WO2015168860A1 - 多维载波侦听的方法、装置及接收端设备 - Google Patents
多维载波侦听的方法、装置及接收端设备 Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- the embodiments of the present invention relate to communication technologies, and in particular, to a method, an apparatus, and a receiving end device for multi-dimensional carrier sensing. Background technique
- CSMA Carrier Sense Multiple Access
- collision Avoidance Collision Avoidance
- IEEE Institute of Electrical and Electronics Engineers
- the CA mechanism avoids collisions on the channel when multiple network devices need to transmit data.
- the basis of CSMA/CA is carrier sense, which is also called “listen after listening", that is, the sender device listens to the channel before sending data.
- a multi-dimensional carrier sensing method was proposed in the 2011 paper "Random Access Heterogeneous MIMO Networks", which allows multiple transceiver pairs to communicate simultaneously on the same channel.
- the receiving end device in the transmitting and receiving center processes the received signal through one or more direction vectors, first cancels the interference of the unrelated network device, and then performs the signal sent by the transmitting end device in the transmitting and receiving pair. Listen, and then send the signal according to the vector.
- the above vector is randomly selected, all the received signals may be processed very small, even 0, while the interference is eliminated, causing the device to fail to transmit and receive signals normally, which also reduces the signal transmission rate, thereby reducing the cell. Throughput. Summary of the invention
- the embodiment of the invention provides a method, a device and a receiving end device for multi-dimensional carrier sensing, which solves the problem that the processing of all signals received in the prior art is small, even 0, which causes the device to fail to send and receive signals normally. It also reduces the signal transmission rate, which in turn reduces the problem of cell throughput.
- an embodiment of the present invention provides a method for multi-dimensional carrier sensing, including: a receiving end device receiving signals sent by two or more network devices, where the two or more network devices include a transmitting end device and at least one neighboring device. ;
- the receiving end device maximizes the letter between the sending end device and the receiving end device
- the signal to noise ratio of the channel obtains an optimal signal correction vector and processes the signal through the optimal signal correction vector to cancel signal interference of the at least one neighboring device.
- the receiving end device obtains an optimal by maximizing a signal-to-noise ratio of a channel between the transmitting end device and the receiving end device a signal correction vector, and processing the signal by the optimal signal correction vector, further comprising:
- the receiving end device calculates a zero space matrix orthogonal to a channel vector matrix of the neighboring device, where the zero space matrix constitutes an orthogonal subspace, and the channel vector matrix is composed of one or more of the adjacent devices Forming a channel vector of a channel with the receiving device, respectively;
- the receiving end device obtains an optimal signal correction vector by maximizing a signal to noise ratio of a channel between the transmitting end device and the receiving end device, including:
- the receiving end device calculates a signal correction vector that is obtained by vertically acquiring a channel vector of one or more channels between the transmitting end device and the receiving end device, respectively, onto the orthogonal subspace; Determining, according to the number of antennas of the transmitting end device, the number of antennas of the receiving end device, and the total number of data streams of the at least one neighboring device, the number of the optimal signal correction vectors;
- the receiving end device selects, from one or more of the signal correction vectors, a number equal to the number of the optimal signal correction vectors, and causes a channel between the transmitting end device and the receiving end device
- the vector with the largest noise ratio is used as the optimal signal correction vector.
- the receiving end device is configured to maximize the sending end device and the receiving end device Between the signal-to-noise ratio of the channel, obtaining an optimal signal correction vector, and processing the signal by the optimal signal correction vector, further comprising:
- the receiving end device sends data stream update information to the sending end device, so that the sending end device adjusts the number of streams of the sending data according to the data stream update information.
- the receiving end device is configured to maximize the sending A signal to noise ratio of a channel between the end device and the receiving device, obtaining an optimal signal correction vector, and processing the signal by using the optimal signal correction vector, further comprising:
- the receiving device pre-codes the signal according to the optimal signal correction vector, and pre- The encoded signal is sent to the transmitting device.
- an embodiment of the present invention provides a multi-dimensional carrier sensing apparatus, including:
- a receiving module configured to receive signals sent by two or more devices, where the two or more devices include a transmitting device and at least one adjacent device;
- a signal processing module configured to obtain an optimal signal correction vector by maximizing a signal to noise ratio of a channel between the transmitting end device and the receiving end device, and perform the signal on the signal by using the optimal signal correction vector Processing to cancel signal interference of the at least one neighboring device.
- the method further includes: an interference cancellation module, configured to calculate a zero space matrix that is orthogonal to a channel vector matrix of the neighboring device, where the zero The spatial matrix constitutes an orthogonal subspace, and the channel vector matrix is composed of a channel vector of a channel between the one or more adjacent devices and the multi-dimensional carrier sensing device; the signal processing module is specifically used for Calculating a signal correction vector for vertically acquiring a channel vector of one or more channels between the transmitting device and the multi-dimensional carrier sensing device, respectively, onto the orthogonal subspace; according to an antenna of the transmitting device Counting the number of antennas of the multi-dimensional carrier sensing device and the total number of data streams of the at least one neighboring device to determine the number of the optimal signal correction vectors; selecting from one or more of the signal correction vectors Equal to the number of the optimal signal correction vectors, and maximizing the signal-to-noise ratio of the channel between the transmitting device and the receiving
- an interference cancellation module configured to calculate a zero space matrix that is orthogon
- the method further includes:
- an information sending module configured to send data stream update information to the sending end device, so that the sending end device adjusts the number of streams of the sending data according to the data stream update information.
- the first possible implementation of the first to the second aspect, the third possible implementation of the second aspect, further includes:
- a precoding module configured to precode the signal according to the optimal signal correction vector, and send the precoded signal to the transmitting device.
- an embodiment of the present invention provides a receiving end device, including:
- a receiver configured to receive signals sent by two or more network devices, where the two or more network devices include a sender device and at least one neighbor device;
- a processor configured to maximize a channel between the source device and the receiver device The signal to noise ratio, the optimal signal correction vector is obtained, and the signal is processed by the optimal signal correction vector to eliminate signal interference of the at least one neighboring device.
- the method further includes: a calculator, configured to calculate, obtain a zero space matrix orthogonal to a channel vector matrix of the neighboring device, where the zero space The matrix constitutes an orthogonal subspace, and the channel vector matrix is composed of channel vectors of channels between the one or more adjacent devices and the receiving device respectively;
- the calculator is further configured to calculate a signal for directly acquiring a channel vector of one or more channels between the transmitting end device and the receiving end device and vertically projecting onto the orthogonal subspace, to perform the processing Specifically, determining, according to the number of antennas of the sending end device, the number of antennas of the receiving end device, and the total number of data streams of the at least one neighboring device, determining the number of the optimal signal correction vectors; Or selecting, among the plurality of signal correction vectors, a vector equal to the number of the optimal signal correction vectors, and maximizing a signal-to-noise ratio of a channel between the transmitting end device and the receiving end device as a vector The optimal signal correction vector.
- the method further includes:
- a transmitter configured to send data stream update information to the sending end device, so that the sending end device adjusts the number of streams of the sending data according to the data stream update information.
- any one of the first to the second possible implementation manners of the third aspect in a third possible implementation manner of the third aspect, is further configured to The optimal signal correction vector precodes the signal;
- the transmitter is further configured to send the precoded signal to the sending end device.
- the receiving device calculates the obtained optimal signal correction vector, which can eliminate the interference of the adjacent device, and can also be used between the transmitting device and the receiving device.
- the signal-to-noise ratio of the channel is the largest, and the receiving device can listen to the channel of the transmitting device to the receiving device by using carrier sensing in the IEEE802.il standard, so that the receiving device can use the remaining degrees of freedom for communication.
