摘要

借助無線通信標(biāo)準(zhǔn)，例如LTE和5G，對較高的數(shù)據(jù)速率和光譜效率的重點(diǎn)促使無線原始設(shè)備制造商（OEM）采用新的傳輸格式，例如正交頻施加多元化（OFDM）。但是，這些信號在其信封中具有較大的波動(dòng)，由于其高峰值功率比（PAPR）而尤其容易受到非線性功率放大器（PA）畸變的影響。使用該高PAPR信號，PA非線性可以產(chǎn)生大量的信號扭曲，從而增加了位錯(cuò)誤率（BER）并因此而降低了信噪比。本文回顧了PAPR，它們起源于其中，如何分解發(fā)射陣容的RF組件，以及如何擺脫它們或至少減輕其對信號鏈的影響。

介紹

較新的調(diào)制格式（例如OFDM）和各種形式的正交振幅調(diào)制（QAM）在信號信封中具有較大的波動(dòng)。這會在信號中產(chǎn)生高papr。在非線性PA上播放高PAPR信號會產(chǎn)生光譜再生。光譜再生是指由增益壓縮引起的新頻率，而不是在原始輸入中。高papr會導(dǎo)致帶內(nèi)變形，從而降低了整個(gè)系統(tǒng)的BER性能。我們將討論一種解決方案，以幫助找到使用數(shù)字預(yù)性（DPD）和降低峰值因子（CFR）發(fā)動(dòng)機(jī)之間的效率和線性之間的正確系統(tǒng)權(quán)衡。

OFDM調(diào)制 - 每個(gè)人都在這樣做！

在LTE和5G系統(tǒng)中，正在并行傳輸幾個(gè)載體的載體聚集用于提高帶寬和數(shù)據(jù)速率。這些網(wǎng)絡(luò)杠桿OFDM調(diào)制是一種非常熟練且使用廣泛使用的多載波傳輸技術(shù)，可以提高光譜效率并降低多路徑反射對接收器解碼信號的能力的影響。使用OFDM，最終波形是攜帶信息的子載波的正交總和，每個(gè)子載波都有其自己的中心頻率和調(diào)制方案。在時(shí)間域中，有時(shí)這些子載波的峰可以對齊以產(chǎn)生一個(gè)巨大的OFDM波形峰。OFDM的一個(gè)獨(dú)特特征是，子載波波形是正交組合的，因此一個(gè)子載波的空null（或零振幅）與圖1所示的其他子載波的峰值相吻合。這提供了通道帶寬相對有效的使用，從而與傳統(tǒng)的單一單位模塊相比，相對有效地使用了該通道帶寬。

圖1 DM子載體波形的多載體。

OFDM還有其他幾個(gè)好處，包括其對多徑褪色的穩(wěn)健性。但是，OFDM調(diào)制的主要問題之一是傳輸波形遭受高papr的影響。圖2顯示了各種普通移動(dòng)技術(shù)或調(diào)制類型的PAPR?？梢杂^察到，隨著新標(biāo)準(zhǔn)或調(diào)制技術(shù)的出現(xiàn)，典型的PAPR一直在穩(wěn)步增加。

圖2。各種調(diào)制技術(shù)的典型PAPR。

ofm信號

如前所述，由OFDM調(diào)制啟用的載波聚集用于提高5G系統(tǒng)中的帶寬和數(shù)據(jù)速率。 OFDM還會產(chǎn)生信號的信號，其信封是非構(gòu)恒定的，這可能會導(dǎo)致較高的PAPR，這可能會導(dǎo)致系統(tǒng)損壞。如果RF信號系列（尤其是PA）中的RF功率組件不能適當(dāng)?shù)刂付ㄒ蕴幚眍A(yù)期的電壓峰，則這些組件可能會失敗。一個(gè)大的PAPR通過將PA的效率推向飽和，從而降低了PA的效率，即其非線性工作區(qū)域，導(dǎo)致失真導(dǎo)致信號的光譜擴(kuò)散。對于非穩(wěn)定 - 內(nèi)玻璃數(shù)字調(diào)制方案而言，PA的線性一直是一個(gè)關(guān)鍵的設(shè)計(jì)問題。圖3顯示了一個(gè)時(shí)域LTE 64-QAM信號，該信號在ADRV9040的發(fā)射器輸出。

圖3。造成大峰的子載波的正交求和的例證。

互補(bǔ)分布函數(shù)

由于其形式，OFDM信號需要采用統(tǒng)計(jì)方法進(jìn)行適當(dāng)?shù)臏y量。補(bǔ)充累積分布函數(shù)（CCDF）用于評估RF信號鏈中的PAPR降低性能。圖4a顯示了LTE下行鏈路10 MHz帶寬和64個(gè)QAM子載波調(diào)制信號的傳輸波形。圖4b中的CCDF顯示，信號功率在0.01％的時(shí)間內(nèi)至少超過7.4 dB。理論最大峰值出現(xiàn)在0％的概率上，該概率在此圖上不確定。該痕量在約7.4 dB的PAPR處與X軸（0.01％或概率為10E ^-4^ ）相交。這表明每10,000個(gè)中的一個(gè)樣本預(yù)計(jì)將超過7.4 dB的平均功率。

圖4。具有10 MHz帶寬和64個(gè)QAM子載波調(diào)制的LTE下行鏈路的CCDF。

仔細(xì)觀察CCDF圖后，觀察Y軸是累積的概率，通常在對數(shù)刻度上繪制。 X軸是DB中繪制的功率。該圖顯示信號功率超過平均功率或高于平均功率的概率或時(shí)間百分比。從本質(zhì)上講，對于每個(gè)功率水平，CCDF圖描述了信號在平均功率水平以上的時(shí)間。隨著CCDF曲線向右移動(dòng)，我們的峰值功率與平均功率的比率增加。

CCDF圖可驗(yàn)證線性操作，并且在PA之后更常見。與通常在不同功率水平下增益變化的方法相比，它可以更準(zhǔn)確地描述信號壓縮。波峰因子發(fā)生的統(tǒng)計(jì)分析使其成為設(shè)計(jì)人員評估放大器壓縮對系統(tǒng)BER和/或誤差矢量幅度（EVM）的影響的寶貴工具。

