CN100466800C - 一种应用于ofdma蜂窝系统的小区识别的方法 - Google Patents
一种应用于ofdma蜂窝系统的小区识别的方法 Download PDFInfo
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- CN100466800C CN100466800C CNB2006100259863A CN200610025986A CN100466800C CN 100466800 C CN100466800 C CN 100466800C CN B2006100259863 A CNB2006100259863 A CN B2006100259863A CN 200610025986 A CN200610025986 A CN 200610025986A CN 100466800 C CN100466800 C CN 100466800C
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Abstract
本发明涉及一种应用于OFDMA蜂窝系统的小区识别的方法,属于通信技术领域。本发明在每帧中在每帧中仅需要1个OFDM符号作为同步信道数据,具有同步信道数据开销低的优势,并且该符号的峰均功率比很低,另外,运用级联的小区识别过程,通过不同的子载波加载数据的模式图样,区别不同的小区号码组;再通过相邻的已加载数据子载波上的频域差分序列,区别不同的小区号码,达到识别大规模数量蜂窝小区的目的,为了提高本发明的估计性能,采用多符号判决的方法。本发明具有识别小区数量大,计算复杂度较低,且估计错误率较低的优点,在OFDM系统中具有很高的应用价值。
Description
技术领域
本发明涉及一种通信技术领域的识别的方法,具体是一种应用于OFDMA(正交频分复用多址)蜂窝系统的小区识别的方法。
背景技术
OFDM(正交频分复用)技术在越来越多的有线、无线通信领域得到应用,这主要由于OFDM技术具有许多优势:有效对抗多径干扰和窄带干扰,频谱利用率高,数据传输速率高等。目前,OFDM技术已被3GPP组织(第三代移动通信伙伴计划)国际组织确定为EUTRA(演进的通用移动通信系统及陆基无线电接入)和EUTRAN(演进的通用移动通信系统网及陆基无线电接入网)(或者称为Super 3G:超三代移动通信系统)中下行链路的首选技术。在基于OFDMA技术的蜂窝系统中,用户终端在加电时,在待机或通话时,和W-CDMA技术的蜂窝系统一样,必须进行搜索其所属的小区搜索。OFDMA技术的蜂窝系统的小区搜索方案中,除了由于数据调制方式与W-CDMA不同,需要FFT(Fast Fourier Transform,快速傅里叶变换)窗同步用来恢复被调制的数据外,其他方面与W-CDMA三步小区搜索方案类似,所以其包含以下三个步骤:载波频率同步和FFT时间窗同步,帧同步,小区识别。经对现有技术的文件查新,发现绝大部分技术只解决了帧同步及载波频率同步,而没有涉及OFDMA蜂窝系统的小区识别问题。
在仅有的一些文献中,针对EUTRA要求的OFDMA蜂窝系统,有三种方法可用于OFDMA小区识别:
(1)在每一帧中确定1个OFDM符号作为同步信道符号,在频域加载特殊的序列,通过直接识别这一频域序列,达到小区识别的目的。参见文献:3GPP,R1-051329,“Cell Search and Initial Acquisition for OFDM Downlink”,Motorola。(3GPP文档,编号:R1-051329,Motorola公司,“OFDM下行链路的小区搜索和初始同步”)
(2)在每一帧中确定n个(n一般为大于等于4的自然数)OFDM符号作为同步信道符号,在频域上加载特殊的序列。每一种频域序列对应一个码字,n个码字的特定组合对应一个小区号码组(或称为小区扰码号组),共有xG个小区号码组,然后通过类似于WCDMA中的CPICH(公共导频信道)获得小区号码(或称为小区扰码号),共有xI个小区号码。于是,该方法共可以识别xGxI个不同的小区。参见文献:3GPP,R1-060072,ETRI,“Cell Search Scheme for EUTRA & TP”。(3GPP文档,编号:R1-060072,ETRI公司,“应用于EUTRA的小区搜索方案与文字建议”)
