CN102858019B - Down link space-time scheduling method of cognitive cellular network - Google Patents

Down link space-time scheduling method of cognitive cellular network Download PDF

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CN102858019B
CN102858019B CN 201210381011 CN201210381011A CN102858019B CN 102858019 B CN102858019 B CN 102858019B CN 201210381011 CN201210381011 CN 201210381011 CN 201210381011 A CN201210381011 A CN 201210381011A CN 102858019 B CN102858019 B CN 102858019B
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cognitive
step
base station
pheromone
set
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CN102858019A (en )
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魏飞
夏鹏瑞
张燕
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江苏省邮电规划设计院有限责任公司
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Abstract

本发明公开了一种认知蜂窝网的下行链路空时调度方法,包括以下步骤:步骤(1),采集多天线认知基站与单天线认知移动终端之间的信道状态信息向量以及认知基站与单天线主用户之间的信道状态信息向量;步骤(2),初始化构建图中每条边上分布的信息素以及启发式信息;步骤(3),生成人工蚂蚁;步骤(4),认知基站计算对应认知移动终端的双重正交波束赋形向量;步骤(5),分配发送功率给认知基站发送至认知移动终端的数据流;步骤(6),判断是否达到预设的最大迭代次数,若达到则停止并输出最优接入集,最大迭代次数取自然数;步骤(7),更新构建图中所有边上分布的信息素并返回步骤(3);由此完成下行链路空时调度。 The present invention discloses a cognitive empty downlink scheduling method for a cellular network, comprising the following steps: Step (1), collecting multi-antenna base station and the single antenna Cognition Cognitive vectors and channel status information between the mobile terminals identified vector broadcast channel state information between the base station and the main single antenna user; step (2), each edge initialized in FIG construct distributed pheromone and heuristic information; step (3), generates an artificial ants; step (4) cognitive cognitive base station calculates the mobile terminal corresponding to the double orthogonal beamforming vector; step (5), allocated to the transmission power of the transmission data stream to the mobile terminal cognition cognitive base station; step (6), it is determined whether the pre- set the maximum number of iterations, and if the output is stopped reaches the optimal set of access, the maximum number of iterations is a natural number; step (7), a construction diagram of the update distribution along all sides of the pheromone and returns to the step (3); thus completion empty downlink scheduling time.

Description

一种认知蜂窝网的下行链路空时调度方法 A cognitive empty downlink scheduling method for a cellular network

技术领域 FIELD

[0001] 本发明涉及一种认知无线电技术中无线通信与通信信号处理技术领域,特别是一种基于认知无线电的认知蜂窝网的下行链路空时调度方法。 [0001] The present invention relates to a cognitive radio technology in wireless communication with a communications signal processing technology, and particularly to a downlink null cognitive cognitive radio cellular network based scheduling.

背景技术 Background technique

[0002] 随着无线业务与应用的不断增长,可供分配的无线频谱资源越来越紧张。 [0002] With the continuous growth of wireless services and applications available for the allocation of radio spectrum resources are increasingly strained. 目前, 可分配频谱的匮乏已极大的阻碍了无线通信的可持续发展。 At present, the lack of available spectrum allocation has been greatly hindered the sustainable development of wireless communications. 在另一方面,实际测量结果表明大部分的已分配的频谱却处于低利用率状态。 On the other hand, the actual measurement results show that most of the spectrum has been allocated in the low utilization state. 在这种背景下,认知无线电(Cognitive Radio, CR)技术应运而生,CR网络通过与持有授权频谱的主用户(Primary User, PU)网络共存,在时间和空间上共享PU授权频谱,从而可以提高现有授权频谱的利用率,为新的无线业务与应用提供带宽。 In this context, a cognitive radio (Cognitive Radio, CR) technology emerges, CR networks coexist network by primary users of the licensed spectrum (Primary User, PU), PU licensed spectrum sharing in time and space, thereby improving the utilization of existing licensed spectrum to provide a bandwidth of new wireless services and applications.

[0003] 基于CR的蜂窝网络(认知蜂窝网络)通过利用PU的授权频谱,有望解决当前商业移动通信所面临的频谱匮乏问题。 [0003] CR-based cellular network (cellular network awareness) by using the PU licensed spectrum, the spectrum is expected to solve this problem of lack of commercial mobile communication face. 在典型的认知蜂窝网络的下行链路中,多天线的认知基站(Cognitive Base Station, CBS)通过空间复用技术支持多路数据流传输至不同的单天线认知移动终端(Cognitive Mobile Station, CMS)。 Cognitive downlink typical cellular network, the multi-antenna base station cognitive (Cognitive Base Station, CBS) supports multiplexing multiple data streams transmitted by a single antenna to a different spatial perception of the mobile terminal (Cognitive Mobile Station , CMS).

[0004] 在频谱共享时,为不影响已有PU网络的操作,实现与之"透明"共存,认知蜂窝网络需要具备有效避免对PU干扰的能力。 [0004] When the shared spectrum, does not affect the operation of the existing network PU achieved with "transparent" coexist, cellular networks need to cognitive ability to effectively avoid interference PU. 因而,与传统蜂窝网不同的是,在认知蜂窝网中, CBS传输至认知移动终端CMS的数据信号应避免对PU带来任何有害的干扰。 Thus, with the conventional cellular networks are different, cognitive cellular network, CBS cognitive transmitted to the mobile terminal data signals CMS should avoid any harmful interference caused PU.

