analysis, we use the Hitachi © 32-bit SuperH RISC micro controller with a maximum clock frequency of 28.7 MHz, where RMUL takes 4 cycles while RADD ...
A Low-Complexity PAPR Reduction Technique for LTE-Advanced Uplink with Carrier Aggregation Abdel-karim Ajami, Hassan A. Artail, Mohammad M. Mansour Department of Electrical and Computer Engineering American University of Beirut Beirut, Lebanon Emails: {asa72, hartail, mmansour} @aub.edu.lb
Abstract—In LTE-Advanced, carrier aggregation (CA) is a key enabling technique to increase the peak data rates of users and enhance the mobility management in heterogeneous networks (HetNets) using dual connectivity solutions. Several CA schemes have been proposed with a maximum of five LTE Release 8 component carriers (CCs) where the NxSC-FDMA has been chosen as the bandwidth extension scheme for the uplink. This enables the extension of the bandwidth allocated to a user up to 100 MHz while maintaining backward compatibility with LTE release 8 legacy users. However, CA leads to a severe increase in the peak-to-average-power ratio (PAPR) of the aggregated time domain NxSC-FDMA signal at the user equipment (UE). This is an important issue as it affects the power amplifier (PA) efficiency and hence the coverage of transmissions. In this paper, we propose a low-complexity post-IFFT technique to reduce the PAPR of carrier aggregated NxSC-FDMA signals in the uplink of LTE-Advanced. Several case studies of CA were analyzed by using the proposed technique. Simulation results show that the PAPR improvement is 2.5 dB for the case of 2 CCs at only about 4% of the complexity required by the partial selective mapping (PSLM) technique to achieve the same PAPR reduction. Keywords - Carrier Aggregation; LTE-Advanced; N×SC-FDMA; PAPR; Uplink;
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 system has specified peak data rates of 1 Gbps in the downlink and 500 Mbps in uplink [1][2]. The 3rd Generation Partnership Project (3GPP)’s Long Term Evolution – Advanced (LTE-Advanced, or LTE-A) 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 adopted by LTE-Advanced to this feature is CA of multiple LTE Release 8 CCs [3]. Since LTE Release 8 supports CCs with maximum bandwidth of 20 MHz, LTE-A allows carrier aggregation of up to five 20 MHz CCs using either Frequency Division Duplexing (FDD) or Time Division Duplexing (TDD). An advantage of CA can be realized in important deployment scenarios in HetNets such as Inter-site CA where the control plane (C-plane) and the user plane (U-plane) are separated in order to enhance the mobility
of users in densely populated areas [4]. 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 bands (Inter-band). Hence, different scenarios of CA impose several challenges like the increase of PAPR of time domain signals when a single Radio Frequency (RF) chain with one PA is used at the transmitter side [5]. This occurs in the case of Intra-band CA scenario only. The increase in PAPR is a serious issue for the uplink of LTE-A systems with CA. This increase is caused by the existence of the same reference signal (RS) pattern in addition to the inherent increase in the data across the CCs, thus adding constructively as the number of aggregated CCs increases [6]. The reason for the same RS pattern is the use of the same Cell ID across aggregated CCs. This issue is critical due to the sensitivity of the 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 using the N×SC-FDMA access scheme. 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 signals with high PAPR at the transmitter’s PA. To overcome the above problems, various approaches were proposed to reduce the PAPR in carrier-aggregated systems, as in the case of LTE-A. In [7] and [8], the authors proposed a combined method of frequency domain spectrum shaping using an RRC filter and time domain random phase rotation using a set of phase masks such as {-1, -j, 1, j} with different iterations, after which the signal with minimum PAPR and corresponding phase sequence are transmitted. In [9], the authors presented a precoding method based on polyphase constant amplitude zero auto-correlation sequence where modulation symbols of each CC are multiplied by the corresponding element in the generated sequence before Inverse Fast Fourier Transform (IFFT) processing. In [10], the authors propose a codeword mixing technique where the symbols of different codewords coming from different CCs are mixed via a certain pattern before the DFT block. Multiple techniques were presented in [11] and [12] based on selective mapping and interleaving, respectively, where PAPR is
978-1-4799-5952-5/15/$31.00 ©2015 IEEE
