WO2017096539A1 - 一种多移动中继最佳通信位置的搜寻方法及搜寻系统 - Google Patents

一种多移动中继最佳通信位置的搜寻方法及搜寻系统 Download PDF

Info

Publication number
WO2017096539A1
WO2017096539A1 PCT/CN2015/096736 CN2015096736W WO2017096539A1 WO 2017096539 A1 WO2017096539 A1 WO 2017096539A1 CN 2015096736 W CN2015096736 W CN 2015096736W WO 2017096539 A1 WO2017096539 A1 WO 2017096539A1
Authority
WO
WIPO (PCT)
Prior art keywords
mobile relay
relay
mobile
signal
destination
Prior art date
Application number
PCT/CN2015/096736
Other languages
English (en)
French (fr)
Inventor
谢宁
梁远
陈敬坤
王晖
林晓辉
Original Assignee
深圳大学
谢宁
梁远
陈敬坤
王晖
林晓辉
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳大学, 谢宁, 梁远, 陈敬坤, 王晖, 林晓辉 filed Critical 深圳大学
Priority to PCT/CN2015/096736 priority Critical patent/WO2017096539A1/zh
Publication of WO2017096539A1 publication Critical patent/WO2017096539A1/zh

Links

Images

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Definitions

  • the invention belongs to the field of wireless communication technologies, and in particular relates to a search method and a search system for optimal communication positions of multiple mobile relays based on variable step size disturbance.
  • Collaborative communication is a rapidly developing and promising technology that uses relayed data to improve received signal quality.
  • the performance of the wireless communication system is mainly restricted by the wireless channel.
  • the propagation path between the transmitter and the receiver is very complicated, and the transmitted signal often passes through various fading and multipath propagation to reach the destination end, and the diversity technology passes.
  • the signal samples that are independently fading and carrying the same information are processed at the destination end, thereby effectively reducing the influence of the wireless channel fading effect.
  • UAVs unmanned aerial vehicles
  • the existing search algorithms for the optimal communication position for UAV relay are mainly: UAV uses the ground user to obtain the geographical location for optimal relay communication position search by GPS, and the perturbation-based extreme value search control ( Extremum Seeking Control (ESC) algorithm, based on multi-airborne antenna algorithms.
  • the existing optimal relay communication location search algorithm for UAVs can make the UAV find the best relay location on the basis of each, but these algorithms or applicable scopes also have certain deficiencies and defects, mainly reflecting In: (1) communication relay relies on GPS to be vulnerable to attacks and GPS signals are not always available, and may also suffer from GPS spoofing or interference, resulting in communication relay failure. More importantly, in a lot of special circumstances In the case of communication, there is no GPS function or the GPS device is damaged.
  • the GPS device is damaged due to natural disasters.
  • DOA Direction of Arrival
  • the technical problem to be solved by the present invention is to provide a search method and a search system for a multi-mobile relay optimal position based on variable step size disturbance, aiming at solving the optimal communication position currently applied to the UAV relay.
  • the search algorithm is vulnerable to GPS spoofing or interference, which causes communication relay failure, is prone to estimation error, and increases the complexity and algorithm complexity of the UAV communication device.
  • the present invention is implemented in such a manner that a multi-mobile relay optimal communication location search method includes the following steps:
  • Step A each mobile relay receives a training sequence sent from the source end at an arbitrary position on the fixed track, and transmits the training sequence to the destination end;
  • Step B The destination end receives independent fading signals from each mobile relay and performs maximum ratio combining, and then generates single-bit information broadcast feedback to all mobile relays according to the combined result in each time slot;
  • the independent fading signal is The signal of the training sequence after reaching the destination end after fading;
  • Step C Each mobile relay records current location information and performs calculation according to the single bit information, performs location movement according to the calculation result, and returns to step A to finally determine an optimal relay communication location.
  • the final determination of the optimal relay communication location can be determined by a limited time length or communication performance meeting system requirements.
  • step A before performing the optimal relay communication location search, each mobile relay is placed on a different track to initialize its location information, and the training sequence transmitted from the source end is received and transmitted to the destination end; There is no intersection between the running tracks and the gyroscope keeps the mobile relays running on their respective tracks.
  • step B It indicates that the destination end receives the k-channel independent fading signals from the k mobile relays, and outputs the combined signals after the maximum ratio combining, and the combined signals are represented by y D , then:
  • i represents the ith mobile relay
  • I the weighting coefficient of the ith branch
  • a i is the signal amplitude of the ith branch
  • ⁇ i 2 is the average power of the ith branch noise, 0 ⁇ i ⁇ k.
  • each mobile relay uses a gyroscope to maintain a fixed motion trajectory and perform positional movement, and performs calculation according to the single-bit information while introducing a correction factor, a cumulative positive feedback counter, a continuous negative feedback counter, and The threshold correction mechanism, and then each mobile relay performs position shifting by changing the motion step and direction according to the calculation result, and returns to step A.
  • step C specifically includes:
  • each mobile relay records its current position, with the current position as the preliminary optimal position, the preliminary optimal position is represented by ⁇ i (n), i represents the i-th mobile relay, and n represents the nth time.
  • Step C2 Each mobile relay changes a motion step length in each iteration time slot according to the single bit information, and the transformed motion step size includes a random disturbance step size plus a correction factor;
  • Step C3 Each mobile relay calculates a next time position according to the changed motion step size, and each mobile relay performs positional movement according to the next time position, returns to step A, receives a training sequence transmitted from the source end, and transmits To the destination;
  • step C4 the destination calculates the maximum signal-to-noise ratio of the combined signal, and compares the calculated signal-to-noise ratio with the known signal-to-noise ratio of the best received signal, and updates the best in memory. Receiving signal signal-to-noise ratio strength, and then the destination broadcasts feedback single-bit information to all mobile relays, the single-bit information including information on whether the received signal performance is improved;
  • Step C5 each mobile relay performs calculation according to the single-bit information of the feedback and transforms the motion step and direction, updates the known position and stores, and finally determines the best known position, and the best known position is the most Good relay communication location.
  • step C5 specifically includes:
  • Step C51 Each mobile relay determines the single bit information.
  • Step C52 when it is determined that the performance of the received signal is improved, the accumulated positive feedback counter is incremented by 1, the correction factor is cleared, and the continuous negative feedback counter is cleared, and it is determined whether the accumulated positive feedback counter reaches a preset cumulative positive feedback threshold;
  • Step C53 if it is determined that the cumulative positive feedback counter in step C52 reaches the preset cumulative positive feedback threshold, the cumulative positive feedback counter is cleared, and the motion step size is increased and the cumulative positive feedback threshold is increased and returned to step C3;
  • Step C54 if it is determined that the cumulative positive feedback counter in step C52 does not reach the preset cumulative positive feedback threshold, then return to step C3;
  • Step C55 when it is determined that the performance of the received signal is not improved, the mobile relay returns to the position of the previous time slot, and the continuous negative feedback counter is incremented by 1, the correction factor is modified to the opposite of the motion step of the previous time slot, and the continuous negative is determined. Whether the feedback counter reaches a preset continuous negative feedback threshold;
  • Step C56 if it is determined that the continuous negative feedback counter in step C55 reaches the preset continuous negative feedback threshold, the accumulated positive feedback counter and the continuous negative feedback counter are cleared, and the motion step size is decreased and the continuous negative feedback counter threshold is decreased. Return to step C3;
