Cell search method and device based on spatiotemporal statistical information

Abstract

The terminal performs a cell search in a wireless network. The terminal determines the best search mode and performs a cell search test based on statistical information of one or a combination of time and location. The search mode includes an adjustable combination sequence under one or more consecutive search times and non-search times. In addition, the search mode includes an increasing, decreasing or unchanged search time or non-search time derived from statistical information. The UE performs a cell search according to the search mode.

Description

[0001] Cross-references

[0002] This application claims priority to U.S. Provisional Patent Application No. 63 / 123,504, filed on December 10, 2020, and U.S. Patent Application No. 17 / 537,848, filed on November 30, 2021, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0003] Embodiments of the present invention relate generally to wireless communications and, more particularly, to a cell search procedure in a wireless network. Background Art

[0004] Cell search is a process used by a user equipment (UE) terminal to acquire time and frequency synchronization with a cell and decode the cell ID of the cell. The UE can acquire time and frequency synchronization based on a downlink reference signal from a base station.

[0005] The fifth generation (5G) new radio (NR) is a new radio developed by the 3rd Generation Partnership Project (3GPP). rd Telecommunications standards issued by 3GPP TM ) is used for mobile broadband communications to significantly improve performance indicators such as latency, reliability, and throughput. In 5G NR, cell search is based on the detection and decoding of synchronization signal blocks (SSBs), which include primary synchronization signals (PSSs), secondary synchronization signals (SSSs), and demodulation reference signals (DMRSs). During the SSB-based measurement timing configuration (SMTC) window, the UE detects the SSB. The UE can calculate the cell ID based on the information in the PSS and SSS. 5G NR further defines the steps that the UE performs after obtaining the cell ID to receive 5G cell services.

[0006] Improvements to the cell search process can benefit network operators and wireless communication users. These improvements can be applied to a wide range of multiple access technologies and the telecommunication standards that employ these technologies. Summary of the invention

[0007] In one embodiment, a method for a UE to perform a cell search in a wireless network is provided. The method includes determining a search pattern based on statistical information of search trials performed at one or both of a time and a place under a recurrent time cycle, and performing a cell search according to the search pattern. The search pattern includes a combined sequence of consecutive search times and non-search times for a configurable number of searches. In addition, the search pattern includes a search time or a non-search time that increases, decreases, or remains unchanged according to a probability derived from the statistical information.

[0008] In another embodiment, a device for wireless communication is provided, the device being a UE. The UE includes an antenna circuit, a memory, and a processing circuit coupled to the memory and performing a cell search. The processing circuit further performs: determining a search pattern based on statistical information of search trials performed at one or both of a time and a place under a repetitive time period, and performing a cell search according to the search pattern. The search pattern includes a combined sequence of continuous search times and non-search times for a configurable number of searches. In addition, the search pattern includes a search time or a non-search time that increases, decreases, or remains unchanged according to a probability derived from the statistical information.

[0009] The cell search method based on spatiotemporal statistical information proposed in the present invention can balance the demand for obtaining a cell ID and reducing UE power consumption.

[0010] Other aspects and features of the present invention will become apparent to those skilled in the art from the following description of specific embodiments read in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The present invention is described by way of example, but the examples are not limiting. In the accompanying drawings, the same references indicate similar components. It should be noted that different references to "one" or "an" embodiment of the present invention are not necessarily for the same embodiment, and the multiple references mean at least one. In addition, when describing specific features, structures or characteristics related to the embodiments, it should be claimed that whether or not explicitly described, it is within the scope of cognition of those skilled in the art to realize these features, structures or characteristics in combination with other embodiments.

[0012] Figure 1 It is a network diagram for implementing the embodiment of the present invention.

[0013] Figure 2 is a flowchart illustrating a cell search procedure performed by a UE according to an embodiment.

[0014] Figure 3A and Figure 3BA probability model that may be used by a cell search process according to some embodiments is described.

[0015] Figure 4A and Figure 4B Adaptive adjustment of a probability model according to some embodiments is described.

[0016] Figure 5 is a flow chart describing a cell search process at a given location according to an embodiment.

[0017] Figure 6 is a flowchart describing a cell search process performed by a UE according to an embodiment.

