DM-RS-free operation in wireless systems

Abstract

Systems, methods, and instrumentalities for demodulation reference signal-free (DM-RS) operation in a wireless system are described herein. A data channel structure (e.g., a DM-RS-free data channel structure) may be used. According to the DM-RS-free data channel structure, unsupervised DM-RS-free equalization can be realized. The DM-RS-free data channel structure may enable reporting of performance indicators and parameters associated with the DM-RS-free data channel structure.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of Provisional U.S. Patent Application No. 63 / 405,021, filed on September 9, 2022, the disclosure of which is incorporated herein by reference in its entirety. Background Art

[0003] Mobile communications using wireless communications are constantly evolving. The fifth generation may be referred to as 5G. Previous (legacy) generations of mobile communications may be, for example, fourth generation (4G) Long Term Evolution (LTE). Summary of the invention

[0004] Systems, methods, and means for demodulation reference signal (DM-RS)-free operation in wireless systems are described herein. A data channel structure (e.g., a DM-RS-free data channel structure) may be used. The DM-RS-free data channel structure may enable unsupervised DM-RS-free equalization. The DM-RS-free data channel structure may enable reporting of performance indicators and parameters associated with the DM-RS-free data channel structure.

[0005] The WTRU may perform a canonical correlation analysis (CCA) (e.g., associated with a DM-RS-free data channel structure). The WTRU may receive configuration information (e.g., CCA configuration information). The configuration information may indicate CCA view parameters and / or CCA views. The CCA view parameters may include one or more of the following: the location of repeated resource elements, CCA view length, starting symbol, resource block offset, mapping order, CCA reference signal configuration, etc. The WTRU may determine (one or more) CCA views, for example, based on the configuration information. The CCA view may include a set of REs. For example, a first CCA view may have a first set of REs, and a second CCA view may have a second set of REs (e.g., where the second set of REs may be a copy of the first set of REs). The CCA view may be associated with a CCA view length, where the CCA view length may be associated with a repetition pattern density. The WTRU may determine a first CCA view and a second CCA view (e.g., based on the configuration information). The WTRU may measure a CCA correlation coefficient associated with the first CCA view and the second CCA view. The WTRU may determine CCA subgrid information (e.g., subgrid size, number of subgrids, and / or number of CCA reference signals (CCA-RS) (e.g., for each subgrid), for example, based on a first CCA view, a second CCA view, and a CCA correlation coefficient. The determined subgrid size may be the number of resource blocks (RBs). The WTRU may determine whether to send an indication of the determined subgrid size based on whether the determined subgrid size is equal to the configured subband size. The WTRU may send a report (e.g., to a network) based on the determination of whether to send an indication of the subgrid size. The report may indicate the determined number of CCA-RS and the CCA correlation coefficient. The WTRU may, for example, demodulate and equalize a data channel using the received CCA-RS, the first CCA view, and the second CCA view.

[0006] The WTRU may determine that the determined sub-grid size is not equal to the configured sub-band size. Based on determining that the determined sub-grid size is not equal to the configured sub-band size, the report may indicate the determined sub-grid size.

[0007] The WTRU may receive a channel state information reference signal (CSI-RS). The WTRU may perform measurements based on the CSI-RS. The determination of the CCA subgrid information may be performed, for example, based on the measurements performed based on the CSI-RS. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1A is a system diagram illustrating an example communication system in which one or more disclosed embodiments may be implemented;

[0009] Figure 1B is a diagram showing that according to an embodiment, Figure 1A A system diagram of an example wireless transmit / receive unit (WTRU) for use within a communication system is shown in FIG.

[0010] Figure 1C is an example of an embodiment in which Figure 1A A system diagram of an example radio access network (RAN) and an example core network (CN) used within the illustrated communication system;

[0011] Figure 1D is an example of an embodiment in which Figure 1A A system diagram of another example RAN and another example CN used in the communication system shown;

[0012] Figure 2 An example of (e.g., NR) DM-RS symbol configuration type 1 for 4×4 MIMO is illustrated.

[0013] Figure 3 An example of DM-RS based channel estimation and equalization is illustrated.

[0014] Figure 4 An example of a DM-RS data channel structure is illustrated.

[0015] Figure 5 An example of a DMRS-free data channel structure is illustrated.

[0016] Figure 6 An example view in a DM-RS-free data channel structure is illustrated.

[0017] Figure 7 An example of CCA-based data channel processing by a WTRU is illustrated.

[0018] Figure 8 An example configuration / format of a CCA view with an example range of values ​​of Delay Spread to Doppler Ratio (SDR) is illustrated.

[0019] Fig. 9 Examples of CCA view configurations (eg, repetition types) for performance evaluation are illustrated.

[0020] Fig.10 Example CCA subgrids and CCA views for each subgrid are illustrated.

[0021] Fig.11 Example SER results (eg, simulation results) for different CCA view configurations (eg, different repetition types) for frequency selective and / or fast fading channels are illustrated.

[0022] Fig.12 Examples of CCA performance for different view lengths 6≤N≤20 are illustrated.

[0023] Fig.13 Examples of CCA performance for different view lengths 40≤N≤160 are illustrated.

[0024] Fig.14 Example SER results for equal and non-overlapping sub-grids in a CDL-C channel with a delay spread of 30 ns and a WTRU speed of 1 km / hour are illustrated.

[0025] Fig.15 An example graph of SER versus SNR for data sent on a CDL-C channel and a resource grid of 52 RBs with a sub-grid size of 4 RBs is illustrated.

[0026] Fig.16 An example of the relationship between sub-grid and sub-band size is illustrated, where the REs within a sub-band SBn can be encoded with precoder f n Precoding.

[0027] Fig.17 Example graphs of SER versus SNR for different sub-grid sizes in a resource grid of 48 RBs and a sub-band size of 6 RBs are illustrated.

[0028] Fig.18 An example of a DM-RS pattern is illustrated.

[0029] Fig.19 Example illustrating CCA mode. The lines shown in the example separate groups of REs combined with the same combiner.

[0030] Fig. 20 Examples of throughput and SNR based on CCA and DM-RS for an RG of 52 RBs and a sub-grid size of 4 RBs are illustrated.

[0031] Fig.21 An example of throughput and SNR based on CCA and DM-RS for an RG of 52 RBs is illustrated.

[0032] Fig. 22 An example of determining and reporting CCA subgrid parameters is illustrated.

[0033] Fig.23 Examples associated with fallback to DM-RS data transmission are illustrated, where the WTRU may perform one or more of the illustrated actions.

[0034] Fig.24 Examples associated with determination of (eg, preferred) CCA repetition types and parameters are illustrated, where the WTRU may perform one or more of the illustrated actions. DETAILED DESCRIPTION

[0035] Figure 1A 1 is a schematic diagram illustrating an example communication system 100 in which one or more disclosed embodiments may be implemented. The communication system 100 may be a multiple access system that provides content such as voice, data, video, messaging, broadcast, etc. to multiple wireless users. The communication system 100 may enable multiple wireless users to access such content by sharing system resources (including wireless bandwidth). For example, the communication system 100 may use one or more channel access methods, such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), single carrier FDMA (SC-FDMA), zero tail unique word DFT-spread OFDM (ZT UW DTS-s OFDM), unique word OFDM (UW-OFDM), resource block filtered OFDM, and filter bank multi-carrier (FBMC), etc.

[0036] like Figure 1A As shown, the communication system 100 may include wireless transmit / receive units (WTRUs) 102a, 102b, 102c, 102d, RAN 104 / 113, CN 106 / 115, public switched telephone network (PSTN) 108, Internet 110, and other networks 112, but it should be understood that the disclosed embodiments contemplate any number of WTRUs, base stations, networks, and / or network elements. Each of the WTRUs 102a, 102b, 102c, 102d may be any type of device configured to operate and / or communicate in a wireless environment. As examples, the WTRUs 102a, 102b, 102c, 102d (any of which may be referred to as a “station” and / or “STA”) may be configured to transmit and / or receive wireless signals and may include user equipment (UE), a mobile station, a fixed or mobile subscriber unit, a subscription-based unit, a pager, a cellular phone, a personal digital assistant (PDA), a smart phone, a laptop, a netbook, a personal computer, a wireless sensor, a hotspot or Mi-Fi device, an Internet of Things (IoT) device, a watch or other wearable device, a head-mounted display (HMD), a vehicle, a drone, medical devices and applications (e.g., remote surgery), industrial devices and applications (e.g., robots and / or other wireless devices operating in an industrial and / or automated process chain environment), a consumer electronic device, a device operating on a commercial and / or industrial wireless network, etc. Any of the WTRUs 102a, 102b, 102c, and 102d may be interchangeably referred to as a UE.

[0037] The communication system 100 may also include a base station 114a and / or a base station 114b. Each of the base stations 114a, 114b may be any type of device configured to facilitate access to one or more communication networks (e.g., the CN 106 / 115, the Internet 110, and / or other networks 112) by wirelessly interfacing with at least one of the WTRUs 102a, 102b, 102c, 102d. By way of example, the base stations 114a, 114b may be a base transceiver station (BTS), a Node B, an eNode B, a Home Node B, a Home eNode B, a gNB, an NR Node B, a site controller, an access point (AP), a wireless router, and the like. Although the base stations 114a, 114b are each described as a single element, it should be appreciated that the base stations 114a, 114b may include any number of interconnected base stations and / or network elements.

[0038] The base station 114a may be part of the RAN 104 / 113, which may also include other base stations and / or network elements (not shown), such as a base station controller (BSC), a radio network controller (RNC), a relay node, etc. The base station 114a and / or the base station 114b may be configured to transmit and / or receive wireless signals on one or more carrier frequencies, which may be referred to as cells (not shown). These frequencies may be in a licensed spectrum, an unlicensed spectrum, or a combination of a licensed spectrum and an unlicensed spectrum. A cell may provide coverage for wireless services to a specific geographic area, which may be relatively fixed or may change over time. The cell may be further divided into cell sectors. For example, a cell associated with the base station 114a may be divided into three sectors. Therefore, in one embodiment, the base station 114a may include three transceivers, i.e., one transceiver for each sector of the cell. In an embodiment, the base station 114a may use multiple-input multiple-output (MIMO) technology, and may use multiple transceivers for each sector of the cell. For example, beamforming may be used to transmit and / or receive signals in a desired spatial direction.

[0039] The base stations 114a, 114b may communicate with one or more of the WTRUs 102a, 102b, 102c, 102d over an air interface 116, which may be any suitable wireless communication link (e.g., radio frequency (RF), microwave, centimeter wave, micrometer wave, infrared (IR), ultraviolet (UV), visible light, etc.). The air interface 116 may be established using any suitable radio access technology (RAT).

[0040] More specifically, as described above, the communication system 100 may be a multiple access system and may use one or more channel access schemes such as CDMA, TDMA, FDMA, OFDMA, SC-FDMA, etc. For example, the base station 114a in the RAN 104 / 113 and the WTRUs 102a, 102b, 102c may implement a radio technology such as Universal Mobile Telecommunications System (UMTS) Terrestrial Radio Access (UTRA), which may use Wideband CDMA (WCDMA) to establish the air interface 115 / 116 / 117. WCDMA may include communication protocols such as High Speed ​​Packet Access (HSPA) and / or Evolved HSPA (HSPA+). HSPA may include High Speed ​​Downlink (DL) Packet Access (HSDPA) and / or High Speed ​​UL Packet Access (HSUPA).

[0041] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as Evolved UMTS Terrestrial Radio Access (E-UTRA), which may establish the air interface 116 using Long Term Evolution (LTE) and / or LTE-Advanced (LTE-A) and / or LTE-Advanced Pro (LTE-A Pro).

[0042] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement a radio technology such as NR radio access, which may establish the air interface 116 using new radio (NR).

[0043] In an embodiment, the base station 114a and the WTRUs 102a, 102b, 102c may implement multiple radio access technologies. For example, the base station 114a and the WTRUs 102a, 102b, 102c may implement LTE radio access and NR radio access together, for example using the dual connectivity (DC) principle. Thus, the air interface used by the WTRUs 102a, 102b, 102c may be characterized by multiple types of radio access technologies and / or transmissions sent to / from multiple types of base stations (e.g., eNBs and gNBs).

[0044] In other embodiments, the base station 114a and the WTRUs 102a, 102b, 102c may implement radio technologies such as IEEE 802.11 (i.e., Wireless Fidelity (WiFi)), IEEE 802.16 (Worldwide Interoperability for Microwave Access (WiMAX)), CDMA2000, CDMA2000 1X, CDMA2000EV-DO, Interim Standard 2000 (IS-2000), Interim Standard 95 (IS-95), Interim Standard 856 (IS-856), Global System for Mobile Communications (GSM), Enhanced Data rates for GSM Evolution (EDGE), GSM EDGE (GERAN), etc.

[0045] , Figure 1A The base station 114b in the example may be, for example, a wireless router, a Home NodeB, a Home eNodeB, or an access point, and may use any appropriate RAT to facilitate wireless connectivity in a local area, such as a business location, a residence, a vehicle, a campus, an industrial facility, an air corridor (e.g., for use by drones), and a road, etc. In one embodiment, the base station 114b and the WTRUs 102c, 102d may establish a wireless local area network (WLAN) by implementing a radio technology such as IEEE 802.11. In an embodiment, the base station 114b and the WTRUs 102c, 102d may establish a wireless personal area network (WPAN) by implementing a radio technology such as IEEE 802.15. In another embodiment, the base station 114b and the WTRUs 102c, 102d may establish a picocell or a femtocell by using a cellular-based RAT (e.g., WCDMA, CDMA2000, GSM, LTE, LTE-A, LTE-A Pro, NR, etc.). As Figure 1A As shown, the base station 114b may have a direct connection to the Internet 110. Thus, the base station 114b may not be required to access the Internet 110 via the CN 106 / 115.

[0046] The RAN 104 / 113 may be in communication with the CN 106 / 115, which may be any type of network configured to provide voice, data, applications, and / or Voice over Internet Protocol (VoIP) services to one or more of the WTRUs 102a, 102b, 102c, 102d. Data may have varying quality of service (QoS) requirements, such as different throughput requirements, latency requirements, fault tolerance requirements, reliability requirements, data throughput requirements, mobility requirements, etc. The CN 106 / 115 may provide call control, billing services, mobile location-based services, prepaid calls, Internet connectivity, video distribution, etc., and / or perform advanced security functions, such as user authentication. Although in Figure 1AAlthough not shown, it will be appreciated that the RAN 104 / 113 and / or CN 106 / 115 may be in direct or indirect communication with other RANs that employ the same RAT or a different RAT as the RAN 104 / 113. For example, in addition to being connected to the RAN 104 / 113, which may employ NR radio technology, the CN 106 / 115 may also be in communication with another RAN (not shown) employing GSM, UMTS, CDMA 2000, WiMAX, E-UTRA, or WiFi radio technology.