- all the signals received by the prior art are processed to be small, even 0, which causes the device to fail to transmit and receive signals normally, and also reduces the signal transmission rate, thereby reducing the problem of cell throughput.
- 1 is a vector diagram 1 of a STA received signal
- 2 is a vector diagram 2 of a STA received signal
- Embodiment 3 is a flowchart of Embodiment 1 of a method for multi-dimensional carrier sensing according to the present invention
- Embodiment 4 is a flowchart of Embodiment 2 of a method for multi-carrier carrier sensing according to the present invention
- FIG. 5 is a schematic structural diagram of Embodiment 1 of a multi-dimensional carrier sense device according to the present invention.
- Embodiment 2 of a multi-dimensional carrier sense device according to the present invention
- Embodiment 7 is a schematic structural diagram of Embodiment 1 of a receiving end device according to the present invention.
- FIG. 8 is a schematic structural diagram of Embodiment 2 of a receiving end device according to the present invention. detailed description
- the multi-dimensional carrier sensing method proposed in the paper "Random Access Heterogeneous MIMO Networks” allows multiple transceiver pairs to communicate simultaneously on the same channel.
- the API and the STA are one transceiver pair.
- the STA can hear the AP2, and the signal sent by the AP2 interferes with the STA. Since the STA has two antennas corresponding to two data streams, one of which is used to eliminate the interference of the AP2, the STA competes for the second degree of freedom, that is, uses another spare data stream. If the signal sent by AP2 is p, the API sends the number y to:
- FIG. 1 is a schematic diagram 1 of a vector of a STA received signal.
- the signal obtained by the STA multiplying the received signal y by the vector w is:
- the carrier sense method in the IEEE 802.il standard listens to the channel of the API, so that the STA can communicate using the second degree of freedom.
- the STA has 3 antennas
- the API has 1 antenna
- AP2 sends 1 stream.
- the API and the STA are one transceiver pair.
- the STA can hear the signal sent by AP2 and AP2 to interfere with the STA. Since the STA has three antennas corresponding to three data streams, one of which is used to eliminate the interference of the AP2, since the API has only one antenna, the STA interacts with the API through one data stream, so the STA competes for the second degree of freedom. If the signal sent by AP2 is p, the signal sent by the API is r.
- the actual received signal y of the STA is
- h ttl is the channel vector of the channel between ⁇ 2 and STA
- h tt2 is the channel vector of the channel between the API and the STA.
- FIG. 2 is a vector diagram 2 of a STA receiving signal.
- the signal obtained by the STA multiplying the received signal y by the vector w is:
- the processed signal only includes the signal from the API, eliminating the signal of the AP2, and the STA is used again.
- the carrier sense method in the IEEE 802.il standard listens to the channel of the API, so that the STA can communicate using the second degree of freedom.
- the angle 0 will change with w, for example from 45 degrees to 90 degrees, so that co will also change, and the minimum may even be zero. Therefore, the signal processed by the STA is uncertain, and the signal processing of the API may be small or even zero, which may result in failure to properly transmit and receive signals, and also reduce the signal transmission rate, thereby reducing the cell throughput.
- the receiving end device in the present invention may be the STA in the above prior art example, or may be an AP. As long as it is a device that receives data, the received signal is processed to eliminate interference of the neighboring device.
- FIG. 3 is a flowchart of Embodiment 1 of a method for multi-layer carrier sensing according to the present invention. As shown in FIG. 3, the method in this embodiment may include:
- Step 101 The receiving device receives a signal sent by two or more network devices.
- the receiving end device in this embodiment receives signals sent by two or more network devices, where two or more network devices include a transmitting end device and at least one neighboring device, that is, the signal received by the receiving end device may include the sending end device.
- the signal sent may also include signals sent by other neighboring devices.
- the sender device and the receiver device are one transceiver pair.
- the neighbor device is another network device adjacent to the receiver device. The neighbor device can share the channel with the transceiver. Therefore, the signal sent by the neighbor device is used by the receiver device. It is an interference signal, which is not conducive to the listening of the channel by the receiving device.
- Step 102 The receiving end device obtains an optimal signal correction vector by maximizing a signal to noise ratio of a channel between the transmitting end device and the receiving end device, and corrects a vector pair by using the optimal signal The signal is processed.
- the receiving end device processes the received signal through an optimal signal correction vector to eliminate signal interference of the at least one neighboring device.
- the optimal signal correction vector is similar to the vector w in the prior art, and the receiving device can orthogonalize the interference signal through the vector w, and the two are multiplied to eliminate signal interference of adjacent devices.
- the optimal signal correction vector also satisfies the requirement of maximizing the signal-to-noise ratio of the channel between the transmitting device and the receiving device.
- the optimal signal correction vector is selected from the three vectors.
- the optimal signal correction vector can make the signal-to-noise ratio of the channel between the transmitting device and the receiving device 1 W ' h " 2 ' f
- the maximum signal-to-noise ratio can be converted to m ax ( COS , 0 is the angle between w and h tt2 .
- ⁇ is selected as the optimal signal correction vector, which is due to ⁇ It is a vertical projection of 2 in the two-dimensional subspace, which satisfies the condition of m aX ( COS .
- the receiving device multiplies the received signal by Wl to eliminate the interference of the adjacent device, and can realize the device of the transmitting end device and the receiving end device.
- the signal to noise ratio of the channel between the channels is maximized.
- the receiving end device calculates the obtained optimal signal correction vector, and processes the received signal by using the optimal signal correction vector, thereby achieving elimination of interference between adjacent devices and between the transmitting device and the receiving device.
- the signal-to-noise ratio of the channel is maximized, and the channel of the transmitting device to the receiving device is monitored by carrier sensing in the IEEE802.il standard, and the receiving device can use the remaining degrees of freedom to communicate, thereby solving the existing In the technology, all the received signals are processed very small, even 0, which causes the device to fail to send and receive signals normally, which also reduces the signal transmission rate, thereby reducing the problem of cell throughput.
- the method further includes: the receiving end device calculates a zero space matrix that is orthogonal to a channel vector matrix of the neighboring device, where the zero space matrix constitutes an orthogonal sub- Space, the channel vector matrix is composed of channel vectors of channels between the one or more adjacent devices and the receiving device respectively;
- the specific implementation method of step 102 may be: the receiving end device calculates that the channel vectors of one or more channels between the sending end device and the receiving end device are vertically projected onto the orthogonal subspace respectively. a signal correction vector; the receiving device determines the optimal signal correction vector according to the number of antennas of the transmitting device, the number of antennas of the receiving device, and the total number of data streams of the at least one neighboring device; The receiving device selects from the one or more signal correction vectors that the number of the optimal signal correction vectors is equal, and the device between the transmitting end device and the receiving end device The vector with the signal to noise ratio of the channel is maximized as the optimal signal correction vector.
- the orthogonal subspace may be, for example, a two-dimensional subspace as shown in FIG.
- the channel quality of one or more channels between the transmitting device and the receiving device is vertically mapped to the orthogonal subspace, respectively, to obtain one or more signal corrections.
- these signal correction vectors are W corresponding to each channel to satisfy the maximum signal-to-noise ratio.
- the channel vector h tt2 is vertically projected onto the two-dimensional subspace, corresponding to Wl , and the angle between ⁇ and 2 satisfies m ax ( COS .
- the maximum degree of freedom that the receiving device can use is determined (ie, optimal) Number of signal correction vectors N ) :
- N min(N AP N STA - N AP2 )
- the number of antennas of the transmitting device is N ⁇ , and the number of antennas of the receiving device is! ⁇ ,
- the total number of streams of adjacent devices is ⁇ 2 .
