Control information indication and function performance with intelligence for wireless communications
Patent Information
- Authority / Receiving Office
- EP · EP
- Patent Type
- Applications
- Current Assignee / Owner
- ZTE CORP
- Filing Date
- 2023-09-22
- Publication Date
- 2026-07-08
Smart Images
Figure CN2023120872_24102024_PF_FP_ABST
Abstract
Description
CONTROL INFORMATION INDICATION AND FUNCTION PERFORMANCE WITH INTELLIGENCE FOR WIRELESS COMMUNICATIONSTECHNICAL FIELD
[0001] This document is directed generally to control information indication and performing associated functions in combination with an intelligence component for wireless communications.BACKGROUND
[0002] In wireless communication systems, control information is communicated as overhead in order to provide flexibility of traffic or data transmission. For example, downlink control information (DCI) is generated and transmitted in the transmitter, and decoded and applied in the receiver. Ways to improve the efficiency and flexibility of use of such control information may be desirable.SUMMARY
[0003] This document relates to methods, systems, apparatuses and devices for wireless communication. In some implementations, a method for wireless communication includes: determining, by a first communication node, control information comprising at least one field or at least one parameter determined by an intelligence component, the at least one field or the at least one parameter associated with a function; and transmitting, by the first communication node, the control information to a second communication node for performance of the function.
[0004] In some other implementations, a method for wireless communication includes: receiving, by a second communication node, control information comprising at least one field or at least one parameter determined by an intelligence component; and performing, by the second communication node, a function according to the control information.
[0005] In some other implementations, a device, such as a network device, is disclosed. The device may include one or more processors and one or more memories, wherein the one or more processors are configured to read computer code from the one or more memories to implement any of the methods above.
[0006] In yet some other implementations, a computer program product is disclosed. The computer program product may include a non-transitory computer-readable program medium with computer code stored thereupon, the computer code, when executed by one or more processors, causing the one or more processors to implement any of the methods above.
[0007] The above and other aspects and their implementations are described in greater detail in the drawings, the descriptions, and the claims.BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIG. 1 shows a block diagram of an example of a wireless communication system.
[0009] FIG. 2 shows a flow chart of a method for wireless communication.
[0010] FIG. 3 shows a flow chart of a method for wireless communication.DETAILED DESCRIPTION
[0011] The present description describes various embodiments of systems, apparatuses, devices, and methods for wireless communications related to control information and associated functions in combination with an intelligence component.
[0012] FIG. 1 shows a diagram of an example wireless communication system 100 including a plurality of communication nodes (or just nodes) that are configured to wirelessly communicate with each other. In general, the communication nodes include at least one user device 102 and at least one network device 104. The example wireless communication system 100 in FIG. 1 is shown as including two user devices 102, including a first user device 102 (1) and a second user device 102 (2) , and one device 104. However, various other examples of the wireless communication system 100 that include any of various combinations of one or more user devices 102 and / or one or more network devices 104 may be possible.
[0013] In general, a user device as described herein, such as the user device 102, may include a single electronic device or apparatus, or multiple (e.g., a network of) electronic devices or apparatuses, capable of communicating wirelessly over a network. A user device may comprise or otherwise be referred to as a user terminal, a user terminal device, or a user equipment (UE) . Additionally, a user device may be or include, but not limited to, a mobile device (such as a mobile phone, a smart phone, a smart watch, a tablet, a laptop computer, vehicle or other vessel (human, motor, or engine-powered, such as an automobile, a plane, a train, a ship, or a bicycle as non-limiting examples) or a fixed or stationary device, (such as a desktop computer or other computing device that is not ordinarily moved for long periods of time, such as appliances, other relatively heavy devices including Internet of things (IoT) , or computing devices used in commercial or industrial environments, as non-limiting examples) . In various embodiments, a user device 102 may include transceiver circuitry 106 coupled to an antenna 108 to effect wireless communication with the network device 104. The transceiver circuitry 106 may also be coupled to a processor 110, which may also be coupled to a memory 112 or other storage device. The memory 112 may store therein instructions or code that, when read and executed by the processor 110, cause the processor 110 to implement various ones of the methods described herein.
[0014] Additionally, in general, a network device as described herein, such as the network device 104, may include a single electronic device or apparatus, or multiple (e.g., a network of) electronic devices or apparatuses, and may comprise one or more wireless access nodes, base stations, or other wireless network access points capable of communicating wirelessly over a network with one or more user devices and / or with one or more other network devices 104. For example, the network device 104 may comprise a 4G LTE base station, a 5G NR base station, a 5G central-unit base station, a 5G distributed-unit base station, a next generation Node B (gNB) , an enhanced Node B (eNB) , or other similar or next-generation (e.g., 6G) base stations, in various embodiments. A network device 104 may include transceiver circuitry 114 coupled to an antenna 116, which may include an antenna tower 118 in various approaches, to effect wireless communication with the user device 102 or another network device 104. The transceiver circuitry 114 may also be coupled to one or more processors 120, which may also be coupled to a memory 122 or other storage device. The memory 122 may store therein instructions or code that, when read and executed by the processor 120, cause the processor 120 to implement one or more of the methods described herein.
[0015] In various embodiments, two communication nodes in the wireless system 100-such as a user device 102 and a network device 104, two user devices 102 without a network device 104, or two network devices 104 without a user device 102-may be configured to wirelessly communicate with each other in or over a mobile network and / or a wireless access network according to one or more standards and / or specifications. In general, the standards and / or specifications may define the rules or procedures under which the communication nodes can wirelessly communicate, which, in various embodiments, may include those for communicating in millimeter (mm) -Wave bands, and / or with multi-antenna schemes and beamforming functions. In addition or alternatively, the standards and / or specifications are those that define a radio access technology and / or a cellular technology, such as Fourth Generation (4G) Long Term Evolution (LTE) , Fifth Generation (5G) New Radio (NR) , or New Radio Unlicensed (NR-U) , as non-limiting examples.
[0016] Additionally, in the wireless system 100, the communication nodes are configured to wirelessly communicate signals between each other. In general, a communication in the wireless system 100 between two communication nodes can be or include a transmission or a reception, and is generally both simultaneously, depending on the perspective of a particular node in the communication. For example, for a given communication between a first node and a second node where the first node is transmitting a signal to the second node and the second node is receiving the signal from the first node, the first node may be referred to as a source or transmitting node or device, the second node may be referred to as a destination or receiving node or device, and the communication may be considered a transmission for the first node and a reception for the second node. Of course, since communication nodes in a wireless system 100 can both send and receive signals, a single communication node may be both a transmitting / source node and a receiving / destination node simultaneously or switch between being a source / transmitting node and a destination / receiving node.
[0017] Also, particular signals can be characterized or defined as either an uplink (UL) signal, a downlink (DL) signal, or a sidelink (SL) signal. An uplink signal is a signal transmitted from a user device 102 to a network device 104. A downlink signal is a signal transmitted from a network device 104 to a user device 102. A sidelink signal is a signal transmitted from a one user device 102 to another user device 102, or a signal transmitted from one network device 104 to a another network device 104. Also, for sidelink transmissions, a first / source user device 102 directly transmits a sidelink signal to a second / destination user device 102 without any forwarding of the sidelink signal to a network device 104.