[0018] Figure 7 It is a block diagram describing wireless communication between a UE and a base station. DETAILED DESCRIPTION

[0019] In the following description, many specific details are set forth. However, it should be understood that embodiments of the present invention may be implemented without these specific details. In other embodiments, well-known circuits, structures, and techniques are not shown in detail in order not to obscure the understanding of the description. However, those with ordinary knowledge in the art will understand that the present invention may be implemented without such specific details. With the included description, those skilled in the art will be able to achieve appropriate functionality without undue experimentation.

[0020] Embodiments of the present invention provide a mechanism for a UE to perform a cell search in a wireless network. The mechanism balances the need for cell ID acquisition and reduced UE power consumption. The UE determines a search pattern based on statistical information of search trials at a given location and / or a given time. The term "search pattern" refers to a combined sequence of consecutive search times and non-search times. The term "given time" or "given time period" herein may refer to a time instant or period in a repetitive time cycle, such as a time of day, a few days of a week, etc. In each search trial, the UE determines a search pattern for performing a cell search. The UE uses statistical information of the search trial to determine parameters of the search pattern, wherein the parameters include but are not limited to: the length of each search time, the length of each non-search time, and the number of search times in the search pattern. These parameters can be configured to generate a search pattern including increasing, decreasing, or unchanged search times, and increasing, decreasing, or unchanged non-search time search patterns from start to end. The following description also mentions the term "search timer", and the UE can use the search timer to set the start time of each search time. In addition, the term "search interval" is used to indicate how often the UE performs a cell search; a longer search interval means fewer cell searches; a shorter search interval means more cell searches. The UE performs a cell search procedure during each search time. The UE does not perform a cell search during any non-search time (e.g., the UE may be in an idle or sleep state, or perform other operations that are not cell search operations).

[0021] The statistical information of the cell search is stored and maintained in a database that can be retrieved by the UE and can also be updated by the UE. The statistical information can be modeled as a probability model that indicates the probability of a successful cell search for a given location and / or a given time. The probability model represents the variation of the probability in time and / or space. When the probability is high, the UE may try to speed up cell acquisition by using a search mode that includes one or more of the following attributes: a longer search time, a shorter non-search time, a more frequent search, and more searches in the search trial. When the probability is low, the UE may try to save power by using a search mode that includes one or more of the following attributes: a shorter search time, a longer non-search time, a less frequent search, and less searches in the search trial. The UE may change some parameters in the search mode and keep other parameters unchanged. After each search trial, the UE may record the statistical information of the test results, or may maintain the probability model of a given cell within a given time interval. The statistical information may be recorded in the form of a histogram, a probability model, or other statistical representations. When the UE performs a cell search at the same location and / or the same given time period next time, the UE may utilize a statistical or probability model to determine a search pattern for a new search trial.

[0022] In one embodiment, when the probability is high, the UE may gradually reduce the length of the search time in the search mode, and when the probability is low, the UE may gradually increase the length of the search time in the search mode. In another embodiment, when the probability is getting higher, the UE may gradually search more and more frequently, and when the probability is getting lower, the UE may gradually search less and less frequently. For example, the UE may adjust the non-search time in the search mode to change the frequency of the UE search.

[0023] Cell services can vary in time and space. For example, in the initial deployment phase, 5G coverage may be more extensive in large cities than in rural areas. In addition, some 5G operators may temporarily shut down 5G base stations (e.g., gNBs) at specific times (e.g., at night) to save energy. The temporary downtime may vary depending on the service operator, operator settings, or other factors. In some areas, cell services may be provided by non-terrestrial networks (NTNs). For example, 5G satellite networks can use nonstationary satellites to provide or enhance 5G coverage. However, because the link quality is susceptible to satellite movement, cell services provided by nonstationary satellites may experience intermittent downtime.

[0024] The temporal and spatial impacts on cell service availability can occur on any wireless communication technology. Therefore, while the disclosed methods and devices and computer products implementing the methods may be described using terms typically associated with 5G or NR wireless technologies, the present invention may be applied to other multiple access technologies and telecommunication standards that employ these technologies.

[0025] Figure 1 1 is a schematic diagram of a network 100 in which an embodiment of the present invention is implemented. The network 100 is a wireless network which may be a 5G NR network. Figure 1 The number and arrangement of wireless entities (e.g., devices, base stations, etc.) shown are provided as examples. In practice, network 100 may include Figure 1 Additional wireless entities, fewer wireless entities, or differently arranged wireless entities are shown.

