Transmit signal quality for probabilistically shaped messages

Abstract

Methods, systems, and devices for wireless communication are described. Techniques described herein enable a probabilistically shaped message to meet quality requirements that an empirical probability distribution of the probabilistically shaped message approaches a target probability distribution. The proximity of the empirical probability distribution to the target probability distribution may be measured using a distribution proximity metric that is compared to a threshold. The distribution proximity metric may quantify a difference between the empirical probability distribution and the target probability distribution. In addition, the distribution proximity metric may quantify differences between respective moments of one or more orders of the empirical probability distribution and the target probability distribution.

Description

[0001] Cross-references

[0002] This patent application claims priority to U.S. patent application No. 18 / 168,846, filed by Yang et al. on February 14, 2023, entitled “TRANSMIT SIGNALQUALITY FOR A PROBABILISTICALLY SHAPED MESSAGE,” which is assigned to the assignee of this application and is expressly incorporated herein by reference. Technical Field

[0003] The following relates to wireless communications, including transmitted signal quality of probabilistically shaped messages. Background Art

[0004] Wireless communication systems are widely deployed to provide various types of communication content, such as voice, video, packet data, messaging, broadcast, etc. These systems may be able to support communication with multiple users by sharing available system resources (e.g., time, frequency, and power). Examples of such multiple access systems include fourth generation (4G) systems (such as long term evolution (LTE) systems, advanced LTE (LTE-A) systems, or LTE-A Pro systems) and fifth generation (5G) systems (which may be referred to as new radio (NR) systems). These systems may employ techniques such as code division multiple access (CDMA), time division multiple access (TDMA), frequency division multiple access (FDMA), orthogonal FDMA (OFDMA), or discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-S-OFDM). A wireless multiple access communication system may include one or more base stations, each of which supports wireless communication for communication devices, which may be referred to as user equipment (UE). Summary of the Invention

[0005] The described technology relates to methods, systems, devices and apparatus for supporting improved signal quality of probabilistically shaped messages. For example, the described technology allows probabilistically shaped messages to meet quality requirements of a target probability distribution close to the empirical probability distribution of the probabilistically shaped message. A distribution proximity metric that is compared with a threshold value can be used to measure the proximity of the empirical probability distribution to the target probability distribution. The distribution proximity metric can quantify the difference between the empirical probability distribution and the target probability distribution. In addition, the distribution proximity metric can quantify the difference between the corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution. A threshold value can be defined based on parameters of the probabilistically shaped message, such as the number of modulation symbols in the shaped block, the number of bits in the shaped block, the shaping rate, or the modulation order.

[0006] A method for wireless communication at a first wireless communication device is described. The method may include: performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits; and sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness measure between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0007] An apparatus for wireless communication at a first wireless communication device is described. The apparatus may include a processor, a memory coupled to the processor, and instructions stored in the memory. The instructions may be executable by the processor to cause the apparatus to: perform probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits; and send a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0008] Another apparatus for wireless communication at a first wireless communication device is described. The apparatus may include: means for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits; and means for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness measure between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0009] A non-transitory computer-readable medium storing code for wireless communication at a first wireless communication device is described. The code may include instructions executable by a processor to: perform probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits; and transmit a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0010] In some examples of the methods, apparatuses, and non-transitory computer-readable media described herein, the empirical probability distribution may be an empirical probability distribution of the shaped set of bits.

[0011] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for measuring the empirical probability distribution across transmissions of one or more shaped messages over a target duration.

[0012] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for modulating the set of shaped bits to generate a set of modulated symbols, wherein the empirical probability distribution may be an empirical probability distribution of corresponding amplitudes of the set of modulated symbols.

[0013] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the distribution closeness metric quantifies a difference between the empirical probability distribution and the target probability distribution.

[0014] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the distribution closeness metric can be a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

[0015] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the distribution closeness metric quantifies a difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

[0016] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for determining the threshold based on a parameter of the shaped message.

[0017] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the parameter may be the number of modulation symbols in a shaped block, the number of bits in a shaped block, a shaping rate, a modulation order, or a combination thereof.

[0018] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, sending the shaped message may include operations, features, components, or instructions for sending the shaped message according to a first maximum power reduction (MPR) associated with the shaped message, the first maximum power reduction (MPR) being different from a second MPR associated with uniform quadrature amplitude modulation (QAM).

[0019] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may also include operations, features, components, or instructions for sending the shaped message based on a first error vector magnitude (EVM) associated with the shaped message, the first error vector magnitude (EVM) being different from a second EVM associated with uniform QAM.

[0020] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for: decoding the shaped set of bits; reconstructing demodulated symbols based in part on the decoded shaped set of bits; and measuring an EVM associated with the shaped message based in part on the equalized probability shaped transmit waveform and the demodulated symbols.

[0021] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for receiving signaling indicating the distribution proximity metric.

[0022] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for receiving signaling indicating the target probability distribution.

[0023] A method for wireless communication at a second wireless communication device is described. The method may include receiving a shaped message from a first wireless communication device and outputting a signal indicating whether a distribution closeness measure between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message satisfies a threshold.

[0024] An apparatus for wireless communication at a second wireless communication device is described. The apparatus may include a processor, a memory coupled to the processor, and instructions stored in the memory. The instructions may be executable by the processor to cause the apparatus to: receive a shaped message from a first wireless communication device; and output a signal indicating whether a distribution closeness measure between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message satisfies a threshold.

[0025] Another apparatus for wireless communication at a second wireless communication device is described. The apparatus may include: means for receiving a shaped message from a first wireless communication device; and means for outputting a signal indicating whether a distribution closeness measure between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message satisfies a threshold.

[0026] A non-transitory computer-readable medium storing code for wireless communication at a second wireless communication device is described. The code may include instructions executable by a processor to: receive a shaped message from a first wireless communication device; and output a signal indicating whether a distribution closeness measure between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message satisfies a threshold.

[0027] Some examples of the methods, apparatus, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for demodulating a shaped set of bits from the shaped message, wherein the empirical probability distribution may be an empirical probability distribution of the shaped set of bits.

[0028] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for measuring the empirical probability distribution across transmissions of one or more shaped messages over a target duration.

[0029] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the empirical probability distribution may be an empirical probability distribution of respective amplitudes of a set of modulated symbols of the shaped message.

[0030] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the distribution closeness metric quantifies a difference between the empirical probability distribution and the target probability distribution.

[0031] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the distribution closeness metric can be a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

[0032] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the distribution closeness metric quantifies a difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

[0033] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for determining the threshold based at least in part on a parameter of the shaped message.

[0034] In some examples of the methods, apparatus, and non-transitory computer-readable media described herein, the parameter may be the number of modulation symbols in a shaped block, the number of bits in a shaped block, a shaping rate, a modulation order, or a combination thereof.

[0035] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for receiving signaling indicating the distribution proximity metric.

[0036] Some examples of the methods, apparatuses, and non-transitory computer-readable media described herein may further include operations, features, components, or instructions for receiving signaling indicating the target probability distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 An example of a wireless communication system supporting transmit signal quality of probabilistically shaped messages in accordance with one or more aspects of the present disclosure is illustrated.

[0038] Figure 2 An example of a wireless communication system supporting transmit signal quality of probabilistically shaped messages in accordance with one or more aspects of the present disclosure is illustrated.

[0039] Figure 3 An example of a diagram illustrating a channel coding based shaping technique to support transmit signal quality of a probabilistically shaped message in accordance with one or more aspects of the present disclosure is illustrated.

[0040] Figure 4 An example of a process flow for supporting transmit signal quality of probabilistically shaped messages in accordance with one or more aspects of the present disclosure is illustrated.

[0041] Figure 5 and Figure 6 A block diagram illustrating an apparatus supporting transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure is illustrated.

[0042] Figure 7 A block diagram illustrating a communications manager that supports transmit signal quality of probabilistically shaped messages in accordance with one or more aspects of the present disclosure is illustrated.

[0043] Figure 8 A diagram illustrating a system including a device supporting transmit signal quality of probabilistically shaped messages in accordance with one or more aspects of the present disclosure is illustrated.

[0044] Figure 9 and Figure 10 A block diagram illustrating an apparatus supporting transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure is illustrated.

[0045] Figure 11 A block diagram illustrating a communications manager that supports transmit signal quality of probabilistically shaped messages in accordance with one or more aspects of the present disclosure is illustrated.

[0046] Figure 12 A diagram illustrating a system including a device supporting transmit signal quality of probabilistically shaped messages in accordance with one or more aspects of the present disclosure is illustrated.