[0005] 为实现频谱资源的有效利用,最大化系统容量,需要在CMS之间进行调度。 [0005] In order to achieve efficient use of spectrum resources, and to maximize the system capacity needs to be scheduled between CMS. CBS通过对自身与PU以及自身与CMS之间的时变衰落信道的估计,并利用收集到的信道状态信息可以实现用户调度,在给定时间内调度具有最好信道状况的用户或用户子集实现数据传输,从而最大化系统容量,优化对频谱资源的利用。 CBS by estimating itself with the PU and between itself and CMS-varying fading channel, using the channel state information collected may implement user scheduling, scheduling user or subset of users with the best channel conditions at a given time data transmission, to maximize system capacity, optimize the use of spectrum resources.

发明内容 SUMMARY

[0006] 发明目的:本发明所要解决的技术问题是针对现有技术的不足,提供一种认知蜂窝网的下行链路空时调度方法。 [0006] Object of the invention: The present invention solves the technical problem of the deficiency of the prior art, provides downlink scheduling method when a cognitive air cellular network.

[0007] 为了解决上述技术问题,本发明公开了一种认知蜂窝网的下行链路空时调度方法,包括以下步骤: [0007] To solve the above problems, the present invention discloses a cognitive empty downlink scheduling method for a cellular network, comprising the steps of:

[0008] 步骤(1),采集多天线认知基站与N个单天线认知移动终端之间的信道状态信息向量比,i = 1,2,...,N以及认知基站与M个单天线主用户之间的信道状态信息向量gj,j -1,2,• • •,M ; [0008] Step (1), collecting channel state information between a base station and a plurality of N antenna Cognition Cognitive mobile terminal to a single-antenna ratio, i = 1,2, ..., N and M of the base station and cognitive vector channel state information between the primary single-antenna user gj, j -1,2, • • •, M;

[0009] 步骤(2),初始化构建图中每条边es,s+1 (j)上分布的信息素ts,s+1 (j)= (Tmax"min)/2,以及启发式信息ns,s+1(j) = |h」2, s = 0, l,...,nT-M,j = 1,2,...,N,其中Tma!^ T mij别为信息素含量的上界与下界,T ">«的设定值范围为10〜20, T *的设定值范围为0〜10, |hj|表示求信道状态信息向量hj的幅值,nT为认知基站的天线数目; [0009] Step (2), each edge initialized in FIG construct es, s + 1 ts distributed over pheromone (j), s + 1 (j) = (Tmax "min) / 2, and heuristic information ns , s + 1 (j) = | h '2, s = 0, l, ..., nT-M, j = 1,2, ..., N, wherein Tma ^ T mij respectively pheromone content! upper and lower bounds, T "> setpoint range« is 10~20, T * is set to a value in the range of 0~10, | hj | denotes the channel state information required amplitude vector hj, nT cognitive the number of antennas of the base station;

[0010] 步骤(3),生成m只人工蚂蚁,其中m的设定值范围为5〜30,放置蚂蚁于构建图中顶点V。 [0010] Step (3) generates only an artificial ants m, where m is the predetermined range 5~30, placing vertices in the graph constructed in ant V. 处,每只蚂蚁按概率Pr(es,s+1(j))选择边es,s+1(j)从顶点vs移动至顶点vs+1,s= 0, 1. ..,nT-M ;记录蚂蚁%,次移动经过的路径,选择路径中的边所对应的认知移动终端组成接入集乂; At each ant moves in probability Pr (es, s + 1 (j)) selected edge es, s + 1 (j) from apex to apex vs vs + 1, s = 0, 1. .., nT-M ; recording ants%, times the movement path passes, cognitive selected mobile terminal side corresponding to the path set consisting qe access;

[0011] 步骤(4),认知基站计算对应于第k个认知移动终端的双重正交波束赋形向量w_4_/:,keA; [0011] Step (4), corresponding to the base station calculates the cognitive dual orthogonal beamforming vector of the k-th mobile terminal cognitive w_4 _ / :, keA;

[0012] 步骤(5),分配发送功率给认知基站发送至认知移动终端的数据流;计算每只蚂蚁选择的接入集义的系统容量如下: [0012] Step (5), allocated to the transmission power of the data stream to the base station cognitive perception of the mobile terminal; ant was calculated for each set of the selected access system capacity defined as follows:

[0013] [0013]

Figure CN102858019BD00051

[0014] 其中,見u为给接入集乂中第k个CMS的数据流分配的发送功率,h#表示接入集乂第k个认知移动终端与认知基站之间的信道状态信息向量,h。 [0014] wherein u is to see the access to the stream distribution qe k-th set of transmit power CMS, h # denotes a channel between the access state of the k-th set qe Cognitive the mobile terminal and the base station information awareness vector, h. 表示对向量h#进行转置操作,< 为认知移动终端的接收机的噪声功率;选择最大系统容量对应的接入集为最优接入集义%步骤(6),判断是否达到预设的最大迭代次数,若达到则停止并输出最优接入集X%最大迭代次数取自然数; H # representation of the vector transpose operation, <cognitive noise power of the mobile terminal receiver; selecting the maximum system capacity corresponding to the optimal set of access% sense current access step (6), it is determined whether the preset the maximum number of iterations, and is stopped when the output reached the maximum number of iterations set optimal access X% is a natural number;

[0015] 步骤(7),更新构建图中所有边上分布的信息素并返回步骤(3);由此完成下行链路空时调度。 [0015] Step (7), a construction diagram of the update distribution along all sides of the pheromone and returns to the step (3); whereby upon completion of the downlink scheduling empty.

[0016] 本发明步骤(3)中蚂蚁选择边es,s+1(j)的概率Pr(es,s+1(j))按以下方法计算: [0016] The present invention, in step (3) selection of an edge ant es, s + probability 1 (j) of Pr (es, s + 1 (j)) is calculated as follows:

[0017] [0017]

Figure CN102858019BD00052

[0018] 其中C(5)表示连接顶点Vs与顶点Vs+1的所有边的集合,a与0为对应于信息素与启发式信息的加权系数,a与0的设定值范围为〇〜10。 [0018] where C (5) represents a linking vertices Vs + Vs and the set of all vertices of an edge, a is 0 and corresponding to the weighting factor pheromone and heuristic information, a is 0 and the predetermined range is 〇~ 10.