reduced by generating multiple versions of the carrier aggregated signal and then selecting the one with the smallest PAPR for transmission along with side information. In [13], a KLT based technique which allow for optimal decorrelation of the signals of CCs was proposed. Finally, in [14] and [15] the authors proposed techniques based on clipping and filtering of the generated signal of each CC to a certain threshold while reducing the in-band and out-of-band distortion resulting from such techniques. In this paper we address the severe increase of PAPR in uplink of LTE-Advanced CA systems due to both data and RS pattern. Our contributions can be summarized as follows: We propose a low-complexity, distortion-less, post-IFFT PAPR reduction technique for LTE-Advanced systems with CA. The proposed technique is based on the circular shift property of the Discrete Fourier Transform (DFT) and is backward compatible with LTE-release 8. The signalling overhead required by the proposed technique is reduced by exploiting the demodulation RS (DMRS) symbol used in each uplink time slot. The trade-off between the PAPR reduction performance and the required processing time is controlled by a parameter Q that determines the number of candidate aggregated signals to be generated. Finally, our proposed technique allows for a significant reduction in the computational complexity and processing time delay, as compared to the partial selective mapping (PSLM) technique [11], for the same PAPR performance. Note that although the idea of circular shift has been used to enhance the performance of partial transmit sequence (PTS) technique [16] in OFDM systems. However, it comes at the cost of very high computational complexity due to the requirement of several IFFT routines in frequency domain in order for the algorithm to converge. In this work, we provide promising PAPR improvement for carrier aggregated signals at low computational complexity where we apply circular shifts to the signals of different CCs without the need of repetitive IFFT routines. The remainder of this paper is organized as follows. Section II presents the uplink system model. Section III describes our proposed technique, while Section IV presents the technique used to reduce signalling overhead. Section V derives the computational complexities of our technique and that of PSLM. Section VI discusses the experimental results, and finally, section VII concludes the paper. II. LTE-A UPLINK SYSTEM MODEL AND THE PAPR PROBLEM For carrier aggregation, the N×SC-FDMA system is used in uplink to aggregate signals of several CCs. Considering the case of a user assigned with M subcarriers over Nsymb SCFDMA symbols per subframe of each CC, the serial data stream of each CC is converted into a parallel data stream and then QAM-modulated. 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. The QAM modulation symbols {xi,λ,k} are then precoded using DFT operation. The DFT block output is:
X i, λ, k =
M −1
1 M
∑x
i, λ, k
e
−j
2 π km M
(1)
m =0
where λ = 0, 1 … Nsymb -1 except for the SC-FDMA symbols that are used for the reference signal (RS). We let fi be the difference between the center frequency of the ith CC and the first CC (i = 1), where i ∈ { 1, 2, ... CCnb } and CCnb denotes the number of aggregated CCs. 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: UL S i,λ [n] =
1 N
N −1
∑X
i,λ,k
e j2πΔfn e
j2π f i n
,
k =0
Δf =
k N
(2)
where N corresponds to the IFFT size, while n = 0, 1 …, N-1 and λ = 0, 1 … Nsymb -1. As in [11], we ignore the cyclic prefix (CP) in our PAPR calculations as it is simply the cyclic extension of the signal itself. Fig. 1 (a) shows the LTE Release 8 uplink transmitter model which corresponds to one CC.
Fig. 1 LTE-Release 8 Uplink transmitter & receiver
Then the SC-FDMA signal in (2) is aggregated with the signals of other CCs to produce the corresponding aggregated N×SCFDMA signal as follows: UL S AGG, λ [n] =
CC nb
∑S
UL j,λ
[n]
(3)
j =1
A. Subcarrier Mapping Subcarrier mapping at the input of the IFFT can be done using two different methods for N×SC-FDMA in the uplink transmission of LTE-Advanced. The two methods are localized subcarrier mapping and distributed subcarrier mapping. In localized subcarrier mapping, the subcarriers are adjacent to each other, while 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 [17] the performance of different subcarrier mapping methods was compared, and simulation results showed that the interleaved distributed subcarrier mapping has the best PAPR performance among all used methods. B. PAPR Problem The PAPR of the aggregated N×SC-FDMA signal in (3) is defined as the ratio between the maximum instantaneous power and the average power of the signal as follows: PAPR =
UL max S AGG, λ [n ]
2
2⎤ UL E ⎡ S AGG, λ [n] ⎥ ⎢⎣ ⎦
(4)
Fig. 2 Proposed post-IFFT partitioning scheme
where E[.] denotes the expected value. In order to measure the PAPR performance, the complementary cumulative distribution function (CCDF) is used. It allows to evaluate the statistical characteristics of the PAPR by estimating the probability of PAPR to exceed a certain PAPR level defined as PAPR0. The CCDF expression of the PAPR can be written as: (5) CCDF = Pr (PAPR > PAPR 0 ) III.
