A millimeter wave mobile communication beam management method

Abstract

A millimeter wave mobile communication beam management method belongs to the field of mobile communication technology. For millimeter wave mobile communication, the channel characteristics on the mobile trajectory are mapped to the beam configuration to match the beam adjustment with the actual environment; the beam adjustment steps based on the wide / narrow beam service coverage and the quantitative analysis and calculation steps of the system delay and system overhead; the optimization iteration steps of the beam management scheme, by weighing the system performance and system complexity, continuously iterate to obtain the appropriate system configuration; the beam training and beam tracking steps based on machine learning, complete the selection and continuous iteration of the system configuration.

Description

Technical Field

[0001] The invention relates to a millimeter wave mobile communication beam management method, belonging to the technical field of mobile communications. Background Art

[0002] Millimeter wave communications have attracted considerable interest in the past few years, thanks to the high data rates brought by their large available bandwidth. However, millimeter wave communication links are very susceptible to rapid channel changes and obstruction by obstacles, and suffer from severe free space path loss and atmospheric absorption. Although the existing millimeter wave large-scale multiple-input multiple-output system can compensate for certain propagation losses, it has huge hardware complexity and expensive hardware cost problems. In addition, due to frequent beam adjustments, the overhead and latency (initial access, switching and processing) of millimeter wave mobile communication systems are significantly increased, which greatly affects the communication quality.

[0003] Therefore, the beam at the signal transmitter and the beam at the signal receiver need to be precisely aligned to reduce propagation losses. The millimeter wave directional link consists of two parts, the initial access phase and the beam tracking phase. Fine beam alignment significantly prolongs the access process, which makes the millimeter wave link performance more sensitive. In addition, the millimeter wave beam alignment and beam tracking processes are time-consuming, which poses a major challenge in mobile communication scenarios. Generally speaking, fast initial access and beam tracking processes allocate a large amount of time-frequency resources to users in the system at the cost of increased overhead.

[0004] In the 3GPP standard, beam management mainly includes the following four basic steps:

[0005] (1) Beam scanning, that is, the synchronization signal block reference symbols of beams in different directions cover a spatial area.

[0006] (2) Beam measurement, which is to measure and compare the quality of the received signal or beam through a certain indicator (for example, signal-to-noise ratio).

[0007] (3) Beam determination, that is, selecting the appropriate beam based on the beam measurement results.

[0008] (4) Beam reporting, that is, reporting the results of beam measurement and beam determination to the wireless access network.

[0009] Existing beam training methods are divided into three categories: blind beam training, prior information assisted beam training, and beam training based on machine learning. In addition, beam tracking methods also include three forms based on Bayesian statistics, side information assisted beam tracking, and machine learning.

[0010] In order to reduce the overhead of beam training, other literature proposes an interactive learning design paradigm that fully utilizes the knowledge in the field of wireless communications and the adaptive learning capabilities of machine learning. These existing beam management solutions ignore the environmental cognition of the wireless environment, resulting in a lack of robustness in the beam tracking method. Existing beam management methods lack more consideration of the environment and do not establish a good connection between environmental cognition and beam management solutions, resulting in a lack of robustness in beam management methods. Summary of the invention

[0011] In order to overcome the deficiencies of the prior art, the present invention provides a millimeter wave mobile communication beam management method.

[0012] A millimeter wave mobile communication beam management method comprises the following steps:

[0013] For millimeter-wave mobile communications, the channel characteristics on the mobile trajectory are mapped to the beam configuration so that the beam adjustment can match the actual environment.

[0014] Beam adjustment steps based on wide / narrow beam service coverage and quantitative analysis and calculation steps for system delay and system overhead.

[0015] The optimization iterative step of the beam management solution is to continuously iterate and obtain the appropriate system configuration by balancing system performance and system complexity.

[0016] The machine learning-based beam training and beam tracking steps complete the selection and continuous iteration of system configuration.

[0017] System complexity is the product of system overhead and delay.

[0018] The system configuration includes antenna configuration and beam configuration.

[0019] A millimeter wave mobile communication beam management method further comprises the following steps:

[0020] Step 1: Identify the scene, initialize the wireless environment map, and obtain the initial feature information of the environment.

