閆文君,張立民,凌 青,孔東明
(1.海軍航空工程學(xué)院a.電子信息工程系;b.信息融合所,山東煙臺(tái)264001;2.海軍裝備部,太原030027)
空時(shí)分組碼的二階循環(huán)平穩(wěn)特性分析
閆文君1a,張立民1b,凌 青1a,孔東明2
(1.海軍航空工程學(xué)院a.電子信息工程系;b.信息融合所,山東煙臺(tái)264001;2.海軍裝備部,太原030027)
針對(duì)空時(shí)分組碼的盲識(shí)別問題,研究空時(shí)分組碼信號(hào)的二階循環(huán)平穩(wěn)特性。利用空時(shí)分組碼矩陣元素之間的相關(guān)性,給出了空時(shí)分組碼相關(guān)矩陣的傅里葉變換形式,推導(dǎo)出空時(shí)分組碼信號(hào)在不同時(shí)延參數(shù)下具有循環(huán)頻率的特征。通過仿真實(shí)驗(yàn),驗(yàn)證了推導(dǎo)過程的正確性,并定義了用于空時(shí)分組碼識(shí)別的決策樹,對(duì)空時(shí)分組碼盲識(shí)別技術(shù)的發(fā)展進(jìn)行了展望。
信號(hào)處理;空時(shí)分組碼;二階循環(huán)平穩(wěn)
近年來(lái),隨著無(wú)線通信技術(shù)發(fā)展,無(wú)線系統(tǒng)中信息的傳輸數(shù)量和傳輸速率越來(lái)越大,給無(wú)線通信技術(shù)帶來(lái)了巨大的挑戰(zhàn)。一個(gè)滿足傳輸信息數(shù)量增多、傳輸速率加快的需求的重要技術(shù)就是多輸入多輸出系統(tǒng)(Multiple Input Multiple Output,MIMO)[1]。MIMO系統(tǒng)中,不可避免地存在時(shí)變多徑衰落問題,解決有效手段之一就是天線分集技術(shù)[2]。利用天線分集的方法有發(fā)射分集和接收分集。接收分集可獲得很大的性能增益,它不僅有較好的鏈路預(yù)算資源,而且具有更強(qiáng)的抗鄰道干擾能力。來(lái)自不同接收天線的信號(hào)通常是通過數(shù)字硬件進(jìn)行合并,其性能增益與分集效果相關(guān),分集效果受不同天線不同路徑的信號(hào)之間的衰落的相互獨(dú)立性影響。當(dāng)今很多通信系統(tǒng)的基站都是采用接收分集。例如全球移動(dòng)通信系統(tǒng)(GSM)[2]的基站通常采用2根接收天線。然而,由于接收端功率、天線尺寸和成本的限制,在接收端通常不能實(shí)現(xiàn)任意增加天線。發(fā)射分集是在發(fā)射端增加發(fā)射天線,它可以改善整個(gè)無(wú)線通信系統(tǒng)的通信質(zhì)量而不需要每個(gè)接收者改善設(shè)備,這對(duì)于通信網(wǎng)絡(luò)運(yùn)營(yíng)商負(fù)擔(dān)不大,接收端用戶也樂于接受。增加基站復(fù)雜度,減少接收端復(fù)雜度也是未來(lái)無(wú)線通信系統(tǒng)發(fā)展的要求[3]。
空時(shí)分組碼(Space-Time Block Code,STBC)是隨著分集技術(shù)的發(fā)展而出現(xiàn)的一種非常有效的信道編碼方式[4]??諘r(shí)分組碼盲識(shí)別技術(shù)是一個(gè)新的重要的信號(hào)處理方向。如圖1所示,識(shí)別的問題主要有:發(fā)射天線數(shù)識(shí)別[5]、調(diào)制方式識(shí)別[6-8]、正交識(shí)別[9]和類型識(shí)別[10-23]4個(gè)方面。其中,空時(shí)分組碼類型識(shí)別分為基于最大似然的算法(Maximum Likelihood,ML)[10]和基于特征參數(shù)(Feature Based,F(xiàn)B)的算法。FB算法又分為基于高階統(tǒng)計(jì)量的算法[11-14]和基于二階相關(guān)特性的算法[15-23]。圖2為空時(shí)分組碼類型識(shí)別算法分類?;谧畲笏迫坏乃惴軌虻玫骄植孔顑?yōu)解,識(shí)別效果較好,但識(shí)別之前需要知道傳輸信號(hào)的信道信息、噪聲信息和調(diào)制信息,且計(jì)算復(fù)雜度較高?;谔卣鲄?shù)的算法識(shí)別前不需要知道傳輸信號(hào)的信道信息、噪聲信息和調(diào)制信息,計(jì)算復(fù)雜度較低。在實(shí)際系統(tǒng)中可根據(jù)系統(tǒng)狀況合理選擇識(shí)別方法。
圖1 空時(shí)分組碼識(shí)別問題分類Fig.1 Category of classification for STBC
圖2 空時(shí)分組碼識(shí)別算法Fig.2 Classification alaorithm for STBC
