A Mobile Wireless Energy Transfer Method Based on Channel State Information Clustering

Abstract

The present invention discloses a mobile wireless energy transfer method based on channel state information clustering. The method includes: at the staying positions of the user's moving trajectory, the base station transmits wireless energy supply frames; the user terminal estimates the wireless channel state information based on the received pilot symbols and collects channel matrix sample data; the base station stratifies based on the channel matrix sample data set and performs channel state information clustering in each layer, so as to obtain a plurality of representative channel matrix templates and the corresponding relationship between precodings in different time periods in the indoor environment; when the base station performs energy transfer, energy transfer is performed based on the wireless energy transfer frames, wherein the wireless energy transfer frames are sent in a precoding manner, and the precoding is obtained based on the corresponding relationship between a plurality of channel matrix templates and precodings. The present invention improves the harvesting efficiency of long-distance energy transfer and solves the problem of waste of pilot symbols under large-scale antennas.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and more specifically, to a mobile wireless energy transfer method based on channel state information clustering. Background Art

[0002] Wireless Power Transfer (WPT) technology is a technology that transfers energy to a receiver via radio waves. This technology can be used for various applications, including charging and energy replenishment of devices such as smartphones, wireless sensors, medical devices, and drones.

[0003] In recent years, with the rapid development of technologies such as the Internet of Things and smart homes, WPT technology has been further developed. New WPT technologies include wireless energy transfer implemented based on technologies such as magnetic resonance, radio frequency identification, microwave, and laser. The working principle of radio frequency wireless energy transfer technology is that the energy signal transmitted by the transmitting end experiences attenuation such as atmospheric loss or occlusion loss in space and then is received by the receiving end module. As Figure 1 shown, the direct current electrical energy is converted into radio frequency energy after power amplification, sent to the rectenna on the transmitting antenna, and finally the electrical energy is converted by the rectification and filtering circuit at the receiving end.

[0004] In practical applications, WPT technology also faces some challenges, such as transmission efficiency, transmission distance, security, etc. To solve these problems, researchers are developing new technologies or improving existing technologies to further improve the efficiency and security of WPT technology. Existing wireless energy transfer schemes usually rely on pilots. A pilot is a known signal transmitted in a communication channel, generally sent from the transmitting end to the receiving end in advance so that the receiving end can perform phase correction and channel estimation on the received signal. In energy transfer, pilots can be used to determine the phase and frequency of the signal, thereby improving the efficiency and reliability of energy transfer.

[0005] For example, the literature (M. Tang, H. Cui, and C. L. Law, “A Survey of Wireless Power Transfer Via Magnetic Resonant Coupling,” IEEE Trans. on Industrial Electronics, vol. 64, no. 11, pp. 8693 - 8705, Nov. 2017) proposed an energy transfer scheme based on a multiple-input multiple-output (MIMO) system, which uses pilots to correct the phase deviation of the mobile receiving end and improves the transmission efficiency by optimizing the pilot sequence. On the other hand, some researchers have proposed wireless energy transfer schemes based on reflected signals.

[0006] Upon analysis, the existing technologies mainly have the following defects:

[0007] 1) Currently, in the single-user mobile scenario, the energy transfer scheme of the wireless energy transfer system usually has problems of low wireless energy transfer efficiency and mobility limitations. On the one hand, the wireless energy receiver needs to convert the signal power received from the radio frequency antenna into usable DC power, but the actual power conversion efficiency is usually very low (such as less than 10%) and is non-linear. Therefore, realizing the "causality" constraint of wireless energy in the wireless energy transfer system is an important challenge. On the other hand, in order to improve the energy harvesting efficiency of the receiver, a multi-antenna wireless energy transfer system can be adopted, but this system requires relatively accurate channel information for precoding. Obtaining the MIMO channel state information usually requires time-division pilot transmission, which takes a long time, resulting in a reduction in the time for transmitting wireless energy in a system operation frame and significantly reducing the time transfer efficiency of wireless energy.

[0008] 2) Currently, the pilot-based scheme is sensitive to the position and direction of the receiver and requires precise positioning and alignment of the receiving end. When the position of the mobile receiver changes, it may cause the energy transfer to be interrupted. Therefore, the pilot-based wireless energy transfer scheme still needs further improvement to improve the transfer efficiency and reliability to meet the energy transfer requirements of users in the mobile scenario.