[0019] 本发明步骤(4)中依据以下方法计算第k个认知基站的双重正交波束赋形向量 [0019] The present invention step (4) to calculate the k th base station according to the following methods cognitive dual orthogonal beamforming vector

[0020] 对第k个认知基站,构建如下矩阵F_4,t: [0020] The k-th base station cognitive, matrix was constructed as follows F_4, t:

[0021] [0021]

Figure CN102858019BD00053

0ik 0ik

[0022] 计算矩阵p的0特征值所对应的特征向量n 归一化" 得到W#=17T° hA,k °Ak* 0_4,*, |°4乂| [0022] p is 0 matrix calculated feature value corresponding to a normalized feature vector n "obtained W # = 17T ° hA, k ° Ak * 0_4, *, | ° 4 qe |

[0023] 本发明步骤(5)中依据以下注水运算给接入集乂中的用户k分配发送功率[0024] CN 102858019 B 说明书3/8 页 [0023] The steps of the present invention (5) transmission power is allocated to the access qe set of user k based on the following injection operation [0024] CN 102858019 B specification 3/8

Figure CN102858019BD00061

[0025] 其中X为注水运算的水位,A >〇, A满足LA ' Ptot为基站总发送功率, 为能够给单个认知移动终端数据流分配的最大发送功率,符号定义为:b,tUx>b[0026] [x]>< 〇,如其中1___对应x,b 对应卩_,& = 0。 [0025] wherein X is a water injection operation, A> square, A satisfies LA 'Ptot is the total transmission power of the base station, so as to be the maximum transmit power to a single data stream cognitive assigned mobile terminals, the symbol is defined as: b, tUx> b [0026] [x]> <square, such as where 1___ corresponding to x, b corresponds Jie _, & = 0. 其他义[0027] 本发明步骤(7)中边es,s+1(j)上的信息素ts,s+1(j)按以下方法更新: Other sense [0027] The present invention step (7) in the edge es, s + ts pheromone on the (j) 1, s + 1 (j) updated by the following method:

Figure CN102858019BD00062

[0028] [0028]

[0029] [0029]

[0030] ist为迄今为止蚂蚁所发现的最大系统容量,为^;SV所对应的路径,P为信息素挥发系数,其设定值范围为〇〜1,Q为调节信息素增量大小的常量,其设定值范围为0• 01 〜0• 1〇 [0030] ist maximum system capacity ants found so far, is ^; SV corresponding path, P is the pheromone evaporation rate, the set value in the range of 〇~1, Q is adjusted pheromone increment size constant whose value is set in the range of 0 • 01 ~0 • 1〇

[0031] 有益效果:本发明中提出的双重正交传输空间复用技术通过给不同用户分配正交的空间复用向量使得对PU的干扰为零,能够满足下一代认知蜂窝网对ro干扰控制的要求。 [0031] Advantageous Effects: double orthogonal transmission spatial multiplexing proposed in the present invention, different users are assigned by spatial multiplexing orthogonal vectors is zero so that the interference with the PU to meet the next generation of cellular cognitive interference ro control requirements. 通过实验表明,相对于目前常用的次优方法,本发明中提出的基于ACO的低复杂度用户调度方法在增加一定的计算量的基础上能够获得接近最优方法的性能。 Experiments show that, with respect to the commonly used method of suboptimal, ACO-based low complexity user scheduling method of the present invention set forth in the constant increase in the amount of calculation can be obtained based on the method of near-optimal performance.

附图说明 BRIEF DESCRIPTION

[0032] 下面结合附图和具体实施方式对本发明做更进一步的具体说明,本发明的上述和/或其他方面的优点将会变得更加清楚。 [0032] The present invention will be further detailed description in conjunction with the accompanying drawings and specific embodiments, the above and / or other aspects of the advantages of the present invention will become more apparent.

[0033] 图1为本发明的系统场景示意图。 [0033] FIG. 1 is a schematic diagram of a system scenario of the present invention.

[0034] 图2为用户调度问题的相应构建图。 [0034] FIG. 2 is a construction diagram corresponding user scheduling problem.

[0035] 图3a〜图3c为不同PU数下的实时系统容量比较。 [0035] FIG 3a~ FIG. 3c is a real-time system capacity in comparison to the number of different PU.

[0036] 图4为不同PU数下的平均系统容量比较。 [0036] Figure 4 compares the average system capacity at different numbers PU.

[0037] 图5为本发明方法流程图。 [0037] FIG. 5 is a flowchart of a method invention.

具体实施方式 detailed description

[0038] 本发明考虑的下一代认知蜂窝网的下行链路场景,如图1所示,其中认知蜂窝网络由1个装备n T根天线的认知基站CBS与N个待接入的单天线CMS组成,同时还存在M个单天线主用户PU。 [0038] The present invention contemplates a downlink scenario generation cognitive cellular network shown in Figure 1, wherein the cognitive of a cellular network equipped with n T antennas of the base station cognitive CBS to be accessed with the N CMS composed of a single antenna, but also there are M antennas single primary user PU. 为便于表示,用#与別分别表示CBS与PU的索引集合。 To facilitate said other respectively by # and the CBS and the index set PU. CBS与第i个CMS之间的信道系数为hi,CBS与第j个PU之间的信道系数为%。 CBS channel coefficients between the i-th CMS hi, a channel coefficient between the j-th CBS% of PU. CBS通过空间复用技术支持多路数据流传输至不同的CMS。 CBS supports multiplexing multiple data streams transmitted by CMS to a different space. 对第i路数据流,发送至CMSi的信息符号^被加以发送功率Pi,随后经过波束赋形向量Wi处理。 Of the i-th data streams transmitted to the information symbol to be transmitted is CMSi ^ power of Pi, then passes through beamforming vector Wi process. 最后,在CBS的发送天线端,N路数据流经过叠加后被发送至不同的CMS。 Finally, at the transmission antenna end of the CBS, N data streams through the different superimposed then sent to CMS.

