SYSTEM, APPARATUS AND METHOD FOR SEMI-PERSISTENT SCHEDULING IN A COMMUNICATION NETWORK - Patent application

Abstract

A method for semi-persistent scheduling (SPS)-based resource allocation in a private 5G network includes receiving location data of a plurality of user equipments (UEs) in the private 5G network in a last subframe of a current communication period of each of the UEs, and determining a distance distribution of the UEs in a subsequent communication period of a candidate UE among the plurality of UEs based on the location data of each of the UEs. The method further includes determining a signal-to-noise ratio expectation value of the UE for the subsequent communication period, solving an optimization problem that optimizes an expectation value of data to be carried by each of one or more SPS channels in the subsequent communication period to obtain a scheduling result for each of the one or more SPS channels, and generating resource allocation data for the candidate UE based on the scheduling result.

Description

[Technical field]

[0001] The present invention relates generally to systems, apparatus, and methods for semi-persistent scheduling in communication networks, and more particularly to a semi-persistent scheduling scheme for low latency and high reliability transmission in private and local fifth generation (5G) networks. [Background technology]

[0002] In almost all communication systems that are compliant with multiple devices, resource availability is limited to support full-duplex communication. Some communication systems utilize multiple access techniques to serve multiple users with fewer resources available for processing. An important aspect of currently available multiple access techniques is scheduling devices for communication. In traditional scheduling schemes, resources are assigned according to the data requirements and channel conditions of the users. This involves devices performing a series of complex steps before being assigned resources for communication, and such steps introduce significant delays into the entire communication process. Thus, in addition to being unsuitable, such communication systems also act as an obstacle to the development of applications that rely on time-dependent communication. Thus, there is a need for a robust scheduling scheme that is suitable for time-dependent and related mission-critical applications. Summary of the Invention

[0003] The embodiments of the present disclosure are based on the recognition that when a device has data to transmit, it must first receive a measurement configuration from a base station (BS) so that it can transmit a reference signal to the BS for uplink channel measurement. Meanwhile, the device needs to transmit a scheduling request indicator (SRI) to the BS, requesting radio resources for uplink transmission. Based on the measured uplink channel condition and the user's request, the BS performs scheduling for all users and informs the users of the scheduling results via a scheduling signal transmission transmitted on a physical downlink control channel (PDCCH). Some embodiments are based on the recognition that the scheduling should be performed and updated very frequently in order to adapt to changes in the radio environment. Some embodiments are based on the recognition that the traditional scheduling method that relies on a series of the aforementioned complex system procedures may be inapplicable in time-dependent network applications, such as private and local fifth generation (5G) communications, due to some special characteristics of the time-dependent network.

[0004] Some embodiments are based on the recognition that the network may be part of an industrial setup where short but frequent communications occur between devices connected by the network. Some embodiments are based on the recognition that the data that is often transmitted may be short messages such as machine control instructions, sensor information, and health care data that need to be transmitted periodically and frequently but consist of only a small amount of data. Some embodiments are based on the recognition that some messages may be sensitive to delays and have a predefined lifespan and become stale when their lifespan expires.

[0005] Some embodiments are based on the recognition that a large number of users may coexist in a private network. For example, in an industrial environment, a large number of Industrial Internet of Things (IIoT) devices may need to be supported by a private 5G network. Some embodiments are based on the recognition that for industrial automation, for example, motion control, low latency, high reliability, and determinism are important quality of service (QoS) requirements.

[0006] The above realization leads to the conclusion that traditional scheduling schemes cannot support private and local 5G networks, which have two main technical problems. First, when traditional scheduling, which relies on complex system procedures, is applied, a large number of users with a large number of frequent short messages will bring a large burden and overhead to the system. Second, a large number of users and a large number of messages will extend the time of signal processing and calculation in traditional scheduling, causing long delays and delay-sensitive messages may expire. Obviously, traditional approaches for SPS do not provide reliability, since radio resources cannot be allocated according to accurate and instantaneous channel conditions.

[0007] Some embodiments of the present disclosure are directed to redesigning the scheduling process for private and local 5G networks with licensed frequency bands. To this end, some embodiments provide a semi-persistent scheduling (SPS) scheme for low latency and high reliability uplink transmission to enable "grant-free" and instant uplink access for private 5G users. To truly support time-sensitive communications, some embodiments of the present disclosure enhance clarity regarding SPS reliability improvements. Some embodiments are directed to the technical detailed design of the redesigned SPS scheme and the scheduling algorithm aimed at improving reliability.

[0008] According to some embodiments, instead of rescheduling the SPS channel in each subframe, a minimum scheduling time unit consisting of multiple subframes, called an SPS period, may be defined. The user equipment (UE) performs uplink transmission within the SPS period using the same allocated and reserved radio resources. In this way, when a private 5G device, which is also a UE, has a message that needs to be transmitted, it can immediately access its assigned SPS channel to transmit data without waiting for scheduling by the base station (BS). This reduces the latency of uplink transmission. Furthermore, the system processes of both the private 5G BS and the user become more efficient with low operational complexity, since complex system procedures supporting frequent and instantaneous resource allocation are not required.

[0009] Therefore, to enhance the reliability of the proposed SPS over variations in the radio environment, an embodiment of the present invention utilizes the following two steps based on the distance distribution of private 5G users within the SPS period.

[0010] Some embodiments utilize probability geometry for deriving the distance distribution of private 5G users. First, the modulation and coding scheme (MCS) is appropriately selected, taking into account not only the current channel conditions but also the potential channel conditions and risks during the SPS period. Second, the selected MCS and data expectation on the SPS channel are used to perform SPS optimization processing aimed at improving reliability, ensuring fairness, and maximizing data rates.

[0011] Some embodiments provide an SPS scheme for uplink transmissions of local and private 5G networks, enabling "grant-free" and immediate uplink access for private 5G devices. According to some example embodiments, instead of rescheduling the SPS channel at each subframe (e.g., 1 ms), the smallest time unit for SPS channel scheduling can be selected as an SPS period consisting of multiple subframes. For example, an SPS period may include 1000 subframes of 1 ms each, thereby making the SPS period 1 s. Thus, within an SPS period, users may perform uplink transmissions using the same radio resources. In this way, when a UE has a message that needs to be transmitted, the UE can immediately access its assigned / reserved SPS channel to transmit data without waiting for scheduling by the base station. Thus, some example embodiments reduce the latency of uplink transmissions. Some exemplary embodiments also lead to system processes of both private 5G base stations and users becoming more efficient with low operational complexity, since complex system procedures supporting instantaneous resource allocation, such as periodic and frequency channel measurements, resource allocation, and signal transmission exchange, are no longer required.

[0012] Some exemplary embodiments consider the movement range of private 5G users (as well as UEs) and their data rate expectations to improve reliability. With the movement range taken into account, the scheduling system (e.g., BS) takes into account not only the current channel conditions, but also the possible channel conditions in the next SPS period, so that sufficient SPS channel resources are scheduled for each user to cover all possible channel condition situations in the next SPS period and ensure transmission reliability.