  • step C57 if it is determined that the continuous negative feedback counter in step C55 has not reached the preset continuous negative feedback threshold, then return to step C3.
  • the present invention also provides a search system for multi-mobile relay optimal communication location, including a source end, a plurality of mobile relays, and a destination end;
  • the source end is configured to send a training sequence to the relay
  • the mobile relay is configured to transmit the received training sequence to the destination for calculation; the training sequence is received by the destination end in the form of an independent fading signal after being fading in the transmission process;
  • the destination end is configured to perform maximum ratio combining according to the received independent fading signal, and then generate single-bit information feedback to all mobile relays according to the combined result in each time slot; the mobile relay record
  • the location information is calculated according to the single-bit information, and the position is moved according to the calculation result, and the sequence information sent by the source end is transmitted to the destination end for calculation in real time, and finally the optimal relay communication position is confirmed.
  • each mobile relay is placed on different tracks to initialize its location information, and the training sequence transmitted from the source end is received and transmitted to the destination end; There is no intersection between them, and the mobile relays are kept running on their respective tracks through the gyroscope.
  • the destination end receives the k-channel independent fading signals from the k mobile relays, and outputs the combined signals after the maximum ratio combining, and the combined signals are represented by y D , then:
  • i represents the ith mobile relay
  • I the weighting coefficient of the ith branch
  • a i is the signal amplitude of the ith branch
  • ⁇ i 2 is the average power of the ith branch noise, 0 ⁇ i ⁇ k.
  • each mobile relay uses a gyroscope to maintain a fixed motion trajectory and perform positional movement, and performs calculation based on the single-bit information while introducing a correction factor, a cumulative positive feedback counter, a continuous negative feedback counter, and a threshold correction mechanism, and then each The mobile relay transforms the motion step and direction according to the calculation result to perform positional movement, and receives the training sequence transmitted from the source end in real time and transmits it to the destination end.
  • the present invention has the beneficial effects that the search method provided by the present invention uses the airborne single antenna of each mobile relay without relying on GPS, and does not need to know the location information of the terrestrial communication unit, and each mobile relay only utilizes The single-bit information fed back from the destination can find the best relay communication position within a given range of motion trajectory. Further, the present invention can be applied to search for the optimal communication position of multiple mobile relays and improve the performance of relay communication. Suitable for relaying enhanced multi-track motion.
  • FIG. 1 is a flowchart of a method for searching for a multi-mobile relay optimal position according to Embodiment 1 of the present invention.
  • FIG. 2 is a second embodiment of the present invention, using a multi-unmanned aerial vehicle as an optimal position of a mobile relay Schematic diagram of the search system.
  • FIG. 3 is a detailed step diagram of using a multi-UAV as a mobile communication optimal communication location searching method according to Embodiment 1 of the present invention.
  • FIG. 4 is a schematic diagram of signal to noise ratio distribution in a search process using a multi-UAV as a best position for a mobile relay according to Embodiment 1 of the present invention.
  • FIG. 5 is a schematic diagram of a time slot and a signal to noise ratio of a search process using a multi-UAV as a best location for a mobile relay according to Embodiment 1 of the present invention.
  • FIG. 6 is a schematic diagram of a time slot and a position of each drone using a multi-UAV as a mobile relay optimal location search process according to Embodiment 1 of the present invention.
  • FIG. 7 is a schematic diagram of a bit error rate distribution corresponding to a mobile relay location using a multi-UAV according to Embodiment 1 of the present invention.
  • FIG. 8 is a schematic diagram of the time slot and the achieved bit error rate of the search process using the multi-UAV as the optimal location of the mobile relay according to the first embodiment of the present invention.
  • the search method provided by the present invention uses an on-board single antenna, and does not need to know the location information of the terrestrial communication unit, and the UAV can still use the single-bit information fed back by the destination end.
  • Fixed motion track Find the best UAV relay communication location within the perimeter and expand the application scenario.
  • the large step size is used to accelerate the convergence speed, which accelerates the convergence speed of the algorithm.
  • the small convergence is used to speed up the convergence by making full use of the continuous negative feedback information.
  • the present invention provides a method for searching for a multi-mobile relay optimal communication location as shown in FIG. 1.
  • the steps include:
  • Each mobile relay receives the training sequence sent from the source end and transmits it to the destination end at any position on the fixed track. Specifically, in this step, before performing the optimal relay communication location search, each mobile relay is placed on different tracks to initialize its location information, and the location is the initial optimal location, and then continues in the subsequent search process. Update its known best position, there is no intersection between the tracks of each mobile relay, and the mobile relays are kept running on their respective tracks through the gyroscope.
  • the destination end receives independent fading signals from each mobile relay and performs maximum ratio combining, and then generates single-bit information broadcast feedback to all mobile relays according to the combined result in each time slot; the independent fading signal is The signal that the training sequence passes through the fading to the destination.
  • the combined result is compared with the known best performance to determine whether the performance is improved, the performance may be a signal to noise ratio or a bit error rate, and the single bit information fed back to all mobile relays indicates the received signal performance. Whether it is improved or not, in practical applications, the single-bit information generally indicates that the received signal performance is improved by 1 and 0 indicates that the received signal performance is not improved.
  • Each mobile relay records current location information and performs calculation according to the single bit information, performs location shift according to the calculation result, and returns to step S1 to finally determine an optimal relay communication location.
  • each mobile relay records current location information, performs calculation according to the single bit information, and introduces a correction factor, a cumulative positive feedback counter, a continuous negative feedback counter, and a threshold correction mechanism, and then each mobile relay is configured according to The result of the calculation changes the motion step and direction for positional movement, and returns to step S1 to finally determine the optimal relay position.
  • the final determined optimal relay communication location can be determined by a limited time length or communication performance that meets the system requirements.
  • a mobile relay it can be a drone, or it can be a hot air balloon or a satellite.
  • the drone is used as a mobile relay, and the present invention is further illustrated by FIGS. 2 to 8.
  • a search system using a multi-unmanned aerial vehicle as an optimal location of a mobile relay including a source end, a plurality of drones, and a destination end, is provided in the embodiment of the present invention;
  • Sending a training sequence to the drone the drone is configured to transmit the received training sequence to the destination for calculation;
  • the training sequence is lapsed in the form of an independent fading signal during transmission
  • Receiving by the destination end the destination end is configured to perform maximum ratio combining according to the received independent fading signal, and then generate single-bit information feedback to all the drones according to the combined result in each time slot;
  • the drone The position information is recorded and calculated according to the single-bit information, and the position is moved according to the calculation result, and the sequence information sent by the source end is transmitted to the destination end for calculation in real time, and finally the optimal relay communication position is confirmed.