[0021] Step 2: Map the environmental channel characteristics and beam management to each other. The mapping includes two progressive meanings.

[0022] Step 3: Based on the scene characteristics and terminal location information, a standard model or formula is used to obtain the mobile communication performance in the scene, including path loss, signal-to-interference-and-noise ratio, and bit error rate.

[0023] Step 4: Correct the estimated path loss error between the data results analyzed in the actual environment and the calculation results of the standard model to obtain the actual system performance.

[0024] Step 5: When performing beam adjustment, flexibly select a suitable beam to serve the end user based on the service range of the wide beam or narrow beam.

[0025] Step 6: Based on the scenario type and optimization strategy, and in response to system performance requirements, continuously iterate to obtain the appropriate system configuration by weighing system performance and system complexity.

[0026] The technical effect of the present invention is to reduce the sensitivity of millimeter wave communication to rapidly changing channels based on environmental cognition, efficiently and flexibly adjust the beam and perform beam tracking; in millimeter wave mobile communication beam management, reduce the high system overhead and system delay caused by large-scale antenna configuration and the use of narrow beams; by balancing system performance and system complexity, reasonably select appropriate antenna configuration and beam configuration based on system requirements.

[0027] The advantage of the present invention is that by mapping the channel characteristics on the terminal movement trajectory into the beam configuration scheme, the beam adjustment is matched with the actual environment, and a more flexible beam management scheme based on environmental cognition is proposed to achieve effective beam adjustment and beam tracking to better balance system performance and system overhead.

[0028] Based on environmental awareness, the sensitivity of millimeter-wave communication to rapidly changing channels is reduced. The channel characteristics in a known environment can be used to obtain suitable beam and antenna configurations. Considering the asymmetric uplink and downlink beams, the beam configuration and antenna configuration can be adjusted efficiently and flexibly. The channel characteristics of the environment in the terminal's mobile trajectory are matched with the beam configuration scheme (establishing a good connection between environmental awareness and the beam management scheme) to better balance system performance and system complexity, select appropriate beam configuration and antenna configuration, and achieve effective beam tracking, thereby reducing the high system overhead and system latency caused by large-scale antenna configuration and the use of narrow beams in millimeter-wave mobile communication beam management. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] When considered in conjunction with the accompanying drawings, the present invention can be more completely and better understood and many of the accompanying advantages can be easily known by referring to the detailed description below, but the drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention, as shown in the figure:

[0030] Figure 1 It is a schematic diagram of the process of the present invention.

[0031] Figure 2 It is a schematic diagram of the beam management structure based on environment cognition of the present invention.

[0032] Figure 3 It is a schematic diagram of the system scenario structure of the present invention.

[0033] Figure 4 FIG. 4 is a graph comparing the number of beam adjustment of the present invention (comparison algorithm vs. proposed algorithm).

[0034] Figure 5 This is a chart comparing the system overhead and delay of the present invention (comparison algorithm vs. proposed algorithm).

[0035] Figure 6 It is a trade-off chart between the system performance (downlink bit error rate at a given position on the mobile trajectory) and the system complexity (defined as the product of system overhead and system delay) of the present invention. DETAILED DESCRIPTION

[0036] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0037] Obviously, many modifications and changes made by those skilled in the art based on the purpose of the present invention belong to the protection scope of the present invention.

[0038] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein, including technical and scientific terms, have the same meaning as generally understood by those skilled in the art.

[0039] To facilitate understanding of the embodiments, further explanations will be given below, and each embodiment does not constitute a limitation on the embodiments.

[0040] Example 1: Figure 1 , Figure 2 , Figure 3 , Figure 4 , Figure 5 and Figure 6 As shown, a millimeter wave mobile communication beam management method is used to achieve low system overhead in a millimeter wave mobile communication system.

[0041] A beam management method for millimeter wave mobile communications is a beam management process based on 3GPP standards. The overall environmental characteristics and system performance requirements of mobile communications (for example, communication continuity, quality of service (QoS), bit error rate (BER)) are comprehensively considered to achieve efficient and flexible beam management of millimeter wave mobile communications based on environmental cognition. The initial beam configuration factor can be pre-allocated according to the moving trajectory of the terminal. A higher-gain asymmetric beam configuration is used at locations with poor channel conditions in the wireless environment to flexibly switch between wide / narrow beams, thereby ultimately improving communication quality and reducing system overhead.