[0013] Some example embodiments provide a method for semi-persistent scheduling (SPS)-based resource allocation in a private 5G network. The method includes receiving location data of a plurality of user equipments (UEs) in a UE private 5G network at a last subframe of a current communication period of each of the UEs. The method further includes determining a distance distribution of the UEs in a subsequent communication period of a candidate UE of the plurality of UEs based on the location data of each of the UEs. A signal-to-noise ratio (SNR) expectation value of the UE for the subsequent communication period is also determined based at least in part on the distance distribution of the UEs. The SNR expectation value defines an amount of data to be carried by one or more SPS channels in the subsequent communication period. The method for SPS-based resource allocation further includes solving an optimization problem that optimizes an expectation value of data to be carried by each of the one or more SPS channels in the subsequent communication period to obtain a scheduling result for each of the one or more SPS channels. The method further includes generating resource allocation data for the candidate UEs based on the scheduling result and transmitting the resource allocation data to the candidate UEs for uplink communication.

[0014] Some example embodiments provide a communication device for semi-persistent scheduling (SPS) based resource allocation in a private 5G network, comprising a circuit configured to receive location data of a plurality of user equipments (UEs) in the private 5G network in a last subframe of a current communication period of each of the UEs. The circuit is further configured to determine a UE distance distribution in a subsequent communication period of a candidate UE among the plurality of UEs based on the location data of each of the UEs. The circuit is further configured to determine a signal-to-noise ratio (SNR) expectation value of the UE for the subsequent communication period based at least in part on the distance distribution of the UE, the SNR expectation value further defining an amount of data to be carried by one or more SPS channels in the subsequent communication period. The circuit is further configured to solve an optimization problem optimizing an expectation value of data to be carried by each of the one or more SPS channels in the subsequent communication period to obtain a scheduling result for each of the one or more SPS channels, generate resource allocation data for the candidate UE based on the scheduling result, and transmit the resource allocation data to the candidate UE for uplink communication.

[0015] Another embodiment of the present disclosure provides a non-transitory computer-readable storage medium embodied with a program executable by a computer to perform a method for semi-persistent scheduling (SPS)-based resource allocation in a private 5G network. The method includes receiving location data of a plurality of user equipments (UEs) in the private 5G network in a last subframe of a current communication period of each of the UEs. The method further includes determining a distance distribution of the UEs in a subsequent communication period of a candidate UE of the plurality of UEs based on the location data of each of the UEs. A signal-to-noise ratio (SNR) expectation value of the UE for the subsequent communication period is also determined based at least in part on the distance distribution of the UEs. The SNR expectation value further defines an amount of data to be carried by one or more SPS channels in the subsequent communication period. The method for SPS-based resource allocation further includes solving an optimization problem that optimizes an expectation value of data to be carried by each of the one or more SPS channels in the subsequent communication period to obtain a scheduling result for each of the one or more SPS channels. The method further includes generating resource allocation data for the candidate UEs based on the scheduling result and transmitting the resource allocation data to the candidate UEs for uplink communication.

[0016] Some exemplary embodiments also provide a method for communication between a communication device and a base station in a private 5G network. The communication device and the base station have a basic period of transmission defined therebetween as a minimum scheduling period. The method includes transmitting location data of the communication device in a last subframe of a current communication period of the communication device, and receiving resource allocation data including a transmission period extension factor for one or more subsequent communication periods of the communication device, the transmission period extension factor defining an extension of the basic period of transmission, and the method further includes calculating a semi-persistent scheduling (SPS) period as the subsequent communication period based on the transmission period extension factor and the basic period of transmission. The method further includes performing uplink communication based on the resource allocation data and the SPS period.

[0017] Some exemplary embodiments also provide a communication device for communicating with a base station in a private 5G network. The communication device and the base station have a basic period of transmission defined as a minimum scheduling period between them. The communication device includes a circuit, the circuit is configured to transmit location data of the communication device in a last subframe of a current communication period of the communication device, and receive resource allocation data including a transmission period extension factor, the transmission period extension factor defining an extension of the basic period of transmission, and the circuit is further configured to calculate a semi-persistent scheduling (SPS) period as a subsequent communication period based on the transmission period extension factor and the basic period of transmission. The circuit is further configured to perform uplink communication based on the resource allocation data and the SPS period.

[0018] Another embodiment of the present disclosure provides a non-transitory computer-readable storage medium embodied with a program executable by a computer to execute a method for communication between a communication device and a base station in a private 5G network. The communication device and the base station have a basic period of transmission defined therebetween as a minimum scheduling period. The method includes transmitting location data of the communication device in a last subframe of a current communication period of the communication device and receiving resource allocation data including a transmission period extension factor, the transmission period extension factor defining an extension of the basic period of transmission, and the method further includes calculating a semi-persistent scheduling (SPS) period as a subsequent communication period based on the transmission period extension factor and the basic period of transmission. The method further includes performing uplink communication based on the resource allocation data and the SPS period.

[0019] Some exemplary embodiments provide means and opportunities for implementing applications utilizing true time-sensitive networks (TSN). For example, in the context of an industrial setting, the exemplary embodiments help to schedule communications for a large number of interdependent and interconnected devices in a manner that is not detrimental to the underlying industrial process. By taking into account the mobile area reports corresponding to the respective locations of users in the network, the exemplary embodiments of the present disclosure help to achieve seamless connectivity between users.

[0020] As described above, the exemplary embodiments provide a TSN network that supports applications that cannot be supported by conventional networks that require rescheduling of transmissions every SPS period. The advantages and benefits of some of these features can result in increased network capacity, addressing today's growing demand for faster networking speeds.

[0021] For example, VOIP solutions and video chat apps are part of business and our personal lives today, along with online multiplayer gaming that has become a mainstream hobby. To enable these applications, vast amounts of data are exchanged online at increasingly massive rates. Delays in the transmission of data, or latency, can significantly impact the user experience. The methods and systems of the present disclosure can provide the capacity necessary to meet the demanding network capacity requirements of today's businesses and consumers.

[0022] Thus, communication devices, systems, and networks implemented using the exemplary scheduling scheme may represent significant improvements over the prior art. User equipment performing communications according to the exemplary scheduling scheme may perform data communications with reduced delay, thus supporting new applications that would otherwise require wired or other dedicated connection means. Base stations implementing the exemplary scheduling scheme do not need to repeatedly and frequently reschedule devices, thus reducing computational load and increasing capacity to serve more devices simultaneously.