[0047] Figures 13 to 15 A flow chart illustrating a method of supporting transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure is illustrated. DETAILED DESCRIPTION

[0048] Existing wireless communication systems, such as cellular and Wi-Fi communication systems, may use higher-order modulation schemes (e.g., quadrature amplitude modulation (QAM)) to improve spectral efficiency at high signal-to-noise ratio (SNR) values. In such existing systems, constellation points may be fixed, and each constellation point may be used with equal probability (e.g., a wireless communication device may have equal probability of selecting a first constellation point and a second constellation point). Probabilistic shaping is a technique for generating non-uniformly distributed constellation points for a modulation scheme, and can improve spectral efficiency. One technique for probabilistic shaping may be probability amplitude shaping (PAS), which shapes the amplitudes of constellation points of a modulation scheme while uniformly distributing the symbols of the constellation points. Techniques for PAS may include compression-based schemes and channel coding-based shaping schemes. With probabilistic shaping, a wireless communication device, such as a user equipment (UE) or a network entity, may send a probabilistically shaped message intended to conform to a target probability distribution. If the probabilistically shaped message does not conform to the target probability distribution, another wireless communication device may not be able to correctly receive and decode the probabilistically shaped message.

[0049] A wireless communication device (e.g., a UE or a network entity) may meet a transmit signal quality requirement that an empirical probability distribution of a probabilistically shaped message is close to a target probability distribution (e.g., the closeness satisfies a threshold). The transmit signal quality requirement may be configurable or standardized. The wireless communication device may probabilistically shape information bits to generate a set of shaped bits and modulate the set of shaped bits to generate a set of modulated symbols. The empirical probability distribution of the probabilistically shaped message may be determined based on the respective amplitudes of the set of shaped bits or the set of modulated symbols. The empirical probability distribution may be measured across transmissions of one or more probabilistically shaped messages within a target duration.

[0050] A distribution proximity metric that is compared to a threshold value can be used to measure the proximity of the empirical probability distribution to the target probability distribution. The distribution proximity metric quantifies the difference between the empirical probability distribution and the target probability distribution. For example, the distribution proximity metric can be a Kullback-Leibler divergence score, entropy difference, total variation distance, Hellinger distance, or statistical distance. As another example, the distribution proximity metric can quantify the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution. In some examples, the threshold value can be defined based on parameters of the probabilistically shaped message. For example, the threshold value can be defined based on the number of modulation symbols in the shaped block, the number of bits in the shaped block, the shaping rate, or the modulation order.

[0051] Formulating and representing the transmit signal quality of probabilistically shaped messages can enable wireless communication devices to reliably communicate using probabilistically shaped messages. Wireless communication devices can correctly decode and transmit probabilistically shaped messages, and wireless communication devices can correctly receive and decode probabilistically shaped messages. Probabilistically shaped messages can improve spectral efficiency.

[0052] Various aspects of the present disclosure are first described in the context of a wireless communication system. Additional aspects of the present disclosure are described in the context of a wireless communication system, an example channel decoding-based shaping technique diagram, and an example process flow. Aspects of the present disclosure are further illustrated by and described with reference to apparatus diagrams, system diagrams, and flow diagrams related to transmit signal quality of probabilistically shaped messages.

[0053] Figure 1 An example of a wireless communication system 100 that supports transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure is illustrated. The wireless communication system 100 may include one or more network entities 105, one or more UEs 115, and a core network 130. In some examples, the wireless communication system 100 may be a Long Term Evolution (LTE) network, an Advanced LTE (LTE-A) network, an LTE-A Pro network, a New Radio (NR) network, or a network operating according to other systems and radio technologies, including future systems and radio technologies not explicitly mentioned herein.

[0054] The network entities 105 may be dispersed throughout a geographic area to form the wireless communication system 100 and may include devices in different forms or with different capabilities. In various examples, the network entities 105 may be referred to as network elements, mobility elements, radio access network (RAN) nodes, or network equipment, among other nomenclature. In some examples, the network entities 105 and the UEs 115 may communicate wirelessly via one or more communication links 125 (e.g., radio frequency (RF) access links). For example, the network entities 105 may support a coverage area 110 (e.g., a geographic coverage area) within which the UEs 115 and the network entities 105 may establish one or more communication links 125. The coverage area 110 may be an example of a geographic area within which the network entities 105 and the UEs 115 may support signal communication according to one or more radio access technologies (RATs).

[0055] The UEs 115 may be dispersed throughout the coverage area 110 of the wireless communication system 100, and each UE 115 may be stationary or mobile or both stationary and mobile at different times. The UEs 115 may be devices that take different forms or have different capabilities. Figure 1Some example UEs 115 are illustrated in FIG. The UEs 115 described herein may be capable of supporting communication with various types of devices, such as Figure 1 105 or other UEs 115 or network entities 105 as shown.

[0056] As described herein, a node of the wireless communication system 100 (which may be referred to as a network node or wireless node) may be a network entity 105 (e.g., any network entity described herein), a UE 115 (e.g., any UE described herein), a network controller, an apparatus, a device, a computing system, one or more components, or another suitable processing entity configured to perform any of the techniques described herein. For example, the node may be a UE 115. As another example, the node may be a network entity 105. As another example, a first node may be configured to communicate with a second node or a third node. In one aspect of this example, the first node may be a UE 115, the second node may be a network entity 105, and the third node may be a UE 115. In another aspect of this example, the first node may be a UE 115, the second node may be a network entity 105, and the third node may be a network entity 105. In other aspects of this example, the first node, the second node, and the third node may be different relative to these examples. Similarly, references to UE 115, network entity 105, apparatus, device, computing system, etc. may include disclosure of UE 115, network entity 105, apparatus, device, computing system, etc. as nodes. For example, a disclosure that UE 115 is configured to receive information from network entity 105 also discloses that the first node is configured to receive information from the second node.

[0057] In some examples, network entities 105 can communicate with core network 130, with each other, or both. For example, network entities 105 can communicate with core network 130 via one or more backhaul communication links 120 (e.g., according to S1, N2, N3, or other interface protocols). In some examples, network entities 105 can communicate with each other directly (e.g., directly between network entities 105) or indirectly (e.g., via core network 130) via backhaul communication links 120 (e.g., according to X2, Xn, or other interface protocols). In some examples, network entities 105 can communicate with each other via midhaul communication links 162 (e.g., according to a midhaul interface protocol) or fronthaul communication links 168 (e.g., according to a fronthaul interface protocol), or any combination thereof. Backhaul communication links 120, midhaul communication links 162, or fronthaul communication links 168 can be or include one or more wired links (e.g., electrical links, fiber optic links), one or more wireless links (e.g., radio links, wireless optical links), etc., or various combinations thereof. UE 115 may communicate with core network 130 via communication link 155 .

[0058] One or more of the network entities 105 described herein may include or may be referred to as a base station 140 (e.g., a base transceiver station, a radio base station, an NR base station, an access point, a radio transceiver, a Node B, an evolved Node B (eNB), a next-generation Node B, or a gigabit Node B (any of which may be referred to as a gNB), a 5G NB, a next-generation eNB (ng-eNB), a Home Node B, a Home evolved Node B, or other suitable terminology). In some examples, the network entity 105 (e.g., a base station 140) may be implemented in a converged (e.g., monolithic, stand-alone) base station architecture that may be configured to utilize a protocol stack that is physically or logically integrated within a single network entity 105 (e.g., a single RAN node, such as the base station 140).

[0059] In some examples, the network entity 105 can be implemented in a disaggregated architecture (e.g., a disaggregated base station architecture, a disaggregated RAN architecture) that can be configured to utilize a protocol stack that is physically or logically distributed between two or more network entities 105, such as an integrated access backhaul (IAB) network, an open RAN (O-RAN) (e.g., a network configuration sponsored by the O-RAN Alliance), or a virtualized RAN (vRAN) (e.g., a cloud RAN (C-RAN)). For example, the network entity 105 can include one or more of the following: a central unit (CU) 160, a distributed unit (DU) 165, a radio unit (RU) 170, a RAN intelligent controller (RIC) 175 (e.g., a near real-time RIC (near RT RIC), a non-real-time RIC (non-RT RIC)), a service management and orchestration (SMO) 180 system, or any combination thereof. The RU 170 may also be referred to as a radio head, smart radio head, remote radio head (RRH), remote radio unit (RRU), or transmit receive point (TRP). One or more components of the network entity 105 in the disaggregated RAN architecture may be co-located, or one or more components of the network entity 105 may be located in distributed locations (e.g., separate physical locations). In some examples, one or more network entities 105 of the disaggregated RAN architecture may be implemented as virtual units (e.g., virtual CU (VCU), virtual DU (VDU), virtual RU (VRU)).