[0042] In a millimeter wave mobile communication beam management method, asymmetry is represented by that the beams of the uplink and downlink in the millimeter wave mobile communication are different.

[0043] For example, the base station uses a high-gain downlink narrow beam for signal transmission, and the terminal uses a downlink wide beam for signal reception; in the uplink, the terminal uses a narrow beam for signal transmission, and the base station uses a wide beam for signal reception.

[0044] like Figure 1 As shown, a millimeter wave mobile communication beam management method comprises the following steps:

[0045] Step 1: Identify the scene, initialize the wireless environment map, and obtain the initial feature information of the environment.

[0046] Step 2: Map the environmental channel characteristics and beam management to each other. The mapping includes two progressive meanings.

[0047] Step 3: Based on the scene characteristics and terminal location information, a standard model or formula is used to obtain the mobile communication performance in the scene, including path loss, signal-to-interference-and-noise ratio, and bit error rate.

[0048] Step 4: Correct the estimated path loss error between the data results analyzed in the actual environment and the calculation results of the standard model to obtain the actual system performance.

[0049] Step 5: When performing beam adjustment, flexibly select a suitable beam to serve the end user based on the service range of the wide beam or narrow beam.

[0050] Step 6: According to the scenario type and optimization strategy, and in view of the system performance requirements, the appropriate system configuration is obtained through continuous iteration by weighing the system performance and system complexity;

[0051] After weighing the system performance and system complexity obtained at this time (as an example, the system complexity is defined in the present invention as the product of system overhead and delay; the definition of system complexity also includes (1) system overhead; (2) system delay; (3) the computational complexity (computational amount) of the beam management process; (4) the amount of data stored in the beam management process; etc.), the appropriate antenna configuration and uplink and downlink asymmetric wide / narrow beams (i.e., beams with different gains and directions) are obtained through continuous iteration.

[0052] Flexible selection and continuous iteration of system configuration: Beam management based on environmental awareness can be implemented efficiently and flexibly according to the scenario type.

[0053] In actual applications, due to the configuration of large-scale antennas and a large number of high-gain narrow beams on the base station side, the online beam management process causes large system processing delays and high processing overhead. Therefore, the system performance and system complexity can be compared and weighed for different system scenario types and optimization strategies to iteratively obtain a more appropriate system configuration.

[0054] The "scenario" in step 1 of "identifying the scene, initializing the wireless environment map, and obtaining the initial feature information of the environment" is flexibly carried out according to the characteristics of the following three scenarios:

[0055] Scenario 1: Fixed track scenario (e.g. high-speed rail scenario)

[0056] In this scenario, the movement trajectory of the terminal is completely known or completely predictable. Therefore, the system performance (such as bit error rate) can be used as the optimization target to perform beam training within the complete beam range and correct the estimated path loss error. In the early stage, the trained beam configuration and antenna configuration results are predefined. When the relevant configuration is actually used later, the system performance can be guaranteed while ensuring the real-time processing of the system and reducing the overall system overhead.

[0057] Scenario 2: Semi-fixed trajectory scenario (e.g., highway scenario)

[0058] In this scenario, the movement trajectory of the terminal is basically known or basically predictable. Therefore, based on scenario 1, we can obtain prior knowledge, reduce the beam search range and beam training overhead, and reduce the system performance requirements to perform low-overhead beam training and appropriate error correction.

[0059] Scenario 3: Random trajectory scenario (e.g. pedestrian movement scenario)

[0060] In this scenario, the movement trajectory of the terminal is relatively random, so the movement trajectory can be predicted based on the terminal positioning accuracy, thereby reducing the beam search range and training overhead. At the same time, within the controllable range allowed by the processing delay, the system configuration with the most locations can be obtained based on scenarios 1 and 2.

[0061] Step 6 also includes: system overhead and system delay analysis steps,

[0062] In the entire beam management process of the millimeter wave mobile communication system, the directional link process includes two stages: initial access and beam tracking. Therefore, its system overhead and system delay are also analyzed from these two aspects.

