Beam forming method, signal transmitting device and signal transmission system

Abstract

The invention relates to a beam forming method, a signal transmitting device and a signal transmission system. The beam forming method provided by the invention comprises the following steps: SE1, acquiring current environment information and current target information of target equipment; sE2, predicting future environment information and future target information according to the current environment information and the current target information to obtain prediction conditions; sE3, determining an optimal beam according to the prediction condition; sE4, solving a phase deviation value of each antenna unit according to the optimal beam; and SE5, controlling the phase of the signal transmitted by each antenna unit according to the phase deviation value, so that the phased-array antenna outputs an actual wave beam. According to the invention, the phased-array antenna is adopted to transmit the millimeter wave signal, and the beam direction is rapidly and accurately adjusted through the improved beam forming method, so that the energy of the millimeter wave signal is focused at the position of the target equipment, thereby overcoming the problems of high propagation loss and signal blocking in millimeter wave communication.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a beam forming method, a signal transmitting device and a signal transmission system. Background Art

[0002] Millimeter waves refer to high-frequency radio waves with a frequency above 24GHz. Wireless communications on the market generally use the ISM band with a frequency of 2400-2483.5MHz. Due to the high frequency of millimeter waves, wireless communication technology based on millimeter waves can achieve higher bandwidth, lower latency and higher transmission rate compared to existing wireless communication technology based on the ISM band, and is more suitable for the field of high-fidelity audio transmission.

[0003] However, the high frequency and narrow beam of millimeter waves result in high propagation loss of millimeter waves, and the signals are easily blocked by human bodies, buildings and furniture. How to overcome the problem of high propagation loss of millimeter waves and easy signal blocking is an important problem that current millimeter wave communication technology needs to overcome. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide a beamforming method, a signal transmitting device and a signal transmission system, which use a phased array antenna combined with MIMO to transmit millimeter wave signals, and use an improved beamforming method to quickly and accurately adjust the beam direction so that the energy of the millimeter wave signal is focused on the position of the target device, thereby overcoming the problems of high propagation loss and signal blocking in millimeter wave communications.

[0005] The present invention provides a beamforming method for a phased array antenna, comprising the following steps: SE1, acquiring current environment information and current target information of a target device; SE2, predicting future environment information and future target information according to the current environment information and current target information to obtain prediction conditions; SE3, determining an optimal beam according to the prediction conditions; SE4, solving a phase offset value of each antenna unit according to the optimal beam; SE5, controlling the phase of a signal transmitted by each antenna unit according to the phase offset value, so that the phased array antenna outputs an actual beam.

[0006] The beamforming method of the present invention improves the quality of millimeter wave communication from the following perspectives: 1. The present invention fully considers environmental information, can actively avoid interference sources and occupied frequency bands based on environmental information, and improves the stability of millimeter wave communication; 2. The present invention considers future changing trends of environmental information and target information, can predict future environmental information and future target information, and generates millimeter wave beams based on future environmental information and future target information, thereby improving the targetedness of beamforming, and can focus signal energy near the target device even if the target device is in motion, thereby improving the quality of the signal received by the target device.

[0007] Furthermore, step SE2 is specifically as follows: through a prediction model, based on the current environment information and current target information, predict future environment information and future target information to obtain prediction conditions; the prediction model is a machine learning model, which is trained by historical environment information and historical target information, and is used to predict future environment information and future target information based on current environment information and current target information.

[0008] Furthermore, the prediction model is an LSTM model; the LSTM model is trained by the following training method: ST1, obtaining historical environment information and historical target information; ST2, dividing the historical environment information and historical target information into several segments, and inputting them into the LSTM model as training samples; ST3, the LSTM model extracts and predicts features for each segment to obtain a predicted segment; ST4, comparing the predicted segment with the next segment corresponding to the current segment, and calculating a loss function; ST5, optimizing the parameters of the LSTM model according to the loss function; ST6, repeating steps ST3-ST5, the LSTM model updates the parameters each time a predicted segment is obtained, until the parameters of the LSTM model converge or the number of parameter updates reaches a set threshold, and a trained LSTM model is obtained.