本文對(duì)空時(shí)分組碼的二階循環(huán)平穩(wěn)特性進(jìn)行分析,二階循環(huán)平穩(wěn)特性算法屬于基于二階相關(guān)特性的算法,通過建立接收信號(hào)的二階循環(huán)平穩(wěn)模型,可對(duì)不同空時(shí)分組碼進(jìn)行識(shí)別。
給定一個(gè)具有nt個(gè)發(fā)射天線、nr個(gè)接收天線的具有空時(shí)分組碼的線性通信系統(tǒng),設(shè)每個(gè)空時(shí)分組碼矩陣傳輸符號(hào)數(shù)為ne,各符號(hào)之間獨(dú)立同分布,經(jīng)歷的時(shí)間間隔數(shù)為L(zhǎng),則第k個(gè)碼矩陣傳輸?shù)姆?hào)為Sk=[sk(1),sk(2),…,sk(ne)],則空時(shí)分組碼碼矩陣是nt×L維矩陣,表示為Cu(Sv),其中u和v表示空時(shí)分組碼的第v個(gè)傳輸塊的第u列,其中0<u≤L。
空時(shí)分組碼類型很多,一般文獻(xiàn)常涉及的用于識(shí)別的典型空時(shí)分組碼有以下4種。
SM(Spatial Multiplexing,空間復(fù)用):發(fā)射天線數(shù)為nt=j,碼矩陣長(zhǎng)度L=1[8],
嚴(yán)格的講,SM并非空時(shí)分組碼。
AL(Alamouti STBC):發(fā)射天線數(shù)為nt=2,碼矩陣長(zhǎng)度L=2[4],
STBC3:發(fā)射天線數(shù)nt=3,碼矩陣長(zhǎng)度L=4[9],
STBC4:發(fā)射天線數(shù)nt=3,碼矩陣長(zhǎng)度L=8[9],
通過空時(shí)分組碼矩陣可以看出,在一個(gè)空時(shí)分組碼內(nèi),不同列之間的符號(hào)是相關(guān)的,而不在一個(gè)空時(shí)分組碼內(nèi)的不同列之間的符號(hào)是無(wú)關(guān)的。這在頻域上將表現(xiàn)出不同的循環(huán)譜和循環(huán)頻率。使用基于二階循環(huán)平穩(wěn)的算法的前提就是尋找接收信號(hào)的四階循環(huán)譜的循環(huán)頻率。定義接收信號(hào)為[23]:
式(1)中:t為符號(hào)周期T0內(nèi)一點(diǎn);Δf為載波頻偏;φ為相位偏移和相位噪聲;n(t)為加性高斯噪聲信號(hào),噪聲信號(hào)之間相互獨(dú)立,且與接收信號(hào)相互獨(dú)立;x(t)為第t時(shí)刻傳輸信號(hào),且有[23]:
式(2)、(3)中:hi(t)代表第i個(gè)發(fā)射天線的信道系數(shù);n為整數(shù)(本文中如無(wú)特殊說(shuō)明均如此定義);(t)表示為g(t-(k+l-1)T+ε);g(t)是發(fā)射端整形濾波器和接收端濾波器的級(jí)聯(lián);T為符號(hào)周期;ε代表發(fā)射濾波器和接收濾波器的時(shí)延;Ci,l代表編碼矩陣的第i行第l列元素,0<i≤nt、0<l≤L,且i和l必須是整數(shù)。
接收信號(hào)的二階時(shí)變自相關(guān)函數(shù)定義為[15]
式中,τ為時(shí)延參數(shù)。
接收信號(hào)二階時(shí)變自相關(guān)函數(shù)c(t,τ)的傅里葉變換為[23]
式中,α為時(shí)變自相關(guān)函數(shù)的循環(huán)頻率。
SM信號(hào)之間互不相關(guān),因而SM信號(hào)不具有循環(huán)頻率。因此
由式(8)可以觀察到cAL(t,τ)是周期為2T的周期函數(shù),式(7)可以進(jìn)一步寫為:
式(11)、(12)中,A(α,τ)是a(t,τ)的傅立葉變換。
如A(α,τ)與α相互獨(dú)立,顯然可得到FAL(α,τ)具有1/2T的整數(shù)倍的循環(huán)頻率。STBC3和STBC4的推導(dǎo)過程同理可得,本文不再進(jìn)行推導(dǎo)。
本節(jié)對(duì)本文提出的算法進(jìn)行驗(yàn)證,假定接收天線數(shù)為2,信號(hào)數(shù)為8 192,信號(hào)經(jīng)過QPSK調(diào)制,信道采用Nakagami-m衰落信道,信道參數(shù)m=3,噪聲采用高斯白噪聲,信噪比取-10dB。取不同時(shí)延參數(shù)τ∈{1,2,4}進(jìn)行仿真,見圖3~5。
圖3 τ=1時(shí),接收信號(hào)功率譜Fig.3 Power spectrum of received signals withτ=1
圖4 τ=2時(shí),接收信號(hào)功率譜Fig.4 Power spectrum of received signals withτ=2
圖5 τ=4時(shí),接收信號(hào)功率譜Fig.5 Power spectrum of received signals withτ=4