[0018] Additionally, signals communicated between communication nodes in the system 100 may be characterized or defined as a data signal or a control signal. In general, a data signal is a signal that includes or carries data, such multimedia data (e.g., voice and / or image data) , and a control signal is a signal that carries control information that configures the communication nodes in certain ways in order to communicate with each other, or otherwise controls how the communication nodes communicate data signals with each other. Also, certain signals may be defined or characterized by combinations of data / control and uplink / downlink / sidelink, including uplink control signals, uplink data signals, downlink control signals, downlink data signals, sidelink control signals, and sidelink data signals.
[0019] For at least some specifications, such as 5G NR, data and control signals are transmitted and / or carried on physical channels. Generally, a physical channel corresponds to a set of time-frequency resources used for transmission of a signal. Different types of physical channels may be used to transmit different types of signals. For example, physical data channels (or just data channels) , also herein called traffic channels, are used to transmit data signals, and physical control channels (or just control channels) are used to transmit control signals. Example types of traffic channels (or physical data channels) include, but are not limited to, a physical downlink shared channel (PDSCH) used to communicate downlink data signals, a physical uplink shared channel (PUSCH) used to communicate uplink data signals, and a physical sidelink shared channel (PSSCH) used to communicate sidelink data signals. In addition, example types of physical control channels include, but are not limited to, a physical downlink control channel (PDCCH) used to communicate downlink control signals, a physical uplink control channel (PUCCH) used to communicate uplink control signals, and a physical sidelink control channel (PSCCH) used to communicate sidelink control signals. As used herein for simplicity, unless specified otherwise, a particular type of physical channel is also used to refer to a signal that is transmitted on that particular type of physical channel, and / or a transmission on that particular type of transmission. As an example illustration, a PDSCH refers to the physical downlink shared channel itself, a downlink data signal transmitted on the PDSCH, or a downlink data transmission. Accordingly, a communication node transmitting or receiving a PDSCH means that the communication node is transmitting or receiving a signal on a PDSCH.
[0020] Additionally, for at least some specifications, such as 5G NR, and / or for at least some types of control signals, a control signal that a communication node transmits may include control information comprising the information necessary to enable transmission of one or more data signals between communication nodes, and / or to schedule one or more data channels (or one or more transmissions on data channels) . For example, such control information may include the information necessary for proper reception, decoding, and demodulation of a data signals received on physical data channels during a data transmission, and / or for uplink scheduling grants that inform the user device about the resources and transport format to use for uplink data transmissions. In some embodiments, the control information includes downlink control information (DCI) that is transmitted in the downlink direction from a network device 104 to a user device 102. In other embodiments, the control information includes uplink control information (UCI) that is transmitted in the uplink direction from a user device 102 to a network device 104, or sidelink control information (SCI) that is transmitted in the sidelink direction from one user device 102 (1) to another user device 102 (2) .
[0021] In some implementations, the control information may include and / or be used for at least one of: resource allocation, beam related information, power control, one or more modulation and code schemes (MCS) , one or more antenna ports, precoding information and / or a number of layers, and / or hybrid automatic repeat request (HARQ) -acknowledgement (ACK) feedback related information, as non-limiting examples. The control information may be included or packaged in and / or used as one or more fields, such as in accordance with a predetermined format. Also, downlink control information (DCI) may be generated and transmitted by a transmitting device (e.g., a network device 104) , and may be received, decoded, and / or applied by a receiving device (e.g., a user device 102) . For at least some implementations, the procedure of including the control information in each field according to a given format may be semi-static, configured, and / or dynamically indicated by the network device 104. For example, the frequency domain resource allocation for a traffic channel may be indicated by the network device 104 though a scheduling algorithm, and the user device 102 may decode the traffic channel according to location indicated by the resource allocation.
[0022] In the present description, an intelligent and efficient utilization or procedure for control information may be performed through application of an enhancement for at least one field in a format of control information. In some implementations, such an enhancement may be employed through use of an intelligence component. For example, a network device 104 may send a DCI to a user device 102 in combination with an intelligence component. As another example, a user device 102 may send a UCI to a network device 104 in combination with an intelligence component. The generation, communication, and / or prediction indication of control information (including a DCI and / or a UCI) may be more intelligent and / or efficient through use of the intelligence component, as described in further detail below.
[0023] As used herein, an intelligence component is a circuit, implemented in only hardware or a combination of hardware and software, that includes a model in the form of an algorithm that is initialized and trained based on a training data set, and that, upon being at least partially trained using the training data set, is used to generate a set of one or more outputs based on a set of one or more inputs. In any of various implementations, the model may be an artificial intelligence (AI) model and / or a machine learning (ML) model. Accordingly, as used herein, the term AI / ML for a given component refers to the component having artificial intelligence functionality and / or machine learning functionality, and / or refers to the component having an AI model and / or a ML model. Accordingly, an intelligence component and an AI / ML component are used herein interchangeably, unless expressly specified otherwise.
[0024] Additionally, in some implementations, at least one field and / or at least one parameter may be associated with a function. In some implementations, the at least one field and / or the at least one parameter may be included in or be part of control information. In addition or alternatively, the at least one field or the at least one parameter may be determined by an intelligence component. In some implementations, at least one first value used for the at least one field or the at least one parameter may be derived based on the intelligence component. In some of these implementations, all or part of the at least one field or the at least one parameter is omitted from the control information. In addition or alternatively, in some of these implementations, a best one of N predicted parameters determined and / or output by an intelligence component may be used. In addition or alternatively, a sub-set within a set of fields may be used to perform the function.
[0025] Additionally, in some implementations, at least one field or at least one parameter associated with a function may include or corresponding to indication information predicted by an intelligence component. The predicted indication information may include one shot predicted indication or a plurality of predicted indications. In some implementations, predicted parameters output from an intelligence component may be used as X entries of a table instead of, or in replace of, parameters that are not generated by an intelligence component. In some embodiments, N predicted indications (where N > 1) may be indicated by multiple entries or a pattern for a next N instances.
[0026] Additionally, for some implementations, for a same function indicated by one or a set of fields, regardless of whether the predicted indication information includes a one shot predicted indication or a plurality of predicted indications, different indication range may be used. The different indication ranges may include different candidate values, and the metric may include a vector or a table, as non-limiting examples.
[0027] Additionally, for a same function indicated by one or a set of fields, regardless whether the predicted indication information includes a one shot predicted indication or a plurality of predicted indications, a finer granularity indication may be used. The finer granularity may be for the same parameter with different granularities (some being finer than others) or different offsets, or different details to represent the parameter.
[0028] Additionally, for some implementations, an intelligent indication for the function may be based on at least one of: history scheduling information of the user device 102; history or current scheduling information of other user devices 102; performance of the user device 102; or performance of the wireless communication system 100 or other user devices 102.
