Reference signaling overhead reduction device and method

Abstract

A network device receives an indication from a user equipment (UE) that the network device is to transition to sparse reference signaling for the UE, and then the network device sends the sparse reference signaling to the UE. The sparse reference signaling conforms to a sparse signaling pattern, which is determined at the UE side based on a previous reference signaling previously sent to the UE or another UE. At the UE side, the sparse reference signaling is received from the network device, and channel measurement and prediction are performed based on the received sparse reference signaling.

Description

[0001] This application claims priority to U.S. patent application No. 16 / 556,850, filed on August 30, 2019, entitled “REFERENCE SIGNALING OVERHEAD REDUCTION APPARATUS AND METHODS,” the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to wireless communications, and more particularly to reducing reference signaling overhead in wireless communication networks. Background Art

[0003] Signaling overhead in wireless communication networks can be a significant concern because it takes up network resources that could otherwise be used for communication. For example, pilot overhead incurred by channel estimation and acquisition in massive Multiple Input Multiple Output (MIMO) systems is a significant drawback.

[0004] Reducing reference signaling overhead such as pilot overhead without significant performance loss in operations such as reference signal based channel estimation remains a difficult problem. Assuming the signaling overhead is the same, reducing the signaling overhead can be equivalently regarded as providing performance gain compared to existing wireless communication systems. Summary of the invention

[0005] The embodiments of the present disclosure can be applicable to various aspects of user equipment operation, including performing CSI acquisition and feedback using Channel State Information Reference Signal (CSI-RS) signaling, and / or performing channel estimation for data demodulation purposes using Demodulation Reference Signal (DM-RS) signaling and / or Phase Tracking Reference Signal (PT-RS) signaling.

[0006] CSI-RS-based acquisition is performed by the user equipment (UE) through measurements on the CSI-RS antenna port side. Channel estimation for data demodulation purposes is performed by the UE through measurements on the DM-RS and / or PT-RS antenna port side. The embodiments of the present disclosure are mainly focused on reducing the reference signaling overhead associated with CSI-RS, DM-RS and / or PT-RS. For example, this overhead is a major disadvantage in frequency division duplex (FDD) massive MIMO scenarios. Although massive MIMO has a great potential to achieve high data rates by sending multiple parallel data streams, the reference signaling overhead increases proportionally with the number of data streams. In addition, for example, the large reference signaling overhead associated with the pilot signal leads to pilot pollution in which the pilots sent by base stations in different cells overlap on time-frequency resources, which in turn leads to poor channel estimation / CSI acquisition performance.

[0007] One aspect of the present disclosure relates to a method performed by a network device in a wireless communication network. The method includes: receiving an indication from a UE that the network device is to transition to sparse reference signaling for the UE; and sending the sparse reference signaling to the UE in accordance with a sparse signaling pattern. The sparse signaling pattern is determined based on a previous reference signaling previously sent to the UE or another UE.

[0008] According to another embodiment, a network device for a wireless communication network includes a processor and a processor readable memory. The processor readable memory is coupled to the processor and stores processor executable instructions, and when the processor executable instructions are executed by the processor, the processor performs a method. As described above, the method includes: receiving an indication from a UE that the network device is to transition to sparse reference signaling for the UE; and sending the sparse reference signaling to the UE. The sparse reference signaling conforms to a sparse signaling pattern, and the sparse signaling pattern is determined based on a previous reference signaling previously sent to the UE or another UE.

[0009] A processor readable memory may be used to store processor executable instructions which, when executed by a processor in a network device in a wireless communication network, cause the processor to perform such a method.

[0010] Some embodiments relate to a UE. For example, a method performed by a UE in a wireless communication network may include: receiving sparse reference signaling from a network device in the wireless communication network, the sparse reference signaling being determined based on a previous reference signaling previously received by the UE or another UE; and performing channel measurement and prediction based on the received sparse reference signaling.

[0011] According to another embodiment, a UE includes a processor and a processor-readable memory, the processor-readable memory being coupled to the processor and storing processor-executable instructions, the processor-executable instructions causing the processor to perform a method when executed by the processor. The method includes: receiving sparse reference signaling from a network device in a wireless communication network, the sparse reference signaling being determined based on a previous reference signaling previously received by the UE or another UE; and performing channel measurement and prediction based on the received sparse reference signaling.

[0012] In yet another embodiment, a processor readable memory is used to store processor executable instructions, which when executed by a processor in a network device in a wireless communication network, cause the processor to perform such a method. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Embodiments of the present disclosure are described below with reference to the accompanying drawings, in which:

[0014] Figure 1 is a block diagram illustrating a 32-port CSI-RS pattern in a time-frequency grid;

[0015] Figure 2 A block diagram illustrating an example of a base station (BS) and a UE and operations that may be performed in some embodiments;

[0016] Figure 3 To illustrate a signal flow diagram of BS-UE signaling according to another embodiment;

[0017] Figure 4 A two-dimensional diagram including a dense pilot signal pattern and two exemplary sparse patterns #1 and #2;

[0018] Figure 5 Examples of ML module training according to two embodiments are shown;

[0019] Figure 6 A block diagram illustrating an example of a varying sparse reference signaling pattern in a time-frequency grid including multiple sparse patterns across resource blocks (RBs) within a time slot;

[0020] Figure 7 A block diagram illustrating another example of a varying sparse reference signaling pattern in a time-frequency grid including multiple sparse patterns across multiple time slots;

[0021] Figure 8 A block diagram illustrating an example of a varying sparse reference signaling pattern in a time-frequency grid including multiple sparse patterns across RBs and time slots;

[0022] Fig. 9 A block diagram illustrating an example of a varying sparse reference signaling pattern including multiple sparse patterns and providing unequal reference signal densities in a time-frequency grid;

[0023] Fig.10 is a block diagram illustrating an example of a BS and a UE and operations that may be performed in other embodiments;

[0024] Fig.11 To illustrate a signal flow diagram of BS-UE signaling according to another embodiment;

[0025] Fig.12 A flowchart showing an example of a method according to one embodiment;

[0026] Fig.13 An exemplary communication system in which embodiments of the present disclosure may be implemented is shown;

[0027] Fig.14A is a block diagram of an exemplary electronic device;

[0028] Fig. 14B is a block diagram of an exemplary base station;

[0029] Fig.15 A block diagram of the component modules. DETAILED DESCRIPTION

[0030] The embodiments of the present disclosure can be applied to any of various types of communications. For example, consider an FDD system in which a base station or other network device is used to send reference signaling to a user equipment (UE) in the form of CSI-RS signaling, and the user equipment performs channel state information (Channel State Information, CSI) acquisition based on the CSI-RS signaling and feeds back the channel state information to the base station. Then, the base station also performs a CSI acquisition process based on feedback from the UE. According to one embodiment, a CSI-RS configuration including sparse CSI-RS signaling is determined by the UE and signaled to the base station, thereby reducing reference signaling overhead.

[0031] Time Division Duplex (TDD) applications are also possible. In a TDD system, a network device such as a base station sends reference signaling to a UE in the form of DM-RS signaling to enable the UE to perform channel estimation. In some embodiments, the UE determines a sparse DM-RS signaling configuration to reduce signaling overhead, and provides an indication of the signaling configuration to the base station, which will be applied by the base station.

[0032] Partial channel estimation is performed using sparse reference signaling, and channel prediction is performed on any channel element for which the sparse signaling does not include a reference signal. In some embodiments, channel prediction uses the results of partial channel estimation.

[0033] In these examples, for FDD applications in massive MIMO and the like, the goal is to reduce CSI-RS overhead, while for TDD applications, the goal is to reduce DM-RS overhead. CSI-RS and DM-RS are just examples, and other embodiments may be applied to other types of reference signaling.

[0034] Reference signaling overhead can be reduced by exploiting channel correlation in time and frequency. Figure 1 32-port CSI-RS pattern in a time-frequency grid. th This mode is supported by 5G NR (5th Generation New Radio) Release 15 and includes corresponding pilots for each antenna port (AP) 0 to 31. The pattern repeats in time and frequency with a configurable period that depends on the channel correlation in time and frequency.

[0035] In addition to the correlation in time and frequency, the channel correlation between antennas can also be used to improve the performance in operations such as channel acquisition and / or channel estimation. In general, there is a correlation between the channel coefficients corresponding to different transmit antenna elements from the transmitter. In other words, for a number of M transmit antenna elements, the coefficients (h1, h2, ..., h M ) are statistically correlated. While this correlation is low in environments with strong scattering propagation, the correlation between antennas can be quite significant in weak scattering environments with, for example, a strong Line of Sight (LOS) component and relatively few Non Line of Sight (NLOS) components. If the number of channel parameters (path amplitude, path delay, Angle of Arrival (AoA) / Angle of Departure (AoD)) is less than the number of antennas, the channels corresponding to a subset of transmit antennas can usually be copied from the channels corresponding to the remaining transmit antennas.

[0036] See, for example, P. Dong, H. Zhang, and G. Y. Li, “Machine learning prediction based CSI acquisition for FDD massive MIMO downlink,” IEEE GLOBECOM, December 2018. Using channel correlations between antennas, the estimated channels at a subset of antennas are used to predict the channels at other antennas. If the number of channel parameters is significantly smaller than the number of transmit antennas, channels can be constructed for pilot-free antennas in sparse pilot mode. However, this technique is based on sending pilots only on a fixed subset of transmit antennas that does not cover all transmit antennas. Therefore, as the channel conditions move toward a highly scattering environment, the channel prediction error for the pilot-free antennas may increase dramatically, resulting in an imbalance in the estimation errors on different CSI-RS ports. This technique is also based on narrowband transmissions as opposed to wideband transmissions, such as Orthogonal Frequency Division Multiplex (OFDM) transmissions. Moreover, online training to determine channel correlations in communications with the UE is not supported. Furthermore, as disclosed herein, the determination of antenna subsets is at the base station side, not at the UE side.