由圖3~5可得,當(dāng)時(shí)延參數(shù)τ=4時(shí),只有STBC4具有循環(huán)頻率;若排除STBC4,當(dāng)時(shí)延參數(shù)τ=2時(shí),只有STBC3具有循環(huán)頻率;當(dāng)時(shí)延參數(shù)τ=1時(shí),只有AL具有循環(huán)頻率,剩下的信號(hào)就是SM信號(hào)。該識(shí)別過程可用如圖6所示決策樹表示,其中,“是”表示具有循環(huán)頻率,“否”代表不具有循環(huán)頻率。
圖6 空時(shí)分組碼識(shí)別決策樹Fig.6 Decision tree of classification for STBC
本文在全盲條件下對(duì)空時(shí)分組碼識(shí)別中二階循環(huán)平穩(wěn)的算法進(jìn)行了分析,該方法具有不需要預(yù)先估計(jì)信道、噪聲和調(diào)制方式的特點(diǎn),經(jīng)過仿真,算法能明顯區(qū)分不同STBC信號(hào),在工程實(shí)現(xiàn)上具有很大的可行性。
作為無(wú)線通信領(lǐng)域一個(gè)新的重要研究?jī)?nèi)容,空時(shí)分組碼的識(shí)別應(yīng)重點(diǎn)關(guān)注:①接收天線數(shù)較少,甚至只有一根接收天線下空時(shí)分組碼盲識(shí)別問題,增大基站復(fù)雜度減少接收端復(fù)雜度是未來(lái)無(wú)線通信發(fā)展的必然要求;②OFDM與空時(shí)分組碼的結(jié)合條件下的空時(shí)分組碼盲識(shí)別;③STBC信號(hào)的調(diào)制識(shí)別算法。
[1]DOBRE OA,ABDI A,BAR-NESS Y,et al.A survey of automatic modulation classification techniques:classical approaches and new developments[J].IET Communications,2007,1(2):137-156.
[2]LARSSON EG,STOICA P.Space-time block coding for wireless communications[M].任品毅,譯.西安:西安交通大學(xué)出版社,2006:1-4. LARSSON EG,STOICA P.Space-time block coding for wireless communications[M].Ren Pinyi,translated.Xi’an:Xi’an Jiaotong University Press,2006:1-4.(in Chinese)
[3]DOBRE OA.Signal identification for emerging intelligent radios:classical problems and new challenges[J]. IEEE Instrumentation&Measurement Magazine,2015,18(2):11-18.
[4]ALAMOUTI SM.A simple transmit diversity technique for wireless communications[J].IEEE Journal on SelectedAreas in Communications,1998,16(8):1451-1458.
[5]SHI M,BAR-NESS Y,SU W.Adaptive estimation of the number of transmit antennas[C]//IEEE Global Telecommunications Conference.Orlando,F(xiàn)L:IEEE,2007:3034-3039.
[6]MAREY M,DOBRE OA.Blind modulation classification algorithm for single and multiple-antenna systems over frequency-selective channels[J].IEEE Signal Processing Letters,2014,21(9):1098-1102.
[7]PANAGIOTOU P,ANASTASOUPOULOS A,POLYDOROS A.Likelihood ratio tests for modulation classification[C]//21stCentury Military Communications Conference Proceedings.Los Angeles,CA:IEEE,2000:670-674.
[8]HAMEED F,DOBRE OA,POPESCU DC.On the likelihood-based approach to modulation classification[J]. IEEE Transactions on Wireless Communications,2009,8(12):5884-5892.