(3)在每一帧中确定n个(n一般为大于等于5的自然数)OFDM符号作为同步信道符号,在频域上加载经过信道编码的数据序列,通过解调和解码该数据,达到小区识别的目的。参见文献:3GPP,R1-051057,“DownlinkSynchronization Channel Schemes for E-UTRA”,Texas Instruments。(3GPP文档,编号:R1-051057,TI公司,“EUTRA的下行同步信道”)
可是,方法(1)有同步信道结构简单的特点,但存在着小区识别数量少的缺点。方法(2)和方法(3)存在着计算复杂度高,同步信道符号开销大的缺点。因此,上述三种方法在实际应用中遇到较大困难。
发明内容
本发明的目的在于针对现有技术中计算复杂度高,同步信道符号开销大或小区识别数量少的问题,提供一种应用于OFDMA蜂窝系统的小区识别的方法。本发明在每帧中仅需要1个OFDM符号作为同步信道数据,通过在不同模式图样的子载波上加载数据,区别不同的小区大号码,再通过相邻的已加载数据的子载波上的频域差分序列,区别不同的小区小号码,最终由小区大号码和小区小号码联合识别小区,达到识别大规模数量蜂窝小区的目的,同时使本发明保持较低的计算复杂度。
本发明通过以下技术方案实现,具体包括如下步骤:
步骤一:发送端生成含有小区大号码和小区小号码信息的OFDM同步信道符号,在频域上,该同步信道符号中参与小区识别过程的子载波按是否加载数据,分为两类:必有载荷子载波和可有载荷子载波,其中,必有载荷子载波和可有载荷子载波中确实加载数据的子载波合称为启用子载波,不同小区大号码的小区具有不同的可有载荷子载波模式图样,具有不同小区小号码的小区在相邻的启用子载波上加载不同的频域差分序列;
步骤二:接收端根据利用现有技术,获得帧同步与载波频率同步,并提取出同步信道符号,去除循环前缀,经过频偏补偿,再作FFT(快速傅里叶变换),得到同步信道符号的频域序列;
步骤三:识别接收的可有载荷子载波的能量序列模式图样,获得小区大号码,即计算步骤二所得频域同步信道符号的可有载荷子载波的能量序列,作为收到的可有载荷子载波模式图样,将其与事先定义的可有载荷子载波的模式图样集合进行匹配搜索,找到具有最大相关性的图样,进而识别出该图样代表的小区大号码;
步骤四:识别已加载数据的子载波上加载的频域差分序列,获得小区小号码,即先由步骤三确定的可有载荷子载波图样,以及已知的必有载荷子载波集合,得到启用子载波中相邻子载波的序号集合,然后,差分解调该序号集合所对应的频域同步信道序列,获得用于识别小区小号码的频域差分序列,再通过识别该序列,达到识别小区小号码的目的。最终由小区大号码和小区小号码联合识别小区。
完成步骤四后还可以进入多符号判决算法,即考察多个同步信道符号,运用不同的判决合并方法及不同的判决策略,进行小区识别,从而得到比单次判决更可靠的小区大号码和小区小号码判决值。
以下对本发明作进一步说明:
(1)生成含有小区大号码和小区小号码信息的OFDM同步信道符号
OFDM是一种多载波调制系统,每个子载波上都可以承载QAM符号或PSK符号,其调制解调过程可以用IDFT(离散傅里叶反变换)和DFT(离散傅里叶变换)来表示。设N表示OFDM子载波的数目,由于IDFT和DFT的对称性,N也表示OFDM符号的有效部分点数,T表示OFDM符号的有效宽度,子载波间隔为fo=1/T。设a(k)表示发送端在同步信道符号的第k个子载波上加载的频域数据;b(l)表示同步信道符号中,第l个采样点的基带时域数据。对a(k)作b(l)点IDFT,得:
式中,Nu1表示基带负频谱区域的可用子载波的数目,Nu2表示基带正频谱区域的可用子载波的数目,Nu1+Nu2=Nu表示可用子载波的总数目,Ng是循环前缀的点数。
考虑将小区大号码的信息反映到不同的子载波加载数据的模式图样上,依据子载波加载数据,定义子载波序号集合如下:
可用子载波S,含有(C(S)=Nu)个元素:
S={S(i)|1≤i≤C(S),S(i)<S(i+1),-Nu1≤S(i)≤Nu2,S(i)≠0} (2)
参与小区识别过程的子载波Scell,一般由相关协议标准唯一确定,其含有C(Scell)个元素:
Scell={Sc(i)|1≤i≤C(Scell),Sc(i)<Sc(i+1),Sc(i)∈S} (3)
Scell与S的关系是:
必有载荷子载波Sload,含有C(Sload)个元素:
Sload={Sl(i)|1≤i≤C(Sload),Sl(i)<Sl(i+1),Sl(i)∈Scell} (4)
式(4)中,Sload属于系统设计参数,其对于发送端和接收端是透明的,即双方在通信前均准确地知道Sload。
可有载荷子载波Soption,含有C(Soption)=C(Scell)-C(Sload)个元素:
Soption={So(i)|1≤i≤C(Soption),So(i)<So(i+1),So(i)∈Scell\Sload} (5)
Soption在不同号码g的小区中,被不同的二进制序列dg={dg(j)|1≤j≤B}(B为dg的长度,且B=C(Soption))所作用,形成不同的数据加载模式图样,即dg中0元素所对应位置的Soption上不加载数据,1元素所对应位置的Soption上才加载数据,用集合形式将上述两种情况表示为和
选取dg为具有尖锐峰值自相关的伪随机序列(如m序列等等),把dg的循环移位样本dg(1≤g≤B)作为不同的可有载荷子载波的数据加载模式图样,不同小区大号码g的小区采用不同的dg。
接收端通过对收到的可有载荷子载波的能量序列与不同dg进行相关搜索,寻找相关峰值,从而确定当前小区大号码g。可见,通过可有载荷子载波的数据加载模式图样,最多可以区别B个小区大号码。
另外,dg也可以由多个部分级联而成,即将dg分解为 ……, 满足 B1+B2+...+Bn=B。分为具有尖锐峰值自相关的伪随机序列(如m序列等等)。这样,的不同组合总共构成B1×B2×...×Bn个不同的dg。
在实际系统中,可识别的小区大号码数目Cg也是一个可调整的参数,比如,选取长度为B=31的m序列,表示系统最多可以识别31个小区大号码,如果目前只需要区分8个小区大号码,则从31个dg中选取8个dg作为合法的可有载荷子载波的数据加载模式图样即可,此时,Cg=8。
在相同小区大号码的小区内,使用不同的频域差分数据序列来区别不同的小区小号码。定义小区大号码为g(1≤g≤Cg)的小区中,其必有载荷子载波Sload与可有载荷子载波中确实加载数据的子载波,合称为启用子载波
式(9)中,α为相邻子载波的最大定义距离,通常,为了保证相邻子载波受到近似相同的信道影响,一般取α≤4,即当两个子载波之间的距离超过4个子载波间隔时,便认为二者不相邻。的元素个数为,这是用以区分小区小号码的频域差分数据序列的长度。需要指出的是,在不同g的条件下,可能不一样,为了保证各个小区小号码的信息加载在相同长度的频域差分序列上,将按照最小长度进行截短,于是,所有的长度被确定为D:
进而修正式(9),得:
假设共有Cq个频域差分序列pq={pq(i)}(1≤q≤Cq,1≤i≤D)(例如PN序列或是GCL(Generalized chirp-like,广义似脉冲)差分序列等等)用来区别Cq个小区小号码。小区大号码为g,小区小号码为q的小区选取pq加载到和对应的相邻子载波上:
式(12)中,θ是任意的随机相位,表示部分启用子载波上的数据不受g和q的约束,可以用于改善同步信道符号的PAPR(峰均功率比)。
接收端通过差分解调和对应位置上的数据,然后再与所有可能的pq作互相关,寻找峰值,识别出pq,从而确定小区小号码q。可见,为了识别尽可能多的q,pq的长度D应尽可能大,考虑到 因此,在C(Scell)一定的条件下,选取适当的参数C(Sload)和C(Soption),并使尽可能大,就可以使D变大。
(2)帧同步与频率同步
目前,OFDM的帧同步与频率同步是一项较为成熟的技术。比如,选取
Scell={Sc(i)|1≤i≤C(Scell),Sc(i)<Sc(i+1),Sc(i)∈S,Sc(i)=0(modL)} (13)
然后在S\Scell的子载波上不加载数据,就可以生成L等分结构的OFDM同步信道符号,在时域上计算同步信道符号的特定延迟自相关,寻找峰值来确定帧的起始位置,再求峰值的相角估计出频率偏差。参见文献:T.Keller,L.Piazzo,P.Mandarini,L.Hanzo,″Orthogonal Frequency Division MultiplexSynchronization Techniques for Frequency-Selective Fading Channels,″IEEE Journal on Selected Areas in Communications,VOL.19,NO.6,June2001 page(s):999-1007。(“频率选择性衰落信道下的OFDM同步技术”IEEE精选通信技术领域期刊)