[0029] FIG. 2 shows a flow chart of example method 200 for wireless communication that includes control information. At block 202, a first communication node (e.g., a user device 102 or a network device 104) may determine control information that includes at least one field or at least one parameter determined by an intelligence component. The at least one field or the at least one parameter is associated with a function. At block 204, the first communication node may transmit the control information to a second communication node (e.g., a user device 102 or a network device 104) for performance of the function.
[0030] FIG. 3 shows a flow chart of another example method 300 for wireless communication that includes control information. At block 302, a second communication node (e.g., a user device 102 or a network device 104) may receive control information that includes at least one field or at least one parameter determined by an intelligence component. At block 304, the second communication node may perform a function according to the control information.
[0031] In some implementations of the method 200 and / or the method 300, at least one first value used for the at least one field or the at least one parameter of the function is derived based on the intelligence component, and the intelligence component is located in the first communication node or the second communication node.
[0032] In some implementations of the method 200 and / or the method 300, the at least one first value includes one of a plurality of predicted values, where the plurality of predicted values are derived based on the intelligence component.
[0033] In some implementations of the method 200 and / or the method 300, the at least one first value includes a best one of a plurality of predicted first values and the at least one field or the at least one parameter is absent in the control information.
[0034] In some implementations of the method 200 and / or the method 300, the at least one first value is used to replace at least one second value for the parameter that is determined without the intelligence component.
[0035] In some implementations of the method 200 and / or the method 300, the at least one first value includes at least one value in at least one entry of a vector or a table.
[0036] In some implementations of the method 200 and / or the method 300, the at least one first value indicates one instance or a plurality of instances, wherein the plurality of instances is indicated by multiple entries or a pattern of the at least one field or the at least one parameter.
[0037] In some implementations of the method 200 and / or the method 300, the at least one first value includes a plurality of predicted values for the at least one field or the at least one parameter, or for a plurality of parameters to represent or replace the at least one field or the at least one parameter.
[0038] In some implementations of the method 200 and / or the method 300, the plurality of predicted values corresponds to different granularities or offsets from the at least one first value.
[0039] In some implementations of the method 200 and / or the method 300, the at least one field or the at least one parameter includes transmission configuration information (TCI) , and the at least one first value corresponds to at least one predicted downlink transmission beam.
[0040] In some implementations of the method 200 and / or the method 300, the at least one field or the at least one parameter includes a modulation and coding scheme (MCS) , and the at least one first value corresponds to at least one predicted MCS index, at least one channel state information (CSI) , or at least one channel quality information (CQI) .
[0041] In some implementations of the method 200 and / or the method 300, the function include resource allocation, and the at least one first value corresponds to at least one predicted value of a location for the at least one field or the at least one parameter of the resource allocation.
[0042] In some implementations of the method 200 and / or the method 300, the function include power control, and the at least one first value corresponds to at least one predicted value of power tracking for at least one physical channel.
[0043] In some implementations of the method 200 and / or the method 300, the at least one first value corresponds to at least one value of a traffic or power tracking, and the function includes determining a power saving pattern.
[0044] In some implementations of the method 200 and / or the method 300, the function includes power saving indication, and the at least one first value corresponds to at least one predicted value of monitoring manner for the at least one field or the at least one parameter of the power saving indication.
[0045] In some implementations of the method 200 and / or the method 300, the function includes feedback indication, and the at least one first value corresponds to at least one predicted value of a resource or a timeline for the at least one field or the at least one parameter of the feedback indication.
[0046] In some implementations of the method 200 and / or the method 300, the multiple entries or the pattern of the at least one field or the at least one parameter includes an N-number of predicted values of the at least one field or the at least one parameter, and one or more offsets or a scaling is used to indicate a last (N-1) instances of the N-number of predicted values of the at least one field or the at least one parameter.
[0047] In some implementations of the method 200 and / or the method 300, the intelligence component is located in the first communication node, and the at least one field or the at least one parameter that is indicated includes the at least one first value derived based on the intelligence component.
[0048] In some implementations of the method 200 and / or the method 300, the intelligence component is located in the second communication node, and the at least one first value or additional information is delivered and is derived based on the intelligence component.
[0049] In some implementations of the method 200 and / or the method 300, the additional information is related to at least one of a physical layer (PHY) beam, a power headroom (PHR) , or a maximum output power (Pcmax) .
[0050] In some implementations of the method 200 and / or the method 300, an input of the intelligence component comprises at least one of: history scheduling information of a user device; a history or a current scheduling information of other user devices; performance of the user device; performance of a wireless communication system, or performance of the other user devices.
[0051] Further details of actions performed by one or more communication nodes within the wireless communication system 100, any of which may be included in the various implementations of the method 200, the method 300, or other methods, are now described.
[0052] In some implementations, a network device 104 (e.g., gNB) may indicate and / or adjust transmission configuration information (TCI) based on beam management. In particular of these implementations, the network device 104 may indicate the DCI in combination with an intelligence component. For example, the intelligence component may perform spatial-domain downlink beam prediction or temporal downlink beam prediction. Correspondingly, scheduling for TCI indication performed by the network device 104 in combination with prediction performed with the intelligence component may be more intelligent and / or efficient, including when using beam management enhancement with AI / ML model training and inference.
[0053] Additionally, TCI indication may be used in combination with an intelligence component in one or more of the following implementations or schemes.
[0054] In a first implementation (Scheme 1) involving TCI indication, the TCI field may not be included in a DCI or otherwise indicated, and a value of the TCI may be determined implicitly. For example, a communication node may use a best one of N predicted downlink (DL) transmit (Tx) beams predicted and / or output by an intelligence component, such as for beam management (BM) enhancement, to determine a value of the TCI. In some of these implementations, the intelligence component may determine and / or output only the top-1 predicted beams, that is N=1. In particular of these implementations, the TCI field may be omitted.
[0055] In a second implementation (Scheme 2) involving TCI indication, a TCI value may be indicated using at least one TCI candidate value determined or predicted by the intelligence component instead of, or in replace of, at least one TCI candidate value determined without the intelligence component. In some implementations, one or more TCI values may indicated using a table, such as a medium access control control element (MAC CE) table. The table may include a plurality of entries. At least one of the plurality of entries may be replaced by one or more predicted beams, such as one or more predicted downlink (DL) transmit (Tx) beams, predicted and / or output by the intelligence component. The one or more predicted beams may be beams within, from, and / or part of an N-number of predicted DL Tx beams predicted and / or output by the intelligence component, such as for beam management (BM) enhancement. For example, the network device 104 may indicate at least one TCI value using a table, such as a MAC CE table, that includes predicted beams within, from, and / or comprising the N predicted DL Tx beams of the predicted and / or output by the intelligence component, such as for BM enhancement.
[0056] In a third implementation (Scheme 3) involving TCI indication, a TCI may be indicated for N instances. In some of these implementations, the N instances may be a next N instances. For example, a table (e.g., a MAC CE table indicated by a MAC CE among radio resource control (RRC) configured candidate values, may include one or more predicted beams within, from, or that include N predicted DL Tx beams output or predicted by an intelligence component, such as for BM enhancement. For example, multiple entries of the table may be indicated for the TCI value for N instances. In addition or alternatively, a TCI pattern, or other candidate patterns configured by a higher layer (e.g., higher than the MAC layer) signaling associated with a next N instances, may be indicated directly or may be predicted and / or output by the intelligence component.