[0047] The CN 106 / 115 may also serve as a gateway for the WTRUs 102a, 102b, 102c, 102d to access the PSTN 108, the Internet 110, and / or other networks 112. The PSTN 108 may include a circuit-switched telephone network that provides plain old telephone service (POTS). The Internet 110 may include a global system of interconnected computer networks and devices that use common communication protocols, such as the Transmission Control Protocol (TCP), the User Datagram Protocol (UDP), and / or the Internet Protocol (IP) in the TCP / IP Internet protocol suite. The networks 112 may include wired and / or wireless communication networks owned and / or operated by other service providers. For example, the networks 112 may include another CN connected to one or more RANs, which may employ the same RAT as the RAN 104 / 113 or a different RAT.

[0048] Some or all of the WTRUs 102a, 102b, 102c, 102d in the communication system 100 may include multi-mode capabilities (e.g., the WTRUs 102a, 102b, 102c, 102d may include multiple transceivers for communicating with different wireless networks via different wireless links). Figure 1A The illustrated WTRU 102c may be configured to communicate with the base station 114a, which may employ a cellular-based radio technology, and with the base station 114b, which may employ an IEEE 802 radio technology.

[0049] Figure 1B is a system diagram illustrating an example WTRU 102. Figure 1B As shown, the WTRU 102 may include, among other things, a processor 118, a transceiver 120, a transmit / receive element 122, a speaker / microphone 124, a keyboard 126, a display / touchpad 128, non-removable memory 130, removable memory 132, a power source 134, a global positioning system (GPS) chipset 136, and / or other peripherals 138. It will be appreciated that the WTRU 102 may include any sub-combination of the foregoing elements while remaining consistent with an embodiment.

[0050] The processor 118 may be a general purpose processor, a special purpose processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors associated with a DSP core, a controller, a microcontroller, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) circuit, any other type of integrated circuit (IC), a state machine, etc. The processor 118 may perform signal coding, data processing, power control, input / output processing, and / or any other functionality that enables the WTRU 102 to operate in a wireless environment. The processor 118 may be coupled to the transceiver 120, which may be coupled to the transmit / receive element 122. Although Figure 1B The processor 118 and the transceiver 120 are depicted as separate components, but it is understood that the processor 118 and the transceiver 120 may be integrated together in an electronic package or chip.

[0051] The send / receive element 122 can be configured to send a signal to a base station (e.g., base station 114a) or receive a signal from a base station (e.g., base station 114a) via an air interface 116. For example, in one embodiment, the send / receive element 122 can be an antenna configured to send and / or receive an RF signal. In one embodiment, the send / receive element 122 can be a transmitter / detector configured to send and / or receive, for example, an IR, UV, or visible light signal. In another embodiment, the send / receive element 122 can be configured to send and / or receive both RF and optical signals. It should be understood that the send / receive element 122 can be configured to send and / or receive any combination of wireless signals.

[0052] Although the transmit / receive element 122 is Figure 1B Although depicted as a single element in the embodiment, the WTRU 102 may include any number of transmit / receive elements 122. More specifically, the WTRU 102 may employ MIMO technology. Thus, in one embodiment, the WTRU 102 may include two or more transmit / receive elements 122 (e.g., multiple antennas) for transmitting and receiving wireless signals over the air interface 116.

[0053] The transceiver 120 may be configured to modulate signals to be transmitted by the transmit / receive element 122 and to demodulate signals received by the transmit / receive element 122. As described above, the WTRU 102 may have multi-mode capabilities. Thus, the transceiver 120 may include multiple transceivers to enable the WTRU 102 to communicate via multiple RATs (e.g., NR and IEEE 802.11).

[0054] The processor 118 of the WTRU 102 may be coupled to the speaker / microphone 124, the keyboard 126, and / or the display / touchpad 128 (e.g., a liquid crystal display (LCD) display unit or an organic light emitting diode (OLED) display unit), and may receive user input data from these components. The processor 118 may also output user data to the speaker / microphone 124, the keyboard 126, and / or the display / touchpad 128. In addition, the processor 118 may access information from and store data in any type of suitable memory, such as the non-removable memory 130 and / or the removable memory 132. The non-removable memory 130 may include a random access memory (RAM), a read-only memory (ROM), a hard disk, or any other type of memory storage device. The removable memory 132 may include a subscriber identity module (SIM) card, a memory stick, a secure digital (SD) memory card, and the like. In other embodiments, the processor 118 may access information from and store data in memories that are not physically located on the WTRU 102, such as on a server or a home computer (not shown).

[0055] The processor 118 may receive power from the power source 134, and may be configured to distribute and / or control power for use by other components in the WTRU 102. The power source 134 may be any suitable device for powering the WTRU 102. For example, the power source 134 may include one or more dry cell batteries (e.g., nickel-cadmium (NiCd), nickel-zinc (NiZn), nickel-metal hydride (NiMH), lithium-ion (Li-ion), etc.), solar cells, fuel cells, etc.

[0056] The processor 118 may also be coupled to the GPS chipset 136, which may be configured to provide location information (e.g., longitude and latitude) regarding the current location of the WTRU 102. In addition to or in lieu of the information from the GPS chipset 136, the WTRU 102 may receive location information from a base station (e.g., base stations 114a, 114b) over the air interface 116 and / or determine its location based on the timing of signals received from two or more nearby base stations. It should be appreciated that the WTRU 102 may acquire location information via any suitable location-determination method while remaining consistent with an embodiment.

[0057] The processor 118 may also be coupled to other peripherals 138, which may include one or more software and / or hardware modules that provide additional features, functionality, and / or wired or wireless connectivity. For example, the peripherals 138 may include an accelerometer, an electronic compass, a satellite transceiver, a digital camera (for photos and / or video), a universal serial bus (USB) port, a vibration device, a television transceiver, a hands-free headset, module, a frequency modulation (FM) radio unit, a digital music player, a media player, a video game console module, an Internet browser, a virtual reality and / or augmented reality (VR / AR) device, an activity tracker, etc. The peripheral device 138 may include one or more sensors, which may be one or more of a gyroscope, an accelerometer, a Hall effect sensor, a magnetometer, an orientation sensor, a proximity sensor, a temperature sensor, a time sensor; a geolocation sensor; an altimeter, a light sensor, a touch sensor, a magnetometer, a barometer, a gesture sensor, a biometric sensor, and / or a humidity sensor.

[0058] The WTRU 102 may include a full-duplex radio for which transmission and reception of some or all signals may be concurrent and / or simultaneous (e.g., associated with specific subframes for both UL (e.g., for transmission) and downlink (e.g., for reception)). The full-duplex radio may include an interference management unit to reduce and / or substantially eliminate self-interference via hardware (e.g., choke) or via signal processing by a processor (e.g., a separate processor (not shown) or via the processor 118). In an embodiment, the WRTU 102 may include a half-duplex radio for which transmission and reception of some or all signals may be concurrent and / or simultaneous (e.g., associated with specific subframes for both UL (e.g., for transmission) or downlink (e.g., for reception)).

[0059] Figure 1C 1 is a system diagram illustrating the RAN 104 and the CN 106 in accordance with an embodiment. As described above, the RAN 104 may employ an E-UTRA radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 104 may also be in communication with the CN 106.

[0060] The RAN 104 may include eNode-Bs 160a, 160b, 160c, though it will be appreciated that the RAN 104 may include any number of eNode-Bs while remaining consistent with an embodiment. The eNode-Bs 160a, 160b, 160c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the eNode-Bs 160a, 160b, 160c may implement MIMO technology. Thus, for example, the eNode-B 160a may use multiple antennas to transmit wireless signals to and / or receive wireless signals from the WTRU 102a.

[0061] Each of the eNodeBs 160a, 160b, 160c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, user scheduling in UL and / or DL, etc. Figure 1C As shown, the eNode-Bs 160a, 160b, 160c may communicate with one another via an X2 interface.

[0062] Figure 1C The illustrated CN 106 may include a mobility management entity (MME) 162, a serving gateway (SGW) 164, and a packet data network (PDN) gateway (or PGW) 166. While each of the foregoing elements is depicted as part of the CN 106, it should be understood that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0063] The MME 162 may be connected to each of the eNode-Bs 162a, 162b, 162c in the RAN 104 via an S1 interface and may serve as a control node. For example, the MME 162 may be responsible for authenticating users of the WTRUs 102a, 102b, 102c, bearer activation / deactivation, selecting a particular serving gateway during an initial attach of the WTRUs 102a, 102b, 102c, and the like. The MME 162 may provide a control plane function for switching between the RAN 104 and other RANs (not shown) that employ other radio technologies, such as GSM and / or WCDMA.

[0064] The SGW 164 may be connected to each of the eNode-Bs 160a, 160b, 160c in the RAN 104 via an S1 interface. The SGW 164 may generally route and forward user data packets to / from the WTRUs 102a, 102b, 102c. The SGW 164 may perform other functions, such as anchoring the user plane during inter-eNode-B handovers, triggering paging when DL data is available for the WTRUs 102a, 102b, 102c, managing and storing the context of the WTRUs 102a, 102b, 102c, and the like.

[0065] The SGW 164 may be connected to the PGW 166, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices.

[0066] The CN 106 may facilitate communications with other networks. For example, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to circuit-switched networks, such as the PSTN 108, to facilitate communications between the WTRUs 102a, 102b, 102c and traditional land-line communications devices. For example, the CN 106 may include or communicate with an IP gateway (e.g., an IP Multimedia Subsystem (IMS) server) that serves as an interface between the CN 106 and the PSTN 108. In addition, the CN 106 may provide the WTRUs 102a, 102b, 102c with access to other networks 112, which may include other wired and / or wireless networks owned and / or operated by other service providers.

[0067] Although the WTRU Figure 1A-Figure 1D Although described as a wireless terminal, it is contemplated that in certain representative embodiments such a terminal may (eg, temporarily or permanently) use a wired communication interface with a communication network.

[0068] In a representative embodiment, other network 112 may be a WLAN.

[0069] A WLAN using an infrastructure basic service set (BSS) mode may have an access point (AP) for a BSS and one or more stations (STAs) associated with the AP. The AP may have access or an interface to a distribution system (DS) or another type of wired / wireless network that sends traffic into and / or out of the BSS. Traffic originating from outside the BSS to a STA may arrive through the AP and may be delivered to the STA. Traffic originating from a STA to a destination outside the BSS may be sent to the AP to be delivered to the corresponding destination. Traffic between STAs within the BSS may be sent through the AP, for example, where a source STA may send traffic to the AP, and the AP may deliver traffic to the destination STA. Traffic between STAs within the BSS may be considered and / or referred to as peer-to-peer traffic. Peer-to-peer traffic may be sent between a source STA and a destination STA (e.g., directly between a source STA and a destination STA) using direct link establishment (DLS). In certain representative embodiments, the DLS may use 802.11e DLS or 802.11z tunnel DLS (TDLS). A WLAN using an independent BSS (IBSS) mode may not have an AP, and STAs (eg, all STAs) within or using the IBSS may communicate directly with each other. The IBSS communication mode may sometimes be referred to herein as an "ad-hoc" communication mode.

[0070] When using the 802.11ac infrastructure mode of operation or a similar mode of operation, the AP may send beacons on a fixed channel (e.g., a primary channel). The primary channel may be a fixed width (e.g., a 20 MHz wide bandwidth) or a width dynamically set via signaling. The primary channel may be an operating channel of the BSS and may be used by the STA to establish a connection with the AP. In certain representative embodiments, carrier sense multiple access with collision avoidance (CSMA / CA) may be implemented, for example, in an 802.11 system. For CSMA / CA, a STA (e.g., each STA) (including the AP) may sense the primary channel. If the primary channel is sensed / detected and / or determined to be busy by a particular STA, the particular STA may back off. One STA (e.g., only one station) may transmit at any given time in a given BSS.

[0071] A high throughput (HT) STA may communicate using a 40 MHz wide channel, for example, by combining a 20 MHz wide primary channel with an adjacent or non-adjacent 20 MHz wide channel to form a 40 MHz wide channel.

[0072] Very high throughput (VHT) STA can support 20MHz, 40MHz, 80MHz and / or 160MHz wide channels. 40MHz and / or 80MHz channels can be formed by combining continuous 20MHz channels. A 160MHz channel can be formed by combining 8 continuous 20MHz channels or by combining two non-continuous 80MHz channels (which can be referred to as an 80+80 configuration). For the 80+80 configuration, the data after channel coding can be passed through a segment parser, which can divide the data into two streams. Inverse Fast Fourier Transform (IFFT) processing and time domain processing can be performed on each stream separately. The stream can be mapped to two 80MHz channels, and the data can be sent by the transmitting STA. At the receiver of the receiving STA, the above operations for the 80+80 configuration can be reversed, and the combined data can be sent to the medium access control (MAC).

[0073] The sub-1 GHz operating mode is supported by 802.11af and 802.11ah. The channel operating bandwidth and carrier in 802.11af and 802.11ah are reduced relative to the channel operating bandwidth and carrier used in 802.11n and 802.11ac. 802.11af supports 5MHz, 10MHz and 20MHz bandwidths in the TV White Space (TVWS) spectrum, and 802.11ah supports 1MHz, 2MHz, 4MHz, 8MHz and 16MHz bandwidths using non-TVWS spectrum. According to a representative embodiment, 802.11ah can support instrument type control / machine type communication, such as MTC devices in macro coverage areas. MTC devices may have certain capabilities, such as limited capabilities including support for (e.g., only support for) certain and / or limited bandwidths. MTC devices may include batteries with battery life above a threshold (e.g., to maintain very long battery life).

[0074] WLAN systems (e.g., 802.11n, 802.11ac, 802.11af, and 802.11ah) that can support multiple channels and channel bandwidths include channels that can be designated as primary channels. The primary channel may have a bandwidth equal to the maximum common operating bandwidth supported by all STAs in the BSS. The bandwidth of the primary channel may be set and / or limited by a STA from all STAs operating in the BSS that support the minimum bandwidth operating mode. In the example of 802.11ah, for STAs (e.g., MTC type devices) that support (e.g., only support) a 1MHz mode, the primary channel may be 1MHz wide, even if the AP and other STAs in the BSS support 2MHz, 4MHz, 8MHz, 16MHz, and / or other channel bandwidth operating modes. Carrier sensing and / or network allocation vector (NAV) settings may depend on the state of the primary channel. If the primary channel is busy, for example, because a STA (which only supports a 1MHz operating mode) sends to the AP, the entire available band may be considered busy even if most of the band remains idle and may be available.

[0075] In the United States, the available frequency band that 802.11ah can use is from 902MHz to 928MHz. In South Korea, the available frequency band is from 917.5MHz to 923.5MHz. In Japan, the available frequency band is from 916.5MHz to 927.5MHz. Depending on the country code, the total bandwidth available for 802.11ah is 6MHz to 26MHz.

[0076] Figure 1D1 is a system diagram illustrating the RAN 113 and the CN 115 according to an embodiment. As described above, the RAN 113 may employ NR radio technology to communicate with the WTRUs 102a, 102b, 102c over the air interface 116. The RAN 113 may also be in communication with the CN 115.