  • the source end and the destination end can be functionally switched to each other, that is, in the implementation process, the source end and the destination end simultaneously have the functions of sending
  • the three coordinate variables in the cylindrical coordinate system provided in Figure 2 are (r, ⁇ , z).
  • r is the radius of motion of the drone on the xoy plane
  • ⁇ is the angle rotated from the x-axis in the counterclockwise direction to oR' i from the positive z-axis
  • oR' i is the drone in the xy plane
  • the projection, z is the height of the drone.
  • the drone moves on a circle with a height of z and a radius of r.
  • the coordinates of the center of the circle o (0, 0, z), the coordinates of the source end S (x s , y s , z s ), the coordinates of the destination end D (x) d , y d , z d ).
  • the coordinates of the i-th drone at time n are R i (r i , ⁇ i (n), z), then the coordinates of the i-th drone at n+1 time R i (r i , ⁇ i (n+1), z).
  • the communication distance between the source S and the destination D of the i-th drone R i (r i , ⁇ i (n), z) at time n is:
  • x is the source S transmitting a unit average power signal
  • n 1 is an additive white Gaussian noise of E[
  • 2 ] N 01 . It is the free space path loss of the first hop channel source S to the drone relay R i , ⁇ is the carrier wavelength, and P S is the transmit power.
  • G i is the gain of the relay R i to the signal
  • n 2 is the additive white Gaussian noise of E[
  • 2 ] N 02 . Is the free space path loss of the second hop channel.
  • I the weighting coefficient of the ith branch, where A i is the signal amplitude of the ith branch and ⁇ i 2 is the average power of the ith branch noise.
  • the performance of the current time slot and the previous time slot is compared. If the target is improved, single-bit positive feedback is performed, and if it is reduced, single-bit negative feedback is performed.
  • a detailed step-by-step diagram of using a multi-unmanned aerial vehicle based on a variable step size as an optimal communication location search method for a mobile relay includes:
  • Step A each drone records its current position, with the current position as the preliminary optimal position, the preliminary optimal position is represented by ⁇ i (n), i represents the i-th drone, and n represents the nth time Gap
  • Step B Each UAV changes the motion step and direction in each iteration slot according to the single bit information, and the transformed motion step includes a random disturbance step plus a correction factor;
  • Step C Each drone calculates a next time position according to the changed motion step, performs position movement according to the calculated next time position, returns to step S1, receives the training sequence transmitted from the source end, and transmits the training sequence to the destination end. ;
  • step D the destination calculates the signal-to-noise ratio intensity of the maximum ratio combined signal, and compares the calculated signal-to-noise ratio intensity with the known signal-to-noise ratio of the best received signal, and updates the most in memory.
  • the signal-to-noise ratio is received, and then the destination broadcasts feedback single-bit information to all the drones, the single-bit information including information on whether the received signal performance is improved; the single-bit information indicates that the received signal performance is improved by 1 0 indicates that the received signal performance has not improved.
  • each drone calculates and converts the motion step and direction according to the single-bit information of the feedback, updates the known position and stores, and finally determines the best known position, and uses the best known position as the optimal relay. Communication location.
  • step E specifically includes:
  • Step E1 each drone judges the single bit information
  • step E2 when it is determined that the performance of the received signal is improved, the accumulated positive feedback counter is incremented by 1, the correction factor is cleared, and the continuous negative feedback counter is cleared, and it is determined whether the accumulated positive feedback counter reaches a preset cumulative positive feedback threshold;
  • Step E3 if it is determined that the cumulative positive feedback counter in step E2 reaches the preset cumulative positive feedback threshold, the cumulative positive feedback counter is cleared, and the motion step size is increased and the cumulative positive feedback threshold is increased and returned to step C;
  • Step E4 if it is determined that the cumulative positive feedback counter in step E2 does not reach the preset cumulative positive feedback threshold, then return to step C;
  • step E5 when it is determined that the performance of the received signal is not improved, the drone returns to the position of the previous time slot, and the continuous negative feedback counter is incremented by 1, the correction factor is modified to the opposite of the motion step of the previous time slot, and the continuous negative is determined. Whether the feedback counter reaches a preset continuous negative feedback threshold;
  • step E6 if it is determined that the continuous negative feedback counter in step E5 reaches the preset continuous negative feedback threshold, the accumulated positive feedback counter and the continuous negative feedback counter are cleared, and the motion step size is decreased and the continuous negative feedback counter threshold is decreased.
  • step E7 if it is determined that the continuous negative feedback counter in step E5 has not reached the preset continuous negative feedback threshold, then return to step C.
  • the correction factor ⁇ i (n) the cumulative positive feedback counter C P and the continuous negative feedback counter C N and the threshold correction mechanism are introduced.
  • ⁇ 0 is the variable disturbance step of the algorithm
  • n is the time slot
  • i is the ith. Drone.
  • the receiver at the destination measures the signal-to-noise ratio SNR MRC (n) of the maximum ratio of the combined signal, while the known best maximum ratio is the SNR MRC_best (n) of the combined signal, and then updates the in-memory
  • SNR MRC_best (n+1) max (SNR MRC_best (n), SNR MRC (n)).
  • the receiver then feeds back a single bit of information to all of the drones to indicate whether the received signal is improved.
  • the i-th drone updates its best known position ⁇ i (n) based on the single-bit information returned from the feedback.
  • the update rules are as follows:
  • ⁇ i (n+1) ⁇ i (n)+ ⁇ i (n)+ ⁇ i (n);
  • C T1 represents the cumulative positive feedback threshold
  • C T2 represents the continuous negative feedback threshold
  • R I is the step size amplification factor
  • R D is the step size reduction factor
  • ⁇ T1 is the cumulative positive feedback threshold increase factor
  • the optimal communication location simulation for multiple UAV relays is as follows:
  • the horizontal axis represents ⁇ i (n), and the vertical axis represents the end-to-end signal-to-noise ratio ⁇ of the relay position corresponding to ⁇ i (n);
  • the horizontal axis of Fig. 5 shows the number of time slots spent by the multi-UAV in searching for the best position
  • the vertical axis represents the end-to-end signal-to-noise ratio ⁇ , as the drone-MRC can see when searching for the 80th time slot.
  • the 8dB position was found, and the best relay communication position was found in the 160th time slot, that is, the maximum point in Fig. 4 and the position corresponding to the drone in Fig. 6.
  • the horizontal axis of Fig. 6 indicates the number of time slots spent by the multi-UAV in searching for the optimum position
  • the vertical axis indicates the position of each of the unmanned aerial vehicles at the time slot.
  • the horizontal axis of Fig. 7 represents ⁇ i (n), and the vertical axis represents the end-to-end error rate of the relay position corresponding to ⁇ i (n);
  • the horizontal axis of Fig. 8 shows the number of time slots spent by the multi-UAV in searching for the best position, and the vertical axis represents the end-to-end error rate.
  • the algorithm basically converges. That is, the minimum point in Figure 7 is found.
  • the algorithm provided by the present invention is very advantageous for the convergence effect of the initial small step disturbance, that is, the convergence to the optimal relay communication position can be accelerated in the early and late stages of the convergence of the algorithm.
  • the continuous negative feedback threshold C T2 of the continuous negative feedback counter C N is reduced by a fixed value ⁇ T2 every time the disturbance motion step ⁇ 0 is reduced, which will improve the convergence speed of the algorithm in the later stage of convergence. .
  • the algorithm is applicable to initial perturbation motion step values of any size.
  • the invention belongs to the field of wireless communication technologies and can be applied to search for multi-relay optimal communication locations and improve the performance of relay communication. This method is suitable for enhancing the relay of multi-track motion.
  • Potential application areas include the construction of temporary communication systems and communication connections at disaster sites.