[0057] Accordingly, operations involving control information may be combined with an intelligence component to indicate one or more TCI values, which in turn may make the control information operations more intelligent and / or efficient.
[0058] Additionally, in some implementations, a network device 104 (e.g., a gNB) may indicate and / or adjust a modulation and coding scheme (MCS) based on channel state information (CSI) and / or channel quality information (CQI) reported from a user device 102. In some implementations, the MCS indication may be combined with an intelligence component, which in turn may reduce overhead, improve accuracy, and / or improve prediction. In turn, gNB scheduling for MCS indication may be more intelligent and / or efficient with AI / ML model training and inference.
[0059] Additionally, MCS indication may be used in combination with an intelligence component in one or more of the following implementations or schemes.
[0060] In a first implementation (Scheme 1) involving MCS indication, a MCS field may not be included in a DCI or otherwise indicated, and a value of the MCS may be determined implicitly. For example, a communication node may use a best one of N predicted MCS indices predicted or output by an intelligence component, or an MCS corresponding to the best one of N predicted CSI and / or N predicted CQI predicted and / or output by the intelligence component. In some implementations, the intelligence component may determine and / or output only the top-1 predicted MCS, or top-1 predicted CSI or CQI, that is N=1. In particular of these implementations, the MCS field may be omitted.
[0061] In a second implementation (Scheme 2) involving MCS indication, at least one candidate value for an MCS may be replaced by one or more values predicted by the intelligence component. For example, MCS indication may be performed using an MCS table, where X entries of the table are replaced by one or more predicted MCS values determined by the intelligence component, or one or more MCS corresponding to one or more predicted CSI or CQI values determined by the intelligence component. In some implementations, X is dynamically or semi-statically determined. In some of these embodiments, at least one specific modulation manner, and / or at least one finer code rate between two adjacent or among several MCS indexes may also be indicated or determined. As an example, MCS indication may be performed using a table that includes predicted beams within, from, or comprising N prediction values, such as of an MCS index, a CSI value, a CQI value, a code rate, or a modulation determined and / or output from the intelligence component.
[0062] In a third implementation (Scheme 3) involving MCS indication, MCS indication may be performed for N instances. In some of these implementations, N predicted indications may be for the next N instances. For example, a table, such as a MCS table, may be configured or predefined by RRC or may be dynamically determined by a radio network temporary identifier (RNTI) . The table may include one or more predicted MCS values within, from, or comprising N predictions, such as of an MCS index, a CSI value, a CQI value, a code rate, and / or a modulation, generated and / or output by the intelligence component. Multiple entries in the table may be used to provide MCS indication for N instances. In some implementations, a MCS pattern for a next N instances may be indicated directly, or by using one or more candidate patterns configured by higher layer signaling or predicted from the intelligence component.
[0063] Accordingly, operations involving control information may be combined with an intelligence component to indicate one or more MCS values, which in turn may make the control information operations more intelligent and / or efficient.
[0064] Additionally, in some embodiments, a network device 104 may indicate and / or adjust resource allocation, such as frequency domain resource allocation (FDRA) and / or time domain resource allocation (TDRA) , based on a scheduler in the network. In some embodiments, performance of resource allocation and / or resource allocation indication may be performed in combination with an intelligence component. For example, at least one of traffic arrival, size, or priority of a user device 102 may be predicted by the intelligence component. Correspondingly, a network device 104 configured to perform scheduling for resource allocation may be more intelligent and / or efficient when operating in conjunction with AI / ML model training and inference.
[0065] Additionally, resource allocation may be used in combination with an intelligence component in one or more of the following implementations or scheme.
[0066] In a first implementation (Scheme 1) involving resource allocation, at least one field of the control information used for resource allocation indication may not be used, and a value or location of the resource allocation may be determined implicitly. For example, a communication node may use a best one of N predicted locations predicted and / or output by an intelligence component. In some implementations, the intelligence component may be in the user device 102, and may output one or more predicted values based on traffic tracking for DL traffic, which in turn may be used to determine the resource allocation implicitly. As another example, the communication node may use the best one of the N predicted locations predicted by the intelligence component. The intelligence component may be in the user device 102 (i.e., at the UE side) , and may generate an output based on traffic prediction for UL traffic and / or UE-to-UE communication, which in turn may be used to determine the resource allocation implicitly. In addition or alternatively, the output of the intelligence component may include only the top-1 predicted locations, that is N=1. In particular of these implementations, the resource allocation field can be omitted. As another example, a sub-set within a set of fields may be used to achieve the function of resource allocation. Correspondingly, one or more fields for resource allocation may be omitted. For example, one or more fields for FDRA may be omitted, and only one or more fields for TDRA may be used. Additionally, in some implementations, FDRA may be determined implicitly in accordance with the first implementation.
[0067] In a second implementation (Scheme 2) involving resource allocation, resource allocation indication may be performed by replacing at least one candidate value for resource allocation with one or more predicted values. In particular of these implementations, one shot predicted indication is performed. For some of these embodiments, multi-transmission time interval (TTI) or cell scheduling may also be indicated. For example, TDRA indication may be performed using a table, such as a TDRA table configured by RRC signaling, where X entries of the table may be replaced by predicted allocations output by the intelligence component or predicted allocations within, from, or comprising N predicted allocations output from the intelligence component, and where X may be dynamically or semi-statically determined. As another example, TDRA indication may be performed using a table, such as a TDRA table configured by RRC signaling, that includes predicted allocations within, from, or comprising N predicted allocations output from the intelligence component.
[0068] In a third implementation (Scheme 3) involving resource allocation, resource allocation indication may be performed for N instances. In some implementations, N predicted resource allocation indications may be used for a next N instances. For example, a table, such as a TDRA table configured or predefined by RRC, may include one or more predicted allocations within, from, or comprising N predictions output by the intelligence component. In some implementations, multiple entries in the table may be indicated for N instances, or one entry with multiple elements (e.g., elements {k0 / 2, SLIV, mapping type} ) may be indicated for N instances. In addition, in some implementations, a resource allocation pattern for a next N instances may be indicated directly, or may be indicated using one or more candidate patterns configured by higher layer signaling or predicted from an intelligence component. Additionally, in some embodiments for FDRA, an offset and / or scaling may be used for a last (N-1) indications.
[0069] Additionally, in some implementations where the intelligence component is located in the network device 104, information (such as the latency for the traffic) may be reported from the user device 102 to the network device 104 to assist the network-side intelligence component in making its inference and / or prediction. For example, a user device 102 may report the measurement results of the latency for packets within a duration in one reporting instance. The network device 104 may use the information reported from user device 102 (which may be a single user device 102 or multiple user devices 102 in a same cell) to assist the network-side intelligence component in predicting traffic arrival, size, and / or priority.