[0039] 本发明的基于蚁群优化(Ant Colony Optimization,ACO)的低复杂度空时调度方法,最大化认知蜂窝网系统信息速率。 [0039] The method of the present invention, low-complexity scheduling empty ACO (Ant Colony Optimization, ACO) based cellular system to maximize the recognition rate information. 本发明实质上包括了PU零干扰的双重正交传输空间复用方法与基于AC0的低复杂度用户选择方法两个部分内容。 The present invention essentially comprises a double zero interference PU orthogonal transmission spatial multiplexing method and selection method based on two parts of low complexity user AC0.

[0040] (1)双重正交传输空间复用 [0040] (1) double transmission spatial multiplexing orthogonal

[0041] 本发明中,CBS通过波束赋形技术来传输信号至CMS。 [0041] In the present invention, CBS signal is transmitted to the CMS via beamforming technology. 为便于CMS接收CBS信号, 波束赋形向量的选择需使得在不同的CMS链路上传输的CBS信号彼此正交;同时为了对PU 零干扰,还需使得CBS信号与PU信号正交,从而与PU共存。 To facilitate CMS CBS reception signal, selecting beamforming vectors such that required CBS signals transmitted on different links CMS orthogonal to each other; PU zero interference in order to simultaneously, so that the need CBS quadrature signal and a signal PU, and so PU coexist.

[0042] 令乂表示被选取的CMS的集合,则Z中的第k个CMS的波束赋形权值〜#的选择需满足 [0042] qe so that the CMS is represented by the selected set, the beamforming weights selection Z ~ # k-th in the CMS must meet

[0043] [0043]

Figure CN102858019BD00071

[0044] 其中•表示接入集^第i个CMS与CBS之间的信道状态信息向量,上标T表示转置,上标H表示共轭转置。 [0044] wherein ^ • represents the access channel state set information of the i-th vector between the CMS and the CBS, the superscript T denotes the transpose, the superscript H denotes a conjugate transpose.

[0045] 为实现尽可能多的CMS接入,本发明中认知蜂窝网采用支持最大用户数策略。 [0045] In order to achieve access to as many CMS, awareness of the present invention using the cellular network support the maximum number of user policies. 由于受式(1)中的条件约束,CBS最多可支持n TM个CMS同时接入。 Since the by formula (1) Constraint, CBS can support up to n TM simultaneous access to CMS.

[0046] 双重正交波束构造:第k个CMS的波束赋形权值可通过如下方法计算:CMSk构建矩阵如下: [0046] The configuration of the double orthogonal beams: a k-th CMS beamforming weights can be calculated by the following method: CMSk constructing a matrix as follows:

[0047] [0047]

Figure CN102858019BD00072

[0048] 通过特征分解计算的0特征值所对应的特征向量,再经过归一化Ru即可得第k个CMS的波束赋形权值为"心其中| |. | |表示求向量的模。显然^^唯一满足式(1)中的条件。 [0048] Decomposition characteristic calculated by the characteristic value 0 corresponding eigenvector, then after normalization Ru beamforming weight was obtained by the k-th value of CMS "heart wherein | |. | | Denotes the vector mode seek obviously ^^ uniquely satisfies the condition of formula (1).

[0049] 最优发送功率分配:由于CBS发送功率受限,CBS需要分配发送功率给乂中的不同的CMS以最大化系统信息速率,即求解: [0049] The optimal transmit power allocation: transmit power is limited due to the CBS, CBS transmission power needs to be allocated to a different CMS qe the system to maximize the information rate, i.e., solving:

[0050] [0050]

Figure CN102858019BD00081

[0051] 其中見u为给接入集义中第k个CMS的数据流分配的发送功率,er"2为接收端的噪声功率,Pmax为能够给单个CMS数据流分配的最大发送功率,P ^为CBS的总发送功率。由KKT(Karush Kuhn Tucker)条件,CBS可通过以下注水运算来分配发送功率: [0051] wherein See transmission power u of the data stream is allocated a sense k th CMS access set, er "2 is the receiver noise power, Pmax is able to give a single CMS maximum transmit power of the data stream allocation, P ^ . CBS is the total transmit power by KKT (Karush Kuhn Tucker) conditions, CBS transmission power may be assigned by injection operations:

[0052] [0052]

Figure CN102858019BD00082

6,如X之办 6, as do the X

[0053] 其中^ a,如x Q ,入>0为注水运算的水位,其值的选择需使得 [0053] wherein ^ a, such as x Q, the> 0 to water level operation, such that the need to select the value

Figure CN102858019BD00083

^,其他 ^ Other

[0054] (2)低复杂度用户选择方法 [0054] (2) low complexity user selection method

[0055] 由于双重正交传输空间复用最多可支持nT_M个CMS同时接入,而在实际的移动通信应用场景中CMS的用户数N常常大于n TM的,因而需要从N个CMS中选择最优的nT-M个用户。 [0055] Because of the double transmission spatial multiplexing orthogonal supports up nT_M simultaneous access to CMS, the CMS and mobile communication applications in an actual number of users N scenario often greater than n TM, and thus need to select the most CMS from the N excellent nT-M users. 令k 表示给定接入集乂时双重正交传输空间复用技术所取得的最大系统信息速率,即式(3)中优化问题的最优值。 Let k represents the maximum system dual orthogonal transmission spatial multiplexing rate when the acquired access information set qe, the optimal value of the optimization problem in the formula (3) given. 最优用户选择即如下的离散优化问题: Users select the optimal discrete optimization problem that is as follows:

[0056] [0056]

Figure CN102858019BD00084

[0057] 本发明中提出基于ACO的低复杂度用户调度算法来解决上面的问题。 [0057] The present invention is based on the ACO proposed low complexity user scheduling algorithm to solve the above problems. 在ACO中, 人工蚂蚁通过在构建图(Construction Graph)上移动来构造解。 In the ACO, the artificial ants moving constructed on the build FIG solution (Construction Graph) through. 在每次迭代中,每只蚂蚁通过构建图的边从一个顶点移动到另一个顶点,来不断构造部分解。 In each iteration, each ant from one vertex to another vertex by constructing FIG edge, configured to continuously partial solution. 当完全解被构造出后, 蚂蚁会在经过的边上留下一定量的信息素。 When the solution is completely constructed, the ants will leave a certain amount of pheromone through the edge. 信息素的量与解的质量有关,解的质量越好,则信息素的数量越大。 Quality and quantity of pheromone solution is related to the better, the greater the amount of pheromone solution quality. 下一次迭代中的蚂蚁通过信息素的指引来进一步搜索解空间的有前途的区域并更新信息素。 The next iteration of the search area ant to further promising solution space and update the pheromone by directing pheromone. 对于每次迭代中执行的解构建与信息素更新过程的进一步详细描述如下: Construction of the solution for each iteration performing the update process of the pheromone is described in further detail as follows:

[0058] •解构建 [0058] • solutions constructed

[0059] 式(5)中的问题的对应构建图如图2所示。 Corresponding to [0059] of formula (5) issues construct shown in Figure 2. 每条边es,s+1 (j)对应于一个可供选择接入的CMS,s表示当前顶点索引,s+1表示下一顶点索引。 Each edge es, s + 1 (j) corresponds to an alternative access CMS, s represents the current vertex index, s + 1 represents the next vertex index. 每个蚂蚁从顶点V(l出发,通过选择边到达下一顶点。对于本发明,在顶点%时,可供蚂蚁选择的边的数目为N,每移动一次,可供蚂蚁选择的边的数目减1,这样经过叫-M次移动后,蚂蚁选择了nT-M条边到达最终的顶点,这些边对应的CMS即为问题的解。在构建解的过程中,蚂蚁通过一种随机机制来选择CMS。在顶点\时,蚂蚁通过一种概率的方式选择一条边到达顶点v S+1,其选择边j的概率为: Ant the number of edges per vertex from V (l, by selecting the next vertex edges reach. For the present invention, at the apex% for ant selected for N, move every time, for a selected number of edges ants after minus 1, so called after the secondary mobile -M, ants selected nT-M reach a final vertex edges, edges corresponding to CMS of these solutions is the problem in the process of building the solution, by means of a random mechanism ants CMS selected vertex \ when the ants through a probabilistic mode selection reaches an edge vertex v S + 1, j is the probability of selection of an edge as follows:

[0060] [0060]

Figure CN102858019BD00091

[0061] 其中C(>y)表示连接顶点\与¥;3+1的所有边的集合,ts,s+1(j)表示边es,s+1(j)上的信息素含量,ns,s+1(j)表示边es, s+1(j)上的启发式信息值,a与0分别为对应于信息素与启发式信息的加权系数,其设定值范围皆为〇〜10。 [0061] where C (> y) represents a linking vertices \ and ¥; the set of all edges 3 + 1, ts, s + 1 (j) represent the edges es, s + pheromone content of the (j) 1, ns , s + 1 (j) represent the edges es, s + heuristic information value on the (j) 1, a 0, respectively, and corresponding to the weighting factor pheromone and heuristic information, which are all set value range 〇~ 10. a取值越大则算法在寻找解的过程中受信息素的影响越大,反之,0越大则受启发式信息的影响越大。 a value greater the greater the impact by the algorithm in finding solutions pheromone process, whereas the larger the greater the impact by 0 heuristic information.

[0062] •信息素更新 [0062] • pheromone update

[0063] 信息素更新的目的是增加与优质解或潜在优质解相关的信息素含量,同时降低与劣质解相关的信息素含量。 [0063] The purpose is to increase the pheromone update pheromone content associated with high quality potential solution or solution, while reducing the pheromone content associated with low-quality solution. 方法的信息素更新规则如下: Method pheromone updating rule is as follows:

[0064] [0064]

Figure CN102858019BD00092

[0065] 其中P为信息素挥发系数,其设定值范围为0〜1,在此范围内P取值越大则使得上次迭代中的信息素对本次迭代的遗留影响越小。 [0065] wherein P is a pheromone evaporation rate, the set value in the range of 0~1, P values ​​in this range such that the greater the previous iteration pheromone smaller legacy of this iteration pair. 1_与1_分别为信息素含量的上界与下界,其设定值范围分别为10〜20与0〜10, 定义如下: 1_ 1_ are upper and lower bounds for the pheromone content set value range 0 ~ 10 and 10-20 are defined as follows:

[0066] [0066]

Figure CN102858019BD00093

[0067] 其中Q为调节信息素增量大小的常量,其设定值范围为0. 01〜0. 1,在此范围内Q 取值越大则使得本次迭代中产生的最优解包含的边上的信息素增加越快,从而使得算法能够较快的收敛,但解的质量较差;反之,算法收敛较慢,但解的质量较好。 [0067] wherein Q is a constant increment size pheromone adjustment, the set value in the range of 0. 01~0. 1, in this range such that the greater the Q value of the optimal solution generated in this iteration comprising edge pheromone increases quickly, so that the algorithm can be faster convergence, but poor solution quality; conversely, the algorithm converges slowly, but better quality solution.