Landscapes

  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Radio Relay Systems (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

本发明适用于无线通信领域，提供了一种多移动中继最佳通信位置的搜寻方法，步骤包括：A，各移动中继在固定轨道的任意位置上，接收来自源端发送的训练序列，并传输至目的端；B，所述目的端接收来自各移动中继的独立衰落信号并进行最大比合并，然后在每一时隙根据合并结果生成单比特信息广播反馈至所有的移动中继；C，各移动中继记录当前位置信息并根据所述单比特信息进行计算，根据计算结果进行位置移动，并返回步骤A，最终确定最佳中继通信位置。本发明提供的搜寻方法使用机载单天线且无需依赖GPS，且无需知道地面通信单元的位置信息，各移动中继只利用目的端反馈的比特信息就能够在给定运动轨迹范围内找到最佳的中继通信位置。

Description

一种多移动中继最佳通信位置的搜寻方法及搜寻系统 技术领域
本发明属于无线通信技术领域，尤其涉及一种基于可变步长扰动的多移动中继最佳通信位置的搜寻方法及搜寻系统。
背景技术
协作通信是目前发展迅速并且很有潜力的技术，协作通信采用中继转发数据来提高接收信号质量。无线通信系统的性能主要是受到无线信道的制约，在现实环境中，发射机和接收机之间的传播路径非常复杂，发送信号往往经过多种衰落及多径传播才能到达目的端，分集技术通过在目的端合并处理经过独立衰落且承载相同信息的信号样本，进而可以有效减轻无线信道衰落效应的影响。随着人类通信需求的日益增长，对于崎岖多山或者市区等无线通信易被障碍物阻挡的地理环境，飞机、卫星及无人机(Unmanned Aerial Vehicles，UAVs)作为通信中继能够有效地连接其中的用户。近些年来，使用无人机作为通信中继已经吸引了不少学者的关注和研究。利用单比特的反馈机制实现多无人机自动搜寻最佳的通信位置，有利于提高通信质量，增大通信范围，因此变得越来越重要。
现有的应用于无人机中继的最佳通信位置的搜寻算法主要有：无人机利用地面用户通过GPS获取地理位置进行最佳中继通信位置的搜寻，基于扰动的极值搜索控制(Extremum Seeking Control，ESC)算法，基于多机载天线的算法。现有的无人机最佳中继通信位置搜寻算法，在各自的基础上都可以使无人机找到最佳的中继位置，但是这些算法或适用范围也存在一定的不足和缺陷，主要体现在：(1)通信中继依赖于GPS容易遭受攻击并且GPS信号并不是时刻可用，也可能遭受GPS欺骗或干扰而导致通信中继失败。更重要的是，在很多特殊情 况下通信双方没有GPS功能或者GPS设备已损坏，如自然灾害导致GPS设备损坏。(2)使用机载多天线对信号到达角(Direction of Arrival，DOA)进行估计来搜寻最佳中继通信位置，但是容易出现估计误差，且增加了无人机通信设备的复杂度和算法复杂度。
发明内容
本发明所要解决的技术问题在于提供一种基于可变步长扰动的多移动中继最佳位置的搜寻方法及搜寻系统，旨在解决现有应用于无人机中继的最佳通信位置的搜寻算法容易遭受GPS欺骗或干扰而导致通信中继失败，容易出现估计误差，且增加了无人机通信设备的复杂度和算法复杂度的问题。
本发明是这样实现的，一种多移动中继最佳通信位置的搜寻方法，步骤包括：
步骤A，各移动中继在固定轨道的任意位置上，接收来自源端发送的训练序列，并传输至目的端；
步骤B，所述目的端接收来自各移动中继的独立衰落信号并进行最大比合并，然后在每一时隙根据合并结果生成单比特信息广播反馈至所有的移动中继；所述独立衰落信号为所述训练序列经过衰落后到达目的端的信号；
步骤C，各移动中继记录当前位置信息并根据所述单比特信息进行计算，根据计算结果进行位置移动，并返回步骤A，最终确定最佳中继通信位置。所述的最终确定最佳中继通信位置，可以通过有限时间长度或者通信性能满足系统要求来进行确定。
进一步地，步骤A中，进行最佳中继通信位置搜寻前，将各移动中继放在不同轨道上来初始其位置信息，接收来自源端发射的训练序列，并传输至目的端；各移动中继运行的轨道之间没有交集，并通过陀螺仪保持移动中继在各自轨道上运行。
进一步地，步骤B中，以
Figure PCTCN2015096736-appb-000001
表示目的端接收来自k个移动中继 的k路独立衰落信号，经最大比合并后输出合并信号，以yD表示所述合并信号，则：
Figure PCTCN2015096736-appb-000002
其中，i表示第i个移动中继，
Figure PCTCN2015096736-appb-000003
为第i条支路的加权系数，其中Ai为第i条支路的信号幅度，σi 2为第i条支路噪声的平均功率，0≤i≤k。
进一步地，所述步骤C中，各移动中继使用陀螺仪保持固定的运动轨迹和进行位置的移动，根据所述单比特信息进行计算同时引入修正因子、累积正反馈计数器、连续负反馈计数器和阈值修正机制，然后各移动中继根据计算结果变换运动步长和方向进行位置移动，并返回步骤A。
进一步地，所述步骤C具体包括：
步骤C1，各移动中继记录其当前位置，以当前位置为初步最佳位置，所述初步最佳位置用θi(n)表示，i表示第i个移动中继，n表示第n个时隙；
步骤C2，各移动中继根据所述单比特信息在每个迭代时隙变更运动步长，变换后的运动步长包括随机扰动步长加修正因子；
步骤C3，各移动中继根据变更后的运动步长计算下一时刻位置，各移动中继根据所述下一时刻位置进行位置移动，返回步骤A，接收来自源端发射的训练序列，并传输至目的端；
以
Figure PCTCN2015096736-appb-000004
表示所述下一时刻位置，以δi(n)所述随机扰动步长，ξi(n)表示修正因子，则：
Figure PCTCN2015096736-appb-000005
步骤C4，目的端计算最大比合并后信号的信噪比强度，根据计算出的信噪比强度的结果与已知的最佳接收信号的信噪比强度相比，并且更新内存中的最佳接收信号信噪比强度，然后目的端广播反馈单比特信息给所有移动中继，所述单比特信息包括接收信号性能是否提高的信息；
步骤C5，各移动中继根据反馈的单比特信息进行计算并变换运动步长和方向，更新已知位置并存储，最终确定最佳已知位置，以该最佳已知位置作为最 佳中继通信位置。
进一步地，所述步骤C5具体包括：
步骤C51，各移动中继对所述单比特信息进行判断；
步骤C52，在判断为接收信号性能提高时，累积正反馈计数器加1，修正因子清零和连续负反馈计数器清零，并判断累积正反馈计数器是否达到预设的累积正反馈阈值；
步骤C53，若判断步骤C52中的累积正反馈计数器达到预设的累积正反馈阈值，则累积正反馈计数器清零，并且增大运动步长和增大累积正反馈阈值并返回步骤C3；
步骤C54，若判断步骤C52中的累积正反馈计数器未达到预设的累积正反馈阈值，则返回步骤C3；
步骤C55，在判断为接收信号性能未提高时，移动中继返回上一时隙的位置，同时连续负反馈计数器加1，修正因子修改为上一时隙的运动步长的相反数，并判断连续负反馈计数器是否达到预设的连续负反馈阈值；
步骤C56，若判断步骤C55中的连续负反馈计数器达到预设的连续负反馈阈值，则累积正反馈计数器和连续负反馈计数器清零，并且减小运动步长和减小连续负反馈计数器阈值并返回步骤C3；
步骤C57，若判断步骤C55中的连续负反馈计数器未达到预设的连续负反馈阈值，则返回步骤C3。
本发明还提供了一种多移动中继最佳通信位置的搜寻系统，包括源端、若干移动中继和目的端；
所述源端，用于发送训练序列至所述中继；
所述移动中继，用于将接收到的训练序列传输至所述目的端进行计算；所述训练序列在传输过程中经衰落后以独立衰落信号的形式被所述目的端接收；
所述目的端，用于根据接收到的独立衰落信号进行最大比合并，然后在每一时隙根据合并结果生成单比特信息反馈至所有移动中继；所述移动中继记录 位置信息并根据所述单比特信息进行计算，根据计算结果进行位置移动，并实时将所述源端发送的序列信息传输至所述目的端进行计算，最终确认最佳中继通信位置。
进一步地，进行最佳中继通信位置搜寻前，将各移动中继放在不同轨道上来初始其位置信息，接收来自源端发射的训练序列，并传输至目的端；各移动中继运行的轨道之间没有交集，并通过陀螺仪保持移动中继在各自轨道上运行。