[0009] In summary, for the existing wireless energy transfer schemes, due to the relatively fast channel changes in the mobile scenario, the transfer efficiency is low and it cannot well meet the energy transfer requirements of devices during movement. In addition, due to the limitation of the energy transfer distance, the energy transfer efficiency of long-distance devices is low. Summary of the Invention

[0010] The object of the present invention is to overcome the above-mentioned defects of the existing technologies and provide a mobile wireless energy transfer method based on channel state information clustering. The method includes the following steps:

[0011] At the staying positions of the user's mobile trajectory, the base station sends a wireless power supply frame, where the wireless power supply frame includes a preamble symbol, multiple pilot symbols, and multiple data symbols. The preamble symbol is used for the user side to perform frame synchronization, the pilot symbols are used for the user side to perform channel estimation, and the data symbols are used for the user side to perform energy rectification;

[0012] The user side estimates the wireless channel state information based on the received pilot symbols and collects channel matrix sample data;

[0013] The base station side stratifies based on the channel matrix sample data set, and performs channel state information clustering on each layer, so as to obtain a plurality of representative channel matrix templates and the corresponding relationship between precodings in different time periods in the indoor environment, where each layer represents a subcarrier group;

[0014] When the base station side performs energy transmission, it performs energy transmission based on the wireless energy transmission frame, where the wireless energy transmission frame is sent in a precoding manner, and the precoding is obtained based on the corresponding relationship between a plurality of channel matrix templates and precodings.

[0015] Compared with the prior art, the advantages of the present invention are that it designs a mobile radio frequency energy transmission method based on channel state information clustering, which can be flexibly applied to radio frequency energy transmission in a single user terminal mobile scenario, and provides energy guarantee for low-power user terminals (such as sensors). And the present invention uses a multi-antenna wireless energy transmission system to improve the harvesting efficiency of long-distance energy transmission, and solves the problem of pilot symbol waste under large-scale antennas.

[0016] Through the following detailed description of the exemplary embodiments of the present invention with reference to the accompanying drawings, other features and advantages of the present invention will become clear. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings incorporated in the specification and constituting a part of the specification illustrate embodiments of the present invention and, together with the description, are used to explain the principles of the present invention.

[0018] Figure 1 is a schematic diagram of radio frequency wireless energy transmission in the prior art;

[0019] Figure 2 is a schematic diagram of the structure of a wireless power supply frame sent by the base station side according to an embodiment of the present invention;

[0020] Figure 3 is a schematic diagram of the system architecture of a wireless energy transmission scheme according to an embodiment of the present invention;

[0021] Figure 4 is a schematic diagram of the structure of a wireless energy efficient transmission frame according to an embodiment of the present invention;

[0022] Figure 5 is a schematic diagram of wireless energy transmission in a user terminal mobile scenario according to an embodiment of the present invention;

[0023] Figure 6 is a schematic diagram of the base station side sending time-division pilots according to an embodiment of the present invention;

[0024] Figure 7 is a schematic diagram of channel matrix collection and processing according to an embodiment of the present invention;

[0025] Figure 8 It is a schematic diagram of a sample data hierarchical model according to an embodiment of the present invention;

[0026] Figure 9 It is a process schematic diagram of a wireless energy transmission method according to an embodiment of the present invention;

[0027] Figure 10 It is a schematic diagram of an indoor mobile experimental environment according to an embodiment of the present invention;

[0028] Figure 11 It is a schematic diagram of single-frame energy comparison according to an embodiment of the present invention; [[ID=1�]]

[0029] Figure 12 It is a performance schematic diagram of an energy transmission scheme according to an embodiment of the present invention. Detailed implementation manners

[0030] Now, various exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. It should be noted that: Unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions and values set forth in these embodiments do not limit the scope of the present invention.

[0031] ] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way a limitation on the present invention and its application or use.

[0032] Techniques, methods, and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, the techniques, methods, and devices should be regarded as part of the specification.

[0033] In all the examples shown and discussed herein, any specific values should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values.

[0034] It should be noted that: Like reference numerals and letters denote like items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0035] The purpose of the present invention is to address the problem of low wireless energy transmission efficiency in wireless energy transmission systems caused by frequent pilot signal transmission from the base station when a single user terminal moves between different indoor locations. Compared to wireless RF energy transmission in a stationary state, mobile scenarios require consideration of factors such as changes in the wireless channel and the user terminal's movement speed. Therefore, it is necessary to design corresponding energy transmission strategies to improve transmission efficiency and stability. In addition, in mobile scenarios, it is also necessary to consider the user's requirements for the portability and flexibility of mobile devices. Therefore, it is necessary to design a lightweight, low-power, and easy-to-integrate wireless energy transmission solution.