[0037] Embodiments disclosed herein provide a novel method to jointly exploit channel correlation in space / time / frequency to reduce reference signaling overhead such as pilot overhead. In some embodiments, reduced density or sparse reference signaling configuration allows balanced pilot density between different antenna ports. In other embodiments, different antenna ports have different densities of reference signaling in sparse signaling configuration.

[0038] In some embodiments, signaling from the UE to the base station or other network device is introduced. For example, such signaling can be used to indicate that training is complete. In addition to or in lieu of such signaling, signaling from the UE to the network device can be used to indicate that retraining is required to support adjusting the reference signaling configuration to a lower or higher density.

[0039] In some embodiments, support for online training is provided in addition to or even in place of offline training. In offline training, taking FDD applications as an example, the UE measures a geographic area and may measure the channel at the CSI-RS antenna port at different locations within the area and / or using different base stations within the area. Although dense signaling during training may generally be the first choice for expected better performance, training can be performed as long as the channel measurement results include some elements in the input and output data sets. Once sufficient channel measurement results are collected, one or more predictors can be developed by training a machine learning (ML) module based on one or more sparse pilot patterns, etc. The UE provides an indication of the pilot pattern to the base station, which then uses the pilot pattern, and then the UE uses the predictor to predict one or more elements of the channel. In online training, again taking FDD applications as an example, when the UE is performing normal data demodulation / CSI feedback, the UE collects channel measurements based on the downlink CSI-RS signaling sent by the network device. As in offline training, once sufficient channel measurements are collected, one or more predictors can be developed based on one or more pilot patterns, the UE provides an indication of the pilot pattern to the base station, the base station then uses the pilot pattern, and the UE then uses the predictor to predict one or more elements of the channel.

[0040] In some embodiments, the network device configures one or more parameters for the UE to enable the UE to perform channel estimation based on the sparse reference signaling. Therefore, the BS and the UE are consistent in configuration. The UE configuration is within the jurisdiction of the network. In some embodiments, the UE indicates to the network device that the multiple sparse pilot patterns that the UE has determined are suitable for the UE to use. The network device can then select a pattern and configure the UE for the pattern.

[0041] Online training may generally be preferred to avoid network equipment being offline during training. Since the UE participating in the training may be more likely to actively communicate with the network equipment after the training is completed, online training may also be more suitable than offline training to support training and / or predictors for each UE.

[0042] ML is an emerging and rapidly developing field due to advances in computer architecture (e.g., General Purpose Graphics Processing Units (GP-GPUs)). For example, deep convolutional neural networks have attracted attention due to their ability to find patterns in data with intrinsic structure by using convolutional filters. The application of ML in the field of communications is largely unexplored, but may help outperform existing solutions and / or help conceptually reshape wireless networks. Depending on the implementation of the ML mechanism, the ML modules mentioned herein are intended to be components or blocks. An example of an ML implementation is a neural network implemented in hardware, one or more components of executing software, or a combination thereof.

[0043] It should be appreciated that in some embodiments, ML is used for channel prediction based on sparse reference signaling. While ML can be very useful and efficient in predicting channel coefficients and / or other parameters for "non-pilot" channels or locations based on sparse reference signaling, etc., ML represents only one possible type of implementation. Non-ML implementations are also possible.

[0044] As described elsewhere herein, pilot overhead in FDD massive MIMO is a significant drawback. Embodiments disclosed herein are to reduce pilot overhead without significant performance loss in reference signal-based operations such as channel estimation. In other words, assuming the same signaling overhead, embodiments may provide performance gains compared to prior art.

[0045] The present disclosure describes techniques used by a UE to learn or otherwise determine correlations between channel coefficients in space (antennas / antenna ports), time, and frequency. These correlations can then be used to determine a sparse reference signaling pattern that uses a low density pilot configuration to reduce pilot overhead, etc. The UE provides an indication of the sparse reference signaling pattern to a network device, which then uses the signaling pattern to reduce reference signaling overhead.

[0046] Embodiments disclosed herein include exemplary embodiments for reducing CSI-RS pilot overhead in FDD massive MIMO, etc. and reducing DM-RS pilot overhead and / or PT-RS pilot overhead in TDD massive MIMO, etc. To reduce reference signaling overhead, these embodiments exploit channel correlation across space, time, and frequency.

[0047] Figure 2A block diagram 200 is shown of a UE 206 and a base station (BS) 202 including a plurality of antenna elements 204. For example, each antenna element 204 may be associated with an antenna port. However, an antenna port is a logical structure and may generally include one or more associated antenna elements 204. In one embodiment, antenna ports are defined such that a channel on which a symbol on the antenna port is transmitted may be inferred from a channel on which another symbol on the same antenna port is transmitted. Antenna ports may also be referred to as virtual antenna ports or logical antenna ports.

[0048] Reference signals or pilots (eg, CSI-RS and DM-RS) may be beamformed using analog beamforming and / or digital beamforming. Therefore, the antenna port may be a physical antenna port or a virtual antenna port actually generated after beamforming.

[0049] Virtual antenna ports may also or alternatively correspond to MIMO layers. Thus, the antenna ports may include virtual antenna ports corresponding to MIMO layers and / or beams. The number of virtual antenna ports may be less than the number of physical antenna ports.

[0050] Therefore, it should be understood that the teachings herein can be applied to embodiments that support features such as beamforming and / or virtual antenna ports. For example, the sparse pilot pattern density can be defined, specified or considered based on the pilot or signaling density per (virtual) antenna port, per MIMO layer and / or per beam.

[0051] More detailed examples of BSs and UEs are provided elsewhere herein. Operations that may be performed in some embodiments to reduce CSI-RS overhead in FDD massive MIMO or the like are shown at 210, 212, 214, 216, 218.

[0052] During the training phase in which the UE 206 is determining suitable sparse reference signaling that can be used to reduce overhead without significantly affecting the performance in determining channel coefficients or parameters, at 210, the BS sends CSI-RS signaling to the UE. In some embodiments, the CSI-RS signaling can be full-density signaling. Full-density signaling is also referred to herein as dense signaling, which is intended to indicate that all reference signal locations (location / position) are filled with reference signals such as pilots. Figure 1 , for example, there is no pilot location (location / position) that is not filled or does not transmit a pilot signal. This is an example of dense reference signaling.

[0053] At 212, CSI acquisition and feedback performed by UE 206 is shown. UE 206 sends CSI feedback corresponding to the CSI-RS transmit antenna ports to BS 202, and CSI-RS signaling is sent by the BS through these ports. In some embodiments, due to UE mobility, etc., 210 and 212 are repeated for different channel implementations until UE 206 collects sufficient UE channel estimates.

[0054] Figure 2 214 in 214 indicates that the UE 206 determines the channel correlation across antenna ports / time / frequency based on the channel measurement results collected at 214 corresponding to the pilot positions. In some embodiments, ML is used to implement 214. This is described in detail by way of example elsewhere herein.

[0055] Based on the antenna port correlation in the illustrated embodiment, UE 206 optimizes the sparse reference signaling pattern and corresponding predictor to be used for UE 206 and / or other possible UEs in addition to or instead of UE 206. The sparse reference signaling pattern determined or otherwise obtained by the UE based on the collected channel measurement results does not need to be used only for the UE subsequently. For example, the same sparse reference signaling pattern is used for all UEs located at or near one or more locations where channel measurement results were previously collected to determine or obtain the sparse reference signaling pattern. At 216, an indication of the sparse reference signaling pattern is sent from UE 206 to BS 202. One or more of the overall reference signaling density, the reference signaling density for each antenna port or antenna port subset, the CSI-RS pattern index or identifier, etc. can be sent from the UE to BS 202 at 216 to inform the BS that the sparse reference signaling pattern has been determined and will be applied.

[0056] Then, at 218, BS 202 sends sparse reference signaling conforming to the above pattern to the same UE 206 and / or another possible UE, and at 220, the UE performs CSI acquisition and feedback. This is similar to 210 and 212 above, but involves sparse CSI-RS signaling, which only includes a subset of CSI-RS from the denser CSI-RS signaling at 210. For CSI acquisition and feedback 220, UE 206 estimates the channel at the pilot positions in the sparse reference signaling, predicts the channel at the non-pilot positions, and uses the channel estimation and channel prediction to derive CSI, such as Channel Quality Indicator (CQI), Rank Indicator (RI), and Precoding Matrix Indicator (PMI) and other appropriate CSI to send to BS 202.

[0057] In some implementations, BS 202 configures UE 206 for low-density reference signaling prior to 218. This may be useful in at least a scenario where a sparse reference signaling pattern determined or otherwise obtained by one UE is to be used by a base station for a different UE. The different UEs may then receive from the base station any information that the UE needs to perform CSI acquisition and feedback based on the sparse reference signaling.

[0058] Figure 3 FIG. 3 is a signal flow diagram showing BS-UE signaling according to another embodiment. In the signal flow diagram 300, the BS and the UE (labeled as UE1) participate in the training phase 310. Although Figure 3 In the example, only one UE is shown to participate in the training phase 310, but in other embodiments, multiple UEs may participate in the training phase with the BS and / or other BSs.

