse

Shaping

& DAC

Bit

Stream

Coding

Modulation M-DFTSubcarrier

MappingN-IFFT

Pulse

Shaping

& DAC

(b)

Fig. 3 LTE-Release 8 Downlink (a) and Uplink (b) transmission schemes

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The QAM modulation symbols of the user for the λth SC-FDMA

symbol on the ith CC are the set {xi,λ,k} where k = 0, 1 … M-1.

However, for the case of uplink, the QAM modulation symbols

are precoded using a Discrete Fourier Transform (DFT) that is

applied to the QAM modulation symbols {xi,λ,k}. The DFT

block output is:

1M

0m

M

km2j

k,i,k,i, exXM

1

λλ (4)

where λ = 0, 1 … Nsymb -1 except for the SC-FDMA symbols

that are used for reference signals. After subcarrier mapping the

output of the IFFT is the complex baseband discrete time signal

corresponding to the λth SC-FDMA symbol of the ith CC in a

certain subframe and which is given by:

N

kf

niffnλλ

,j2π

1N

0k

j2πk,i,

ULi, eeX(n)S

N

1 (5)

Fig. 3 (b) shows the LTE Release 8 uplink transmission model

which corresponds to one CC. The complex passband signal

after RRC pulse filtering is given by:

1N

0n

ULi,

2πULi, nT)(n).r(tSe(t)S λ

tiλ

Fj (6)

C. Subcarrier Mapping

Subcarrier mapping at the input of the IFFT can be done

using two different methods for OFDMA and NxSC-FDMA in

the downlink and uplink of LTE-Advanced respectively. The

two methods are localized subcarrier mapping and distributed

subcarrier mapping, which are shown in Fig. 4.

LocalizedSubcarrierMapping

DistributedSubcarrierMapping

00

f0

f1

f2

fN-1

f0

f1

f2

fN-1

00

00

00

0000

0000

Fig. 4 Subcarrier Mapping Types

In localized subcarrier mapping the subcarriers are adjacent

to each other, while in distributed subcarrier mapping can be

further classified into two types: pure and interleaved

distributed subcarrier mappings. In the first subcarriers are

distributed randomly while in the second the subcarriers are

equidistant. In [18] the performances of different subcarrier

mapping methods were compared, and simulation results

showed that the interleaved distributed subcarrier mapping has

the best PAPR performance among all used methods.

III. PROPOSED LOW COMPLEXITY JOINT INTERLEAVING

PAPR REDUCTION TECHNIQUE

The proposed technique is built on the heuristic notion that

data frames with high correlation lead to large PAPR values.

Thus in order to break the correlation pattern we use K-1

interleavers that are distubuted in a smart way across CCs to

produce K-1 permuted and aggregated OFDM signals. These

signals are compared all together with the original aggregated

signal and the signal with the minimum PAPR is chosen for

transmission along with side information to allow the receiver

to recover the original data using a simple de-interleaving

operation without affecting backward compatibility to LTE-Release 8.

Fig. 5 shows a sketch map of the proposed low complexity

joint interleaving PAPR reduction technique at the transmitter

side for the downlink of LTE-Advanced system with CA. For

the sake of space, CA of only two CCs were presented in Fig.

5, however our proposed algorithm was tested for CA of up to

5 CCs. It is important to note that the proposed technique can

be applied not only in the downlink but also in the uplink case.

NxU

IFFT

Interlea

ver 2

Interlea

ver 1

S/P

b0,0 b0,1 b1,0 b1,1

∑

NxU

IFFTP/S

P/S

f2Coding

Modulation

CC1

Bit

Stream

CC2

Bit

Stream

Interleaving Optimizer PAPR

Coding

Modulation

Coding

Modulation

Coding

Modulation

S/P

Fig. 5 Proposed Low Complexity Joint Interleaving technique used at the

transmitter side for a downlink scenario with 2 CCs where the processing is

done in discrete-time domain which requires larger IFFT with size N U

where U represents the oversampling factor.