[0036] In this invention, the base station is configured not to transfer energy when the user moves, thus avoiding the extensive computation required for mobile channel estimation. For example, the user's predetermined trajectory is pre-divided into multiple locations. As the user moves along the predetermined trajectory, it briefly stops at each fixed point along the path to exchange energy with the base station, then continues to the next location until the entire predetermined trajectory is completed. This design enables energy transfer from the base station to the mobile user.

[0037] In this scenario, each time the user terminal moves to a new location, the traditional energy transmission scheme is no longer used (that is, the base station first sends a pilot signal at the new location, and the user terminal then uses real-time channel estimation to obtain the channel state information matrix and feeds it back to the base station via the uplink. The base station calculates the precoding based on this channel matrix). Instead, the previously collected channel state information data set is first clustered offline to obtain a channel matrix template, and then the channel matrix template is used to calculate the precoding. This eliminates the need for the base station to spend time sending a large number of pilot signals for channel estimation when the user terminal moves frequently. The time originally used to send pilot signals is used to send energy, which increases the energy signal transmission time and solves the problem that the user terminal cannot maximize the received energy along the moving trajectory.

[0038] In summary, the mobile wireless energy transmission method based on channel state information clustering provided by the present invention first designs a wireless energy supply frame structure in the wireless energy transmission system, such as Figure 2 As shown, the wireless power supply frame consists of a preamble symbol, multiple pilot symbols, and multiple data symbols. Based on this frame structure, the base station first transmits the pilot symbol, allowing the user end to perform channel estimation operations to calculate channel state information and obtain the channel matrix within the coherence time of the frame. Wireless power supply frames are transmitted at different time points, and the user end collects channel matrix sample data for each frame in real time.

[0039] Next, combine Figure 3As shown, a channel state information denoising algorithm is proposed. The collected channel matrix sample data is preprocessed to remove abnormal data during the channel sample collection process, so as to avoid affecting the performance of subsequent clustering operations.

[0040] After completing the denoising preprocessing operation on the channel matrix, a wireless energy transfer scheme based on channel matrix clustering is further proposed. This scheme first stratifies the collected channel matrix sample data set, then performs channel state information clustering on each layer, and finally obtains multiple representative channel matrix templates at different time periods in the indoor environment. When the base station performs energy transfer, the channel matrix template is used instead of sending pilots.

[0041] Finally, when the base station performs energy transfer in the indoor environment, a wireless energy efficient transmission frame without pilot symbols is redesigned. As Figure 4 shown, for the energy symbols in the frame structure, the precoding is directly calculated using the channel matrix obtained after clustering.

[0042] In the following, the design of the energy transfer scheme in the indoor user terminal movement scenario will be specifically introduced. This is mainly because the channel state information in the indoor environment tends to be stable and has a low change amplitude at each time period.

[0043] As Figure 5 shown, in the indoor environment, the user terminal moves between multiple positions along a predetermined trajectory and stays briefly at each fixed position. The user terminal initially stays at position loc A . In this research scenario, the base station knows the movement trajectory of the user terminal and the position coordinates of the stays at each position. The base station only sends energy to the user terminal when it stays, and the user terminal does not receive energy during movement. Considering that the battery carried by the user terminal mobile device just meets the energy requirement for the user terminal to move along the predetermined trajectory, the radio frequency energy obtained by the user terminal from the base station is only used for energy collection.

[0044] When the base station transmits energy to the user terminal staying at a fixed position, since the energy transfer does not require modulation and demodulation, it is less sensitive to the channel state. Considering that the user terminal moves between multiple positions in a relatively stable indoor channel environment, the present invention proposes a wireless energy transfer scheme based on channel matrix clustering to solve the problem of low energy reception efficiency of the mobile user terminal.

[0045] The present invention has been verified on a system platform based on software radio. The total bandwidth of the system platform is 30 MHz, where the upper and lower frequency bands of 12 MHz are guard bands, and the actual effective working frequency band is the middle 18 MHz. The system is based on orthogonal frequency division multiplexing (OFDM) technology, drawing on the LTE standard, with the OFDM subcarrier spacing Δf = 15 KHz and the number of OFDM subcarriers being 1200. In the system, the base station side is configured with 32 transmit antennas, and the user side is configured with 2 receive antennas.

[0046] The energy transfer from the base station side to the user side is completed through the transmission of radio frequency signals between the antennas at the transceiver ends. The terminal device is empowered by sending a continuous frame sequence from the base station as the carrier of the radio frequency signal. As Figure 2 shown, first, drawing on the frame structure of LTE, a wireless energy frame sequence structure is designed, and the generated wireless energy frame sequence is sent from the 32 - antenna array at a carrier frequency of 1.2 GHz.