进一步地，以
Figure PCTCN2015096736-appb-000006
表示目的端接收来自k个移动中继的k路独立衰落信号，经最大比合并后输出合并信号，以yD表示所述合并信号，则：
Figure PCTCN2015096736-appb-000007
其中，i表示第i个移动中继，
Figure PCTCN2015096736-appb-000008
为第i条支路的加权系数，其中Ai为第i条支路的信号幅度，σi 2为第i条支路噪声的平均功率，0≤i≤k。
进一步地，各移动中继使用陀螺仪保持固定的运动轨迹和进行位置的移动，根据所述单比特信息进行计算同时引入修正因子、累积正反馈计数器、连续负反馈计数器和阈值修正机制，然后各移动中继根据计算结果变换运动步长和方向进行位置移动，并实时接收来自源端发射的训练序列，并传输至目的端。
本发明与现有技术相比，有益效果在于：本发明提供的搜寻方法使用各移动中继的机载单天线且无需依赖GPS，且无需知道地面通信单元的位置信息，各移动中继只利用目的端反馈的单比特信息就能在给定运动轨迹范围内找到最佳的中继通信位置，进一步地，本发明可以被应用来搜寻多移动中继最佳通信位置，提高中继通信的性能，适用于增强多轨道运动的中继。
附图说明
图1是本发明实施例一提供的一种多移动中继最佳位置的搜寻方法的流程图。
图2是本发明实施例二提供的一种使用多无人机作为移动中继最佳位置的 搜寻系统的结构示意图。
图3是本发明实施例一提供的一种使用多无人机作为移动中继最佳通信位置搜寻方法的详细步骤图。
图4是本发明实施例一提供的使用多无人机作为移动中继最佳位置的搜寻过程中的信噪比分布示意图。
图5是本发明实施例一提供的使用多无人机作为移动中继最佳位置的搜寻过程所花时隙与达到信噪比的示意图。
图6是本发明实施例一提供的使用多无人机作为移动中继最佳位置搜寻过程的所花时隙与各无人机的位置的示意图。
图7是本发明实施例一提供的使用多无人机作为移动中继位置对应的误码率分布示意图。
图8是本发明实施例一提供的使用多无人机作为移动中继最佳位置的搜寻过程的所花时隙与达到的误码率的示意图。
具体实施方式
为了使本发明的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本发明进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本发明，并不用于限定本发明。
针对现有无人机最佳中继通信位置搜寻算法的不足和缺陷，即：(1)无人机需要获取地面通信用户利用自身的GPS功能测量自己的位置，然而GPS信号并不是时刻可用且依赖GPS功能容易受到攻击和干扰而导致位置搜寻失败；(2)对于没有GPS功能或者GPS设备已损坏的地面通信用户，现有的一些算法是无法使用的；(3)机载多天线相比于单天线增加了无人机的复杂性，且不可避免的会有角度估计误差，同时也增加了算法的复杂性。在多无人机中继通信的场景中，本发明提供的搜寻方法使用机载单天线，且无需知道地面通信单元的位置信息，无人机只利用目的端反馈的单比特信息依然能够在给定运动轨迹范 围内找到最佳的无人机中继通信位置，应用场景扩大。为了使无人机在运动过程中尽快收敛到最佳通信位置，在收敛的初始阶段，通过对累积正反馈信息的充分利用，使用大步长加快收敛速度，加快了算法的收敛速度。在收敛后期阶段，通过对连续负反馈信息的充分利用，使用小步长加快收敛速度。
基于上述原理，本发明提供了如图1所示的一种多移动中继最佳通信位置的搜寻方法，步骤包括：
S1，各移动中继在固定轨道的任意位置上，接收来自源端发送的训练序列，并传输至目的端。具体的，在本步骤中，进行最佳中继通信位置搜寻前，将各移动中继放在不同轨道上来初始其位置信息，以该位置为初步最佳位置，然后在后续的搜寻过程中不断更新其已知最佳位置，各移动中继运行的轨道之间没有交集，并通过陀螺仪保持移动中继在各自轨道上运行。
S2，所述目的端接收来自各移动中继的独立衰落信号并进行最大比合并，然后在每一时隙根据合并结果生成单比特信息广播反馈至所有的移动中继；所述独立衰落信号为所述训练序列经过衰落后到达目的端的信号。具体的，在本步骤中，合并结果与已知最佳性能进行比较，以判断性能是否提高，性能可以是信噪比或误码率，反馈至所有移动中继的单比特信息表示接收信号性能是否提高，在实际应用中，所述单比特信息，一般以1表示接收信号性能提高，0表示接收信号性能未提高。
S3，各移动中继记录当前位置信息并根据所述单比特信息进行计算，根据计算结果进行位置移动，并返回步骤S1，最终确定最佳中继通信位置。具体的，在本步骤中，各移动中继记录当前位置信息，根据所述单比特信息进行计算同时引入修正因子、累积正反馈计数器、连续负反馈计数器和阈值修正机制，然后各移动中继根据计算结果变换运动步长和方向进行位置移动，并返回步骤S1，最终确定最佳中继位置。最终确定的最佳中继通信位置，可以通过有限时间长度或者通信性能满足系统要求来进行确定。
但实际应用中，作为移动中继的可以为无人机，也可以为热气球、卫星等， 在本实施例中，使用无人机作为移动中继，通过图2至图8对本发明进行进一步的阐述。
如图2所示，在本发明实施例提供的一种使用多无人机作为移动中继最佳位置的搜寻系统，包括源端、若干无人机和目的端；所述源端，用于发送训练序列至所述无人机；所述无人机，用于将接收到的训练序列传输至所述目的端进行计算；所述训练序列在传输过程中经衰落后以独立衰落信号的形式被所述目的端接收；所述目的端，用于根据接收到的独立衰落信号进行最大比合并，然后在每一时隙根据合并结果生成单比特信息反馈至所有无人机；所述无人机记录位置信息并根据所述单比特信息进行计算，根据计算结果进行位置移动，并实时将所述源端发送的序列信息传输至所述目的端进行计算，最终确认最佳中继通信位置。在具体应用中，源端和目的端可以进行功能上的相互切换，即：在实施过程中，源端和目的端同时具备发送训练时序和进行信号处理等功能。
在图2提供的柱坐标系中的三个坐标变量是(r，θ，z)。其中r为无人机在xoy平面上的运动半径，θ为从正z轴来看自x轴按逆时针方向转到oR′i所转过的角，oR′i为无人机在xy平面的投影，z为无人机的高度。特别的，在图2中：
①、无人机运动的固定步长δ(n)＝±δ0，δ(n)＝+δ0表示逆时针方向移动，δ(n)＝-δ0表示顺时针方向移动。
②、无人机在高度为z，半径为r的圆周上移动，圆心坐标o(0，0，z)，源端坐标S(xs，ys，zs)，目的端坐标D(xd，yd，zd)。
③、第i个无人机在n时刻的坐标为Ri(ri，θi(n)，z)，那么第i个无人机在n+1时刻的坐标Ri(ri，θi(n+1)，z)。
④、柱坐标系(r，θ，z)与空间直角坐标系(x，y，z)的转换关系如下：
Figure PCTCN2015096736-appb-000009
⑤、n时刻第i个无人机Ri(ri，θi(n)，z)离源端S与目的端D的通信距离分别是：
Figure PCTCN2015096736-appb-000010
3.多无人机中继通信过程
1)：第一跳通信：源端S→Ri，Ri表示第i个无人机；
Figure PCTCN2015096736-appb-000011
x是源端S发射单位平均功率信号，n1是E[|n1|2]＝N01的加性高斯白噪声。
Figure PCTCN2015096736-appb-000012
是第一跳信道源端S到无人机中继Ri的自由空间路径损耗，λ是载波波长，PS是发射功率。
2)：第二跳通信：Ri→D，其中，Ri表示第i个无人机，D表示目的端；
Figure PCTCN2015096736-appb-000013
Gi是中继Ri对信号的增益，n2是E[|n2|2]＝N02的加性高斯白噪声。
Figure PCTCN2015096736-appb-000014
是第二跳信道的自由空间路径损耗。
其中增益Gi如下：(
Figure PCTCN2015096736-appb-000015
是Ri的输出功率)
Figure PCTCN2015096736-appb-000016
因此，每条支路最终的端到端信噪比为：
Figure PCTCN2015096736-appb-000017
其中：
Figure PCTCN2015096736-appb-000018
Figure PCTCN2015096736-appb-000019
3)：目的端进行最大比合并