[0060] The functional split between CU 160, DU 165, and RU 170 is flexible and can support different functions depending on which functions (e.g., network layer functions, protocol layer functions, baseband functions, RF functions, and any combination thereof) are performed at CU 160, DU 165, or RU 170. For example, a functional split of the protocol stack can be employed between CU 160 and DU 165 such that CU 160 can support one or more layers of the protocol stack and DU 165 can support one or more different layers of the protocol stack. In some examples, CU 160 can host higher protocol layer (e.g., Layer 3 (L3), Layer 2 (L2)) functions and signaling (e.g., Radio Resource Control (RRC), Service Data Adaptation Protocol (SDAP), Packet Data Convergence Protocol (PDCP)). The CU 160 may be connected to one or more DUs 165 or RUs 170, and the one or more DUs 165 or RUs 170 may host lower protocol layers, such as Layer 1 (L1) (e.g., physical (PHY) layer) or L2 (e.g., radio link control (RLC) layer, medium access control (MAC) layer) functions and signaling, and may each be at least partially controlled by the CU 160. Additionally or alternatively, a functional split of the protocol stack may be employed between the DU 165 and the RU 170, such that the DU 165 may support one or more layers of the protocol stack and the RU 170 may support one or more different layers of the protocol stack. The DU 165 may support one or more different cells (e.g., via one or more RUs 170). In some cases, the functional split between the CU 160 and the DU 165 or between the DU 165 and the RU 170 can be within the protocol layer (e.g., some functions of the protocol layer can be performed by one of the CU 160, DU 165, or RU 170, while other functions of the protocol layer are performed by a different one of the CU 160, DU 165, or RU 170). The CU 160 can be further functionally split into CU control plane (CU-CP) and CU user plane (CU-UP) functions. The CU 160 can be connected to one or more DUs 165 via midhaul communication links 162 (e.g., F1, F1-c, F1-u), and the DU 165 can be connected to one or more RUs 170 via fronthaul communication links 168 (e.g., open fronthaul (FH) interface). In some examples, midhaul communication link 162 or fronthaul communication link 168 may be implemented according to interfaces (eg, channels) between layers of a protocol stack supported by respective network entities 105 communicating via these communication links.

[0061] In some wireless communication systems (e.g., wireless communication system 100), the infrastructure and spectrum resources for radio access may support wireless backhaul link capabilities to supplement wired backhaul connections, thereby providing an IAB network architecture (e.g., to the core network 130). In some cases, in an IAB network, one or more network entities 105 (e.g., IAB nodes 104) may be partially controlled by each other. One or more IAB nodes 104 may be referred to as a donor entity or IAB donor. One or more DUs 165 or one or more RUs 170 may be partially controlled by one or more CUs 160 associated with a donor network entity 105 (e.g., a donor base station 140). One or more donor network entities 105 (e.g., IAB donors) may communicate with one or more additional network entities 105 (e.g., IAB nodes 104) via supported access and backhaul links (e.g., backhaul communication links 120). The IAB node 104 may include an IAB mobile terminal (IAB-MT) controlled (e.g., scheduled) by the DU 165 of the coupled IAB donor. The IAB-MT may include an independent set of antennas for relaying communications with the UE 115, or may share the same antennas of the IAB node 104 (e.g., RU 170) for access via the DU 165 of the IAB node 104 (e.g., referred to as a virtual IAB-MT (vIAB-MT)). In some examples, the IAB node 104 may include a DU 165 that supports communication links with additional entities (e.g., IAB node 104, UE 115) within a relay chain or configuration (e.g., downstream) of the access network. In such cases, one or more components of the decomposed RAN architecture (e.g., one or more IAB nodes 104 or components of the IAB node 104) may be configured to operate according to the techniques described herein.

[0062] In the context of a decomposed RAN architecture, one or more components of the decomposed RAN architecture may be configured to support transmit signal quality of probabilistically shaped messages as described herein. For example, some operations described as being performed by a UE 115 or a network entity 105 (e.g., a base station 140) may additionally or alternatively be performed by one or more components of the decomposed RAN architecture (e.g., an IAB node 104, a DU 165, a CU 160, a RU 170, a RIC 175, a SMO 180).

[0063] UE 115 may include or may be referred to as a mobile device, a wireless communication device, a remote device, a handheld device, or a subscriber device, or some other suitable terminology, where "device" may also be referred to as a unit, a station, a terminal, or a client, etc. UE 115 may also include or may be referred to as a personal electronic device, such as a cellular phone, a personal digital assistant (PDA), a tablet computer, a laptop computer, or a personal computer. In some examples, UE 115 may include or may be referred to as a wireless local loop (WLL) station, an Internet of Things (IoT) device, an Internet of Everything (IoE) device, or a machine type communication (MTC) device, etc., which may be implemented in various objects, such as appliances or vehicles, meters, etc.

[0064] The UE 115 described herein may be capable of communicating with various types of devices, such as other UEs 115, which may sometimes act as relays, as well as network entities 105 and network equipment including macro eNBs or gNBs, small cell eNBs or gNBs, or relay base stations, etc. Figure 1 shown.

[0065] The UE 115 and the network entity 105 may wirelessly communicate with each other via one or more communication links 125 (e.g., access links) using resources associated with one or more carriers. The term "carrier" may refer to a collection of RF spectrum resources having a physical layer structure defined for supporting the communication link 125. For example, a carrier used for the communication link 125 may include a portion of an RF spectrum band (e.g., a bandwidth portion (BWP)) that operates according to one or more physical layer channels for a given radio access technology (e.g., LTE, LTE-A, LTE-A Pro, NR). Each physical layer channel may carry acquisition signaling (e.g., synchronization signals, system information), control signaling for coordinating carrier operations, user data, or other signaling. The wireless communication system 100 may support communications with the UE 115 using carrier aggregation or multi-carrier operation. Depending on the carrier aggregation configuration, the UE 115 may be configured with multiple downlink component carriers and one or more uplink component carriers. Carrier aggregation may be used for both frequency division duplex (FDD) and time division duplex (TDD) component carriers. Communication between the network entity 105 and other devices may refer to communication between those devices and any portion (e.g., entity, sub-entity) of the network entity 105. For example, the terms "send," "receive," or "communicate" when referring to the network entity 105 may refer to any portion of the network entity 105 (e.g., base station 140, CU 160, DU 165, RU 170) of the RAN communicating with another device (e.g., directly or via one or more other network entities 105).

[0066] The signal waveform transmitted via the carrier may include multiple subcarriers (e.g., using a multicarrier modulation (MCM) technique such as orthogonal frequency division multiplexing (OFDM) or discrete Fourier transform spread OFDM (DFT-S-OFDM)). In a system employing MCM techniques, a resource element may refer to the resource of one symbol period (e.g., the duration of one modulation symbol) and one subcarrier, in which case the symbol period and subcarrier spacing may be inversely related. The number of bits carried by each resource element may depend on the modulation scheme (e.g., the order of the modulation scheme, the coding rate of the modulation scheme, or both), such that a relatively high number of resource elements (e.g., in the transmission duration) and a relatively high order modulation scheme may correspond to a relatively high communication rate. Wireless communication resources may refer to a combination of RF spectrum resources, time resources, and spatial resources (e.g., spatial layers or beams), and the use of multiple spatial resources may increase the data rate or data integrity used for communication with UE 115.

[0067] The time interval for the network entity 105 or the UE 115 may be expressed as a multiple of a basic time unit, which may be, for example, a sampling period T s =1 / (Δf max ·N f ) seconds, where Δf max It can represent the supported subcarrier spacing, and N f The supported discrete Fourier transform (DFT) size may be indicated. Time intervals of communication resources may be organized according to radio frames, each having a specified duration (e.g., 10 milliseconds (ms)). Each radio frame may be identified by a system frame number (SFN) (e.g., in the range of 0 to 1023).

[0068] Each frame may include a plurality of consecutively numbered subframes or time slots, and each subframe or time slot may have the same duration. In some examples, a frame may be divided (e.g., in the time domain) into subframes, and each subframe may be further divided into a certain number of time slots. Alternatively, each frame may include a variable number of time slots, and the number of time slots may depend on the subcarrier spacing. Each time slot may include a certain number of symbol periods (e.g., depending on the length of the cyclic prefix appended in front of each symbol period). In some wireless communication systems 100, the time slot may be further divided into a plurality of mini-time slots associated with one or more symbols. Excluding the cyclic prefix, each symbol period may be associated with one or more (e.g., N f The duration of a symbol period may depend on the subcarrier spacing or the operating frequency band.

[0069] A subframe, slot, mini-slot, or symbol may be the smallest scheduling unit (e.g., in the time domain) of the wireless communication system 100 and may be referred to as a Transmit Time Interval (TTI). In some examples, the TTI duration (e.g., the number of symbol periods in a TTI) may be variable. Additionally or alternatively, the smallest scheduling unit of the wireless communication system 100 may be dynamically selected (e.g., in bursts of shortened TTIs (sTTIs)).

[0070] Physical channels may be multiplexed according to various techniques for communication using a carrier. For example, physical control channels and physical data channels may be multiplexed using one or more of time division multiplexing (TDM), frequency division multiplexing (FDM), or hybrid TDM-FDM techniques for signaling via a downlink carrier. A control region (e.g., a control resource set (CORESET)) of a physical control channel may be defined by a set of symbol periods and may extend across the system bandwidth of a carrier or a subset of that bandwidth. One or more control regions (e.g., CORESETs) may be configured for a set of UEs 115. For example, one or more of UEs 115 may monitor or search the control region for control information according to one or more search space sets, and each search space set may include one or more control channel candidates in one or more aggregation levels arranged in a cascaded manner. The aggregation level of a control channel candidate may refer to the amount of control channel resources (e.g., control channel elements (CCEs)) associated with coded information for a control information format having a given payload size. The search space sets may include a common search space set configured for transmitting control information to multiple UEs 115 and a UE-specific search space set for transmitting control information to a specific UE 115 .