[0047] Figure 2 The length of one frame in frame is T

[0048] = 3 milliseconds (ms), which contains a total of 42 OFDM symbol positions (Symbols). The time length of each symbol position is approximately 0.07 ms. The first symbol position is the preamble symbol position for user - side synchronization; the base station sends pilot symbols in the 2nd to 33rd symbol positions so that the user side can accurately estimate the complete wireless channel state information The complete wireless channel matrix can be represented by a large - scale three - dimensional matrix with a dimension of 32×2×1200. For example,

[0049]

[0050] Among them, for and H i,j is a complex column vector with a dimension of 1200×1. H i,j represents the complex channel state information from the i - th transmit antenna at the base station side to the j - th receive antenna at the user side on all 1200 subcarriers.

[0051] In order for the user side to accurately construct the complete channel matrix the base station side needs to ensure that the user side can accurately obtain the channel state information H between each pair of transmit and receive antennas i,j. To avoid signal interference between different transmitting antennas, the base station can adopt a time-division pilot method, allowing 32 transmitting antennas to sequentially transmit pilot signals at different OFDM symbol positions. In each frame, the pilot signals occupy the 2nd to the 33rd OFDM symbol positions, a total of 32 positions. As Figure 6 shown, at the (i + 1)-th OFDM symbol position, where i ∈ {1, …, 32}, only the i-th transmitting antenna transmits the pilot signal, and all other antennas remain silent. In this way, it can be ensured that each antenna at the user side will only receive the signal from the i-th transmitting antenna at the base station at the (i + 1)-th OFDM symbol position. Using the classic LS algorithm (Ozdemir M K, Arslan H, and Arvas E. Toward real-time adaptive low-rank LMMSE channel estimation of MIMO-OFDM systems. IEEE Transactions on Wireless Communications, 2006, 5(10): 2675 - 2678), the user side can estimate H i,1 and H i,2 . When the base station completes the transmission of the time-division pilot signal at the 33rd symbol position, the user side obtains the channel state information between all transceiver antenna pairs, thus obtaining the complete channel matrix

[0052] The 34th symbol position in the frame structure is an empty symbol, used for the user side to distinguish the pilot signal sent by the base station from the subsequent data signals. The 35th to the 42nd symbol positions are data symbol positions, used to send energy to the user side.

[0053] Under the condition that the user side's movement trajectory is known, wireless power supply frames are sent at each stop position of the user side's movement trajectory. After receiving the frame signal, the user side performs channel estimation based on the pilot symbols and calculates the channel matrix Wireless power supply frames are periodically sent from the base station to the user side to collect channel matrix sample data. Denote the set of channel matrix samples between the base station and the position loc m where the current user equipment stops as . Since the channel state information changes over time, in order to obtain rich channel state information samples, it is necessary to sample the channel matrix at the position loc m of the user side's stop at different times multiple times.

[0054]

[0055] In formula (2), the channel matrix of the user side at the position loc m is Sampling is carried out in different time periods. A total of T time periods are collected, and S consecutive frame channel estimation matrix sample data are collected within each time period. When the user equipment is at location loc m A total of T*S channel estimation matrices in this scenario are obtained At location loc m The set of sample data collected at In the and is the large-scale three-dimensional channel state matrix of dimension 32×2×1200 obtained by the user side within the t-th frame time. Let N = T*S, which represents the total number of sample data collected by the user side at loc m The total number of sample data collected at

[0056] The initial sample data collected when the user side is at location loc m is preprocessed. As can be seen from formulas (1) and (2), can be expressed as That is, when the user side stays at location loc N channel state matrix sample data are collected on all channels between the 32 transmitting antennas of the base station side and the 2 receiving antennas of the user side m when

[0057] As can be seen from formula (1), for is a complex column vector of dimension 1200×N. Since the sample data is huge, to reduce the amount of computation, the two-dimensional matrix is divided as follows according to subcarriers: The original 1200 subcarriers are divided into groups of 12 subcarriers each, and the channel estimation sample matrix of each group of subcarriers is replaced by the first subcarrier of each group. Finally, a two-dimensional matrix of 100*N

[0058] All elements in are complex elements representing channel state information, and the real part and imaginary part of the elements represent the signal strength and phase information respectively. However, the real part and imaginary part usually have different units and ranges, making it difficult to compare or intuitively understand the nature of the channel state. Converting the complex number to polar coordinate form can represent the channel state as an amplitude with a unit of dB and a phase represented by an angle, making it easier to compare the strength and phase information of different channel states and more intuitively understand the characteristics of the channel state. For The two-dimensional matrix collected at location loc m will be The 100*N complex channel state sample data elements of the form a+b*i are transformed into polar coordinates to obtain a 100*N*2 three-dimensional matrix The three-dimensional matrix The first column of elements is the angle value θ, and the second column of elements is the amplitude value r.