[0026] refer to Figure 1, the network 100 may include multiple base stations (shown as BSs), such as base stations 120a, 120b, and 120c, collectively referred to as base stations 120. In some network environments such as 5G NR networks, base stations may be referred to as gNodeBs, gNBs, etc. In alternative network environments, base stations may be referred to by other names. Base station 120 may provide communication coverage for a specific geographic area called a cell (e.g., cell 130a, 130b, or 130c, collectively referred to as cell 130). The radius of the cell size may range from a few kilometers to a few meters. The base station may communicate directly or indirectly with one or more other base stations or network entities via a wireless or wired backhaul.

[0027] The network controller 110 may be coupled to a group of base stations, such as base stations 120, to coordinate, configure, and control the base stations 120. The network controller 110 may communicate with the base stations 120 via a backhaul.

[0028] The network 100 also includes a plurality of UEs, such as UEs 150a, 150b, 150c, and 150d, collectively referred to as UEs 150. UEs 150 may be located anywhere in the network 100, and each UE 150 may be fixed or mobile. Transmissions from a UE to a base station are referred to as uplink transmissions, and transmissions from a base station to a UE are referred to as downlink transmissions.

[0029] In one embodiment, UE 150 may communicate with respective base stations 120 serving respective cells 130. UE may use cell services from more than one serving cell. For example, UE 150a may use cell 130a as its primary serving cell. Network 100 may instruct UE 150a (e.g., via base station 120a) to add cell 130c, which is unknown to UE 150a at this time, as its secondary serving cell. In response, UE 150a performs a cell search to acquire synchronization information and decode the cell ID of cell 130c.

[0030] refer to Figure 2 , Figure 5 and Figure 6Many cell search processes and methods are described. When a predefined scenario occurs, the UE can perform a cell search. Some non-limiting examples are provided below. In one scenario, the UE currently receives a low-speed cell service in a low-speed wireless network (e.g., a 4G network), and is instructed by the network to search for high-speed cell services in a high-speed wireless network (e.g., a 5G network). The UE can be in an idle state or a connected state. In other scenarios, when the UE service is out of service or a cell service needs to be added or changed, the UE can perform a cell search for cell selection or reselection. For example, the UE is currently out of service and is ready to select a cell to receive cell service. As another example, the UE detects a decrease in the signal power received in the current cell and is ready to reselect another cell. As yet another example, the UE is served by a primary cell and is instructed by the network to select a secondary cell.

[0031] Figure 2 2 is a flowchart showing a cell search process 200 performed by a UE according to an embodiment. At step 210, the UE starts a new cell search trial. Before the cell search, at step 220, the UE determines a search mode based on the statistics of the search trials for the current time period (e.g., a time of day, a weekday or a weekend, etc.) in a repetitive time cycle and / or the location of the UE. As shown in blocks 221 and 222, the search mode includes a combined sequence of consecutive search times and non-search times, and the search mode parameters include one or more of the following: the length of each search time, the length of each non-search time, and the number of searches. These parameters can be used to configure a search mode with an increasing length, a decreasing length, or a same length of search time, and / or a search mode with an increasing length, a decreasing length, or a same length of non-search time.

[0032] At step 230, the UE performs a cell search according to the search pattern, for example, by detecting a downlink reference signal during each search time. If detection and decoding are successful within the search pattern, the cell search is successful and the UE may perform subsequent operations to begin receiving cell service. If detection and decoding are unsuccessful at the end of the search pattern, the UE stops searching. At step 240, the UE may update the statistical information to incorporate the search trial results. The UE may update the statistical information of the location or time based on the results of the cell search trial. As shown in box 243, the UE may update the probability model to incorporate the search trial results. The probability model may be derived from the statistical information.

[0033] A successful search attempt may increase the probability of the UE location and / or the current time period, while an unsuccessful search attempt may decrease the probability of the UE location and / or the current time period. The cell search process 200 may be restarted when the UE performs a new call search.

[0034] Figure 3A and Figure 3B is a schematic diagram of a probability model for a given location and a given time period according to some embodiments. In one embodiment, the location of the UE may be indicated by one or more of the following: longitude and latitude, cell ID, tracking area code (TAC) of the cell, mobile network code (MNC) of the cell, and mobile country code (MCC) of the cell. The cell ID, TAC, MNC, and MCC may identify a cell in a low-speed wireless network, and the UE may attempt to obtain a cell ID in a high-speed wireless network (e.g., a 5G network) or another cell. Other location information may be inferred from location information of wireless fidelity (Wi-Fi), Bluetooth, or other networks accessible to the UE.