那么，為什么PAPR很重要？

PAS本質(zhì)上是非線性的，在線性和效率之間表現(xiàn)出權(quán)衡。常見的非線性問題是增益壓縮和相失真，包括帶外和帶外變形。這些因素中的每一個(gè)都會降低系統(tǒng)的性能，并創(chuàng)建帶外光譜再生，從而導(dǎo)致相鄰的渠道干擾，并違反了監(jiān)管機(jī)構(gòu)規(guī)定的帶外排放標(biāo)準(zhǔn)。

在測試PA時(shí)，輸入幅度逐漸增加，直到測得的比率降低1 dB，代表1 dB增益壓縮。 1 dB壓縮點(diǎn)是功績的關(guān)鍵圖形，它為RF設(shè)計(jì)師提供了有關(guān)其放大器性能的假設(shè)。從本質(zhì)上講，放大器的1 dB壓縮點(diǎn)被定義為從其小信號值降低設(shè)備增益下降1 dB的輸出功率。該參數(shù)通常用作放大器非線性開始的參考點(diǎn)，大約等于放大器的最大可用峰輸出功率。這就是為什么許多RF設(shè)計(jì)人員通常估計(jì)其PA的最大工作輸出功率比其1 dB壓縮點(diǎn)低幾dB的原因。這使得在PA的1 dB壓縮點(diǎn)成為關(guān)鍵練習(xí)，為了使PAPR高的信號永遠(yuǎn)不會飽和PA。 PAPR的另一個(gè)名稱是波峰因素。圖5顯示了所示的1 dB壓縮點(diǎn)的AM-AM曲線。

圖5。具有1 dB壓縮點(diǎn)的AM-AM曲線。

現(xiàn)在，設(shè)計(jì)師已經(jīng)評估了PA并確定了其1 dB的壓縮點(diǎn)，他們需要在其線性區(qū)域中以輸入功率向后進(jìn)行操作PA（例如，在其工作曲線的線性部分內(nèi)以較低的功率操作PA）以避免光譜增長，對嗎？好吧，不完全是！

僅僅備份了遠(yuǎn)離PA的飽和點(diǎn)的輸入，肯定可以幫助避免討論的所有非線性問題，但會導(dǎo)致非常低的效率并增加散熱耗散。通過增加系統(tǒng)的功耗來解決這種低效率問題并不是可行的權(quán)衡。如圖2所示，隨著標(biāo)準(zhǔn)機(jī)構(gòu)具有新的調(diào)制方案的創(chuàng)新性，可以更好地利用現(xiàn)有頻譜，這導(dǎo)致信號具有越來越高的波峰因素。因此，從長遠(yuǎn)來看，使用PA返回實(shí)施策略將不起作用。本文的下一個(gè)部分將討論兩種實(shí)施策略，結(jié)合在一起，將使PA運(yùn)行到其飽和點(diǎn)，同時(shí)仍保持良好的線性性并大大提高其效率。第一個(gè)使用振幅剪切技術(shù)來減少PAPR，第二種方法是將PA在其預(yù)期功率范圍內(nèi)的非線性響應(yīng)線性化。

非常成功的數(shù)字前端解決方案的兩個(gè)功能

在無線數(shù)字前端（DFE）系統(tǒng)中，涵蓋了廣泛的子系統(tǒng)，包括DPD，Digital Upconversion（DUC），數(shù)字下降轉(zhuǎn)換（DDC）和CFR。還有其他重要領(lǐng)域，例如DC偏移校準(zhǔn)，脈搏形成，圖像排斥，數(shù)字混合，延遲/增益/不平衡補(bǔ)償，誤差校正和其他相關(guān)塊。 DPD電路使用PA輸出處捕獲的數(shù)據(jù)來線性化PA輸出。 DPD通過允許PAS更有效地操作來改善系統(tǒng)線性，而CFR有助于限制信號PAPR。使用CFR減少信號的動(dòng)態(tài)范圍后，使用DPD發(fā)動(dòng)機(jī)，并允許PA在線性區(qū)域上方操作。盡管這些塊中的每個(gè)塊涵蓋了DFE的關(guān)鍵功能，但本文的這一部分將僅關(guān)注CFR和DPD塊。

波峰因子降低

OFDM波形的大多數(shù)輸入信號將在PA的線性范圍內(nèi)。但是，如前所述，該信號的峰值可能超過PA的線性工作范圍，由于其對系統(tǒng)損害的貢獻(xiàn)，它引起了長期可靠性問題。同樣，非常需要在不飽和的情況下以最高輸入功率驅(qū)動(dòng)PA。為了避免由于峰值而導(dǎo)致的飽和度，使用了CFR，而不是衰減整個(gè)信號，而是減弱了PA線性范圍以上信號的部分。簡而言之，CFR有助于保持PA線性。

抑制峰時(shí)，這會導(dǎo)致恒定的輸出功率，從而確保信號保持在PA的線性范圍內(nèi)。請注意，CFR不是線性化技術(shù)，而是一種效率提高方案。 CFR憑借其最有效的實(shí)施，消除了發(fā)射信號的峰值，以降低峰與平均比率，同時(shí)遵守所需的光譜發(fā)射掩碼，相鄰的通道功率比和EVM規(guī)格。圖6顯示了檢測到的信號峰高于閾值水平。峰的幅度降低至低于某些目標(biāo)值。這通常是過濾以重塑信號頻譜。

圖6。檢測到的信號峰高于閾值。

CFR的缺點(diǎn)是剪輯會導(dǎo)致帶內(nèi)信號失真，導(dǎo)致BER性能下降和帶外輻射，從而將帶外干擾信號施加到相鄰的通道上。簡而言之，剪輯的后果是信號ACLR和EVM差。過濾夾板信號通常用于以峰值再生成本減少帶外輻射。

數(shù)字預(yù)性

使用DPD，可以將PA推動(dòng)以直至飽和區(qū)域，而不會損害其線性特性。 DPD允許RF設(shè)計(jì)人員在PA的有效但非線性區(qū)域操作其系統(tǒng)，同時(shí)保留OFDM調(diào)制所需的發(fā)送信號線性。換句話說，使用DPD，PA的線性區(qū)域擴(kuò)展了。 DPD發(fā)動(dòng)機(jī)通過對PA的逆AM-AM和AM-PM特性進(jìn)行建模來產(chǎn)生預(yù)性系數(shù)。本質(zhì)上，DPD專注于提高PA在其峰值效率點(diǎn)運(yùn)行時(shí)產(chǎn)生的信號的質(zhì)量。 DPD旨在引入彌補(bǔ)PA增益的反非線性。這是一種通過將精確的反抗原引入輸入波形，以補(bǔ)償PA的帶內(nèi)非線性產(chǎn)品的輸入波形，以提高非線性PA的線性。圖7顯示了DPD線性化PA響應(yīng)的概念。