[0009] Furthermore, step SE3 is specifically as follows: determining the direction and coverage of the optimal beam according to the future target information in the prediction condition, and eliminating interference sources according to the future environment information in the prediction condition, thereby determining the optimal beam.

[0010] Furthermore, step SE4 is specifically as follows: according to the geometric arrangement of the phased array antenna, a relationship formula between the output beam and the phase offset value of each antenna unit is obtained; the optimal beam is substituted into the relationship formula as the output beam, and the phase offset value of each antenna unit corresponding to the optimal beam is solved.

[0011] Furthermore, the beam forming method further comprises the step of: SJ, real-time monitoring and correcting the actual beam. The present invention automatically corrects the actual beam according to the difference between the actual beam and the optimal beam, thereby improving the accuracy of beam control.

[0012] Furthermore, step SJ specifically includes: SJ1, monitoring the actual beam and calculating the difference function between the actual beam and the optimal beam; SJ2, correcting the phase offset value in the direction of gradient descent of the difference function; SJ3, controlling the phase of the signal transmitted by each antenna unit according to the corrected phase offset value, thereby correcting the actual beam in real time.

[0013] Based on the same inventive concept, the present invention also provides a millimeter-wave based signal transmitting device, comprising: a MIMO phased array antenna system and a controller; the MIMO phased array antenna system comprises a plurality of antenna units arranged in a preset array; the controller controls the millimeter-wave beam ultimately output by the signal transceiver by controlling the phase of the signal transmitted by each antenna unit; wherein the controller comprises the following modules: an information acquisition module, for acquiring current environmental information and current target information of the target device; a prediction module, for predicting future environmental information and future target information based on the current environmental information and current target information to obtain prediction conditions; an optimal beam determination module, for determining an optimal beam based on the prediction conditions; a phase calculation module, for solving the phase offset value of each antenna unit based on the optimal beam; and an antenna control module, for controlling the phase of the signal transmitted by each antenna unit based on the phase offset value.

[0014] Furthermore, the prediction module is specifically a prediction model; the prediction model is a machine learning model, which is trained by historical environmental information and historical target information, and is used to predict future environmental information and future target information based on current environmental information and current target information.

[0015] Based on the same inventive concept, the present invention also provides a millimeter wave-based signal transmission system, comprising a transmitting device and a target device; the transmitting device transmits a millimeter wave beam to the target device, thereby performing wireless communication with the target device; wherein the transmitting device is any one of the above-mentioned millimeter wave-based signal transmitting devices.

[0016] For better understanding and implementation, the present invention is described in detail below with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of a module of a millimeter wave based signal transmission system of the present invention;

[0018] Figure 2 It is a schematic diagram of a module of a millimeter wave based signal transmitting device of the present invention;

[0019] Figure 3 A schematic diagram of a module of a controller of a millimeter wave-based signal transmitting device of the present invention;

[0020] Figure 4 A schematic flow chart of a beamforming method executed by a controller of the present invention;

[0021] Figure 5 This is a structural diagram of the LSTM model. DETAILED DESCRIPTION

[0022] MIMO (Multiple-Input Multiple-Output) technology can effectively solve the problem of signal propagation loss. MIMO technology encodes the original data into multiple data streams through coding technology, and transmits multiple data streams in parallel through multiple groups of antennas. Finally, the multiple data streams are restored to the original data through decoding technology at the signal receiving end. Since the fading characteristics of multiple data stream signal transmission are independent of each other, combining multiple data streams with appropriate methods can achieve a more stable and more fidelity transmission effect than single antenna transmission.

[0023] A phased array antenna is a signal transceiver device that includes multiple antenna units. It achieves beamforming and directional control of the final output signal by changing the phase difference of the signals transmitted by different antenna units. The phased array antenna can adjust the direction and shape of the transmitted signal through electronic control without moving the physical position of the antenna.