[0059] The three-dimensional matrix Split by column, that is, for the stop position loc m For all channels on the user equipment at , after preprocessing, two 100*N two-dimensional vector coordinate matrices can be obtained, representing the horizontal coordinates r and (subs,spl) and the vertical coordinate θ (subs,spl) , where subs∈{1,…,100},spl∈{1,…,N}, respectively represent the subcarrier grouping and the number of sample data.

[0060] Any location where the user stays loc m The sample data collection and processing process on any transmitting and receiving antenna channel at Figure 7 shown.

[0061] When the user stays at any location loc m When processing, the sample data on any transmitting and receiving antenna channel collected by the user end is used Figure 8 Interpretation. Figure 8 As shown, at each stop position, the pre-processed channel state information on any pair of transmitting and receiving antenna channels has a total of 100 levels, each level represents a subcarrier group; each level has N sample data points. Figure 8 The sample data in

[0062] Due to the influence of various interferences and signal attenuation in the wireless channel, the collected channel state matrix contains noise. Therefore, the collected sample data is first denoised. For the convenience of explanation, refer to formula (3) and use express Figure 8 The channel sample data set of each layer in , where subs∈{1,…,100}.

[0063]

[0064] Since the base station has 32 antennas and the user end has 2 antennas, the channel state information sample data collected on the 64 pairs of transmitting and receiving antenna channels between the base station and the user end will be presented as follows: Figure 8 The hierarchical relationship shown in the figure. It is necessary to denoise the sample data collected on each pair of transmitting and receiving antenna channels.

[0065] First of all, Figure 8 The sample data points in are layered denoised.Figure 8 For any layer subs ∈ {1, …, 100}, a parameter α is defined to measure whether the data points in the two-dimensional plane are at the edge position. Then, all two-dimensional coordinate edge noise points in are removed to prevent individual sample points that are too far from the main body of the sample distribution from appearing due to the influence of interference noise during the process of sample data collection.

[0066] The specific operation is to define a rectangular region (x1, x2, y1, y2) for all sample data points in each layer, where x1, x2, y1, and y2 are all two-dimensional coordinate points. Referring to formula (4), the size of the rectangular region is determined by the parameter α, where minx(), maxx(), miny(), and maxy() respectively represent the abscissa of the leftmost point, the abscissa of the rightmost point, the ordinate of the leftmost point, and the ordinate of the rightmost point in this layer. If the sample data coordinates on this layer are outside this region, then this coordinate point is deleted from the sample data set.

[0067]

[0068] Next, a secondary denoising operation is performed on all sample points within the rectangular region. When collecting samples, in order to make the sample data set fully represent the channel state information at each time period in the indoor environment, the sample data is collected in units of time periods. Considering that in the indoor environment, the channel state information usually does not change much in a short period of time. If the coordinate position of the sample data collected within a single time period is greater than a given boundary parameter β from the sample center coordinate of this time period, then this point is also considered a noise point and needs to be removed from the sample set.

[0069] The specific operation is as follows: First, calculate according to formula (5) the center point coordinates of the N two-dimensional data points (x1, y1), (x2, y2),..., (x N , y N ) in

[0070]

[0071] Then, calculate the Euclidean distance between each data point (x p , y p ) and the center point according to formula (6), and then obtain the average value d mean and the standard deviation d std .

[0072]

[0073] Given the marginal parameter β, update the two-dimensional coordinate set according to formula (7)

[0074]

[0075] The sample data sets of each layer in Figure 8 are subjected to secondary denoising processing to obtain processed data representing the channel state information. The above operations are performed offline in 64 channels.

[0076] Cluster the denoised sample data sets. Through continuous iteration, Figure 8 all samples belonging to the same cluster class in each layer are adjusted towards the direction where the sum of the distances to the cluster center of this class is minimized, and the sample points belonging to different cluster ranges are divided until the optimal K subs cluster centers of the current layer are found, where subs ∈ {1, …, 100}, and it is ensured that all samples have found the optimal cluster set they belong to.

[0077] Because in an indoor environment, the channel state is relatively stable within the same time period, as shown in formula (2), the initial cluster centers are divided according to the time period. Randomly select one of the S sample data points collected in each time period as the cluster center, and finally T initial cluster centers can be obtained. When executing the algorithm, the sample data after secondary denoising and the initial cluster centers are input simultaneously.