- the receiving device selects the optimal signal correction vector from the plurality of ws obtained by the previous calculation, that is, although each w can maximize the signal-to-noise ratio of the corresponding channel, considering the maximum degree of freedom available to the receiving device , especially when: N ⁇ - N ⁇ ), the number of signal correction vectors calculated above is greater than the number of data streams that can be used by the receiving device, so it is necessary to select the optimal one among the signal correction vectors.
- the criterion selected at this time may be to select the largest corresponding signal correction vector, that is, the optimal signal correction vector. This is because
- Embodiment 2 is a flowchart of Embodiment 2 of a method for multi-layer carrier sensing according to the present invention. As shown in FIG. 4, the method in this embodiment may include:
- Step 201 The receiving end device receives a signal sent by two or more network devices.
- the process in which the receiving end device receives the signals sent by the two or more network devices is similar to the step 101 in the foregoing method embodiment, and details are not described herein again.
- Step 202 The receiving end device obtains an optimal signal correction vector by maximizing a signal to noise ratio of a channel between the transmitting end device and the receiving end device, and corrects a vector pair by using the optimal signal The signal is processed;
- the receiving end device obtains an optimal signal correction vector by maximizing a signal to noise ratio of a channel between the transmitting end device and the receiving end device, and corrects a vector pair by using the optimal signal.
- the process of processing the signal is similar to the step 102 of the foregoing method embodiment, and details are not described herein again.
- Step 203 The receiving end device sends data stream update information to the sending end device, so that the sending end device adjusts the number of streams of the sending data according to the data stream update information.
- the receiving end device may The number is notified to the sending device by the data stream update information, so that the sending device can adjust the number of streams of the sent data in time to avoid data loss.
- Step 204 The receiving end device pre-codes the signal according to the optimal signal correction vector, and sends the pre-encoded signal to the sending end device.
- the receiving device may pre-code the signal according to the optimal signal correction vector, because the optimal signal correction vector is orthogonal to the channel quality of the neighboring device and is a signal.
- the noise ratio is the largest, so the precoded signal does not interfere with the signals of the adjacent devices, and the maximum signal to noise ratio is achieved, and the signal transmission rate and the cell throughput are improved.
- Embodiment 1 It is assumed that the receiving device has three antennas for the STA, the transmitting device has one antenna for the API, and the neighboring device sends one stream for the AP2. The STA can hear the signal sent by AP2 and AP2 to interfere with the STA.
- AP2 sends the signal to p, and the API sends the signal to r, according to
- N min(N AP N STA - N AP2 )
- the STA can compete for one degree of freedom.
- Embodiment 2 It is assumed that the receiving device has three antennas for the STA, the transmitting device has two antennas for the API, and the neighboring device sends one stream for the AP2. The STA can hear the signal sent by AP2 and AP2 to interfere with the STA.
- AP2 sends the signal to p, and the API sends the signal to r, according to
- N min(N AP N STA - N AP2 )
- h ttl is the channel vector of AP2 to STA
- h tt2 is the channel vector of one antenna of the API to the STA
- h &3 is the channel vector of the other antenna of the API to the STA.
- Embodiment 3 It is assumed that the receiving device has three antennas for the STA, the transmitting device has three antennas for the API, and the neighboring device sends one stream for the AP2. The STA can hear the signal sent by AP2 and AP2 to interfere with the STA.
- AP2 sends the signal to p, and the API sends the signal to r, according to
- N min(N AP N STA - N AP2 )
- 1 ⁇ is the channel vector of AP2 to STA
- h tt2 is the API: the channel vector of the antenna to the STA
- 1 ⁇ is the channel vector of the second antenna of the API to the STA
- the STA can re-transmitting two data streams, so it will then select a channel vector from the corresponding Wl, w n W3 in h tt2, h tx3 and h tt4 correspond to the angle h ttl largest of the two angles Signal correction vector.
- the apparatus of this embodiment may include: a receiving module 11 and a signal processing module 12, where the receiving module 11 is configured to receive two Signals transmitted by more than one device, the two or more devices include a transmitting device and at least one adjacent device; and the signal processing module 12 is configured to maximize a channel between the transmitting device and the receiving device A signal to noise ratio, an optimal signal correction vector is obtained, and the signal is processed by the optimal signal correction vector to cancel signal interference of the at least one neighboring device.
- the device in this embodiment can be used to implement the technical solution of the method embodiment shown in FIG. 3, and the principle and the technical effect are similar, and details are not described herein again.
- FIG. 6 is a schematic structural diagram of Embodiment 2 of a multi-dimensional carrier sense apparatus according to the present invention.
- the apparatus of this embodiment is further included in the structure of the apparatus shown in FIG. 5, and may further include: The interference cancellation module 21, the information sending module 22, and the precoding module 23, wherein the interference cancellation module 21 is configured to calculate a zero space matrix orthogonal to a channel vector matrix of the neighboring device, where the zero space matrix is composed a channel space matrix, the channel vector matrix is composed of a channel vector of a channel between the one or more adjacent devices and the multi-dimensional carrier sensing device; the signal processing module 12 is specifically configured to calculate and obtain the transmission Channel vectors of one or more channels between the end device and the multi-dimensional carrier sensing device are respectively vertically projected onto a signal correction vector on the orthogonal subspace; according to the number of antennas of the transmitting device, the multidimensional Determining the number of the optimal signal correction vectors by the number of antennas of the carrier sensing device and the total number of data streams
- the information sending module 22 is configured to send data stream update information to the sending end device, so that the sending end device adjusts the number of streams of the sending data according to the data stream update information.
- the precoding module 23 is configured to precode the signal according to the optimal signal correction vector, and send the precoded signal to the transmitting device.
- the device in this embodiment can be used to implement the technical solution of the method embodiment shown in FIG. 3 or FIG. 4, and the implementation principle and technical effects are similar, and details are not described herein again.
- FIG. 7 is a schematic structural diagram of Embodiment 1 of a receiving end device according to the present invention.
- the apparatus in this embodiment may include: a receiver 11 and a processor 12, where the receiver 11 is configured to receive two or more networks. a signal sent by the device, the two or more network devices include a sender device and at least one neighbor device, and the processor 12 is configured to maximize signal noise of the channel between the sender device and the receiver device And obtaining an optimal signal correction vector, and processing the signal by the optimal signal correction vector to cancel signal interference of the at least one neighboring device.
- the device in this embodiment can be used to implement the technical solution of the method embodiment shown in FIG. 3, and the principle and the technical effect are similar, and details are not described herein again.
- FIG. 8 is a schematic structural diagram of Embodiment 2 of the receiving end device according to the present invention.
- the device in this embodiment is further included in the structure of the device shown in FIG. 7 , and may further include: a calculator 21 and a sending
- the calculator 22 is configured to calculate a zero space matrix that is orthogonal to a channel vector matrix of the neighboring device, where the zero space matrix constitutes an orthogonal subspace, and the channel vector matrix is composed of one or more Channel vector of the channel between the adjacent device and the receiving device a signal correction vector that is obtained by vertically acquiring a channel vector of one or more channels between the source device and the receiving device to the orthogonal subspace;
- the processor 12 is specifically configured to Determining the number of the optimal signal correction vectors by the number of antennas of the transmitting device, the number of antennas of the receiving device, and the total number of data streams of the at least one neighboring device; from one or more of the signals Selecting, in the correction vector, a number equal to the number of the optimal
- the transmitter 22 is configured to send data stream update information to the sending end device, so that the sending end device adjusts the number of streams of the sending data according to the data stream update information.
- the processor 12 is further configured to pre-code the signal according to the optimal signal correction vector; the transmitter 22 is further configured to send the pre-encoded signal to the transmitting device.
- the device in this embodiment can be used to implement the technical solution of the method embodiment shown in FIG. 3 or FIG. 4, and the implementation principle and technical effects are similar, and details are not described herein again.