[0070] Additionally, in some implementations where the intelligence component is located in the user device 102, signaling may be used for labels of the intelligence component may be indicated from the network 104 to the user device 102. In particular of these implementations, the signaling may be Layer 1 (L1) signaling (e.g. DCI) , Layer 3 (L2) signaling (e.g. MAC CE) , or Layer 3 (L3) signaling (e.g. RRC) . In some of these embodiments, in event there are no labels for unsupervised learning or reinforcement learning, the types of classification for the inference may be derived. In addition or alternatively, the user device 102 may report the predicted information to the network device 104, where the predicted information is based on the output of the intelligence component, such as traffic arrival, size, or priority, or predicted resource allocation. In addition or alternatively, the user device 102 may report the predicted information of N future time instances to the network device 104, where the predicted information is based on the output of intelligence component. In addition or alternatively, the user device 102 may report confidence and / or probability information of the predicted information to the network device 104.
[0071] Accordingly, operations involving control information may be combined with an intelligence component to indicate resource allocation, which in turn may make the control information operations more intelligent and / or efficient.
[0072] In some implementations, a network device 104 may indicate and / or configure transmit power control (TPC) for a PUCCH and / or for PUSCH, and / or open-loop power control (OLPC) set for a PUSCH based on UL transmission interference or reliability. In some of these implementations, power control indication may be combined with an intelligence component, such as one that outputs a beam pairs prediction, a power headroom report (PHR) prediction, or a maximum output power (Pcmax) prediction. As a result, power control for a user device through indication of TPC, OLPC, or sounding reference signal resource indicator (SRI) may be more intelligent and / or efficient through use of power control and / or beam management with AI / ML model training and / or inference.
[0073] Additionally, power control may be used in combination with an intelligence component in one or more of the following implementations or schemes.
[0074] In a first implementation (Scheme 1) involving power control, at least one field of the control information used for power control may not be used, and at least one value used for power control and / or power control indication may be determined implicitly. For example, a communication node may use a best one of N predicted locations predicted and / or output by an intelligence component. In some implementations, the intelligence component may generate an output based on power tracking for UL traffic and / or UE-to-UE communication to determine the power control implicitly. In some embodiments, the output of the intelligence component is only the top-1 prediction, that is N=1. In particular of these implementations, the power control fields may be omitted. As an example, a sub-set within a set of fields to achieve power control may be used, and at least one field for power control may not be used. For example, TPC for a PUCCH or for a PUSCH may be omitted, while OLPC set indication may be used. Additionally, in some embodiments, TPC for a PUCCH or a PUSCH may be determined implicitly in accordance with the first implementation.
[0075] In a second implementation (Scheme 2) involving power control, power control indication may be performed by replacing at least one candidate value for power control with one or more predicted values. This may also be considered as one shot predicted indication. For example, TPC for a PUCCH or PUSCH may be indicated using a table, where X entries are replaced by predicted values or steps output from the intelligence component, or by predicted values or steps within, from, or comprising N predictions output from the intelligence component, and where X may be dynamically or semi-statically determined. As an example, TPC for a PUCCH or a PUSCH may be indicated from a predefined or configured table or a table that includes predicted values or steps within, from, or comprising the N predictions generated and / or output by an intelligence component.
[0076] In a third implementation (Scheme 3) : power control may be performed for N instances. In some implementations, N predicted indications may be used for a next N instances. For example, a table, such as a predefined or configured table, may include one or more predicted values or steps within, from, or comprising N predictions output by the intelligence component, where multiple entries of the table may be indicated to provide TPC indications for N instances, or one entry with multiple elements may be used to provide TPC indication. For example, a TPC indication pattern for a next N instances may be used to indicate TPC directly, or at least one candidate pattern configured by higher layer signaling or predicted from an intelligence output may be used to indicate TPC. In some implementations, an offset and / or scaling may be used for a last (N-1) indications.
[0077] Additionally, in some implementations where the intelligence component is located in the network device 104, information (e.g. L1 beam related information, PHR, and / or Pcmax) may be reported from the user device 102 to the network device 104 to assist the network-side intelligence component for making inferences and / or predictions. For example, a user device 102 may report the measurement results of L1 beam related information within a duration in one reporting instance. The network device 104 may use the information reported from the user device 102 (which may include a single user device 102 or multiple user devices 102 in a same cell) to assist the network-side intelligence component for power control prediction.
[0078] In some implementations where the intelligence component is located in the user device 102, signaling used for labels of intelligence component may be indicated from the network device 104 to the user device 102, where the signaling may include L1 signaling (e.g. DCI) , L2 signaling (e.g. MAC CE) or L3 signaling (e.g. RRC) . In some implementations, in event there are no labels for unsupervised learning or reinforcement learning, types of classification for the inference may be derived. In addition or alternatively, the user device 102 may report the predicted information to the network device 104, where the predicted information may be based on output from the intelligence component, such as L1 beam or beam pair related information, PHR, or Pcmax. In some implementations, the user device 102 may report the predicted information of N future time instances to the network device 104, where the predicted information is based on output from the intelligence component. In addition or alternatively, the user device 102 may report confidence and / or probability information of the predicted information to the network device 104.
[0079] Accordingly, operations involving control information may be combined with an intelligence component to indicate power control, which in turn may make the control information operations more intelligent and / or efficient.
[0080] In some implementations, a network device 104 may indicate and / or configure information corresponding to energy or power saving, including information related to discontinuous transmission (DTX) and / or discontinuous reception (DRX) , a wake-up indication, a PDCCH monitoring adaptation indication, a minimum applicable scheduling offset indicator, or a SCell dormancy indication, as non-limiting examples. In some implementations, indication of information related to power saving may be combined with an intelligence component that outputs a UE traffic prediction and / or a power consumption prediction. Correspondingly, operation on network energy saving for the network device 104 and / or power saving for the user device 102 may be more intelligent and / or efficient through use of AI / ML model training and inference.
[0081] Additionally, energy or power saving indication may be combined with an intelligence component in one or more of the following implementations or schemes.
[0082] In a first implementation (Scheme 1) involving power saving, at least one field of the control information for energy / power saving indication may not be used, and at least one value used for energy / power saving may be determined implicitly. For example, the intelligence component may be located in the user device 102, and may make a prediction for traffic or power tracking, and may report a power saving pattern to the network device 104. An example of a power saving pattern may include: keep sleep for the on duration, skip duration, search space set group (SSSG) index, minimum applied k0 / 2, SCell dormancy pattern. As another example, the intelligence component may be located in the network device 104, and may use a model input based on X%of UE traffic tracking or reported from the X%of user devices 102, in order to derive the network energy saving manner. As another example, a communication node may use a best one of N predicted power saving patterns predicted and / or output by an intelligence component. In some implementations, the intelligence component may generate an output based on power tracking and / or UE-to-UE communication, to determine the power saving pattern implicitly. In addition or alternatively, an output of the intelligence component may be only a top-1 prediction, that is N=1. In some implementations, energy / power saving fields may be omitted. As another example, a sub-set within a set of fields may be used to achieve power saving indication. That is, at least one field for energy / power saving may not be used or omitted, where the at least one field may be for at least one of: a wake-up indication, a PDCCH monitoring adaptation indication, or a minimum applicable scheduling offset indicator, while a SCell dormancy indication may be used. In some implementations, a wake-up indication, a PDCCH monitoring adaptation indication, or a minimum applicable scheduling offset indicator may be determined implicitly, such as in accordance with the first implementation.