圖7。用于線性化PA響應(yīng)的DPD的通用概念：（a）典型的AM-AM曲線顯示整個(gè)線性區(qū)域?yàn)榫G色； （b）DPD的基本概念及其如何提高功率放大器效率。

它根據(jù)預(yù)測數(shù)字域中的傳輸數(shù)據(jù)的原理來取消模擬域中的PA壓縮引起的失真。 DPD的方法可以從簡單的解決方案（例如基本查找表（LUT））到更復(fù)雜的實(shí)時(shí)信號處理方法。 DPD實(shí)現(xiàn)可以分類為具有內(nèi)存的無內(nèi)存模型和模型。

無內(nèi)存的DPD

無內(nèi)存的DPD僅基于當(dāng)前樣本來糾正智商樣本的幅度和相位。嚴(yán)格無記憶的PA可以以AM-AM和AM-PM轉(zhuǎn)換為特征。這種瞬時(shí)非線性通常以PA的AM-AM和AM-PM響應(yīng)為特征，其中PA輸出的輸出信號振幅和相位偏差作為其當(dāng)前輸入幅度的函數(shù)。因此，可以通過其AM-AM和AM-PM響應(yīng)來表征無內(nèi)存的PA。這些測量用于創(chuàng)建將每個(gè)輸入功率/相組合與產(chǎn)生所需線性輸出所需的功率/相相關(guān)聯(lián)的LUT數(shù)據(jù)。無內(nèi)存DPD的優(yōu)點(diǎn)是它可以作為查找表實(shí)現(xiàn)相對簡單。圖7a和7b顯示了具有和沒有DPD校正的PA的AM-AM響應(yīng)，應(yīng)用于2×100 MHz，400 MHz帶寬4096樣品數(shù)據(jù)集。

圖8。在2×100 MHz，400 MHz帶寬信號上具有和不帶DPD的PA的AM-AM響應(yīng)。

帶有內(nèi)存的DPD

隨著傳輸信號帶寬的變化，PA將開始表現(xiàn)出記憶效應(yīng)。這些是某些組件中的頻率響應(yīng)，例如偏置網(wǎng)絡(luò)，解耦電容器，電源電路，或可以歸因于活動(dòng)設(shè)備的熱常數(shù)。結(jié)果，PA的當(dāng)前輸出不僅取決于當(dāng)前輸入，還取決于過去的輸入值。在這種情況下，這意味著PA已成為具有內(nèi)存的非線性系統(tǒng)。帶有內(nèi)存的DPD基于以前的幾個(gè)樣本及其相互依賴性，糾正了iQ數(shù)據(jù)樣本的振幅和階段。 PA的響應(yīng)通常不僅取決于當(dāng)前信號振幅，還取決于先前樣品的幅度。因此，數(shù)字預(yù)性也需要具有內(nèi)存結(jié)構(gòu)，這是DPD的數(shù)學(xué)骨干。 Volterra系列是具有內(nèi)存的非線性最通用的多項(xiàng)式類型，用于模擬具有內(nèi)存的非線性系統(tǒng)。因此，引入內(nèi)存的最通用方法是使用Volterra系列。有關(guān)與Volterra系列的建模PA失真背后的數(shù)學(xué)細(xì)節(jié)的精心討論，該系列超出了本文的范圍，請參閱Masterson（2022）。這超出了本文的范圍，請參考Masterson（2022）。這超出了本文的范圍，請參考Masterson（2022）。^2^

輕松設(shè)計(jì)5G RF信號鏈的框架

ADRV9040 RF收發(fā)器提供了一個(gè)簡化的框架，可輕松設(shè)計(jì)，實(shí)現(xiàn)和測試5G通信系統(tǒng)的RF信號鏈陣容。一個(gè)離散的大型MIMO系統(tǒng)需要以其離散的部署形式進(jìn)行四個(gè)芯片級別，包括RF收發(fā)器，DFE FPGA，基帶FPGA/ASIC和控制FPGA。由于該收發(fā)器附帶了DFE集成，因此它消除了對競爭性離散解決方案中使用的幾種FPGA的需求，在該解決方案中，在計(jì)算機(jī)代碼中實(shí)現(xiàn)了DPD，CFR，DUC和DDC塊。 FPGA的實(shí)施通常是昂貴的，并且饑餓。這款高度集成的RF收發(fā)器有助于消除這種渴望強(qiáng)力的專用FPGA。在本文的這一部分中，我們強(qiáng)調(diào)了該RF收發(fā)器和提議的框架，用于檢查典型的PA增益陣容并通過在設(shè)備內(nèi)實(shí)現(xiàn)寄存器寫入噪聲限制的理智檢查。

芯片（SOC）上的這種高度集成的射頻敏捷收發(fā)器系統(tǒng)提供了八個(gè)發(fā)射器，兩個(gè)用于監(jiān)視發(fā)射機(jī)通道的觀察接收機(jī)，八個(gè)接收器，集成的本地振蕩器（LO）和時(shí)鐘合成器以及數(shù)字信號處理功能，以提供具有重要數(shù)字前端能力的完整收集器。該設(shè)備提供了由小細(xì)胞無線電單元（RUS），宏觀4G/5G RUS和大量MIMO RUS所需的高無線電性能和低功耗。完整的收發(fā)器子系統(tǒng)包括自動(dòng)和手動(dòng)衰減控制，DC偏移校正，正交誤差校正和數(shù)字過濾。收發(fā)器具有完全集成的數(shù)字前端，該數(shù)字前端支持一些關(guān)鍵塊，包括DPD（最多400 MHz IBW），高性能的三階段CFR發(fā)動(dòng)機(jī)，集成的數(shù)字下調(diào)和數(shù)字上轉(zhuǎn)換都能夠支持多達(dá)八個(gè)組件載體。該設(shè)備適用于帶有小型單頻段，多波段，TDD Massive Mimo和TDD/FDD的此類部署/應(yīng)用程序。圖9顯示了一個(gè)高級功能框圖。