[0077] The RAN 113 may include gNBs 180a, 180b, 180c, though it will be appreciated that the RAN 113 may include any number of gNBs while remaining consistent with an embodiment. The gNBs 180a, 180b, 180c may each include one or more transceivers for communicating with the WTRUs 102a, 102b, 102c over the air interface 116. In one embodiment, the gNBs 180a, 180b, 180c may implement MIMO technology. For example, the gNBs 180a, 180b may utilize beamforming to transmit signals to and / or receive signals from the gNBs 180a, 180b, 180c. Thus, for example, the gNB 180a may use multiple antennas to transmit wireless signals to and / or receive wireless signals from the WTRU 102a. In an embodiment, the gNBs 180a, 180b, 180c may implement carrier aggregation techniques. For example, the gNB 180a may send multiple component carriers (not shown) to the WTRU 102a. A subset of these component carriers may be on an unlicensed spectrum, while the remaining component carriers may be on a licensed spectrum. In an embodiment, the gNBs 180a, 180b, 180c may implement coordinated multi-point (CoMP) techniques. For example, the WTRU 102a may receive coordinated transmissions from the gNB 180a and the gNB 180b (and / or the gNB 180c).

[0078] The WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c using transmissions associated with scalable numerologies. For example, OFDM symbol spacing and / or OFDM subcarrier spacing may vary for different transmissions, different cells, and / or different portions of the wireless transmission spectrum. The WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c using subframes or transmission time intervals (TTIs) of multiple or scalable lengths (e.g., containing different numbers of OFDM symbols and / or lasting different lengths of absolute time) .

[0079] The gNBs 180a, 180b, 180c may be configured to communicate with the WTRUs 102a, 102b, 102c in a standalone configuration and / or a non-standalone configuration. In a standalone configuration, the WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c without accessing other RANs (e.g., such as the eNode-Bs 160a, 160b, 160c). In a standalone configuration, the WTRUs 102a, 102b, 102c may utilize one or more of the gNBs 180a, 180b, 180c as mobility anchors. In a standalone configuration, the WTRUs 102a, 102b, 102c may communicate with the gNBs 180a, 180b, 180c using signals in an unlicensed band. In a non-standalone configuration, the WTRUs 102a, 102b, 102c may communicate / connect with the gNBs 180a, 180b, 180c while also communicating / connecting with another RAN, such as an eNode-B 160a, 160b, 160c. For example, the WTRUs 102a, 102b, 102c may implement the DC principle to communicate with one or more gNBs 180a, 180b, 180c and one or more eNode-Bs 160a, 160b, 160c substantially simultaneously. In a non-standalone configuration, the eNode-Bs 160a, 160b, 160c may serve as mobility anchors for the WTRUs 102a, 102b, 102c, and the gNBs 180a, 180b, 180c may provide additional coverage and / or throughput for serving the WTRUs 102a, 102b, 102c.

[0080] Each of the gNBs 180a, 180b, 180c may be associated with a particular cell (not shown) and may be configured to handle radio resource management decisions, handover decisions, user scheduling in UL and / or DL, support network slicing, dual connectivity, interworking between NR and E-UTRA, routing of user plane data to a user plane function (UPF) 184a, 184b, routing of control plane information to an access and mobility management function (AMF) 182a, 182b, and the like. Figure 1D As shown, gNBs 180a, 180b, and 180c may communicate with each other via an Xn interface.

[0081] Figure 1DThe illustrated CN 115 may include at least one AMF 182a, 182b, at least one UPF 184a, 184b, at least one session management function (SMF) 183a, 183b, and may include a data network (DN) 185a, 185b. Although each of the foregoing elements is depicted as part of the CN 115, it should be understood that any of these elements may be owned and / or operated by an entity other than the CN operator.

[0082] The AMF 182a, 182b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N2 interface and may serve as a control node. For example, the AMF 182a, 182b may be responsible for authenticating users of the WTRU 102a, 102b, 102c, supporting network slicing (e.g., handling different PDU sessions with different requirements), selecting a specific SMF 183a, 183b, managing registration areas, termination of NAS signaling, mobility management, etc. The AMF 182a, 182b may use network slicing to customize CN support for the WTRU 102a, 102b, 102c based on the type of service used by the WTRU 102a, 102b, 102c. For example, different network slices may be established for different use cases (e.g., services relying on ultra-reliable low latency (URLLC) access, services relying on enhanced massive mobile broadband (eMBB) access, services for machine type communication (MTC) access, etc.). The AMF 162 may provide a control plane function for switching between the RAN 113 and other RANs (not shown) that employ other radio technologies, such as LTE, LTE-A, LTE-APro, and / or non-3GPP access technologies such as WiFi.

[0083] The SMF 183a, 183b may be connected to the AMF 182a, 182b in the CN 115 via the N11 interface. The SMF 183a, 183b may also be connected to the UPF 184a, 184b in the CN 115 via the N4 interface. The SMF 183a, 183b may select and control the UPF 184a, 184b, and configure the routing of services through the UPF 184a, 184b. The SMF 183a, 183b may perform other functions, such as managing and allocating UE IP addresses, managing PDU sessions, controlling policy enforcement and QoS, providing downlink data notification, etc. The PDU session type may be IP-based, non-IP-based, Ethernet-based, etc.

[0084] The UPF 184a, 184b may be connected to one or more of the gNBs 180a, 180b, 180c in the RAN 113 via an N3 interface, which may provide the WTRUs 102a, 102b, 102c with access to packet-switched networks, such as the Internet 110, to facilitate communications between the WTRUs 102a, 102b, 102c and IP-enabled devices. The UPF 184, 184b may perform other functions, such as routing and forwarding packets, enforcing user plane policies, supporting multi-homed PDU sessions, handling user plane QoS, buffering downlink packets, providing mobility anchoring, etc.

[0085] The CN 115 may facilitate communications with other networks. For example, the CN 115 may include or may communicate with an IP gateway (e.g., an IP Multimedia Subsystem (IMS) server) that serves as an interface between the CN 115 and the PSTN 108. In addition, the CN 115 may provide the WTRUs 102a, 102b, 102c with access to other networks 112, which may include other wired and / or wireless networks owned and / or operated by other service providers. In one embodiment, the WTRUs 102a, 102b, 102c may be connected to a local data network (DN) 185a, 185b through the UPF 184a, 184b via an N3 interface to the UPF 184a, 184b and an N6 interface between the UPF 184a, 184b and the DN 185a, 185b.

[0086] In view of Figure 1A-Figure 1D and about Figure 1A-Figure 1D As described above, one or more or all of the functions described herein for one or more of the WTRUs 102a-d, base stations 114a-b, eNodeBs 160a-c, MMEs 162, SGWs 164, PGWs 166, gNBs 180a-c, AMFs 182a-b, UPFs 184a-b, SMFs 183a-b, DNs 185a-b, and / or any other devices described herein may be performed by one or more emulation devices (not shown). An emulation device may be one or more devices configured to emulate one or more or all of the functions described herein. For example, an emulation device may be used to test other devices and / or simulate network and / or WTRU functions.

[0087] The simulation device may be designed to implement one or more tests of other devices in a laboratory environment and / or an operator network environment. For example, one or more simulation devices may perform one or more or all functions while being fully or partially implemented and / or deployed as part of a wired and / or wireless communication network in order to test other devices within the communication network. One or more simulation devices may perform one or more or all functions while being temporarily implemented / deployed as part of a wired and / or wireless communication network. For testing purposes, the simulation device may be directly coupled to another device, and / or may use over-the-air wireless communications to perform testing.

[0088] The one or more simulation devices can perform one or more functions, including all functions, while not being implemented / deployed as part of a wired and / or wireless communication network. For example, the simulation device can be used in a test scenario in a test lab and / or a non-deployed (e.g., testing) wired and / or wireless communication network to implement testing of one or more components. The one or more simulation devices can be test devices. The simulation device can send and / or receive data using direct RF coupling and / or wireless communication via RF circuits (e.g., which can include one or more antennas).

[0089] Systems, methods, and means for demodulation reference signal (DM-RS)-free operation in wireless systems are described herein. A data channel structure (e.g., a DM-RS-free data channel structure) may be used. The DM-RS-free data channel structure may enable unsupervised DM-RS-free equalization. The DM-RS-free data channel structure may enable reporting of performance indicators and parameters associated with the DM-RS-free data channel structure.

[0090] The WTRU may perform a canonical correlation analysis (CCA) (e.g., associated with a DM-RS-free data channel structure). The WTRU may receive configuration information (e.g., CCA configuration information). The configuration information may indicate CCA view parameters and / or CCA views. The CCA view parameters may include one or more of the following: the location of repeated resource elements, CCA view length, starting symbol, resource block offset, mapping order, CCA reference signal configuration, etc. The WTRU may determine (one or more) CCA views, for example, based on the configuration information. The CCA view may include a set of REs. For example, a first CCA view may have a first set of REs, and a second CCA view may have a second set of REs (e.g., where the second set of REs may be a copy of the first set of REs). The CCA view may be associated with a CCA view length, where the CCA view length may be associated with a repetition pattern density. The WTRU may determine a first CCA view and a second CCA view (e.g., based on the configuration information). The WTRU may measure a CCA correlation coefficient associated with the first CCA view and the second CCA view. The WTRU may determine CCA subgrid information (e.g., subgrid size, number of subgrids, and / or number of CCA reference signals (CCA-RS) (e.g., for each subgrid), for example, based on a first CCA view, a second CCA view, and a CCA correlation coefficient. The determined subgrid size may be the number of resource blocks (RBs). The WTRU may determine whether to send an indication of the determined subgrid size based on whether the determined subgrid size is equal to the configured subband size. The WTRU may send a report (e.g., to the network) based on the determination of whether to send an indication of the subgrid size. The report may indicate the determined number of CCA-RS and the CCA correlation coefficient. The WTRU may, for example, demodulate and equalize the data channel using the received CCA-RS, the first CCA view, and the second CCA view.

[0091] The WTRU may determine that the determined sub-grid size is not equal to the configured sub-band size. Based on determining that the determined sub-grid size is not equal to the configured sub-band size, the report may indicate the determined sub-grid size.

[0092] The WTRU may receive a channel state information reference signal (CSI-RS). The WTRU may perform measurements based on the CSI-RS. The determination of the CCA subgrid information may be performed, for example, based on the measurements performed based on the CSI-RS.

[0093] The data channel structure as described herein may enable unsupervised DM-RS-free equalization. A mobile terminal (e.g., WTRU, STA) may determine and / or report one or more performance indicators and / or parameters of a DMRS-free data channel structure to a base station (e.g., gNB, access point (AP), etc.).

[0094] A data channel structure such as disclosed herein may employ a repetition protocol to achieve unsupervised DM-RS-free equalization. The repetition structure may be utilized at the receiver, for example, by creating multiple (e.g., two) data views (e.g., referred to as canonical correlation analysis (CCA) views). Unsupervised equalization may be achieved (e.g., using CCA) based on a repetition-based data channel structure.

[0095] Features associated with determining a preferred CCA subgrid size are disclosed herein. A WTRU may be configured with a CCA view for a data channel. As an example, the WTRU may measure a CCA correlation coefficient based on a received CCA view. The WTRU may determine one or more of: a CCA subgrid size, for example based on a received CCA view, a measured CCA correlation coefficient, and / or a configured CSI subband size or PRG size; or a number of CCA-RS (e.g., pilots) per subgrid, for example, based on an SNR, RSRP / RSRQ, and / or CCA view length per subgrid. As an example, if the determined CCA subgrid size is different from the configured subband size / PRG size, the WTRU may report a preferred CCA subgrid size, a CCA correlation coefficient per subgrid, and / or a preferred number of CCA-RS per subgrid. The WTRU may demodulate and equalize the data channel with the received CCA view and CCA-RS.

[0096] Features associated with a WTRU falling back to a legacy DM-RS are disclosed herein. The WTRU may be configured for CCA processing of a data channel. The WTRU may receive a CCA view configuration from a network device such as a base station (e.g., a gNB). The WTRU may receive a CCA-enabled data channel. The WTRU may determine a combiner based on a configured CCA view. The WTRU may measure a CCA correlation coefficient between CCA views. The WTRU may compare the CCA correlation with a configured threshold. The WTRU may determine whether it is necessary to fall back to the legacy, for example, based on the measured CCA correlation coefficient satisfying a threshold (e.g., being lower than a configured CCA correlation coefficient threshold).

[0097] Channel structures (e.g., new data channel structures) for low RS overhead and low complexity may be defined herein. CCA view structures and related parameters may be associated with channel structures (e.g., CCA view length, CCA repetition type, CCA multi-layer repetition offset, and / or CCA-RS). WTRU measurements of CCA parameters may be performed, for example, CCA correlation coefficients may be measured.

[0098] Determination of CCA parameters may be described herein. The WTRU may determine the view length and the repetition configuration type, for example, based on the measured channel. The WTRU may determine the CCA subgrid size based on the configured CCA view, the measured CCA correlation coefficient and / or the PRG size. The WTRU may determine the number of CCA-RS, for example, based on the SNR of each subgrid and / or the CCA view length.

[0099] Demodulation reference signal (DM-RS)-free operation may be implemented in a wireless system. A data channel structure may implement unsupervised DM-RS-free equalization. A mobile terminal (e.g., WTRU, STA) may determine and / or report one or more performance indicators and / or parameters of a DMRS-free data channel structure to a network (e.g., a base station such as a gNB and / or an access point (AP)).

[0100] A network (e.g., 5G NR) may include various types of reference signals (RS) that may be used for different purposes. For example, a demodulation reference signal (DM-RS) may be used to estimate an effective (e.g., precoded) channel response for coherent demodulation of a physical downlink shared channel (PDSCH) and / or a physical uplink shared channel (PUSCH). A DM-RS-based channel estimator may use (e.g., a large number of) several DM-RSs, for example, to support (e.g., ensure acceptable) channel estimation performance, which may result in an increase in overhead and / or (e.g., inversely) affect (e.g., overall) spectral efficiency. Reducing overhead may affect channel estimation, which may result in degradation of data equalization performance. In some examples (e.g., for multi-layer transmissions, such as simple user (SU)- or multi-user (MU)-multiple input multiple output (MIMO)), DM-RSs associated with different layers and / or users (e.g., in a MU-MIMO setting) may be orthogonal. Maintaining orthogonality may involve (e.g., tight) coordination between different base stations (e.g., gNBs, APs), which may be difficult to meet in a multi-cell network.

[0101] Artificial intelligence (AI) / machine learning (ML)-based techniques (e.g., which may include supervised and / or unsupervised learning) may be used to address (e.g., avoid or overcome) limitations of RS-based techniques (e.g., RS-based techniques). Canonical correlation analysis (CCA) (e.g., ML tools) may enhance data equalization performance (e.g., in an unsupervised manner), e.g., with low complexity. Canonical correlation analysis may be a statistical machine learning technique that may extract potential common representations from multiple (e.g., two) data views. Common components may be extracted, for example, by finding linear projections (e.g., linear CCA) of multiple (e.g., two) data views. Common components may be extracted, for example, by finding nonlinear projections (e.g., referred to as kernel CCA (KCCA) or deep CCA (DCCA)).