[0063] like Figure 2 As shown, the beam management method based on environmental awareness, the frame structure and the periodic configuration of symbols are displayed.

[0064] Firstly, based on environmental information, terminal location and its moving trajectory, various channel propagation characteristics in the millimeter wave communication wireless channel are analyzed, including free space path loss, vegetation loss, atmospheric loss, etc.

[0065] Secondly, by mapping the channel characteristics on the terminal movement trajectory into the beam configuration scheme, the beam adjustment is matched with the actual environment, and beam management based on environmental cognition is implemented, including obtaining environment-adaptive uplink and downlink beam configuration vectors based on environmental cognition and saving them in a mapping table. At the same time, the system performance (including path loss, signal-to-interference-noise ratio, bit error rate, etc.) is analyzed, and then the estimated path loss error between the data results analyzed in the actual environment and the calculation results of the standard model is corrected, and the appropriate uplink and downlink asymmetric beams are flexibly selected based on the service range of the beam, and the mapping table is updated at the same time.

[0066] Then, the system performance and system complexity obtained at this time are weighed. Specifically, as the antenna configuration complexity (number of uplink and downlink antennas) increases, the system performance (for example, signal-to-noise ratio, bit error rate, QoS, etc.) and system complexity (for example, the product of system overhead and delay) are weighed.

[0067] Finally, after weighing the system performance and system complexity, the appropriate system configuration (antenna configuration and uplink and downlink asymmetric wide / narrow beams) is obtained through continuous iteration. Therefore, effective beam adjustment and beam tracking are achieved to better balance system performance and system overhead.

[0068] In the initial access phase, the downlink measurement signal is a synchronization signal block (SSB).

[0069] In the beam tracking phase, the downlink measurement signal includes the channel state information-reference signal (CSI-RS) and the synchronization signal block; the uplink measurement signal is mainly the sounding reference signal (SRS).

[0070] Therefore, according to the scheme and steps proposed in the present invention, a calculation formula for the system delay and system overhead of the millimeter wave mobile communication system is proposed as follows.

[0071] System delay calculation for mmWave beam management:

[0072] T system =T access +T tracking (1)

[0073] Where T access is the initial access delay, T tracking is the beam tracking delay.

[0074] System overhead calculation for mmWave beam management:

[0075] Ω system =Ω downlink_ref +Ω uplink_ref +Ω beam_adj (2)

[0076] Among them, Ω downlink_ref is the overhead occupied by the downlink measurement signal, Ω uplink_ref is the overhead occupied by the uplink measurement signal, Ω beam_adj It is the overhead occupied by the beam adjustment process.

[0077] By balancing system overhead and latency with system performance, appropriate antenna and beam configurations can be obtained.

[0078] A millimeter wave mobile communication beam management method includes selecting a cloud server. In mobile communications, in order to ensure the real-time and operability of the system and reduce the calculation and processing overhead on the base station side and the terminal side, some supporting technologies can be selected to improve the feasibility of the method.

[0079] As an example, a cloud server can be selected to integrate the computing resources and storage resources of the entire network or system, so that flexible selection and continuous iteration of system configuration can be carried out in the cloud server.

[0080] Wireless environment maps of various scenarios (channels) may exist on the cloud server. The wireless environment map contains information such as geographic environment information, network type and topology information, radio management policies, existing data experience (such as past measurement data and existing channel models), etc. Therefore, the interference distribution of each area can be obtained. Based on the environmental channel characteristics and interference information, the wireless environment map can predict the channel characteristics to perform active beam adjustment or switching to ensure the continuity of communication services.

[0081] In millimeter wave mobile communications, since the terminal basically remains in a mobile state, the mobile communication beam management process based on the cloud server runs continuously and obtains the optimal beam management system solution corresponding to the terminal's moving trajectory.

[0082] like Figure 3 The following is a system scenario diagram. When the terminal user moves, the millimeter wave signal may be blocked by buildings or vegetation in the terminal's moving trajectory (in this example, the vegetation blocking is mainly considered), which will cause the millimeter wave signal strength to be greatly weakened or even cause signal interruption.

[0083] See the simulation steps for a detailed description of the scenario.