[0059] 312 and 314 show the CSI-RS / CSI feedback signaling interaction between the BS and UE1. This interaction is similar to Figure 2 The CSI-RS transmission at 210 and the corresponding feedback described above. The BS sends CSI-RS signaling (possibly dense CSI-RS signaling) at 312 and receives corresponding CSI feedback from UE1 at 314. Figure 3 Only one CSI-RS / CSI feedback interaction is shown at 312 and 314 in FIG. 1 , but there may be multiple interactions between the BS and UE1 as UE1 moves between multiple locations during a training phase or the like.

[0060] In some embodiments, UE1 provides an indication of the current UE location corresponding to the CSI feedback, or the BS determines the UE location in other ways. The UE location information may be useful in embodiments where the training is not necessarily UE-specific, in which case the training based on feedback from a certain UE is also used for communication with one or more other UEs. For example, the BS may associate the UE location information with the sparse reference signaling configuration of UE1 at one UE location, and then use the same sparse reference signaling configuration for other UEs at or near the same UE location.

[0061] UE location is not necessarily used only in implementations where training is not UE-specific. The UE may also track its own location and record information associated with the sparse reference signaling pattern and / or predictor in a memory for use the next time the UE is at or near one of its previous locations. In addition to or in lieu of implementations where training is not UE-specific, UE location may be tracked in implementations with UE-specific training to enable the BS and / or UE to determine when the UE has moved an amount that may affect channel conditions. In response to detecting such movement, the BS and / or UE may initiate a new training phase or a retraining phase for the new UE location.

[0062] UE1 generates CSI for feedback at 314 providing data samples collected by UE1. UE1 uses the collected data samples at 316 to determine a sparse reference signaling pattern by training one or more ML modules, etc. Data sample collection does not need to be fully completed before starting pattern determination at 316. For example, data samples can be used for ML module training when these data samples are collected. In some embodiments, UE1 sends an indication to the BS at 318 to signal the end of training and / or provide the BS with an indication of a sparse reference signaling pattern to be used for UE1 and / or possibly one or more other UEs.

[0063] In operation phase 320, the sparse reference signaling pattern determined at 316 is used in CSI-RS signaling for UE2. In this example, the training is not UE-specific. The training performed with UE1 during the training phase is applied to one or more other UEs, in this case UE2, and at 321, the UE is configured for sparse CSI-RS configuration. For example, information that UE2 needs to perform channel prediction on non-pilot channels is sent by the BS to UE2. In other embodiments, the BS uses the sparse reference signaling configuration only for one or more UEs that determine or otherwise obtain the sparse reference signaling pattern, and at 321, further configuration of the UE by the BS may or may not be performed.

[0064] Even for UEs for which sparse signaling configuration is determined at 316, UE configuration may be performed. For example, sending CSI-RS signaling may include performing CSI-RS configuration of the UE through Radio Resource Control (RRC) signaling and sending CSI-RS signaling. Such CSI-RS configuration may be used to provide the UE with information such as one or more locations of the CSI-RS within the time-frequency grid and antenna port mapping relationships. Actual transmission of CSI-RS signaling enables the UE to estimate the channel at the transmitted CSI-RS location.

[0065] Channel characteristics may vary depending on UE location, so the particular sparse reference signaling pattern used at 322 may be dependent on the UE location. Figure 3 Not shown, but the BS may determine the location of UE2 based on a UE location indication provided by UE2 to the BS or in other ways and obtain a sparse reference signaling configuration of the current location of UE2. The BS may select from multiple sparse reference signaling configurations based on the current UE location, etc.

[0066] At 324, UE2 performs CSI estimation and prediction, and at 326, UE2 sends CSI feedback to the BS. Figure 3 In the example, the CSI feedback is marked as sparse CSI feedback to indicate that the CSI feedback is based on sparse reference signaling.

[0067] Figure 3 The behavior of the UE during the training phase 310 includes receiving dense CSI-RS signaling at 312, sending CSI feedback at 314, determining a sparse signaling mode at 316, and sending an indication to the BS at 318. During the operation phase 320, UE2 receives configuration information from the BS at 321, receives sparse CSI-RS signaling from the BS at 322, performs estimation and prediction at 324, and sends CSI feedback to the BS at 326. UE2 may also send an indication of the location of UE2 to the BS before 322, and may receive configuration information at 321.

[0068] Figure 3 The BS's behavior in the training phase 310 includes sending CSI-RS signaling (possibly dense CSI-RS signaling) at 312, receiving CSI feedback (possibly dense CSI feedback) at 314, and receiving an indication at 318. Other behaviors of the BS in the operation phase 320 may optionally include sending sparse CSI-RS configuration information at 321, sending sparse CSI-RS signaling at 322, and receiving sparse CSI feedback at 326. In some embodiments, the BS may also receive UE location information or otherwise determine the UE location.

[0069] and Figure 2 , Figure 3 Embodiments consistent with and / or other teachings herein may be implemented in any of a variety of ways. For example, a neural network may be trained using UE data samples such that the neural network learns antenna port correlations and may be used to determine a sparse reference signaling pattern and / or a channel predictor. Such ML applications enable sparse reference signaling patterns and / or channel predictors to be obtained and / or optimized during training and subsequently used for partial channel estimation using sparse reference signaling and partial channel prediction using non-dense reference signaling each time a channel parameter is to be determined.

[0070] Although Figure 3 An implementation using a two-stage process including a training phase 310 and an operation phase 320 is shown, but this is not intended to imply that the training phase must be offline. Offline training is just one possible implementation. The data samples for training may also or alternatively be collected in real-time communication. The CSI-RS signaling at 312 may be part of the normal communication between the BS and UE1, and after sufficient data samples are collected in online training, the BS may transition to sparse CSI-RS signaling for UE1 and / or UE2.

[0071] In some embodiments, the UE position is specified using an ordered set of values ​​(e.g., (x, y) or (x, y, z)) according to a coordinate system. There are some methods to reduce the UE position signaling overhead. For example, the UE position information signaled to the BS can be an incremental value rather than an absolute value. It is expected that the UE position will change continuously rather than intermittently with significant changes between positions, at least when the UE is actively in use. An example of an incremental value for signaling the UE position is a quantized offset indicating the new UE position relative to the previous position. For example, the distance from the previous position can be signaled as an n*D unit distance from the previous position, where n is the number of quantized distance units and D is the quantized direction, such as east, west, south, north. For example, if the UE moves northwest from its previous position, multiple increments can be signaled. Sending one or more quantized incremental values ​​can reduce the location information overhead compared to sending absolute position information each time the UE moves.

[0072] Similarly, the sparse reference signaling configuration can be specified in any of a variety of ways. For example, the pilot and / or non-pilot antenna port indexes of the signaling pattern can be specified in the signaling configuration. In addition to or instead of the pilot and / or non-pilot antenna port indexes of the signaling pattern, the time-frequency grid positions corresponding to the pilot and / or non-pilot positions in the signaling pattern can be specified in the signaling configuration. An ordered pair represents an example of a data element that can be used to specify a position in a two-dimensional grid. A series of 1s and 0s can be used to indicate pilot positions where pilots are to be sent (e.g., "1") and pilots are not to be sent (e.g., "0"). For example, a pattern for a 32-antenna port implementation with one pilot position per antenna port can be specified in a 32-bit binary sequence.

[0073] In some embodiments, the positions of the basic or dense antenna ports in the time-frequency grid are known, and a subset of these positions is signaled using a bitmap such as a 32-bit binary sequence in the above example. The subset constitutes a sparse pattern. Considering a known basic mode, such as a conventional possible dense mode, the difference between the basic mode and the sparse mode can be signaled by a bitmap sequence or other means, rather than signaling the sparse mode itself. By enabling any single AP to be designated as a pilot or non-pilot, configuration per antenna port can be supported. In some embodiments, these pattern differences can be semi-statically signaled by RRC signaling, or dynamically signaled by a control channel in dynamic downlink control information (DCI).

[0074] These examples involve defining or specifying reference signaling patterns. In some embodiments, the patterns themselves are indexed or otherwise specified so that the details of each pattern can be accessed, determined, or otherwise obtained from a pattern index or other identifier. The pattern index or identifier can be used as a key or lookup in a pattern list or table stored in a memory to determine the exact position in the pattern where reference signaling such as a pilot should be sent. Lookup is just one example of how a pattern index or identifier can be used. Another example is a pattern index or identifier that specifies the value "x" of the x-th pattern in a pattern list or sequence. Yet another example is a pattern index or identifier corresponding to a binary representation of an on-off pilot position, such as a decimal value pattern index corresponding to a binary value specifying an on and off pilot position in a pattern.

[0075] Mode indices or identifiers may be particularly useful in embodiments involving multiple modes. For example, variable or changing reference signaling may involve jumping or switching between multiple modes. The signaling configuration may specify a series of mode indices or identifiers to define a jumping or switching sequence for the variable or changing signaling mode. In addition to or in lieu of the signaling configuration, the jumping or switching may be specified in other ways, for example, based on a starting position or offset in a series of modes and a step size, the step size indicating the sequence position of the next mode to be used at the next jump or switching time or event (next resource block and / or next time slot, etc.) relative to the current position.

[0076] The signaling configuration or mode may be associated with the corresponding CSI measurement result or estimation value via a mode index, etc. and / or associated with the antenna port via an antenna port index, etc. These associations may be implicit or explicit and may help identify or otherwise obtain an appropriate predictor for partial channel prediction.

[0077] Other configuration options may also be apparent or become apparent. Regardless of which particular configuration is used, the configuration information may be stored in a memory, included in control signaling such as RRC signaling, or both. The configuration information may be sent from the UE to the BS in signaling, such as at 318, and / or from the BS to the UE, such as at 321.