设来自k个无人机的k路独立衰落信号分别为
Figure PCTCN2015096736-appb-000020
则合并后输出为：
Figure PCTCN2015096736-appb-000021
式中，
Figure PCTCN2015096736-appb-000022
为第i条支路的加权系数，其中Ai为第i条支路的信号幅度，σi 2为第i条支路噪声的平均功率。
目的端对接收到的信号进行最大比合并后，则比较当前时隙与上一时隙的性能，若是提高了则进行单比特的正反馈，若是降低了则进行单比特的负反馈。
如图3所示，为本发明实施例提供的一种基于变步长的使用多无人机作为移动中继最佳通信位置搜寻方法的详细步骤图，其中包括：
步骤A，各无人机记录其当前位置，以当前位置为初步最佳位置，所述初步最佳位置用θi(n)表示，i表示第i个无人机，n表示第n个时隙；
步骤B，各无人机根据所述单比特信息在每个迭代时隙变更运动步长和方向，变换后的运动步长包括随机扰动步长加修正因子；
步骤C，各无人机根据变更后的运动步长计算下一时刻位置，根据计算出的下一时刻位置进行位置移动，返回步骤S1，接收来自源端发射的训练序列，并传输至目的端；
以
Figure PCTCN2015096736-appb-000023
表示所述下一时刻位置，以δi(n)所述随机扰动步长，ξi(n)表示修正因子，则：
Figure PCTCN2015096736-appb-000024
步骤D，目的端计算最大比合并后信号的信噪比强度，根据计算出的信噪比强度的结果与已知的最佳接收信号的信噪比强度相比，并且更新内存中的最 佳接收信号信噪比强度，然后目的端广播反馈单比特信息给所有无人机，所述单比特信息包括接收信号性能是否提高的信息；所述单比特信息以1表示接收信号性能提高，以0表示接收信号性能未提高。
步骤E，各无人机根据反馈的单比特信息进行计算并变换运动步长和方向，更新已知位置并存储，最终确定最佳已知位置，以该最佳已知位置作为最佳中继通信位置。
进一步地，所述步骤E具体包括：
步骤E1，各无人机对所述单比特信息进行判断；
步骤E2，在判断为接收信号性能提高时，累积正反馈计数器加1，修正因子清零和连续负反馈计数器清零，并判断累积正反馈计数器是否达到预设的累积正反馈阈值；
步骤E3，若判断步骤E2中的累积正反馈计数器达到预设的累积正反馈阈值，则累积正反馈计数器清零，并且增大运动步长和增大累积正反馈阈值并返回步骤C；
步骤E4，若判断步骤E2中的累积正反馈计数器未达到预设的累积正反馈阈值，则返回步骤C；
步骤E5，在判断为接收信号性能未提高时，无人机返回上一时隙的位置，同时连续负反馈计数器加1，修正因子修改为上一时隙的运动步长的相反数，并判断连续负反馈计数器是否达到预设的连续负反馈阈值；
步骤E6，若判断步骤E5中的连续负反馈计数器达到预设的连续负反馈阈值，则累积正反馈计数器和连续负反馈计数器清零，并且减小运动步长和减小连续负反馈计数器阈值并返回步骤C；
步骤E7，若判断步骤E5中的连续负反馈计数器未达到预设的连续负反馈阈值，则返回步骤C。
下面进行详细的阐述：
1)第i个无人机在内存中记录其最佳已知位置θi(n)，并使用陀螺仪使无人 机保持固定的运动轨迹，即让无人机调整其偏向角，进行圆形运动，每个迭代时隙增加一个随机扰动δi(n)＝±δ0。同时引入了修正因子ξi(n)、累积正反馈计数器CP和连续负反馈计数器CN及阈值修正机制，δ0为本算法的变扰动步长，n表示时隙，i表示第i个无人机。
2)第i个无人机计算它的下一时刻位置：
Figure PCTCN2015096736-appb-000025
3)目的端的接收机测量最大比合并后信号的信噪比强度SNRMRC(n)，而已知的最佳最大比合并后信号的信噪比强度为SNRMRC_best(n)，然后更新内存中的最佳接收信号信噪比强度，更新规则为SNRMRC_best(n+1)＝max(SNRMRC_best(n)，SNRMRC(n))。随后接收机反馈单比特的信息给所有无人机，以此表明接收信号性能否提高。
4)第i个无人机根据反馈回来的单比特信息，更新自己的最佳已知位置θi(n)，更新规则如下：
if SNRMRC(n)＞SNRMRC_best(n)
   θi(n+1)＝θi(n)+δi(n)+ξi(n)；
   ξi(n+1)＝0；CN＝0；
   CP＝CP+1；
   if CP≥CT1
      CP＝0；δ0＝δ0·RI；
      CT1＝CT1+ΔT1；
   end
else
   θi(n+1)＝θi(n)；ξi(n+1)＝-δi(n)；
   CN＝CN+1；
   if CN≥CT2
      CN＝0；δ0＝δ0·RD；
      CP＝0；CT2＝CT2-ΔT2；
   end
end
上述式子中，CT1表示累积正反馈阈值，CT2表示连续负反馈阈值，RI是步长放大因子，RD是步长缩小因子，ΔT1是累积正反馈阈值增大因子，ΔT2是连续负反馈阈值减小因子。
接下来，通过具体的仿真实验对本发明进行进一步的解释：
多无人机中继最佳通信位置仿真如下：
初始步长：
Figure PCTCN2015096736-appb-000026
CT1＝3，CT2＝7，ΔT1＝0.3，ΔT2＝0.3，RI＝1.1，RD＝0.75；
(1)以信噪比为基准表示通信性能的好坏，也就是公式(4)和(5)
源的位置坐标：(xs，ys，zs)＝(0，-700，1)
目的端的位置坐标：(xd，yd，zd)＝(0，800，1)
无人机1，无人机2，无人机3的位置坐标：(r1，θ1(n)，z)＝(500，θ1(n)，30)，(r2，θ2(n)，z)＝(300，θ2(n)，30)，(r3，θ3(n)，z)＝(100，θ3(n)，30)，无人机-MRC表示进行最大比合并。
各无人机初始位置
Figure PCTCN2015096736-appb-000027
图4横轴表示θi(n)，纵轴表示与θi(n)相对应的该中继位置的端到端信噪比γ；
图5横轴表示多无人机搜寻最佳位置过程中花费的时隙数，纵轴表示端到端信噪比γ，如无人机-MRC可以看到在搜寻到第80个时隙时就找到了8dB的位置，在第160个时隙找到了最佳的中继通信位置，也就是图4中的极大值点和图6中的无人机对应的位置。图6横轴表示多无人机搜寻最佳位置过程中花费的时隙数，纵轴表示在该时隙时对应的各无人机的位置。
(2)以误码率为基准表示通信性能的好坏
源的位置坐标：(xs，ys，zs)＝(0，-700，1)
目的端的位置坐标：(xd，yd，zd)＝(0，800，1)
无人机1，无人机2，无人机3的位置坐标：(r1，θ1(n)，z)＝(500，θ1(n)，30)，(r2，θ2(n)，z)＝(300，θ2(n)，30)，(r3，θ3(n)，z)＝(100，θ3(n)，30)，无人机-MRC表示进行最大比合并。
CT1＝2，CT2＝9，ΔT1＝0.3，ΔT2＝0.3，RI＝1.8，RD＝0.78；
图7横轴表示θi(n)，纵轴表示与θi(n)相对应的该中继位置的端到端误码率；
图8横轴表示多无人机搜寻最佳位置过程中花费的时隙数，纵轴表示端到端误码率，如无人机-MRC在搜寻到第160个时隙时算法基本收敛结束，也就是找到了图7中的极小值点。
通过本发明提供的算法对于初始小步长扰动的收敛效果十分有利，即在算法收敛前期和后期都能加速收敛到最佳中继通信位置。
由算法的步骤可知，由于引入了累积正反馈计数器CP，当其累积到设定的累积正反馈阈值CT1时，便会增大扰动运动步长δ0，增大的倍数为RI倍，这样会使得算法在收敛前期的收敛速度得到提高。本发明在循环搜寻过程中慢慢地接近最佳中继位置，最后找到最佳中继位置，即接收信号强度最高的位置即为最佳中继位置。
新算法中，连续负反馈计数器CN的连续负反馈阈值CT2在每减小一次扰动运动步长δ0时都会减小一个固定值ΔT2，这样会使得算法在收敛后期的收敛速度得到提高。
该算法对于任意大小的初始扰动运动步长值都是适用的。
本发明属于无线通信技术领域，可以被应用来搜寻多中继最佳通信位置，提高中继通信的性能。本方法适用于增强多轨道运动的中继。潜在的应用领域有：临时通信系统的搭建、灾害现场的通信连接等。
以上所述仅为本发明的较佳实施例而已，并不用以限制本发明，凡在本发明的精神和原则之内所作的任何修改、等同替换和改进等，均应包含在本发明的保护范围之内。