又比如,在S\Scell中的一部分子载波上加载固定的频域序列,从而生成固定的时域序列,该时域序列对于发送端和接收端都是事先已知的,接收端用这一时域序列对接收到的信号进行连续的相关搜索,相关峰所在位置就是OFDM符号的起始位置,然后考察接收序列的相位特征,估算出频率偏差、参见文献:3GPP,R1-060781,NTT DoCoMo,“Cell Search Time Performance of Three-Step CellSearch Method”。(3GPP文档,编号:R1-060781,NTT DoCoMo公司,“三步骤小区搜索方法在搜索时间方面的性能表现”)
设r(m)表示接收端收到前导符号的第m个采样点的基带时域数据,h(l)表示延时为l个采样时刻路径所对应的时域信道响应;n(m)表示信道对r(m)的时域加性高斯噪声;Ψ是初相,fΔ是对子载波间隔归一化后的频偏,ε是对采样点间隔归一化后的帧同步偏差,则r(m)的表达式为:
根据帧同步与频率同步的结果,对r(m)进行相应补偿,并去除循环前缀,得:
对r(m)作N点DFT,得到同步信道符号的频域序列:
将式(1)代入式(15),再代入式(16),得到其等效的频域表达式为:
z(k)=a(k)H(k)+n′(k)(-Nu1≤k≤Nu2) (17)
式中,H(k)是多径衰落信道对第k个子载波的频域影响,n′(k)是信道对第k个子载波的频域加性噪声。
(3)识别接收的可有载荷子载波的能量序列模式图样,获得小区大号码g
对于{z(k)},计算Soption对应的子载波的能量序列,将其与dg作相关,如式(18)所示:
这一步骤的计算主要集中在式(18),计算|z(So(i))|2需要C(Soption)次复数乘法。由于dg是二进制序列,因此,式(18)中的乘积和退化为实数加法,总共只需要次实数加法,等效为次复数加法。
(4)识别已加载数据的子载波上加载的频域差分序列,获得小区小号码q
根据前级得到的g,由式(6)和式(7)得到和,再由式(8)获得然后根据式(9)考察所有的,并由式(10)得到频域差分序列的长度D,于是,根据式(11),确定相邻子载波对的集合。当不考虑噪声,仅考虑多径衰落信道时,差分解调和对应的相邻子载波上的数据,由式(12)和式(17)得:
考虑式(9)的条件,当α较小时,可以认为 于是,式(20)简化为:
计算向量w={w(i)}与pq的相关:
这一步骤的计算主要集中在式(21),式(22)和式(23)。式(21)需要D次复数乘法,式(22)需要D×Cq次复数乘法和(D-1)×Cq次复数加法,式(23)中计算|T(q)|需要Cq次复数乘法。
(5)多符号判决算法
由式(19)和式(23)可知,本发明总共可识别CgCq个不同的小区,为了更可靠地完成小区识别任务,可以采用多符号判决算法,即考察多个同步信道符号,运用不同的判决策略,进行小区识别,从而得到比单次判决更可靠的小区大号码和小区小号码判决值。
不考虑OFDM的时间同步和频率同步,仅仅考虑小区识别问题。
其中,表示中等于g的元素个数。当存在两个以上的值时,需要追加考察1个同步信道符号,直至出现唯一的。设总共用去U′个同步信道符号,得到唯一的。根据,对每个同步信道符号,计算式(21)和式(22),得Tx(q)(1≤x≤U),平方合并Tx(q)之后,再用式(25)得到小区小号码的估计值
方法一总共需要的复乘次数为U′×(C(Soption)+D+D×Cq+Cq),复加次数为
方法二:考察U个同步信道符号,对于每个同步信道符号,按照式(18)计算得Rx(g)(1≤x≤U),然后加法合并Rx(g):
式(26)等效需要(U-1)Cg/2次复加。然后,按照式(19)得到。根据对每个同步信道符号,计算式(21)和式(22),得Tx(q)(1≤x≤U),平方合并Tx(q)之后,再用式(25)得到小区小号码的估计值
方法二总共需要的复乘次数为U×(C(Soption)+D+D×Cq+Cq),复加次数为
在采用了多次判决算法后,本发明的估计性能得到显著提高。