[0024] The present invention adopts a phased array antenna combined with MIMO to transmit and receive millimeter wave signals, and uses an improved beam forming method to quickly and accurately adjust the beam direction so that the energy of the millimeter wave signal is focused near the target device (signal receiving end), thereby overcoming the problem of high millimeter wave propagation loss and easy signal blocking.

[0025] See also Figure 1 , Figure 1 Schematic diagram of a module of a millimeter wave based signal transmission system of the present invention. The millimeter wave based signal transmission system of the present invention comprises a transmitting device 100 and a target device 200. The transmitting device 100 transmits a millimeter wave beam to the target device 200, thereby performing millimeter wave based wireless communication with the target device 200. The transmitting device 100 is a millimeter wave based signal transmitting device of the present invention.

[0026] In one embodiment, the transmitting device 100 may be an audio source device (such as a mobile phone), and the target device 200 may be a wireless headset. The audio source device transmits audio data to the wireless headset by transmitting a millimeter wave beam, and the wireless headset plays music according to the audio data.

[0027] In another embodiment, the transmitting device 100 and the target device 200 may both have the ability to transmit and receive millimeter wave signals, thereby performing bidirectional millimeter wave communication. In this case, the signal transmission system includes a first device and a second device. When the first device transmits a millimeter wave beam to the second device, the first device is the transmitting device 100 and the second device is the target device 200; when the second device transmits a millimeter wave beam to the first device, the second device is the transmitting device 100 and the first device is the target device 200. The present invention does not limit the number of the first device and the second device.

[0028] See also Figure 2 , Figure 2 Schematic diagram of the module of the millimeter wave based signal transmitting device of the present invention. The millimeter wave based signal transmitting device 100 of the present invention comprises a MIMO phased array antenna system 101 and a controller 102. The MIMO phased array antenna system 101 comprises a plurality of antenna units arranged in a preset array (e.g., a linear array, a circular array, or a planar array, etc.), and the phase of the signal transmitted by each antenna unit is individually controlled by the controller 102. The controller 102 controls the millimeter wave beam finally output by the signal transceiver 100 by adjusting the phase of the signal transmitted by different antenna units.

[0029] Based on the working principle of the above-mentioned MIMO phased array antenna system 101, as long as the controller 102 can control the phase offset values ​​corresponding to multiple antenna units, it can control the direction and shape of the beam, so that the signal energy is focused near the target device 200, thereby overcoming the problem of high millimeter wave propagation loss and easy signal blocking.

[0030] See also Figure 3-4 , Figure 3 Schematic diagram of a module of a controller of a millimeter wave based signal transmitting device of the present invention. Figure 4 FIG. 4 is a flow chart of a beamforming method executed by a controller of the present invention.

[0031] The controller 102 includes: an information acquisition module E1, a prediction module E2, an optimal beam determination module E3, a phase calculation module E4 and an antenna control module E5.

[0032] The information acquisition module E1 is used to execute step SE1: acquire current environment information and current target information of the target device 200. The current environment information includes electromagnetic spectrum usage information, interference source location and interference signal strength, etc. The current target information includes the current location, speed and moving direction of the target device 200, etc.

[0033] The MIMO phased array antenna system 101 can be used for both transmitting and receiving signals, so the information acquisition module E1 of the controller 102 can receive environmental signals in the environment and the request signal sent by the target device 200 through the MIMO phased array antenna system 101, and obtain the current environmental information and the current target information by parsing the environmental signals and the request signals.

[0034] The prediction module E2 is used to execute step SE2: predict future environment information and future target information according to the current environment information and current target information to obtain prediction conditions.

[0035] Specifically, the prediction module E2 is a prediction model. The prediction model is a machine learning model, which is trained by historical environment information and historical target information, and is used to predict future environment information and future target information based on current environment information and current target information, including but not limited to deep neural network models (Deep Neural Networks, DNN), convolutional neural network models (Convolutional Neural Networks, CNN), recurrent neural network models (Recurrent Neural Network, RNN), long short-term memory network models (Long Short-term Memory, LSTM) and other machine learning models.