PROPOSED PAPR REDUCTION TECHNIQUE
The proposed technique is based on the heuristic notion that the aggregation of CC signals with high correlation leads to large PAPR values. Thus in order to break the correlation pattern among the time domain signals of different CCs we propose to apply first a smart partitioning scheme as shown in Fig. 2 along the SC-FDMA signals generated across each of the ith CCs. We keep the first CC intact in order to maintain backward compatibility with LTE Release 8 users. Then we generate a candidate set of aggregated N×SC-FDMA signals by applying incremental circular shifts across each ith CC, i.e., i > 1, with a step size equals to the number of discrete time samples in each partition. Finally the aggregated N×SCFDMA signal with the minimum PAPR is selected for transmission along with the circular shifts applied across the corresponding CCs. Fig. 3 shows a sketch map of the proposed technique where we first generate at each ith CC the corresponding SC-FDMA signal using equations (1) and (2). Note that we process the signals in discrete time domain using an oversampling factor U equals to 4 for a better estimation of PAPR [18]. Thus the size of the IFFT becomes N×U. The SCFDMA signals coming from different CCs are then aggregated to generate the original aggregated N×SC-FDMA signal according to the following equation: UL S AGG, λ [ n , v = 1] =
CC nb
∑ Si,ULλ [ n, v = 1]
(9)
i =1
where v =1,2 … V represents the index of the aggregated N×SC-FDMA signal among the different V versions in the set, and λ = 0, 1 … Nsymb -1. Then in order to generate extra (V-1) different versions of the original aggregated signal we keep the SC-FDMA signal of the first CC intact while modifying the SC-FDMA signals of other CCs e.g. i = 2, … CCnb. Each time domain SC-FDMA signal corresponding to CCi , i ≥ 2 is first partitioned into Q subsets as shown in Fig. 2 where Q = 8 is chosen for proof of concept. This results in V = QCCnb -1 different versions of the same N×SC-FDMA signal. The
output of IFFT block at the ith CC which appears in (2) can be expressed by the following equation: UL S i,λ ( v ) = [ y 0 y 1 y 2 y 3 y 4 " y N ×U -1 ] (10) After applying the partitioning operation on the output of the IFFT that appears in (10), we get: Si,ULλ (v ) = [ p 0 p1 p 2 " p Q−1 ] (11) where each partition pq is of size (N×U)/Q with q = 0,1... Q 1. Next, for each ith CC, we start applying incremental circular shifts with a factor βi ∈ { 1, 2, ... Q } on the partitions that are shown in (11) to produce with each circular shift that is equivalent to ri = (βi×N×U)/Q a new SC-FDMA signal at the corresponding ith CC according to the following equation: UL S' UL i, λ ( v ) = C{S i, λ ( v ) , β i } = [ p ' 0 p '1 p ' 2 " p 'Q −1 ]
(12)
where p'q =0..Q−1 ∈ {p q }
Fig. 3 Proposed low-complexity PAPR reduction technique applied at the transmitter side for an uplink scenario in LTE-Advanced CA.
Then the signal in (12) is aggregated with the signals of the other CCs to produce the corresponding aggregated N×SCFDMA signal as follows: UL SAGG, λ [ n, v ] =
CC nb
∑S
UL j,λ
[ n, v ] + S'i,ULλ [ n, v ]
(13)
j =1, j ≠ i
The PAPR of the aggregated signal in (13) is calculated according to (4). Then after V iterations, the aggregated signal * with the lowest PAPR is selected along with side information βi = 1, 2 … CCnb for transmission. This can be described as follows: UL UL SAGG, λ [ n, v*] = arg min PAPR[ SAGG, λ [ n, v ] ]
v
(14)
\
where v =1, 2, …. V. In order to recover the original data, the receiver needs to know the number of partitions Q as well as the amount of circular shift applied for transmission, which is why side information must be passed from the transmitter to the receiver. As a result, the receiver can use this information to recover the transmitted signal at the ith CC where the output of the FFT block shown in Fig. 1 (b) is multiplied by exp(j2 kr/N) with k = 0, ... N-1, based on the circular shift property of the DFT [19]:
X i ,λ , k e
j 2πkr
= DFT {S iUL , λ [( n − r ) mod N ]}
N
(15)
The details of the proposed technique at the transmitter side is summarized in Fig. 4. S
UL i, λ
UL
S
UL AGG, λ
[ v* ]
S S
i, λ UL AGG, λ
nearest valid phase value. Based on their detection process we exploit the adjacent subcarriers in the RBs corresponding to each of the ith CC in order to transmit the set of side information β*i for each of the ith CCs. For every SC-FDMA symbol (D or R), shown in Fig. 5, the transmitter needs to send a set of β*i values, i.e., i > 1, corresponding to the circular shift applied along each of the ith CCs. Thus we need to transmit seven β*i values for each ith CC which can be transformed into phases according to exp(j2 β*i ), and transmitted using the first seven subcarriers of the RB with smallest index from the RBs allocated to the user by the eNodeB.