圖9。ADRV9040高級功能框圖。

基于ZIF的體系結(jié)構(gòu)

ADRV9040的發(fā)射和接收信號路徑使用零IF（ZIF）體系結(jié)構(gòu)，該體系結(jié)構(gòu)提供寬帶寬度，具有適用于非連續(xù)多載波RU應(yīng)用程序的動(dòng)態(tài)范圍。 ZIF架構(gòu)具有低功率加上RF頻率和帶寬敏捷性的好處。該體系結(jié)構(gòu)提供了比離散解決方案的尺寸，重量和功率優(yōu)勢。該體系結(jié)構(gòu)使OEM能夠設(shè)計(jì)最小，最輕的5G巨大MIMO收音機(jī)40％輕40％，能源效率高約10％。對完整的小信號無線電板的分析表明，ZIF體系結(jié)構(gòu)可以在RF BOM與簡單導(dǎo)數(shù)RU上節(jié)省大量成本（PER 32T32R）。

零IF體系結(jié)構(gòu)還以LO頻率傳輸能量。由于智商混合和數(shù)據(jù)路徑的差異，引入了正交和LO泄漏誤差（例如，載體不集中在LO上）（例如，兩個(gè)混合器從未真正具有相同的特征）。在多載波和不對稱載體應(yīng)用中，這是一個(gè)更大的問題。為了減少這種不需要的發(fā)射，收發(fā)器具有TX LO泄漏校正算法，該算法都用于初始校準(zhǔn)，然后是在運(yùn)行時(shí)操作期間使用的跟蹤校準(zhǔn)。

CFR塊

該設(shè)備的CFR有助于保持PAS線性。這種低功率CFR發(fā)動(dòng)機(jī)可幫助設(shè)計(jì)人員降低輸入信號的峰值與平均值，從而使效率更高的傳輸線路UPS。如前所述，校正峰的光譜再生始終是CFR的關(guān)注點(diǎn)。至關(guān)重要的是，ADRV9040在優(yōu)化算法中起著至關(guān)重要的作用，以確保CFR塊的影響與OEM的系統(tǒng)規(guī)格保持一致。理想的CFR塊具有非常低的延遲，零缺少峰值。

圖10顯示了5G新無線電（NR）信號上PAPR降低的結(jié)果。 PER-CFR（左）圖顯示了峰值壓縮，這是由輸出信號的CCDF（黃色痕跡）以陡峭的速率掉落的，而隨著PAPR的增加，高斯參考ccdf（綠色痕跡）的速度較高。另一方面，CFR后（右）圖顯示了其CCDF與高斯信號相似的5G NR信號。

圖10。5GNR信號在應(yīng)用CFR之前和之后。

通過從檢測到的峰中減去預(yù)定的脈沖以使信號在PA的線性范圍內(nèi)，使用脈沖取消技術(shù)的變體實(shí)現(xiàn)此CFR。 CFR塊由CFR發(fā)動(dòng)機(jī)的三個(gè)副本組成，每個(gè)副本都使用檢測閾值來檢測峰和校正閾值，而檢測到的峰被減弱。這些頻譜校正脈沖從數(shù)據(jù)流中減去，以使信號在PA的線性范圍內(nèi)。校正脈沖需要在光譜上形狀，以將噪聲泄漏到相鄰的頻段中。 ADRV9040可以容納兩個(gè)校正脈沖，同時(shí)對應(yīng)于設(shè)備上的兩個(gè)不同的載波配置。這些校正脈沖可以預(yù)加載，并允許設(shè)備在即時(shí)兩種載波配置之間進(jìn)行切換。

DPD

該設(shè)備包含一個(gè)完全集成的低功率DP??D引擎，用于RF信號鏈線性化應(yīng)用。該引擎提供行業(yè)領(lǐng)先的DPD性能。如所討論的，介紹記憶的最通用方法是使用Volterra系列。該DPD發(fā)動(dòng)機(jī)基于廣義記憶多項(xiàng)式（GMP）和動(dòng)態(tài)偏差（DDR）的縮寫實(shí)現(xiàn)，它們是眾所周知的Volterra系列的廣義子集。在收發(fā)器的用戶指南和其他設(shè)計(jì)側(cè)支中詳細(xì)討論了ADRV9040中使用的廣義內(nèi)存多項(xiàng)式。通過DPD執(zhí)行器硬件將逆PA模型（PA ^-1^ ）應(yīng)用于插值數(shù)字基帶樣本。專用的嵌入式^ARM?Cortex?^^^A55處理器用于計(jì)算GMP系數(shù)。 DPD執(zhí)行器是可編程的多項(xiàng)式計(jì)算器。圖11顯示了應(yīng)用于插值數(shù)字基帶樣品的PA ^-1模型。^

圖11。將逆PA模型應(yīng)用于插值的數(shù)字基帶樣品。

該DPD算法支持間接學(xué)習(xí)和直接學(xué)習(xí)DPD機(jī)制，用于提取DPD模型系數(shù)。間接學(xué)習(xí)涉及使用觀察接收器數(shù)據(jù)作為預(yù)測與參考相對應(yīng)的輸入樣本的參考，而直接學(xué)習(xí)涉及使用DPD前執(zhí)行器發(fā)送信號作為參考以最大程度地減少觀察到的參考數(shù)據(jù)之間的誤差。兩者之間的區(qū)別在于，間接學(xué)習(xí)算法是時(shí)間效率的，但是直接學(xué)習(xí)算法更準(zhǔn)確，因?yàn)樗枰L的時(shí)間來收斂。在不需要DPD的系統(tǒng)應(yīng)用中，ADRV9040提供了一種通過GPIO控制繞過預(yù)性的機(jī)制。圖12顯示了在20 MHz LTE信號中使用DPD后ACLR的功率譜密度提高。通過在右圖上使用DPD，消除了左圖所示的ACLR的障礙。

圖12。功率光譜密度顯示DPD后ACLR的改善。

電源管理注意事項(xiàng)