In this technique, we first generate at each CC an OFDM

signal using the initial modulation symbols for each CC without

any interleaving operation. Then these signals which

corresponds to the available CCs are aggregated together to

produce the original aggregated OFDM signal. In order to

produce K-1 additional versions of the aggregated OFDM

signal we propose to interleave sequentially the modulation

symbols corresponding to only one selected CC at each interleaving iteration v where v = 1,2 … K-1. This allows us to

generate a new OFDM signal at the selected CC only which is

then aggregated with the previously generated OFDM signals

of other CCs resulting in a new aggregated OFDM signal. The

interleaving operation is performed using a random block

interleaver that can achieve better PAPR reduction performance

among other types of block interleavers such as the periodic

interleaver as shown in [15]. The random interleaver permutes

a block of M modulation symbols on each CC in a pseudo

random order where a symbol of sequences x = (x0, x1, x2 …

xM-1 ) is reordered into x’ = (x𝜋(0), x 𝜋(1), x 𝜋(2), … x𝜋(M-1) ). The

mapping from {m} to {𝜋(m)} and vice versa is one-to-one

mapping where 𝜋(m) ∈ {0,1,2, … , M-1} for all m.

In order to control the interleaving operation as well as the

IFFT operation at a certain CC as shown in Fig. 5 we use control

bits {b0,0, b0,1, b1,0, b1,1} where b0,0 and b1,0 are used to control

the interleaving operation at the first CC (CC1) and the second

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677

CC (CC2) respectively. Setting b0,0 or b1,0 to one means that the

input modulation vector at the corresponding CC is randomly

interleaved. Otherwise, when b0,0 or b1,0 are set to zero the

modulation vector is forwarded as it is without any interleaving.

On the other hand, b0,1 and b1,1 are used to control the IFFT

operation at CC1 and CC2 respectively. Setting b1,0 or b1,1 to one means that the IFFT block will process the input vector of

modulation symbols and thus generate a new OFDM signal at

the corresponding CC otherwise the previously generated

OFDM signal remains the same.

At the the first iteration v = 1, we set b0,0 = b1,0 = 0. This

ensures that the original sequence of the vector of modulation

symbols of size M at each of CC1 and CC2 remains intact as

follows:

x1,λ = [ x1, λ,0 x1, λ ,1 x1, λ ,2 … x1, λ ,M-1 ] (7)

x2,λ = [ x2, λ,0 x2, λ ,1 x2, λ ,2 … x2, λ ,M-1 ] (8)

where λ = 0, 1 … Nsymb -1. Then in order to generate the OFDM

signal of each CC we set b0,1 = b1,1 = 1. This orders the IFFT

block to process x1 and x2 of CC1 and CC2 respectively as

follows:

N

kf

nffnλλ v

,1j2π1N

0k

j2πk,1,

DL1, eex

N

11)(n,S (9)

N

kf

nffnλλ v

,2j2π1N

0k

j2πk,1,

DL2, eex

N

11)(n,S

(10)

n = 0, 1 …, N-1. After generating (9) and (10) according to (2) the aggregated OFDM signal can be written as:

1)(t,S1)(t,S1)(t,SDL2,

DL1,

DLAGG, vvv λλλ

(11)

Then the PAPR of the aggregated signal in (11) is calculated as follows where E [.] represent the expectation:

2DLAGG,

2DLAGG,

)(t,S

)(t,S PAPR

v

v

λ

λ

E

max

(12)

In the next iterations v ≥ 2, we sequentially select only one CCi where i ∈ { 1, 2, ... CCnb }. CCnb is equal to two in this case. Each time i is incremented according to the following equation:

i = (i) mod (CCnb ) + 1

(13)

As a result, we start by selecting CC1. Then we interleave only modulation symbols of CC1 by setting bi-1,0 = b0,0 = 1 as follows:

x’i,λ = [ x’i, λ,0 x’i, λ ,1 x’i, λ ,2 … x’i, λ ,M-1 ] (14)

and generate the corresponding new OFDM signal at CCi by setting bi-1,1= b0,1 = 1 according to:

N

kf

niffnλλ v

,j2π

1N

0k

j2πk,

DLi, eex'

N

1)(n,S i, (15)

The OFDM signals of other CCs that were previously generated remains the same by setting bj-1,0 and bj-1,1 to zero for j ≠ i where j ∈ { 1, 2, ... CCnb }. Then the signals from different CCs are aggregated according to the following equation:

NBCC

1i

DLi,

DLAGG, )(t,S)(t,S vv λλ

(16)