[0102] The data channel structure may employ a (e.g., simple) repetition protocol to achieve unsupervised, DM-RS-free equalization. The repetition structure may (e.g., then) be exploited at the receiver, e.g., by creating multiple (e.g., two) data views (e.g., referred to as CCA views). The CCA views may use canonical correlation analysis (CCA) to achieve unsupervised equalization.

[0103] CCA views and / or parameters (e.g., preferred CCA views and / or parameters) may be determined. The determined parameters may include, for example, one or more of the following: CCA view length; density in the time domain or frequency domain; mapping (e.g., time first / frequency first), which may be determined as a function of measured channel parameters (e.g., based on CSI-RS); the CCA view may be configured with PRB bundling. The WTRU may indicate CCA parameters. In an example (e.g., for a WTRU operating using a CCA-based data channel (without DM-RS)), the WTRU may determine whether it is better to fall back to legacy DM-RS operation. The repetition type (e.g., time vs. frequency) may be determined. Multi-layer / SU-MIMO operation may be enabled for CCA-based DM-RS-free operation.

[0104] Features associated with determining a preferred CCA subgrid size are disclosed herein. A WTRU may determine (e.g., be configured with) a CCA view for a data channel. As an example, the WTRU may measure a CCA correlation coefficient based on a received CCA view. The WTRU may determine one or more of: a CCA subgrid size, e.g., based on a received CCA view, a measured CCA correlation coefficient, and / or a configured CSI subband size or PRG size; a number of CCA-RS (e.g., pilots) per subgrid, e.g., based on a signal-to-noise ratio (SNR), a reference signal received power (RSRP) / reference signal received quality (RSRQ), and / or a CCA view length per subgrid. The WTRU may report a preferred CCA subgrid size, a CCA correlation coefficient per subgrid, and / or a preferred number of CCA-RS per subgrid, e.g., if the determined CCA subgrid size is different from the configured subband size / PRG size. The WTRU may demodulate and equalize the data channel with the received CCA view and CCA-RS.

[0105] Features associated with a WTRU falling back to a legacy DM-RS are disclosed herein. The WTRU may be configured for CCA processing of a data channel. The WTRU may receive a CCA view configuration from a network device such as a base station (e.g., a gNB). The WTRU may receive a CCA-enabled data channel. The WTRU may determine a combiner based on a configured CCA view. The WTRU may measure a CCA correlation coefficient between CCA views. The WTRU may compare the CCA correlation with a configured threshold. The WTRU may determine whether it is necessary to fall back to the legacy, for example, based on the measured CCA correlation coefficient satisfying a threshold (e.g., being lower than a configured CCA correlation coefficient threshold).

[0106] Channel structures (e.g., new data channel structures) for low RS overhead and low complexity may be defined herein. CCA view structures and related parameters may be associated with the channel structure, such as CCA view length, CCA repetition type, CCA multi-layer repetition offset, and / or CCA-RS. WTRU measurements of CCA parameters may be performed, such as CCA correlation coefficients may be measured.

[0107] Determination of CCA parameters may be described herein. The WTRU may determine the view length and the repetition configuration type, for example, based on the measured channel. The WTRU may determine the CCA subgrid size based on the configured CCA view, the measured CCA correlation coefficient, and / or the precoding resource block group (PRG) size. The WTRU may determine the number of CCA-RS, for example, based on the SNR of each subgrid and / or the CCA view length.

[0108] Machine learning (ML) may refer to a type of (one or more) algorithms that solve problems based on learning through experience (e.g., data), for example, without being (e.g., explicitly) programmed (e.g., configured with a set of rules). Machine learning may be considered a subset of artificial intelligence (AI). Different machine learning paradigms may be utilized (e.g., based on the nature of the data or feedback available to the learning algorithm). For example, supervised learning methods may involve learning a function that maps an input to an output based on labeled training examples. (E.g., each) training example may include a pair containing an input and a corresponding output. Unsupervised learning methods may involve detecting patterns in data without pre-existing labels. For example, reinforcement learning methods may involve performing a series of actions in an environment to maximize cumulative rewards. In some examples, a machine learning algorithm may be applied using a combination or interpolation of one or more methods (e.g., as described herein). For example, a semi-supervised learning method may use a combination of (e.g., a small amount of) labeled data and (e.g., a large amount of) unlabeled data during training. Semi-supervised learning may fall between unsupervised learning (e.g., no labeled training data) and supervised learning (e.g., only labeled training data).

[0109] Deep learning (DL) may refer to a class of machine learning algorithms that employ artificial neural networks (e.g., deep neural networks (DNNs)), which may be based on (e.g., roughly inspired by) biological systems. A deep neural network (DNN) may be a (e.g., special) class of machine learning models inspired by the human brain. The input to the DNN may be linearly transformed and / or may pass through a nonlinear activation function multiple times. The DNN may include multiple layers. (e.g., each) layer may include a linear transformation and / or one or more nonlinear activation functions. For example, the DNN may be trained using training data via a back-propagation algorithm. The DNN may provide state-of-the-art performance in various fields (e.g., speech, vision, natural language, etc.) and / or for various machine learning settings (e.g., supervised, unsupervised, and / or semi-supervised). An artificial intelligence markup language (AIML)-based method / processing may refer to implementing behavior and / or conforming to requirements by learning based on data (e.g., without configuration (e.g., explicit configuration) of a sequence of steps for an action). An AIML-based method may enable learning of complex behaviors that may be difficult to specify and / or implement (e.g., if / when traditional methods are used).

[0110] Factor analysis techniques can be used for machine learning, data analysis, and / or signal processing. For example, principal component analysis (PCA), coupled matrix factorization (CMF), independent component analysis (ICA), and / or canonical correlation analysis (CCA) can be used in compression, dimensionality reduction, visualization, subspace estimation, etc. Factor analysis techniques can operate in an unsupervised manner under one or more (e.g., different) objectives (e.g., depending on the application under consideration). Some factor analysis tools can extract latent components from one or more data views / matrices (e.g., PCA, ICA). Some factor analysis tools can recover latent common information from multiple data views / matrices (e.g., CMF, CCA).

[0111] Canonical correlation analysis (CCA) may include machine learning techniques that can be used in different fields of machine learning and / or signal processing. CCA may include multi-view analysis techniques that can be used to discover potential common information between multiple (e.g., two) data views. Single view analysis techniques (e.g., PCA) can be used to extract (e.g., strong) components from a data matrix. Multi-view analysis tools (e.g., CCA) can be used to (e.g., jointly) analyze different views of data. CCA can be based on a "difference" criterion that causes (e.g., forces) CCA to amplify (e.g., focus on, consider, etc.) (e.g., only) common content between different views (e.g., from an optimization perspective). One or more views may include (e.g., very) strong components that do not exist in another view. CCA can ignore principal components (e.g., no matter how strong they are), for example, as long as they are not common. CCA can operate in a linear manner (e.g., referred to as linear CCA) and / or a nonlinear manner (e.g., referred to as kernel CCA (KCCA), deep CCA (DCCA) and / or nonlinear CCA). Linear CCA may, for example, extract potential common features by finding (e.g., two) linear projections of (e.g., two) data views. Nonlinear CCA may, for example, extract potential common features by finding (e.g., generally) nonlinear projections of data views (e.g., based on DNN).

[0112] CCA can find two vectors and (e.g., referred to as CCA canonical vectors and / or CCA combiners). From two linear projections and The resulting N-dimensional components may be (e.g., maximally) correlated. These expressions and There can be two data views. In some examples (e.g., in an optimization framework), the CCA formula can be given by equation (1):

[0113]

[0114] Scaling constraints can be used to exclude (e.g., all) zero and / or meaningless solutions. A (e.g., simple) algebraic solution via eigenvalue decomposition can be implemented. The (e.g., overall) complexity can involve solving for the principal eigenvectors of the matrix, which involves multiplication of the autocovariance matrix and / or the cross-covariance matrix.

[0115] A demodulation reference signal (DM-RS) may be used to demodulate a signal. Coherent demodulation of a signal sent over a radio interface may use (e.g., require) knowledge of a (e.g., precoded / valid) wireless channel. A channel estimation process at a receiver in NR may use (e.g., rely on) transmission of a physical channel accompanied by one or more demodulation reference signals (DM-RS). The DM-RS may be generated using a pseudo-random sequence that may be based on one or more system parameters that may be known to the receiver. Parameters for controlling sequence generation may include, for example, one or more of a scrambling identity, symbol position, number of OFDM symbols in a slot, and the like. DM-RS operation in a network (e.g., NR) may include one or more (e.g., several) predefined options for a pattern (e.g., uniform / equally spaced) and / or density of RSs, which may be based on the physical channel. The RSs may be configured, for example, using scheduling (e.g., based on DCI) and / or (e.g., higher layer) configuration information to meet different use cases and / or WTRU capabilities.

[0116] The configuration of the DM-RS may include configuration of one or more of the following: density and / or pattern in the resource grid; duration; starting symbol (e.g., front-loaded DM-RS) and / or cover code, for example to distinguish between antenna ports, which may share the same time / frequency resources (e.g., for single-user and / or multi-user MIMO cases). The parameter set of the DM-RS may be set (e.g., may be different), for example, depending on the physical channel and / or depending on the WTRU capabilities. In some examples (e.g., for PDSCH DM-RS), there may be one or more of the following: configuration type 1 or type 2, mapping type A or type B, starting symbol for mapping type A, single symbol DM-RS vs. dual symbol DM-RS, DM-RS additional position and / or duration. The DM-RS may be grouped on one or more (e.g., several) resource blocks. For example, the precoder may be constant, for example, the receiver may perform wideband channel estimation.

[0117] The selection of DM-RS may be performed by (eg, based on) (eg, higher layer) configuration (eg, configuration information) and / or dynamic (eg, based on DCI) signaling. In some examples, there may be a default configuration. Figure 2 An example of a DM-RS pattern on (e.g., one) symbol and (e.g., one) resource block in a network (e.g., NR) is shown. Figure 2In some examples shown in FIG. 1 , the DM-RS may be configured with configuration type 1, mapping type A, and start symbol 3, using downlink antenna ports 1000-1003, with CDM grouping across frequency domain and code domain. The network (e.g., base station) may signal the selection of the DM-RS setting to the terminal (e.g., WTRU). The network (e.g., base station) may signal the setting, for example, using RRC, MAC-CE, and / or PDCCH / DCI.

[0118] The terminal (e.g., WTRU) may utilize the DM-RS to perform channel estimation and / or (e.g., coherent) demodulation of the corresponding physical channel. For example, channel estimation (e.g., and demodulation) may be performed using a receiver filter implementation (e.g., least squares, minimum mean square error (MMSE), etc.) that may estimate the composite channel by mapping the transmitted layers to the receive antennas for the scheduled resource blocks.

[0119] The channel estimation process may include, for example, one or more of the following: (i) a receiver may determine an estimate of the channel for a DMRS symbol based on its known position in a receive slot, where an averaging window may be used to minimize the effects of noise; (ii) multidimensional interpolation and extrapolation operations may be used to estimate loss values ​​associated with (e.g., all) other resource elements (REs) from a channel estimation grid; (iii) noise power estimation, which may be performed to improve performance by comparing direct and / or average channel estimates; (iv) a terminal (e.g., a WTRU) may use the channel and noise estimates to design an equalizer (e.g., MMSE); and / or (v) a terminal (e.g., a WTRU) may perform (e.g., coherent) OFDM demodulation on a precoded / beamformed physical channel. Figure 3 An example of an end-to-end DM-RS framework is shown.

[0120] Figure 2 An example of (e.g., NR) DM-RS symbol configuration type 1 for 4×4 MIMO is illustrated.

[0121] Figure 3 An example of DM-RS based channel estimation and equalization is illustrated.

[0122] The following notation is provided for one or more examples described herein: t It can be the number of transmitting antennas; N r It can be the number of receiving antennas; N s It can be the number of flows (e.g., the number of flows N s and the number of layers N Lmay be used interchangeably herein); N may be the number of REs per view, the number of symbols per view, and / or the CCA view length; and N CCA-RS It can be the number of reference signals used for CCA complex scaling ambiguity resolution.

[0123] Channel estimation may be used, for example, to equalize and / or demodulate a data channel. A WTRU (e.g., a 3GPP mobile terminal) may use DM-RS to estimate an effective (e.g., precoded) channel response experienced by a receiver, which may be (e.g., subsequently) used for equalization and / or demodulation. The quality of the channel estimate may (e.g., directly) affect equalization performance and / or channel / link performance. A large number of DM-RS symbols may be used to achieve channel estimation (e.g., acceptable channel estimation performance), which may result in high DM-RS overhead and / or a negative impact on spectral efficiency. Reducing the number of DM-RS symbols may reduce RS overhead and / or reduce channel estimation performance, which may reduce link performance. In some examples (e.g., for multi-layer transmission (SU- or MU-MIMO)), DM-RS signals across different layers / users may (e.g., need to) be orthogonal, which may (e.g., further) increase DM-RS overhead, for example, as the number of layers / co-scheduled users increases.

[0124] For example, if the channel estimator uses (e.g., additional) processing blocks such as one or more of: a noise estimator, a Doppler estimator, interpolation and / or extrapolation to (e.g., all) REs in the allocated channel, the implementation complexity of such an approach may be high.

[0125] The loss of orthogonality of DM-RS may result in poor channel estimation performance, which may degrade system performance.

[0126] One or more limitations of DM-RS based approaches may include, for example, RS overhead, implementation complexity, and / or performance degradation (eg, due to loss of orthogonality in a multi-cell network).

[0127] Features associated with a CCA-based processing configuration are disclosed herein. A data channel structure may be implemented with low overhead and / or low complexity.

[0128] The data channel structure(s) described herein may not include DM-RS (e.g., any DM-RS), which may be different from a data channel structure including reserved REs for DM-RS, e.g., as Figure 4 As shown. A data channel structure for CCA processing is shown and described herein for a WTRU (e.g., supporting CCA-based processing). The data structure may repeat one or more (e.g., several) data symbols in a time-frequency grid, such as Figure 5 As shown in the example in . Repetition may be employed in time and / or frequency (e.g., a mixture of time and frequency). Different repetition patterns may yield different performance. The repetition structure may be utilized on the WTRU side to derive a CCA combiner that may be used to decode PDSCH data in the repetition location, for example, as well as data in its neighborhood.

[0129] Figure 4 An example of a DM-RS data channel structure is illustrated. Figure 4 Reserved REs 402 and data REs 404 for DM-RS are shown.

[0130] Figure 5 An example of a DMRS-free data channel structure is illustrated. Figure 5 Shown are reserved / redundant REs 502 (eg, due to duplication), data REs 504, and data REs 506 at a "copied from" location. Figure 6 An example view in a DM-RS-free data channel structure is illustrated.