[0078] The present disclosure is not limited to any particular form of UE location information or configuration information.

[0079] The number of data samples collected for determining the sparse reference signaling pattern may be statically or dynamically configured at the UE side. Another option for ML implementation includes: monitoring the ML module for convergence; and transitioning from the training phase to the operational phase, or from a relatively denser reference signaling to the sparse reference signaling, when a target convergence level is reached. Any of various types of cost functions and / or other convergence testing techniques may be applied to determine convergence.

[0080] Regardless of the specific metric or technique used to assess convergence and declare online or offline training complete, after training is complete, the BS uses one or more sparse reference signaling patterns to reduce reference signaling overhead compared to more dense reference signaling.

[0081] Since changes in the communication environment may affect LOS and / or NLOS (reflection or diffraction) paths or links, etc., the training is repeated in some embodiments. In these embodiments, the training can be considered semi-static. The retraining can be online or offline.

[0082] Figure 2 and Figure 3 This generally introduces sparse reference signaling and configuration. Detailed examples are provided below.

[0083] For illustration purposes only, consider an example of learning antenna port correlations using ML in the context of two dimensions, space (transmit antenna port index) and frequency (subcarrier index), and an FDD application with CSI-RS signaling and CSI feedback signaling. Other implementations may be applied to different dimensions and / or more dimensions. For example, spatial correlation may be exploited along with correlations in time and frequency. In some implementations, channels may be considered in the context of a four-dimensional grid of transmit antenna port index, receive antenna port index, subcarrier index, and OFDM symbol index.

[0084] In training, the BS sends CSI-RS signaling (possibly dense CSI-RS signaling) to the UE, so that the UE can estimate the channel at the CSI-RS location (antenna port index, subcarrier index in this example) and feedback the CSI to the BS. This process can be continued for different channel implementations, such as through UE movement, until the UE collects enough UE channel estimates. The non-dense (sparse) reference signaling mode can be defined in the RRC configuration or other configuration signaling, etc., and it includes a set of points (A p ) and the point set without pilot or other reference signals (A np ). For ease of reference, this example refers to a pilot. However, in addition to or in place of the reference signaling described above, the techniques disclosed with reference to the pilot may be applied to other types of reference signaling.

[0085] In one ML implementation, with A p The corresponding channel coefficients are used as input and are compared with A np The corresponding channel coefficients are labels or outputs of the ML module. In some embodiments, the UE estimates multiple (sparse) CSI-RS patterns and selects one or more best patterns for subsequent CSI-RS transmission. In addition to or instead of these patterns, the UE may indicate several suitable patterns or configurations to the network device, and the selection of the pattern or configuration is made by the network device.

[0086] Figure 4 A two-dimensional diagram including a dense pilot signal pattern and two exemplary sparse patterns #1 and #2. Figure 4 In the figure, the grid points with pilots are marked as "p" and the grid points without pilots are marked as "x". Figure 4 The sparse patterns #1 and #2 in are just examples; other sparse patterns are possible and more examples are provided elsewhere in this article.

[0087] In the example shown, the dense mode includes 2 pilots per antenna port, while the sparse modes #1 and #2 include only one pilot per antenna port. Although all antenna ports have one pilot in the sparse modes #1 and #2, these modes are still sparse modes because they do not include all the pilots in the dense mode. In other words, the sparse modes #1 and #2 are semi-dense relative to the dense mode because there is only one pilot per antenna port instead of two pilots in the dense mode. Since there is one pilot in each sparse mode for every two pilots in the dense mode, the pilot density in this example is 1 / 2. More generally, the density of sparse reference signaling is less than 1 relative to dense reference signaling.

[0088] In one embodiment, the UE trains one ML module for each of a plurality of sparse CSI-RS configurations. Figure 5 Two embodiments are shown. Figure 4 An example of training an ML module based on the sparse patterns #1 and #2 in . p The corresponding channel coefficient (H Ap ) is used as input, and A np The corresponding channel coefficient (H Anp ) is used as the output of each ML module. Figure 5 , example (1) is shown for sparse pattern #1, and example (2) is shown for sparse pattern #2.

[0089] The selection of a sparse reference signaling pattern may be based on any of a variety of factors. In one embodiment, a sparse pattern that provides better performance than other sparse patterns based on a metric such as mean square error (MSE) observed for test data using each of a plurality of candidate patterns is selected to reduce reference signaling overhead.

[0090] After the UE selects or otherwise obtains a sparse reference signaling pattern, the UE sends an indication of the sparse signaling pattern to the BS, and the BS then sends CSI-RS signaling consistent with the pattern to the UE. As described elsewhere herein, this includes configuring the UE for sparse signaling in some embodiments. The UE estimates the A with CSI-RS from the received signal. p The channel corresponding to the grid point is predicted to be np The channel corresponding to the grid point and feeds back the CSI to the BS.

[0091] Figure 6 is a block diagram showing an example of a varying sparse reference signaling pattern including a plurality of sparse patterns 610 and 620 in a time-frequency grid. Figure 6 The examples shown and Figures 7 to 9 The other examples in apply to a 32-port CSI-RS pattern and an RB consisting of 14 OFDM symbols. OFDM may be helpful in providing an additional pilot dimension. Without OFDM, there is only the "antenna" dimension, and pilots can be sent on a subset of antennas to estimate the channel for those antennas, and then predict the channel on the antennas without pilots. Since there is a larger channel estimation error for antennas without pilots, this leads to an imbalance in the channel estimation errors on different antennas. However, according to an aspect of the present disclosure, in some embodiments, the additional dimension provided by OFDM supports one or more pilots for all antenna ports while reducing the pilot density.

[0092] and Figure 1 Compared to the dense mode shown, Figure 6The example in corresponds to a half-density configuration, in which the pilots are sent on all antenna ports. This half-density configuration is provided by introducing a hopping pattern across multiple resource blocks (RBs) in the same time slot. According to the dense signaling configuration, Figure 1 The pattern in is sent every few RBs. Figure 6 In , only half of the pilots from dense mode are sent.

[0093] exist Figure 7 In the block diagram shown, an exemplary varying sparse reference signaling pattern includes multiple sparse patterns 710 and 720 across multiple time slots. Figure 7 The examples in Figure 6 As in the example in , since the jump pattern spans multiple time slots, it complies with Figure 1 Dense signaling configuration involves sending a signal at regular intervals (e.g., every few time slots). Figure 1 In the mode, and Figure 7 In , only half of the pilots from dense mode are sent.

[0094] Steering Figure 8 , a hopping mode is introduced to jump or switch between multiple sparse modes 810, 820, 830 and 840 across RBs and time slots. Figure 1 Dense signaling configuration, Figure 8 The example shown has a density of 3 / 4.

[0095] Figures 6 to 8 The examples in provide an overall pilot density of 1 / 2 or 3 / 4, and each antenna port has the same pilot density. Fig. 9 The block diagram in shows an example of a varying sparse reference signaling pattern including multiple sparse patterns 910 and 920 and providing different reference signaling densities between some antenna ports. In the example shown, APs 0 to 15 have full density and APs 16 to 31 have 1 / 2 density. Fig. 9 The overall density of the sparse reference signaling pattern relative to Figure 1 The dense mode and dense signaling configuration shown is 3 / 4.

[0096] Although Fig. 9 shows the hopping pattern across RBs in one time slot, but Figures 6 to 8 Other hopping patterns such as the examples shown may also be applied to different pilot density implementations.

[0097] Other implementations are also possible. In general, the sparse reference signaling pattern can provide the same or different reference signaling densities for different antenna ports. Switching between the involved modes (e.g., Figures 6 to 9In an embodiment of the jump mentioned in the description of ), the mode switching can span any one or more of the following items or between any one or more of the following items: RBs, time slots and / or one or more other signaling characteristics or dimensions.

[0098] It should also be understood that the basic 32-port CSI-RS discussed herein is only an example. Implementations of the present disclosure can be applied to any other CSI-RS pattern, or to other reference signal patterns in general. Furthermore, implementations of providing different signaling densities for different APs are not in any way limited to Fig. 9 Specific examples in . Fig. 9 The sparse signaling pattern shown is an example of a scenario where APs 0 to 15 have a density of 1 and APs 16 to 31 have a density of 0.5. Other patterns where the density is not the same are also possible.

[0099] In FDD applications, the embodiments disclosed herein may help reduce CSI-RS overhead, or in other words, improve channel estimation or prediction performance under the same pilot overhead.Introducing sparse RS configuration may additionally or alternatively help mitigate pilot contamination in FDD massive MIMO and the like.

[0100] TDD applications for reducing DM-RS overhead and / or PT-RS overhead in TDD massive MIMO and the like are also considered. Fig.10 To further elaborate on this point, we give an example. Fig.10 1 is a block diagram 1000 showing a UE 1006 and a BS 1002 including a plurality of antenna elements 1004. For example, each antenna element 1004 can be associated with an antenna port; or, more than one antenna element can be associated with an antenna port. Figure 2 As mentioned, more detailed examples of BS and UE are provided elsewhere herein. Operations that can be performed to reduce DM-RS overhead in TDD massive MIMO and the like in some embodiments are shown at 1010, 1012, 1014, 1016, 1018, and 1020.

[0101] In a training phase that may be either online or offline, the UE 1006 determines suitable sparse reference signaling, in which case sparse DM-RS signaling may be used to reduce overhead without significantly affecting performance in determining channel coefficients or parameters. At 1010, the BS 1002 sends DM-RS signaling (possibly full-density DM-RS signaling) to the UE 1006. The UE 1006 performs channel estimation based on the received DM-RS signaling at 1012. In some implementations, due to UE mobility, etc., 1010 and 1012 are repeated for different channel implementations until the UE 1006 collects sufficient UE channel estimation values ​​in the form of channel measurement results / estimates on the DM-RS antenna port side.