After K iterations the aggregated signal with the lowest PAPR is selected along with the interleaving sequences indexes for transmission. This can be described as follows:

where v =1, 2, …. K-1. The pseudo random sequences are stored at the transmitter and receiver sides respectively. In order to recover the original data, the receiver needs to know the interleaved sequence used for transmission thus side information must be passed from the transmitter to the receiver. The receiver then uses this information to de-interleave the modulation symbols at the ith CC as follows:

xi,,λ = 𝜋-1(x’i,,λ) = [ xi, λ,0 xi, λ ,1 xi, λ ,2 … xi, λ ,M-1 ] (18)

IV. COMPLEXITY ANALYSIS

In this section, we study the computational complexity of the proposed algorithm and compare it to the PSLM technique of [13] when both are applied to LTE-Advanced system with CA. As shown in the previous section, in the proposed joint interleaving technique, only the first iteration requires the IFFT operation to be performed over all the CCs, while other iterations only require one IFFT operation on the selected CC. This results in (CCnb+K – 1) IFFT operations where each operation requires

an IFFT of size (NU). In order to derive the complexity of the proposed joint interleaving technique, we divide the IFFT operation into multiplication and addition operations. Considering a radix-2 decimation-in-time IFFT implementation,

each IFFT operation of size NU requires (NU)log2(NU)

complex additions and (NU/2)log2(NU) complex multiplications [7]. These complex operations can be further realized in terms of real multiplications (RMUL) and additions (RADD) where each complex multiplication requires four RMUL and two RADD whereas each complex addition requires

two RADD. This results in 2(NU)log2(NU) RMUL and

3(NU)log2(NU) RADD for each NU IFFT operation. Thus the complexity of the proposed technique for CA of CCnb

component carriers and K interleaving iterations is equivalent to

(CCnb+K-1)(NU)log2(NU) RMUL and 3(CCnb+K-

1)(NU)log2(NU) RADD.

In the PSLM technique, we consider that the number of phase vectors applied is H. In each iteration v where v ∈ {1 ,2 , …, H}, the IFFT operation is performed across each CC. This implies that in each iteration we have CCnb IFFT operations

resulting in a total of (HCCnb) IFFT operations during the H

iterations. Each IFFT has a size of NU. As a result by breaking

this IFFT operation, we have 2(HCCnb)(NU)log2(NU)

RMUL and 3(HCCnb)(NU)log2(NU) RADD. However in addition to the IFFT operations done at each CC, PSLM applies

} ])(t,SPAPR[ {*)(t,SDLAGG,

DLAGG, min arg v

vv λλ (17)

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678

phase rotation to a selected number of subcarriers. The subcarriers are initially divided into S groups and P out of S groups (P < S) are selected for phase rotation. Then at each

iteration v the modulation symbols of size (P/S)N corresponding to the P selected groups of each CC are multiplied by a phase sequence of the same length and whose elements ∈ {0,𝜋}. According to [7], for each CC these phases can be

implemented in hardware using H(P/S)N addition operations instead of multiplications. As a result, for CA of CCnb

component carriers the phase rotation method requires

(CCnbH(P/S)N) addition operations. Thus the overall complexity of the PSLM technique for CA of CCnb component carriers and H interleaving iterations is equivalent to

2(HCCnb)(NU)log2(NU) RMUL and (HCCnb)((P/S) N +

3(NU)log2(NU)) RADD. The computational complexity of both the proposed joint interleaving technique as well as the PSLM technique is shown in Table I. In order to compare the computational complexity of both techniques we consider in section V the cost required for each technique to achieve the same PAPR reduction performance. Then we show the amount of complexity reduction that our proposed technique provides in terms of percentage of RMUL and RADD operations.

Table I – SUMMARY OF THE DERIVED COMPLEXITIES

Technique

Complexity

Proposed Joint

Interleaving

2(CCnb+K-1)(NU)log2(NU) RMUL

3(CCnb+K-1)(NU)log2(NU) RADD

PSLM

2(HCCnb)(NU)log2(NU) RMUL

(HCCnb)((P/S)N + 3(NU)log2(NU)) RADD

V. RESULTS AND DISCUSSION

In this section we show the simulation results for the proposed joint interleaving technique with various scenarios of CA in both uplink and downlink of LTE-Advanced. In addition, we provide a comparison between our proposed technique and the PSLM technique in terms of performance and computational complexity reduction. The PAPR reduction performance is measured using the complementary cumulative distribution function (CCDF) of the PAPR. Each CC has a bandwidth of 5 MHz. The simulation parameters adopted are the same as those of LTE-Advanced specifications shown in [2]. For the downlink, the number of subcarriers occupied by different users on each CC is 1320 subcarriers. While in the uplink each user occupies 72 subcarriers. The size of the IFFT is N = 2048 and the oversampling factor used for PAPR calculation is U = 8 for a better estimation of the PAPR. Thus the IFFT size becomes