使用正確的功率解決方案設(shè)計(jì)ADRV9040對于避免在TDD接收到傳輸過渡和實(shí)現(xiàn)最佳RF性能的問題之類的問題至關(guān)重要。 ADI SilentSwitcher?^技術(shù)^提供了多種區(qū)別，包括高切換頻率，超低RMS噪聲和點(diǎn)噪聲。無聲切換器3功率設(shè)計(jì)需要更少的組件，小的PCB足跡（尺寸），最重要的是一個(gè)更快且控制良好的瞬態(tài)沉降時(shí)間，從而導(dǎo)致超值EMI排放。圖13顯示了帶有一些建議的功率IC的宏基站的高級框圖，LT8627SP 和ADM7172 用于為ADRV9040電壓導(dǎo)軌提供動(dòng)力。

圖13。具有ADRV9040功率解決方案的宏RRH的系統(tǒng)級框圖。

ADS10-V1EBZ和ADRV904X-MB/PCBZ評估平臺

ADRV9040評估平臺有助于建立一個(gè)簡單明了的框架，用于測試用戶的設(shè)計(jì)。圖14呈現(xiàn) ADS10-V1EBZ （主板）和ADRV904X-MB/PCBZ評估板。請聯(lián)系您的ADI銷售代表以訂購您的評估系統(tǒng)。 RF設(shè)計(jì)師只需要將其設(shè)備連接到Eval平臺即可捕獲不同的圖，而ADRV9040進(jìn)行了繁重的舉重，以通過Data Byte將其寫入其寄存器中找到最佳性能配置。

圖14。ADS10-V1EBZ（主板）和ADRV904X-MB/PCBZ評估板。

結(jié)論

電信技術(shù)的進(jìn)步能夠通過載體聚合來提高數(shù)據(jù)速率通信和提高光譜效率，這也有助于PAPR的增加。但是，通過將CFR和DPD功能集成到專業(yè)設(shè)計(jì)的ADRV9040收發(fā)器中，無線電設(shè)計(jì)過程得到了簡化，從而減少了RF材料清單（BOM）成本，董事會尺寸，重量，重量和功耗，而不是常規(guī)的FPGA實(shí)施。隨著大量無線基站和全球部署的遠(yuǎn)程單元，提高的功率放大器效率可以顯著降低服務(wù)提供商的能源和冷卻成本。這不僅加速了上市時(shí)間，還可以幫助降低運(yùn)營費(fèi)用，并確保部署在網(wǎng)絡(luò)中時(shí)的合規(guī)性。

作者

Hamed M. Sanogo

Hamed M. Sanogo是ADI公司全球應(yīng)用部門的云和通信終端市場專家。Hamed擁有密歇根大學(xué)迪爾本分校的電子工程碩士學(xué)位，之后還獲得了達(dá)拉斯大學(xué)的工商管理碩士學(xué)位。在加入ADI公司之前，畢業(yè)后的Hamed曾在通用汽車擔(dān)任高級設(shè)計(jì)工程師，并在摩托羅拉系統(tǒng)擔(dān)任過高級電氣工程師以及Node-B和RRH基帶卡設(shè)計(jì)師。在過去的17年里，Hamed擔(dān)任過不同的職務(wù)，包括FAE/FAE經(jīng)理、產(chǎn)品線經(jīng)理，目前是通信和云終端市場專家。

附英文原文給大家參考：

Simplifying Your 5G Base Transceiver Station Transmitter Line-Up, Design, and Evaluation

摘要

With wireless communication standards such as LTE and 5G, the emphasis on higher data rates and spectral efficiency has driven the wireless original equipment manufacturers (OEMs) to adopt new transmission formats such as orthogonal frequency division multiplexing (OFDM). However, these signals, with large fluctuations in their envelopes, are especially vulnerable to nonlinear power amplifier (PA) distortions due to their high peak-to-average power ratios (PAPR). With this high PAPR signal, a PA nonlinearity can produce substantial signal distortions that increased bit error rates (BERs) and decreased signal-to-noise ratio as a result. This article reviews PAPRs, where they originate, how they can break down the RF components of the transmit line-up, and how to get rid of them or at least mitigate their effects on the signal chain.

Introduction

The newer modulation formats, such as OFDM, and various forms of quadrature amplitude modulation (QAM) have large fluctuations in their signal envelopes. This creates a high PAPR in the signal. Playing a high PAPR signal on a nonlinear PA generates spectral regrowth. Spectral regrowth refers to new frequencies that are caused by gain compression and were not in the original input. The high PAPR causes in-band distortion, which degrades the BER performance of the entire system. We will discuss a solution to help find the right system trade-off between efficiency and linearity using digital predistortion (DPD) and crest factor reduction (CFR) engines.

OFDM Modulation—Everyone Is Doing It!

In LTE and 5G systems, carrier aggregation, which is transmitting several carriers in parallel, is used to increase bandwidth and data rate. These networks leverage OFDM modulation, a very proficient and widely used multicarrier transmission technique that enables better spectral efficiency and reduces the impact of multipath reflections on the receiver’s ability to demodulate the signal. With OFDM, the final waveform is an orthogonal summation of subcarriers that carry information, where each subcarrier has its own center frequency and modulation scheme. In the time domain, sometimes the peaks of these subcarriers can align to produce an aggregate large OFDM waveform peak. A unique feature of OFDM is that the subcarrier waveforms are orthogonally combined such that the null (or zero amplitude) of one subcarrier coincides with the peak of other subcarriers as shown in Figure 1. This provides a relatively efficient use of the channel bandwidth, resulting in improved spectral efficiency compared to traditional single-carrier modulation.

Figure 1. Multicarriers OFDM subcarriers waveforms.

OFDM has several other benefits including its robustness against multipath fading. However, one of the major problems with OFDM modulation is that the transmitting waveforms suffer from a high PAPR. Figure 2 shows the PAPR of various common mobile technologies or modulation types. One can observe that the typical PAPR has been steadily increasing as new standards or modulation technologies have emerged.

Figure 2. Typical PAPR for various modulation technologies.