[0068] 具体而言,如图5所示,本发明公开了以下步骤: [0068] Specifically, as shown in Figure 5, the present invention discloses the following steps:

[0069] 步骤(1),CBS采集其与N个CMS之间的信道状态信息tv i = 1,2, ...,N以及与M个PU之间的信道状态信息g」,j = 1,2,. . .,M。 [0069] Step (1), CBS collection which tv channel state information between the CMS number N i = 1,2, ..., N channel state between the PU information and the M g ', j = 1 , 2 ,..., M.

[0070] 步骤(2),设置Tmax= 10,tmin= 5,初始化构建图中每条边es,s+1(j)上分布的信息素Ts,s+l (j) = ( T max+ T min)/2与启发式信息Is+l (j) = I hj I 2, S =0,【,…,nT_M,= 1,2, • • •,N〇 [0070] Step (2), provided Tmax = 10, tmin = 5, the initialization build FIG every edge es, s + 1 pheromone Ts distributed over (j), s + l (j) = (T max + T min) / 2 and heuristic information Is + l (j) = I hj I 2, S = 0, [, ..., nT_M, = 1,2, • • •, N〇

[0071] 步骤(3),生成m只人工蚂蚁,每只蚂蚁按以下概率选择边es,s+1(j): [0071] Step (3), only generates m artificial ants, each ant selected according to the following probability side es, s + 1 (j):

[0072] [0072]

Figure CN102858019BD00094

[0073] 记录蚂蚁nT_M次移动经过的路径,选择路径中的边所对应的CMS组成接入集^。 [0073] ant path nT_M recording times moved through, edge selection path corresponding set of access CMS ^ composition. 蚂蚁数m设定为5-30之间,权重a,0设置为a = 2, 0 = 1。 Ants number m is set to 5 to 30, weight a, 0 is set to a = 2, 0 = 1.

[0074]步骤(4),按如下方法计算CBS对应于不同CMS的双重正交波束赋形向量wb-, 灸e 乂:对第k个CMS,构建矩阵? [0074] Step (4), calculated as follows CBS corresponds to double the orthogonal beamforming vectors of different WB-CMS, e qe moxibustion: a k-th of CMS, constructing a matrix? ."如下: ."as follows:

[0075] [0075]

Figure CN102858019BD00101

[0076] 计算p的〇特征值所对应的特征向量" 再通过归一化n\\; [0076] p is calculated eigenvalue square corresponding eigenvectors "n \\ then by normalizing;

[0077]步骤(5),按下式分配发送功率A4i给发送至乂中的CMSk的数据流: [0077] Step (5), the following equation allocated to the transmission power to the transmission data stream A4i qe in CMSk of:

[0078] [0078]

Figure CN102858019BD00102

[0079] 其中A >〇的选择需使得g A °计算每只蚂蚁选择的接入集^的系统容量如下: [0079] where A> square so choices need to set access g A ° is calculated each ant ^ system capacity selected as follows:

[0080] [0080]

Figure CN102858019BD00103

[0081] 选择最大系统容量对应的接入集为最优接入集乂' [0081] selecting an access system capacity corresponding to the maximum set for the optimum set of access qe '

[0082] 步骤(6),判断是否达到最大迭代次数,最大迭代次数为大于0的自然数,一般设置为5〜50之间,若满足则停止并输出^% [0082] Step (6), it is determined whether the maximum number of iterations, a maximum number of iterations is a natural number greater than zero, typically between 5~50 set, if yes then stopped and outputs ^%

[0083]步骤(7),设置P = 0. 04, Q = 0. 02,按下式更新所有边上的信息素并返回至步骤(3)〇 [0083] Step (7), provided P = 0. 04, Q = 0. 02, the following equation pheromone update all sides and return to step (3) square

[0084] [0084]

Figure CN102858019BD00104

[0085] 其中Ar=二如〜(J)eAesl,rsbyf为迄今为止蚂蚁所发现的最大系统丨0,其他容量,对应的路径。 [0085] wherein two Ar = as ~ (J) eAesl, rsbyf 0 to the maximum system Shu ants found so far, the additional capacity, the corresponding path.

[0086] 实施例 [0086] Example

[0087] 为验证本发明中提出的基于AC0的用户选择方法的性能,下面比较了其与最优方法一穷举搜索(Brute Force Search)以及另一种广泛采用的次优方法一贪婪方法所获得的系统容量。 [0087] To verify the performance of the user based AC0 selection method proposed in the present invention, the following comparison with an exhaustive search for optimal methods (Brute Force Search) and another widely used method of a sub-optimal greedy method system capacity available. 为避免对PU的干扰,以上三种方法都使用了本发明中提出的双重正交传输空间复用技术。 In order to avoid interference with the PU, the above three methods are used in transmission dual orthogonal spatial multiplexing proposed in the present invention. 穷举搜索比较N个CMS中所有n TM个CMS的组合所获得的系统容量,选择对应于最大值的组合。 An exhaustive search of all combinations of n TM system capacity to CMS Comparison of the obtained N to CMS, select the maximum value corresponding to the combination. 贪婪方法比较CBS与所有CMS之间的信道质量,选择最优的前n TM个接入,其广泛应用于商业通信系统中,如3G1X与Qualcomm HDR。 Greedy method is relatively CBS channel quality among all CMS, select an optimal number n TM front access, which is widely used in commercial communications systems, such as 3G1X and Qualcomm HDR.