Claims (10)

  1. 一种多移动中继最佳通信位置的搜寻方法，其特征在于，所述搜寻方法的步骤包括：
    步骤A，各移动中继在固定轨道的任意位置上，接收来自源端发送的训练序列，并传输至目的端；
    步骤B，所述目的端接收来自各移动中继的独立衰落信号并进行最大比合并，然后在每一时隙根据合并结果生成单比特信息广播反馈至所有的移动中继；所述独立衰落信号为所述训练序列经过衰落后到达目的端的信号；
    步骤C，各移动中继记录当前位置信息并根据所述单比特信息进行计算，根据计算结果进行位置移动，并返回步骤A，最终确定最佳中继通信位置
  2. 如权利要求1所述的搜寻方法，其特征在于，步骤A中，进行最佳中继通信位置搜寻前，将各移动中继放在不同轨道上来初始其位置信息，接收来自源端发射的训练序列，并传输至目的端；各移动中继运行的轨道之间没有交集，并通过陀螺仪保持移动中继在各自轨道上运行。
  3. 如权利要求1所述的搜寻方法，其特征在于，步骤B中，以
    Figure PCTCN2015096736-appb-100001
    表示目的端接收来自k个移动中继的k路独立衰落信号，经最大比合并后输出合并信号，以yD表示所述合并信号，则：
    Figure PCTCN2015096736-appb-100002
    其中，i表示第i个移动中继，
    Figure PCTCN2015096736-appb-100003
    为第i条支路的加权系数，其中Ai为第i条支路的信号幅度，σi 2为第i条支路噪声的平均功率，0≤i≤k。
  4. 如权利要求1所述的搜寻方法，其特征在于，所述步骤C中，各移动中继使用陀螺仪保持固定的运动轨迹和进行位置的移动，根据所述单比特信息进行计算同时引入修正因子、累积正反馈计数器、连续负反馈计数器和阈值修正机制，然后各移动中继根据计算结果变换运动步长和方向进行位置移动，并 返回步骤A。
  5. 如权利要求4所述的搜寻方法，其特征在于，所述步骤C具体包括：
    步骤C1，各移动中继记录其当前位置，以当前位置为初步最佳位置，所述初步最佳位置用θi(n)表示，i表示第i个移动中继，n表示第n个时隙；
    步骤C2，各移动中继根据所述单比特信息在每个迭代时隙变更运动步长，变换后的运动步长包括随机扰动步长加修正因子；
    步骤C3，各移动中继根据变更后的运动步长计算下一时刻位置，各移动中继根据所述下一时刻位置进行位置移动，返回步骤A，接收来自源端发射的训练序列，并传输至目的端；
    以
    Figure PCTCN2015096736-appb-100004
    表示所述下一时刻位置，以δi(n)所述随机扰动步长，ξi(n)表示修正因子，则：
    Figure PCTCN2015096736-appb-100005
    步骤C4，目的端计算最大比合并后信号的信噪比强度，根据计算出的信噪比强度的结果与已知的最佳接收信号的信噪比强度相比，并且更新内存中的最佳接收信号信噪比强度，然后目的端广播反馈单比特信息给所有移动中继，所述单比特信息包括接收信号性能是否提高的信息；
    步骤C5，各移动中继根据反馈的单比特信息进行计算并变换运动步长和方向，更新已知位置并存储，最终确定最佳已知位置，以该最佳已知位置作为最佳中继通信位置。
  6. 如权利要求5所述的搜寻方法，其特征在于，所述步骤C5具体包括：
    步骤C51，各移动中继对所述单比特信息进行判断；
    步骤C52，在判断为接收信号性能提高时，累积正反馈计数器加1，修正因子清零和连续负反馈计数器清零，并判断累积正反馈计数器是否达到预设的累积正反馈阈值；
    步骤C53，若判断步骤C52中的累积正反馈计数器达到预设的累积正反馈阈值，则累积正反馈计数器清零，并且增大运动步长和增大累积正反馈阈值并返回步骤C3；
    步骤C54，若判断步骤C52中的累积正反馈计数器未达到预设的累积正反馈阈值，则返回步骤C3；
    步骤C55，在判断为接收信号性能未提高时，移动中继返回上一时隙的位置，同时连续负反馈计数器加1，修正因子修改为上一时隙的运动步长的相反数，并判断连续负反馈计数器是否达到预设的连续负反馈阈值；
    步骤C56，若判断步骤C55中的连续负反馈计数器达到预设的连续负反馈阈值，则累积正反馈计数器和连续负反馈计数器清零，并且减小运动步长和减小连续负反馈计数器阈值并返回步骤C3；
    步骤C57，若判断步骤C55中的连续负反馈计数器未达到预设的连续负反馈阈值，则返回步骤C3。
  7. 一种多移动中继最佳通信位置的搜寻系统，其特征在于，所述搜寻系统包括源端、若干移动中继和目的端；
    所述源端，用于发送训练序列至所述中继；
    所述移动中继，用于将接收到的训练序列传输至所述目的端进行计算；所述训练序列在传输过程中经衰落后以独立衰落信号的形式被所述目的端接收；
    所述目的端，用于根据接收到的独立衰落信号进行最大比合并，然后在每一时隙根据合并结果生成单比特信息反馈至所有移动中继；所述移动中继记录位置信息并根据所述单比特信息进行计算，根据计算结果进行位置移动，并实时将所述源端发送的序列信息传输至所述目的端进行计算，最终确认最佳中继通信位置。
  8. 如权利要求7所述的搜寻系统，其特征在于，进行最佳中继通信位置搜寻前，将各移动中继放在不同轨道上来初始其位置信息，接收来自源端发射的训练序列，并传输至目的端；各移动中继运行的轨道之间没有交集，并通过陀螺仪保持移动中继在各自轨道上运行。
  9. 如权利要求7所述的搜寻系统，其特征在于，以
    Figure PCTCN2015096736-appb-100006
    表示目的端接收来自k个移动中继的k路独立衰落信号，经最大比合并后输出合并信号， 以yD表示所述合并信号，则：
    Figure PCTCN2015096736-appb-100007
    其中，i表示第i个移动中继，
    Figure PCTCN2015096736-appb-100008
    为第i条支路的加权系数，其中Ai为第i条支路的信号幅度，σi 2为第i条支路噪声的平均功率，0≤i≤k。
  10. 如权利要求7所述的搜寻系统，其特征在于，各移动中继使用陀螺仪保持固定的运动轨迹和进行位置的移动，根据所述单比特信息进行计算同时引入修正因子、累积正反馈计数器、连续负反馈计数器和阈值修正机制，然后各移动中继根据计算结果变换运动步长和方向进行位置移动，并实时接收来自源端发射的训练序列，并传输至目的端。
PCT/CN2015/096736 2015-12-08 2015-12-08 一种多移动中继最佳通信位置的搜寻方法及搜寻系统 WO2017096539A1 (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/CN2015/096736 WO2017096539A1 (zh) 2015-12-08 2015-12-08 一种多移动中继最佳通信位置的搜寻方法及搜寻系统

