在長期演進技術進階版(LTE-A)裡，利用載波聚合 (Carrier Aggregation)技術來提升傳輸的頻寬，藉此達到高傳輸速率。在LTE-A系統裡，上行系統為單載波分頻多重存取(SC-FDMA)擁有低峰均值功率比的特性，但是隨著聚合的載波個數越多，導致峰均值功率比的上升，打破原先的特性，因此本文採用部分選擇性映射(PSLM)的技術來降低因載波聚合所造成的峰均值功率比。傳送訊號因藉由乘上相位因子而能降低峰均值功率比，但是在接收端的部分須使用側訊息(Side Information)來還原訊號，其中側訊息代表為相位因子。由於系統需要額外傳送側訊息，使得傳送速率的降低。
為了避免造成上述情況，本文架構採用LTE-A上行的實體層上行分享通道(PUSCH)，其 PUSCH傳送時槽中的參考符元能夠替代側訊息的功能，因此不须額外傳送側訊息，但是需要在接收端的部分利用參考符元進行估測，將估測出的相位來進行訊號的還原。所以在本論文裡，探討現有兩種不須使用側訊息的相位估測技術，以及提出這兩種方法的修正型，並提出一個不需要側訊息的新方法。將這些方法在不同通道模型、不同等化器、不同的相位選擇性以及不同載波數的情境下進行BER效能模擬。最後進行全部方法的複雜度比較。

LTE-Advanced proposes carrier aggregation techniques which utilizes aggregated multiple carriers to increase the bandwidth and achieve high data rate. In practice, LTE-Advanced uplink systems adopt single carrier frequency division multiple access (SC-FDMA) which has a low Peak to Average Power Ratio (PAPR) characteristic. However, this characteristic will be lost as the number of aggregated carrier increasing. Therefore, we adopt the Partial Selected Mapping (PSLM) technique to reduce PAPR. PAPR will reduce by multiplying phase factor which represents as the side information (SI) at the receiver side. The receiver must have received the side information which can recover the signal’s phase and Systems will decrease data rate by extra transmitting SI.
To avoid this situation, our structure adopts Physical Uplink Shared Channel (PUSCH), its time slot structure includes reference symbol which be used for channel estimation. Therefore, we use the reference symbol to substitute the SI to achieve without directly sending SI. And we also use reference symbol’s characteristics to estimate the phase factor and recovery the signal’s phase by estimated phase. In this thesis, we will discuss the two phase detection techniques without using side information and modified them. In addition, we propose a new technique without using side information. Then, we will simulate the BER performance of all methods in different channel models, equalizers, phase candidates and number of aggregated carriers. Further, we will compare all methods in computational complexity.

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