PAPR in OFDM Signals

As noted, carrier aggregation, enabled by OFDM modulation, is used to increase the bandwidth and data rate in 5G systems. OFDM also results in a signal whose envelope is nonconstant, and this can lead to high PAPR, which can contribute to system damage. If the RF power components in the RF signal line-up, especially the PA, are not suitably specified to handle the expected voltage peaks, these components can fail. A large PAPR reduces the efficiency of the PA by driving it deep into saturation, its nonlinear operating region, leading to distortion that results in spectral spreading of the signal. The linearity of the PA has always been a critical design issue for nonconstant-envelope digital modulation schemes. Figure 3 shows a time domain LTE 64-QAM signal captured at the ADRV9040’s transmitter output.

Figure 3. An illustration of orthogonal summation of subcarriers causing large peaks.

Complementary Cumulative Distribution Function

Due to its form, an OFDM signal requires a statistical approach for proper measurement. The complementary cumulative distribution function (CCDF) is used to evaluate the PAPR reduction performance in an RF signal chain. Figure 4a shows the transmitted waveform of an LTE downlink 10 MHz bandwidth and 64 QAM subcarrier modulation signal. The CCDF in Figure 4b shows that the signal power exceeds the average by at least 7.4 dB for 0.01% of the time. The theoretical maximum peak occurs at 0% probability, which is undefined on this plot. The trace intersects the x-axis (0.01%, or a probability of 10e ^-4^ ) at a PAPR of about 7.4 dB. This would indicate that one sample out of every 10,000 would be expected to exceed the average power by more than 7.4 dB.

Figure 4. CCDF of an LTE downlink with 10 MHz bandwidth and 64 QAM subcarrier modulation.

Upon taking a closer look at the CCDF graph, observe that the y-axis is cumulative probability and is usually plotted on a log scale; and the x-axis is power plotted in dB. The graph displays the probability or the percentage of time that a signal power is at or above the average power. Essentially, for each power level, the CCDF plot depicts the amount of time the signal spends above the average power level. As the CCDF curve moves to the right, the ratio of our peak power to the average power increases.

The CCDF plot verifies linear operation and is more often measured immediately after a PA. It can give a more accurate depiction of signal compression compared to the commonly used method of tracking changes in gain at differing power levels. The statistical analysis of crest factor occurrence makes it a valuable tool for designers to assess the impact of amplifier compression on the system’s BER and/ or error vector magnitude (EVM).

So, Why Is PAPR Important?

PAs are nonlinear in nature and exhibit a trade-off between linearity and efficiency. The common nonlinear problems are gain compression and phase distortion, including in-band and out-of-band distortions. Each of these factors degrades the BER performance of the system, as well as creates out-of-band spectral regrowth, which leads to adjacent channel interference, and violates out-of-band emissions standards mandated by regulatory bodies.

While testing a PA, the input amplitude is gradually increased until the measured ratio decreases by 1 dB, representing 1 dB gain compression. The 1 dB compression point is a key figure of merit that provides RF designers with assumptions about their amplifier’s performance. Essentially, the 1 dB compression point of an amplifier is defined as the output power at which the device’s gain drops by 1 dB from its small-signal value. This parameter is commonly used as a reference point for the beginning of amplifier nonlinearity and is approximately equal to the maximum useable peak output power for the amplifier. This is why many RF designers typically estimate their PA’s maximum operating output power to be a few dB lower than its 1 dB compression point. This makes finding the 1 dB compression point of a PA a crucial exercise, in order that a signal with a high PAPR is never allowed to saturate the PA. Another name for PAPR is crest factor. Figure 5 shows the AM-AM curve with the 1 dB compression point shown.

Figure 5. The AM-AM curve with the 1 dB compression point.

Now that the designer has evaluated the PA and identified its 1 dB compression point, they need to operate the PA in its linear region with an input power back-off (for example, operate the PA at a lower power within the linear portion of its operating curve) to avoid the spectral growth, right? Well, not exactly!

Simply backing off the input, far from the PA’s saturation point, can certainly help avoid all the nonlinear problems discussed, but results in very low efficiencies and increases heat dissipation. Solving this low efficiency problem by increasing the power consumption of the system is not a viable trade-off. As seen in Figure 2, as the standard bodies got innovative with new modulation schemes to make better use of the existing spectrum, this has resulted in signals with higher and higher levels of crest factor. So, using a PA back off implementation strategy would not work in the long run. The next sections of this article will discuss two implementation strategies that, when combined, will operate the PA up to its saturation point while still maintaining a good linearity and significantly increasing its efficiency. The first uses an amplitude clipping technique for PAPR reduction and the second method is to linearize the nonlinear response of a PA over its intended power range.

The Two Features of a Highly Successful Digital Front-End Solution

In a wireless digital front-end (DFE) system, a broad range of subsystems are covered, including DPD, digital upconversion (DUC), digital down-conversion (DDC), and CFR. There are also other important areas such as DC-offset calibration, pulse-shaping, image rejection, digital mixing, delay/gain/imbalance compensation, error correction, and other relevant blocks. The data captured at the output of the PA is utilized by the DPD circuit to linearize the PA output. DPD improves system linearity by allowing PAs to operate more efficiently, while CFR helps limit the signal PAPR. The DPD engine is used after using CFR to reduce the dynamic range of the signal and allows the PA to be operated above the linear region. While each of these blocks covers key features of the DFE, this section of the article will only focus on the CFR and DPD blocks.

Crest Factor Reduction

Most of the input signal of an OFDM waveform will be within the linear range of the PA. However, as previously shown, the signal has peaks that may exceed the PA’s linear operating range, which invites long-term reliability concerns due to their contribution to system damage. Again, it is highly desirable to drive the PA at the highest input power possible without having it saturate. To avoid saturation due to the peaks, CFR is used, where instead of attenuating the whole signal, only the portions of the signal that are above the PA’s linear range are attenuated. In short, CFR assists in keeping the PA linear.

When peaks are suppressed, this results in a constant output power, thus ensuring that the signal remains within the PA’s linear range. Note that CFR is not a linearization technique, but it is rather an efficiency improvement scheme. With its most effective implementation, CFR eliminates the peaks of the transmit signal to reduce the peak-to-average ratio while complying with the desired spectral emission mask, adjacent channel power ratio, and EVM specifications. Figure 6 shows detected signal peaks above a threshold level. The magnitude of the peaks is reduced to below some target value. This is usually followed by filtering to reshape the signal spectrum.

Figure 6. Detected signal peaks above the threshold level are reduced.