- the disclosed apparatus and method may be implemented in other manners.
- the device embodiments described above are merely illustrative.
- the division of the unit is only a logical function division.
- there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not executed.
- the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be electrical, mechanical or otherwise.
- the units described as separate components may or may not be physically separated, and the components displayed as the unit may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. . Some or all of the units may be selected according to actual needs to achieve the objectives of the solution of the embodiment.
- each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
- the above integrated unit can be implemented in the form of hardware or in the form of hardware plus software functional units.
- the above-described integrated unit implemented in the form of a software functional unit can be stored in a computer readable storage medium.
- the above software functional unit is stored in a storage medium, including several fingers Some steps are taken to cause a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor to perform the methods described in various embodiments of the present invention.
- the foregoing storage medium includes: a U disk, a removable hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like, which can store program codes. .
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Abstract
本发明实施例提供一种多维载波侦听的方法、装置及接收端设备。本发明多维载波侦听的方法，包括：接收端设备接收两个以上网络设备发送的信号，所述两个以上网络设备包括发送端设备和至少一个相邻设备；所述接收端设备通过最大化所述发送端设备与所述接收端设备之间的信道的信噪比，获取最优信号矫正向量，并通过所述最优信号矫正向量对所述信号进行处理，以消除所述至少一个相邻设备的信号干扰。本发明实施例解决解决现有技术中会将接收到的全部信号处理的很小，甚至为0，导致设备无法正常收发信号，也会降低信号传输速率，进而降低小区吞吐量的问题。
Description
多维载波侦听的方法、 装置及接收端设备
技术领域
本发明实施例涉及通信技术， 尤其涉及一种多维载波侦听的方法、 装置 及接收端设备。 背景技术
电气禾口电子工禾呈师协会 ( Institute of Electrical and Electronics Engineers, 简称 IEEE ) 802.11 标准中通过载波侦听多点接入 （Carrier Sense Multiple Access, 简称： CSMA) /冲突避免（Collision Avoidance, 简称： CA)机制避 免多个网络设备需要进行数据传输时在信道上发生冲突。 CSMA/CA 的基础 是载波侦听， 又称为"先听后说"， 即发送端设备在发送数据前先侦听信道。
2011年发表的论文《随机访问异构的多输入多输出网络（Random Access Heterogeneous MIMO Networks ) 》 中提出了多维载波侦听方法， 可以让多个 收发对在同一信道上同时通信。 该方法中， 收发对中的接收端设备通过一个 或多个方向向量对接收到的信号进行处理， 先消除掉不相关的网络设备的干 扰， 再对收发对中的发送端设备发送的信号进行侦听， 并根据该向量对信号 处理后再发出。 但是如果上述向量是随机选取的， 则可能在消除干扰的同 时， 会将接收到的全部信号处理的很小， 甚至为 0， 导致设备无法正常收发 信号， 也会降低信号传输速率， 进而降低小区吞吐量。 发明内容
本发明实施例提供一种多维载波侦听的方法、 装置及接收端设备， 以解 决解决现有技术中会将接收到的全部信号处理的很小， 甚至为 0， 导致设备 无法正常收发信号， 也会降低信号传输速率， 进而降低小区吞吐量的问题。
第一方面， 本发明实施例提供一种多维载波侦听的方法， 包括： 接收端设备接收两个以上网络设备发送的信号， 所述两个以上网络设备 包括发送端设备和至少一个相邻设备；
所述接收端设备通过最大化所述发送端设备与所述接收端设备之间的信
道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正向量对所述 信号进行处理， 以消除所述至少一个相邻设备的信号干扰。
结合第一方面， 在第一方面的第一种可能的实现方式中， 所述接收端设 备通过最大化所述发送端设备与所述接收端设备之间的信道的信噪比， 获取 最优信号矫正向量， 并通过所述最优信号矫正向量对所述信号进行处理之 m , 还包括：
所述接收端设备计算获取与所述相邻设备的信道向量矩阵正交的零空间 矩阵， 所述零空间矩阵组成正交子空间， 所述信道向量矩阵由一个或多个所 述相邻设备分别与所述接收端设备之间的信道的信道向量组成；
所述接收端设备通过最大化所述发送端设备与所述接收端设备之间的信 道的信噪比， 获取最优信号矫正向量， 包括：
所述接收端设备计算获取所述发送端设备与所述接收端设备之间的一个 或多个信道的信道向量分别垂直投影到所述正交子空间上的信号矫正向量； 所述接收端设备根据所述发送端设备的天线数、 所述接受端设备的天线 数和所述至少一个相邻设备的总数据流数确定所述最优信号矫正向量的个 数；
所述接收端设备从一个或多个所述信号矫正向量中选择出与所述最优信 号矫正向量的个数相等， 且使所述发送端设备与所述接收端设备之间的信道 的信噪比最大化的向量作为所述最优信号矫正向量。
结合第一方面或第一方面的第一种可能的实现方式， 在第一方面的第二 种可能的实现方式中， 所述接收端设备通过最大化所述发送端设备与所述接 收端设备之间的信道的信噪比， 获取最优信号矫正向量， 并通过所述最优信 号矫正向量对所述信号进行处理之后， 还包括：
所述接收端设备向所述发送端设备发送数据流更新信息， 以使所述发送 端设备根据所述数据流更新信息调整发送数据的流数。
结合第一方面、 第一方面的第一种至第二种中任一种可能的实现方式， 在第一方面的第三种可能的实现方式中， 所述接收端设备通过最大化所述发 送端设备与所述接收端设备之间的信道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正向量对所述信号进行处理之后， 还包括：