[0083] In a second implementation (Scheme 2) involving power saving, power saving indication may be performed by replacing at least one candidate value for power saving with one or more predicted values. This may also be considered as one shot predicted indication. For example, a monitoring adaptation may be indicated from a RRC configuration, where X entries are replaced by an output of an intelligence component, where the output is a predicted duration, SSSG, or other information within, from, or comprising N predictions output by the intelligence component, and where X may be dynamically and / or semi-statically determined. As another example, a monitoring adaptation may be indicated from a legacy RRC configuration or using a predicted duration, SSSG, or other configuration information within, from, or comprising N predictions output by the intelligence component.
[0084] In a third implementation (Scheme 3) involving power saving, power saving indication may be performed for N instances. In some implementations, N predicted indications may be used for a next N instances. For example, a table, such as a predefined or configured table, may include one or more predicted values or steps within, from, or comprising N predictions output by the intelligence component, multiple entries may be indicated for N instances, or one entry with multiple elements of may be indicated for the N instances. In an example, an energy or power saving indication pattern for a next N instances may be indicated directly, or at least one candidate pattern configured by higher layer signaling or predicted from the intelligence component may indicate a power saving pattern indirectly. In some embodiments, an offset or a scaling may be used for a last (N-1) indications. In addition or alternatively, a time domain pattern may include at least one of: a sleep and / or a wake up pattern, a skipping duration pattern, or a SSSG switching pattern. In addition or alternatively, a frequency domain pattern may include a SCell dormancy pattern.
[0085] Additionally, in some implementations where the intelligence component is located in the network device, information (e.g. assistance information of a preferred configuration, such as DTX / DRX, aggregated bandwidth, SCell configuration, a multiple input multiple output (MIMO) configuration, a RRC state, or minimum scheduling offset values, may be used to assist a user device 102 to achieve a power saving gain. In some implementations, the information may be reported from the user device 102 to the network device 104 to assist the intelligence component located in the network device 104 to make its prediction or inference. For example, the user device 102 may report preferred information with one or more values in one reporting instance. The network device 104 may use the information reported from user device 102 (which may include a single user device 102 or x%of user devices 102 in a same cell) to assist the network-side intelligence component for power control prediction.
[0086] Additionally, in some implementations where the intelligence component is located in the user device 102, signaling used for labels of the intelligence component can be indicated from the network device 104 to the user device 102, where the signaling may be L1 signaling (e.g. DCI) , L2 signaling (e.g. MAC CE) , or L3 signaling (e.g. RRC) . In some implementations, in event there are no labels for unsupervised learning or reinforcement learning, the types of classification for the inference may be derived. In addition or alternatively, the user device 102 may report the predicted information to the network device 104, where the predicted information is based on the output of intelligence component, such as the assistance information of a preferred configuration, which may include information such as DTX / DRX, aggregated bandwidth, a SCell configuration, a MIMO configuration, a RRC state, or minimum scheduling offset values in order for the network device 104 to assist the user device 102 to achieve a power saving gain. In some embodiments, the user device 102 may report the predicted information of N future time instances to the network device 104, where the predicted information is based on the output of intelligence component. In some implementations, the user device 102 may report confidence and / or probability information of the predicted information to the network device 104.
[0087] Accordingly, operations involving control information may be combined with an intelligence component to indicate power or energy saving, which in turn may make the control information operations more intelligent and / or efficient.
[0088] Additionally, in some implementations, a network device 104 may indicate and / or configure a downlink assignment index (DAI) , an UL DAI, a PUCCH resource indicator, a PDSCH-to-HARQ timing indicator, a one-shot HARQ-ACK request, an enhanced Type 3 codebook indicator, a PDSCH group index, a new feedback indicator, a number of requested PDSCH group (s) , a HARQ-ACK retransmission indicator, a PUCCH cell indicator, or a priority indicator for HARQ-ACK feedback. In some of these implementations, indication of this information may be combined with an intelligence component, such as one that performs feedback resource prediction or performance prediction. As a result, the operation on HARQ-ACK feedback may be more intelligent and / or efficient through use of AI / ML model training and inference.
[0089] Additionally, HARQ-ACK feedback may be performed in combination with an intelligence component in one or more of the following implementations or schemes.
[0090] In a first implementation (Scheme 1) involving HARQ-ACK feedback, at least one field of the control information for HARQ-ACK feedback may not be used, and at least one value used for HARQ-ACK feedback may be determined implicitly. For example, a communication node may use a best one of N predicted HARQ-ACK feedback generated and / or output by an intelligence component. In some implementations, the intelligence component may generate the output based on traffic performance tracking to determine the HARQ-ACK feedback prediction implicitly. In addition or alternatively, the output of the intelligence component is only a top-1 prediction, that is N=1. In some implementations, the HARQ-ACK feedback fields may be omitted. As an example, a sub-set within a set of fields may be used to achieve HARQ-ACK feedback. That is, at least one field for HARQ-ACK feedback, such as the DAI and the resource, may be omitted, while field for the timeline is used or included. In some implementations, the DAI and / or the resource may be determined implicitly, such as in accordance with the first implementation.
[0091] In a second implementation (Scheme 2) involving HARQ-ACK feedback, HARQ-ACK feedback indication may be performed by replacing at least one candidate value for HARQ-ACK feedback indication with one or more predicted values. This may also be considered as one shot predicted indication. For example, a resource may be used for feedback from a RRC configuration, where X entries are replaced by an output of the intelligence component, where the output includes predicted time and / or frequency domain resources or other information within, from, or comprising N predictions output by the intelligence component, and where X may be dynamically or semi-statically determined. As another example, a resource may be used for feedback from a RRC configuration, or predicted time and / or frequency domain resources or other configuration information within, from, or comprising N predictions of the output of the intelligence component may be used.
[0092] In a third implementation (Scheme 3) involving HARQ-ACK feedback, HARQ-ACK feedback indication may be performed for N instances. In some implementations, N predicted indications may be used for a next N instances. As an example, a table, such as a predefined or configured table, may include predicted values or steps within, from, or comprising N predictions output from the intelligence component, may include multiple entries indicated for N instances, or may include one entry with multiple elements to provide the indication for the N instances. Of note, for N predicted allocations: a time domain pattern may include, for example, a k1 pattern; and / or a frequency domain pattern may include, for example, a PUCCH cell pattern. As another example, a HARQ-ACK feedback indication pattern for a next N instances may be indicated directly, or may be indicated by at least one candidate pattern configured by higher layer signaling or predicted by the intelligence component. In some implementations, an offset or scaling may be used for a last (N-1) indications. In addition or alternatively, a time domain pattern may include, for example, a k1 (timeline for PDSCH to HARQ-ACK feedback) pattern. In addition or alternatively, a frequency domain pattern may include, for example, a PUCCH cell pattern.