[0084] Steps 3 to 5 also include the beam management process and the beam adjustment algorithm steps. For the wireless channel of millimeter wave mobile communication, this example considers three main propagation loss models, including free space propagation loss, vegetation loss in the environment, and atmospheric loss. For propagation loss, for example, the path loss model of the 3GPP standard can be used, PL(d)[dB]=61.4+20log 10 (d)+ξ,

[0085] is the distance from the base station to the terminal,

[0086] And σ SF The shadow standard deviation is 5.8dB.

[0087] For atmospheric loss, the calculation formula in ITU-R P.676-12 in 2019 can be used. Relevant parameters can be found in the literature [ITU-R, “Attenuation by atmospheric gases and related effects,” P.676-12, Aug. 2022.], and different calculation results will be obtained for different signal operating frequencies.

[0088] As described in the above references, γ atmo [dB / km] = γ o +γ w =0.1820f(N" O (f)+N” W (f)), where γ o and γ w are the attenuation caused by oxygen and water vapor, respectively, f is the operating frequency (GHz), N" O (f) and N” W (f) are the frequency-dependent imaginary parts of the complex refractive indices of oxygen and water vapor, respectively. O (f) = ∑ i(o) Si F i +N” D (f),N” W (f) = ∑ i(w) S i F i , S i is the intensity of the ith oxygen or water vapor line, F i is the shape factor of the oxygen or water vapor line, N' D (f) Drying continuum caused by pressure-induced nitrogen absorption.

[0089] For vegetation occlusion loss, the formula is used:

[0090] Lveg[dB]=Af B log 10 d tree (θ+E)G -4 ,

[0091] Where, f is the millimeter wave signal operating frequency (GHz),

[0092] d tree is the propagation distance blocked by vegetation, which can be calculated from the intersection distance between the millimeter wave signal propagation path and the vegetation in the environment.

[0093] θ is the elevation angle from the base station side transmitting antenna to the terminal side receiving antenna,

[0094] θ can be calculated based on the real-time location of the mobile terminal.

[0095] B represents the calculation parameters related to the month (time)

[0096] For relevant parameters, please refer to ITU-R, "Attenuation in Vegetation," P.833-10, Sept. 2021. As mentioned in the reference, A, E, and G are empirical parameters (when the vegetation type is cedar, A, E, and G are 1.87, 0.01, and -0.12, respectively). In the northern hemisphere, kh = |Month-6.5|, and in the southern hemisphere, kh = 6-|Month-6.5|, where Month represents the value of the month.

[0097] In the present invention, the millimeter wave mobile communication beam management algorithm based on environmental cognition can be described as follows. For a given scenario, beams of different azimuths are designed by codebook. It is assumed that the service range of the adjacent base station is not on the terminal movement trajectory assumed in this example, so its interference can be ignored. Based on environmental cognition, the environment-adaptive uplink and downlink beam configuration vectors (W, F) are obtained and saved in the mapping table.

[0098] The base station performs beam scanning in different directions and calculates the real-time signal-to-noise ratio (SNR) of the terminal trajectory point. UEi , if SNR UEi Greater than the set signal-to-noise ratio threshold SNR th (The threshold needs to be determined in advance according to the terminal service requirements), calculate the service coverage range l of the beam beami (l beami =(h BS -h UE ) / tan(θ-α 3dB ), where h BS is the base station antenna height, h UE is the height of the terminal antenna, θ is the elevation angle from the base station side transmitting antenna to the terminal side receiving antenna, and α 3dB is the half-power beam width), perform beam tracking within the beam service range, and align the beam direction on the base station side with the terminal in sequence; if SNR UEi The signal-to-noise ratio threshold SNR is set to th , the base station searches for and adjusts the appropriate beam to align the wide beam on the terminal side, and updates the environment-aware beam configuration in the mapping table.

[0099] Then, at the next moving trajectory point outside the current beam service range, determine whether the loop stop condition is met (i.e., reaching the end of the moving trajectory). If not, continue with the above steps; if the loop stop condition is met, calculate the number of beam adjustments, and calculate the system overhead and delay of the entire beam management process.

[0100] Step 6 also includes specific calculation steps for system overhead and system delay.