NU = 20488 =16384. The modulation symbols of each CC are mapped to the corresponding subcarriers using localized subcarrier mapping mode. The same RS pattern is generated across the aggregated CCs. In order to evaluate the PAPR reduction performance of our proposed technique and compare it to that of the PSLM technique, we run extensive simulations using different numbers of CCs as well as different types of CA scenarios in each of the uplink and the downlink. In the uplink

case of PSLM, we consider (S = 6, P = 3) where as in the downlink we consider (S = 10, P = 3). Fig. 6 shows the case of CA of 2 non-contigous CCs in the uplink for small and large values of H and K used in PSLM and our proposed technique respectively.

Fig. 6 PAPR comparison for LTE-Advanced uplink with CA of two non-contiguous CCs and 16-QAM Modulation.

Fig. 7 PAPR comparison for LTE-Advanced downlink with CA of three contiguous CCs and 16-QAM Modulation

According to Fig. 6 we can see that with same number of iterations used in the proposed technique and PSLM both algorithms where K = H we have approximately the same PAPR reduction performance in the case of the uplink. On the other hand, Fig. 7 presents the downlink case also for small and large values of H and K when CA of three contiguous CCs is applied.

Fig. 8 PAPR comparison for LTE-Advanced downlink and uplink with CA of five contiguous CCs and 16-QAM Modulation.

Similarly, we can see that both algorithms have approximately the same PAPR reduction performance in the case of downlink. In order to investigate further the performance of both

8 8.5 9 9.5 10 10.5 11 11.510

-3

10-2

10-1

100

CC

DF

PAPR (dB)

Original

Proposed, K = 32

PSLM, H = 32

Proposed, K = 128

PSLM, H = 128

11 11.5 12 12.5 13 13.5 14 14.5 1510

-3

10-2

10-1

100

PAPR (dB)

CC

DF

Original

Proposed, K = 32

PSLM, H = 32

Proposed, K = 128

PSLM, H = 128

9 10 11 12 13 14 15 1610

-3

10-2

10-1

100

PAPR (dB)

CC

DF

Original UL

PSLM UL, H = 32

Proposed UL, K = 32

Original DL

PSLM DL, H = 128

Proposed DL, K = 128

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algorithms, we consider the case of CA of 5 contigous CCs in each of the uplink and the downlink. Fig. 8 shows that in the downlink as well as the uplink both techniques have the same PAPR reduction performance at different values of H and K repectively. Based on this result, we compare the number of RMUL and RADD required by substituting H = K in the second row of Table I. With simple calculations, it is possible to obtain the ratios of RMUL and RADD required by the proposed technique relative to that needed in the PSLM technique as shown in Table II.

Table II – COMPARISON OF THE PROPOSED TECHNIQUE AND

THE PSLM TECHNIQUE

Further more, to evaluate the complexity reduction that is achieved by the proposed technique we consider CA of three and five CCs where S = 6 and P = 3 as the case of the uplink. Same parameters used in simulations are adopted for the case of N and U where N = 2048 and U = 8. However regarding the number of iterations we consider K = 32. Fig. 9 shows the complexity reduction achieved by the proposed technique in terms of RMUL and RADD. It is clear that as the number of aggregated CCs increase the complexity reduction increases from 66 % at 3 CCs to 78% at 5 CCs. This is due mainly to the extra IFFTs operations required by PSLM and which increase as the number of CCs increase.

Fig. 9 Complexity reduction achieved by the proposed technique in case of

CA of three and five CCs.

VI. CONCLUSION

High PAPR signals remain a challenging issue for the CA LTE-Advanced system, especially in the case of the uplink, where the UE has energy constraints. In this paper, we have proposed a low-complexity method to reduce the high PAPR of the aggregated signal resulting from CA. Simulation results show that this method can effectively reduce the PAPR in different CA scenarios which allow to decrease the power consumption in both the uplink and downlink and increase the

efficiency of the PA. This results in better coverage and system capacity.

REFERENCES

[1] 3GPP TS 36.211, "Evolved Universal Terrestrial Radio Access

(EUTRA); Physical Channels and Modulation, Release 9," Dec. 2009.