[0023] The present invention will now be described in more detail with reference to the accompanying drawings, in which: The drawings shown are not necessarily to scale, with emphasis generally being placed upon illustrating the principles of embodiments of the present disclosure. [Brief description of the drawings]

[0024] [Figure 1] FIG. 1 is a diagram of a corporate private network in accordance with some illustrative embodiments. [Diagram 2] FIG. 1 is a schematic diagram illustrating a system model of private and local 5G networks, according to some exemplary embodiments. [Figure 3A] 1 is a timing diagram illustrating a frame structure for semi-persistent scheduling, in accordance with some example embodiments of the present disclosure. [Figure 3B] FIG. 2 is a schematic diagram illustrating some steps of a semi-persistent scheduling method according to some example embodiments. [Figure 4] FIG. 2 is a schematic diagram illustrating a model for determining a distance between a base station and a user equipment, according to some example embodiments. [Diagram 5] 4 is a flow diagram illustrating several steps of a method for semi-persistent scheduling in wireless networks, according to some example embodiments. [Figure 6] 4 illustrates a mapping table used to determine a modulation and coding scheme, according to some example embodiments. [Figure 7] 2 is a block diagram illustrating elements of a base station in accordance with some exemplary embodiments. [Figure 8] 1 is a flow diagram illustrating certain steps of a method for communication using semi-persistent scheduling in a wireless network, according to some example embodiments. [Figure 9] 1 is a flowchart illustrating a method for implementing semi-persistent scheduling in a wireless network, according to some example embodiments. [Figure 10] FIG. 2 is a block diagram illustrating an implementation of a user equipment in accordance with some exemplary embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0025] The following description provides exemplary embodiments only and is not intended to limit the scope, applicability, or configuration of the present disclosure. Rather, the following description of exemplary embodiments provides those skilled in the art with an enabling description for implementing one or more exemplary embodiments. It is contemplated that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the disclosed subject matter as set forth in the appended claims.

[0026] In the following description, specific details are given for a thorough understanding of the embodiments. However, those skilled in the art will understand that the embodiments may be practiced without these specific details. For example, systems, processes, and other elements in the disclosed subject matter may be shown as components in block diagram form so as not to obscure the embodiments in unnecessary detail. In other examples, well-known processes, structures, and techniques may be shown without unnecessary detail so as to avoid obscuring the embodiments. Additionally, like reference numbers and names in the various drawings refer to like elements.

[0027] Also, particular embodiments may be described as a process that is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe operations as a sequential process, many of the operations may be performed in parallel or simultaneously. In addition, the order of operations may be rearranged. A process may be terminated when its operations are completed, but may have additional steps not discussed or included in the diagram. Moreover, not all operations in any process specifically described may occur in all embodiments. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, the end of the function may correspond to a return to the calling function or the main function of the function.

[0028] Some embodiments of the present invention provide systems and methods for semi-persistent scheduling in communication networks. For mobile users, some services are characterized by periodically occurring transmissions of relatively small payloads. For most of these services, it is essential that the payloads reach their destination within a defined period of time to meet an acceptable level of quality of service. To this end, some attempts have been made to reduce the delay between the availability of data to be transmitted and the actual transmission of that data at a node. Since there may be several participants in a communication system, there is no particular order or pattern in which data communication may occur from the participants. It is therefore a challenge to meet the communication requirements of all users.

[0029] Multiple access (MA) is a phenomenon that addresses the problem of how to ensure the most productive use of a communication channel (i.e., maximize the aggregate or "total" throughput) when users need to transmit sporadically and their needs and actions cannot be coordinated among users. For a large number of users and to provide seamless connectivity options, it is important to provide a robust scheme to realize multiple access. Scheduling is one such scheme, where the system allocates radio resources according to the data requirements and channel conditions of users. In most scenarios, when a device has data to transmit, it must first receive a measurement configuration from a base station (BS) so that the device can send a reference signal to the BS for uplink channel measurement. Meanwhile, the device must transmit a scheduling request indicator (SRI) to the BS, requesting radio resources for uplink transmission. Based on the measured uplink channel conditions and user requests, the BS schedules all users and informs the users of the scheduling results via a scheduling signal transmission transmitted on the physical downlink control channel (PDCCH).

[0030] In most scenarios, the set of bidirectional communication steps listed above must be performed every time a device has data to transmit. Since each instance of communication with a BS is subject to delay, these steps incur a significant amount of delay. Furthermore, in the entire communication process when a user is moving, there may be frequent changes in the radio environment. To adapt to the changes in the radio environment, the scheduling is updated very frequently, which may be done every subframe (1 ms). Thus, conventional scheduling relies on a series of complex system procedures and may cause significant latency and overhead.

[0031] As connectivity applications grow exponentially across industries and domains, industrial networks are becoming more critical and diverse. It is common to deploy multiple technologies at a single site, such as Low Power WAN (LPWAN) for sensors, location / positioning beacon mesh, Wi-Fi, industrial Ethernet Programmable Logic Controllers (PLCs), and enterprise wide area networks (WANs) for branch / supply chain connectivity. Companies deploying private cellular networks to serve specific needs not addressed by telecom operators are well aware that industrial networks are complex, fragmented, and expensive.

[0032] 5G communications technology aims to simplify private and semi-private network configuration and management by bringing about a high degree of interoperability with legacy technologies and network slicing technologies that can open up new ways of collaboration between industry parties and the telecom ecosystem.

[0033] State-of-the-art manufacturing sites, distribution centers, and numerous other campus environments can benefit from the deployment of private 5G infrastructure supporting either 4G or 5G radio access networks. From algorithm updates to real-time interaction with manufacturing processes, predictive maintenance of machines, and autonomous delivery vehicles, private 5G networks offer numerous advantages to the modern enterprise. 5G service-based architecture (SBA) offers the ability to establish separate network slices, including fully independent control and user plane functions. This allows mobile network operators to carve out their own public networks, creating a virtually unlimited number of private LTE or 5G instances supporting their own enterprise customers.

[0034] Private networks are a promising new connectivity model for businesses and individuals. Private network owners can optimize services at their facilities by planning and installing their own networks and establishing reliable communications within a particular area exclusively using available resources. For example, for factors such as safety, security, privacy, reliability, latency, device density, and throughput, some industrial and private applications such as transportation, mining, container ports, health care, and manufacturing intend to operate on their own private networks rather than public commercial networks. Such private networks require a high level of flexibility and customization to meet their requirements. Since private network owners have full control over every aspect of the network, they can determine how resources are utilized, how traffic is prioritized, how specific security standards are deployed, and so on. Deployment of private networks can be feasible in shared or unlicensed spectrum. The main motivation behind private 5G is support for the Industrial Internet of Things (IIoT), where companies have the ability to operate their own networks (e.g., in factories, processing plants, airports, mining facilities, etc.).

[0035] However, private 5G networks hold special characteristics and come with their own set of challenges. A large number of users may coexist in a private 5G network. For example, in an industrial environment, a large number of Industrial Internet of Things (IIoT) devices may need to be supported by a private 5G network. Secondly, the data transmitted may be short messages, such as machine control instructions, sensor information, and health management, which consist of only a few data, but need to be transmitted periodically and frequently. Some of the messages are sensitive to delays and have predefined lifespans, and will become stale when their lifespan expires. Furthermore, for industrial automation, e.g., motion control, integration of wide-reaching sensing technologies, and worker safety, ultra-low latency, reliability, and determinism are key requirements. Unlike traditional 5G networks, which are mainly for outdoor coverage, private 5G networks and local 5G networks are developed for specific areas where the channel conditions are much more unstable and hostile, which presents a challenge to scheduling. In the case of public 5G networks, users may have high mobility. However, in local and private 5G networks, user mobility may be relatively low or localized. Some example embodiments take advantage of this fact in scheduling to improve reliability.