[0101] System delay calculation:

[0102] Supplement: Among them, T access and t 0,access Both represent the initial access delay, t CSI-RS Indicates the delay corresponding to the CSI-RS reference symbol during beam tracking, Indicates the delay corresponding to the SSB reference symbol during beam tracking.

[0103] System cost calculation:

[0104]

[0105] Supplement: Among them, Ω SS_blocks and Ω CSI-RS Indicates the overhead occupied by the downlink measurement signal SSB and CSI-RS, Ω UE is the overhead occupied by the uplink measurement signal, Ω beam_adj It is the overhead occupied by the beam adjustment process.

[0106] The detailed calculation of each part is expressed as:

[0107] R SS_blocks =N SS_blocks 4T symb 240N rep Δf (5)

[0108] R CSI-RS =N CSI N symb，csi T symb βB w (6)

[0109] R UE =4T symb N RB ·12ΔfN d (7)

[0110] R beam =t out 4T symb N CSI (8)

[0111] Among them, R ss blocks Indicates the time-frequency resources occupied by the synchronization signal block in the downlink,

[0112] R CSI-RS Indicates the time-frequency resources occupied by the channel state information in the downlink,

[0113] R UE Indicates the time-frequency resources occupied by the physical resource block in the uplink.

[0114] R beam Indicates the overhead of beam adjustment during beam management.

[0115] The specific description of the relevant parameters in the frame structure of the symbol periodic configuration in the beam management method is shown in Table 1.

[0116] Table 1. Description of relevant parameters for system delay and system overhead calculation in beam management

[0117]

[0118] It can be seen from formula (3) to formula (8) that the system overhead and delay of millimeter wave beam management are mainly related to the synchronization signal block and channel state information, the duration of communication interruption and the number of beam adjustments.

[0119] A millimeter wave mobile communication beam management method also includes a simulation step: the simulation scenario considered in this example is a weak line-of-sight scenario.

[0120] The sector cell radius of the base station is 577 meters. It is assumed that there is uneven vegetation distributed on the movement trajectory of the terminal to conform to the characteristics of random distribution of vegetation in the actual environment. For simplicity, the movement trajectory of the terminal (the distance of the trajectory is 1000 meters) is set on a straight line 300 meters away from the base station. A disturbance value is added to each position point of the terminal movement trajectory to simulate different terminal position points in actual mobile communications. In multiple simulations, the trajectory points of the terminal are slightly different. During the movement of the terminal, the alignment angle between the uplink and downlink beams changes continuously. Due to the obstruction of uneven vegetation, the length of vegetation penetration changes, and the millimeter wave signal is affected.

[0121] In the simulation step, the base station and the terminal use different antenna configurations shown in Table 2, where the antenna type is a uniform linear array (ULA) and the antenna unit is a square patch antenna. The outage probability results shown in Table 2 show that increasing the number of antenna configurations can improve communication performance. When the downlink narrow beam of the base station and the uplink wide beam used by the terminal are aligned, the system shows better performance.

[0122] Table 2. Outage probability for different antenna configurations

[0123]

[0124]

[0125] Specifically, it generates beams in multiple directions in the base station cell area by designing a beam codebook. In the method, the base station frequently adjusts the directional beam to serve the terminal at each position on the mobile trajectory.

[0126] Figure 4 The beam adjustment results of 10 simulations are shown when the base station is configured as 128-ULA (i.e., the linear array antenna has 128 antenna elements) and the terminal is configured as 128-ULA.

[0127] When the proposed beam management algorithm is used, the average number of beam adjustments is 85 times, while when the comparison algorithm is used, the average number of beam adjustments is 117 times. Therefore, when the proposed algorithm is used, the system overhead caused by beam adjustment is reduced by about 23%.

[0128] In addition, the system delay and system overhead comparison results of the beam management process are shown in Figure 5 The calculation method of system delay and system overhead proposed above can be used to perform corresponding calculation and analysis.

[0129] Among them, the system overhead includes the time and frequency resources allocated to uplink / downlink beam adjustment and beam tracking, and the system delay includes access delay and beam tracking delay.

[0130] In order to facilitate calculation and comparison, Δt is used as the basic quantization unit in the simulation when calculating the system delay.

[0131] Through calculation, the system overhead reduction rate of the proposed algorithm can reach 40%, and the system delay reduction rate is about 13%.