[0036] In this embodiment, the prediction model is an LSTM model. The LSTM model is a special recurrent neural network that controls the flow of information by introducing the concept of "gate", thereby solving the gradient vanishing and gradient exploding problems that are prone to occur in traditional recurrent neural networks when processing long sequences. The gated unit structure of the LSTM model consists of an input gate, an output gate, and a forget gate. The LSTM model can process the relationship between historical input information and current input information through three types of gate calculations.

[0037] See also Figure 5 , Figure 5 This is a structural diagram of the LSTM model. Figure 5 Middle C t represents the cell state at time t, h t represents the information at time t, x t Represents the input at the current moment, tanh is the activation function, and σ is the sigmoid function. Figure 3 The region g1 in the figure represents the forget gate, the region g2 represents the input gate, and the region g3 represents the output gate.

[0038] The forget gate is used to decide which information to keep and which to forget. t-1 and the current information xt-1 Processing is performed and a value between 0 and 1 is output through the sigmoid function to determine the cell state C t-1 How much should be remembered. The forget gate expression is as follows: t =σ(W f ·[h t-1 ,x t ]+b f ), where W f and b f are the weight and bias of the forget gate respectively.

[0039] The input gate determines what information is added to the unit. First, h t-1 and x t-1 The sigmoid function is used to select which information to update, and the tanh function is used to obtain the candidate unit state. The expression of the input gate is as follows: t =σ(W i ·[h t-1 ,x t ]+b i ), The input gate updates the cell state by the following formula: Where i t represents the output of the input gate, W i and b i is the weight and bias of the input gate, W c and b c is the candidate unit state at time t The weights and biases.

[0040] The output gate controls what information the storage unit outputs. First, the output gate uses the sigmoid function to determine part of the output, and then uses the tanh function to process the storage unit state C. t , and multiply it with the output of the sigmoid function to get the output h at the current moment t The output gate expression is as follows: t =σ(W o ·[h t-1 ,x t ]+b o )h t ,h t =o t tanh(C t ), where o t represents the output of the output gate, W o and b o are the weight and bias of the output gate respectively.

[0041] Furthermore, the LSTM model is trained by the following training method: ST1, obtaining historical environment information and historical target information. ST2, dividing the historical environment information and historical target information into several segments, and inputting them into the LSTM model as training samples. ST3, the LSTM model extracts features and predicts each segment to obtain a predicted segment. ST4, comparing the predicted segment with the next segment corresponding to the current segment, and calculating a loss function. ST5, optimizing the parameters of the LSTM model according to the loss function. ST6, repeating steps ST3-ST5, the LSTM model updates the parameters each time a predicted segment is obtained, until the parameters of the LSTM model converge or the number of parameter updates reaches a set threshold, and a trained LSTM model is obtained.

[0042] The prediction model can be deployed locally on the controller 102 or on a remote cloud server. In an embodiment where the local computing power of the controller 102 is insufficient, the prediction model is preferably deployed on a cloud server, and the controller 102 obtains the prediction conditions by calling the interface of the prediction model.

[0043] The optimal beam determination module E3 is used to execute step SE3: determine the optimal beam according to the prediction condition.

[0044] Specifically, step SE3 is: determine the direction and coverage of the optimal beam according to the future target information in the prediction condition, and eliminate the interference source according to the future environment information in the prediction condition, so as to determine the optimal beam. The future target information in the prediction condition shows the future position, speed and moving direction of the target device 200. The direction range (angle range) of the optimal beam can be determined according to the future position of the target device 200, and the shape coverage of the optimal beam can be determined in combination with the future speed and moving direction of the target device 200. The predicted environment information in the prediction condition shows the future electromagnetic environment. According to the predicted environment information, the direction and shape of the optimal beam can be further optimized to avoid interference sources and occupied frequency bands in the environment.