[0036] FIG. 1 illustrates an enterprise private network 100 according to some exemplary embodiments. An enterprise may generally provide the enterprise private network 100 for communication at one or more business locations of the enterprise. The enterprise private network 504 may include one or more enterprise servers 106 (e.g., application servers, authentication servers, etc.). In this example, the enterprise private 5G network 10 may be provided to a factory or plant of the enterprise. Data communication may occur between one or more user equipment and one or more other equipment in the enterprise facility. For example, the user equipment (UE) 102A may be a handheld device carried by personnel in the enterprise facility, e.g., in the factory. The UE 102A may communicate with other UEs in the factory, with a control system associated with the factory, or with some other communicatively coupled devices that may be present in the factory or outside the factory. Such communication may occur over the private 5G network 10. Similarly, the user equipment 102B may be a vehicle enabled with wireless communication capabilities and may perform data communication with another equipment over the private 5G private network. In some exemplary embodiments, the private 5G network 10 may also provide a communications link between user equipment 102C, which may be a robotic manipulator, and other devices within the enterprise.

[0037] In some exemplary embodiments, the private 5G network 10 may provide communication links to user equipment (102A, 102B, or 102C) via one or more base stations, such as gNodeBs (gNBs). The base station 104 may accommodate multiple UEs and may implement scheduling according to some exemplary embodiments to provide multiple access to all or a subset of the multiple UEs. The base station 104 may perform control signaling transmission with the UEs to communicate individual scheduling results to each of the multiple UEs. The base station 104 may assign a time period for uplink communication (SPS period) to each of the UEs after considering the current channel conditions of the UEs. The SPS period may be calculated by the base station 104 separately or jointly for each of the user equipments. According to some exemplary embodiments, the base station 104 may take into account not only the current channel conditions but also the possible channel conditions in the next SPS period, so that sufficient SPS channel resources are scheduled to each UE to cover all possible channel condition situations in the next SPS period and ensure transmission reliability. In this manner, the base station 104 ensures that every UE is assigned resources by the time data is available at every device for transmission.

[0038] In some exemplary embodiments, the base station 104 repeats the scheduling after one SPS period has elapsed. However, to reduce the latency associated with rescheduling, the base station 104 may provide a different scheme for scheduling in which the back-and-forth exchange of information between the base station 104 and a particular device (i.e., UE) is reduced. To this end, the exemplary embodiments utilize a basic period of communication between the base station 104 and the user equipment. In some exemplary embodiments, the base station 104 and the user equipment (102A, 102B, or 102C) may have a basic period of transmission defined therebetween. The basic period of transmission may be determined when the user equipment connects to the base station for the first time in a communication session. For example, as part of the initial handshake and control signal transmission exchange, the base station and the user equipment may set a minimum scheduling period as the basic period of communication.

[0039] The minimum scheduling period may be determined based on factors such as the computational capabilities of the user equipment, the available bandwidth of the frequency spectrum at the base station, etc. For example, the Japanese government has allocated 200 MHz of bandwidth to service providers, allowing them to build private 5G networks in the 28.2 GHz to 28.3 GHz frequency band. Similarly, the German government has reserved 100 MHz of spectrum at 3.7 to 3.8 GHz for private networks targeting industrial applications. In the United States, the Federal Communications Commission (FCC) has allowed the 3.5 GHz Citizens Broadband Radio Service (CBRS) to be used for private networks.

[0040] In some exemplary embodiments, to reduce the payload associated with the downlink communication of the scheduling result, the base station 104 may transmit a scaling factor for the calculation of the duration of the SPS period in the user equipment, thus further reducing the overhead and latency associated with scheduling. Since every user equipment has some computing capability, it may be easier for the UE to calculate the SPS period using the base period of transmission and the scaling factor.

[0041] An SPS period may consist of multiple subframes. In the developed scheduling scheme, user equipment may perform uplink transmission within an SPS period using the same assigned and reserved radio resources. In this way, when a private 5G device such as user equipment 102A, 102B, or 102C has a message that needs to be transmitted, it can immediately access its assigned SPS channel to transmit data without waiting for scheduling by the BS 104. As a result, the latency of uplink transmission is reduced. In addition, the system processes of both the private 5G BS and the user equipment become more efficient with low operational complexity, since complex system procedures supporting frequent and instantaneous resource allocation are not required.

[0042] FIG. 2 illustrates a system model of a private and local 5G network 20 according to some exemplary embodiments. The private and local 5G network comprises a base station 204, similar to the base station 104 of FIG. 1, and a plurality of user equipments 202A, 202B, and 202C wirelessly coupled to the base station 204. In some exemplary embodiments, one or more of the user equipments (202A, 202B, or 202C) may be coupled to the base station 204 via its own access point. The user equipments 202A, 202B, and 202C may be of the same or different types. The "type" of user equipment may correspond to a class or category of device to which the user equipment may belong. For example, virtual reality (VR) / augmented reality (AR), sensor, actuator, camera, etc. Such classification may be relevant to an enterprise.

[0043] The private and local 5G networks may be implemented as part of an enterprise network, may be standalone or access-controlled slices of a public 5G network. In some example embodiments, the movement of each of the user equipment 202A, 202B, and 202C may be localized to an area of ​​a premise, such as an enterprise premise. Each of the user equipment may have a different type of mobility, such as a human user, a vehicle, and a robot.

[0044] User equipment (202A, 202B, and 202C) connect to a private 5G BS 204 for uplink data transmission, and the BS 204 performs semi-persistent scheduling and periodically schedules each user equipment (or simply user) over a downlink control channel. The private and local 5G networks may have licensed frequency bands. Assuming there are M SPS channels and U users, where U is the set of all users, then:

number

number

[0045] Furthermore, in some exemplary embodiments, the private 5G network 20 may be applied to an environment where wireless signals may be obstructed and scattered by obstacles such as buildings, other equipment, and / or other devices. Accordingly, some exemplary embodiments employ Rayleigh fading to characterize small-scale fading. Thus, the small-scale fading of user i is expressed as h i In licensed frequency bands, private 5G networks can exclusively access their radio channels without interference from other systems. To ensure reliability and avoid interference, the BS 204 may assign one SPS channel to only one user equipment. Thus, in some exemplary embodiments, the signal-to-noise ratio (SNR) can be used to characterize the channel condition, which is given by:

number

[0046] In some exemplary embodiments, a user's mobility may be localized or limited to an area of ​​a premises for a period of time. Thus, resource allocation and scheduling should also take into account the possible locations where the user equipment (indistinguishably referred to as "user") will be in a subsequent period of time to ensure reliability. To this end, the BS 204 receives from each user its location information and generates a mobile area report for that user. The mobile area report for a user may indicate data corresponding to the user's location. The user's location may be expressed, for example, with reference to a universal reference frame, such as in a GPS-based system, or with respect to another element in the network, such as an access point. The user's location information may be transmitted in a mobile area report subframe of the user's SPS period. This will be described in more detail with reference to FIG. 3A.