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2015/096736 WO2017096539A1 (zh) 2015-12-08 2015-12-08 一种多移动中继最佳通信位置的搜寻方法及搜寻系统

Publications (1)

Publication Number Publication Date
WO2017096539A1 true WO2017096539A1 (zh) 2017-06-15

Family

ID=59012456

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2015/096736 WO2017096539A1 (zh) 2015-12-08 2015-12-08 一种多移动中继最佳通信位置的搜寻方法及搜寻系统

Country Status (1)

Country Link
WO (1) WO2017096539A1 (zh)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110324877A (zh) * 2019-04-22 2019-10-11 北京邮电大学 基于伺服骨干网与Vikor多标准决策的中继机器人路由方法
CN112954672A (zh) * 2021-02-09 2021-06-11 大连理工大学 一种针对可飞行监听者的无人机中继隐蔽通信方法
CN115051744A (zh) * 2022-04-26 2022-09-13 北京理工大学 一种基于轨迹和功率联合优化的无人机辅助星地通信方法

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101646178A (zh) * 2009-08-25 2010-02-10 华为技术有限公司 一种确定中继站位置的方法及装置
CN103841572A (zh) * 2012-11-22 2014-06-04 深圳市云通时代科技开发有限公司 获取天线的调整参数的方法、装置及系统
CN104333147A (zh) * 2014-10-31 2015-02-04 北京智谷睿拓技术服务有限公司 无线能量传输方法和移动中继设备
WO2015148262A1 (en) * 2014-03-25 2015-10-01 Amazon Technologies, Inc. Sense and avoid for automated mobile vehicles
CN105554842A (zh) * 2015-12-08 2016-05-04 深圳大学 一种多移动中继最佳通信位置的搜寻方法及搜寻系统

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101646178A (zh) * 2009-08-25 2010-02-10 华为技术有限公司 一种确定中继站位置的方法及装置
CN103841572A (zh) * 2012-11-22 2014-06-04 深圳市云通时代科技开发有限公司 获取天线的调整参数的方法、装置及系统
WO2015148262A1 (en) * 2014-03-25 2015-10-01 Amazon Technologies, Inc. Sense and avoid for automated mobile vehicles
CN104333147A (zh) * 2014-10-31 2015-02-04 北京智谷睿拓技术服务有限公司 无线能量传输方法和移动中继设备
CN105554842A (zh) * 2015-12-08 2016-05-04 深圳大学 一种多移动中继最佳通信位置的搜寻方法及搜寻系统

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
CHAMSEDDINE, A. ET AL.: "Optimal Position Seeking for Unmanned Aerial Vehicle Communication Relay Using Only Signal Strength and Angle of Arrival", 53RD IEEE CONFERENCE ON DECISION AND CONTROL, 15 December 2014 (2014-12-15), pages 976 - 981, XP032734087 *
CHOI, D.H. ET AL.: "Low-complexity Maneuvering Control of a UAV-based Relay without Location Information of Mobile Ground Nodes", 2014 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 23 June 2014 (2014-06-23), pages 1 - 6, XP032649904, ISSN: 1530-1346 *
LIN, MIN ET AL.: "Optimal Design and Performance Analysis for Two-Hop Wireless Links with UAV Relaying", SYSTEMS ENGINEERING AND ELECTRONICS, vol. 37, no. 6, 30 June 2015 (2015-06-30), pages 1391 - 1398 *

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110324877A (zh) * 2019-04-22 2019-10-11 北京邮电大学 基于伺服骨干网与Vikor多标准决策的中继机器人路由方法
CN112954672A (zh) * 2021-02-09 2021-06-11 大连理工大学 一种针对可飞行监听者的无人机中继隐蔽通信方法
CN112954672B (zh) * 2021-02-09 2022-09-23 大连理工大学 一种针对可飞行监听者的无人机中继隐蔽通信方法
CN115051744A (zh) * 2022-04-26 2022-09-13 北京理工大学 一种基于轨迹和功率联合优化的无人机辅助星地通信方法
CN115051744B (zh) * 2022-04-26 2023-08-08 北京理工大学 一种基于轨迹和功率联合优化的无人机辅助星地通信方法

Similar Documents

Publication Publication Date Title
CN108337034B (zh) 全双工无人机移动中继系统及其路径优化方法
CN107017940B (zh) 无人机中继广播通信系统航迹优化方法
CN107094044B (zh) 一种空时分组编码的无人机中继通信航迹规划方法
CN105491637B (zh) 基于固定步长的移动中继最佳中继位置搜寻方法及系统
CN105554842B (zh) 一种多移动中继最佳通信位置的搜寻方法及搜寻系统
CN109640257B (zh) 一种基于无人机的iot网络安全传输方法
CN109991998B (zh) 一种基于接收信号强度的无人机中继航迹优化方法
WO2020248443A1 (zh) 一种基于二维相控天线阵列的快速精确波束跟踪方法
CN108668257B (zh) 一种分布式无人机邮差中继轨迹优化方法
CN111479239A (zh) 一种多天线无人机数据采集系统的传感器发射能耗优化方法
CN105553537A (zh) 基于累加正反馈变步长的最佳中继位置搜寻方法与系统
WO2017096539A1 (zh) 一种多移动中继最佳通信位置的搜寻方法及搜寻系统
CN105356930B (zh) 基于定时机制的全局最优中继位置搜寻方法及系统
La Scalea et al. Opportunities for autonomous UAV in harsh environments
Liang et al. Age of information based scheduling for UAV aided emergency communication networks
CN105554841B (zh) 一种基于步长阈值机制的最佳中继位置搜寻方法及系统
Li et al. Proactive eavesdropping via jamming for trajectory tracking of UAVs
Chen et al. A QoS-aware underwater optimization framework for inter-vehicle communication using acoustic directional transducers
He et al. Intelligent terahertz medium access control (MAC) for highly dynamic airborne networks
CN102035588A (zh) 基于角度信息的发射多播赋形方法及系统
Nijsure et al. WSN-UAV monitoring system with collaborative beamforming and ADS-B based multilateration
CN105554840A (zh) 基于反向补偿机制的最佳中继位置的搜寻方法及系统
WO2017096542A1 (zh) 基于累加正反馈变步长的最佳中继位置搜寻方法与系统
CN114630297B (zh) 一种携带智能反射面的无人机中继的位置优化方法
He et al. Reliable auxiliary communication of UAV via relay cache optimization

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 15910014

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 31/10/2018)

122 Ep: pct application non-entry in european phase

Ref document number: 15910014

Country of ref document: EP

Kind code of ref document: A1