[0131] The repetition-based data structure may include, for example, one or more of the following parameters: RepetitionConfigType; RepetitionReservedStartSymbolIndex; RepetitionReservedAddPos; RepetitionReservedLengthPerSymbol; CCAViewsOffset; RepetitionReservedStartSubcarrierIndex; NROFcCAR; and / or MultilayerRepetitionOffset.

[0132] The parameter RepetitionConfigType may indicate the repetition type adopted at the gNB. This parameter may be one bit indicating, for example, whether it is time repetition or frequency repetition. This parameter may be more than one bit, for example, to indicate more types (e.g., mixed). The WTRU may assume a default value (e.g., time repetition), for example, if this field is not present / indicated.

[0133] The parameter RepetitionReservedStartSymbolIndex may represent / indicate the start of an OFDM symbol index, which may include reserved REs. The parameter RepetitionReservedStartSymbolIndex may also represent / indicate the start of an OFDM symbol index for the location to copy to. The parameter RepetitionReservedStartSymbolIndex may be used (e.g., only) in conjunction with time repetition. For example, the parameter RepetitionReservedStartSymbolIndex may be set to 10 (e.g., as Figure 5 (shown in the example on the left).

[0134] The parameter RepetitionReservedAddPos may indicate the number of additional symbols that include the reserved REs. The repetition parameter may be considered for (e.g., only) half a slot. The repetition parameter may have a value such as 1 or 2, for example, where 1 may represent one additional symbol and / or 2 may represent two additional symbols. The WTRU may be configured with up to three OFDM symbols that may carry the reserved elements. The WTRU may assume a default value (e.g., only one symbol for the index signaled under the field RepetitionReservedStartSymbolIndex), for example, if the repetition field is not present / not indicated.

[0135] The parameter RepetitionReservedLengthPerSymbol may indicate the spacing (e.g., frequency density) between reserved REs in an OFDM symbol. This parameter may have values ​​such as (0, 1, 2, 3), for example, where 0 may indicate that (e.g., all) subcarriers are reserved for the starting symbol index under consideration. In some examples (e.g., Figure 5 (shown on the left), the parameter can be set to 0.

[0136] The parameter CCAViewsOffset may represent the time / frequency offset between multiple (e.g., two) CCA views (e.g., the "copy to" and "copy from" positions). This parameter may have time-repeated values, such as four values ​​in the range 1 to 13. For example, if the start OFDM symbol of the reserved RE is set to 13, the offset may be at most 13, which may indicate that the copy from position is or should be the data in OFDM symbol 0. The WTRU may find the position to copy from (another CCA view), for example, by subtracting the RepetitionSymbolOffset from the RepetitionReservedStartSymbolIndex.

[0137] The parameter RepetitionReservedStartSubcarrierIndex may represent a starting subcarrier index, which may include reserved REs. The parameter RepetitionReservedStartSubcarrierIndex may (e.g., also) represent / indicate a subcarrier index of the start of the replication to position. This parameter may (e.g., only) be used in conjunction with frequency repetition.

[0138] The parameter NrofcCAR may indicate the number of configured CCA-RS used for CCA scaling ambiguity resolution.

[0139] The parameter MultilayerRepetitionOffset may allow the WTRU to identify repetition patterns associated with other transport layers. For example, the parameter may indicate a pseudo-random seed that the WTRU may use on top of a reference pattern (e.g., a reference pattern for layer 1) to find other patterns. In some examples, the parameter may indicate an offset in time and / or frequency between the reference pattern and the pattern of one or more other layers.

[0140] In some examples, the WTRU may be configured with a set (e.g., known) of patterns that may include repetitions in time and / or frequency. The pattern employed may be signaled to the WTRU, for example to construct (e.g., two) views. In some examples, the WTRU may be configured with multiple (e.g., two or more) subsets. For example, there may be subsets for (e.g., each) repetition type (e.g., with different densities). The WTRU may be configured with one of the patterns associated with a subset (e.g., associated with any subset).

[0141] The WTRU may perform CCA based processing.

[0142] The WTRU may construct (eg, based on / upon receiving a PDSCH transmission with a repetition-based data structure) (eg, two) CCA views Y. 1 and Y 2 (For example, and ). Parameter N may be defined as the number of REs per view, the number of symbols per view, and / or the CCA view length (eg, as described herein). Parameter N r may be the number of receive antennas. The WTRU may (eg, once two views are constructed) drive the CCA combiners q1 and q2 (eg, and ), for example, by solving CCA, for example, as shown in the example of equation (1). The WTRU may (e.g., then) apply the derived combiner to (e.g., the entire) received signal (e.g., ), for example, to decode PDSCH data symbols. Parameter N data may be the total number of data symbols in the received resource grid. The WTRU may select one of the combiners (e.g., q 1 or q 2 ), for example, to combine (e.g., all) data REs in the received resource grid, for example, this may occur if the (e.g., two) combiners are the same or close to each other (e.g., up to ∈). In some examples, the WTRU may (e.g., select) the data portion to combine using q 1 part of the data and use q 2 For example, q 1 It can be used to combine REs near the symbol in the first CCA view, while q 2 The WTRU may (e.g., also) calculate (e.g., measure) and / or report the resulting CCA correlation coefficient, which may be determined, for example, according to equation (2):

[0143]

[0144] The value of the parameter ρ may be 0≤ρ≤1. The parameter ρ may be a CCA-related parameter indicating detection performance.

[0145] The data signal recovered after CCA combining may be subject to (e.g., complex) scaling ambiguity, which may be part of (e.g., inherent to) CCA. The scaling ambiguity may be resolved, for example, using a type of reference signal (RS), which may be referred to as CCA-RS (e.g., as described herein). The WTRU may be configured with (one or more) CCA-RS locations (e.g., number (N)). CCA-RS )) and / or (one or more) symbol sequences, which may be known at the WTRU and the network (NW). The symbols may be (e.g., only) used for complex scaled ambiguity resolution.

[0146] The WTRU may repeat / perform the process multiple times, for example, based on the assigned BWP.The WTRU may solve multiple CCA problems (eg, in parallel), for example, depending on the resource grid size and / or channel conditions (eg, as described herein).

[0147] The WTRU may be configured for CCA-based processing. The WTRU may be configured with, for example, a higher layer parameter DataStructureType, which may be a bit indicating whether the received data channel structure is for CCA reception or for DM-RS reception. For example, if DataStructureType is set to '1', the WTRU may assume CCA processing, otherwise (for example, if DataStructureType is set to '0'), the WTRU may assume DM-RS processing. The WTRU may (for example, if configured for CCA processing) use CCA parameters and / or repetition pattern parameters to form (for example, two) CCA views that can be used to derive a combiner. CCA parameters may include, for example, pattern-related parameters (for example, for constructing CCA views) and / or CCA-RS sequences and / or positions (for example, for CCA scaling correction). The WTRU may be configured with a number of CCA subgrids (for example, as described herein) and / or an associated number of CCA-RSs in (for example, each) configured subgrid.

[0148] Different patterns associated with different layers may be different, which may support CCA in multi-layer operation. Different patterns may be shifted in time and / or frequency, and / or pattern indices may be permuted versions of each other. The WTRU may be configured with a parameter MultilayerRepetitionOffset, which may allow the WTRU to find other layer patterns from a reference pattern.

[0149] The WTRU may be configured for CCA parameter determination. The WTRU may be configured to calculate (e.g., measure) and / or report (one or more) CCA correlation coefficients, for example, in the case of solving one or more CCA problems. For example, the WTRU may be configured with multiple CCA subgrids. The WTRU may report the correlation coefficient associated with each subgrid. In some examples, the WTRU may report an average correlation coefficient, for example, in the case of solving multiple CCA problems. In some examples (e.g., in the case of multi-layer transmission), the WTRU may be configured to report one or more correlation coefficients associated with (e.g., each) layer.

[0150] The WTRU may be configured to determine and / or report one or more (e.g., some) of the CCA related parameters. For example, the WTRU may be configured to determine the number of CCA subgrids and / or the required number of CCA-RS for (e.g., each) subgrid. The WTRU may (e.g., also) be configured to determine and / or report the repetition type. The WTRU may (e.g., also) be configured to recommend whether to (e.g., better) use (e.g., switch to) CCA processing or DMRS processing.

[0151] exist Figure 7 An example of CCA-based data channel processing (eg, by a WTRU) is shown in FIG.

[0152] Figure 7 An example of CCA-based data channel processing by a WTRU is illustrated.

[0153] One or more CCA parameters may be determined.

[0154] The CCA view format can be determined. For example, a CCA-based method can use multiple (e.g., two) views of the same data to estimate equalizer parameters. The estimation of the equalizer (e.g., an accurate estimation of the equalizer) can be performed, for example, by making the REs associated with the view observe the same channel with low variation. For example, the channel can be flat (e.g., as flat as possible) for (e.g., all) REs in the view. Channel characteristics can change gradually across subcarriers and / or OFDM symbols. REs suitable for forming (e.g., with low variation) CCA views can be adjacent to each other within a resource grid (e.g., with a high probability) and / or can be clustered together.

[0155] Although REs within a view may be clustered together, the (e.g., exact) set and / or (e.g., exact) format of REs that contribute to CCA may depend (e.g., heavily depend) on one or more channel properties, such as delay spread, Doppler, etc. The configuration and / or format of a view may change (e.g., as the properties change), for example, to satisfy the condition that the channel at the REs within the view is as flat as possible.

[0156] The CCA view format may be selected, for example, based on one or more (e.g., different) strategies, which may, for example, utilize one or more of: one or more optimization techniques, knowledge about the problem being solved (e.g., a priori knowledge), and / or a machine learning / deep learning solution (e.g., to utilize channel properties and / or raw channel values ​​to select the CCA view format).

[0157] The CCA view format may be determined, for example, based on one or more optimization strategies. In some examples, a subgrid of a channel matrix may have (e.g., a total of) REs. One or more (eg, two) of the following objectives may be evaluated, for example, from a CCA perspective. A CCA view may be based, for example, on (eg, two) non-overlapping subsets S of REs. 1c and S 2c to construct, which can be chosen to carry the symbol x of the copy cl .. In some examples, |S 1c |=|S 2c|=N and For example, where N can be defined as the view length. The grid of REs can be divided into (eg, two) non-overlapping subsets S 1 and S 2 , for example The two subsets may or may not have an equal number of REs. The subsets may be labeled (e.g., using two CCA-based equalizers q 1 ,q 2 The parameter S is the element to be balanced. 1c and S 2c can be subsets S 1 and S 2 .

[0158] One or more of the objectives may be modeled as a variance minimization formula, e.g., with a goal of dividing N REs into (e.g., two) non-overlapping subsets. The variance of the channel and / or channel amplitude on the REs within the subset may be minimized. The formula may be modeled as a set partitioning problem, which may be solved as a combinatorial optimization problem.

[0159] In some (e.g., alternative) examples, set partitioning can (e.g., also) be modeled as a clustering problem. Data clustering can be performed. For example, a linear discriminant analysis (LDA)-style model can be used. The LDA model can have an objective (e.g., similar objective) of minimizing variance within a cluster and / or maximizing variance across clusters. The LDA model can be implemented with low computational complexity.

[0160] The CCA view format may be determined, for example, based on a priori knowledge (e.g., a priori knowledge of the problem). The WTRU may be configured to determine and / or report the CCA view format. The CCA view format information may include, for example, one or more of: a repetition configuration type (e.g., RepetitionConfigType) and / or a repetition boundary.

[0161] A repetition configuration type (e.g., RepetitionConfigType) may indicate a preferred repetition type (e.g., the position of the (two) views). A repetition type may be (e.g., may indicate) for example Figure 5 The times and / or frequencies (e.g., mixed) shown (e.g., and described / defined herein).

[0162] A repeating border may represent a border between (eg, two) views (eg, Figure 5The repetition boundary line 508 in the CCA subgrid may be defined as an OFDM symbol offset for time-based repetition, a subcarrier offset for frequency repetition, and / or both an OFDM symbol offset and a subcarrier offset for hybrid repetition. For example, the offset may be measured relative to an OFDM symbol (e.g., a first OFDM symbol) and / or a subcarrier (e.g., a first subcarrier) of the CCA subgrid.

[0163] The WTRU may determine the CCA view format, for example, based on one or more channel measurements. For example, a combination of delay spread and Doppler may be used to identify a CCA view (e.g., Figure 8 ) and repeated boundaries (e.g., by Figure 8 ). The ratio of delay spread and / or Doppler parameters of the channel may be evaluated and / or their ratio (eg, delay spread to Doppler ratio (SDR)) may be utilized to select a CCA view format. Figure 8 An example configuration of a CCA view for a corresponding range of SDR values ​​is shown.

[0164] Figure 8 An example configuration / format of a CCA view with an example range of values ​​of Delay Spread to Doppler Ratio (SDR) is shown.

[0165] The CCA view format may be determined, for example, based on (e.g., as an alternative or in addition to utilizing prior knowledge about channel properties that may affect the CCA view format) one or more machine learning strategies. One or more available channel properties may be used. The ML model may learn a relationship (e.g., an appropriate relationship) between the channel properties and the CCA format / configuration.

[0166] The WTRU may send the associated channel attributes and / or rely on the gNB and the WTRU to (e.g., independently) estimate the same CCA view format, e.g., depending on the channel attributes used and / or the quantization / precision used to represent the channel attributes (e.g., each of the channel attributes). The WTRU may select a (e.g., appropriate) configuration and / or format of the CCA view and / or signal the configuration / format of the CCA view to the gNB, e.g., in case the number of bits used to send the channel attributes is high.

[0167] CCA view selection can (e.g., also) be modeled as a deep learning (DL) problem. For example, a DL model can predict a CCA view format for the (e.g., entire) channel matrix H. Format prediction can be modeled as a classification problem and / or a segmentation problem. In some examples (e.g., in a classification setting), multiple sets of potential configurations / formats of CCA views can be (e.g., considered to be) a priori referred to as a codebook. The DL model can be tasked with predicting the configuration / format that is likely to be most suitable for the input channel. In some examples (e.g., in a segmentation setting), the model can produce an output with the same size as the input channel. The model can predict a label for (e.g., each) RE, for example, to identify whether the RE is for view 1, view 2, or view 3. Figure 2 Contribute to either or neither.

[0168] The described machine learning methods (e.g., as described herein) can (e.g., also) be used for one or more other objectives (e.g., as described herein with respect to optimization).

[0169] CCA views may be reported. A CCA view (e.g., evaluated using ML and / or optimization strategies) may be reported, for example, in one or more of the following forms.

[0170] The CCA views may be reported based on a fixed set of (e.g., potential) CCA view formats / configurations and / or codebooks that may be maintained. The codebook may be known a priori at the WTRU and / or the network (e.g., gNB). The WTRU may identify (e.g., using ML and / or optimization strategies such as described herein) the (e.g., best) view format from the pre-selected formats / configurations. The WTRU may signal a codebook index corresponding to the selected CCA view format.