S S
UL AGG, λ
UL
[v = 0]
AGG, λ
[v = 0 ]
[ v = 0]
β i* = 0
Fig. 5 Uplink Time Slot Structure (Normal CP)
S
UL
i>1, λ
S
UL AGG, λ
S
[v ]
UL i, λ
S
UL AGG, λ
[v ]
At the eNodeB, the same phase detection process, as in [11], can be applied to recover the set of β*i values and thus apply the circular shifts. V.
PAPR{SUL AGG, λ [v]} < PAPR MIN ? , β i* = β i UL PAPR MIN = PAPR{SAGG, λ [v ]} UL
S
AGG, λ
UL
[v* ] = S AGG, λ [ v ]
v = v +1 v ≤V ?
S [v*] & β i*=0,1 ... CC Fig. 4 Transmission Algorithm UL
AGG,λ
IV.
nb
SIDE INFORMATION
In this section, we propose to reduce the signalling overhead by exploiting the SC-FDMA symbol for the demodulation reference signal (DMRS) in the uplink time slot, as shown in Fig. 5, where the DMRS is represented by the symbol “R”, and the data symbols are represented by the symbol “D”. The DMRS symbols are used for uplink channel estimation and data detection at the receiver, and the length of the DMRS sequence is equal to the number of subcarriers in the resource blocks (RBs) allocated to a certain user in uplink, where each RB corresponds to 12 subcarriers. In [11], the authors proposed to apply the same phase rotations used for PAPR reduction to the DMRS so that the receiver can detect the phase rotations applied to the data symbols from the DMRS where the phase processing used does not affect uplink channel estimation and is compensated for by the channel equalization process automatically. Note that in [11], the authors applied phase detection by extracting the phase difference between symbols of two adjacent subcarriers. The latter are assumed to have almost the same channel gain, which significantly reduces the effect of the channel on the phase detection. The phase difference is then rounded to the
COMPLEXITY ANALYSIS
In this section, we study the computational complexity of the proposed algorithm at the transmitter and receiver side, and compare it to the PSLM technique in [11], which has the most promising PAPR performance out of the techniques mentioned in section I. In our proposed technique, we process the signal in the time domain, thus the IFFT operation should be done only once across each CC. This results in (CCnb) IFFT operations where each operation requires an IFFT of size (N×U). To derive the complexity, we divide the IFFT operation into multiplication and addition operations. Considering a radix-2 decimation-in-time IFFT implementation, each IFFT operation of size N×U requires (N×U)log2(N×U) complex additions and (N×U/2)log2(N×U) complex multiplications [7]. These 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(N×U)log2(N×U) RMUL and 3(N×U)log2(N×U) RADD for each N×U IFFT operation. In addition, to produce each version v = 1, 2 .. V of the aggregated N×SC-FDMA signal, we need to do V aggregations and PAPR computations. According to [18], this translates to V×(2N×U 1) RMUL and V×(3N×U+CCnb -3) RADD. Similarly to recover the signal at the receiver side, this requires N×(CCnb -1) complex multiplications resulting in 4×N×(CCnb -1) RMUL and 2×N×(CCnb -1) RADD operations. On the other hand, the side information reduction technique used to transmit and receive the set of β*i requires 112×(CCnb -1) RMUL and 56×(CCnb -1) RADD operations. Thus the complexity of our technique requires 2(N×U)log2(N×U) +V× (2N×U - 1) + (4×N+112)×(CCnb -1) RMUL and 3(N×U)log2(N×U) + V(3N×U + CCnb - 3) +(2×N+56)×(CCnb -1) RADD operations. In the PSLM technique, we consider that the number of phase vectors applied is H. In each iteration h where h ∈ {1 ,2 , …, H}, the IFFT operation is performed across each CC. This