A downside of CFR is that clipping leads to in-band signal distortion, resulting in BER performance degradation, and out-of-band radiation, which imposes out-of-band interference signals to adjacent channels. In short, the consequence of clipping is poor signal ACLR and EVM. Filtering the clipped signal is often used to reduce out-of-band radiation at the cost of peak regrowth.

Digital Predistortion

With DPD, the PA can be pushed to operate up to the saturation region, without compromising its linear characteristics. DPD allows RF designers to operate their systems in the efficient, yet nonlinear, region of a PA while retaining the transmit signal linearity required of the OFDM modulation. In other words, with DPD the PA’s linear region is extended. The DPD engine produces predistorter coefficients by modeling the inverse AM-AM and AM-PM characteristics of the PA. Essentially, DPD focuses on improving the quality of a signal that the PA produces when operating at its peak efficiency point. DPD aims to introduce inverse nonlinearities that compensate for the PA gain. This is a technique for improving the linearity of a nonlinear PA by introducing precise antidistortion into the input waveform that compensates for the PA’s in-band nonlinear products. Figure 7 shows the concept of DPD for linearizing a PA response.

Figure 7. Generic concept of DPD for linearizing the PA response: (a) Typical AM-AM curve showing the overall linear region is in green; (b) basic concept of DPD and how it improves power amplifier efficiency.

It works on the principle of predistorting the transmitted data in the digital domain to cancel the distortion caused by PA compression in the analog domain. The approach to DPD can range from simple solutions such as a basic lookup table (LUT) to a more complex real-time signal processing approach. DPD implementations can be classified into memoryless models and models with memory.

Memoryless DPD

Memoryless DPD corrects the amplitude and phase of the IQ samples based on the current sample only. PAs that are strictly memoryless can be characterized by their AM-AM and AM-PM conversions. This instantaneous nonlinearity is usually characterized by the AM-AM and AM-PM responses of the PA, where the output signal amplitude and phase deviation of the PA output are given as functions of the amplitude of its current input. Therefore, a memoryless PA can be characterized by its AM-AM and AM-PM responses. These measurements are used to create LUT data that relates every input power/phase combination to the power/phase required to produce the desired linear output. The advantage of memoryless DPD is that it can be implemented relatively straightforward as a lookup table. Figures 7a and 7b show AM-AM response of a PA with and without DPD correction applied to a 2× 100 MHz, 400 MHz bandwidth 4096 samples dataset.

Figure 8. AM-AM response of a PA with and without DPD on a 2× 100 MHz, 400 MHz bandwidth signal.

DPD with Memory

As the transmit signal bandwidth gets wider, PAs will begin to exhibit memory effects. These are nonuniform frequency responses in certain components like the biasing network, decoupling capacitors, power supply circuitry, or can be attributed to thermal constants of the active devices. As a result, the current output of the PA then depends not only on the current input but also on past input values. When this is the case, this means that the PA has become a nonlinear system with memory. DPD with memory corrects amplitude and phase of IQ data samples based on several previous samples and their interdependencies. The response of the PA generally does not only depend on the current signal amplitude, but also on the amplitudes of the previous samples. Thus, the digital predistorter would also need to have memory structures—it is the mathematical backbone of DPD. The Volterra series is the most general polynomial type of nonlinearity with memory and used to model nonlinear systems with memory. Therefore, the most general way to introduce memory is to use the Volterra series. For an elaborate discussion on the details of the math behind modeling PA distortion with the Volterra series, which is beyond the scope of this article, please refer to Masterson (2022).^2^

Framework for Designing 5G RF Signal Chains with Ease

The ADRV9040 RF transceiver provides a streamlined framework for designing, implementing, and testing the RF signal chain lineup of a 5G communication system with ease. A discrete massive MIMO system requires four chip levels in its discrete form of deployment, including an RF transceiver, DFE FPGAs, baseband FPGA/ASIC, and a control FPGA. Since this transceiver comes with the DFE integrated, it eliminates the need for several FPGAs used in competitive discrete solutions where the DPD, CFR, DUC, and DDC blocks are implemented in computer code. The FPGA implementation is typically costly and power hungry. This highly integrated RF transceiver helps eliminate such power-hungry dedicated FPGAs. In this section of the article, we highlight this RF transceiver and a proposed framework for checking a typical PA gain line-up and doing a sanity check for noise limits by implementing register writes inside the device.

This highly integrated, radio frequency agile transceiver system on chip (SoC) offers eight transmitters, two observation receivers for monitoring transmitter channels, eight receivers, integrated local oscillator (LO) and clock synthesizers, and digital signal processing functions to provide a complete transceiver with significant digital front-end capability. The device provides the high radio performance and low power consumption demanded by cellular infrastructure applications such as small cell radio units (RUs), macro 4G/5G RUs, and massive MIMO RUs. The complete transceiver subsystem includes automatic and manual attenuation control, DC offset correction, quadrature error correction, and digital filtering. The transceiver has a fully integrated digital front-end that supports a few key blocks, including DPD (up to 400 MHz IBW), a high performance three-stage CFR engine, integrated digital downconversion and digital upconversion both capable of supporting up to eight component carriers. The device is suitable for such deployments/applications with small cell single-band, multi-band, TDD massive-MIMO, and TDD/FDD in macro-RU equipment. Figure 9 shows a high level functional block diagram.

Figure 9. An ADRV9040 high level functional block diagram.

ZIF-Based Architecture

The transmit and receive signal paths of the ADRV9040 use a zero-IF (ZIF) architecture that provides a wide bandwidth with dynamic range suitable for noncontiguous multicarrier RU applications. The ZIF architecture has the benefits of low power plus RF frequency and bandwidth agility. This architecture provides size, weight, and power advantages over discrete solutions. The architecture enables OEMs to design the smallest and lightest 5G massive-MIMO radios 40% lighter and ~10% more energy efficient. Analysis of a complete small signal radio board shows that the ZIF architecture enables significant cost savings (per 32T32R) on RF BOM vs. simple derivative RUs.

The zero-IF architecture also transmits energy at the LO frequency. The quadrature and LO leakage errors (for example, carriers are not centered on LO) are introduced due to differences in IQ mixing and data paths (for example, two mixers never really have the same characteristics). This is an even bigger issue in multicarrier and asymmetric-carrier applications. To reduce this undesired emission, the transceiver has a Tx LO leakage correction algorithm, which is used both for initial calibration followed by a tracking calibration used during runtime operation.