[0171] CCA views can be reported based on modeling as ellipses. For example, two CCA views can be modeled as ellipses (e.g., Figure 8 (as shown by the bounding ellipse around the reserved RE in ). The ellipse can be (e.g., completely) characterized by four (4) parameters, which can be given by the center coordinates (x1, y1) and the axis lengths (a, b). Four (4) quantities can be reported to uniquely define a CCA view. For example, a CCA view can be defined according to equation (3):

[0172]

[0173] The CCA view may be reported based on an unconstrained CCA view selection (e.g., performed in a fully unconstrained setting). The REs that contribute to the CCA view (e.g., all REs) may be expanded (e.g., across the entire grid of available REs). The locations of the REs may be sent (e.g., explicitly) from the WTRU to the network (e.g., gNB). The locations of the REs within the view may be sent, for example (e.g., directly) in uncompressed form and / or using one or more compressed forms.

[0174] The impact of different CCA view configurations (e.g., using different repetition types) on symbol error rate (SER) can be indicated (e.g., using simulation) for one or more (e.g., various) channel conditions, such as a frequency selective channel (e.g., high delay spread) and / or a fast fading channel. Fig. 9 An example of a CCA view configuration is shown. Fig. 9 As shown in the example in , mode 1 can use time domain repetition, mode 3 can use frequency domain repetition, and mode 2 can be a mixture.

[0175] Fig. 9 Examples of CCA view configurations (eg, repetition types) for performance evaluation are illustrated. Fig.10 Example CCA subgrids and CCA views for each subgrid are illustrated.

[0176] Fig.11 Shows Fig. 9 Examples of symbol error rates (SERs) for the example CCA repetition patterns shown in FIG. Fig.11 It is shown that, for example, in high delay spread and / or low Doppler scenarios, Mode 3 may perform better than Mode 1 and / or Mode 2. Fig.11 It is shown that, for example, in low delay spread and / or high Doppler scenarios, Mode 1 may perform better than Mode 2 and / or Mode 3 (e.g., Mode 3 fails). The example SER results for example CCA repetition patterns may indicate / suggest that repetition type and / or mode selection may be important (e.g., critical) to optimize CCA performance.

[0177] Fig.11 Example SER results (eg, simulation results) for different CCA view configurations (eg, different repetition types) in frequency selective and / or fast fading channels are illustrated.

[0178] The CCA view length may be determined.

[0179] The CCA view length (N) is a (e.g., critical) parameter that can be (e.g., carefully) selected. The CCA view length can be referred to as the repetition pattern density. Increasing N (e.g., to a higher value of N) can improve CCA performance, but can (e.g., simultaneously) reduce and / or throttle the transmission rate, which can reduce the maximum achievable throughput, e.g., because more reserved / redundant REs can be used for repetition.

[0180] The WTRU may (e.g., be configured to) determine and / or report the CCA view length. For example, the WTRU may determine the preferred view length based on the PDSCH performance (e.g., by tracking the BLER performance). The WTRU may indicate an increase in the CCA view length, for example, if the BLER exceeds a (pre-)configured BLER threshold (γ BELR ). The WTRU may determine the view length, for example, based on available computational resources, receiver complexity, and / or communication latency. A higher N may increase the number of multiplications that may be used to construct an autocovariance matrix and / or a cross-covariance matrix that may be used to derive a CCA combiner. A higher N may (e.g., thereby) affect receiver complexity. In some examples, the WTRU may determine the view length based on a preconfigured CCA correlation coefficient threshold (ρ th ) to determine the view length, e.g., as described herein. Increasing N may result in an improvement in the CCA correlation coefficient, which may (e.g., in turn) imply better CCA performance. The WTRU may recommend a (e.g., preferred) value for N, e.g., by tracking the correlation coefficient, which may be compared to a (pre-)configured threshold. For example, the WTRU may indicate to the network (e.g., gNB) to decrease, increase, or fix N based on the measured correlation. The WTRU may send an indication to decrease N, e.g., if the measured p is higher than p th The WTRU may send an indication to increase N, for example, if the measured p is less than p th The WTRU may not send anything, for example, if the measured p is equal to or close to p th Up to ∈.

[0181] The WTRU may (e.g., be configured to) independently solve one or more CCA problems. (e.g., one) CCA problem may be solved for each CCA subgrid (e.g., as described / defined herein). Channel conditions across different subgrids may (e.g., naturally) be different. CCA may (e.g., accordingly) behave differently for (e.g., each) CCA subgrid. The WTRU may (e.g., be configured to) report a (e.g., preferred) CCA view length for (e.g., each) CCA subgrid, for example based on a measured CCA correlation coefficient for (e.g., each) subgrid. The WTRU may receive configuration information indicating (e.g., be configured with) a set of possible values ​​for the view length, for example to reduce associated uplink overhead. The WTRU may recommend one or more of the available values.

[0182] A WTRU (e.g., supporting multi-layer transmission) may (e.g., independently) determine and / or report a (e.g., preferred) CCA view length for (e.g., each) layer. For example, the WTRU may measure a received SNR associated with each layer. The WTRU may determine the per-layer view length for each layer, for example, based on the measured SNR.

[0183] The CCA view length may be determined based on numerical results. The impact of the CCA view length performance may be evaluated, for example, via simulations.

[0184] Fig.12 An example graph of SER versus received SNR for different values ​​of N is shown, where 6≤N≤20. Increasing the view length may improve the average SER performance, for example, up to the value of N. Fig.12 As shown, the improvement may be (eg, only) a slight improvement in SER, for example, if / when N exceeds 14.

[0185] Fig.12 Examples of CCA performance for different view lengths 6≤N≤20 are illustrated.

[0186] Larger values ​​of N (eg, significantly larger values ​​of N) may reduce the overall transmission rate (eg, as the number of non-data REs increases), for example, without improving detection accuracy. Fig.13 Shown in Fig.13 Examples of results (eg, simulation results) for a higher range of N of 40≤N≤160 under various channel models identified in FIG.

[0187] Fig.13 Examples of CCA performance for different view lengths 40≤N≤160 are illustrated.

[0188] Fig.13It is shown (eg, consistent with other findings described herein) that larger values ​​of N may not (eg, significantly) enhance performance. A trade-off between view length and transmission rate may be considered.

[0189] CCA performance may be optimized in frequency selective channels (e.g., by subgridding). Subgridding may be used to optimize CCA performance, for example, in (e.g., highly) frequency selective channel scenarios. Subgridding may be motivated by RB bundling (e.g., to mitigate the effects of frequency selectivity). Subgridding may be different from the subband concept used to derive PMI as part of the CSI report. Subgridding may be used to determine the number of CCA problems to be solved to maintain target performance. Subgridding may involve the WTRU dividing an allocated BWP (e.g., the entire resource grid) into multiple subgrids (e.g., referred to as CCA subgrids). The WTRU may divide the (e.g., entire) resource grid into non-joined / non-overlapping and / or partially overlapping subgrids. CCA-based equalization may be performed for each CCA subgrid (e.g., independently). Subgrids may allow the CCA combiner to be based on a (e.g., approximately) flat channel (e.g., design / implementation). More than two combiners may be used on a resource grid, which may allow better interpolation / extrapolation of optimal equalization for different REs. Each sub-grid may be assigned a number of CCA-RSs that may be used for scaling ambiguity resolution, for example, because each sub-grid may be involved in solving (e.g., one) CCA problem. The number of CCA-RSs may be configurable per sub-grid. The WTRU may determine and / or report the number and / or sub-grid size of CCA sub-grids to be used for (e.g., to meet) a target performance.

[0190] The WTRU may determine one or more sub-gridding parameters (e.g., sub-grid information). The WTRU may derive one or more sub-gridding parameters (e.g., the number of CCA sub-grids, the size of each CCA sub-grid, and / or the number of CCA-RS per sub-grid), for example, based on (e.g., all) channel state information measurements, CCA correlation coefficients (e.g., and CCA views), and / or computational complexity.

[0191] In some examples, the WTRU may (e.g., be configured to) determine one or more sub-gridding parameters (e.g., sub-grid information), which may include the number of sub-grids (N). GS ) and / or subgrid size (SGS). The WTRU may determine the CCA subgrid size (e.g., measured in number of RBs), for example, based on a CCA correlation coefficient f(ρ) (e.g., and based on a CCA view). The CCA correlation coefficient f(ρ) may be determined / selected, for example, according to equation (4) (e.g., based on (one or more) CCA views, such as, for example, a first CCA view and a second CCA view):

[0192]

[0193] Referring to equation (4), the coefficient α i and ρ i The WTRU may determine N by comparing f(ρ) with the (pre-)configured correlation coefficient. SG For example, the WTRU may find a correlation coefficient that results in the measured correlation coefficient being close to a pre-configured CCA correlation coefficient threshold γ th SGS.

[0194] In some examples, the WTRU may determine the sub-gridding parameter (N) based on (e.g., complete) CSI measurements. SG , SGS) (e.g., the WTRU may receive the CSI-RS and may perform measurements associated with the CSI-RS, where, for example, CCA subgrid information may be determined based on the measurements). For example, the WTRU may determine the CSI-RS by using the channel matrix H j (j=1, ..., SGS) to determine SGS, which may be estimated via CSI-RS. The WTRU may calculate f(H) of SGS and / or a preconfigured CCASCIerror parameter j ). The function f(H) can be converted, for example, according to equation (5) j ) is determined / selected as the mean squared error (MSE):

[0195]

[0196] Referring to equation (5), ||.|| F may represent the Frobenius norm. The WTRU may adjust the SGS (e.g., based on a pre-configured CCACSIerror) until the MSE condition is met. In some examples, f(H j ) can be taken as the sum or weighted sum of cosine similarities.

[0197] The WTRU may (e.g., be configured to) determine the number of CCA-RS symbols, for example, based on a measured SNR for each sub-grid and / or one or more reference signals (e.g., reference signal related measurements such as RSRP and / or RSRQ). The WTRU may receive (e.g., be configured with) configuration information indicating a mapping between the number of CCA-RS and an associated SNR threshold. For example, a higher SNR may involve fewer CCA-RS relative to a low SNR region (e.g., as described herein). The CCA-RS locations (e.g., relative to the start of a sub-grid) may be (pre-)defined at the network (e.g., gNB) and / or the WTRU.

[0198] A WTRU (e.g., configured for CCA processing and / or using sub-gridding) may (e.g., also) determine and / or report a CCA-RBoffset parameter to the gNB. CCA-RBoffset may be a value or amount that defines the periodicity of repetition of a CCA pattern across RBs. For example, CCA-RBoffset=1RB may indicate that the CCA pattern is repeated in every RB, while CCA-RBoffset=2RB may indicate that the repetition is performed in every other RB (e.g., RB 1, 3, 5, ..., etc.). The parameter CCA-RBoffset may help improve the transmission rate, for example, because a smaller number of reserved REs may be used if CCA-RBoffset is greater than 1 (e.g., when CCA-RBoffset is greater than 1). The WTRU may (e.g., if configured), for example, determine the CCA-RBoffset parameter based on (e.g., full) CSI measurements (e.g., by measuring the variation of the channel across different RBs). The WTRU may select or pick a CCA-RBoffset that satisfies a pre-configured MSE threshold. The WTRU may satisfy one or more conditions, for example, if determining a value of CCA-RBoffset for a time repetition pattern (e.g., when determining a value of CCA-RBoffset for a time repetition pattern). For example, the condition (e.g., for a time repetition pattern) may be 1≤CCARBoffset≤subgridsize. The WTRU may satisfy one or more conditions, for example, if determining a value of CCA-RBoffset for a frequency repetition pattern (e.g., when determining a value of CCA-RBoffset for a frequency repetition pattern). For example, the condition (e.g., for a frequency repetition pattern) may be

[0199] The condition may ensure that (eg, all) sub-grids have CCA symbols to construct the combiner. For example, if this field is not indicated / missing, then the WTRU may assume a default value. For example, if this field is not indicated, then the WTRU may assume CCA-RBoffset=1RB.

[0200] The network (e.g., gNB) may send configuration information indicating CCA-RS and / or CCA parameters (e.g., configured CCA parameters, such as, for example, configured subband sizes) (e.g., CCA mode for each subgrid) (e.g., providing configuration of CCA-RS and / or CCA parameters). The WTRU may report subgridding information to the gNB, for example, to enable the gNB to generate the configuration. The subgridding information may be a sequence of starting points of subgrids in the resource grid. Uplink signaling overhead may be reduced or minimized. For example, the WTRU may report a single integer value defining the subgrid size, for example, if / when equal-sized and non-overlapping subgrids are configured for CCA equalization.

[0201] Subgridding parameters can be determined based on numerical results.

[0202] Fig.14 Examples of SER results (eg, simulation results) for various sub-grid sizes from 1 to 50 RBs in a (eg, highly) frequency selective channel (eg, where channel coherence BW << signal BW) are shown. Fig.14 , example results are shown for a CDL-C channel with 30 ns delay spread, 1 km / hour WTRU speed, and equal-sized and non-overlapping sub-grids.

[0203] Fig.14 Example SER results for equal and non-overlapping sub-grids in a CDL-C channel with a delay spread of 30 ns and a WTRU speed of 1 km / hour are illustrated.

[0204] Example SER results indicate that CCA performance may degrade for larger subgrid sizes (e.g., subgrids of size 50 and 25 RBs). The performance degradation may occur because symbols within the CCA signal experience different channel responses, which may violate the condition that symbols within the CCA should be constructed and / or repeated within time-bandwidth coherent blocks. The SER may decrease based on a reduction in the subgrid size (e.g., to subgrids of size 10, 5, and / or 2 RBs), for example, because the channel affecting the CCA signal within each subgrid tends to be flatter. If the subgrid size is 1 RB (e.g., when the subgrid size is 1 RB), the (e.g., average) SER may degrade, for example, because the view length of each subgrid tends to be (e.g., significantly) too small.

[0205] Fig.15Example SER results (e.g., simulation results) of average SER for a CCA pattern with 12 reserved REs / RBs and different CCA-RBoffset values ​​are shown. The CCA-RB offset may increase the transmission data rate, for example, because a smaller number of reserved REs are required. The WTRU may (e.g., then) implement one or more methods (e.g., as described herein) to assist in the decision of an appropriate CCA-RBoffset value to be reported to the gNB (e.g., and used by the gNB).

[0206] Fig.15 An example graph of SER versus SNR for data transmitted on a CDL-C channel and a resource grid of 52 RBs with a sub-grid size of 4 RBs is illustrated.

[0207] Sub-gridding may be based on (eg, have a relationship to) a sub-band size.

[0208] A WTRU (e.g., configured for CCA processing and / or employing sub-gridding) may assume that CCA symbols within a view may be precoded with the same precoder, for example, based on a pre-configured subband size. Different CCA views may be precoded with different precoders (e.g., CCA patterns that utilize a frequency repetition structure and / or where each view in the view is located in a different subband). Symbols within a view may be precoded with the same precoder (e.g., CCA patterns that repeat in time and / or where symbols in each view span (e.g., all) resource blocks within a sub-grid).