[0035] The given time period is a repeatable or cyclical time period; for example, a time period in a day (such as 2 pm to 11 pm every day), or every weekday. The probability model can be obtained by the UE based on assumptions, or constructed based on big data statistics of search trials performed by hundreds or thousands of UEs over a time span of days, months, or years. The probability model can be stored in a database that the UE can access online or pre-downloaded to the UE. For example, the probability model of the UE's main location (e.g., home, office, etc.) can be frequently referenced by the UE and can be downloaded to the UE's memory or storage device.

[0036] Figure 3A The histogram 300 is described by way of example. The X-axis of the histogram 300 represents a location or time, and the Y-axis represents a histogram value of a successful cell search. A histogram value above a threshold (TH) is called a high probability, and a histogram value below the threshold (TH) is called a low probability. When the probability is higher than the threshold, the UE uses a search mode comprising one or more of the following: a long search time, a short non-search time, and a more number of searches. When the probability is not higher than the threshold, the UE uses a search mode comprising one or more of the following: a short search time, a long non-search time, and a fewer number of searches. It should be understood that the probability model can be constructed in the form of a histogram or in the form of any other statistical model suitable for modeling the probability of a successful cell search for a location and / or time period.

[0037] Figure 3BThe probability model 350 is described by way of example. The probability model 350 is for a given geographical location (e.g., the location of the UE) and a given time. The X-axis of the probability model 350 represents time, and the Y-axis represents the probability of a successful cell search. Probability values ​​above a threshold (TH) are high probabilities of success, and probability values ​​below the threshold (TH) are low probabilities of success. This example illustrates that increasing probability values ​​correspond to more frequent searches in the search pattern, while decreasing probability values ​​correspond to less frequent searches in the search pattern.

[0038] In one embodiment, when the probability is on the rise (such as in regions I and II), the UE searches at an increasing frequency, and when the probability is on the decline (such as in regions III and IV), the UE searches at a decreasing frequency. The UE may use a search timer to set the time to start each search time. The search timer may be configured by the length of the search time plus the length of the non-search time (immediately following the search time). The length of the search timer indicates the frequency of the UE search. For example, the search timer in region I may be a combined sequence of {50, 40, 30, ...} time units, and the search timer in region IV may be a combined sequence of {30, 40, 50, ...} time units, where each time unit may be minutes, seconds, milliseconds, etc. That is, in region I, the first search time and the first non-search time last for 50 time units, the second search time and the second non-search time last for 40 time units, and so on. Similarly, the search timers in regions II and III may be a combined sequence of {10, 5, 2, 2, 5, 10, ...} time units, including increasing, unchanged, and decreasing search timer values ​​corresponding to changes in probability values.

[0039] In addition, Figure 3B In the example of , each search timer value in a high probability area (e.g., areas II and III) may include a shorter non-search time than in a low probability area (e.g., areas I and IV). In addition, each search timer value in a high probability area (e.g., areas II and III) may include a longer search time than in a low probability area (e.g., areas I and IV). Within each area and / or across areas, the search time may increase, remain unchanged, or decrease according to a change in the probability value, and the non-search time may increase, remain unchanged, or decrease according to a change in the probability value. In one embodiment, if the UE's resident cell changes during the search trial, the UE resets the search timer to an initial value.

[0040] Figure 4A and Figure 4BAn example is given to describe the adaptive adjustment of the probability model by the UE. The UE may update the probability model through the results of its own search trials. The results of the UE's search trials, whether failed or successful, may be used to update the probability model. The initial probability model may be based on assumptions or data aggregated from a large number of UEs over time. The UE may download or otherwise access the initial probability model and adapt it to device capabilities and / or user behavior; for example, a user of the UE may habitually turn on the UE at 9 a.m. in an underground garage with low cell signals. The UE may adaptively adjust the probability model based on the UE's past search trials.

[0041] In one embodiment, the UE may update the probability model using maximum likelihood estimation (MLE) or other statistical methods to estimate the mean μ and variance σ of the probability distribution curve. 2 . The UE may also perform machine learning to update the probability model. As described above in conjunction with FIG. 3B , when the UE identifies the highest probability time period for 5G service, a search mode of a short search timer may be applied within a time period of μ±n·σ (n is a predetermined constant), and a search mode of a long search timer may be applied outside the time period.