[0071] In some examples, network entities 105 (e.g., base stations 140, RUs 170) can be mobile and, therefore, provide communication coverage for mobile coverage areas 110. In some examples, different coverage areas 110 associated with different technologies can overlap, but the different coverage areas 110 can be supported by the same network entity 105. In some other examples, overlapping coverage areas 110 associated with different technologies can be supported by different network entities 105. The wireless communication system 100 can include, for example, a heterogeneous network in which different types of network entities 105 provide coverage for various coverage areas 110 using the same or different radio access technologies.

[0072] The wireless communication system 100 can be configured to support ultra-reliable communication or low-latency communication or various combinations thereof. For example, the wireless communication system 100 can be configured to support ultra-reliable low-latency communication (URLLC). The UE 115 can be designed to support ultra-reliable or low-latency or critical functions. Ultra-reliable communication can include private communication or group communication and can be supported by one or more services (such as push-to-talk, video or data). Support for ultra-reliable, low-latency functions can include prioritization of services, and such services can be used for public safety or general commercial applications. The terms ultra-reliable, low-latency and ultra-reliable low-latency can be used interchangeably in this article.

[0073] In some examples, a UE 115 can be configured to support communication directly with other UEs 115 via a device-to-device (D2D) communication link 135 (e.g., according to a peer-to-peer (P2P), D2D, or sidelink protocol). In some examples, one or more UEs 115 in a group performing D2D communication can be within a coverage area 110 of a network entity 105 (e.g., a base station 140, a RU 170), which can support aspects of such D2D communication configured (e.g., scheduled) by the network entity 105. In some examples, one or more UEs 115 in such a group can be outside of the coverage area 110 of the network entity 105 or can otherwise be unable or not configured to receive transmissions from the network entity 105. In some examples, a group of UEs 115 communicating via D2D communication can support a one-to-many (1:M) system, in which each UE 115 transmits to each of the other UEs 115 in the group. In some examples, network entity 105 may facilitate scheduling of resources for D2D communications. In some other examples, D2D communications may be performed between UEs 115 without involving network entity 105.

[0074] The core network 130 may provide user authentication, access authorization, tracking, Internet Protocol (IP) connectivity, and other access, routing, or mobility functions. The core network 130 may be an evolved packet core (EPC) or a 5G core (5GC), which may include at least one control plane entity (e.g., a mobility management entity (MME), an access and mobility management function (AMF)) for managing access and mobility and at least one user plane entity (e.g., a serving gateway (S-GW), a packet data network (PDN) gateway (P-GW), or a user plane function (UPF)) for routing packets or interconnecting to external networks. The control plane entity may manage non-access stratum (NAS) functions such as mobility, authentication, and bearer management for UEs 115 served by network entities 105 (e.g., base stations 140) associated with the core network 130. User IP packets may be transferred through the user plane entity, which may provide IP address allocation and other functions. The user plane entity may be connected to the IP services 150 of one or more network operators. IP services 150 may include access to the Internet, an intranet, an IP Multimedia Subsystem (IMS), or packet-switched streaming services.

[0075] The wireless communication system 100 can operate using one or more frequency bands that can range from 300 megahertz (MHz) to 300 gigahertz (GHz). Generally speaking, the region from 300 MHz to 3 GHz is referred to as the ultra-high frequency (UHF) region or decimeter band because the wavelengths range from about one decimeter to one meter in length. UHF waves can be blocked or redirected by buildings and environmental features (which can be referred to as clusters), but these waves can penetrate structures sufficiently for a macro cell to provide service to a UE 115 located indoors. Communication using UHF waves can be associated with smaller antennas and a shorter range (e.g., less than 100 kilometers) than communication using the smaller frequencies and longer wavelengths of the high frequency (HF) or very high frequency (VHF) portions of the spectrum below 300 MHz.

[0076] The wireless communication system 100 can utilize both licensed and unlicensed RF spectrum bands. For example, the wireless communication system 100 can use unlicensed bands (such as the 5 GHz Industrial, Scientific, and Medical (ISM) band) to employ license-assisted access (LAA), LTE-unlicensed (LTE-U) radio access technology, or NR technology. When operating using unlicensed RF spectrum bands, devices such as the network entity 105 and the UE 115 can employ carrier sensing for conflict detection and avoidance. In some examples, operations using unlicensed bands can be based on a carrier aggregation configuration (e.g., LAA) in conjunction with component carriers operating using licensed bands. Operations using the unlicensed spectrum can include downlink transmissions, uplink transmissions, P2P transmissions, or D2D transmissions, among others.

[0077] A network entity 105 (e.g., a base station 140, a RU 170) or a UE 115 may be equipped with multiple antennas that can be used to employ techniques such as transmit diversity, receive diversity, multiple-input, multiple-output (MIMO) communications, or beamforming. The antennas of the network entity 105 or UE 115 may be located within one or more antenna arrays or antenna panels, which may support MIMO operations or transmit or receive beamforming. For example, one or more base station antennas or antenna arrays may be co-located at an antenna assembly, such as an antenna tower. In some examples, the antennas or antenna arrays associated with the network entity 105 may be located at different geographical locations. The network entity 105 may include an antenna array having a set of multiple rows and columns of antenna ports that the network entity 105 may use to support beamforming for communications with the UE 115. Similarly, the UE 115 may include one or more antenna arrays that may support various MIMO or beamforming operations. Additionally or alternatively, the antenna panels may support RF beamforming for signals transmitted via the antenna ports.

[0078] Beamforming (which may also be referred to as spatial filtering, directional transmission, or directional reception) is a signal processing technique that can be used at a transmitting device or a receiving device (e.g., a network entity 105, a UE 115) to shape or steer an antenna beam (e.g., a transmit beam, a receive beam) along a spatial path between the transmitting device and the receiving device. Beamforming can be achieved by combining signals communicated via antenna elements of an antenna array so that some signals propagating in a particular direction relative to the antenna array experience constructive interference, while other signals experience destructive interference. Adjustments to signals communicated via antenna elements can include the transmitting device or the receiving device applying an amplitude offset, a phase offset, or both to signals carried via antenna elements associated with the device. The adjustments associated with each of these antenna elements can be defined by a set of beamforming weights associated with a particular direction (e.g., relative to the antenna array of the transmitting device or the receiving device or relative to some other direction).

[0079] Existing wireless communication systems (such as cellular communication systems and Wi-Fi communication systems) may use higher-order modulation schemes (e.g., QAM) to improve spectral efficiency at high SNR values. In such existing systems, the constellation points of the modulation scheme may be fixed, and each constellation point of the modulation scheme may be used with equal probability (e.g., a wireless communication device may have equal probability of selecting the first constellation point and the second constellation point of the modulation scheme). Probabilistic shaping is a technique for generating non-uniformly distributed constellation points for a modulation scheme, and probabilistic shaping may improve spectral efficiency. One technique for probabilistic shaping may be PAS, which shapes the amplitudes of constellation points while uniformly distributing the signs of the constellation points. Techniques for PAS may include compression-based schemes and channel coding-based shaping schemes. For probabilistic shaping, a wireless communication device (e.g., UE 115 or network entity 105) may send a probabilistically shaped message that conforms to a target probability distribution. If the probabilistically shaped message does not conform to the target probability distribution, another wireless communication device (e.g., UE 115 or network entity 105) may not be able to correctly receive and decode the probabilistically shaped message.

[0080] A wireless communication device (e.g., UE 115 or network entity 105) may meet a transmit signal quality requirement that an empirical probability distribution of a probabilistically shaped message is close to a target probability distribution (e.g., meets a threshold). The wireless communication device (e.g., UE 115 or network entity 105) may probabilistically shape information bits to generate a set of shaped bits and modulate the set of shaped bits to generate a set of modulated symbols. The empirical probability distribution of the probabilistically shaped message may be determined based on the respective amplitudes of the set of shaped bits or the set of modulated symbols. The empirical probability distribution may be measured across transmissions of one or more probabilistically shaped messages within a target duration.

[0081] A distribution proximity metric that is compared to a threshold value can be used to measure the proximity of the empirical probability distribution to the target probability distribution. The distribution proximity metric quantifies the difference between the empirical probability distribution and the target probability distribution. For example, the distribution proximity metric can be a Kullback-Leibler divergence score, entropy difference, total variation distance, Hellinger distance, or statistical distance. As another example, the distribution proximity metric can quantify the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution. In some examples, the threshold value can be defined based on parameters of the probabilistically shaped message. For example, the threshold value can be defined based on the number of modulation symbols in the shaped block, the number of bits in the shaped block, the shaping rate, or the modulation order.

[0082] Figure 2An example of a wireless communication system 200 that supports transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure is illustrated. In some examples, the wireless communication system 200 can implement aspects of the wireless communication system 100. The wireless communication system 200 can include a first wireless communication device 215, a second wireless communication device 220, and a third wireless communication device 205. In some examples, the first wireless communication device 215 and the second wireless communication device 220 can be UEs 115 as described herein. The third wireless communication device 205 can be a network entity 105 as described herein. In some examples, the second wireless communication device 220 can be a test device that determines whether a probabilistically shaped message meets signal quality requirements.