and different CA scenarios. Fig. 6 shows the simulation results in the case of two and three contiguous CCs for different values of Q, while Fig. 7 shows the results in case of four and five contiguous CCs. Figs. 6 and 7 show that for different CA scenarios, as the number of CCs increase the PAPR of the original aggregated signal increases. Moreover, PAPR decreases as Q increases, and hence the PAPR performance improves with the increase of V, which is the number of candidate aggregated signals. In order to compare our proposed technique to PSLM, we ran extensive simulations using several CA scenarios. In this comparison, we consider the values of Q and H for which both techniques provide the same PAPR reduction performance, so that we are able to compare their complexities. In the uplink case of PSLM, we consider (S = 6, P = 3). 0
10
-1
10
-2
10
-3
10
8
9
10 11 PAPR (dB)
Original Uplink 4 CCs Proposed 4 CCs, Q=2 Proposed 4 CCs, Q=4 Proposed 4 CCs, Q=8 Original Uplink 5 CCs Proposed 5 CCs, Q=2 Proposed 5 CCs, Q=4 Proposed 5 CCs, Q=8
-1
PSLM
10
RMUL
3(CCnb)(N×U)log2(N×U) +V(3N×U+CCnb-3) + (2×N+56)×(CCnb -1)
RADD
2(H×CCnb)(N×U)log2(N×U) + H(2N×U -1) (H×CCnb)(2×(P/S)×N+ 3(N×U)log2(N×U)) + H(3N×U + CCnb - 3)
VI.
CCDF
Proposed Technique
13
0
10
Complexity 2(CCnb)(N×U)log2(N×U) + V(2N×U - 1) + (4×N+112)×(CCnb -1)
12
Fig. 6 PAPR performance with CA of 2 and 3 contiguous CCs with 16-QAM
Table I – SUMMARY OF THE DERIVED COMPLEXITIES Technique
Original Uplink 2 CCs Proposed 2 CCs, Q=2 Proposed 2 CCs, Q=4 Proposed 2 CCs, Q=8 Original Uplink 3 CCs Proposed 3 CCs, Q=2 Proposed 3 CCs, Q=4 Proposed 3 CCs, Q=8
CCDF
implies that in each iteration we have CCnb IFFT operations resulting in a total of (H×CCnb) IFFTs during the H iterations. Each IFFT has a size of N×U. As a result by breaking this IFFT operation, we have 2(H×CCnb)(N×U)log2(N×U) RMUL and 3(H×CCnb)(N×U)log2(N×U) RADD. However in addition to the IFFT operations done for each CC, PSLM applies phase rotation to a selected number of subcarriers. The subcarriers are initially divided into S groups, and P out of the 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, }. According to [18], 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 CCs the phase rotation method requires (CCnb×H×(P/S)×N) RADD at the transmitter and (CCnb×H×(P/S)×N) RADD at the receiver to recover the initial modulation symbols. Furthermore, the aggregation operations and PAPR computations required in PSLM is equivalent to H×(2N-1) RMUL and H×(3N +CCnb 3) RADD. Thus the overall complexity of the PSLM technique for CA of CCnb component carriers and H iterations is equivalent to 2(H×CCnb)(N×U)log2(N×U) + H×(2N×U-1) RMUL and (H×CCnb)(2× (P/S)×N +3(N×U)log2(N×U)) + H×(3N×U + CCnb - 3) RADD. The computational complexity of both the proposed technique as well as that of the PSLM technique is shown in Table I. In order to compare the computational complexity and the time delay of both techniques, we consider in section VI the cost required for each technique to achieve the same PAPR reduction performance.