[9]趙知?jiǎng)牛x少萍,王海泉.OSTBC信號(hào)累積量特征分析[J].電路與系統(tǒng)學(xué)報(bào),2013,18(1):150-155. ZHAO ZHIJIN,XIE SHAOPING,WANG HAIQUAN. The characteristic analysis of cumulants of the OSTBC signals[J].Journal of Circuits and Systems,2013,18(1):150-155.(in Chinese)
[10]CHOQUEUSE V,MARAZIN M,COLLIN L,et al.Blind recognition of linear space time block codes:a likelihoodbased approach[J].IEEE Transactions on Signal Processing,2010,58(3):1290-1299.
[11]ELDEMERDASH YA,MAREY M,DOBRE OA,et al. Fourth-order statistics for blind classification of spatial multiplexing and alamouti space-time block code signals [J].IEEE Transaction on Communications,2013,61(6):2420-2431.
[12]CHOQUEUSE V,MANSOUR A,BUREL G,et al.Blind channel estimation for STBC system using higher-order statistics[J].IEEE Transactions on Wireless Communications,2011,10(2):495-505.
[13]ELDEMERDASH YA,DOBRE OA,MAREY M,et al. An efficient algorithm for space-time block code classification[C]//IEEE Global Communications Conference.Atlanta,GA:IEEE,2013:3329-3334.
[14]DEYOUNG M,HEALTH R,EVANS BL.Using higher order cyclostationarity to identify space-time block codes [C]//IEEE Global Telecommunications Conference.New Orleans,LO:IEEE,2008:3370-3374.
[15]CHOQUEUSE V,YAO K,COLLIN L.Hierarchical space-time block code recognition using correlation matrices[J].IEEE Transactions on Wireless Communications,2008,7(9):3526-3534.
[16]CHOQUEUSE V,YAO K,COLLIN L,BUREL G.Blind recognition of linear space time block codes[C]//Proc. IEEE International Conference Acoustics Speech and Signal Processings.Las Vegas:IEEE,2008:2833-2836.
[17]MAREY M,DOBRE OA,LIAO B.Classification of STBC system over frequency-selective channels[J].IEEE Transactions on Vehicular Technology,2015,64(5):2159-2164.
[18]QIAN G,LI L,LUO M,et al.Blind recognition of spacetime block code in MISO system[J].Journal on Wireless Communications and Networking,2013(6):201-205.
[19]LUO M,GAN L,LI L.Blind recognition of space-time block code using correlation matrices in a high dimensional feature space[J].Journal of Information&Computational Science,2012,9(6):1469-1476.
[20]MOHAMMADARIMI M,DOBRE O.A.Blind identification of spatial multiplexing and Alamouti space-time block code via Kolmogorov-Smirnov(K-S)test[J].IEEE Communications Letters,2014,18(10):1711-1714.
[21]MAREY M,DOBRE OA,INKOL R.Classification of space time block codes based on second-order cyclostationarity with transmission impairments[J].IEEE Transaction on Wireless Communication,2012,11(7):2574-2584.
[22]KARAMI E,DOBRE OA.Identification of SM-OFDM and AL-OFDM signals based on their second-order cyclostationarity[J].IEEE Transactions on Vehicular Technology,2015,64(3):942-953.
[23]MAREY M,DOBRE OA,INKOL.Cyclostationaritybased blind classification of STBCs for cognitive radio systems[C]//IEEE International Conference on Communications.Ottawa ON:IEEE,2012:1715-1720.
Characteristic Analysis of Blind Classification for STBC Based on Second-Order Cyclostationarity Statistics
YAN Wenjun1a,ZHANG Limin1b,LING Qing1a,KONG Dongming2
(Naval Aeronautical and Astronautical University a.Department of Electronic and Information Engineering; b.Institute of Information Fusion,Shandong Yantai 264001,China; 3.Naval Equipment Department,Taiyuan 030027,China)
In the light of the problem of blind classification for space-time block coding(STBC),the second-order cyclosta?tionarity statistics were analyzed.Using the correlation of the elements in STBC matrix,the Fourier coefficients were de?fined,and the characters that signals of STBC have cycle frequencies was proved.Simulation showed the validity of the der?ivation,and the decision tree was made for classification.And finally,the proposed algorithms were summarized and the fu?ture development of classification of STBC was pointed out.
signal processing;space-time block bode;second-order cyclostationarity
TN911.7
A
1673-1522(2015)05-0409-05
10.7682/j.issn.1673-1522.2015.05.002
2015-06-07;
2015-08-11
國(guó)家自然科學(xué)基金資助項(xiàng)目(61102167)
閆文君(1986-),男,博士生。