[0083] In some examples, the first wireless communication device 215 can communicate with the third wireless communication device 205a via the communication link 125-a, and the first wireless communication device 215 can communicate with the second wireless communication device 220 via the communication link 135-a. The communication link 125-a can be a reference Figure 1 Examples of the communication link 125 described, and the communication link 135-a may be referenced Figure 1 Examples of communication links 135 described herein. Communication link 125-a may include a bidirectional link that enables both uplink and downlink communication. For example, first wireless communication device 215 may use communication link 125-a to send uplink signals (e.g., uplink transmissions), such as uplink control signals or uplink data signals, to third wireless communication device 205, and third wireless communication device 205 may use communication link 125-a to send downlink signals (e.g., downlink transmissions), such as downlink control signals or downlink data signals, to first wireless communication device 215. In some examples, communication link 135-a may include a bidirectional link that enables sidelink communication. As another example, first wireless communication device 215 may use communication link 135-a to send sidelink signals, such as sidelink control signals or sidelink data signals, to second wireless communication device 220.

[0084] For example, the first wireless communication device 215 may communicate a message 210-b, such as a data transmission, with the second wireless communication device 220a via the communication link 135-a, and the first wireless communication device 215 may communicate a message 210-a, such as a data transmission, with the third wireless communication device 205 via the communication link 135-a. In some examples, the messages 210-a and 210-b may be probabilistically shaped messages.

[0085] In existing wireless communication systems (such as cellular and Wi-Fi), higher-order modulation schemes (e.g., 16QAM, 64QAM, and 256QAM) can be used to improve spectral efficiency at high SNR values. In such existing systems, the constellation points of the modulation scheme can be fixed (e.g., in a square constellation), and each constellation point can be used with equal probability (e.g., a wireless communication device can have equal probability of selecting a first constellation point and a second constellation point). Probability shaping can be a technique for generating non-uniformly distributed constellation points, and probability shaping can improve the spectral efficiency of coded modulation. For example, non-uniformly distributed QAM can achieve higher capacity than uniformly distributed QAM.

[0086] One technique for probability shaping can be PAS, which shapes the amplitudes of constellation points non-uniformly while uniformly distributing the signs of the constellation points. Techniques for PAS can include compression-based schemes (e.g., constant component distribution matching (CCDM), compression based on Huffman decoding or arithmetic decoding) and shaping schemes based on channel coding, such as reusing the decoder used for the channel code to generate a target probability distribution for a probability-shaped transmission generated using a specific modulation scheme. For probability shaping, the goal can be to generate non-uniformly distributed constellations for the modulation scheme that can achieve greater mutual information than uniformly distributed constellations at the same SNR. In some examples, the probability shaper can also be referred to as a distribution matcher. The distribution matcher can use inverse lossless source decoding (e.g., inverse arithmetic decoding or Huffman decoding) to encode an information payload of a uniform set of bits into a larger payload of non-uniform bits.

[0087] In some examples, a method for PAS can be based on source compression technology, such as arithmetic decoding and Huffman decoding. For source compression technology, source decoding can convert a non-uniformly distributed source into uniform bits, which can be the inverse process of probability shaping. Some example source compression technologies may include CCDM, multi-component distribution matching and sphere shaping. For sphere shaping, the input codeword (e.g., a multidimensional complex vector) can be constrained to a power sphere. In some examples, in order to use PAS based on source compression technology for messages 210-a and 210-b, a technology for compressing information into bits in a bit-accurate manner can be specified. For example, a compression algorithm that reaches a fixed point by quantizing probability values ​​to a given precision can be specified. For wireless communication systems, algorithms for many different configurations can be specified in terms of shaping rate, target probability distribution, block length, and modulation order. In addition, the source code can be nonlinear and may be difficult to design in conjunction with forward error correction. In some examples, new hardware and software can be used to achieve high-speed compression and decompression.

[0088] Figure 3An example of a channel decoding-based shaping technique diagram 300 that supports transmit signal quality of a probabilistically shaped message according to one or more aspects of the present disclosure is illustrated. Channel decoding-based shaping techniques may be another approach for PAS. In some examples, Figure 3 The channel decoding-based shaping techniques exemplified in Figure 1 and Figure 2 The wireless communication system 100 and the wireless communication system 200 described in the accompanying drawings are conveyed.

[0089] In some examples, the shaping technique based on channel decoding can be based on block codes and bit masks. The channel-based shaping technique can be used to perform probability shaping on a set of u information bits 305 according to a target probability distribution to generate a set of u+v shaped bits 310. In some examples, a mask bit generator 320 can be used to generate v mask bits 315 to provide u+v shaped bits 310 (bits after masking) with a target probability distribution. The v mask bits 315 can be a codeword of a block code generated from a generator matrix G of the block code. In some examples, the v mask bits 315 can be based on the product of s shaper bits 325 and the generator matrix G (e.g., v=s*G). In another example, the matcher can directly generate a shaped bit set from the information bit set to achieve the target probability distribution without using a mask. For these examples, a decoder for a block code can be used to generate the shaped bit set.

[0090] For PAS using channel coding-based shaping techniques, different wireless communication devices may implement different channel coding-based shaping algorithms or may use different source coding algorithms using a common code (e.g., linear code or polar code). Different channel coding-based shaping algorithms may be implemented by different wireless communication devices, similar to how different wireless communication devices may implement different channel decoders. In addition, different channel coding-based shaping algorithms may reuse existing polar codes and existing encoder or decoder hardware to perform probability shaping.

[0091] In wireless communication systems (such as wireless communication systems 100 and 200), wireless communication devices (e.g., first wireless communication device 215, second wireless communication device 220, and third wireless communication device 205) may meet transmit signal quality requirements. For example, a standard may impose various requirements on waveforms, signals, or messages (such as radio frequency portions) transmitted by first wireless communication device 215, second wireless communication device 220, and third wireless communication device 205. Some example requirements may include frequency error, error vector magnitude (EVM), and transmission requirements. The first wireless communication device 215, second wireless communication device 220, and third wireless communication device 205 may be expected to meet the transmit signal quality requirements in order to reliably communicate with other wireless communication devices.

[0092] refer to Figure 2 For the probabilistically shaped message 210-a and the probabilistically shaped message 210-b, different wireless communication devices (e.g., the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205) may implement different probabilistic shaping techniques. For example, different wireless communication devices (e.g., the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205) may use different decoders for channel decoding-based shaping. Accordingly, the wireless communication devices (e.g., the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205) may be expected to meet the transmission quality requirements for the probabilistically shaped messages or signals. If the wireless communication devices (e.g., the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205) do not send probabilistically shaped messages that conform to the target probability distribution, the receiving wireless communication device may not be able to correctly receive and decode the shaped messages.

[0093] In some examples, a transmit signal quality of a probabilistically shaped message may be defined, and the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205 may transmit a probabilistically shaped message that meets the expected quality. x The wireless communication devices (e.g., the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205) may send a message with a near-target probability distribution Q of the modulated symbols or shaped bits. x The empirical probability distribution P x A probabilistically shaped message of bits or modulation symbols.

[0094] Empirical probability distribution P x It can be a probability mass function defined as follows

[0095]

[0096] Where S represents the constellation set of modulation and x represents a modulation symbol in the set of modulation symbols S. The empirical probability distribution P can be measured across one or more transmissions of n modulation symbols. x (x). For example, an empirical probability distribution P may be measured across one or more transmissions of one or more probabilistically shaped messages within a target duration. x (x). The value of n may be determined by the duration over which the distribution is measured (e.g., 1 slot, 1 ms, 10 ms). A target probability distribution Q may be defined over the same set of modulation symbols. x (x). In another example, the empirical probability distribution P can be measured on the magnitude of the symbol (such as on |x|). x (x). In another example, the empirical probability distribution P may be measured over a set of shaped or coded bits. x (x); A distance metric may similarly be defined on shaped bit sets (eg, on the joint distribution of b0, b1, b2, ...).

[0097] In some examples, a distribution proximity metric can be used to quantify how close the empirical probability distribution is to a target probability distribution. The distribution proximity metric can indicate the quality of the transmitted signal. In one example, the distribution proximity metric quantifies the difference between the empirical probability distribution and the target probability distribution.

[0098] In one example, the distribution closeness measure can be the Kullback-Leibler (KL) divergence score. The KL divergence can be defined as KL divergence measures the closeness between two distributions in terms of entropy or information. The closer the empirical probability distribution is to the KL divergence, the better the match between the empirical probability distribution and the target probability distribution in terms of information capacity. KL divergence can be expected when P x When (x) = 0, then Q x (x)=0, and vice versa.

[0099] In another example, the distribution closeness metric may be the entropy difference, which may be defined as H(P X )-H(Q X ), where H(P X )=∑ x∈S -P X (x)log P X (x) and H(Q X )=∑ x∈S -Q X (x)log Q X (x). H(P X ) represents the entropy of the empirical probability distribution, and H(Q X) represents the entropy of the target probability distribution.