CFR Block

The device’s CFR assists in keeping PAs linear. This low power CFR engine helps designers reduce the peak-to-average ratio of the input signal, enabling higher efficiency transmit line ups. As mentioned previously, spectral regrowth of corrected peaks is always a concern with CFR. It is crucial to note that the ADRV9040 plays a vital role in optimizing the algorithm to ensure that the impact of the CFR block aligns with the system specifications of the OEM. The ideal CFR block has very low latency and zero missed peaks.

Figure 10 shows the results of a PAPR reduction on a 5G new radio (NR) signal. The pre-CFR (left) plot shows peak compression, which is indicated by the output signal’s CCDF (yellow trace) falling off at a steeper rate than the input, Gaussian reference, CCDF (green trace) as the PAPR increases. On the other hand, the post-CFR (right) plot shows a much improved 5G NR signal where its CCDF is similar to that of the Gaussian signal.

Figure 10. 5G NR signal before and after applying CFR.

This CFR is implemented using a variation of a pulse cancellation technique by subtracting a precomputed pulse from the detected peaks to bring the signal within the PA’s linear range. The CFR block consists of three copies of CFR engines, each of which uses a detection threshold to detect the peaks and a correction threshold to which the detected peaks are attenuated. These spectrally shaped correction pulses are subtracted from the data stream to bring the signal within the PA’s linear range. The correction pulse needs to be spectrally shaped to manage the noise leakage into adjacent bands. The ADRV9040 can hold two correction pulses corresponding to two different carrier configurations on the device at the same time. These correction pulses can be preloaded and allow the device to switch between two carrier configurations on-the-fly.

DPD Block

The device includes a fully integrated, low power DPD engine for use in RF signal chain linearization applications. This engine provides industry-leading DPD performance. As discussed, the most general way to introduce memory is to use the Volterra series. This DPD engine is based on an abbreviated implementation of generalized memory polynomial (GMP) and dynamic deviation reduction (DDR), which are generalized subsets of the well-known Volterra series. The generalized memory polynomials used in the ADRV9040 are discussed in detail in the transceiver’s user guide and other design collaterals. An inverse PA model (PA ^-1^ ) is applied to the interpolated digital baseband samples through the DPD actuator hardware. A dedicated embedded Arm^?^ Cortex^?^ A55 processor is used for the computation of the GMP coefficients. The DPD actuator is a programmable polynomial calculator. Figure 11 shows a PA^-1^ model applied to the interpolated digital baseband samples.

Figure 11. An inverse PA model is applied to the interpolated digital baseband samples.

This DPD algorithm supports both indirect learning and direct learning DPD mechanisms for extracting DPD model coefficients. Indirect learning involves using the observation receiver data as a reference for predicting the input samples corresponding to the reference, while direct learning involves using the pre-DPD actuator transmit signal as a reference to minimize the error between the observed and reference data. The difference between the two is that the indirect learning algorithm is time efficient, but the direct learning algorithm is more accurate since it requires a longer time to converge. In a system application where DPD is not needed, the ADRV9040 provides a mechanism to bypass predistortion through GPIO control. Figure 12 shows the power spectral density improvement in ACLR after the application of DPD for a 20 MHz LTE signal. The impairments that provoked the ACLR skirt shown on the left plot have been removed by using DPD on the right plot.

Figure 12. Power spectral density showing improvement in ACLR post-DPD.

Power Management Considerations

Designing the ADRV9040 with the right power solutions is paramount to avoiding issues such as the first symbol poor EVM (for example, Cyclic prefix) at the TDD receive-to-transmit transitions and to achieving optimum RF performance. The ADI Silent Switcher^?^ technology offers several differentiations, including high switching frequency, ultralow rms noise, and spot noise. A Silent Switcher 3 power design requires fewer components, a small PCB footprint (size), and most importantly a faster and well-controlled transient settling time, which results in ultralow EMI emissions. Figure 13 shows a high-level block diagram of a macro base station with a few suggested power ICs, LT8627SP and ADM7172 for powering the ADRV9040 voltage rails.

Figure 13. System-level block diagram of a macro RRH with the ADRV9040 power solutions.

ADS10-V1EBZ and ADRV904X-MB/PCBZ Evaluation Platform

The ADRV9040 evaluation platform facilitates the establishment of a simple and straightforward framework for testing the user’s design. Figure 14 presents the ADS10-V1EBZ (motherboard) and ADRV904X-MB/PCBZ evaluation board. Please contact your ADI sales representative to order your evaluation system. The RF designer only needs to connect his equipment to the eval platform to capture the different plots while the ADRV9040 does the heavy lifting to find the optimal performance configuration via data byte writes into its registers.

Figure 14. ADS10-V1EBZ (motherboard) and ADRV904X-MB/PCBZ evaluation board.

Conclusion

The advancements in telecom technologies that enable higher data rate communications and improved spectral efficiency through carrier aggregation also contribute to an increase in PAPR. However, by integrating CFR and DPD capabilities into the expertly designed ADRV9040 transceiver, the radio design process is simplified, resulting in reduced RF bill of materials (BOM) cost, board size, weight, and power consumption compared to conventional FPGA-based implementations. With a large number of wireless base stations and remote units deployed globally, improved power amplifier efficiency can significantly reduce energy and cooling costs for service providers. This not only accelerates time-to-market but also helps lower operational expenses (energy and truck rolls) and ensures compliance when deployed in networks.

關(guān)于作者

Hamed M. Sanogo

Hamed M. Sanogo是ADI公司全球應(yīng)用部門的云和通信終端市場專家。Hamed擁有密歇根大學(xué)迪爾本分校的電子工程碩士學(xué)位，之后還獲得了達(dá)拉斯大學(xué)的工商管理碩士學(xué)位。在加入ADI公司之前，畢業(yè)后的Hamed曾在通用汽車擔(dān)任高級設(shè)計(jì)工程師，并在摩托羅拉系統(tǒng)擔(dān)任過高級電氣工程師以及Node-B和RRH基帶卡設(shè)計(jì)師。在過去的17年里，Hamed擔(dān)任過不同的職務(wù)，包括FAE/FAE經(jīng)理、產(chǎn)品線經(jīng)理，目前是通信和云終端市場專家。