[0102] Fig.10 1014 in the figure indicates that the UE 1006 determines the channel correlation across the DM-RS antenna port / time / frequency based on the channel estimation values ​​collected at 1012. In some embodiments, ML is used to implement 1014. In addition to or in lieu of these embodiments, the ML examples and other examples provided herein, including those disclosed in the context of CSI-RS embodiments, can be used to determine antenna port correlation in DM-RS overhead reduction embodiments, and are generally applied to embodiments for reducing overhead associated with other types of reference signaling (e.g., PT-RS signaling).

[0103] Based on the antenna port correlation in the illustrated embodiment, UE 1006 optimizes the sparse reference signaling pattern and corresponding predictor to be used for UE 1006 and / or other possible UEs in addition to or instead of UE 1006. The sparse reference signaling pattern determined or otherwise obtained by the UE based on the collected channel measurement results does not need to be subsequently used only for the UE, as described elsewhere herein.

[0104] At 1016, the UE 1006 sends an indication of one or more sparse reference signaling patterns to the BS 1002. One or more of an overall reference signaling density, a reference signaling density per antenna port or antenna port subset, a DM-RS configuration index or identifier, etc. may be sent from the UE to the BS 1002 at 1016 to inform the BS that a sparse reference signaling configuration has been determined and will be applied. Examples of how a sparse signaling configuration may be determined are provided elsewhere herein and may be implemented in a DM-RS / PT-RS application.

[0105] The BS 1002 then sends sparse reference signaling consistent with the above configuration to the same UE 1006 and / or another possible UE at 1018, and the UE performs channel estimation and prediction at 1020. This is similar to 1010 and 1012 described above, but involves sparse DM-RS signaling that includes only a subset of DM-RSs from the DM-RS signaling at 1010. For the channel estimation and prediction at 1020, the UE 1006 estimates the channel at the pilot positions in the sparse reference signaling, predicts the channel at the non-pilot positions, and uses the channel estimation and channel prediction together to decode the downlink data.

[0106] In some embodiments, the BS 1002 configures the UE 1006 for low-density reference signaling prior to 1018. This may be useful in at least a scenario where a sparse reference signaling pattern determined or otherwise obtained by one UE is to be used by a base station for a different UE. The different UEs may then receive from the base station any information that the UE needs to perform channel estimation based on the sparse reference signaling. UE configuration may be performed even for UEs that determine a sparse reference signaling pattern to be used by the BS 1002.

[0107] Fig.11 FIG. 11 is a signal flow diagram showing BS-UE signaling according to another embodiment. In the signal flow diagram 1100 , the BS and the UE (labeled as UE1) participate in a training phase 1110 , which can be either online or offline. Fig.11 By way of example, only one UE is shown participating in the training phase 1110, but in other embodiments, multiple UEs may be in the training phase with the BS and / or other BSs.

[0108] 1112 shows the DM-RS signaling interaction between the BS and UE1. This is similar to the above Fig.10 DM-RS transmission at 1010. BS sends DM-RS signaling at 1112 (possibly dense DM-RS signaling), and UE1 performs channel estimation at 1114. Fig.11 1112 and 1114 in FIG. 1 only show one DM-RS transmission and channel estimation, but there may be multiple DM-RS transmissions and channel estimations as UE1 moves between multiple locations during a training phase or the like.

[0109] Based on the channel estimation values ​​collected at 1114, a sparse reference signaling pattern is determined at 1116, in this case, the sparse reference signaling pattern is for sparse DM-RS signaling that can be used to reduce DM-RS signaling overhead. UE1 can test or evaluate multiple sparse signaling patterns using the same training data set from the channel estimation at 1114.

[0110] In some implementations, UE1 tracks and records its location during training, and associates the location information with the channel estimate at 1114 and / or one or more sparse signaling patterns at 1116 .

[0111] In some embodiments, UE1 sends an indication to the BS at 1118 to signal the end of training and / or provide the BS with an indication of a sparse reference signaling pattern to be used for UE1 and / or possibly one or more other UEs. UE location information and / or other information may also be signaled to the BS at 1118.

[0112] In operation phase 1120, the sparse reference signaling pattern determined at 1116 is used in DM-RS signaling with UE2. In this example, the training is not UE-specific. The training with UE1 in the training phase is applied to one or more other UEs, in this case UE2, and at 1121, UE2 is configured according to the sparse DM-RS configuration. For example, information that UE2 needs to perform channel prediction on a non-pilot channel is sent by the BS to UE2. In other embodiments, the BS uses the sparse reference signaling configuration only for one or more UEs that determine or otherwise obtain the sparse reference signaling pattern, and at 1121, further configuration of the UE may or may not be performed.

[0113] The channel characteristics may vary based on the UE location, as described elsewhere herein. The sparse reference signaling configuration used at 1122 may be related to the UE location. The BS may determine the location of UE2 based on a UE location indication provided by UE2 to the BS or otherwise, and obtain the sparse reference signaling configuration for the current location of UE2. The BS may select from a plurality of sparse reference signaling configurations based on, for example, the current UE location.

[0114] At 1124 , UE2 performs channel estimation and prediction according to the sparse DM-RS signaling received at 1122 , and uses the estimated and predicted channel information when demodulating data.

[0115] Fig.11 The behavior of the UE in the training phase 1110 includes receiving dense DM-RS signaling at 1112, performing channel estimation at 1114, determining a sparse signaling pattern at 1116, and sending an indication to the BS at 1118. In the operation phase 1120, UE2 receives sparse DM-RS signaling from the BS at 1122 and performs estimation and prediction at 1124. UE2 may also send an indication of the location of UE2 to the BS before 1122, and may receive configuration information at 1121.

[0116] Fig.11The behavior of the BS in the training phase 1110 includes: sending dense DM-RS signaling at 1112 and receiving an indication at 1118. Other behaviors of the BS in the operation phase 1120 optionally include: sending sparse DM-RS configuration information at 1121 and sending sparse DM-RS signaling at 1122. In some embodiments, the BS may also receive UE location information or determine the UE location in other ways.

[0117] In addition to or in lieu of the above-described embodiments, implementation options disclosed elsewhere herein with reference to CSI-RS embodiments, etc., may be applied to DM-RS embodiments and / or other embodiments such as PT-RS embodiments. Variations disclosed elsewhere herein may similarly be applied to DM-RS embodiments and / or other embodiments such as PT-RS embodiments.

[0118] Fig.12 12 is a flowchart of an example of a method according to an embodiment. Flowchart 1200 includes both network-side operations 1202, 1204, 1206, 1208, 1210, and 1212 and UE-side operations 1220, 1222, 1224, 1226, 1228, and 1230.

[0119] Although Fig.12 Other operations are shown, but in some embodiments, the core of a method performed by a network device in a wireless communication network includes receiving an indication from a UE that the network device is to transition to sparse reference signaling for the UE at 1204. The indication may be or may include an indication of one or more parameters of the sparse signaling pattern, an indication of the location of the UE, or an indication of other information from which a pattern is determined or otherwise obtained.

[0120] The sparse reference signaling conforms to a sparse signaling pattern, which is determined based on previous reference signaling sent to the UE or another UE before 1202 or the like. At 1208, sparse reference signaling is sent to the UE. The network device may also receive signaling from the UE at 1202 and 1208, so these operations are performed in Fig.12 1202 and / or 1208, and receive signaling in the form of CSI feedback from the UE. Similarly, one or more UEs may not only receive reference signaling from the BS at 1220 and 1224, but may also send signaling such as CSI feedback to the BS at 1220 and 1224.

[0121] The sparse signaling pattern is determined based on previous reference signaling previously sent to the UE or another UE. Although the reference signaling based on which the sparse signaling pattern is determined is sent by the network device to the UE at 1202, in some implementations, the sparse signaling pattern may be determined by a different UE.

[0122] Fig.12 The determination of the sparse signaling pattern shown in 1222 is Figure 3 and Fig.11 The training may be performed offline or online. For offline training, the previous reference signaling sent to the UE at 1202 is used for offline operation, which is separate from the reference signaling used for communication with the UE at 1208. For online training, the reference signaling at 1202 is used for online operation associated with communication with the UE. Therefore, the signaling exchanged at 1202 and 1220 can be used by the network device and / or UE to perform channel estimation in normal communication, but Fig.12 This is not shown.

[0123] In some implementations, the sparse reference signaling exchanged at 1208 and 1226 includes CSI-RS signaling, DM-RS signaling, or PT-RS signaling.

[0124] Some embodiments further involve sending configuration information to the UE to configure the UE for the sparse reference signaling at 1206. At 1224, the UE receives the configuration information.

[0125] Although the embodiments herein mainly focus on UE channel measurement and prediction, the network device may also perform channel estimation at 1210 and may also perform channel prediction.

[0126] In some embodiments, retraining may be supported, as shown in 1212. The network device may initiate retraining, or at 1230, the UE may request retraining. The UE may request retraining based on any one or more of the following: a threshold amount of time since the previous training or retraining, the UE moving more than a threshold distance, a false detection rate greater than a threshold, and / or any of various other factors. Based on these items and / or other factors, retraining may be initiated on the network side. In the case of network-initiated retraining, the UE does not need to request retraining. Embodiments in which both network-initiated retraining and UE-initiated retraining are also possible.