所述接收端设备根据所述最优信号矫正向量对信号进行预编码， 并将预
编码后的信号发送给所述发送端设备。
第二方面， 本发明实施例提供一种多维载波侦听装置， 包括：
接收模块， 用于接收两个以上装置发送的信号， 所述两个以上装置包括 发送端装置和至少一个相邻装置；
信号处理模块， 用于通过最大化所述发送端设备与所述接收端设备之间 的信道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正向量对 所述信号进行处理， 以消除所述至少一个相邻装置的信号干扰。
结合第二方面， 在第二方面的第一种可能的实现方式中， 还包括： 干扰消除模块， 用于计算获取与所述相邻装置的信道向量矩阵正交的零 空间矩阵， 所述零空间矩阵组成正交子空间， 所述信道向量矩阵由一个或多 个所述相邻装置分别与所述多维载波侦听装置之间的信道的信道向量组成； 所述信号处理模块， 具体用于计算获取所述发送端装置与所述多维载波 侦听装置之间的一个或多个信道的信道向量分别垂直投影到所述正交子空间 上的信号矫正向量； 根据所述发送端装置的天线数、 所述多维载波侦听装置 的天线数和所述至少一个相邻装置的总数据流数确定所述最优信号矫正向量 的个数； 从一个或多个所述信号矫正向量中选择出与所述最优信号矫正向量 的个数相等， 且使所述发送端设备与所述接收端设备之间的信道的信噪比最 大化的向量作为所述最优信号矫正向量。
结合第二方面或第二方面的第一种可能的实现方式， 在第二方面的第二 种可能的实现方式中， 还包括：
信息发送模块， 用于向所述发送端装置发送数据流更新信息， 以使所述 发送端装置根据所述数据流更新信息调整发送数据的流数。
结合第二方面、 第二方面的第一种至第二种中任一种可能的实现方式， 在第二方面的第三种可能的实现方式中， 还包括：
预编码模块， 用于根据所述最优信号矫正向量对信号进行预编码， 并将 预编码后的信号发送给所述发送端装置。
第三方面， 本发明实施例提供一种接收端设备， 包括：
接收器， 用于接收两个以上网络设备发送的信号， 所述两个以上网络设 备包括发送端设备和至少一个相邻设备；
处理器， 用于通过最大化所述发送端设备与所述接收端设备之间的信道
的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正向量对所述信 号进行处理， 以消除所述至少一个相邻设备的信号干扰。
结合第三方面， 在第三方面的第一种可能的实现方式中， 还包括： 计算器， 用于计算获取与所述相邻设备的信道向量矩阵正交的零空间矩 阵， 所述零空间矩阵组成正交子空间， 所述信道向量矩阵由一个或多个所述 相邻设备分别与所述接收端设备之间的信道的信道向量组成；
所述计算器， 还用于计算获取所述发送端设备与所述接收端设备之间的 一个或多个信道的信道向量分别垂直投影到所述正交子空间上的信号矫正向 所述处理器， 具体用于根据所述发送端设备的天线数、 所述接受端设备 的天线数和所述至少一个相邻设备的总数据流数确定所述最优信号矫正向量 的个数； 从一个或多个所述信号矫正向量中选择出与所述最优信号矫正向量 的个数相等， 且使所述发送端设备与所述接收端设备之间的信道的信噪比最 大化的向量作为所述最优信号矫正向量。
结合第三方面或第三方面的第一种可能的实现方式， 在第三方面的第二 种可能的实现方式中， 还包括：
发送器， 用于向所述发送端设备发送数据流更新信息， 以使所述发送端 设备根据所述数据流更新信息调整发送数据的流数。
结合第三方面、 第三方面的第一种至第二种中任一种可能的实现方式， 在第三方面的第三种可能的实现方式中， 所述处理器， 还用于根据所述最优 信号矫正向量对信号进行预编码；
所述发送器， 还用于将预编码后的信号发送给所述发送端设备。
本发明实施例多维载波侦听的方法、 装置及接收端设备， 接收端设备计 算获取的最优信号矫正向量即可以消除相邻设备的干扰， 又可以使发送端设 备与接收端设备之间的信道的信噪比最大， 接收端设备可以使用 IEEE802.i l 标准中的载波侦听对发送端设备到接收端设备的信道进行侦听， 这样， 接收 端设备就可以利用剩余的自由度来进行通信， 解决现有技术中会将接收到的 全部信号处理的很小， 甚至为 0， 导致设备无法正常收发信号， 也会降低信 号传输速率， 进而降低小区吞吐量的问题。
附图说明 为了更清楚地说明本发明实施例或现有技术中的技术方案， 下面将对实 施例或现有技术描述中所需要使用的附图作一简单地介绍， 显而易见地， 下 面描述中的附图是本发明的一些实施例， 对于本领域普通技术人员来讲， 在 不付出创造性劳动性的前提下， 还可以根据这些附图获得其他的附图。
图 1为 STA接收信号的矢量示意图一；
图 2为 STA接收信号的矢量示意图二；
图 3为本发明多维载波侦听的方法实施例一的流程图；
图 4为本发明多维载波侦听的方法实施例二的流程图；
图 5为本发明多维载波侦听装置实施例一的结构示意图；
图 6为本发明多维载波侦听装置实施例二的结构示意图；
图 7为本发明接收端设备实施例一的结构示意图；
图 8为本发明接收端设备实施例二的结构示意图。 具体实施方式
论文 《Random Access Heterogeneous MIMO Networks》 中提出的多维载 波侦听方法可以让多个收发对在同一信道上同时通信。 以下举例说明该方法 的原理： 假设接收站点（Station, 简称： STA)有 2根天线， 接入点（Access Point, 简称： AP) 1有 1根天线， AP2发送 1个流。 API与 STA是一个收发 对， STA能够听到 AP2， AP2发出的信号对 STA造成干扰。 由于 STA有 2 根天线分别对应两个数据流， 其中一个用于消除 AP2的干扰， 因此 STA竞争 第 2个自由度， 即使用另一个空余的数据流。 如果 AP2发送的信号为 p， API 发送 号 y为：
其中， （/¾ ¾)τ (即 httl )是 AP2与 STA之间的信道的信道向量， （ h2' f (即 htt2 ) 是 API与 STA之间的信道的信道向量。
图 1为 STA接收信号的矢量示意图一， 如图 1所示， 为了消除 AP2对 STA的干扰， STA可以选取一个向量 w， 该向量需要与 AP2的信道向量 httl 正交， 即满足 w.httl =0。 STA对接收信号 y乘上向量 w后的信号即为：
y' = w -y = w-(h&1 - /7 + h&2 T) = wh&2 T
处理后的信号只包括来自 API的信号， 消除了 AP2的信号， STA再使用
IEEE802.il标准中的载波侦听方法对 API的信道进行侦听， 这样 STA就可 以利用第 2个自由度来进行通信。
进一歩的， 假设 STA有 3根天线， API有 1根天线， AP2发送 1个流。 API与 STA是一个收发对， STA能够听到 AP2， AP2发出的信号对 STA造 成干扰。 由于 STA有 3根天线分别对应三个数据流， 其中一个用于消除 AP2 的干扰， 由于 API只有一根天线， STA与 API交互通过一个数据流即可， 因 此 STA竞争第 2个自由度。 如果 AP2发送的信号为 p， API发送的信号为 r，
STA的实际接收的信号 y为
其中， httl是 ΑΡ2与 STA之间的信道的信道向量， htt2是 API与 STA之 间的信道的信道向量。
图 2为 STA接收信号的矢量示意图二， 如图 2所示， 为了消除 AP2对 STA 的干扰， STA可以选取一个向量 w， 该向量位于与 httl正交的二维子空 间上， 满足 w.htt, =0。 STA对接收信号 y乘上向量 w后的信号即为：
y' = W.y = W.(h&1.p+h&2 T) = wh&2 T
处理后的信号只包括来自 API的信号， 消除了 AP2的信号， STA再使用
IEEE802.il标准中的载波侦听方法对 API的信道进行侦听， 这样 STA就可 以利用第 2个自由度来进行通信。