[0042] Figure 4A Adaptive adjustment of a probability model according to one embodiment is described. For example, the probability model for a location of a UE and a given time period may be updated over time by the results of the UE's search trials, such as 510 (day 1, as indicated by arrow 410), 520 (day 2, as indicated by arrow 420), and 530 (day 3, as indicated by arrow 430). The time period (t0-t1) represents the same time period of a day. The UE may achieve more success in cell search during a given time period (t0-t1) and update the probability model so that the probability of a successful cell search increases over time in the time period (t0-t1). The UE may use the updated probability model to determine a search pattern for the same location and time of day.

[0043] Figure 4B Adaptive adjustment of the probability model according to another embodiment is described. In the embodiment, as shown in histograms 440 and 450, the probability model for the location of the UE and a given time period can be updated over time. The UE can achieve more success in cell search during a given time period (t0-t1) and update the probability model so that the probability of successful cell search increases over time in the time period (t0-t1). The UE can use the updated probability model to determine the search mode for the same location and the same time of day.

[0044] although Figure 4A and Figure 4BThe probability model shown in is for location and time, but it should be understood that the UE may use a probability model that applies to all locations using time.

[0045] Figure 5 is a flow chart showing a cell search process 500 performed by a UE according to an embodiment. When the UE currently receives a low-speed cell service in a low-speed wireless network (e.g., a 4G network) and is instructed by the network to search for a high-speed cell service in a high-speed wireless network (e.g., a 5G network), the UE may perform the cell search process 500. The UE may perform the cell search process 500 when its service is out of service (OOS). The cell search process 500 may also be used in other scenarios.

[0046] For example, when a UE in a certain area detects its OOS, it records its location and calculates the mean, standard deviation, and number of successful / failed searches to form an OOS distribution. Different areas may have different OOS distributions. Next time, when the UE enters the same area and encounters OOS, it can initiate a recovery cell search. The UE checks the location-based OOS distribution to determine the time period to start the recovery search.

[0047] The cell search process 500 begins when the UE performs a cell search at step 510. At step 520, the UE determines whether the cell search is successful. If the cell search is successful, the UE begins receiving cell service at step 525. If the cell search is unsuccessful, at step 530, the UE determines the probability of a successful cell search at the UE's current location. If at step 540, the probability is above a threshold, at step 550, the UE determines a search mode that gradually shortens the search interval (i.e., the UE searches more frequently). If the probability is not above the threshold, at step 560, the UE determines a search mode that gradually lengthens the search interval (i.e., the UE searches less frequently).

[0048] Figure 6 6 is a flow chart of a method 600 for a UE in a wireless network to perform a cell search according to an embodiment. The UE may be Figure 1 UE 150 and / or Figure 7 Any one of the UE 700 in.

[0049] The method 600 begins at step 610, where the UE determines a search pattern based on statistical information of search trials performed at one or both of time and place in a repetitive time period. The search pattern includes a combined sequence of consecutive search times and non-search times for a configurable number of searches. The search pattern includes increasing, decreasing, or unchanged search times or non-search times based on probabilities derived from the statistical information. Then, at step 620, the UE performs a cell search based on the search pattern.

[0050] Figure 7 7 is a diagram showing that a UE 700 according to an embodiment performs a cell search based on a reference signal from a base station 750. The base station 750 may be any one of the base stations 120, and the UE 700 may be Figure 1 The base station 650 includes an antenna array for forming a beam for transmitting a downlink signal (including a reference signal for the UE 700 to perform a cell search).

[0051] As shown, UE 700 may include antenna 710 and radio frequency (RF) circuit 720, RF circuit 720 further includes a transmitter and a receiver, configured to provide wireless communication with another station (e.g., base station 750) in a wireless access network. UE 700 also includes processing circuit 730, processing circuit 730 further includes one or more control processors, signal processors, central processing units, cores and / or processor cores. In one embodiment, processing circuit 730 includes Figure 2 , Figure 5 and Figure 6 The cell search circuit 732 performs a cell search according to the method of the present invention. The UE 700 also includes a memory circuit (also referred to as a memory 740) coupled to the processing circuit 730. The UE 700 also includes an interface (eg, a user interface). It should be understood that the present invention is simplified for the purpose of illustration. Figure 7 Other hardware components may be included.