[2] 3GPP TR 36.913, "Requirements for further advancements for Evolved

Universal Terrestrial Radio Access (E-UTRA) (LTE-Advanced) Release

9," Dec. 2009.

[3] Iwamura, M.; Etemad, K.; Mo-Han Fong; Nory, R.; Love,R., "Carrier

aggregation framework in 3GPP LTE-advanced [WiMAX/LTE

Update]," Communications Magazine, IEEE , vol. 48, no. 8, pp. 60-67,

August 2010.

[4] 3GPP R1-091812, "CM issues for UL carrier aggregation," May. 2009.

[5] 3GPP R1-093363, "CM/PAPR Reduction of Aggregated Carriers for

Uplink of LTE-Advanced," August, 2009.

[6] "3GPP Green activities / Energy Saving, V0.1.0, (2012-09)".

[7] Y. Rahmatallah and S. Mohan, "Peak-To-Average Power Ratio

Reduction in OFDM Systems: A Survey And Taxonomy", IEEE

Communications Surveys & Tutorials., vol. 15, no. 4, Fourth Quarter

2013.

[8] L. Kewen ; X. Ning, "PAPR Reduction of Uplink for Carrier

Aggregation in LTE-Advanced," in Proc. Int. Conf. on Information

Science and Engineering (ICISE), , pp. 224-226, Dec. 2010.

[9] H. W. Tseng; Y. G. Jan; Y. H. Lee; C. H. Chan; T. H. Kang;, "Low-

PAPR Spectral Filter For Carrier Aggregated Transmission System," in

Proc. Int. MultiConference of Engineers and Computer Scientists, pp.

623-627, March 2014.

[10] S. Zhang; J. Zhou; Q. Zhu; L. Qi;, "Downlink Reference-Signal for

Carrier Aggregation with Reduced Cubic Metric in LTE-Advanced," in

Proc. Int. Conf. on Information Engineering, pp. 292-295, Aug. 2010.

[11] Y. RUI; P. CHENG; M. LI; Q.T. ZHANG; M. GUIZANI, "Carrier

Aggregation For LTE-Advanced: Uplink Multiple Access and

Transmission Enhancement Features," IEEE Transactions on Wireless

Communications, vol. 20, no. 4, pp. 101-108, 2013.

[12] Y. Meng; G. shen; W. Zheng; Qi Jiang; Y.Tang; “PAPR Reduction with

Multiple Antennas Transmission for Carrier Aggregation”, in Proc. IEEE

Int. Sympos. On Personal, Indoor, and Mobile Commun. (PIMRC), pp.

615-619, Sept. 2012.

[13] P.Yen ; H. Minn ; C.C. Chong; “PAPR reduction for bandwidth-

aggregated OFDM and SC-FDMA systems” in Wireless

Communications and Networking Conference (WCNC), pp. 1363 -1368,

March 2011.

[14] Srivastava, G.K. ; Tadkapalli N.K.; “Crest factor reduction for carrier

aggregated OFDM systems” in Proc. Int. Conf. on Software,

Telecommunications and Computer Networks, pp. 1-6, Sept. 2012.

[15] A. D. Jayalath and C. Tellambura; "The use of interleaving to reduce the

peak-to-average power ratio of an OFDM signal", in Global

Telecommunications Conference (GLOBECOM), pp. 82-85, Dec. 2000.

[16] A. Wyglinski; R. Rajbanshi.; G.J Minden.; "OFDM symbol design for

peak-to-average power ratio reduction employing non-data bearing

subcarriers", in Proc. IEEE Conf. Wireless Communications and

Networking Conference (WCNC), pp. 554-558, Apr. 2008.

[17] A. Ghassemiand T. Gulliver,"PAPR reduction in OFDM based cognitive

radio with blockwise-subcarrier activation", in IEEE International

Conference on Communications (ICC), pp. 5598-5602, June 2012.

[18] G. Hyung, L. L. Junsung, and J. David , "Peak-to-average power ratio

of single carrier FDMA signals with pulse shaping," in Proc. IEEE Conf.

on Personal Indoor and Mobile Radio Communications (PIMRC), pp. 1-

5, Sep. 2006.

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2015 IEEE Wireless Communications and Networking Conference (WCNC 2015) - Track 1: PHY and Fundamentals

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