但是， 在处理图 2所示的情况时， STA选取的向量 w可以是二维子空间 上的任一向量， 这是由于二维子空间与 httl正交， 因此在该二维子空间上任 意选择的向量都满足 w.httl=0， 图 2中选择了三个向量 Wl、 w2、 w3， 其中， ^是 2在二维子空间上的垂直投影， 与 htt2之间的夹角 为 45度； ^与 2 之间的夹角 为 60度； ^与 2之间的夹角 为 90度。 上述处理后的信号 y' 可以
如果在二维子空间上随机选取向量 w， 夹角 0会随着 w发生变化， 例如 从 45度到 90度， 这样 co 也随之变化， 最小甚至可以为 0。 因此 STA处理 后的信号不确定， 可能会出现将 API的信号处理的很小甚至为 0的情况， 导 致无法正常收发信号， 也会降低信号传输速率， 进而降低小区吞吐量。
为使本发明实施例的目的、 技术方案和优点更加清楚， 下面将结合本发 明实施例中的附图， 对本发明实施例中的技术方案进行清楚、 完整地描述， 显然， 所描述的实施例是本发明一部分实施例， 而不是全部的实施例。 基于 本发明中的实施例， 本领域普通技术人员在没有作出创造性劳动前提下所获 得的所有其他实施例， 都属于本发明保护的范围。
本发明中的接收端设备可以是上述现有技术举例中的 STA, 也可以是 AP， 只要是作为接收数据的设备， 对接收到的信号都要进行处理以消除相 邻设备的干扰。
图 3为本发明多维载波侦听的方法实施例一的流程图， 如图 3所示， 本 实施例的方法可以包括：
歩骤 101、 接收端设备接收两个以上网络设备发送的信号；
本实施例中的接收端设备接收两个以上网络设备发送的信号， 这里两个 以上网络设备包括发送端设备和至少一个相邻设备， 即接收端设备收到的信 号中可能包括了发送端设备发送的信号， 也可能包括其他相邻设备发送的信 号。 发送端设备与接收端设备是一个收发对， 相邻设备是与接收端设备相邻 的其他网络设备， 相邻设备可以与收发对共用信道， 因此相邻设备发出的信 号对于接收端设备来讲是干扰信号， 不利于接收端设备对信道的侦听。
歩骤 102、 所述接收端设备通过最大化所述发送端设备与所述接收端设 备之间的信道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正 向量对所述信号进行处理。
本实施例中， 接收端设备通过最优信号矫正向量对接收到的信号进行处 理， 以消除所述至少一个相邻设备的信号干扰。 该最优信号矫正向量类似上 述现有技术中的向量 w， 接收端设备可以通过向量 w与干扰信号正交， 二者 做相乘处理以消除相邻设备的信号干扰。 本发明中， 最优信号矫正向量还满 足使发送端设备与接收端设备之间的信道的信噪比最大化的要求。
具体来讲， 以图 2所示的场景为例， 接收端设备从与 httl正交的二维子空 间上选取了三个向量 Wl、 w2、 w3， 这三个向量已满足 w .httl = 0。 进一歩的， 还要从这个三个向量中选出最优信号矫正向量， 最优信号矫正向量可以使发 送端设备与接收端设备之间的信道的信噪比1 W'h"2 ' f|2最大化。 由于上述处理 后的信号 y'可以表示为：
y' = w -h&2 - r = |w| - |h&2| - cos^ T
因此， 信噪比最大化可以转换为 max(COS ， 0为 w与 htt2的夹角。 图 2中 根据信噪比最大化原则， 将^选为最优信号矫正向量， 这是由于 ^是 2在 二维子空间上的垂直投影， 满足 maX(COS 的条件。 接收端设备将接收信号乘 上 Wl， 即可消除相邻设备的干扰， 又可以实现发送端设备与接收端设备之间 的信道的信噪比最大化。
本实施例， 接收端设备通过计算获取的最优信号矫正向量， 并用最优信 号矫正向量对接收信号进行处理， 实现既消除相邻设备的干扰， 又使发送端 设备与接收端设备之间的信道的信噪比最大化， 再使用 IEEE802.i l标准中的 载波侦听对发送端设备到接收端设备的信道进行侦听， 接收端设备就可以利 用剩余的自由度来进行通信， 解决现有技术中会将接收到的全部信号处理的 很小， 甚至为 0， 导致设备无法正常收发信号， 也会降低信号传输速率， 进 而降低小区吞吐量的问题。
进一歩的， 上述方法实施例的歩骤 102之前， 还包括： 所述接收端设备 计算获取与所述相邻设备的信道向量矩阵正交的零空间矩阵， 所述零空间矩 阵组成正交子空间， 所述信道向量矩阵由一个或多个所述相邻设备分别与所 述接收端设备之间的信道的信道向量组成；
歩骤 102具体的实现方法可以是： 所述接收端设备计算获取所述发送端 设备与所述接收端设备之间的一个或多个信道的信道向量分别垂直投影到所 述正交子空间上的信号矫正向量； 所述接收端设备根据所述发送端设备的天 线数、 所述接受端设备的天线数和所述至少一个相邻设备的总数据流数确定 所述最优信号矫正向量的个数； 所述接收端设备从一个或多个所述信号矫正 向量中选择出与所述最优信号矫正向量的个数相等， 且使所述发送端设备与 所述接收端设备之间的信道的信噪比最大化的向量作为所述最优信号矫正向 量。
具体来讲， 相邻设备可以是有多个的， 即上述信道向量 httl有一个以 上， 此时要满足 w .httl = 0， 实际上是计算与多个 httl组成的信道向量矩阵正交 的零空间矩阵， 那么只要是位于该零空间矩阵组成的正交子空间上的任何向 量均满足 whttl = 0。 正交子空间例如可以是图 2 所示的二维子空间。 再根据 上述信道的信噪比最大化原则， 将发送端设备与接收端设备之间的一个或多 个信道的信道质量分别垂直映射到正交子空间上， 得到一个或多个信号矫正
向量， 这些信号矫正向量即为各信道分别对应的满足信噪比最大化的 W。 以 图 2为例， 将信道向量 htt2垂直投影到二维子空间上， 对应 Wl， ^与 2的夹 角 满足 max(COS 。 然后确定接收端设备能够使用的最大自由度 （即最优信 号矫正向量的个数 N ) ：
N = min(NAP NSTA - NAP2 )
其中， 发送端设备的天线数为 N^ , 接收端设备的天线数为！^^， 相邻 设备的总流数为^^2。
接收端设备从之前计算获取的多个 w中再选出最优信号矫正向量， 即虽 然每个 w都可以使其对应的信道的信噪比最大， 但是考虑到接收端设备可用 的最大自由度， 尤其是当 ： N^ - N^ )时， 上述计算出来的信号矫正向量 的个数是大于接收端设备可使用的数据流数的， 因此需要再在这些信号矫正 向量中选出最优的， 此时选择的标准可以是选择最大 对应的信号矫正向量 即为最优信号矫正向量。 这是由于
max(cos Θ) - max(cos(90。― φ、、= max(sin φ)
其中， 为 httl与 htt2之间的夹角， 因此还可以将信噪比最大化转换为 max(^?) o
图 4为本发明多维载波侦听的方法实施例二的流程图， 如图 4所示， 本 实施例的方法可以包括：
歩骤 201、 接收端设备接收两个以上网络设备发送的信号；
本实施例中， 接收端设备接收两个以上网络设备发送的信号的过程与上 述方法实施例的歩骤 101类似， 此处不再赘述。
歩骤 202、 所述接收端设备通过最大化所述发送端设备与所述接收端设 备之间的信道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正 向量对所述信号进行处理；
本实施例中， 所述接收端设备通过最大化所述发送端设备与所述接收端 设备之间的信道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫 正向量对所述信号进行处理的过程与上述方法实施例的歩骤 102类似， 此处 不再赘述。
歩骤 203、 所述接收端设备向所述发送端设备发送数据流更新信息， 以 使所述发送端设备根据所述数据流更新信息调整发送数据的流数；
本实施例中， 接收端设备在确定了最优信号矫正向量的个数后， 可以将
该个数通过数据流更新信息通知给发送端设备， 可以使发送端设备及时调整 发送数据的流数， 避免数据丢失。