[0045] The phase calculation module E4 is used to execute step SE4: solving the phase offset value of each antenna unit according to the optimal beam.

[0046] The relationship between the final synthesized beam of the phased array antenna and the phase offset value of each antenna unit depends on the geometric arrangement of the antenna array. Take a phased array array with multiple antenna units arranged linearly at equal intervals as an example, the distance between two adjacent antenna units is d, and the transmission angle between two adjacent antenna units is θ m When the time delay of the electromagnetic wave signal is τ m, the phase difference of the transmitted signals of two adjacent antennas is According to the geometric relationship, it can be deduced:

[0047] Where λ represents the wavelength of the electromagnetic wave signal.

[0048] The number of antenna units is N, and the distance d between each antenna unit is set to λ / 2. m The beam direction of the phased array array is the corresponding phase shift of the nth antenna element It is expressed as:

[0049]

[0050] The output signal y(t) is equal to the weighted sum of the products of each input signal x(t) and the phase shifter, expressed as:

[0051] Where x 0 (t) represents the first input signal, w n Represents the weight of the phase shifter, weight

[0052] Substituting the optimal beam as the final synthesized output signal y(t) of the phased array antenna into the above relationship, the phase offset value of each antenna unit corresponding to the optimal beam can be reversely solved.

[0053] In phased array arrays with other geometric arrangements, there is also a definite relationship between the beam finally synthesized by the phased array antenna and the phase offset value of each antenna unit. A person skilled in the art can derive the relationship formula between the final output beam and the phase offset value through mathematical operations, thereby solving the phase offset value of each antenna unit according to the optimal beam. Based on this, step SE4 is specifically as follows: according to the geometric arrangement of the phased array antenna, obtain the relationship formula between the output beam and the phase offset value of each antenna unit; substitute the optimal beam as the output beam into the relationship formula, and solve the phase offset value of each antenna unit corresponding to the optimal beam.

[0054] The antenna control module E5 is used to execute step SE5: control the phase of the signal transmitted by each antenna unit according to the phase offset value, so that the MIMO phased array antenna system 101 outputs an actual beam.

[0055] Furthermore, the controller 102 also includes a real-time monitoring module J, which is used to execute step SJ: real-time monitoring and correction of the actual beam. Specifically, step SJ includes: SJ1, monitoring the actual beam, and calculating the difference function between the actual beam and the optimal beam. The difference function can be defined as the mean absolute error (MAE), mean square error (MSE) or root mean square error (RMSE) between the actual beam and the optimal beam. SJ2, correcting the phase offset value in the direction of the gradient descent of the difference function. SJ3, controlling the phase of the signal transmitted by each antenna unit according to the corrected phase offset value, thereby correcting the actual beam in real time.

[0056] The improved beamforming method of the present invention improves the quality of millimeter wave communication from multiple angles: 1. The present invention fully considers environmental information, can actively avoid interference sources and occupied frequency bands according to environmental information, and improves the stability of millimeter wave communication; 2. The present invention considers the future change trend of environmental information and target information, can predict future environmental information and future target information, and generate millimeter wave beams based on future environmental information and future target information, thereby improving the pertinence of beamforming, and can focus signal energy near the target device even if the target device is in motion, thereby improving the quality of the target device receiving the signal; 3. The present invention can also monitor the output beam in real time, and automatically correct the actual beam according to the difference between the actual beam and the optimal beam, thereby improving the accuracy of beam control. Through the above technical means, the present invention overcomes the problems of high propagation loss and easy signal blocking in existing millimeter wave communication, and better exerts the advantages of high bandwidth, low latency and high transmission rate of millimeter wave communication, and is suitable for application in the field of high-fidelity audio transmission with high requirements for signal transmission quality.

[0057] The above-mentioned embodiments only express several implementation methods of the present invention, and the description is relatively specific and detailed, but it cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, and the present invention is also intended to include these modifications and modifications.