[0088] 图3a〜图3c所示的为不同PU数下以上三种方法所取得的实时系统容量,其中图3a、图3b、图3c中分别对应PU数为1、2与3时的情况。 [0088] FIG 3a~ real-time system shown in FIG 3c is different than the number of three methods PU acquired capacity, wherein FIG. 3a, 3b, the corresponding FIG. 3c is a case where the number of PU's 1 and 2 and 3 . 图4所示的为PU数分别为1、2与3时以上三种方法取得的平均系统容量。 PU is a number the average system capacity is 1, 2 are shown in Figure 4 with three methods of obtaining 3 or more. 设定CMS的总数为50, CBS的天线数为4,同时令所有的CMS以及PU距CBS的距离相等且归一化为1,与;为CMS端的平均接收信噪比,及而咖=5dB , _tot =10dB,其定义分别为观兄丽全I / of,SA%ot全// <。 CMS 50 to set the total number of antennas is 4 CBS, and at the same time so that all CMS PU equal distance from CBS and normalized to 1, and; CMS is the average received SNR end, and the coffee = 5dB , _tot = 10dB, which is defined as a concept were full brother Li I / of, SA% ot whole // <. 对于本发明方法,设定蚂蚁数为5, PU数为1、2与3时本发明方法的最大迭代次数分别设定为25、10 与5。 For the method of the present invention, the number of ants is set to 5, the number is 1, 2 PU maximum number of iterations of the method of the present invention is 3 to 25, 10 and 5 are set.

[0089] 由于复杂度主要位于式(5)中的目标函数,因而我们基于目标函数的评估次数来比较三种方法的复杂度。 [0089] Because of the complexity of the objective function mainly in the formula (5), so we assessed based on the number of the objective function to compare the complexity of the three methods. 贪婪方法、穷举搜索方法与本发明方法的计算复杂度比较如下表所示: Greedy method, computational complexity of an exhaustive search method of the present invention and comparative methods as follows:

[0090] [0090]

Figure CN102858019BD00111

[0091] 由图3a〜图3c、图4与上表可知,相对于传统的贪婪计算方法,本发明方法能够改善其性能较差的缺点;而相对于穷举搜索方法,本发明方法能够在取得接近的系统性能时极大降低计算量。 [0091] FIG 3a~ to Figure 3c, the table can be seen in FIG. 4, with respect to the conventional calculation method greedy method of the present invention can improve the drawback of poor performance; with respect to the exhaustive search method, the method of the present invention is capable of greatly reducing the amount of calculation made accessible system performance. 本发明方法能够有效降低调度方法性能与计算复杂度间的冲突,适应认知蜂窝网中对调度方法性能的要求。 The method of the present invention can effectively reduce scheduling conflicts between computational complexity and performance of the method, in a cellular network to adapt to the requirements of the cognitive scheduling method performance.

[0092] 本发明提供了一种认知蜂窝网的下行链路空时调度方法,具体实现该技术方案的方法和途径很多,以上所述仅是本发明的优选实施方式,应当指出,对于本技术领域的普通技术人员来说,在不脱离本发明原理的前提下,还可以做出若干改进和润饰,这些改进和润饰也应视为本发明的保护范围。 [0092] The present invention provides a cognitive empty downlink scheduling method for a cellular network, the specific ways and means to achieve many of the technical solution, the above embodiment is merely a preferred embodiment of the present invention, it should be noted that for the present ordinary skill in the art, in the present invention without departing from the principle of the premise, can make various improvements and modifications, and these improvements and modifications should be the scope of the invention. 本实施例中未明确的各组成部分均可用现有技术加以实现。 The various components are not explicitly described in this embodiment can be realized by the prior art.

Claims (5)