[0047] FIG. 3A is a timing diagram illustrating a frame structure for semi-persistent scheduling according to some exemplary embodiments of the present disclosure. FIG. 3B is a schematic diagram illustrating some steps of a semi-persistent scheduling method according to some exemplary embodiments. Details of some exemplary embodiments of semi-persistent scheduling methods and algorithms are described with joint reference to FIG. 3A and FIG. 3B. The time domain may be divided into SPS periods with equal or unequal time lengths. Each SPS period may consist of multiple subframes, such as a data subframe for data transmission, an SPS scheduling signal transmission subframe for communicating SPS scheduling results, and a mobile area reporting subframe. At time instance t0, a user may note the availability of data transmitted over a private 5G network. For example, in a scenario similar to that shown in FIG. 2, a user 202A, a robot manipulator in a factory setting, may acquire image data of an object. The robot manipulator 202A is programmed to transmit this image data of the object to a central server for further processing. Thus, the robot manipulator 202A may communicate the availability of image data to its interface, which may trigger the communication process described in some embodiments of the present disclosure. Thus, the controller of the user (the robot manipulator 202A in the reference example of FIG. 2) may send a request 301 for radio resource allocation to the BS. The BS may then transmit the request 301 for radio resource allocation for the current period P C , and the user receives a scheduling signal transmission 303 from the BS at time instance t1. The time delay ΔT1 occurring between the instance when data is available for transmission at a user and its actual transmission is defined as follows:

number

[0048] Upon receiving a scheduling signal transmission, the user C However, during the current SPS period P C In the last subframe of the , the user's location information 307 may be transmitted to the base station. For this purpose, the user equipment may be equipped with a suitable location sensor that determines the geolocation of the user equipment. For example, the user equipment may be equipped with a Global Positioning System (GPS) sensor. In some exemplary embodiments, the user's geolocation information may be determined from signals provided by an access point to which the user may be connected. Any suitable positioning technique may be utilized, such as, for example, triangulation. In some exemplary embodiments, the user equipment may be localized to move within an area around the access point. In such a scenario, if the area is limited to within a threshold distance from the user equipment, the geolocation information of the access point may be considered to be the geolocation information of the user equipment.

[0049] The BS uses the user's geolocation information to determine the next SPS period P N The BS can evaluate the user's moving area in the next SPS period P N Executes scheduling for the current SPS period P C The user may then transmit (304, 310) a scheduling result 309 near time instance t2, which marks the end of the next SPS period P. N Then, the data transmission 306 may begin or continue in the next SPS period P N In the last subframe of P, the user can transmit its location information (302, 308) and the process can continue. N The time delay ΔT2 incurred during the actual transmission of data corresponding to

number

[0050] FIG. 4 is a schematic diagram illustrating a model for determining the distance between a base station and a user equipment according to some exemplary embodiments. The coordinates (x0, y0) correspond to the location of the user and are provided by its reported geolocation information. The maximum speed v of the user and the time length of the SPS period T can then be obtained. For example, the maximum speed v of the user can be obtained from an analysis of the geolocation information over a period of time. In some exemplary embodiments, the user operates within a pre-defined premises, so there may be constraints imposed on the maximum limit of the speed. Thus, the upper limit of the user's allowed speed may be considered as the value of the maximum speed v. In some exemplary embodiments, the user may operate at a pre-defined speed, and in such a case, the value of the maximum speed may be considered as the pre-defined speed.

[0051] Since a user's movement may be unpredictable within an SPS period, a user's moving area may be defined using localization techniques. For example, a user may be assumed to be localized within an area defined as a circle centered at coordinates (x0, y0) with radius v×T without loss of generality. Obviously, the moving area involves all possible locations of the user in the next SPS period. In some exemplary embodiments, apart from location information, a user may also report and update its data rate requirements through a moving area reporting subframe if its data communication requirements change. For freshness, the moving area reporting subframe is located in the last subframe of each SPS period to provide the latest location information. That is, the moving area subframe means the most recent location of the user since it is located in the last subframe of the SPS period. Therefore, the estimation of the moving area using the most recent location of the user is likely to be accurate, and therefore the scheduling performed using accurate moving area reporting is preferable and reliable.

[0052] In some exemplary embodiments, the location of the user equipment may be provided by a positioning module within the user equipment. As previously mentioned, the user equipment may be equipped with a GPS sensor, a GLONASS sensor, an IRNSS sensor, or equivalent, to provide the user's recent location. In some exemplary embodiments, in addition or as an alternative, the user equipment may be equipped with other on-board / device-mounted facilities such as an accelerometer, a compass, and computer vision. In some exemplary embodiments, alternative methods using on-device techniques may be used to improve or completely provide the required positioning accuracy when a GPS signal is not available. For this purpose, suitable techniques available in the art may be used without departing from the scope of this disclosure. Such scenarios may find use in local areas where channel conditions are much more unstable and hostile, creating challenges for scheduling.

[0053] In some exemplary embodiments, user equipment may be a "thing" in an industrial IoT setup. A "thing" may only operate or move within a specific area to perform certain operations and tasks. Some non-limiting examples of "things" may include robots, vehicles, machines, and sensors. Thus, a non-limiting but feasible way to collect location information without GPS may be to deploy an access point (AP) / sensor in each predefined moving area. In some exemplary embodiments, the AP or sensor may be used to detect the signal strength of a user. If the user's signal is detected as strongest at a certain AP / sensor, the corresponding moving area of ​​that AP / sensor may be considered as the user's moving area. In some exemplary embodiments, for a user who moves unpredictably and does not have a specific moving area, such as a wireless device held by a human, the user's moving area may be assumed to be very large, which is equal to the entire area covered by the base station.

[0054] After obtaining the user's location information, the BS performs signal processing and calculation processing to obtain the SPS channel scheduling result for the user in the network. One example is to build a virtual environment of things to build interactive monitoring and control under dynamic wireless environment by AR and IoT devices. The base station notifies all users of the SPS channel scheduling result through the SPS scheduling signal transmission subframe, which is the first subframe of each SPS period, as described with reference to 303 in FIG. 3A and 304 in FIG. 3B. According to the SPS channel scheduling result, the user of the private network performs uplink transmission on his / her assigned SPS channel in the rest of the SPS period, including all data subframes and mobile area reporting subframes. Therefore, unlike the conventional SPS, the proposed SPS considers user mobility prediction. In addition, the SPS scheduling of the present invention is formulated as an optimization problem, thus providing optimal scheduling.

[0055] To calculate the corresponding coverage probability, we may refer back to FIG. 4, where the base station may be assumed to be located at the origin (0,0) of height l, and the center of the user's mobile area and any location within the SPS period may be specified via coordinates (x0,y0) and (x1,y1), respectively. The coordinates (x0,y0) may be fixed and known, e.g., provided by reported user location information. In some exemplary embodiments, (x1,y1) may be unknown and selected randomly. Let X0=(x0,y0), X1=(x1-x0,y1-y0), and Y=(x1,y1) represent the vector from the BS to the mobile area center, the vector from the mobile area center to the user, and the vector from the BS to the user, respectively. The distance between the BS and the user is given by

number

number

[0056] For example, referring to FIG. 4, a base station may determine a user's moving area based on location information obtained for the user. The center of gravity of the moving area may correspond to the user's location, and the distance d between user "i" and the base station may be calculated based on the location information obtained for the user. i can be defined in any suitable way. This distance d i may reflect a representation of the distance distribution of users in the network. Since users may be dynamic, the distance distribution may also be dynamic. In other words, the distance d imay be a random variable due to user mobility. Using knowledge of probability geometry, the distance distribution of users can be determined at 502. An example of such a use of probability geometry is provided in the paper “M. Afshang, HS Dhillon, and PH Joo Chong, “Modeling and performance analysis of clustered device-to-device networks,” IEEE Trans. on Wireless Commun., vol. 15, no. 7, pp. 4957-4972, July 2016,” the contents of which are incorporated herein in their entirety.