[0100] In another example, the distribution closeness measure may be the total variation distance, which may be defined as

[0101] In another example, the distribution closeness metric may be the Hellinger distance, which may be defined as

[0102] In another example, the distribution closeness measure may be a statistical distance (eg, chi-square distance), which may be defined as χ 2 (P X ,Q X )=∑ x∈S Q X (x)(P X (x) / Q X (x)-1) 2 The distribution closeness measures described are example distance measures or distribution closeness measures, and other measures or metrics may be possible.

[0103] In another example, the distribution closeness metric may quantify the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution. For example, the distribution closeness metric may be the ratio of the power scaling factors ξ(P X ) / ξ(Q X ), where ξ(P X ) means that the following power equation ξ·∑ x∈S |x| 2 P X (x) = 1 parameter ξ, and where ξ(Q X ) means that the following power equation ξ·∑ x∈S |x| 2 Q X In addition to power scaling or second-order moments, the distribution closeness measure can also be one of the high-order moments of the transmitted shaped message relative to the target distribution (e.g., In some cases, one or more of the distance metrics discussed herein may be used to determine transmitted signal quality.

[0104] In some examples, the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205 may transmit a shaped message, and a distributional proximity metric between the empirical probability distribution of the shaped message and a target probability distribution may satisfy a threshold. The first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205 may be expected to meet a transmit signal quality requirement defined by the distributional proximity metric between the empirical probability distribution and the target probability distribution in order to reliably communicate with other wireless communication devices. For examples where the distributional proximity metric is KL divergence, entropy difference, total variation distance, Hellinger distance, and statistical distance, the threshold may be a real number. For example, the distributional proximity metric may satisfy the threshold by being less than the threshold. In some examples, each distributional proximity metric may have an associated target threshold. For example, the KL divergence may have an associated threshold, the entropy distance may have an associated threshold, the total variation distance may have an associated threshold, the Hellinger distance may have an associated threshold, and the statistical distance may have an associated threshold.

[0105] For an example where the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution, the threshold value may be a decibel (dB) number. For example, the distribution closeness metric may satisfy the threshold value by being less than a threshold dB number. For example, the ratio between the power (second-order moment) or higher-order moment of the target distribution and the transmitted signal distribution (empirical distribution) may be less than X dB (e.g., X = 0.5, 1 dB), as given by For examples where the distribution closeness measure quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution, the threshold value may be a percentage. For example, the relative difference in power or higher-order moments measured in percentiles may be less than X%, as given by defined.

[0106] In some examples, the threshold value may be based on parameters of the probabilistically shaped message. For example, different target threshold values ​​may be defined for the same distribution proximity metric depending on the parameters of the probabilistically shaped message. In some examples, the parameters may be one or more of the number of modulation symbols in a shaped block, the number of bits in a shaped block, the shaping rate, the modulation order, or any combination thereof. In some examples, the parameters may be the modulation order, a shaping parameter (e.g., the shaping rate), or any combination thereof. For example, the threshold value may be adjusted based on the number of modulation symbols in a shaped block or the number of bits in a shaped block. The larger the number of symbols or bits in a shaped block, the closer the empirical distribution may be to the target distribution, and thus the smaller the threshold value may be. In some examples, a set of information bits may be processed by multiple shaper blocks, in which case the parameter may be the number of symbols generated or received for a single shaped block.

[0107] In some examples, a wireless communication device (e.g., the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205) may determine whether a distribution proximity metric between an empirical probability distribution of a probabilistically shaped message and a target probability distribution satisfies a threshold. For example, the wireless communication device (e.g., the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205) may determine whether the distribution proximity metric satisfies the threshold at least once (such as after startup, periodically, or occasionally). In some examples, the wireless communication device (e.g., the first wireless communication device 215, the second wireless communication device 220, and the third wireless communication device 205) may receive signaling indicating a request to determine whether the distribution proximity metric satisfies the threshold. In another example, the wireless communication device may receive signaling indicating a distribution proximity metric, a threshold, a target probability distribution, or a combination thereof.

[0108] In some examples, the second wireless communication device 220 may be a test device that evaluates whether a distribution proximity metric between an empirical probability distribution of a received probabilistically shaped message and a target probability distribution satisfies a threshold. The second wireless communication device 220 may output a signal indicating whether the distribution proximity metric satisfies the threshold. In some examples, the first wireless communication device 215 may receive the signal from the second wireless communication device 220. Additionally, the first wireless communication device 215 may adjust the probabilistically shaped message so that the distribution proximity metric satisfies the threshold.

[0109] In some examples, a maximum power reduction (MPR) or additional MPR may define a maximum power reduction that a wireless communication device (e.g., first wireless communication device 215, second wireless communication device 220, and third wireless communication device 205) may perform to meet one or more transmission conditions (e.g., transmission requirements). For example, different modulation orders (e.g., quadrature phase shift keying (QPSK), 16QAM, 64QAM, 256QAM) may have different MPRs, e.g., 256QAM may have a higher MPR than 64QAM. One defining factor for different MPRs may be the peak-to-average power ratio (PAPR) of the waveform. In some examples, a wireless communication device (e.g., first wireless communication device 215, second wireless communication device 220, and third wireless communication device 205) may transmit a shaped message using an MPR that is different from the MPR associated with uniform QAM. A shaped message may have a different PAPR than uniform QAM. Thus, the MPR for a shaped message may be different from the MPR for a uniform QAM message.

[0110] In some examples, wireless communication devices (e.g., first wireless communication device 215, second wireless communication device 220, and third wireless communication device 205) can transmit shaped messages using an EVM that is different from the EVM associated with a uniform QAM message. For example, at the same modulation order, an EVM target level can be defined for the shaped message that is different from the EVM target level for the uniform QAM message (e.g., the EVM requirements for the shaped message can be more relaxed than the EVM requirements for the uniform QAM message).

[0111] In some examples, the EVM measurement for uniform QAM can be tested as X is the measured signal and X' is the reference. For probabilistically shaped systems, the EVM analyzer may not be able to determine the modulated data from the transmitter before decoding the data because the transmitter may choose the shaping bits or shaping method to generate the desired target probability distribution. In some examples, the EVM can be calculated by decoding the data from the channel code, reconstructing the ideal data demodulation symbol i(v) from the decoded data, and comparing the EVM between the equalized waveform z'(v) and the ideal data demodulation symbol i(v) as to measure the EVM for a probabilistically shaped message, where P0 = n -1 ∑ v＝0,...,n-1 |i(v)| 2 is the average power of the ideal or reference signal, and n represents the number of data symbols.

[0112] Figure 4 An example of a process flow 400 for supporting transmit signal quality of a probabilistically shaped message according to one or more aspects of the present disclosure is illustrated. The process flow 400 may include a first wireless communication device 215-a and a second wireless communication device 220-a, which may be devices described herein. Figure 2 The following description of the process flow 400 illustrates an example of a first wireless communication device 215 and a second wireless communication device 220. In the following description of the process flow 400, operations between the first wireless communication device 215-a and the second wireless communication device 220-a may be performed in a different order than the example order shown, or operations performed by the first wireless communication device 215-a and the second wireless communication device 220-a may be performed in a different order or at different times. Some operations may also be omitted from the process flow 400, and other operations may be added to the process flow 400.

[0113] At 420 , the first wireless communication device 215 - a may perform probability shaping on the set of information bits according to a target probability distribution to generate a shaped set of bits.

[0114] At 425, the first wireless communication device 215-a may send a shaped message generated based on the shaped set of bits to the second wireless communication device 220-a. In some examples, a distribution closeness metric between the empirical probability distribution and the target probability distribution of the shaped message may satisfy a threshold.

[0115] In some examples, the empirical probability distribution may be an empirical probability distribution of the shaped set of bits.In some examples, the first wireless communication device 215-a may measure the empirical probability distribution across transmissions of one or more shaped messages within a target duration.

[0116] In some examples, the first wireless communication device 215-a may modulate the shaped set of bits to generate a set of modulated symbols.The empirical probability distribution may be an empirical probability distribution of respective amplitudes of the set of modulated symbols.

[0117] In some examples, a distributional closeness metric may quantify the difference between the empirical probability distribution and the target probability distribution. The distributional closeness metric may be a Kullback-Leibler divergence score, entropy difference, total variation distance, Hellinger distance, or statistical distance. In some examples, the distributional closeness metric may quantify the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

[0118] In some examples, the first wireless communication device 215-a may determine the threshold based on a parameter of the shaped message. The parameter may be the number of modulation symbols in a shaped block, the number of bits in a shaped block, the shaping rate, the modulation order, or a combination thereof.

[0119] In some examples, the first wireless communication device 215-a may send the shaped message according to a first MPR associated with the shaped message.The first MPR associated with the shaped message may be different from a second MPR associated with uniform QAM.

[0120] In some examples, the first wireless communication device 215-a may send the shaped message according to a first EVM associated with the shaped message.The first EVM associated with the shaped message may be different from a second EVM associated with uniform QAM.

[0121] In some examples, the first wireless communication device 215-a may decode the shaped set of bits and may reconstruct the demodulated symbols based in part on the decoded shaped set of bits. The first wireless communication device 215-a may measure the EVM associated with the shaped message based in part on the equalized probability shaped transmit waveform and the demodulated symbols.