Claims

1. A beam forming method for a phased array antenna, It is characterized in that Includes steps: SE1, obtains the current environment information and the current target information of the target device; SE2, predicting future environment information and future target information according to the current environment information and current target information to obtain prediction conditions; SE3, determining an optimal beam according to the prediction condition; SE4, solving the phase offset value of each antenna unit according to the optimal beam; SE5, controlling the phase of the signal transmitted by each antenna unit according to the phase offset value, so that the phased array antenna outputs an actual beam.

2. The beam forming method of the phased array antenna according to claim 1, Features: Step SE2 is specifically as follows: using a prediction model, based on the current environment information and current target information, predict the future environment information and future target information to obtain prediction conditions; the prediction model is a machine learning model, which is trained by historical environment information and historical target information, and is used to predict future environment information and future target information based on the current environment information and current target information.

3. The beam forming method of the phased array antenna according to claim 2, Features: The prediction model is an LSTM model; The LSTM model is trained using the following training method: ST1, obtain historical environment information and historical target information; ST2, dividing the historical environment information and the historical target information into several segments and inputting them into the LSTM model as training samples; ST3, the LSTM model extracts features and predicts each segment to obtain a predicted segment; ST4, comparing the predicted segment with the next segment corresponding to the current segment, and calculating a loss function; ST5, optimizing the parameters of the LSTM model according to the loss function; ST6, repeat steps ST3-ST5, and the LSTM model updates parameters every time a prediction fragment is obtained, until the parameters of the LSTM model converge or the number of parameter updates reaches a set threshold, and a trained LSTM model is obtained.

4. The beam forming method of the phased array antenna according to claim 1, Features: Step SE3 specifically includes: determining the direction and coverage of the optimal beam according to the future target information in the prediction conditions, and eliminating interference sources according to the future environment information in the prediction conditions, thereby determining the optimal beam.

5. The beam forming method of the phased array antenna according to claim 1, Features: Step SE4 is specifically as follows: according to the geometric arrangement of the phased array antenna, a relationship formula between the output beam and the phase offset value of each antenna unit is obtained; the optimal beam is substituted into the relationship formula as the output beam, and the phase offset value of each antenna unit corresponding to the optimal beam is solved.

6. The beam forming method of the phased array antenna according to claim 1, Features: The method also includes the step: SJ, real-time monitoring and correction of the actual beam.

7. The beam forming method of the phased array antenna according to claim 6, Features: Step SJ specifically includes: SJ1, monitoring the actual beam and calculating a difference function between the actual beam and the optimal beam; SJ2, correcting the phase offset value in the direction of the gradient descent of the difference function; SJ3, controlling the phase of the signal transmitted by each antenna unit according to the corrected phase offset value, thereby correcting the actual beam in real time.

8. A millimeter wave based signal transmitting device, It is characterized in that include: MIMO phased array antenna systems and controllers; The MIMO phased array antenna system includes a plurality of antenna units arranged in a preset array; The controller controls the millimeter wave beam ultimately output by the signal transceiver by controlling the phase of the signal transmitted by each antenna unit; Wherein, the controller includes the following modules: An information acquisition module is used to obtain current environment information and current target information of the target device; A prediction module, used to predict future environment information and future target information according to the current environment information and current target information, and obtain prediction conditions; An optimal beam determination module, used to determine an optimal beam according to the prediction condition; A phase calculation module, used to solve the phase offset value of each antenna unit according to the optimal beam; The antenna control module is used to control the phase of the signal transmitted by each antenna unit according to the phase offset value.

9. The millimeter wave based signal transmitting device according to claim 8, Features: The prediction module is specifically a prediction model; the prediction model is a machine learning model, which is trained by historical environmental information and historical target information, and is used to predict future environmental information and future target information based on current environmental information and current target information.

10. A millimeter wave based signal transmission system, It is characterized in that include: Launch equipment and target equipment; The transmitting device transmits a millimeter wave beam to the target device, thereby wirelessly communicating with the target device; Wherein, the transmitting device is the millimeter wave based signal transmitting device as described in claim 8 or 9.

Images