[0127] The network device receives at 1212 a signaling requesting retraining at 1230. The retraining request provides the network device with an indication that the network device is to transition from the sparse reference signaling to dense reference signaling for the UE. The transition is not necessarily to full density signaling, but at least to a signaling density greater than the current sparse signaling density. The network device performs the transition and then sends the dense reference signaling to the UE.

[0128] According to another aspect of the present invention, a method performed by a UE in a wireless communication network includes: receiving sparse reference signaling from a network device in the wireless communication network, for example at 1226, wherein the sparse reference signaling is determined based on a previous reference signaling previously received by the UE or another UE; and performing channel measurement and prediction based on the received sparse reference signaling at 1230.

[0129] In some embodiments, the training phase includes: receiving the previous reference signaling, for example at 1220; determining the sparse reference signaling based on the previous reference signaling, for example at 1222; and sending an indication to the network device that the network device is to transition to the sparse reference signaling for the UE.

[0130] The training may be online, wherein the UE receiving the previous reference signaling includes receiving the previous reference signaling to perform an offline operation, and the offline operation is separate from the communication with the network device; the training may also be offline, wherein the UE receiving the previous reference signaling includes receiving the previous reference signaling to perform an online operation, and the online operation is associated with the communication with the network device.

[0131] Features disclosed elsewhere herein may be implemented in conjunction with UE implementations. For example, implementations may include any one or more of the following features in any of various combinations:

[0132] The sparse reference signaling is or includes CSI-RS signaling, DM-RS signaling or PT-RS signaling;

[0133] The indication is or comprises an indication of one or more parameters of the sparse signalling pattern;

[0134] The indication is or includes an indication of a location of the UE;

[0135] receiving configuration information from the network device to configure the UE for the sparse reference signaling;

[0136] In response to a condition at the UE side, sending an indication to the network device that the network device is to transition from the sparse reference signaling to dense reference signaling for the UE, examples of retraining conditions are provided elsewhere herein;

[0137] receiving the dense reference signaling from the network device;

[0138] An indication is sent to the network device that the network device is to transition to new sparse reference signaling, the new sparse reference signaling being determined based on the received dense reference signaling.

[0139] Fig.12 The description thereof is intended only to provide more illustrative examples of method implementations. Other implementations may include more, fewer, and / or different operations performed in similar or different orders. There may also be various ways to perform the operations in the method, including those disclosed elsewhere herein.

[0140] Various implementations are disclosed by way of examples above. Fig.13 An exemplary communication system 1300 in which embodiments of the present disclosure may be implemented is shown. In general, the communication system 1300 enables multiple wireless or wired elements to transmit data and other content. The purpose of the communication system 1300 may be to provide content (voice, data, video, text) via broadcast, narrowcast, user device to user device, etc. The communication system 1300 may operate by sharing resources such as bandwidth.

[0141] In this example, the communication system 1300 includes electronic devices (ED) 1310a to 1310c, radio access networks (RAN) 1320a and 1320b, a core network 1330, a public switched telephone network (PSTN) 1340, the Internet 1350, and other networks 1360. Fig.13 A certain number of these components or elements are shown, but any reasonable number of these components or elements may be included in the communication system 1300.

[0142] EDs 1310a to 1310c are used to operate and / or communicate in the communication system 1300. For example, EDs 1310a to 1310c are used to transmit, receive, or both through wireless or wired communication channels. Each ED 1310a to 1310c represents any suitable end-user device for wireless operation, and may include (or may be referred to as): user equipment (UE / user device), wireless transmit / receive unit (WTRU), mobile station, fixed or mobile user unit, cellular phone, station (STA), machine type communication (MTC) device, personal digital assistant (PDA), smart phone, laptop, computer, tablet, wireless sensor, or consumer electronic device.

[0143] exist Fig.13 In the embodiment, RAN 1320a and 1320b include base stations 1370a to 1370b, respectively. Each base station 1370a and 1370b is used to wirelessly connect to one or more of ED 1310a to 1310c, so as to access any other base stations 1370a and 1370b, core network 1330, PSTN 1340, Internet 1350 and / or other networks 1360. For example, base stations 1370a to 1370b may include (or may be) one or more of several well-known devices, such as base transceiver station (BTS), Node-B (NodeB), evolved NodeB (eNodeB), Home eNodeB, gNodeB, transmission point (TP), site controller, access point (AP) or wireless router. Any ED 1310a to 1310c may alternatively or additionally be used to connect, access or communicate with any other base station 1370a to 1370b, the Internet 1350, the core network 1330, the PSTN 1340, other networks 1360, or any combination thereof. The communication system 1300 may include a RAN, wherein the corresponding base station accesses the core network 1330 via the Internet 1350. In some embodiments, the EDs 1310a to 1310c include EDs that can communicate directly with each other via a link 1380.

[0144] EDs 1310a to 1310c and base stations 1370a and 1370b are examples of communication devices that may be used to implement some or all of the functions and / or implementations described herein. Fig.13 In the illustrated embodiment, base station 1370a constitutes part of RAN 1320a, which may include other base stations, one or more base station controllers (BSC), one or more radio network controllers (RNC), relay nodes, elements and / or devices. Any base station 1370a and 1370b may be a single element, as shown, or multiple elements distributed in the corresponding RAN, and so on. Similarly, base station 1370b constitutes part of RAN 1320b, which may include other base stations, elements and / or devices. Each base station 1370a and 1370b sends and / or receives wireless signals within a certain geographic area (region / area) (sometimes referred to as a "cell" or "coverage area"). The cell can be further divided into cell sectors, and base stations 1370a to 1370b can, for example, use multiple transceivers to provide services to multiple sectors. In some embodiments, there may be established pico or femto cells where the radio access technology supports these cells. In some embodiments, multiple transceivers may be used for each cell, for example using multiple-input multiple-output (MIMO) technology. The number of RANs 1320a to 1320b shown is only an example. Any number of RANs may be considered when designing the communication system 1300.

[0145] Base stations 1370a to 1370b communicate with one or more of EDs 1310a to 1310c via one or more air interfaces 1390 using wireless communication links such as radio frequency (RF), microwave, infrared (IR), etc. The air interface 1390 may utilize any suitable wireless access technology. For example, the communication system 1300 may implement one or more channel access methods in the air interface 1390, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal frequency division multiple access (OFDMA), or single-carrier FDMA (SC-FDMA).

[0146] The base stations 1370a to 1370b may implement Universal Mobile Telecommunication System (UMTS) Terrestrial Radio Access (UTRA) to establish an air interface 1390 using wideband CDMA (WCDMA). In doing so, the base stations 1370a to 1370b may implement protocols such as HSPA, HSPA+, and HSPA+ may optionally include HSDPA, HSUPA, or both. Alternatively, the base stations 1370a to 1370b may establish an air interface 1390 using LTE, LTE-A, and / or LTE-B with Evolved UTMS Terrestrial Radio Access (E-UTRA). It is contemplated that the communication system 1300 may use multi-channel access functionality, including those described above. Other wireless technologies used to implement the air interface include IEEE802.11, 802.15, 802.16, CDMA2000, CDMA2000 1X, CDMA2000 EV-DO, IS-2000, IS-95, IS-856, GSM, EDGE, and GERAN. Of course, other multiple access schemes and wireless protocols can be used.

[0147] The RANs 1320a to 1320b communicate with the core network 1330 to provide various services, such as voice, data, and other services to the EDs 1310a to 1310c. The RANs 1320a to 1320b and / or the core network 1330 may communicate directly or indirectly with one or more other RANs (not shown), which may or may not be directly served by the core network 1330 and may or may not use the same radio access technology as the RAN 1320a, RAN 1320b, or both. The core network 1330 may also serve as a gateway access between (i) the RANs 1320a and 1320b and / or the EDs 1310a to 1310c or both, and (ii) other networks, such as the PSTN 1340, the Internet 1350, and other networks 1360. In addition, some or all of ED1310a to 1310c may include functionality to communicate with different wireless networks over different wireless links using different wireless technologies and / or protocols. EDs may communicate with a service provider or switch (not shown) and with the Internet 1350 over a wired communication channel, rather than wirelessly (or in addition to wirelessly). PSTN1340 may include a circuit-switched telephone network for providing plain old telephone service (POTS). Internet 1350 may include a computer network and a subnet (intranet) or both, and include protocols such as IP, TCP, and UDP. EDs 1310a to 1310c may be multimode devices capable of operating according to a variety of wireless access technologies, and include multiple transceivers required to support these wireless access technologies.

[0148] Fig.14A and Fig. 14B Exemplary devices that can implement various methods and teachings according to the present disclosure are shown. Specifically, Fig.14A An exemplary ED 1310 is shown, Fig. 14B An exemplary base station 1370 is shown. These components may be used in the communication system 1300 or any other suitable system.

[0149] like Fig.14AAs shown, ED 1310 includes at least one processing unit 1400. Processing unit 1400 implements various processing operations of ED 1310. For example, processing unit 1400 can perform signal encoding, data processing, power control, input / output processing, or any other function that enables ED 1310 to operate in communication system 1300. Processing unit 1400 can also be used to implement some or all of the functions and / or embodiments detailed herein. Each processing unit 1400 includes any suitable processing or computing device for performing one or more operations. For example, each processing unit 1400 can include a microprocessor, a microcontroller, a digital signal processor, a field programmable gate array, or an application-specific integrated circuit.