[0093] Additionally, in some embodiments where the intelligence component is located in the network device 104, information (e.g. assistance information of a preferred configuration, such as a feedback resource or a codebook size) may be reported from the user device 102 to assist the network-side intelligence component to make inferences or predictions. For example, a user device 102 may report the preferred information with one or more values in one reporting instance. In some implementations, a network device 104 may use the information reported from user device 102 (which may include a single user device 102 or X%of user devices 102 in a same cell) to assist the network-side intelligence component for HARQ-ACK feedback prediction.
[0094] Additionally, in some embodiments where the intelligence component is located in the user device 102, signaling may be used for labels of the intelligence component for indication from the network device 104 to the user device 102, wherein the signaling may be L1 signaling (e.g. DCI) , L2 signaling (e.g. MAC CE) , or L3 signaling (e.g. RRC) . In some embodiments, in event there are no labels for unsupervised learning or reinforcement learning, the types of classification for the inference may be derived. In some embodiments, the user device 102 may report the predicted information to the network device 104, where the predicted information is based on the output of intelligence component, such as feedback resource and / or a codebook size. In some embodiments, the user device 102 may report the predicted information of N future time instances to the network device 104, where the predicted information is based on the output of intelligence component. In some embodiments, the user device 102 may report confidence and / or probability information of the predicted information to the network device 104.
[0095] Accordingly, operations involving control information may be combined with an intelligence component to indicate and / or perform HARQ-ACK feedback, which in turn may make the control information operations more intelligent and / or efficient.
[0096] The description and accompanying drawings above provide specific example embodiments and implementations. The described subject matter may, however, be embodied in a variety of different forms and, therefore, covered or claimed subject matter is intended to be construed as not being limited to any example embodiments set forth herein. A reasonably broad scope for claimed or covered subject matter is intended. Among other things, for example, subject matter may be embodied as methods, devices, components, systems, or non-transitory computer-readable media for storing computer codes. Accordingly, embodiments may, for example, take the form of hardware, software, firmware, storage media or any combination thereof. For example, the method embodiments described above may be implemented by components, devices, or systems including memory and processors by executing computer codes stored in the memory.
[0097] Throughout the specification and claims, terms may have nuanced meanings suggested or implied in context beyond an explicitly stated meaning. Likewise, the phrase “in one embodiment / implementation” as used herein does not necessarily refer to the same embodiment and the phrase “in another embodiment / implementation” as used herein does not necessarily refer to a different embodiment. It is intended, for example, that claimed subject matter includes combinations of example embodiments in whole or in part.
[0098] In general, terminology may be understood at least in part from usage in context. For example, terms, such as “and” , “or” , or “and / or, ” as used herein may include a variety of meanings that may depend at least in part on the context in which such terms are used. Typically, “or” if used to associate a list, such as A, B or C, is intended to mean A, B, and C, here used in the inclusive sense, as well as A, B or C, here used in the exclusive sense. In addition, the term “one or more” as used herein, depending at least in part upon context, may be used to describe any feature, structure, or characteristic in a singular sense or may be used to describe combinations of features, structures or characteristics in a plural sense. Similarly, terms, such as “a, ” “an, ” or “the, ” may be understood to convey a singular usage or to convey a plural usage, depending at least in part upon context. In addition, the term “based on” may be understood as not necessarily intended to convey an exclusive set of factors and may, instead, allow for existence of additional factors not necessarily expressly described, again, depending at least in part on context.
[0099] Reference throughout this specification to features, advantages, or similar language does not imply that all of the features and advantages that may be realized with the present solution should be or are included in any single implementation thereof. Rather, language referring to the features and advantages is understood to mean that a specific feature, advantage, or characteristic described in connection with an embodiment is included in at least one embodiment of the present solution. Thus, discussions of the features and advantages, and similar language, throughout the specification may, but do not necessarily, refer to the same embodiment.
[0100] Furthermore, the described features, advantages and characteristics of the present solution may be combined in any suitable manner in one or more embodiments. One of ordinary skill in the relevant art will recognize, in light of the description herein, that the present solution can be practiced without one or more of the specific features or advantages of a particular embodiment. In other instances, additional features and advantages may be recognized in certain embodiments that may not be present in all embodiments of the present solution.
[0101] The subject matter of the disclosure may also relate to or include, among others, the following aspects:
[0102] A first aspect includes a method for wireless communication that includes: determining, by a first communication node, control information that includes at least one field or at least one parameter determined by an intelligence component, the at least one field or the at least one parameter associated with a function; and transmitting, by the first communication node, the control information to a second communication node for performance of the function.
[0103] A second aspect includes a method for wireless communication that includes: receiving, by a second communication node, control information comprising at least one field or at least one parameter determined by an intelligence component; and performing, by the second communication node, a function according to the control information.
[0104] A third aspect includes any of the first or second aspects, and further includes wherein at least one first value used for the at least one field or the at least one parameter of the function is derived based on the intelligence component, and the intelligence component is located in the first communication node or the second communication node.
[0105] A fourth aspect includes the third aspect, and further includes wherein the at least one first value includes one of a plurality of predicted values, the plurality of predicted values derived based on the intelligence component.
[0106] A fifth aspect includes the fourth aspect, and further includes wherein the at least one first value includes a best one of a plurality of predicted first values and the at least one field or the at least one parameter is absent in the control information.
[0107] A sixth aspect includes any of the third through fifth aspects, and further includes wherein the at least one first value is used to replace at least one second value for the parameter that is determined without the intelligence component.
[0108] A seventh aspect includes any of the third through sixth aspects, and further includes wherein the at least one first value includes at least one value in at least one entry of a vector or a table.
[0109] An eighth aspect includes any of the third through seventh aspects, and further includes wherein the at least one first value indicates one instance or a plurality of instances, wherein the plurality of instances is indicated by multiple entries or a pattern of the at least one field or at least one parameter.
[0110] A ninth aspect includes any of the third through eighth aspects, and further includes wherein the at least one first value includes a plurality of predicted values for the at least one field or the at least one parameter, or for a plurality of parameters to represent or replace the at least one field or the at least one parameter.
[0111] A tenth aspect includes the ninth aspect, and further includes wherein the plurality of predicted values corresponds to different granularities or offsets from the at least one first value.
[0112] An eleventh aspect includes any of the third through tenth aspects, and further includes wherein the at least one field or the at least one parameter includes transmission configuration information (TCI) , and wherein the at least one first value corresponds to at least one predicted downlink transmission beam.
[0113] A twelfth aspect includes any of the third through eleventh aspects, and further includes wherein the at least one field or the at least one parameter includes a modulation and coding scheme (MCS) , and wherein the at least one first value corresponds to at least one predicted MCS index, at least one channel state information (CSI) , or at least one channel quality information (CQI) .
[0114] A thirteenth aspect includes any of the third through twelfth aspects, and further includes wherein the function includes resource allocation, and wherein the at least one first value corresponds to at least one predicted value of a location for the at least one field or the at least one parameter of the resource allocation.