-2
10
RMUL -3
RADD
RESULTS AND DISCUSSION
In this section we present the experimental results of our proposed technique with various scenarios, and also provide a comparison between our proposed technique and PSLM. The PAPR reduction performance is measured using the complementary cumulative distribution function (CCDF) of the PAPR. Each CC has a bandwidth of 5 MHz, and the adopted simulation parameters, which comply with the LTE-A specifications shown in [2], are the same as that of [11]. The size of the IFFT is N = 2048, and each user occupies 72 subcarriers. The modulation symbols of each CC are mapped to the corresponding subcarriers using a localized subcarrier mapping mode, and the same RS pattern is generated across the aggregated CCs. We start by presenting the performance achieved by the proposed technique for different values of Q
10
9
10
11 12 PAPR (dB)
13
14
Fig. 7 PAPR performance with CA of 4 and 5 contiguous CCs with 16-QAM
Fig. 8 presents the results for both techniques with two and five contiguous CCs. We observe that in case of two CCs, both techniques achieve the same PAPR reduction when H = 32 for PSLM and Q = 8 (V = 82 -1 = 8) for our proposed technique. However in case of five CCs, both techniques achieve the same PAPR reduction at H = 32 for PSLM and Q = 2 (V= 25-1 = 16) for the proposed technique. We now use the complexity model that appears in Table I to compare the complexity and the time delay of both techniques using the simulation parameters mentioned above. First, we compare the relative computational complexity by calculating the percentage of RMUL and RADD operations required by the proposed technique, when compared to PSLM. Fig. 9 shows the complexity comparison in terms of RMUL and RADD where we can see that the proposed technique requires only
Original 2 CCs Uplink PSLM 2 CCs, H = 32 Proposed 2 CCs, Q = 8 Original 5 CCs Uplink PSLM 5 CCs, H = 32 Proposed 5 CCs, Q = 2
-1
10
32.4
31.2 Proposed PSLM
30 25 20 15 10 5 1.11 0
1.07
2 CCs
5 CCs Number of CCs
Fig. 10 Normalized time delay ratio of the proposed technique as compared to that of PSLM technique when both have same PAPR performance.
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] M. Iwamura, K. Etemad, Fong Mo-Han, R. Nory, and R. Love, "Carrier aggregation framework in 3GPP LTE-advanced [WiMAX/LTE Update]," Communications Magazine, IEEE , vol. 48, no. 8, pp. 60-67, August 2010. [4] Ericsson, Physical Layer Aspects of Dual Connectivity, St. Julians, Malta, Feb. 2013, 3GPP Standard Contribution (R1-130566). [5] 3GPP R1-091812, "CM issues for UL carrier aggregation," May. 2009.
0
10
35 Normalized Time Delay Ratio
about 4 % of the complexity needed by PSLM to achieve the same performance in case of two and five CCs. Next we compare the time delay introduced by both techniques. In this analysis, we use the Hitachi © 32-bit SuperH RISC micro controller with a maximum clock frequency of 28.7 MHz, where RMUL takes 4 cycles while RADD consumes 1 cycle. Thus based on the number of cycles required by each operation and the total number of RMUL and RADD operations required by each technique provided in Table I, we compute the total time delay required by each technique as follows: Time delay = Total number of cycles / Clock frequency We also normalize the time delay of each technique by the delay of the original case where neither techniques are applied. This is shown in Fig. 10, where we see that also the time delay introduced by our technique in the tested CA scenarios is negligible as compared to that of PSLM (e.g., 1.11 vs. 32.4) mainly due to the repeated IFFT routines used in PSLM.
[6] 3GPP R1-093363, "CM/PAPR Reduction of Aggregated Carriers for Uplink of
CCDF
LTE-Advanced," August, 2009.
[7] L. Kewen and X. Ning, "PAPR Reduction of Uplink for Carrier Aggregation in -2
10
[8] [9]
-3
10
9
10
11 12 PAPR (dB)
13
14
Fig. 8 PAPR performance comparison with 16-QAM
Relative Complexity (%)
I. CONCLUSION High PAPR signals remain a challenging issue for CA in the uplink of LTE-Advanced system, where the UE has power constraints. We proposed a distortion-less, low-complexity technique to reduce the high PAPR of the aggregated N×SCFDMA signals resulting from CA. Simulation results show that this technique can effectively reduce the PAPR in different CA scenarios of uplink of LTE-A at low complexity and small time delays. This allows to increase the efficiency of the transmitter’s power amplifier and enhance the coverage of the LTE-Advanced system.
3.34 % 3.38 %
[11] [12]
[13] [14] [15]
RMUL RADD
4
[10]
3.45 % 3.36 %
[16]
3
[17] 2
[18] 1
[19] 0
2 CCs
5 CCs Number of CCs
Fig. 9 Relative complexity of the proposed technique as compared to PSLM
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