[0057] 5 is a flow chart illustrating some steps of a method for semi-persistent scheduling in a wireless network according to some exemplary embodiments. After the base station obtains the user's location information as a moving area report, the base station calculates the frequency between the base station and the user according to the reported moving area. D(d) A distribution of distances, denoted by , is calculated (502). Such a distance distribution may be calculated using probability geometry, for example, in the manner illustrated in and described in more detail herein with reference to Figures 2 and 4.

[0058]

number

[0059] The expected value of the SNR is used to determine (i) the modulation and coding scheme (MCS) to be used for the next SPS period and (ii) the corresponding coverage probability. Any suitable method or technique known in the art may be utilized by the base station for this purpose. For example, to determine the MCS, the LTE specification specifies that there are 168 symbols in the SPS channel, which is a physical resource block (PRB) with a 180 kHz bandwidth. FIG. 6 shows an SNR to MCS mapping table 600 used to determine the MCS according to some exemplary embodiments. The base station may determine the MCS by referring to the SNR-MCS mapping table 600. The expected value of the SNR according to the distance distribution obtained in 504 of FIG. 5 may be compared to the SNR level defined in table 600. Since many signals may have a very wide dynamic range, the SNR may be expressed using a logarithmic decibel scale as shown in 602. In some exemplary embodiments, the SNR may be expressed simply as a ratio as shown in 604. Any suitable technique known in the art may be utilized to associate the expected SNR value obtained at 504 with the corresponding entry of SNR (602 or 604 as the case may be). For example, a distance between the expected SNR value obtained at 504 and the SNR value provided at 602 or 604 may be determined, and the value with the smallest distance may be selected as the best match. Thus, and corresponding to the selected SNR value in table 600, a modulation scheme 606 and a coding rate 608 may be obtained from table 600. Data in symbols defined in bits 610 may also be selected from table 600. In this manner, the MCS may be determined (506) according to the expected SNR value obtained at 504. The SNR to MCS mapping table 600 may be stored in a memory in the base station or in a device accessible to the base station. In some exemplary embodiments, the SNR to MCS mapping table 600 may be predefined, or in some scenarios, may be dynamically updated manually or automatically according to the requirements of the network.

[0060]

number

[0061] The coverage probability may be defined as the probability that the SNR of the received signal exceeds the threshold Γ for successful demodulation and decoding. The value of Γ, determined by the SINR ratio, may be predefined, for example, according to the table shown in FIG. 6. Given the distance distribution, the coverage probability may be obtained as follows:

number

[0062]

number

[0063] Given the selected MCS of user i, the SNR threshold Γ for successful demodulation and decoding can be determined. Furthermore, the amount of data carried by the SPS channel R i is fixed, which is governed by the MCS of user i. Therefore, the optimization problem for improving reliability and ensuring fairness can be formulated and solved as follows (508):

number

[0064] It is worth mentioning that the use of expected values ​​of transmitted data is important for reliability guarantee due to the fact that within an SPS period, users may continue to use pre-allocated resources to transmit data and the resource allocation cannot be adjusted instantaneously according to the changes in the radio environment. It is better if the scheduling does not only depend on the instantaneous channel conditions at a certain moment, but also considers the potential channel conditions in the SPS period.

[0065] The objective function of the optimization problem (7) is to maximize the sum of the expected transmitted data values ​​of all users, and the expected data transmitted on the SPS channel is

number

number

[0066]

number

[0067] In optimization problem (7), the private 5G system intends to allocate SPS channels to users with high expectation of transmitted data for two reasons. First, allocating SPS channels to users with high data expectation is beneficial to global maximization. Second, for users with higher data expectation, under the same data requirement, fewer channels allocated to this user can meet the requirement, and therefore more channel resources can be saved to serve other users, and more users are served with SPS. Obviously, through optimization problem (7), a good tradeoff is achieved between data rate, reliability, and fairness.

[0068] 7 is a block diagram illustrating elements of a base station BS (e.g., base station 204 of FIG. 2). As shown, the base station 700 may include a transceiver 701 configured to provide wireless communication with a plurality of wireless terminals, a network interface 705 configured to provide communication with other base stations of the RAN, a processor 703 coupled to the transceiver and the network interface, and a memory 707 coupled to the processor. The memory 707 may include computer readable program code that, when executed by the processor 703, causes the processor to perform operations according to embodiments disclosed herein. According to other embodiments, the processor 703 may be defined to include a memory such that the memory is not provided separately. The base station 700 may perform at least the steps described with reference to FIG. 5 and FIG. 6.

[0069] FIG. 8 is a flow diagram illustrating some steps of a method for communicating between a user equipment and another device via a base station according to semi-persistent scheduling in a wireless network, according to some exemplary embodiments. A user equipment, such as a UE 202A, may have a communication capability to perform data communication with one or more other devices in the network. A communication session occurring at a current time instance may be referred to as a current session of the user equipment, and a corresponding current session may have an associated current communication period. As mentioned above, every communication period may comprise one or more subframes. The user equipment and the base station may have a basic period of transmission defined between them as a minimum scheduling period. Such a minimum scheduling period may be established as part of an initial handshake process or during a first communication session when the user equipment first establishes a communication session with the base station. This basic period of transmission may be stored in an accessible memory in the user equipment and / or the base station for further use.

[0070] The user equipment may transmit a request for radio resource allocation in a current period, e.g., at the beginning of the current period (802). In some exemplary embodiments, to aid the base station in performing semi-persistent scheduling, the user equipment may also transmit location data in the last subframe of the current period. The request for radio resource allocation may be triggered when the user equipment anticipates or notes the availability of data for transmission on any of its communication interfaces. The user equipment may then utilize a suitable location technique to determine its location data and append it to the last subframe of the current period to reflect the user equipment's most recent location.

[0071] A base station, such as base station 204 in FIG. 2, may receive a request for radio resource allocation and, subsequently, location data of the user equipment. The base station may perform semi-persistent scheduling in a manner similar to that described above with reference to FIGS. 4-6 and provide the scheduling result together with the resource allocation data to each user equipment. The user equipment may receive (804) resource allocation data including, among other things, a transmission period extension factor for one or more subsequent communication periods of the user equipment. The transmission period extension factor defines an extension of the basic period of transmission. For example, the base station may determine an MCS, a channel frequency, and a transmission period extension factor for the user equipment and transmit it to the user equipment.

[0072] The user equipment may utilize the MCS and the channel frequency in an SPS period to perform data transmission. However, to do so, the user equipment must first calculate the SPS period. To this end, the user equipment may calculate the SPS period as a subsequent communication period of one or more subsequent communication periods based on the transmission period expansion factor and the basic period of transmission (806). For example, since the basic period of transmission is predefined and agreed upon between the user equipment and the base station, the user equipment may fetch the basic period of transmission from memory and multiply it by the transmission period expansion factor to determine the SPS period as the subsequent communication period. The user equipment has access to the channel frequency provided in the resource allocation data for a time period equivalent to the calculated SPS period. After the calculated SPS period has elapsed, the user equipment may release control of the channel frequency if a control signal transmission for the next period indicates so. In some exemplary embodiments, if the expected value of data transmission in the subsequent period indicates that the user equipment should continue to have access to the channel frequency, the base station may calculate a wider expansion factor for the user equipment. For the "n" subsequent communication periods, the base station may provide a no-change indicator to the user equipment if there is no requirement to release the channel frequency and if the user equipment still has data to transmit. Finally, the user equipment performs uplink communication on the channel frequency based on the SPS period assigned by the base station and calculated (808).