[0150] ED 1310 also includes at least one transceiver 1402. Transceiver 1402 is used to modulate data or other content for transmission through at least one antenna or network interface controller (NIC) 1404. Transceiver 1402 is also used to demodulate data or other content received through at least one antenna 1404. Each transceiver 1402 includes any suitable structure for generating signals for wireless or wired transmission and / or for processing signals received by wireless or wired means. Each antenna 1404 includes any suitable structure for sending and / or receiving wireless or wired signals. One or more transceivers 1402 can be used in ED 1310. One or more antennas 1404 can be used in ED 1310. Although transceiver 1402 is shown as a single functional unit, transceiver 1402 can also be implemented using at least one transmitter and at least one separate receiver.

[0151] ED 1310 also includes one or more input / output devices 1406 or interfaces (e.g., connected to Fig.13 The input / output devices 1406 allow interaction with users or other devices in the network. Each input / output device 1406 includes any suitable structure including network interface communication for providing information to or receiving information from the user, such as a speaker, microphone, keypad, keyboard, display, or touch screen.

[0152] In addition, ED 1310 includes at least one memory 1408. The memory 1408 stores instructions and data used, generated, or collected by ED 1310. For example, the memory 1408 can store software instructions or modules for implementing some or all of the functions and / or embodiments described herein and executed by one or more processing units 1400. Each memory 1408 includes any suitable one or more volatile and / or non-volatile storage and retrieval devices. Any suitable type of memory can be used, such as random access memory (RAM), read only memory (ROM), hard disk, optical disk, subscriber identity module (SIM) card, memory stick, secure digital (SD) memory card, etc.

[0153] like Fig. 14B As shown, the base station 1370 includes at least one processing unit 1450, at least one transmitter 1452, at least one receiver 1454, one or more antennas 1456, at least one memory 1458 and one or more input / output devices or interfaces 1466. Transceivers not shown may be used instead of transmitters 1452 and receivers 1454. Scheduler 1453 may be coupled to processing unit 1450. Scheduler 1453 may be included in base station 1370 or may be operated separately from base station 1370. Processing unit 1450 implements various processing operations of base station 1370, such as signal encoding, data processing, power control, input / output processing or any other function. Processing unit 1450 may also be used to implement some or all of the functions and / or embodiments described in detail herein. Each processing unit 1450 includes any suitable processing or computing device for performing one or more operations. For example, each processing unit 1450 may include a microprocessor, a microcontroller, a digital signal processor, a field programmable gate array or an application specific integrated circuit.

[0154] Each transmitter 1452 includes any suitable structure for generating signals for wireless or wired transmission with one or more EDs or other devices. Each receiver 1454 includes any suitable structure for processing signals received wirelessly or wired from one or more EDs or other devices. Although at least one transmitter 1452 and at least one receiver 1454 are shown as separate components, they can be combined into a transceiver. Each antenna 1456 includes any suitable structure for sending and / or receiving wireless or wired signals. Although a shared antenna 1456 is shown here as coupled to the transmitter 1452 and the receiver 1454, one or more antennas 1456 can be coupled to one or more transmitters 1452, and one or more separate antennas 1456 can be coupled to one or more receivers 1454. Each memory 1458 includes any suitable one or more volatile and / or non-volatile storage and retrieval devices, such as those described above in combination. Fig.14A The memory 1458 stores instructions and data used, generated, or collected by the base station 1370. For example, the memory 1458 may store software instructions or modules for implementing some or all of the functions and / or embodiments described herein and executed by one or more processing units 1450.

[0155] Each input / output device 1466 allows interaction with users or other devices in the network. Each input / output device 1466 includes any suitable structure for providing information to a user or receiving information from a user / providing information from a user, including network interface communications.

[0156] It should be understood that one or more steps in the embodiments provided herein may be performed according to Fig.15 Executed by the corresponding unit or module. For example, a signal may be sent by a sending unit or a sending module. A signal may be received by a receiving unit or a receiving module. A signal may be processed by a processing unit or a processing module. Other steps may be performed by an ML module. The corresponding unit / module may be implemented using hardware, one or more components or devices of execution software, or a combination thereof. For example, one or more of the above-mentioned units / modules may be an integrated circuit, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC). It should be understood that if the above-mentioned modules are implemented using software for execution by a processor or the like, these modules may be retrieved in whole or in part by the processor in a single or multiple instances as needed, retrieved individually or collectively for processing, and these modules themselves may include instructions for further deployment and instantiation.

[0157] Other details about ED 1310 and base station 1370 are known to those skilled in the art, so these details are omitted here.

[0158] In general, apparatus implementations implementing the methods disclosed herein may take any of a variety of forms. For example, in one embodiment, a network device for a wireless communication network includes multiple antennas, a processor coupled to the multiple antennas, and a processor readable memory coupled to the processor. Base station 1370 is an example of such a network device, including multiple antennas at 1456, a processor in the form of a processing unit 1450, and a processor readable memory 1458 coupled to the processing unit.

[0159] The processor readable memory stores processor executable instructions, which, when executed by the processor, cause the processor to perform the method described herein. In one embodiment, the instructions cause the processor to perform the following method, the method comprising receiving an indication from a UE that the network device is to transition to sparse reference signaling for the UE. The sparse reference signaling conforms to a sparse signaling pattern, and the sparse signaling pattern is determined based on a previous reference signaling previously sent to the UE or another UE. The method also includes sending the sparse reference signaling conforming to the sparse signaling pattern to the UE.

[0160] Features described elsewhere herein can also be applicable to user equipment embodiments. For example, embodiments can include any one or more of the following features in any of various combinations:

[0161] The processor-executable instructions, when executed by the processor, further cause the processor to send the previous reference signaling to the UE or the other UE;

[0162] The processor-executable instructions, when executed by the processor, cause the processor to send the previous reference signaling to perform an offline operation separate from communication with the UE or the other UE;

[0163] The processor-executable instructions, when executed by the processor, cause the processor to send the previous reference signaling to perform an online operation associated with communicating with the UE or the other UE;

[0164] The sparse reference signaling is or includes CSI-RS, DM-RS signaling or PT-RS signaling;

[0165] The processor-executable instructions, when executed by the processor, further cause the processor to send configuration information to the UE to configure the UE for the sparse reference signaling;

[0166] The processor-executable instructions, when executed by the processor, further cause the processor to receive an indication from the UE that the network device is to transition from the sparse reference signaling to dense reference signaling for the UE, and send the dense reference signaling to the UE.

[0167] Other network device implementations are possible.

[0168] For example, the above description focuses on network devices. A wireless communication network may include multiple installations of network devices. In one embodiment, the wireless communication network includes multiple base stations, at least some of which are implemented as or at least include the network devices disclosed herein. For example, each installation of the network device may be provided for training one or more corresponding ML modules for each base station, and for supporting ML-assisted reference signaling reduction for communication between each base station and multiple UEs at locations within the network.

[0169] Method and apparatus embodiments described herein include both training and operation. Considering operations separate from training, in some embodiments, a network device method or operation includes receiving an indication of a current location of the UE in a wireless communication network from a UE, and using the current location of the UE as input to obtain a sparse reference signaling pattern disclosed herein.

[0170] The method implementation and the network device implementation represent illustrative example implementations of the features disclosed herein. Other implementations are also possible. At least some of the features disclosed herein can be applicable to UE. For example, on the UE side, sparse reference signaling is received and used for channel estimation and / or acquisition. In a CSI-RS implementation, channel prediction performed using a channel estimated based on the CSI-RS can be used for the purpose of feeding back codebook-based CSI to a network device. In a DM-RS / PT-RS implementation, channel prediction performed using a channel estimated based on the DM-RS / PT-RS can be used for data demodulation on the UE side.

[0171] For example, according to another embodiment, a UE includes a processor and a processor-readable memory, wherein the processor-readable memory is coupled to the processor and stores processor-executable instructions, and when the processor-executable instructions are executed by the processor, the processor performs the following method, which includes receiving sparse reference signaling from a network device in a wireless communication network, wherein the sparse reference signaling is determined based on a previous reference signaling previously received by the UE or another UE; and performing channel measurement and prediction based on the received sparse reference signaling.

[0172] Features described elsewhere herein can also be applicable to network device embodiments. For example, embodiments can include any one or more of the following features in any of various combinations:

[0173] The processor executable instructions, when executed by the processor, further cause the processor to receive the previous reference signaling and determine the sparse reference signaling based on the previous reference signaling;

[0174] The processor-executable instructions, when executed by the processor, cause the processor to receive previous reference signaling to perform an offline operation separate from channel estimation for communications with the network device;

[0175] The processor-executable instructions, when executed by the processor, cause the processor to receive previous reference signaling to perform an online operation, the online operation being associated with communicating with the network device;

[0176] The sparse reference signaling is or includes CSI-RS, DM-RS or PT-RS;

[0177] The indication is or comprises an indication of one or more parameters of the sparse signalling pattern;

[0178] The indication is or includes an indication of a location of the UE;

[0179] The processor-executable instructions, when executed by the processor, further cause the processor to receive configuration information from the network device to configure the UE for the sparse reference signaling;

[0180] When executed by the processor, the processor executable instructions further cause the processor to: in response to a condition on the UE side, send an indication to the network device that the network device is to transition from the sparse reference signaling to dense reference signaling for the UE; receive the dense reference signaling from the network device; and send an indication to the network device that the network device is to transition to new sparse reference signaling, wherein the new sparse reference signaling is determined based on the received dense reference signaling.

[0181] The features disclosed herein may additionally or alternatively be implemented in the form of processor-executable instructions stored in a processor-readable memory.

[0182] In some embodiments, these processor executable instructions, when executed by a processor in a network device in a wireless communication network, cause the processor to perform the following method, the method comprising: receiving an indication from a UE that the network device is to transition to sparse reference signaling for the UE; sending the sparse reference signaling conforming to a sparse signaling pattern to the UE. The sparse reference signaling conforms to a sparse signaling pattern, the sparse signaling pattern being determined based on a previous reference signaling previously sent to the UE or another UE.