[0115] A fourteenth aspect includes any of the third through thirteenth aspects, and further includes wherein the function includes power control, and wherein the at least one first value corresponds to at least one predicted value of power tracking for at least one physical channel.
[0116] A fifteenth aspect includes any of the third through fourteenth aspects, and further includes wherein the at least one first value corresponds to at least one value of a traffic or power tracking, and wherein the function includes determining a power saving pattern.
[0117] A sixteenth aspect includes any of the third through fifteenth aspects, and further includes wherein the function includes power saving indication, and wherein the at least one first value corresponds to at least one predicted value of a monitoring manner for the at least one field or the at least one parameter of the power saving indication.
[0118] A seventeenth aspect includes any of the third through sixteenth aspects, and further includes wherein the function includes feedback indication, and wherein the at least one first value corresponds to at least one predicted value of a resource or a timeline for the at least one field or the at least one parameter of the feedback indication.
[0119] An eighteenth aspect includes the eighth aspect, and further includes wherein the multiple entries or the pattern of the at least one field or the at least one parameter includes an N-number of predicted values of the at least one field or the at least one parameter, and wherein one or more offsets or a scaling is used to indicate a last (N-1) instances of the N-number of predicted values of the at least one field or the at least one parameter.
[0120] A nineteenth aspect includes any of the third or eleventh through eighteenth aspects, and further includes wherein the intelligence component is located in the first communication node, the method further comprising: indicating the at least one field or the at least one parameter including the at least one first value derived based on the intelligence component.
[0121] A twentieth aspect includes any of the third or eleventh through eighteenth aspects, and further includes wherein the intelligence component is located in the second communication node, the method further comprising: delivering the at least one first value or additional information derived based on the intelligence component.
[0122] A twenty-first aspect includes any of the fourteenth or twentieth aspects, and further includes wherein the additional information is related to at least one of a physical layer (PHY) beam, a power headroom (PHR) , or a maximum output power (Pcmax) .
[0123] A twenty-second aspect includes any of the thirteenth or nineteenth aspects, and further includes wherein an input of the intelligence component comprises at least one of: history scheduling information of a user device; a history or a current scheduling information of other user devices; performance of the user device; performance of a wireless communication system, or performance of the other user devices.
[0124] A twenty-third aspect includes a wireless communications apparatus comprising a processor and a memory, wherein the processor is configured to read code from the memory to implement any of the first through twenty-second aspects.
[0125] A twenty-fourth aspect includes a computer program product comprising a computer-readable program medium comprising code stored thereupon, the code, when executed by a processor, causing the processor to implement any of the first through twenty-second aspects.
[0126] In addition to the features mentioned in each of the independent aspects enumerated above, some examples may show, alone or in combination, the optional features mentioned in the dependent aspects and / or as disclosed in the description above and shown in the figures.
Claims
1.A method for wireless communication, the method comprising:determining, by a first communication node, control information comprising at least one field or at least one parameter determined by an intelligence component, the at least one field or the at least one parameter associated with a function; andtransmitting, by the first communication node, the control information to a second communication node for performance of the function.2.A method for wireless communication, the method comprising:receiving, by a second communication node, control information comprising at least one field or at least one parameter determined by an intelligence component; andperforming, by the second communication node, a function according to the control information.3.The method of any of claims 1 or 2, wherein at least one first value used for the at least one field or the at least one parameter of the function is derived based on the intelligence component, and the intelligence component is located in the first communication node or the second communication node.4.The method of claim 3, wherein the at least one first value comprises one of a plurality of predicted values, the plurality of predicted values derived based on the intelligence component.5.The method of claim 4, wherein the at least one first value comprises a best one of a plurality of predicted first values and the at least one field or the at least one parameter is absent in the control information.6.The method of claim 3, wherein the at least one first value is used to replace at least one second value for the parameter that is determined without the intelligence component.7.The method of claim 3, wherein the at least one first value comprises at least one value in at least one entry of a vector or a table.8.The method of claim 3, wherein the at least one first value indicates one instance or a plurality of instances, wherein the plurality of instances is indicated by multiple entries or a pattern of the at least one field or at least one parameter.9.The method of claim 3, wherein the at least one first value comprises a plurality of predicted values for the at least one field or the at least one parameter, or for a plurality of parameters to represent or replace the at least one field or the at least one parameter.10.The method of claim 9, wherein the plurality of predicted values corresponds to different granularities or offsets from the at least one first value.11.The method of claim 3, wherein the at least one field or the at least one parameter comprises transmission configuration information (TCI) , and wherein the at least one first value corresponds to at least one predicted downlink transmission beam.12.The method of claim 3, wherein the at least one field or the at least one parameter comprises a modulation and coding scheme (MCS) , and wherein the at least one first value corresponds to at least one predicted MCS index, at least one channel state information (CSI) , or at least one channel quality information (CQI) .13.The method of claim 3, wherein the function comprises resource allocation, and wherein the at least one first value corresponds to at least one predicted value of a location for the at least one field or the at least one parameter of the resource allocation.14.The method of claim 3, wherein the function comprises power control, and wherein the at least one first value corresponds to at least one predicted value of power tracking for at least one physical channel.15.The method of claim 3, wherein the at least one first value corresponds to at least one value of a traffic or power tracking, and wherein the function comprises determining a power saving pattern.16.The method of claim 3, wherein the function comprises power saving indication, and wherein the at least one first value corresponds to at least one predicted value of a monitoring manner for the at least one field or the at least one parameter of the power saving indication.17.The method of claim 3, wherein the function comprises feedback indication, and wherein the at least one first value corresponds to at least one predicted value of a resource or a timeline for the at least one field or the at least one parameter of the feedback indication.18.The method of claim 8, wherein the multiple entries or the pattern of the at least one field or the at least one parameter comprises an N-number of predicted values of the at least one field or the at least one parameter, and wherein one or more offsets or a scaling is used to indicate a last (N-1) instances of the N-number of predicted values of the at least one field or the at least one parameter.19.The method of any of claims 3 or 11 to 18, wherein the intelligence component is located in the first communication node, the method further comprising: indicating the at least one field or the at least one parameter including the at least one first value derived based on the intelligence component.20.The method of any of claims 3 or 11 to 18, wherein the intelligence component is located in the second communication node, the method further comprising: delivering the at least one first value or additional information derived based on the intelligence component.21.The method of any of claim 14 or 20, wherein the additional information is related to at least one of a physical layer (PHY) beam, a power headroom (PHR) , or a maximum output power (Pcmax) .22.The method of any of claim 13 or 19, wherein an input of the intelligence component comprises at least one of: history scheduling information of a user device; a history or a current scheduling information of other user devices; performance of the user device; performance of a wireless communication system, or performance of the other user devices.23.A wireless communications apparatus comprising a processor and a memory, wherein the processor is configured to read code from the memory to implement a method of any of claims 1 to 22.24.A computer program product comprising a computer-readable program medium comprising code stored thereupon, the code, when executed by a processor, causing the processor to implement a method of any of claims 1 to 22.