[0073] In some exemplary embodiments, it may not be feasible for some user equipment to calculate SPS periods due to operational limitations such as lack of sufficient computational power or delay intolerance in time-sensitive communications. In such scenarios, the base station may choose to identify the type of device and perform the calculation of SPS periods at the base station itself. That is, in some exemplary embodiments, the base station may identify whether to transmit SPS periods in the radio resource allocation data or only transmit the transmission period extension factor with the radio resource allocation data based on the type of device. Such hybrid capabilities may be particularly useful in scenarios where there may be a mix of different types of devices in the network. FIG. 9 illustrates a hybrid method for implementing semi-persistent scheduling in a wireless network, according to some exemplary embodiments.

[0074] The user equipment 901A and 901B may be communicatively coupled to a control system 905 of the industrial setup via a base station 903. For example, in some exemplary embodiments, the control system 905 may receive sensor data from the user equipment 901A and 901B and execute control processing to issue control commands to the user equipment 901A and 901B. Due to one or more reasons such as operational limitations or process requirements, it may not be feasible for the user equipment 901A to perform high-speed calculations. For example, the user equipment 901A may be a mobile assembly equipment having electromechanical components that generate high heat that is detrimental to the performance of the computing equipment such as a CPU. Thus, the user equipment 901A is not equipped with any special computing power and must be provided with most of the signal transmission to function properly. The user equipment 901A may be connected to the base station 903 via an access point (not shown), and thus the location of the user equipment 901A may be confirmed to be the location reported by the access point.

[0075] On the other hand, the user equipment 901B may be a robotic vehicle equipped with sufficient computing power. In this regard, the user equipment 901B may be considered to be equipped with, among other things, a position sensor, a memory, and a CPU. In 902A and 902B, the user equipments 901A and 902B may transmit a scheduling request indicator (SRI) to the base station in the current period, respectively, to request radio resources for uplink transmission. For example, the SRI may be transmitted in response to the availability of sensor data at the egress interface.

[0076] Following transmission of the SRI, user equipment 901A and 901B may each transmit location data in the last subframe of the current period (904A, 904B). As previously mentioned, the location data is transmitted in the last subframe of the current period to provide an updated location to base station 903. In some exemplary embodiments, each of user equipment 901A, 901B may also transmit to base station 903 the type of device.

[0077] The base station 903 receives the SRI and location data of a number of UEs (including user equipments 901A, 901B) in the last subframe of each of the UEs' current communication periods (906). The base station 903 may also receive the type identifiers of each of the UEs. In response, the base station 903 may perform a scheduling process. For this purpose, the base station 903 may calculate a distance distribution between the BS 903 and the UEs (901A, 901B, and any other UEs that can communicate with the BS 903) in the subsequent communication period based on the location data of the UEs (908). The calculation of the distance distribution may be performed in the manner previously discussed with reference to FIG. 4.

[0078] The base station 903 may then calculate 910 an expected SNR value, determine 912 an MCS, and calculate a coverage probability for all UEs in the subsequent communication period in the manner previously discussed with reference to FIG. 5. The base station 903 may then optimize 914 the data to be carried by the SPS channel in the subsequent communication period to obtain a scheduling result for each of the UEs. In this regard, the base station 903 may perform optimization to obtain a scheduling result according to a type of user equipment. For example, for user equipment 901A, the base station 903 may define an SPS period as part of the scheduling result, and for user equipment 901B, the base station 903 may define a transmission period extension factor as part of the scheduling result. The base station may transmit 916 each scheduling result to the corresponding UE via a downlink control channel.

[0079] The non-computing user equipment 901A receives (918) scheduling data including the length of the SPS period and performs (920) uplink transmission according to the scheduling data. Meanwhile, the user equipment 901B receives (922) resource allocation data including the transmission period extension factor in a manner similar to that described with respect to Figure 8. The user equipment 901B then calculates (924) an SPS period as a subsequent communication period based on the transmission period extension factor and the basic period of transmission, and performs (926) uplink transmission accordingly.

[0080] Thus, the exemplary embodiment provides a significant improvement to the overall scheduling process by performing the scheduling process according to the type of user equipment being served. This helps to delegate the processing load to the user equipment to some extent, thereby ensuring that the base station can cater for time-sensitive scenarios. Furthermore, the user equipment can receive resource allocation data close to the time the data is available for transmission. This significantly improves the performance of the user equipment in time-sensitive scenarios.

[0081] Figure 10 is a block diagram illustrating an example implementation of a user equipment according to an embodiment of the present disclosure. The user equipment 1000 can perform the steps described with reference to Figure 8 and at least some steps shown in Figure 9. The user equipment 1000 can include a controller 1011 with a processor 1040, a computer-readable memory 1012, a storage 1058, and a user interface 1049 having a display 1052 and a keyboard 1051, connected via a bus 1056. For example, the user interface 1049 in communication with the processor 1040 and the computer-readable memory 1012 retrieves and stores data in the computer-readable memory 1012 upon receiving input from a user on the surface of the user interface 1057, the keyboard surface.

[0082] It is contemplated that the memory 1012 may store instructions executable by the processor, historical data, and any data that may be utilized by the methods and systems of the present disclosure. The processor 1040 may be a single-core processor, a multi-core processor, a computing cluster, or any number of other configurations. The processor 1040 may be connected to one or more input and output devices via a bus 1056. The memory 1012 may include random access memory (RAM), read-only memory (ROM), flash memory, or any other suitable memory system.

[0083] 10, the storage device 1058 can be adapted to store supplemental data and / or software modules used by the processor. For example, the storage device 1058 can store historical data and other related data as described above with respect to this disclosure. Additionally or alternatively, the storage device 1058 can store historical data similar to the data referred to above with respect to this disclosure. The storage device 1058 can include a hard drive, an optical drive, a thumb drive, an array of drives, or any combination thereof.

[0084] The system can be optionally linked via bus 1056 to a display interface (not shown) adapted to connect the system to a display device (not shown), which can include a computer monitor, a camera, a television, a projector, or a mobile device, among others.

[0085] The controller 1011 can include a power supply 1054, which, depending on the application, can optionally be located external to the controller 1011. Linked through the bus 1056 can be a user input interface 1057 adapted to connect to a display device 1048, which can include, among other things, a computer monitor, a camera, a television, a projector, or a mobile device. A printer interface 1059 can also be connected through the bus 1056 and adapted to connect to a printing device 1032, which can include, among other things, a liquid inkjet printer, a solid ink printer, a large scale commercial printer, a thermal printer, a UV printer, or a dye sublimation printer. A network interface controller (NIC) 1054 is adapted to connect to a network 1036 over the bus 1056, such that data or other data can be rendered on, among other things, a third party display device, a third party imaging device, and / or a third party printing device outside the controller 1011. Additionally, the bus 1056 may be connected to a Global Positioning System (GPS) device 1001 or similar related type device.