[0122] In some examples, the first wireless communication device 215-a may receive signaling indicating a distribution closeness metric.The first wireless communication device 215-a may receive signaling indicating a target probability distribution.

[0123] In some examples, the second wireless communication device 220-a may receive a shaped message from the first wireless communication device 215-a. At 430, the second wireless communication device 220-a may output a signal indicating whether a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution of the shaped message meets a threshold.

[0124] In some examples, the second wireless communication device 220-a may demodulate the shaped set of bits from the shaped message.The empirical probability distribution may be an empirical probability distribution of the shaped set of bits.

[0125] In some examples, the second wireless communication device 220-a may measure an empirical probability distribution across transmissions of one or more shaped messages within a target duration. The empirical probability distribution may be an empirical probability distribution of respective amplitudes of a set of modulated symbols of the shaped message.

[0126] In some examples, the second wireless communication device 220-a may determine the threshold based on a parameter of the shaped message. The parameter may be the number of modulation symbols in a shaped block, the number of bits in a shaped block, the shaping rate, the modulation order, or a combination thereof.

[0127] In some examples, the second wireless communication device 220-a may receive signaling indicating a distribution closeness metric.The second wireless communication device 220-a may receive signaling indicating a target probability distribution.

[0128] Figure 5 A block diagram 500 illustrates a device 505 that supports transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure. The device 505 can be an example of aspects of the network entity 105 as described herein. The device 505 can include a receiver 510, a transmitter 515, and a communication manager 520. The device 505 can also include a processor. Each of these components can communicate with each other (e.g., via one or more buses).

[0129] Receiver 510 may provide means for obtaining (e.g., receiving, determining, identifying) information associated with various channels (e.g., control channels, data channels, information channels, channels associated with a protocol stack), such as user data, control information, or any combination thereof (e.g., I / Q samples, symbols, packets, protocol data units, service data units). The information may be passed to other components of device 505. In some examples, receiver 510 may support obtaining information by receiving signals via one or more antennas. Additionally or alternatively, receiver 510 may support obtaining information by receiving signals via one or more wired (e.g., electrical, optical) interfaces, wireless interfaces, or any combination thereof.

[0130] The transmitter 515 may provide means for outputting (e.g., transmitting, providing, conveying, transmitting) information generated by other components of the device 505. For example, the transmitter 515 may output information associated with various channels (e.g., control channels, data channels, information channels, channels associated with a protocol stack), such as user data, control information, or any combination thereof (e.g., I / Q samples, symbols, packets, protocol data units, service data units). In some examples, the transmitter 515 may support outputting information by transmitting signals via one or more antennas. Additionally or alternatively, the transmitter 515 may support outputting information by transmitting signals via one or more wired (e.g., electrical, optical) interfaces, wireless interfaces, or any combination thereof. In some examples, the transmitter 515 and the receiver 510 may be co-located in a transceiver, which may include a modem or be coupled to a modem.

[0131] The communication manager 520, the receiver 510, the transmitter 515, or various combinations thereof, or various components thereof, may be examples of means for performing various aspects of transmit signal quality of probabilistically shaped messages as described herein. For example, the communication manager 520, the receiver 510, the transmitter 515, or various combinations thereof, or components thereof, may support methods for performing one or more of the functions described herein.

[0132] In some examples, the communication manager 520, the receiver 510, the transmitter 515, or various combinations or components thereof can be implemented in hardware (e.g., in a communication management circuit). The hardware can include a processor, a DSP, a CPU, an ASIC, an FPGA or other programmable logic device, a microcontroller, discrete gate or transistor logic components, discrete hardware components, or any combination thereof configured as or otherwise supporting components for performing the functions described in this disclosure. In some examples, the processor and a memory coupled to the processor can be configured to perform one or more of the functions described herein (e.g., by executing instructions stored in the memory by the processor).

[0133] Additionally or alternatively, in some examples, the communication manager 520, receiver 510, transmitter 515, or various combinations or components thereof may be implemented in code executed by a processor (e.g., as communication management software or firmware). If implemented in code executed by a processor, the functionality of the communication manager 520, receiver 510, transmitter 515, or various combinations or components thereof may be performed by a general-purpose processor (e.g., configured as or otherwise supporting means for performing the functions described in this disclosure), a DSP, a CPU, an ASIC, an FPGA, a microcontroller, or any combination of these or other programmable logic devices.

[0134] In some examples, communication manager 520 can be configured to perform various operations (e.g., receive, obtain, monitor, output, transmit) using or otherwise cooperating with receiver 510, transmitter 515, or both. For example, communication manager 520 can receive information from receiver 510, transmit information to transmitter 515, or be integrated with receiver 510, transmitter 515, or both to obtain information, output information, or perform various other operations as described herein.

[0135] The communication manager 520 can support wireless communications at a first wireless communication device according to examples as disclosed herein. For example, the communication manager 520 can be configured to or otherwise support components for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits. The communication manager 520 can be configured to or otherwise support components for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0136] By including or configuring a communication manager 520 according to examples as described herein, the device 505 (e.g., a processor controlling or otherwise coupled with the receiver 510, the transmitter 515, the communication manager 520, or a combination thereof) can support techniques for more efficiently utilizing communication resources.

[0137] Figure 6 A block diagram 600 illustrates a device 605 that supports transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure. The device 605 can be an example of aspects of the device 505 or the network entity 105 as described herein. The device 605 can include a receiver 610, a transmitter 615, and a communication manager 620. The device 605 can also include a processor. Each of these components can communicate with each other (e.g., via one or more buses).

[0138] Receiver 610 may provide means for obtaining (e.g., receiving, determining, identifying) information associated with various channels (e.g., control channels, data channels, information channels, channels associated with a protocol stack), such as user data, control information, or any combination thereof (e.g., I / Q samples, symbols, packets, protocol data units, service data units). The information may be passed to other components of device 605. In some examples, receiver 610 may support obtaining information by receiving signals via one or more antennas. Additionally or alternatively, receiver 610 may support obtaining information by receiving signals via one or more wired (e.g., electrical, optical) interfaces, wireless interfaces, or any combination thereof.

[0139] The transmitter 615 may provide means for outputting (e.g., transmitting, providing, conveying, transmitting) information generated by other components of the device 605. For example, the transmitter 615 may output information associated with various channels (e.g., control channels, data channels, information channels, channels associated with a protocol stack), such as user data, control information, or any combination thereof (e.g., I / Q samples, symbols, packets, protocol data units, service data units). In some examples, the transmitter 615 may support outputting information by transmitting signals via one or more antennas. Additionally or alternatively, the transmitter 615 may support outputting information by transmitting signals via one or more wired (e.g., electrical, optical) interfaces, wireless interfaces, or any combination thereof. In some examples, the transmitter 615 and the receiver 610 may be co-located in a transceiver, which may include a modem or be coupled to a modem.

[0140] Device 605 or its various components can be examples of components for performing various aspects of transmit signal quality of probabilistically shaped messages as described herein. For example, communication manager 620 may include probabilistic shaping manager 625, shaped message manager 630, or any combination thereof. Communication manager 620 can be an example of various aspects of communication manager 520 as described herein. In some examples, communication manager 620 or its various components can be configured to use receiver 610, transmitter 615, or both or otherwise collaborate with them to perform various operations (e.g., receive, obtain, monitor, output, transmit). For example, communication manager 620 can receive information from receiver 610, transmit information to transmitter 615, or be integrated with receiver 610, transmitter 615, or both to obtain information, output information, or perform various other operations as described herein.

[0141] The communication manager 620 may support wireless communications at a first wireless communication device according to examples as disclosed herein. The probability shaping manager 625 may be configured to or otherwise support means for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits. The shaped message manager 630 may be configured to or otherwise support means for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0142] Figure 7 Block diagram 700 illustrates a communication manager 720 that supports transmit signal quality of probabilistically shaped messages in accordance with one or more aspects of the present disclosure. Communication manager 720 may be an example of communication manager 520, communication manager 620, or aspects of both as described herein. Communication manager 720 or its various components may be examples of means for performing various aspects of transmit signal quality of probabilistically shaped messages as described herein. For example, communication manager 720 may include a probability shaping manager 725, a shaped message manager 730, an empirical probability distribution manager 735, a modulation manager 740, a threshold manager 745, a maximum power reduction manager 750, an error vector magnitude manager 755, a distribution proximity metric manager 760, a target probability distribution manager 765, or any combination thereof. Each of these components may communicate directly or indirectly with each other (e.g., via one or more buses), which communication may include communication within a protocol layer of a protocol stack, communication associated with a logical channel of a protocol stack (e.g., between protocol layers of a protocol stack, within a device, component, or virtualized component associated with the network entity 105, between devices, components, or virtualized components associated with the network entity 105), or any combination thereof.

[0143] The communication manager 720 may support wireless communications at a first wireless communication device according to examples as disclosed herein. The probability shaping manager 725 may be configured to or otherwise support means for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits. The shaped message manager 730 may be configured to or otherwise support means for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0144] In some examples, the empirical probability distribution is an empirical probability distribution of a shaped set of bits.