[0209] The WTRU may (e.g., therefore) determine the subgrid size based on the configured subband size (e.g., PRG size). The WTRU may, for example, prevent differently precoded symbols within a CCA view by (e.g., first) determining the subgrid size. The subgrid size may be determined, for example, such that one or more conditions for a time repetition scheme are satisfied. For example, the condition (e.g., for a time repetition scheme) may be mod(B, subgrid size) = 0. The subgrid size may be determined, for example, such that one or more conditions for a frequency repetition of one are satisfied. For example, the condition (e.g., for a frequency repetition scheme) may be For example, because CCA views in a frequency repetition scheme can be collected from half of a subgrid.

[0210] Fig.16 An example of the relationship between sub-grid and sub-band size is illustrated, where the REs within a sub-band SBn can be encoded with precoder f n Precoding.

[0211] Subgridding can be based on numerical results.

[0212] Fig.17 An example graph of SER and SNR results (eg, simulation results) for a time repetition scheme in a resource grid of 48 RBs and a subband size of 6 RBs is shown. A subgrid size that does not meet the conditions (eg, for the time repetition scheme) may not be able to recover the transmitted symbols.

[0213] Fig.17 Example graphs of SER versus SNR for different sub-grid sizes in a resource grid of 48 RBs and a sub-band size of 6 RBs are illustrated.

[0214] Phase ambiguity can be resolved.

[0215] The CCA process can produce symbol estimates with scaling errors (e.g., unknown complex scaling errors), which can result in a rotated and / or scaled constellation. For example, points in an observed constellation can be rotated and / or scaled (e.g., by the same amount) relative to a reference constellation, e.g., after applying a CCA combiner. Phase errors can be estimated and / or corrected, e.g., by using a subset of REs in a view to carry CCA pilot symbols (e.g., symbols with known phases), which can be referred to as CCA-RS. CCA-RS symbols can be incorporated into a CCA view. For example, N CCA-RS The symbol may be used to carry pilots for a view defined as a sequence of symbol (RE) indices In = {1:N}. N of the N REs in a view CCA-RS may not be used to carry data symbols, for example, because they may (eg, instead) carry known pilot symbols. IPn,n={1:N CCA-RS {IPn} may be an index for a pilot in a first view. The index {IPn} for the pilot may be a subset of {In}. The same set of indices may be used in the second view (e.g., with an offset of the distance between views). The views may (e.g., in this manner) maintain a repetitive property up to (e.g., any) phase difference (e.g., introduced by a CCA-RS). The REs (e.g., the same REs) in (e.g., each) view may be used to carry CCA pilots. The pilots may be known. The (e.g., each) RE carrying the pilots may be derotated, e.g., by the known phase of the pilots (e.g., before further processing). The REs used to carry the pilots may (e.g., also in this manner) contribute to the estimation of the CCA combiner.

[0216] The WTRU may determine the (eg, preferred) number N of pilots to use in the view CCA-RS and / or how the pilots may be distributed within the view. In some examples, (e.g., only) the preferred Np may be determined and / or reported to the network. The (e.g., exact) position of the pilots within the view may be determined by the view parameters and Np.CCA-RS For example, the first Np REs in a view may be used for CCA pilots. In some examples, IPn=Im, m=1, floor(N*n / N CCA-RS ),…N,n=1,…,N CCA-RS ; For example, pilots can be interleaved across views, which can reduce exposure to narrowband interference.

[0217] In some examples, the WTRU may (e.g., also) determine and / or report how the CCA pilots may be distributed within the view. For example, the WTRU may determine and / or report the number N CCA-RS and / or a starting index within a view (eg, the starting position and / or length of consecutive REs may be reported).

[0218] The WTRU may determine, for example, based on estimated channel properties (e.g., coherence time, SNR, and / or location of pilots) whether to apply a single phase correction to the entire subgroup or whether multiple phase corrections may be applied over a TTI. For example, if the estimated coherence time is small and / or if the views are separated by one or more OFDM symbols, a separate phase correction may be calculated for (e.g., each) CCA combiner. The phase correction estimates from (e.g., two) views may be interpolated and / or extrapolated, for example, to provide a separate phase correction for one or more (e.g., each) OFDM symbols in a TTI.

[0219] A composite channel may be composed on propagation channels, precoding, antennas, and / or radio impairments. Radio impairments may contribute to the dynamics of the channel, for example, in a manner that may not be related to the propagation channel. Phase noise may cause the coherence time of the composite channel to be short, for example, even if the propagation channel itself is unchanged. Short coherence times may occur for higher carrier frequencies (e.g., FR2). Coherence time can be improved, for example, by PTRS pilots. PTRS may be dense in the time domain and / or sparse in the frequency domain. In some examples, there may be up to one (1) subcarrier for PTRS in every other RB in the frequency domain. In some examples, there may be a PTRS for each symbol in the time domain (e.g., except where DMRS is located).

[0220] PTRS can be used for low phase noise. PTRS can be used in FR2 and / or configured for use in FR1. One or more (e.g., some or all) of the PTRS within a subgroup can be used for CCA phase estimation and / or correction, e.g., alone or with N introduced into the view. CCA-RSpilot combinations. For example, if a CCA view is used (e.g., when a CCA view is used), (e.g., existing) PTRS parameters may be used, but the process for interpreting them to locate the PTRS REs may be different. For purposes of determining the PTRS position, the position of the REs in the view may be treated similarly to the DMRS (e.g., the PTRS adapts to the CCA view in a manner similar to that of the PTRS adapts to the DMRS), for example, if the PTRS is configured with CCA (e.g., when the PTRS is configured with CCA). The PT-RS symbol position in a timeslot may start from the first OFDM symbol in the shared channel allocation, and / or may jump every LPT-RS symbol, for example, if a DM-RS symbol is not present in the interval and / or if the PTRS REs may intersect with REs from the view. In some examples, DMRS and CCA views may be used simultaneously.

[0221] In some examples (e.g., if a PTRS RE may intersect with an RE from a CCA view), the PTRS may be inserted into the view (e.g., and the RE may not be used to carry data symbols) and / or the corresponding RE in another view may (e.g., also) be filled with a PTRS RE.

[0222] Symbols carried in a CCA view may be (e.g., inherently) more robust, e.g., due to repetition (e.g., they may be combined). For example, more coded bits may be packed into a view to accommodate signals from PTRS and / or N CCA-RS The overhead of pilots. In some examples (e.g., if / when PTRS REs are populated into a CCA view, as described herein), after the PTRS is inserted into the CCA view, the transport block size may be maintained at its original size, e.g., by increasing the modulation order of other REs in the view. For example, 16QAM may be used, and multiple (e.g., three (3)) PTRS REs may be inserted into the view, in which case 4x3=12 coded bits may be lost. For example, compensation may be achieved by modulating six (6) of the remaining REs in each CCA view with 64QAM (e.g., adding 6*2=12 bits to the view) to maintain the same coded block size (e.g., after adding PTRS). Similarly, the PTRS may be inserted into an allocated (e.g., another) portion (e.g., not part of the CCA view). The lost coded bits may (e.g., similarly) be packed into the CCA view, e.g., using a higher order modulation. Similarly, N CCA-RS pilots may be included in the CCA view. Missing coded bits may (eg, similarly) be packed into the CCA view, eg, using a higher order modulation.

[0223] PTRS can be used in high phase noise. For example, if the phase noise is large (e.g., when the phase noise is large), then PTRS can be used at a higher time domain density (e.g., as dense as each symbol), such as with CCA views to provide additional benefits, such as if the phase noise is large (e.g., when the phase noise is large). CCA views can include Np>0 pilots (e.g., in addition to PTRS pilots) and / or N CCA-RS It may be zero. One or more (e.g., some or all) of the PTRS REs may be used (e.g., together with Np CCA pilots) for phase estimation and / or correction. The PTRS REs may be used to better interpolate the CCA combiner in symbols that may not include a CCA view. For example, the CCA views in symbols 2 and 12 may be interpolated (e.g., normally) without the help of the PTRS in FR1, for example, because the change from one CCA combiner to the next CCA combiner may be due to propagation channel dynamics. In some examples (e.g., for FR1), two OFDM symbols for pilots may be sufficient to track channel changes for demodulation purposes. In some examples (e.g., in high-speed channels that may be caused by phase noise impairment), the interpolation of the CCA combiner may be improved by a high time domain density PTRS. For example, the CCA combiner may be interpolated / extrapolated normally (e.g., without the help of PTRS). The interpolated / extrapolated CCA combiner may be based on (e.g., two) base combiners generated by CCA. The interpolation / extrapolation CCA combiner may include phase and / or amplitude adjustments. The interpolation / extrapolation CCA combiner may be (e.g., fundamentally) limited to slow changes within a TTI, for example, because there may be (e.g., only two) time domain observations of the channel. The interpolation / extrapolation CCA combiner may be (e.g., further) adjusted, for example to possibly correct for phase changes that are visible to high-density PTRS and / or invisible to lower-density CCA views. The adjustment may be (e.g., only) a phase adjustment. The adjustment may be the same for (e.g., all) allocated REs in the corresponding OFDM symbol. The combiner phase in (e.g., each) OFDM symbol may be adjusted by a normalized (e.g., and / or filtered) phase estimate of the PTRS RE. Normalization may be implemented relative to the OFDM symbol in which the CCA view exists, for example, so that the phase adjustment due to PTRS may be zero in the OFDM symbol.

[0224] CCA parameters can be determined based on numerical results.

[0225] The link-level performance of CCA equalization can be compared with (e.g., conventional) DM-RS-based methods. In some examples (e.g., for DMRS), a least squares (LS) estimate can be used to calculate the effective channel at the DMRS symbol position, which can be followed by time / frequency interpolation and / or extrapolation of the estimate in the remaining REs. Minimum mean square error (MMSE) equalization can be performed, for example, for effective channel estimation and / or received signals. The received PDSCH data can be demodulated (e.g., for CCA and DMRS). PDSCH channel processing (e.g., full PDSCH channel processing) can be performed (e.g., for CCA and DMRS). Perfect channel (PCHAN) knowledge results can be incorporated, for example, as an upper limit on BER and / or throughput performance.

[0226] You can Fig.18 The DMRS mode in Fig.19 The CCA mode in is compared.

[0227] Fig.18 An example of a DM-RS pattern is illustrated.

[0228] Fig.19 An example of a CCA mode is illustrated. The red lines shown in the example (eg, the middle vertical line) separate groups of REs that are combined with the same combiner.

[0229] Link level performance may be determined for low delay spread and high speed WTRUs. Link level (eg, simulation) results for low delay spread and high WTRU speeds may be generated, for example, using a CDL-C channel model with a delay spread of 30ns and a WTRU speed of 60km / hr.

[0230] Fig. 20 An example of throughput results for a method based on CCA and (eg, conventional) DM-RS is shown. Fig. 20 As shown, the CCA mode can provide 40% more throughput (e.g., on average) than the DMRS mode. The maximum achievable throughput of (e.g., all) CCA modes can be greater than the maximum achievable throughput of DMRS modes 2 and 3, for example, because the number of reserved RE / RBs of the CCA mode can be less than the corresponding number of DMRS. The CCA mode can provide (e.g., compared to the DM-RS mode) a larger transport block size and / or an increased maximum throughput.

[0231] Fig. 20 Examples of throughput and SNR based on CCA and DM-RS for an RG of 52 RBs and a sub-grid size of 4 RBs are illustrated.

[0232] Link level performance may be determined for high delay spread and low WTRU speed.Link level simulation results for high delay spread and low WTRU speed may be generated, for example, using a CDL-C channel model with a delay spread of 300ns and a WTRU speed of 1km / hr.

[0233] A DMRS pattern (eg, DMRS pattern 1) may be compared to a CCA pattern (eg, as described when the sub-grid size is changed such that the sub-grid size ∈ {2,4}). Fig.21 It is shown that the CCA mode provides higher throughput compared to the considered DMRS.

[0234] Fig.21 An example of throughput and SNR based on CCA and DM-RS for an RG of 52 RBs is illustrated.

[0235] CCA parameters may be indicated.

[0236] The CCA view parameters and / or CCA view performance may be reported, for example, based on one or more triggers. The WTRU may determine the CCA view parameters and / or CCA view performance. The WTRU may be triggered to report the CCA view parameters and / or performance.

[0237] Triggers for reporting CCA view performance may include, for example, one or more of the following: a trigger based on the WTRU detecting a change in channel conditions (e.g., as measured based on a received CSI-RS); a trigger based on the WTRU determining that the CCA performance is below a configured threshold; a trigger based on the WTRU receiving a (e.g., new) CCA view configuration from the gNB; a trigger based on a change in DL assignment parameters (e.g., the number of allocated PRBs may change and / or the gNB may change the precoding resource block group (PRG) size); a periodic trigger (e.g., every N received data channel TTIs, where N may be one or more and / or may be configurable by the gNB); and / or a trigger based on the WTRU receiving a CCA performance report request from the gNB.

[0238] Triggers for reporting CCA view parameters may include, for example, one or more of: triggers based on scheduled transmissions of UL CSI reports (e.g., the WTRU may be configured to include one or more parameters of a preferred CCA view configuration determined by the WTRU in the UL CSI report); triggers based on a WTRU-determined change in channel conditions (e.g., as measured based on received CSI-RS); triggers based on the WTRU determining that CCA performance is below a configured threshold; and / or periodic triggers (e.g., at time instances configured by the gNB).

[0239] CCA view performance may be monitored. The WTRU may measure the performance of the (e.g., current) CCA configuration, for example, based on the received CCA view. In some examples, the WTRU may measure the CCA correlation coefficient of (e.g., each) CCA subgrid in the assigned data channel resources. In some examples (e.g., if the WTRU is configured with more than one CCA subgrid for the assigned resources / when the WTRU is configured with more than one CCA subgrid for the assigned resources), the WTRU may calculate the (e.g., average) CCA correlation coefficient across the subviews. In some examples, the WTRU may measure the CCA correlation coefficient of one or more (e.g., smaller) CCA subgrids. For example, if the measured CCA correlation coefficient for the configured subgrid is below a configured threshold, the WTRU may measure the CCA correlation coefficient for one or more (e.g., smaller) CCA subgrids. For example, if / when multi-layer transmission is used, the WTRU may measure, for example, the CCA correlation coefficient of each transmission layer (e.g., for each subgrid or average value). The WTRU may measure the CCA correlation coefficient during (eg, every) TTI while receiving the data channel.

[0240] In some examples, the WTRU may use data channel ACK / NACK statistics to monitor CCA view performance.