歩骤 204、 所述接收端设备根据所述最优信号矫正向量对信号进行预编 码， 并将预编码后的信号发送给所述发送端设备。
本实施例中， 接收端设备在获取到最优信号矫正向量后， 可以根据该最 优信号矫正向量对信号进行预编码， 由于最优信号矫正向量与相邻设备的信 道质量正交且是信噪比最大， 因此预编码后的信号与相邻设备的信号互不干 扰， 且实现了最大信噪比， 提升信号传输速率和小区吞吐量。
下面采用几个具体的实施例， 对图 3或图 4所示方法实施例的技术方案 进行详细说明。
实施例一： 假设接收端设备为 STA有 3根天线， 发送端设备为 API有 1 根天线， 相邻设备为 AP2发送 1个流。 STA能够听到 AP2， AP2发出的信号 对 STA造成干扰。
AP2发送信号为 p， API发送信号为 r， 根据
N = min(NAP NSTA - NAP2)
可知 STA可以竞争的自由度为 1个。
STA的接收信号
其中， 1 ^是 AP2到 STA的信道向量， htt2是 API到 STA的信道向量。 基于 whttl = 0， 计算获取与 httl正交的二维子空间， 再基于信噪比最大化 原则， 将! ^垂直映射到二维子空间上即获取到最优信号矫正向量 w。
实施例二： 假设接收端设备为 STA有 3根天线， 发送端设备为 API有 2 根天线， 相邻设备为 AP2发送 1个流。 STA能够听到 AP2， AP2发出的信号 对 STA造成干扰。
AP2发送信号为 p， API发送信号为 r， 根据
N = min(NAP NSTA - NAP2)
可知 STA可以竞争的自由度为 2个。
STA的接收信号
其中， httl是 AP2到 STA的信道向量， htt2是 API的一个天线到 STA的 信道向量， h&3是 API的另一个天线到 STA的信道向量。
基于 whttl = 0， 计算获取与！ ^正交的多维正交子空间， 再基于信噪比最 大化原则， 将! ^和! ^分别垂直映射到多维正交子空间上即获取到最优信号 矫正向量^和 w2。
实施例三： 假设接收端设备为 STA有 3根天线， 发送端设备为 API有 3 根天线， 相邻设备为 AP2发送 1个流。 STA能够听到 AP2， AP2发出的信号 对 STA造成干扰。
AP2发送信号为 p， API发送信号为 r， 根据
N = min(NAP NSTA - NAP2)
可知 STA可以竞争的自由度为 2个。
STA的接收信号
y = Κι . ρ +Κι .1 +K3. ri +K4. r3
其中， 1 ^是 AP2到 STA的信道向量， htt2是 API的： 个天线到 STA 的信道向量， 1 ^是 API的第二个天线到 STA的信道向量
三个天线到 STA的信道向量。
基于 w.hrt, = 0， 计算获取与！ ^正交的多维正交子空间， 再基于信噪比最 大化原则， 将 htt2、 htt3以及! ^分别垂直映射到多维正交子空间上即获取到 最优信号矫正向量 和
由于 STA只能再发送两个数据流， 因此再从 Wl、 w nW3中选出其对应 的信道向量 htt2、 htx3以及 htt4分别与 httl的夹角中最大的两个夹角对应的信号 矫正向量。
图 5为本发明多维载波侦听装置实施例一的结构示意图， 如图 5所示， 本实施例的装置可以包括： 接收模块 11和信号处理模块 12， 其中， 接收模 块 11， 用于接收两个以上装置发送的信号， 所述两个以上装置包括发送端装 置和至少一个相邻装置； 信号处理模块 12， 用于通过最大化所述发送端设备 与所述接收端设备之间的信道的信噪比， 获取最优信号矫正向量， 并通过所 述最优信号矫正向量对所述信号进行处理， 以消除所述至少一个相邻装置的 信号干扰。
本实施例的装置， 可以用于执行图 3所示方法实施例的技术方案， 其实 现原理和技术效果类似， 此处不再赘述。
图 6为本发明多维载波侦听装置实施例二的结构示意图， 如图 6所示， 本实施例的装置在图 5所示装置结构的基础上， 进一歩地， 还可以包括： 干
扰消除模块 21、 信息发送模块 22 和预编码模块 23， 其中， 干扰消除模块 21， 用于计算获取与所述相邻装置的信道向量矩阵正交的零空间矩阵， 所述 零空间矩阵组成正交子空间， 所述信道向量矩阵由一个或多个所述相邻装置 分别与所述多维载波侦听装置之间的信道的信道向量组成； 信号处理模块 12， 具体用于计算获取所述发送端装置与所述多维载波侦听装置之间的一个 或多个信道的信道向量分别垂直投影到所述正交子空间上的信号矫正向量； 根据所述发送端装置的天线数、 所述多维载波侦听装置的天线数和所述至少 一个相邻装置的总数据流数确定所述最优信号矫正向量的个数； 从一个或多 个所述信号矫正向量中选择出与所述最优信号矫正向量的个数相等， 且使所 述发送端设备与所述接收端设备之间的信道的信噪比最大化的向量作为所述 最优信号矫正向量。
信息发送模块 22， 用于向所述发送端装置发送数据流更新信息， 以使所 述发送端装置根据所述数据流更新信息调整发送数据的流数。
预编码模块 23， 用于根据所述最优信号矫正向量对信号进行预编码， 并 将预编码后的信号发送给所述发送端装置。
本实施例的装置， 可以用于执行图 3 或图 4 所示方法实施例的技术方 案， 其实现原理和技术效果类似， 此处不再赘述。
图 7为本发明接收端设备实施例一的结构示意图， 如图 7所示， 本实施 例的装置可以包括： 接收器 11和处理器 12， 其中， 接收器 11， 用于接收两 个以上网络设备发送的信号， 所述两个以上网络设备包括发送端设备和至少 一个相邻设备； 处理器 12， 用于通过最大化所述发送端设备与所述接收端设 备之间的信道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正 向量对所述信号进行处理， 以消除所述至少一个相邻设备的信号干扰。
本实施例的装置， 可以用于执行图 3所示方法实施例的技术方案， 其实 现原理和技术效果类似， 此处不再赘述。
图 8为本发明接收端设备实施例二的结构示意图， 如图 8所示， 本实施 例的装置在图 7所示装置结构的基础上， 进一歩地， 还可以包括： 计算器 21 和发送器 22, 其中， 计算器 21， 用于计算获取与所述相邻设备的信道向量 矩阵正交的零空间矩阵， 所述零空间矩阵组成正交子空间， 所述信道向量矩 阵由一个或多个所述相邻设备分别与所述接收端设备之间的信道的信道向量
组成； 计算获取所述发送端设备与所述接收端设备之间的一个或多个信道的 信道向量分别垂直投影到所述正交子空间上的信号矫正向量； 处理器 12， 具 体用于根据所述发送端设备的天线数、 所述接受端设备的天线数和所述至少 一个相邻设备的总数据流数确定所述最优信号矫正向量的个数； 从一个或多 个所述信号矫正向量中选择出与所述最优信号矫正向量的个数相等， 且使所 述发送端设备与所述接收端设备之间的信道的信噪比最大化的向量作为所述 最优信号矫正向量。
进一歩的， 发送器 22， 用于向所述发送端设备发送数据流更新信息， 以 使所述发送端设备根据所述数据流更新信息调整发送数据的流数。
进一歩的， 处理器 12， 还用于根据所述最优信号矫正向量对信号进行预 编码； 发送器 22， 还用于将预编码后的信号发送给所述发送端设备。
本实施例的装置， 可以用于执行图 3 或图 4 所示方法实施例的技术方 案， 其实现原理和技术效果类似， 此处不再赘述。
在本发明所提供的几个实施例中， 应该理解到， 所揭露的装置和方法， 可以通过其它的方式实现。 例如， 以上所描述的装置实施例仅仅是示意性 的， 例如， 所述单元的划分， 仅仅为一种逻辑功能划分， 实际实现时可以有 另外的划分方式， 例如多个单元或组件可以结合或者可以集成到另一个系 统， 或一些特征可以忽略， 或不执行。 另一点， 所显示或讨论的相互之间的 耦合或直接耦合或通信连接可以是通过一些接口， 装置或单元的间接耦合或 通信连接， 可以是电性， 机械或其它的形式。
所述该作为分离部件说明的单元可以是或者也可以不是物理上分开的， 作为单元显示的部件可以是或者也可以不是物理单元， 即可以位于一个地 方， 或者也可以分布到多个网络单元上。 可以根据实际的需要选择其中的部 分或者全部单元来实现本实施例方案的目的。