  1. 1. 一种认知蜂窝网的下行链路空时调度方法,其特征在于,包括以下步骤: 步骤(1),采集多天线认知基站与N个单天线认知移动终端之间的信道状态信息向量Iii, i = 1,2,...,N以及认知基站与M个单天线主用户之间的信道状态信息向量gj,j = I, 2,. . . , M ; 步骤(2),初始化构建图中每条边es,s+1(j)上分布的信息素、s+1(j)= 以及启发式信息ns,s+1(j) = |h」2, s = 0, 1,···,ητ-Μ,j = 1,2,···,Ν,其中^«与τ "^分别为信息素含量的上界与下界,τ ">«的设定值范围为10〜20, τ πίη的设定值范围为〇〜10, IhjI表示求信道状态信息向量比的幅值,ηΤ为认知基站的天线数目; 步骤(3),生成m只人工蚂蚁,其中m的设定值范围为5〜30,放置蚂蚁于构建图中顶点v〇处,每只蚂蚁按概率Pr (es,s+1 (j))选择边es,s+1 (j)从顶点Vs移动至顶点V s+1,s = 0, I. ..,nT-M ;记录蚂蚁%, Empty downlink scheduling method for a cellular network cognition, characterized by comprising the following steps: (1) collected channel state between the base station and multiple antennas Cognition Cognitive N single-antenna mobile terminal information vector Iii, i = 1,2, ..., gj channel state information between the vector N and M and cognitive single base station antenna main user, j = I, 2 ,., M;.. step (2 ), initialize each edge constructed FIG es, s + 1 distributed over (j) pheromone, s + 1 (j) = and heuristic information ns, s + 1 (j) = | h '2, s = 0, 1, ···, ητ-Μ, j = 1,2, ···, Ν, wherein ^ «and τ" ^ pheromone content respectively on upper and lower bounds, τ "> set value« of range of 10-20, the predetermined range of τ πίη 〇~10, IhjI channel state information indicates finding the ratio of the amplitude, ηΤ is the number of antennas of the base station cognitive; step (3) generates only an artificial ants m, wherein the predetermined range of 5~30 m, placed at the ants in FIG v〇 construct vertex, each ant according to the probability Pr (es, s + 1 (j)) selected edge es, s + 1 (j) from Vs vertex to move the vertex V s + 1, s = 0, I. .., nT-M; recording ants% 移动经过的路径,选择路径中的边所对应的认知移动终端组成接入集乂; 步骤(4),认知基站计算对应于第k个认知移动终端的双重正交波束赋形向量w#, keA : 步骤(5),分配发送功率给认知基站发送至认知移动终端的数据流;计算每只蚂蚁选择的接入集乂的系统容量。 After moving path, edge selection path corresponding to the composition of the mobile terminal access to current knowledge qe; step (4), corresponding to the base station calculates the cognitive dual orthogonal beamforming vector w k-th mobile terminal Cognitive #, keA: step (5), allocated to the transmission power of the data stream to the base station cognitive perception of the mobile terminal; ant system capacity was calculated for each of the selected access qe set. (^)如下: (^) As follows:
    Figure CN102858019BC00021
    其中,Au为给接入集Z中第k个单天线认知移动终端的数据流分配的发送功率, hM表示接入集乂第k个认知移动终端与认知基站之间的信道状态信息向量,表示对向量h#进行转置操作,d为认知移动终端的接收机的噪声功率;选择最大系统容量对应的接入集为最优接入集;步骤¢),判断是否达到预设的最大迭代次数,若达到则停止并输出最优接入集^4%最大迭代次数取自然数; 步骤(7),更新构建图中所有边上分布的信息素并返回步骤(3);由此完成下行链路空时调度。 Wherein, Au is the access to the transmission power set Z k-th antenna of the cognitive data stream is allocated a single mobile terminal, hM represents a channel status between the k-th access sets qe Cognitive mobile terminal station information and Cognitive vector, the vector h # expressed transpose operation, d cognitive receiver noise power of the mobile terminal; selecting the maximum system capacity corresponding to the access set is optimal set of access; step ¢), determines whether a preset the maximum number of iterations is reached when the access is stopped and outputs the optimal set ^ 4% maximum number of iterations is a natural number; step (7), a construction diagram of the update distribution along all sides of the pheromone and returns to the step (3); whereby upon completion of the downlink scheduling empty.
  2. 2. 根据权利要求1所述的认知蜂窝网的下行链路空时调度方法,其特征在于,步骤(3) 中蚂蚁选择边63, :3+1(」)的概率? The scheduling method of claim 1 empty downlink cellular network when the cognition claim, wherein 63, ants selection step edge (3): probability of 1 + 3 ( ") is? 1'(6;3,;3+1(」))按以下方法计算: 1 '(6; 3; 1 + 3 ( ")) is calculated as follows:
    Figure CN102858019BC00022
    其中表示连接顶点Vs与顶点vs+1的所有边的集合,α与β为对应于信息素与启发式信息的加权系数,α与β的设定值范围为0〜10。 Wherein denotes the vertex vertex vs + Vs and the set of all edges, α and β 1 corresponding to the weighting coefficient for the heuristic information pheromone, α beta] and the set value in the range of 0 ~ 10.
  3. 3. 根据权利要求1所述的认知蜂窝网的下行链路空时调度方法,其特征在于,步骤(4) 中依据以下方法计算第k个认知基站的双重正交波束赋形向量: 对第k个认知基站,构建如下矩阵F# : The scheduling method of claim 1 empty downlink cellular network when the cognition claim, wherein, in step (4) to calculate the double orthogonal beamforming vector of the k th base station according to the following methods cognitive: cognitive of the k-th base stations, build the following matrix F #:
    Figure CN102858019BC00031
    Figure CN102858019BC00032
    计算矩阵!^的〇特征值所对应的特征向量n 归一化n 得至〖 iUi °Λ,k, OA,k ' Matrix calculation! ^ Square feature of a feature vector corresponding to the value n obtained n normalized to 〖iUi ° Λ, k, OA, k '
  4. 4. 根据权利要求1所述的认知蜂窝网的下行链路空时调度方法,其特征在于,步骤(5) 中依据以下注水运算给接入集乂中的用户k分配发送功率凡u = The blank of claim 1 downlink cognitive cellular network when scheduling method as claimed in claim, wherein step (5) is set to the access qe user u k where allocating transmission power according to the following injection operation =
    Figure CN102858019BC00033
    其中λ为注水运算的水位,λ > 〇,λ满足 Wherein [lambda] is the calculation of the water level, λ> square, λ satisfies
    Figure CN102858019BC00034
    ' Ptot为基站总发送功率,Pniax 为能够给单个认知移动终端数据流分配的最大发送功率,符号定义为: 'Ptot is the total transmission power of the base station, Pniax cognitive capable mobile terminal to a single data stream is allocated the maximum transmit power, the symbol is defined as:
    Figure CN102858019BC00035
    对应X,b对应Pmax,a = 0。 Corresponds to X, b corresponding to Pmax, a = 0.
  5. 5. 根据权利要求1所述的认知蜂窝网的下行链路空时调度方法,其特征在于,步骤(7) 中边es,s+1(j)上的信息素Ts s+1(j)按以下方法更新: The scheduling method of claim 1 empty downlink cellular network when the cognition claim, wherein, in step (7) in the edge es, s + 1 pheromone (j) Ts s + 1 (j ) updated as follows:
    Figure CN102858019BC00036
    Cst为迄今为止蚂蚁所发现的最大系统容量,Afst为ίΓ所对应的路径,P为信息素挥发系数,其设定值范围为〇〜1,Q为调节信息素增量大小的常量,其设定值范围为〇. 01〜 0· Io Cst is the maximum capacity of the system so far discovered ants, Afst ίΓ corresponding path, P is the pheromone evaporation rate, the set value in the range of 〇~1, Q is a constant increment size adjustment pheromone, which is provided value range for the square. 01~ 0 · Io
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