[0241] CCA view parameters (e.g., preferred CCA view parameters) may be determined. The WTRU may determine, for example, a CCA view (e.g., preferred CCA view(s)) (e.g., a first CCA view or a second CCA view) and / or a preferred subset of parameters for a CCA view based on measurements of a received CSI-RS. The WTRU may determine, for example, one or more of: a CCA subgrid size; a number of CCA-RSs (e.g., per subgrid); a CCA view length (e.g., per subgrid); and / or a repetition type (e.g., RepetitionConfigType), which may indicate whether the selected data REs should be repeated in time, frequency, and / or a mixture of time and frequency.

[0242] In some examples, the WTRU may determine one or more CCA view parameters (e.g., preferred CCA view parameters), for example, based on a current (e.g., received) CCA view. For example, the WTRU may calculate a CCA correlation coefficient for a first sub-grid size that is smaller than a configured sub-grid. For example, if the CCA correlation coefficient measured for the first CCA sub-grid is greater than the correlation coefficient for the configured sub-grid, the WTRU may select the first sub-grid size as the (e.g., preferred) CCA view parameter.

[0243] CCA view parameters (e.g., preferred CCA view parameters) may be reported. The WTRU may report parameters or a subset of parameters for the determined (e.g., preferred) CCA view configuration. In some examples, the WTRU may report a complete set of parameters for the determined (e.g., preferred) CCA view. In some examples, the WTRU may report a subset of parameters for a (e.g., preferred) CCA view that is different from the configured CCA view. For example, if / when the (e.g., preferred) CCA subgrid size is different from the PRG size, the WTRU may report the (e.g., preferred) CCA subgrid size.

[0244] The WTRU may use dedicated UL resources to report (eg, preferred) CCA view parameters.

[0245] You can fall back to traditional determination.

[0246] The WTRU may perform measurements for detecting error events. A WTRU (e.g., configured for CCA-based data channel processing) may perform measurements to monitor equalization performance. The measurements performed by the WTRU may include, for example, one or more of: CCA correlation coefficients (e.g., associated with a first CCA view and a second CCA view); one or more channel conditions (e.g., delay spread, Doppler); received SNR and / or RSRP; and / or HARQ ACK statistics.

[0247] The WTRU may measure the CCA correlation coefficient for (eg, each) time slot in which data channel transmission is enabled. The WTRU may (eg, alternatively) measure the CCA correlation coefficient at configured time instances (eg, time slots, frames) during data channel transmission.

[0248] The WTRU may be configured with one or more thresholds (e.g., via RRC signaling). For example, the threshold may be a CCA correlation threshold. The CCA correlation threshold may be fixed or may be a function of the SNR. The WTRU may be configured with a first CCA correlation threshold, for example, to determine a (e.g., preferred) CCA view configuration. The WTRU may be configured with a second CCA correlation threshold (e.g., for error event detection).

[0249] In some examples, the WTRU may receive a CCA-enabled data channel. The WTRU may determine a combiner, for example, based on a configured CCA view. The WTRU may measure a CCA correlation coefficient of the received CCA view. The WTRU may compare the measured CCA correlation coefficient with a first CCA correlation threshold (if configured). For example, if the measured CCA correlation is less than the first configured CCA threshold, the WTRU may determine an alternative CCA view configuration. For example, if channel conditions have changed, the WTRU may determine an alternative CCA view configuration. For example, if the measured CCA correlation is less than the second configured CCA threshold, and / or if the configured CCA view is a (e.g., preferred) view, the WTRU may determine that an error event has occurred. In some examples, if the measured CCA correlation threshold for a preconfigured number of data transmission intervals (e.g., TTIs, time slots) is less than the second configured CCA threshold, the WTRU may (e.g., alternatively) determine that an error event has occurred.

[0250] In some examples, if the CCA correlation error detection threshold is a function of the SNR, the WTRU may first measure the received SNR. The WTRU may determine the error detection threshold. The WTRU may compare the measured CCA correlation coefficient with the determined error detection threshold, for example, to determine whether an error has occurred.

[0251] The WTRU may be configured with one or more actions, for example, if a CCA error event is detected (e.g., when a CCA error event is detected). The WTRU may indicate the error event to the gNB, for example, if the WTRU determines that a CCA error event has occurred. The WTRU may send a request to fall back to a legacy DM-RS based data channel configuration (e.g., based on the CCA error event). The WTRU may report a HARQ NACK indication to the gNB, for example, based on detecting a CCA error event (e.g., when a CCA error event is detected). The WTRU may (e.g., also) report a measured CCA correlation coefficient.

[0252] The WTRU may report an error event detection. In some examples, the WTRU may detect a CCA error event. The WTRU may report a CCA error event, for example, a PUCCH transmission with a configuration associated with the last downlink data assignment. In some examples, the WTRU may use PUSCH (e.g., a PUSCH transmission) to report a CCA error event and / or request a fallback to DM-RS transmission. The WTRU may send a scheduling request for resources to report an error event, a measured CCA correlation coefficient, and / or a fallback request.

[0253] Fig. 22Examples of determining and reporting CCA sub-grid parameters are illustrated. Features associated with determining preferred CCA sub-gridding parameters are disclosed herein. A WTRU may be configured for CCA processing of a data channel, for example, to determine one or more preferred CCA parameters. The WTRU may perform one or more of the following. The WTRU may report its CCA processing capabilities. The WTRU may be configured for CSI-based feedback. The WTRU may receive (one or more) CSI-RS. The WTRU may measure channels and / or channel parameters, such as delay spread, Doppler, etc. The WTRU may receive (e.g., configured) configuration information for CCA processing (e.g., of a data channel) (e.g., based on repeated data channel structure information, which may, for example, include (one or more) CCA view locations, CCA sub-gridding parameters, performance thresholds, configured sub-band sizes, etc., such as Fig. 22 ), which may include receiving or determining (one or more) CCA view parameters (e.g., a first CCA view associated with a data channel and a second CCA view associated with a data channel). The CCA view parameters may include one or more of the following: location of repeated PDSCHREs, CCA view length (N), starting symbol, RB offset, mapping order (e.g., time, frequency, or mixed), default configuration of CCA-RS (e.g., pilot), etc. The WTRU may measure the CCA correlation coefficient (e.g., as shown) based on the (e.g., received) CCA view and / or SNR (e.g., received SNR). Fig. 22 The WTRU may determine sub-grid parameters / information (e.g., Fig. 22 , such as, for example, one or more of: a CCA subgrid size, for example, based on one or more of: a (e.g., received) CCA view, a measured CCA correlation coefficient, a configured CSI subband size or PRG; a number of CCA-RS (e.g., pilots) per subgrid, for example, based on one or more of: an SNR, RSRP / RSRQ, or a CCA view length per subgrid; and / or a number of subgrids, for example, based on one or more of: a (e.g., received) CCA view or a measured CCA correlation coefficient. The WTRU may demodulate and / or equalize a data channel (e.g., as shown) with the received CCA view and CCA-RS. Fig. 22 The WTRU may report a preferred CCA subgrid size, a CCA correlation coefficient for each subgrid, and / or a preferred number of CCA-RSs for each subgrid, for example, if the determined CCA subgrid size is different from the configured subband size / PRG size (e.g., where the WTRU may determine a (e.g., feasible) set of subgrid sizes based on the configured subband size, for example, as Fig. 22 As shown), Fig. 22The WTRU may report the number of CCA-RS per subgrid, for example, if the determined CCA subgrid size is not different from the configured subband size / PRG size (e.g., Fig. 22 The receiving and sending / reporting in this article may be for a base station.

[0254] Features associated with a WTRU falling back to legacy DM-RS are disclosed herein. A WTRU may be configured for CCA processing of a data channel, for example, falling back to legacy DM-RS processing. The WTRU may perform one or more of the following. The WTRU may be configured for CCA processing for a data channel. The WTRU may receive a CCA view configuration from a gNB. The WTRU may receive a CCA-enabled data channel. The WTRU may determine a combiner, for example, based on a configured CCA view. The WTRU may measure a CCA correlation coefficient between CCA views. The WTRU may compare the CCA correlation with a configured threshold. For example, if the measured CCA correlation is greater than a configured threshold, the WTRU may use the determined combiner to equalize the data channel (e.g., legacy FEC processing may be followed). The WTRU may send a request to the gNB to switch to an alternative CCA view, for example, if the measured CCA correlation is less than a configured threshold and / or if the configured CCA view is not a preferred view. The WTRU may send a request to the gNB to fall back to (e.g., legacy) DM-RS data transmission, for example, if the measured CCA correlation is less than a configured threshold and / or if the configured CCA view is the preferred view.

[0255] Fig.23 Examples associated with fallback to DM-RS data transmission are illustrated, where the WTRU may perform one or more of the illustrated actions.

[0256] Features associated with determination of (e.g., preferred) CCA repetition types and parameters are disclosed herein. A WTRU may be configured for CCA processing of a data channel, for example, to determine a preferred CCA repetition type and / or parameters. The WTRU may perform one or more of the following. The WTRU may report the CCA processing capabilities of the WTRU. The WTRU may be configured for CSI-based feedback. The WTRU may receive a CSI-RS. The WTRU may measure a channel and / or channel parameters, such as delay spread, Doppler. The WTRU may be configured for CCA processing (e.g., for a data channel). The CCA view parameters may include, for example, one or more of the following: the location of repeated PDSCH REs, CCA view length (N), starting symbol, RB offset, mapping order (e.g., time, frequency, or mixed), and / or default configuration of CCA-RS (e.g., pilot). The WTRU may measure (e.g., complete) channel measurement CSI, for example, based on the received CSI-RS. The WTRU may determine the CCA repetition type and / or CCA repetition boundary, for example, based on channel measurements, configured CSI subband size, and / or PRG. The WTRU may report a preferred CCA repetition type and / or CCA repetition boundary for each sub-grid. The WTRU may demodulate and / or equalize the data channel with the received CCA view.

[0257] Fig.24 Examples associated with determination of (eg, preferred) CCA repetition types and parameters are illustrated, where the WTRU may perform one or more of the illustrated actions.

[0258] Although the above features and elements are described in particular combinations, each feature or element may be used alone without the other features and elements of the preferred embodiments, or in various combinations with or without the other features and elements.

[0259] Although the implementation described herein may consider 3GPP specific protocols, it should be understood that the implementation described herein is not limited to this scenario and may be applicable to other wireless systems. For example, although the solution described herein considers LTE, LTE-A, New Radio (NR) or 5G specific protocols, it should be understood that the solution described herein is not limited to this scenario and may also be applicable to other wireless systems.

[0260] The above process may be implemented in a computer program, software, and / or firmware incorporated into a computer-readable medium for execution by a computer and / or processor. Examples of computer-readable media include, but are not limited to, electronic signals (transmitted via wired and / or wireless connections) and / or computer-readable storage media. Examples of computer-readable storage media include, but are not limited to, read-only memory (ROM), random access memory (RAM), registers, buffer memory, semiconductor storage devices, magnetic media (such as, but not limited to, internal hard disks and removable disks), magneto-optical media, and / or optical media (such as compact disks (CD)-ROM disks and / or digital versatile disks (DVDs)). A processor associated with the software may be used to implement a radio frequency transceiver used in a WTRU, a terminal, a base station, an RNC, and / or any host computer.

Claims

1. A wireless transmit / receive unit (WTRU), include: A processor, the processor being configured to: receiving canonical correlation analysis (CCA) configuration information; determining a first CCA view and a second CCA view based on the CCA configuration information, wherein the first CCA view and the second CCA view are associated with a data channel; measuring a CCA correlation coefficient associated with the first CCA view and the second CCA view; Determine CCA subgrid information based on the first CCA view, the second CCA view, and the CCA correlation coefficient, wherein the determined CCA subgrid information includes a determined subgrid size, a determined number of subgrids, and a determined number of CCA reference signals (CCA-RS); determining whether to send an indication of the determined sub-grid size based on whether the determined sub-grid size is equal to the configured sub-band size; and A report is sent based on a determination of whether to send the indication of the determined sub-grid size, wherein the report indicates the determined number of CCA-RSs and the CCA correlation coefficient.

2. The WTRU of claim 1 , wherein the processor is further configured to: The data channel is demodulated and equalized using the received CCA-RS, the first CCA view, and the second CCA view.

3. The WTRU of claim 1 , wherein if the determined sub-grid size is not equal to the configured sub-band size, the report indicates the determined sub-grid size.

4. The WTRU of claim 1 , wherein the processor is further configured to: receiving a channel state information reference signal (CSI-RS); and performing measurements associated with the CSI-RS, in, The CCA sub-grid information is further determined based on the measurements associated with the CSI-RS.

5. The WTRU of claim 1, wherein the first CCA view comprises a first set of resource elements (REs), wherein the second CCA view comprises a second set of REs, and wherein the second set of REs comprises a copy of the first set of REs.

6. The WTRU of claim 1, wherein the first CCA view and the second CCA view are associated with a CCA view length, and wherein the CCA view length is associated with a repetition pattern density.

7. The WTRU of claim 1, wherein the determined sub-grid size is the number of resource blocks (RBs).

8. A WTRU according to claim 1, wherein the CCA configuration information includes CCA view parameters, wherein the CCA view parameters are one or more of the position of repeated resource elements, CCA view length, starting symbol, resource block offset, mapping order or CCA reference signal configuration.

9. A method, include: receiving canonical correlation analysis (CCA) configuration information; determining a first CCA view and a second CCA view based on the CCA configuration information, wherein the first CCA view and the second CCA view are associated with a data channel; measuring a CCA correlation coefficient associated with the first CCA view and the second CCA view; Determine CCA subgrid information based on the first CCA view, the second CCA view, and the CCA correlation coefficient, wherein the determined CCA subgrid information includes a determined subgrid size, a determined number of subgrids, and a determined number of CCA reference signals (CCA-RS); determining whether to send an indication of the determined sub-grid size based on whether the determined sub-grid size is equal to the configured sub-band size; and A report is sent based on a determination of whether to send the indication of the determined sub-grid size, wherein the report indicates the determined number of CCA-RSs and the CCA correlation coefficient.

10. The method according to claim 9, in, The method further comprises: The data channel is demodulated and equalized using the received CCA-RS, the first CCA view, and the second CCA view.

11. The method according to claim 9, in, If the determined sub-grid size is not equal to the configured sub-band size, then the report indicates the determined sub-grid size.

12. The method according to claim 9, in, The method further comprises: receiving a channel state information reference signal (CSI-RS); and Performing measurements associated with the CSI-RS, wherein the CCA subgrid information is further determined based on the measurements associated with the CSI-RS.

13. The method according to claim 9, in, The first CCA view includes a first set of resource elements (REs), wherein the second CCA view includes a second set of REs, and wherein the second set of REs includes a copy of the first set of REs.

14. The method according to claim 9, in, The first CCA view and the second CCA view are associated with a CCA view length, and wherein the CCA view length is associated with a repetition pattern density.

15. The method according to claim 9, in, The sub-grid size determined is the number of resource blocks (RBs).

16. The method according to claim 9, in, The CCA configuration information includes CCA view parameters, wherein the CCA view parameters are one or more of a position of repeated resource elements, a CCA view length, a start symbol, a resource block offset, a mapping order, or a CCA reference signal configuration.

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