[0086] 10, data or other data may be transmitted over communication channels of the network 1036, among others, and / or stored in a storage system 1058 for storage and / or further processing. Furthermore, data or other data may be received wirelessly or wired from a receiver 1046 (or an external receiver 1038), or transmitted wirelessly or wired via a transmitter 1047 (or an external transmitter 1039), both of which are connected via a bus 1056. The controller 1011 may be connected to an external routing hardware device 1044 and an external input / output device 1041 via an input interface 1008. The controller 1042 may be connected to an external control system 1072 and a routing hardware device 1044. The routing hardware device 1044 may have incoming data from a router 1073 and a network communication device 1044. Here, the routing hardware device 1044 can have outgoing data to a router 1074 and a network communication device 1075. Also, an external memory device 1006 can be connected to the external sensors 1004 and the machine 1002, and the memory device can be connected to the bus 1056. An output interface 1009 can be used to output processed data from the processor 1040 via the bus 1056.

[0087] The foregoing embodiments of the present invention can be implemented in any of numerous ways. For example, the embodiments can be implemented using hardware, software, or a combination thereof. If implemented in software, the software code can be executed on any suitable processor or collection of processors, whether provided in a single computer or distributed among multiple computers. Such a processor can be implemented as an integrated circuit with one or more processors in an integrated circuit component. However, the processor may be implemented using any suitable form of circuitry.

[0088] Also, the various methods or processes outlined herein may be coded as software executable on one or more processors using any one of a variety of operating systems or platforms. In addition, such software may be written using any of a number of suitable programming languages ​​and / or programming or scripting tools, and may be compiled as executable machine language code or intermediate code that runs on a framework or virtual machine. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments.

[0089] Also, embodiments of the invention may be embodied as methods for which examples have been provided. The acts performed as part of the method may be ordered in any suitable manner. Thus, embodiments may be constructed in which acts are performed in an order different from that illustrated, which may include performing simultaneously some acts shown in the exemplary embodiment as sequential acts.

[0090] Although the invention has been described by way of examples of preferred embodiments, it is to be understood that various other adaptations and modifications can be made within the spirit and scope of the invention. Therefore, it is the object of the appended claims to cover all such variations and modifications which come within the true spirit and scope of the invention.

Claims

1. A method for semi-persistent scheduling (SPS) based resource allocation in a private 5G network, comprising: Receiving location data of a plurality of user equipments (UEs) in the private 5G network at a last subframe of a current communication period of each of the plurality of UEs; determining a distance distribution of the plurality of UEs during a subsequent communication period of a candidate UE among the plurality of UEs based on the respective location data of the plurality of UEs; and determining a signal-to-noise ratio (SNR) expectation for the plurality of UEs for the subsequent communication interval based at least in part on the distance distribution of the plurality of UEs, the SNR expectation further defining an amount of data to be carried by one or more SPS channels in the subsequent communication interval, the method further comprising: solving an optimization problem that optimizes an expected amount of data to be carried by each of the one or more SPS channels in the subsequent communication period to obtain a scheduling result for each of the one or more SPS channels; generating resource allocation data for the candidate UEs based on the scheduling results; and and transmitting the resource allocation data to the candidate UEs for uplink communication.

2. The method of claim 1 , wherein the number of SPS channels to be assigned to a UE is a variable in the optimization problem.

3. the resource allocation data includes a transmission period extension factor for the candidate UE, the transmission period extension factor defining an extension of a basic period of transmission, the basic period being a minimum scheduling period for transmission between the candidate UE and a base station, the candidate UE being configured to calculate the subsequent communication period based on the transmission period extension factor; The method of claim 2 , wherein the resource allocation data further includes a modulation and coding scheme (MCS) for the candidate UE.

4. The method of claim 1 , further comprising: determining a modulation and coding scheme for each UE of the plurality of UEs based on the determined SNR expectation values ​​of the plurality of UEs.

5. 2. The method of claim 1, wherein a plurality of communication periods of channel scheduling are associated with each UE of the plurality of UEs, each communication period of channel scheduling includes a plurality of subframes, a corresponding one of the plurality of UEs utilizes the same set of channels for communication during a communication period, and each communication period is the same length.

6. The method of claim 1 , wherein the location data for each UE of the plurality of UEs includes geolocation information of the respective UE.

7. 2. The method of claim 1, wherein the resource allocation data is transmitted to the candidate UE through a first subframe of the subsequent communication period of the candidate UE, and the candidate UE is configured to perform uplink communication in all but a last subframe of the remaining subframes of the subsequent communication period of the candidate UE.

8. A communication device for Semi-Persistent Scheduling (SPS) based resource allocation in a private 5G network, comprising: a circuit, the circuit comprising: Receive location data of a plurality of user equipments (UEs) in the private 5G network at a last subframe of a current communication period for each of the plurality of UEs; determining a distance distribution of the plurality of UEs during a subsequent communication period of a candidate UE among the plurality of UEs based on the respective location data of the plurality of UEs; and determining a signal-to-noise ratio (SNR) expectation for the plurality of UEs for the subsequent communication interval based at least in part on the distance distribution of the plurality of UEs, the SNR expectation further defining an amount of data to be carried by one or more SPS channels in the subsequent communication interval, the circuitry further configured to: solving an optimization problem that optimizes an expected amount of data to be carried by each of the one or more SPS channels in the subsequent communication period to obtain a scheduling result for each of the one or more SPS channels; generating resource allocation data for the candidate UEs based on the scheduling results; A communications device configured to transmit the resource allocation data to the candidate UEs for uplink communication.

9. The communications device of claim 8 , wherein a number of SPS channels to be assigned to a UE is a variable in the optimization problem.

10. The communications device of claim 8 , wherein the circuitry is further configured to determine a modulation and coding scheme for each UE of the plurality of UEs based on the determined expected SNR values ​​of the plurality of UEs.

11. 9. The communications device of claim 8, wherein a plurality of communication periods of channel scheduling are associated with each UE of the plurality of UEs, each communication period of channel scheduling includes a plurality of subframes, a corresponding one of the plurality of UEs utilizes the same set of channels for communication during a communication period, and each communication period is of the same length.

12. The communications device of claim 8 , wherein the location data for each UE of the plurality of UEs includes geolocation information of the respective UE.

13. 9. The communications device of claim 8, wherein the resource allocation data is transmitted to the candidate UE through a first subframe of the subsequent communication period of the candidate UE, and the candidate UE is configured to perform uplink communications in all but a last subframe of the remaining subframes of the subsequent communication period of the candidate UE.

14. The circuit further comprises: and configured to receive a device identifier from each UE of the plurality of UEs, the device identifier identifying a type of the device, the circuitry further comprising: The communications apparatus of claim 8 , configured to determine the SNR expectations for the plurality of UEs for the subsequent communication period based on the device identifiers of the plurality of UEs.

15. The communications apparatus of claim 8 , wherein the plurality of UEs are mobile devices that transmit time-sensitive data in a factory setting.

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