[0052] UE 700 may also be known by other names, such as a mobile station, a user unit, a wireless device, etc. UE 700 may be implemented as a part of a vehicle. Examples of UE 700 may include a cellular phone (e.g., a smart phone), a wireless communication device, a handheld device, a laptop computer, a cordless phone, a tablet computer, a gaming device, a wearable device, an entertainment device, a sensor, an infotainment device, an Internet of Things (IoT) device, or any device that can perform wireless communication in a cell (e.g., a 5G NR network or another wireless network) with access to a shared spectrum channel.

[0053] In one embodiment, the UE 700 may use non-transitory tangible computer-readable media (e.g., computer-readable media such as disks, optical disks, read-only memories, flash memory devices, etc.) and transient computer-readable transmission media (e.g., electrical, optical, acoustic or other forms of propagated signals) to store and transmit (internally and / or over a network with other electronic devices) code (composed of software instructions) and data. For example, the memory 740 may include a non-transitory computer-readable storage medium storing computer-readable program code. When the code is executed by the processor, the processor is caused to perform operations.

[0054] Although UE 700 is used as an example in the present invention, it should be understood that the methods described herein are applicable to any computing and / or communication device capable of performing wireless communication.

[0055] Figure 7 Also shown is a reference signal sent from the base station 750 to the UE 700 according to an embodiment. Figure 7 In the example shown, the base station 750 forms four beams (e.g., beam 0, beam 1, beam 2, and beam 3) in a scanning cycle, and each beam sends a synchronization signal block (SSB) in a direction different from other beams. For example, the base station 750 may send beams in the order of beam 0, beam 1, beam 2, and beam 3 (in the direction indicated by the dotted arrows) in the scanning cycle. The four beams transmit SSB1, SSB2, SSB3, and SSB4 to form an SSB burst. These beams may be cell-specific, that is, they are broadcast to the entire cell coverage area served by the base station 750. The base station 750 may periodically repeat the beam scanning operation and generate an SSB burst in each scanning cycle. The UE 700 measures the signal strength (e.g., power) of each SSB in the SSB burst and identifies the SSB with the strongest signal strength. The identified SSB index (e.g., SSB3) is used by the UE as a reference signal for determining the cell ID. It will be appreciated that the base station 750 may form a SSB burst with the cell ID. Figure 7 Different numbers of beams are shown.

[0056] Already referenced Figure 1 and Figure 7 The exemplary embodiment describes Figure 2 , Figure 5 and Figure 6 However, it should be understood that Figure 2 , Figure 5 and Figure 6 The operation of the flowchart can be performed by Figure 1 and Figure 7 and Figure 6 and Figure 7 Implementations of the invention may perform operations different from those discussed with reference to the flowcharts. Figure 2 , Figure 5 and Figure 6 The flowcharts show a particular order of operations performed by certain embodiments of the present invention, but it should be understood that such order is exemplary (for example, alternative embodiments may perform operations in a different order, combine certain operations, overlap certain operations, etc.).

[0057] Various functional components or blocks have been described herein. As will be appreciated by those skilled in the art, the functional blocks will preferably be implemented by circuits (special purpose circuits or general purpose circuits operating under the control of one or more processors and encoded instructions) which will typically include transistors configured to control the operation of the circuits according to the functions and operations described herein.

[0058] Although the present invention has been described according to a certain number of examples, those skilled in the art will recognize that the present invention is not limited to the embodiments described and can be practiced through modification and variation without departing from the spirit and scope of the appended claims. Therefore, this description should be considered illustrative rather than restrictive.

Claims

1. A method for a terminal to perform a cell search in a wireless network, comprising: The terminal records statistical information of the search trial, wherein the statistical information includes a probability model indicating a probability value of a successful cell search for each of a plurality of time units within a given location and time period; Starting a new cell search at the given location and current time, the current time being within the time period of the probability model; determining a cell search mode for the new cell search based on the probability model; The cell search mode includes one or more continuous search time and non-search time adjustable combination sequences, and The cell search mode includes increasing, decreasing or unchanged search time or non-search time derived from the statistical information; and The new cell search is performed according to the cell search mode.

2. The method for performing a cell search as claimed in claim 1, further comprising: The statistical information is updated based on the result of the cell search and the user behavior including the time and place where the user habitually turns on the terminal.

3. The method for performing cell search according to claim 1, wherein: The search time corresponding to a high success probability is longer than the search time corresponding to a low success probability, wherein the high success probability is a success probability higher than a threshold value, and the low success probability is a success probability not higher than the threshold value.