本发明的优点在于:在每帧中仅需要1个OFDM符号作为同步信道数据,具有同步信道数据开销低的优势,并且该符号的峰均功率比很低,另外,采用级联的小区识别方法,先通过在不同模式图样的子载波上加载数据,区别不同的小区大号码,再由相邻的已加载数据子载波上加载不同的频域差分序列,区别不同的小区小号码,最终由小区大号码和小区小号码联合识别小区,达到识别大规模数量蜂窝小区的目的,同时使本发明保持较低的计算复杂度。
附图说明
图1为OFDM基带调制解调框图
图2为本发明的实施框图
图3为dg的循环自相关函数图
图4为小区大号码为g=19的小区的同步信道符号的启用子载波的模式图样及频域差分序列的加载位置
图5为R(g)的典型情况图
图6为T(q)的典型情况图
图7为接收端与3个邻近小区的位置关系
图8为在多小区情况下,本发明与Motorola的方案使用第一种多符号判决法的小区识别正确率性能图
图9为在多小区情况下,本发明与Motorola的方案使用第二种多符号判决法的小区识别正确率性能图
具体实施方式
下面给出一个具体的OFDM参数配置,来阐述本发明的实现步骤。需要说明的是,下例中的参数并不影响本发明的一般性。
3GPP组织的文档:TR25.814 V0.3.1,“Physical Layer Aspects forEvolved UTRA”(演进的通用移动通信系统及陆基无线电接入的物理层规范)
给出的一组OFDM参数,如下:
系统带宽 1.92MHz
子载波数N 128
有效子载波数Nu 75(取Nu1=38,Nu2=37)
有效带宽 1.25MHz
子载波间隔fo 15kHz
循环前缀Ng 32点(16.67us)
符号周期T 128点(66.67us)
本发明的参数选取如下:
α=4
S={-38,-37,...,-1,1,...,36,37},C(S)=75。
Scell={Sc(i)|1≤i≤C(Scell),Sc(i)<Sc(i+1),Sc(i)∈S,Sc(i)=0(mod2)},即:
Scell={-38,-36,...,-2,2,...,34,36} (27)
则C(Scell)=37。在S\Scell的子载波上不加载数据,从而生成2等分的同步信道符号。另外,在式(4)中,选取
Sload={-38,-36,-34,32,34,36} (28)
于是,式(5)中,
Soption={-32,-30,...,-2,2,...,28,30} (29)
则有C(Sload)=6和C(Soption)=31。
需要指出的是,本实例中对于Sload和Soption的选取并不影响本发明的通用性。在实际应用中,Sload和Soption的选取只要满足Sload∪Soption=Scell,且Soption不为空集即可。
本发明的实现步骤如下:
(1)生成同步信道符号
由于C(Soption)=31=25-1,而m序列的长度为2i-1(t为正整数),故可以选取dg为t=5的m序列,选择其本原多项式为1+x2+x5,则dg的循环移位样本共有31个,如下:
g | d<sup>g</sup> |
1 | 0000101011101100011111001101001 |
2 | 0001010111011000111110011010010 |
3 | 0010101110110001111100110100100 |
4 | 0101011101100011111001101001000 |
5 | 1010111011000111110011010010000 |
6 | 0101110110001111100110100100001 |
7 | 1011101100011111001101001000010 |
8 | 0111011000111110011010010000101 |
9 | 1110110001111100110100100001010 |
10 | 1101100011111001101001000010101 |
11 | 1011000111110011010010000101011 |
12 | 0110001111100110100100001010111 |
13 | 1100011111001101001000010101110 |
14 | 1000111110011010010000101011101 |
15 | 0001111100110100100001010111011 |