[0078] First, calculate the distance from each sample to each cluster center, and classify each sample into the cluster class where the cluster center closest to it is located. Since N channel sample data are collected in each subcarrier layer, each sample data point is numbered. Let the coordinates of the p-th sample be (x p , y p ), where p ∈ {1, 2, …, N}.

[0079] Let the coordinates of the q-th cluster center be (c qx , c qy ), then the distance from the p-th sample to the q-th cluster center is:

[0080]

[0081] Classify the p-th sample into the class where the cluster center closest to it is located, that is, assign it to the class where the k-th cluster center is located, where k = argmin p d p,q .

[0082] Next, calculate the mean value of all samples in each cluster class as the new cluster center. For the class where the q-th cluster center is located, assume it contains n qA sample, let the coordinates of these samples be (x q1 , y q1 ), Then the new coordinates of the clustering center are:

[0083]

[0084] Define a stopping parameter τ << 1. If the distance between the new clustering center and the previous clustering center is less than τ, then stop the iteration and output all clustering centers. Otherwise, calculate the new d p,q and (c′ qx , c′ qy ), that is, repeat the above process. Let the coordinates of the q-th clustering center at the u-th iteration be At the (u + 1)-th iteration is Then the distance change of the q-th clustering center is:

[0085]

[0086] The maximum value of the distance changes of all clustering centers is:

[0087]

[0088] If Δ (u+1) < τ, stop the iteration and output the final clustering result. During the execution of the above algorithm, update and save the numbers of all sample points belonging to the cluster of each clustering center in real time, and save them in set, where k ∈ {1, 2,..., K subs}.

[0089] Take the K subs clustering centers obtained in each layer as the channel state information template of the current layer, and complete the precoding operation of the energy signal in the system platform.

[0090] As Figure 9 shown, the energy transmission strategy from the base station side to the user side is given. At the beginning of each frame i, the base station directly sends energy using a frame signal without pilots. The base station will first receive the feedback information from the user side to determine whether the user side has moved to a new position. Since the m channel matrix templates at any position loc where the user side stays have been obtained, if the base station receives the feedback information that the user side has not moved to a new position and still stays at the current position loc m , then the base station will send the first K frame energy signals again, that is, from the i-th frame to the (i + K - 1)-th frame, respectively using the m channel matrix templates at the current staying position loc Calculate the precoding matrix using a channel matrix template where According to this scheme, the base station sequentially precodes the energy symbols in the wireless energy-efficient transmission frame and maps them to the RF antennas for transmission. If the base station receives feedback that the user terminal has moved to a new location, then the base station will re-execute the above process.

[0091] When the user terminal stays at location loc m and receives energy, assume that the user terminal is currently receiving the (i - 1)-th frame sent by the base station. After frame synchronization, the user terminal calculates the DC energy value collected from the (i - 1)-th frame where and sequentially records the DC energy values received in the next K frames and the channel matrix template numbers they use, saves the channel matrix number maxval of the frame with the maximum energy among them, maxval ∈ {1, 2... K}, and feeds it back to the base station. After sending the first K frame energy signals, the base station will receive the channel matrix number maxval of the frame with the maximum energy in the first K frames fed back by the user terminal. Then, before the user terminal moves to a new location, the base station always uses the maxval-th channel matrix template to calculate the precoding required for the energy transmission frame, achieving maximum energy transfer to the current location loc where the user terminal stays m of the user terminal.

[0092] During the process of the user terminal receiving energy, it will real-time feed back its location loc m and the channel matrix template number maxval that is most suitable for energy transmission at this point to the base station. After processing the (i - 1)-th frame, the user terminal starts to process the i-th frame. The user terminal updates its battery power at the start of the i-th frame, and then the base station and the user terminal continue to perform the operations of the i-th frame according to the above operations.

[0093] To further verify the effectiveness of the present invention, actual experimental results are demonstrated. The results show that the present invention can achieve a high energy transfer efficiency in a wireless power supply system under indoor stable channel conditions.

[0094] 1) Experimental environment

[0095] The experiment was carried out as Figure 10It is carried out in the indoor environment shown, where 4 eight-antenna array panels are symmetrically placed on both sides of the base station cabinet. All antenna array panels are oriented towards the user side. When the base station transmits signals with 32 antennas, the power at the center point of each eight-antenna array is measured to be approximately 1.5 watts (W) with a spectrum analyzer. Due to signal attenuation, the signal power measured at a distance of 50 cm from the base station cabinet is approximately 0.2 W. The omnidirectional rod antenna of the user equipment is extended through an adapter cable and is bound to the DJI remote control vehicle with a pre-written movement trajectory program. The receiving antenna is bound to the DJI remote control vehicle at a vertical angle, and the remote control vehicle is controlled by the pre-written trajectory program built into the body and moves between the stop points on the horizontal plane. In Figure 10 the indoor environment shown, it moves cyclically along points A, B, and C and observes the energy reception status of the user side. The distances of points A, B, and C from the base station are 4 meters, 5 meters, and 6 meters respectively.