[0132] Therefore, overall high system overhead and latency are improved to varying degrees.

[0133] In order to better reflect the characteristics of the millimeter wave mobile communication beam management method proposed in the present invention, the results of beam management under different system configurations are simulated, such as Figure 6 As shown. As the number of uplink and downlink antennas increases, the bit error rate gradually decreases, but the system delay and system overhead increase rapidly. It can be seen that the appropriate antenna configuration and beam can be obtained by weighing the system performance (such as bit error rate) and system complexity (as an example, the system complexity is defined as the product of system overhead and delay in the present invention). For example, for some communication systems, good communication coverage may be required, and the requirements for bit error rate performance can be lowered; while for some communication systems, high communication quality may be required, and the bit error rate needs to be reduced while minimizing system overhead. Therefore, according to the actual needs of the system, the system delay and overhead can be reduced as much as possible while meeting the system performance.

[0134] As described above, the embodiments of the present invention are described in detail, but it is obvious to those skilled in the art that many variations are possible as long as they do not deviate from the inventive point and effect of the present invention. Therefore, all such variations are also included in the protection scope of the present invention.

Claims

1. A millimeter wave mobile communication beam management method, characterized in that ,Contains the following steps: For millimeter wave mobile communication, by mapping the channel characteristics on the mobile trajectory to the beam configuration, the beam adjustment is matched with the actual environment; The beam adjustment step based on the wide / narrow beam service coverage and the quantitative analysis and calculation step of the system delay and system overhead; the optimization and iteration step of the beam management scheme, by weighing the system performance and system complexity, continuously iterate to obtain the appropriate system configuration; the beam training and beam tracking steps based on machine learning, complete the selection and continuous iteration of the system configuration; it also contains the following steps: step 1, identify the scene, initialize the wireless environment map, and obtain the initial feature information of the environment; step 2, map the environmental channel characteristics with the beam management, and the mapping includes two progressive meanings; step 3, according to the scene characteristics and terminal location information, use the standard model or formula to obtain the mobile communication performance in the scene, including path loss, signal to noise ratio and bit error rate; step 4, correct the estimated path loss error between the data results analyzed in the actual environment and the calculation results of the standard model, and obtain the actual system performance; step 5, when performing beam adjustment, flexibly select the appropriate beam to serve the terminal user based on the service range of the wide beam or narrow beam; step 6, according to the scene type and optimization strategy, according to the system performance requirements, By weighing the system performance and system complexity, the appropriate system configuration is obtained through continuous iteration; the beam adjustment steps based on the wide / narrow beam service coverage and the quantitative analysis and calculation steps of the system delay and system overhead; it also includes the following steps; (1) beam adjustment steps based on the wide / narrow beam service coverage: if the real-time signal-to-noise ratio of the terminal meets the communication threshold, based on environmental cognition, according to the uplink and downlink beam configuration vectors adaptive to the environment, the service coverage of the beam is calculated, and the beam tracking is performed on the terminal within the beam service range to reduce the beam switching overhead; if the communication threshold is not met, the base station searches the beam range and adjusts the appropriate beam to align with the wide beam on the terminal side, and updates the beam configuration vector of environmental cognition; (2) quantitative analysis and calculation steps for system delay and system overhead: the system delay is quantified according to the time overhead of the two stages of beam management of the millimeter wave mobile communication system, namely the initial access stage and the beam tracking stage; and the system overhead is quantified according to the time-frequency resources of different reference symbols for uplink and downlink based on the two stages of beam management.

2. According to claim 1, a millimeter wave mobile communication beam management method is characterized in that ,The system complexity is the product of system overhead and delay, and the ,system configuration is antenna configuration and beam configuration.

3. A millimeter wave mobile communication beam management method according to claim 1, characterized in that The optimization iterative step of the beam management scheme is to obtain the appropriate system configuration through continuous iteration by weighing the system performance and system complexity; it also includes the following steps: According to the scene type fixed trajectory scene, semi-fixed trajectory scene or random trajectory scene and optimization strategy, different beam management optimization methods are adopted to reduce the beam search range and beam training overhead according to the system performance requirements, and obtain the appropriate system configuration through continuous iteration by weighing the system performance and system complexity.

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