16 | 0011111001101001000010101110110 |
17 | 0111110011010010000101011101100 |
18 | 1111100110100100001010111011000 |
19 | 1111001101001000010101110110001 |
20 | 1110011010010000101011101100011 |
21 | 1100110100100001010111011000111 |
22 | 1001101001000010101110110001111 |
23 | 0011010010000101011101100011111 |
24 | 0110100100001010111011000111110 |
25 | 1101001000010101110110001111100 |
26 | 1010010000101011101100011111001 |
27 | 0100100001010111011000111110011 |
28 | 1001000010101110110001111100110 |
29 | 0010000101011101100011111001101 |
30 | 0100001010111011000111110011010 |
31 | 1000010101110110001111100110100 |
需要指出的是,本实例中选取m序列作为dg,并不影响本发明的通用性。在实际系统中,可以选取其他序列作为dg。
于是,本发明在上述物理层条件下,最多可识别B=31个小区大号码,任意dg的循环自相关函数如图3所示。取系统的可识别小区大号码数目为Cg=B=31。
选取pq为GCL差分序列,由于D=16,所以比D大的最小素数为17,于是:
根据GCL差分序列的性质,本发明可以由式(30)区别出Cq=16个小区小号码。于是,本发明总共可识别CgCq=31×16=496个不同小区。
假设某小区g=19,q=6,根据上述表格得:
d19={1111001101001000010101110110001}
根据式(12),得到g=19,q=6的小区在同步信道符号上应该加载的频域数据如下:
在某一次实验中,依据上述表格,a(k)(-38≤k≤37)的具体数值如下:
k | a(k) |
-38 | 0.97999-0.19902j |
-36 | -0.7494-0.66212j |
-34 | 0.84192-0.5396j |
-32 | 0.59014-0.8073j |
-30 | -0.92674+0.37571j |
-28 | -0.45961-0.88812j |
-26 | -0.93798-0.34669j |
-20 | 0.99919+0.040249j |
-18 | -0.97478-0.22316j |
-14 | -0.23473-0.97206j |
-8 | -0.92785+0.37296j |
4 | 0.24902-0.9685j |
8 | -0.75597-0.65461j |
12 | 0.86338+0.50455j |
14 | 0.29813+0.95453j |
16 | 0.97796-0.20879j |
20 | -0.72157+0.69234j |
22 | -0.92295+0.38493j |
30 | 0.40976-0.9122j |
32 | -0.98951-0.14448j |
34 | 0.71161-0.70258j |
36 | 0.71161-0.70258j |
其他 | 0 |
为了保证信号的发射功率保持恒定,在a(k)上将乘以补偿因子 ,将这样的a(k)通过图1的串并转换模块1、IDFT模块2、并串转换模块3,就能生成包含小区大号码信息和小区小号码信息的2等分OFDM同步信道符号,然后该同步信道符号经过图1的模块插入循环前缀模块4、插入同步信道符号模块5、D/A转换模块6、发送滤波处理模块7,到达接收端。
接收端按照图2进入小区识别过程。
(2)帧同步与频率同步