[0096] 2) Experimental results

[0097] It can be seen from the experimental results that wireless energy transmission can still be carried out when the user side is moving, supporting various operations of the user side and maintaining the normal working state of the terminal equipment.

[0098] In Figure 10 the indoor mobile experimental environment, the distances of points A, B, and C from the base station are 4 meters, 5 meters, and 6 meters respectively. In Figure 11 it, in the indoor environment, the DC energy amplitude of a single frame received by the user side when the base station side uses different frame structures and precoding matrices to send energy to the user side is shown at points A, B, and C respectively, where Figure 11 (a) corresponds to the distance at point A, Figure 11 (b) corresponds to the long distance at point B, Figure 11 (c) corresponds to the short distance at point C.

[0099] Figure 11The comparative experimental results are shown. Among them, Curve 1 is the magnitude of the DC energy of a single frame received at the receiving end when the base station no longer adopts the precoding scheme. It can be seen that although the precoding scheme is no longer adopted, the amplitude of the energy received by the user terminal is relatively low. However, thanks to the high-power signal output of the base station, the received energy signal can still reach the receiving energy threshold of the receiving end. Curve 2 is the DC energy obtained by the user terminal when receiving a single RF frame when a large number of OFDMs are used to carry pilots for energy transmission in the traditional way. For Curve 1, although precoding is not adopted, all OFDM symbols in its frame structure are used to transmit energy signals. For Curve 2, the precoding is calculated using the channel state information obtained by the pilots, which improves the received amplitude of the energy signal at the user terminal. However, due to a large number of OFDMs being occupied by pilots, the performance is still low. Curve 3 is the amplitude of the energy transfer of the precoding signal after channel matrix clustering proposed by the present invention. This scheme can maintain a high energy transfer efficiency for a long time without sending pilots.

[0100] Figure 12 It reflects the actual battery energy change of the user terminal after the antenna of the user terminal is bound to the mobile terminal when the mobile terminal makes three rounds of cyclic movement at points A, B, and C and performs energy transmission with the base station at each point.

[0101] In summary, in the current mobile wireless energy transmission system, due to the change of the position of the mobile terminal, the base station continuously sends pilots to the user terminal to obtain the changing channel state information, thus wasting the energy transmission time. And due to the relatively fast channel change and the limitation of the energy transmission distance in the mobile scenario, the energy transfer efficiency of the existing wireless energy transmission scheme is relatively low and cannot well meet the energy transfer requirements of the device during movement. To ensure the maximum energy transmission and avoid excessive energy transmission time occupied by channel estimation, the present invention uses fixed-point sample data capture and clustering processing, enabling the transceiver to not need to perform channel estimation frequently, thereby improving the energy reception efficiency of the user terminal and optimizing the "time - energy" transfer efficiency. And the present invention can enable the user terminal to receive RF energy at different positions for battery charging, improving the time transfer efficiency of wireless energy.

[0102] The present invention can be a system, a method, and / or a computer program product. The computer program product can include a computer-readable storage medium having thereon computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0103] A computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. A computer-readable storage medium may be, for example, but is not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disc (DVD), a memory stick, a floppy disk, a mechanically encoded device such as a punched card or raised structures in grooves having instructions stored thereon, and any suitable combination of the foregoing. The computer-readable storage medium as used herein is not construed as being a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., an optical pulse through an optical fiber cable), or an electrical signal transmitted through a wire.

[0104] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to various computing / processing devices, or downloaded to an external computer or external storage device through a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include a copper transmission cable, an optical fiber transmission, a wireless transmission, a router, a firewall, a switch, a gateway computer, and / or an edge server. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in each computing / processing device.

[0105] The computer program instructions for performing the operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages such as Smalltalk, C++, Python, etc., and conventional procedural programming languages such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider). In some embodiments, by using the state information of the computer-readable program instructions to customize an electronic circuit, such as a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA), the electronic circuit can execute the computer-readable program instructions to implement various aspects of the present invention.