另外， 在本发明各个实施例中的各功能单元可以集成在一个处理单元 中， 也可以是各个单元单独物理存在， 也可以两个或两个以上单元集成在一 个单元中。 上述集成的单元既可以采用硬件的形式实现， 也可以采用硬件加 软件功能单元的形式实现。
上述以软件功能单元的形式实现的集成的单元， 可以存储在一个计算机 可读取存储介质中。 上述软件功能单元存储在一个存储介质中， 包括若干指
令用以使得一台计算机设备（可以是个人计算机， 服务器， 或者网络设备等) 或处理器 （processor) 执行本发明各个实施例所述方法的部分歩骤。 而前述 的存储介质包括： U 盘、 移动硬盘、 只读存储器 （Read-Only Memory , ROM) 、 随机存取存储器 （Random Access Memory, RAM) 、 磁碟或者光 盘等各种可以存储程序代码的介质。
本领域技术人员可以清楚地了解到， 为描述的方便和简洁， 仅以上述各 功能模块的划分进行举例说明， 实际应用中， 可以根据需要而将上述功能分 配由不同的功能模块完成， 即将装置的内部结构划分成不同的功能模块， 以 完成以上描述的全部或者部分功能。 上述描述的装置的具体工作过程， 可以 参考前述方法实施例中的对应过程， 在此不再赘述。
最后应说明的是： 以上各实施例仅用以说明本发明的技术方案， 而非对 其限制； 尽管参照前述各实施例对本发明进行了详细的说明， 本领域的普通 技术人员应当理解： 其依然可以对前述各实施例所记载的技术方案进行修 改， 或者对其中部分或者全部技术特征进行等同替换； 而这些修改或者替 换， 并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。
Claims
1、 一种多维载波侦听的方法， 其特征在于， 包括：
接收端设备接收两个以上网络设备发送的信号， 所述两个以上网络设备 包括发送端设备和至少一个相邻设备；
所述接收端设备通过最大化所述发送端设备与所述接收端设备之间的信 道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正向量对所述 信号进行处理， 以消除所述至少一个相邻设备的信号干扰。
2、 根据权利要求 1 所述的方法， 其特征在于， 所述接收端设备通过最 大化所述发送端设备与所述接收端设备之间的信道的信噪比， 获取最优信号 矫正向量， 并通过所述最优信号矫正向量对所述信号进行处理之前， 还包 括：
所述接收端设备计算获取与所述相邻设备的信道向量矩阵正交的零空间 矩阵， 所述零空间矩阵组成正交子空间， 所述信道向量矩阵由一个或多个所 述相邻设备分别与所述接收端设备之间的信道的信道向量组成；
所述接收端设备通过最大化所述发送端设备与所述接收端设备之间的信 道的信噪比， 获取最优信号矫正向量， 包括：
所述接收端设备计算获取所述发送端设备与所述接收端设备之间的一个 或多个信道的信道向量分别垂直投影到所述正交子空间上的信号矫正向量； 所述接收端设备根据所述发送端设备的天线数、 所述接受端设备的天线 数和所述至少一个相邻设备的总数据流数确定所述最优信号矫正向量的个 数；
所述接收端设备从一个或多个所述信号矫正向量中选择出与所述最优信 号矫正向量的个数相等， 且使所述发送端设备与所述接收端设备之间的信道 的信噪比最大化的向量作为所述最优信号矫正向量。
3、 根据权利要求 1或 2所述的方法， 其特征在于， 所述接收端设备通过 最大化所述发送端设备与所述接收端设备之间的信道的信噪比， 获取最优信 号矫正向量， 并通过所述最优信号矫正向量对所述信号进行处理之后， 还包 括：
所述接收端设备向所述发送端设备发送数据流更新信息， 以使所述发送 端设备根据所述数据流更新信息调整发送数据的流数。
4、 根据权利要求 1~3 中任一项所述的方法， 其特征在于， 所述接收端 设备通过最大化所述发送端设备与所述接收端设备之间的信道的信噪比， 获 取最优信号矫正向量， 并通过所述最优信号矫正向量对所述信号进行处理之 后， 还包括：
所述接收端设备根据所述最优信号矫正向量对信号进行预编码， 并将预 编码后的信号发送给所述发送端设备。
5、 一种多维载波侦听装置， 其特征在于， 包括：
接收模块， 用于接收两个以上装置发送的信号， 所述两个以上装置包括 发送端装置和至少一个相邻装置；
信号处理模块， 用于通过最大化所述发送端设备与所述接收端设备之间 的信道的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正向量对 所述信号进行处理， 以消除所述至少一个相邻装置的信号干扰。
6、 根据权利要求 5所述的装置， 其特征在于， 还包括：
干扰消除模块， 用于计算获取与所述相邻装置的信道向量矩阵正交的零 空间矩阵， 所述零空间矩阵组成正交子空间， 所述信道向量矩阵由一个或多 个所述相邻装置分别与所述多维载波侦听装置之间的信道的信道向量组成； 所述信号处理模块， 具体用于计算获取所述发送端装置与所述多维载波 侦听装置之间的一个或多个信道的信道向量分别垂直投影到所述正交子空间 上的信号矫正向量； 根据所述发送端装置的天线数、 所述多维载波侦听装置 的天线数和所述至少一个相邻装置的总数据流数确定所述最优信号矫正向量 的个数； 从一个或多个所述信号矫正向量中选择出与所述最优信号矫正向量 的个数相等， 且使所述发送端设备与所述接收端设备之间的信道的信噪比最 大化的向量作为所述最优信号矫正向量。
7、 根据权利要求 5或 6所述的装置， 其特征在于， 还包括：
信息发送模块， 用于向所述发送端装置发送数据流更新信息， 以使所述 发送端装置根据所述数据流更新信息调整发送数据的流数。
8、 根据权利要求 5~7中任一项所述的装置， 其特征在于， 还包括： 预编码模块， 用于根据所述最优信号矫正向量对信号进行预编码， 并将 预编码后的信号发送给所述发送端装置。
9、 一种接收端设备， 其特征在于， 包括：
接收器， 用于接收两个以上网络设备发送的信号， 所述两个以上网络设 备包括发送端设备和至少一个相邻设备；
处理器， 用于通过最大化所述发送端设备与所述接收端设备之间的信道 的信噪比， 获取最优信号矫正向量， 并通过所述最优信号矫正向量对所述信 号进行处理， 以消除所述至少一个相邻设备的信号干扰。
10、 根据权利要求 9所述的设备， 其特征在于， 还包括：
计算器， 用于计算获取与所述相邻设备的信道向量矩阵正交的零空间矩 阵， 所述零空间矩阵组成正交子空间， 所述信道向量矩阵由一个或多个所述 相邻设备分别与所述接收端设备之间的信道的信道向量组成；
所述计算器， 还用于计算获取所述发送端设备与所述接收端设备之间的 一个或多个信道的信道向量分别垂直投影到所述正交子空间上的信号矫正向 所述处理器， 具体用于根据所述发送端设备的天线数、 所述接受端设备 的天线数和所述至少一个相邻设备的总数据流数确定所述最优信号矫正向量 的个数； 从一个或多个所述信号矫正向量中选择出与所述最优信号矫正向量 的个数相等， 且使所述发送端设备与所述接收端设备之间的信道的信噪比最 大化的向量作为所述最优信号矫正向量。
11、 根据权利要求 9或 10所述的设备， 其特征在于， 还包括： 发送器， 用于向所述发送端设备发送数据流更新信息， 以使所述发送端 设备根据所述数据流更新信息调整发送数据的流数。
12、 根据权利要求 9~11 中任一项所述的设备， 其特征在于， 所述处理 器， 还用于根据所述最优信号矫正向量对信号进行预编码；
所述发送器， 还用于将预编码后的信号发送给所述发送端设备。
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| CN103532648A (zh) * | 2013-10-22 | 2014-01-22 | 北京邮电大学 | 一种无线通信网络中的子载波感知方法 |
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