首先,接收端按照图2进行帧同步及频率同步。接收的数据经过图1的接收滤波处理模块8,A/D转换模块9、同步单元模块15。由于生成的同步信道符号具有2等分的特性,所以接收端在时域上计算同步信道符号的半个符号延迟自相关,寻找峰值来确定帧的起始位置,再求峰值的相角估计出频率偏差。根据帧同步与频率同步的结果,对同步信道符号进行相应补偿。接收数据经过图1的提取同步信道符号模块10、去除循环前缀模块11、串并转换模块12、DFT及频域均衡模块13、并串转换模块14,得到如式(17)所示的{z(k)}。然后,接收端按照图2开始进行小区识别。
(3)识别小区大号码
接收端按照图2开始进行小区大号码的识别。
依据式(18),得到R(g)。
以R(25)为例,由于d25={1101001000010101110110001111100},根据式(29)和式(18)得:
R(25)=|z(-32)|2+|z(-30)|2+|z(-26)|2+|z(-20)|2+|z(-10)|2+|z(-6)|2+|z(-2)|2+|z(2)|2
+|z(4)|2+|z(8)|2+|z(10)|2+|z(18)|2+|z(20)|2+|z(22)|2+|z(24)|2+|z(26)|2
当小区大号码g=19时,在多径信道条件以及0dB高斯白噪声情况下,R(g)的典型情况如图5所示。
在计算复杂度方面,这一步骤需要16次复数乘法和248次复数加法。
(4)识别小区小号码
接收端按照图2开始进行小区小号码的识别。
若小区大号码判断正确,得到g=19,进而由式(8)和式(11)获得和再根据式(21)和式(22)得T(q)。由于选取的pi为GCL序列,式(22)可以通过17点FFT高效地实现。先对w*(i)尾部补一个零,再对其作17点FFT:
当小区小号码为q=6时,在多径信道条件以及0dB高斯白噪声情况下,T(q)的典型情况如图6所示。
在计算复杂度方面,由于引入FFT辅助计算,这一步骤计算开销大大降低,只需要1个17点FFT运算和32次复数乘法。
(5)多次判决
方法一:考察U个同步信道符号,对于每个同步信道符号,按照式(18)和式(19)得到U个小区大号码估计值,然后按照式(24)对小区大号码作出估计,再用式(25)得到小区小号码的估计值 和的组合便是小区识别的结果。
方法二:考察U个同步信道符号,对于每个同步信道符号,按照式(18)计算得Rx(g)(1≤x≤U),再根据式(26)合并Rx(g),然后按照式(19)对小区大号码作出估计,再用式(25)得到小区小号码的估计值 和的组合便是小区识别的结果。
仿真信道为6-ray GSM Typical Urban Channel(全球移动通信典型城市区域6径信道,简称6-ray TU),其参数如下:
延迟(us) | 相对功率(dB) | |
路径1 | 0 | -3 |
路径2 | 0.2 | 0 |
路径3 | 0.5 | -2 |
路径4 | 1.6 | -6 |
路径5 | 2.3 | -8 |
路径6 | 5.0 | -10 |
假定频偏为-0.6。
在模拟多小区环境时,考虑最恶劣的情况,即接收端位于与3个邻近小区等距的位置上,如图7所示,并认为同步信道信号从3个小区发出后,经过不同的6-ray TU后,同时到达接收端,其中,3个小区的g和q均不相同。3个小区中某个小区(小区大号码为G,小区小号码为Q)的接收功率最强,这是目标接入小区,另外两个小区的接收功率相同,视其为干扰小区的信号。定义目标接入小区的信号接收功率与两个干扰小区的信号接收功率和的比值为SIR(信干比),在此基础上再叠加高斯白噪声,高斯白噪声的功率相对于标接入小区的信号接收功率为0dB。经过本发明的识别过程后,当 且 时,才认为小区识别正确。
仿真时认为已经获得完全正确的帧同步与频率同步。
在仿真中,考察了本发明与Motorola的方案的性能比较。Motorola的方案参见文献:3GPP,R1-051329,“Cell Search and Initial Acquisition for OFDMDownlink”,Motorola。(3GPP文档,编号:R1-051329,Motorola公司,“OFDM下行链路的小区搜索和初始同步”)该方案在上述物理层条件下,只能识别36个不同的小区,其数量仅仅是本发明的7.25%(36/496)。另外,Motorola的方案也可采用方法一(多次估计后,用多数决作判断)和方法二(判决变量合并后再作估计)进行实施。在计算复杂度方面,Motorola的方案每通过一个同步信道符号识别小区,需要36次复乘用于差分解调,再用1个37点FFT运算识别频域序列,最后需要36次复乘用于求模运算,因此,其总共需要1个37点FFT运算和72次复乘,而本发明每通过一个同步信道符号识别小区,总共需要1个17点FFT运算,48次复数乘法和248次复数加法。两者的计算复杂度相当,均属于低复杂度的小区识别方法。