[0106] Aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0107] These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that the instructions, when executed by the processor of the computer or other programmable data processing apparatus, create a means for implementing the functions / acts specified in one or more blocks of the flowchart illustrations and / or block diagrams. These computer-readable program instructions may also be stored in a computer-readable storage medium that causes a computer, a programmable data processing apparatus, and / or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises a manufacture including instructions for implementing various aspects of the functions / acts specified in one or more blocks of the flowchart illustrations and / or block diagrams.

[0108] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices, causing a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other devices to generate a computer-implemented process, such that the instructions executed on the computer, other programmable data processing apparatus, or other devices implement the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0109] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two consecutive blocks may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block of the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, implementation by software, and implementation by a combination of software and hardware are equivalent.

[0110] The embodiments of the present invention have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of the terms used herein is intended to best explain the principles of the embodiments, the practical application, or the improvement of technologies in the market, or to enable other ordinary skilled persons in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A mobile wireless energy transfer method based on channel state information clustering, comprising the following steps: At the stop positions of the user terminal's moving trajectory, the base station transmits a wireless energy supply frame, where the wireless energy supply frame includes a preamble symbol, multiple pilot symbols, and multiple data symbols. The preamble symbol is used for the user terminal to perform frame synchronization, the pilot symbols are used for the user terminal to perform channel estimation, and the data symbols are used for the user terminal to perform energy rectification; The user terminal estimates the wireless channel state information based on the received pilot symbols and collects channel matrix sample data; The base station stratifies based on the channel matrix sample data set and performs channel state information clustering in each layer, so as to obtain the corresponding relationship between multiple representative channel matrix templates and precoding in different time periods in the indoor environment, where each layer represents a subcarrier group; When the base station performs energy transfer, it performs energy transfer based on the wireless energy transfer frame, where the wireless energy transfer frame is transmitted using a precoding method, and the precoding is obtained based on the corresponding relationship between multiple channel matrix templates and precoding.

2. The method according to claim 1, characterized in that The corresponding relationship between the multiple channel matrix templates and precoding is obtained according to the following steps: Perform hierarchical denoising on the collected channel matrix sample data set; Perform channel state information clustering in each layer, adjust the position of the clustering center so that the sum of the distances from all samples belonging to the same cluster class in each layer to the clustering center of this class is minimized, and divide the sample points belonging to different cluster ranges until multiple optimal clustering centers of the current layer are found and all samples have found their respective optimal cluster sets; Use the multiple optimal clustering centers obtained in each layer as the channel state information templates of the current layer to obtain the precoding corresponding to the energy signal.

3. The method according to claim 1, characterized in that, The wireless energy supply frame contains 42 symbols, where the first one is the preamble symbol, the second to 33rd ones are pilot symbols, the 34th one is empty, and the 35th to 42nd ones are data symbols.

4. The method according to claim 1, wherein The wireless energy transfer frame contains 42 symbols, where the first one is the preamble symbol, and the second to 42nd ones are data symbols.

5. The method according to claim 1, characterized in that, The transmission of the wireless energy supply frame by the base station at the stop positions of the user terminal's moving trajectory includes: The base station periodically transmits a wireless energy supply frame to the user terminal to collect channel matrix sample data; The base station samples the channel matrix at the stop positions of the user terminal at different times multiple times to construct a channel matrix sample data set.

6. The method according to claim 1, wherein It further includes: When the base station determines that the user terminal has moved to a new position, it re-obtains the precoding corresponding to the energy signal according to the corresponding relationship between the multiple channel matrix templates and precoding.

7. The method according to claim 2, wherein The hierarchical denoising of the collected channel matrix sample data set includes: Define a rectangular area for all sample data points of each layer , where are all two-dimensional coordinate points; If the sample data coordinates of a certain layer are outside this rectangular area, then delete this coordinate point from the sample data set; Perform secondary denoising on all sample data points within the rectangular area, including: if the sample data coordinate position collected within a single time period is greater than a given boundary parameter from the sample center coordinate of this time period, then consider this point as a noise point and remove it from the sample data set.

8. The method according to claim 1, wherein During the energy transmission process at the base station side, it further includes: Assume that the client is currently receiving the th frame sent by the base station. After frame synchronization, the client calculates the DC energy value collected from the th frame, and records the DC energy values received in the next frames and the channel matrix template numbers they use, and saves the channel matrix number used by the frame with the maximum energy and feedbacks it to the base station; Before the user terminal moves to a new location, the base station side uses the channel matrix template adopted by the frame signal with the maximum energy to calculate the precoding required for the wireless energy transmission frame.

9. A computer-readable storage medium having a computer program stored thereon, wherein, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 8.

10. A communication device, comprising a memory and a processor, wherein a computer program capable of running on the processor is stored on the memory, characterized in that When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 8.

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