[0183] According to another embodiment, when the processor executable instructions are executed by a processor in a UE for a wireless communication network, the processor performs the following method, which includes: receiving sparse reference signaling from a network device in the wireless communication network, wherein the sparse reference signaling is determined based on a previous reference signaling previously received by the UE or another UE; and performing channel measurement and prediction based on the received sparse reference signaling.

[0184] Other features disclosed elsewhere herein can also be applied to methods implemented in the form of processor-executable instructions stored in a processor-readable memory.

[0185] In general, embodiments disclosed herein support new possible low-density reference signaling configurations for CSI-RS, DM-RS and / or PT-RS, etc. Some embodiments introduce hopping between reference signaling patterns in alternating slots and / or RBs, etc.

[0186] Signaling configuration per antenna port is also possible.

[0187] The embodiments disclosed herein enable network devices and / or UEs to exploit channel spatial correlation as well as correlation in time and frequency. In some embodiments, multi-dimensional channel correlation can achieve balanced RS port design. In some embodiments, the dimension is associated with a four-dimensional grid consisting of a transmit antenna port index, a receive antenna port index, a subcarrier index, and an OFDM symbol index. By introducing sparse CSI-RS, DM-RS, and / or PT-RS signaling patterns, support is provided to minimize or at least reduce reference signaling utilization, such as CSI-RS utilization, DM-RS utilization, and / or PT-RS utilization. In some embodiments, the UE uses channel estimates at CSI-RS / DM-RS / PT-RS positions to predict channels at other desired grid positions. On the UE side, machine learning can be used to predict channels, but other implementations are also possible.

[0188] Some embodiments introduce UE to BS signaling to indicate that training is complete and / or that the UE has selected or otherwise obtained a sparse reference signaling pattern. UE to BS signaling may additionally or alternatively indicate from the UE to the BS that retraining is to be performed. Training and / or retraining may be offline and online.

[0189] In the sparse reference signaling configuration, the UE uses estimation and prediction to generate CSI to feed back the CSI to the BS or demodulate the subsequently received data. In some embodiments, the prediction uses machine learning. For example, if the reference signaling is DM-RS / PT-RS, the UE uses channel prediction to decode the downlink data; if the reference signaling is CSI-RS, the UE uses channel prediction to derive the CSI to be fed back to the network device, such as CQI, RI, PMI.

[0190] Multiple reference signaling configurations may be supported, including balanced or unequal density patterns between antenna ports. For example, a separate ML module may be trained for each of multiple reference signaling configurations, where in some embodiments each configuration corresponds to a pilot pattern or partition. The same training data may be used for training all ML modules.

[0191] Many modifications and variations of the present disclosure are possible in light of the above teachings.It is therefore to be understood that, within the scope of the appended claims, the present disclosure may be practiced otherwise than as specifically described herein.

[0192] What is described is merely illustrative of the application of the principles of embodiments of the present disclosure. Other devices and methods may be implemented by those skilled in the art.

[0193] For example, although a combination of features is shown in the illustrated embodiments, not all features need to be combined to achieve the advantages of the various embodiments of the present disclosure. In other words, a system or method designed according to an embodiment of the present disclosure does not necessarily include all features shown in any of the drawings or all parts schematically shown in the drawings. In addition, selected features of one exemplary embodiment may be combined with selected features of other exemplary embodiments.

[0194] Although the present disclosure refers to illustrative embodiments, the present disclosure is not intended to be interpreted in a limiting sense. Various modifications and combinations of the illustrative embodiments and other embodiments of the present disclosure will be apparent to those skilled in the art with reference to this specification. Therefore, the appended claims are intended to cover any such modifications or embodiments.

[0195] Although the present invention has been described with reference to the specific features and embodiments of the present invention, various modifications and combinations may be made without departing from the scope of the present invention. The specification and the drawings are therefore only regarded as an explanation of some embodiments of the present invention as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations or equivalents within the scope of the present invention. Although the present invention and its advantages have been described in detail, various changes, substitutions and modifications may be made without departing from the present invention as defined by the appended claims. In addition, the scope of the present application is not intended to be limited to the specific embodiments of the processes, machines, manufactured products, material components, modes, methods and steps described in the specification. It will be readily understood by those of ordinary skill in the art from the disclosure of the present invention that processes, machines, manufactured products, material components, modes, methods or steps (including currently existing or later developed) that perform or achieve functions or results substantially the same as those of the corresponding embodiments described herein may be used according to the present invention. Accordingly, the appended claims are intended to include these processes, machines, manufactured products, material components, modes, methods or steps within their scope.

[0196] Additionally, although primarily described in the context of methods and apparatus, other implementations are also contemplated, for example, as processor-executable or computer-executable instructions stored in a non-transitory processor-readable medium or a computer-readable medium. These media may store programming or instructions to perform any of the various methods consistent with the present disclosure.

[0197] In addition, any module, component, or device for executing instructions as exemplified herein may include or otherwise access one or more non-transitory computer / processor readable storage media to store information, such as computer / processor readable instructions, data structures, program modules, and / or other data. A non-exhaustive list of examples of non-transitory computer / processor readable storage media includes cassettes, magnetic tapes, disk storage or other magnetic storage devices, such as compact disc read-only memory (CD-ROM), digital video discs or digital versatile discs (DVD), Blu-ray Disc TM(Blu-ray Disc) and other optical disks, or other optical storage, volatile and non-volatile, removable and non-removable media implemented in any method or technology, random-access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other storage technology. Any of these non-transitory computer / processor readable storage media can be part of a device or can be accessed or connected to a device. Any application or module described herein can be implemented using computer / processor readable / executable instructions, which can be stored or otherwise maintained by these non-transitory computer / processor readable storage media.

Claims

1. A method performed by a network device in a wireless communication network, characterized in that: The method comprises: receiving, from a user equipment (UE), an indication that the network device is to transition to sparse reference signaling for the UE, the sparse reference signaling conforming to a sparse signaling pattern determined by the UE based on previous reference signaling previously sent to the UE or another UE; Sending configuration information to the UE to configure the UE for the sparse reference signaling; sending the sparse reference signaling conforming to the sparse signaling pattern to the UE, The method further comprises: sending the previous reference signaling to the UE or the other UE; The sending of the previous reference signaling includes: sending the previous reference signaling to the UE to perform offline training at the UE to determine the sparse signaling pattern, and the previous reference signaling is separated from the reference signaling used for communicating with the UE or the other UE.

2. The method according to claim 1, characterized in that The sparse reference signaling includes: channel state information reference signal (CSI-RS) signaling, demodulation reference signal (DM-RS) signaling or phase tracking reference signal (PT-RS) signaling.

3. The method according to claim 1 or 2, characterized in that: The indication comprises an indication of one or more parameters of the sparse signalling pattern.

4. The method according to claim 1 or 2, characterized in that: The indication comprises an indication of a location of the UE.

5. The method according to claim 1 or 2, characterized in that: Also includes: receiving from the UE an indication that the network device is to transition from the sparse reference signaling to dense reference signaling for the UE; The dense reference signaling is sent to the UE.

6. A network device for a wireless communication network, characterized in that: The network equipment includes: Processor; and A processor readable memory is coupled to the processor and stores processor executable instructions which, when executed by the processor, cause the processor to perform the method according to any one of claims 1 to 5.

7. A processor readable memory storing processor executable instructions, characterized in that: When the processor-executable instructions are executed by a processor in a network device in a wireless communication network, the processor is caused to perform the method according to any one of claims 1 to 5.

8. A method performed by a user equipment UE in a wireless communication network, characterized in that: The method comprises: receiving configuration information from a network device in the wireless communication network to configure the UE for sparse reference signaling; receiving the sparse reference signaling from the network device, the sparse reference signaling being determined by the UE based on previous reference signaling previously received by the UE or another UE; Perform channel measurement and prediction based on received sparse reference signaling, Wherein, the method further comprises: receiving the previous reference signaling; performing offline training based on the previous reference signaling to determine the sparse reference signaling, the previous reference signaling being separate from the reference signaling used by the network device to communicate with the UE or the other UE; An indication is sent to the network device that the network device is to transition to the sparse reference signaling for the UE.

9. The method according to claim 8, characterized in that The sparse reference signaling includes: channel state information reference signal (CSI-RS) signaling, demodulation reference signal (DM-RS) signaling or phase tracking reference signal (PT-RS) signaling.

10. The method according to claim 8, characterized in that The indication comprises an indication of one or more parameters of the sparse signalling pattern.

11. The method according to claim 8, characterized in that The indication comprises an indication of a location of the UE.

12. The method according to any one of claims 8 to 11, characterized in that Also includes: In response to a condition at the UE side, sending an indication to the network device that the network device is to transition from the sparse reference signaling to dense reference signaling for the UE; receiving the dense reference signaling from the network device; An indication is sent to the network device that the network device is to transition to new sparse reference signaling, the new sparse reference signaling being determined based on the received dense reference signaling.

13. A user equipment (UE) for a wireless communication network, characterized in that: The UE includes: Processor; and A processor readable memory is coupled to the processor and stores processor executable instructions which, when executed by the processor, cause the processor to perform the method according to any one of claims 8 to 12.

14. A processor readable memory storing processor executable instructions, characterized in that: The processor executable instructions, when executed by a processor in a user equipment (UE) for a wireless communication network, cause the processor to perform the method according to any one of claims 8 to 12.

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