图8是在多小区情况下,本发明与Motorola的方案使用第一种多符号判决法的小区识别正确率性能图。该图考察了U=5,7,9,11时的情况,仿真曲线表明,本发明虽然在小区识别数量上远远优于Motorola的方案,但其在SIR较小时(SIR<0dB),比Motorola的方案多需要0.6dB左右的信干比,才能达到相同的估计性能。考虑到本发明在小区识别数量上的巨大改进,其在信干比方面付出的少量代价是值得的。
图9在多小区情况下,本发明与Motorola的方案使用第二种多符号判决法的小区识别正确率性能图。该图考察了U=5,7,9,11时的情况,仿真曲线表明,本发明虽然在小区识别数量上远远优于Motorola的方案,但其在SIR较小时(SIR<0dB),比Motorola的方案多需要0.5dB左右的信干比,才能达到相同的估计性能。考虑到本发明在小区识别数量上的巨大改进,其在信干比方面付出的少量代价是值得的。
仿真结果表明,本发明具有识别小区数量大,计算复杂度较低,且估计错误率较低的优点,在OFDM系统中具有很高的应用价值。
本发明的上述具体实施方式只是用于阐述本发明的技术内容的示例。本发明并不限于上述具体实施方式,不应对其进行狭义的解释。在本发明的精神和权力要求的范围内,可进行各种变更来实施之。
Claims (3)
1、一种应用于OFDMA蜂窝系统的小区识别的方法,其特征在于,包括如下步骤:
步骤一:发送端在每一帧中生成一个含有小区大号码和小区小号码信息的OFDM同步信道符号,与每个小区大号码对应的是可有载荷子载波上加载数据的模式图样,所述可有载荷子载波上加载数据的模式图样,为具有尖锐峰值自相关的伪随机序列,并把该序列的循环移位样本作为不同的可有载荷子载波上加载数据的模式图样,与每个小区小号码对应的是在相邻的启用子载波上加载频域差分序列;
步骤二:接收端获得帧同步与载波频率同步,并提取出OFDM同步信道符号,去除循环前缀,经过频偏补偿,再作FFT,得到OFDM同步信道符号的频域序列;
步骤三:识别接收的可有载荷子载波的能量序列模式图样,获得小区大号码估计值;具体通过计算OFDM同步信道符号的频域序列的可有载荷子载波的能量序列,作为收到的可有载荷子载波的能量序列,将其与事先定义的可有载荷子载波上加载数据的模式图样的集合进行匹配搜索,得到集合中每个图样的相关性度量值,作为小区大号码判决变量,小区大号码判决变量的峰值对应的图样作为具有最大相关性的图样,进而识别出该图样代表的小区大号码,作为小区大号码估计值;
步骤四:识别启用子载波上加载的频域差分序列,获得小区小号码估计值,具体通过获得启用子载波中相邻子载波的序号集合,然后差分解调该序号集合所对应的OFDM同步信道符号的频域序列,获得用于识别小区小号码的频域差分序列,将其与事先定义的小区小号码的频域差分序列的集合进行匹配搜索,得到集合中每个频域差分序列的相关性度量值,作为小区小号码判决变量,小区小号码判决变量的峰值对应的频域差分序列作为具有最大相关性的频域差分序列,进而识别出该频域差分序列代表的小区小号码,作为小区小号码估计值。
2、根据权利要求1所述的应用于OFDMA蜂窝系统的小区识别的方法,其特征是,在所述的步骤四后,进入多符号判决算法,即考察多个OFDM同步信道符号,对于多个OFDM同步信道符号,按照步骤三得到多个小区大号码估计值,然后对其进行多数决判断,在得到唯一的小区大号码估计值后,对步骤四中的小区小号码判决变量进行平方合并后,再对小区小号码作出估计。
3、根据权利要求1所述的应用于OFDMA蜂窝系统的小区识别的方法,其特征是,在所述的步骤四后,进入多符号判决算法,即考察多个OFDM同步信道符号,先将多个OFDM同步信道符号中的多个小区大号码判决变量进行加法合并,然后再对小区大号码作出估计,然后,对步骤四中的小区小号码判决变量进行平方合并后,再对小区小号码作出估计。
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