4. The method for performing cell search according to claim 1, wherein: The non-search time corresponding to a high success probability is shorter than the non-search time corresponding to a low success probability, wherein the high success probability is a success probability higher than a threshold, and the low success probability is a success probability not higher than the threshold.

5. The method for performing cell search according to claim 1, wherein: The search in the cell search mode corresponding to a high success probability is more frequent than the search in the cell search mode corresponding to a low success probability, wherein the high success probability is a success probability higher than a threshold, and the low success probability is a success probability not higher than the threshold.

6. The method for performing cell search according to claim 1, wherein: When the probability value is on an upward trend, the search is performed with an increasing frequency, and when the probability value is on a downward trend, the search is performed with a decreasing frequency.

7. The method for performing cell search according to claim 1, characterized in that: When the terminal service is interrupted, the method further includes: determining a probability of a successful cell search; and When the probability is higher than a threshold, determining the search interval to have a gradually shortened search interval, or When the probability is not higher than a threshold value, it is determined that the search interval has a gradually lengthened search interval.

8. The method for performing cell search according to claim 1, wherein: The step of determining the search mode further comprises: recording the results of the cell search test in a database accessible to the terminal; and The search pattern is determined based on the statistical information retrieved from the database.

9. The method for performing cell search according to claim 1, wherein: The statistical information is recorded as a histogram, the probability model or other statistical representations.

10. The method for performing a cell search as claimed in claim 1, further comprising: The probability model is updated using statistical methods or machine learning to evaluate a probability distribution curve calculated based on the statistical information.

11. The method for performing a cell search as claimed in claim 1, further comprising: Receiving low-speed cell service in a low-speed wireless network; as well as The cell search or cell reselection is performed in a high-speed network in an idle state or a connected state of the terminal.

12. The method for performing cell search according to claim 11, characterized in that: A given location of the terminal in the low-speed wireless network is indicated by one or more of: longitude and latitude, cell identity, tracking area code, mobile network code, and mobile country code.

13. The method for performing cell search according to claim 1, wherein: When the terminal service is interrupted or a cell service needs to be added or changed, the cell search is performed.

14. A device for performing a cell search, the device being a terminal, comprising: Antenna circuit; Memory; as well as A processing circuit is coupled to the memory to perform a cell search, and the processing circuit further performs: The terminal records statistical information of the search trial, wherein the statistical information includes a probability model indicating a probability value of a successful cell search for each of a plurality of time units within a given location and time period; Starting a new cell search at the given location and current time, the current time being within the time period of the probability model; determining a cell search mode for the new cell search based on the probability model; The cell search mode includes one or more continuous search time and non-search time adjustable combination sequences, and The cell search mode includes increasing, decreasing or unchanged search time or non-search time derived from the statistical information; and The new cell search is performed according to the cell search mode.

15. The apparatus of claim 14, wherein the processing circuit is further configured to perform: The statistical information is updated based on the result of the cell search and the user behavior including the time and place where the user habitually turns on the terminal.

16. The device according to claim 14, characterized in that The search time corresponding to a high success probability is longer than the search time corresponding to a low success probability, the non-search time corresponding to a high success probability is shorter than the non-search time corresponding to a low success probability, the search in the cell search mode corresponding to the high success probability is more frequent than the search in the cell search mode corresponding to the low success probability, the high success probability is a success probability higher than a threshold, the low success probability is a success probability not higher than the threshold, the high success probability is a success probability higher than a threshold, and the low success probability is a success probability not higher than the threshold.

17. The device according to claim 14, characterized in that When the probability value is on an upward trend, the search is performed with an increasing frequency, and when the probability value is on a downward trend, the search is performed with a decreasing frequency.

18. The device according to claim 14, characterized in that When the terminal service is interrupted, the processing circuit is further configured to execute: determining a probability of a successful cell search; and When the probability is higher than a threshold, determining the search interval to have a gradually shortened search interval, or When the probability is not higher than a threshold value, it is determined that the search interval has a gradually lengthened search interval.

19. The device according to claim 14, characterized in that The step of determining the search mode further comprises: recording the results of the cell search test in a database accessible to the terminal; and The search pattern is determined based on the statistical information retrieved from the database.

20. The apparatus of claim 14, wherein the processing circuit is further configured to perform: The probability model is updated using statistical methods or machine learning to evaluate a probability distribution curve calculated based on the statistical information.

Images