[0145] In some examples, empirical probability distribution manager 735 may be configured or otherwise support components for measuring an empirical probability distribution across the transmission of one or more shaped messages within a target duration.

[0146] In some examples, modulation manager 740 may be configured or otherwise support means for modulating a set of shaped bits to generate a set of modulated symbols, where the empirical probability distribution is an empirical probability distribution of respective amplitudes of the set of modulated symbols.

[0147] In some examples, a distribution closeness metric quantifies the difference between an empirical probability distribution and a target probability distribution.

[0148] In some examples, the distribution closeness measure is a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

[0149] In some examples, the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

[0150] In some examples, threshold manager 745 may be configured or otherwise support components for determining thresholds based on parameters of a shaped message.

[0151] In some examples, the parameter is the number of modulation symbols in a shaped block, the number of bits in a shaped block, the shaping rate, the modulation order, or a combination thereof.

[0152] In some examples, to support sending shaped messages, maximum power reduction manager 750 may be configured or otherwise support components for sending shaped messages according to a first MPR associated with the shaped message that is different from a second MPR associated with uniform QAM.

[0153] In some examples, the error vector magnitude manager 755 can be configured or otherwise support means for sending a shaped message according to a first EVM associated with the shaped message that is different from a second EVM associated with uniform QAM.

[0154] In some examples, the error vector magnitude manager 755 can be configured to or otherwise support means for decoding a shaped set of bits. In some examples, the empirical probability distribution manager 735 can be configured to or otherwise support means for reconstructing demodulated symbols based in part on the decoded shaped set of bits. In some examples, the empirical probability distribution manager 735 can be configured to or otherwise support means for measuring an EVM associated with a shaped message based in part on the equalized probability shaped transmit waveform and the demodulated symbols.

[0155] In some examples, distribution proximity metric manager 760 may be configured or otherwise support components for receiving signaling indicative of a distribution proximity metric.

[0156] In some examples, target probability distribution manager 765 may be configured or otherwise support components for receiving signaling indicating a target probability distribution.

[0157] Figure 8 A diagram of a system 800 including a device 805 supporting transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure is illustrated. The device 805 may be an example of a device 505, a device 605, or a network entity 105 as described herein, or may include components of such devices. The device 805 may communicate with one or more network entities 105, one or more UEs 115, or any combination thereof, which communication may include communication via one or more wired interfaces, via one or more wireless interfaces, or any combination thereof. The device 805 may include components that support output and acquisition of communications, such as a communication manager 820, a transceiver 810, an antenna 815, a memory 825, code 830, and a processor 835. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more buses (e.g., a bus 840).

[0158] The transceiver 810 may support bidirectional communication via a wired link, a wireless link, or both as described herein. In some examples, the transceiver 810 may include a wired transceiver and may communicate bidirectionally with another wired transceiver. Additionally or alternatively, in some examples, the transceiver 810 may include a wireless transceiver and may communicate bidirectionally with another wireless transceiver. In some examples, the device 805 may include one or more antennas 815 that may be capable of transmitting or receiving wireless transmissions (e.g., concurrently). The transceiver 810 may also include a modem that is configured to: modulate a signal; provide the modulated signal for transmission (e.g., via one or more antennas 815, via a wired transmitter); receive the modulated signal (e.g., from one or more antennas 815, from a wired receiver); and demodulate the signal. In some implementations, the transceiver 810 may include one or more interfaces, such as one or more interfaces coupled to one or more antennas 815 configured to support various receive or obtain operations, or one or more interfaces coupled to one or more antennas 815 configured to support various transmit or output operations, or a combination thereof. In some implementations, the transceiver 810 may include or be configured to be coupled to one or more processors or memory components operable to perform or support operations based on received or obtained information or signals, or to generate information or other signals for transmission or other output, or any combination thereof. In some implementations, the transceiver 810, or the transceiver 810 and one or more antennas 815, or the transceiver 810 and one or more antennas 815 and one or more processors or memory components (e.g., processor 835 or memory 825 or both) may be included in a chip or chip assembly installed in the device 805. In some examples, the transceiver may be operable to support communications via one or more communication links (eg, communication link 125 , backhaul communication link 120 , midhaul communication link 162 , fronthaul communication link 168 ).

[0159] The memory 825 may include RAM and ROM. The memory 825 may store computer-readable, computer-executable code 830 including instructions that, when executed by the processor 835, cause the device 805 to perform the various functions described herein. The code 830 may be stored in a non-transitory computer-readable medium (such as system memory or another type of memory). In some cases, the code 830 may not be directly executable by the processor 835, but may (e.g., when compiled and executed) cause the computer to perform the functions described herein. In some cases, the memory 825 may contain a BIOS, etc., which may control basic hardware or software operations, such as interaction with peripheral components or devices.

[0160] The processor 835 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, an ASIC, a CPU, an FPGA, a microcontroller, a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof). In some cases, the processor 835 may be configured to operate a memory array using a memory controller. In some other cases, the memory controller may be integrated into the processor 835. The processor 835 may be configured to execute computer-readable instructions stored in a memory (e.g., memory 825) to cause the device 805 to perform various functions (e.g., functions or tasks that support the quality of transmitted signals of probabilistically shaped messages). For example, the device 805 or a component of the device 805 may include a processor 835 and a memory 825 coupled to the processor 835, the processor 835 and the memory 825 being configured to perform the various functions described herein. The processor 835 may be an example of a cloud computing platform (e.g., one or more physical nodes and supporting software (such as an operating system, a virtual machine, or a container example)) that may host functions (e.g., by executing code 830) to perform the functions of the device 805. The processor 835 can be any one or more suitable processors capable of executing scripts or instructions of one or more software programs stored in the device 805 (such as in the memory 825). In some specific implementations, the processor 835 can be a component of a processing system. A processing system generally refers to a system or a series of machines or components that receives inputs and processes these inputs to produce a set of outputs (which can be passed to, for example, other systems or components of the device 805). For example, the processing system of the device 805 can refer to a system that includes various other components or subcomponents of the device 805, such as the processor 835, or the transceiver 810, or the communication manager 820, or other components or combinations of components of the device 805. The processing system of the device 805 can interface with other components of the device 805 and can process information (such as inputs or signals) received from other components or output information to other components. For example, a chip or modem of the device 805 may include a processing system and one or more interfaces for outputting information or for obtaining information, or both. The one or more interfaces may be implemented as or otherwise include a first interface configured to output information and a second interface configured to obtain information, or the same interface configured to output information and obtain information, among other implementations. In some implementations, the one or more interfaces may refer to an interface between a processing system of a chip or modem and a transmitter, such that the device 805 can transmit information output from the chip or modem. Additionally or alternatively, in some implementations, the one or more interfaces may refer to an interface between a processing system of a chip or modem and a receiver, such that the device 805 can obtain information or signal input, and the information can be passed to the processing system.One of ordinary skill in the art will readily recognize that the first interface may also obtain information or signal input, and the second interface may also output information or signal output.

[0161] In some examples, bus 840 may support communications of protocol layers (e.g., within protocol layers) of a protocol stack. In some examples, bus 840 may support communications associated with logical channels of a protocol stack (e.g., between protocol layers of a protocol stack), which may include communications performed within components of device 805 or between different components of device 805 that may be co-located or located in different locations (e.g., where device 805 may refer to a system in which one or more of communication manager 820, transceiver 810, memory 825, code 830, and processor 835 may be located in one of the different components or divided between the different components).

[0162] In some examples, communication manager 820 can manage aspects of communications with core network 130 (e.g., via one or more wired or wireless backhaul links). For example, communication manager 820 can manage the transfer of data communications for client devices, such as one or more UEs 115. In some examples, communication manager 820 can manage communications with other network entities 105 and can include a controller or scheduler for controlling communications with UEs 115 in coordination with other network entities 105. In some examples, communication manager 820 can support an X2 interface within LTE / LTE-A wireless communication network technology to provide communications between network entities 105.

[0163] The communication manager 820 can support wireless communications at a first wireless communication device according to examples as disclosed herein. For example, the communication manager 820 can be configured to or otherwise support components for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits. The communication manager 820 can be configured to or otherwise support components for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0164] By including or configuring a communication manager 820 according to examples as described herein, the device 805 can support techniques for improving communication reliability, reducing latency, more efficiently utilizing communication resources, and improving coordination between devices.

[0165] In some examples, the communication manager 820 can be configured to perform various operations (e.g., receive, obtain, monitor, output, transmit) using or otherwise coordinating with the transceiver 810, one or more antennas 815 (e.g., where applicable), or any combination thereof. Although the communication manager 820 is illustrated as a separate component, in some examples, one or more functions described with reference to the communication manager 820 can be supported or performed by the transceiver 810, the processor 835, the memory 825, the code 830, or any combination thereof. For example, the communication manager 820 can be configured to receive or transmit messages or other signaling as described herein via the transceiver 810. For example, the code 830 can include instructions that can be executed by the processor 835 to cause the device 805 to perform various aspects of the transmit signal quality of the probabilistically shaped message as described herein, or the processor 835 and the memory 825 can be otherwise configured to perform or support such operations.

[0166] Figure 9 A block diagram 900 illustrates a device 905 that supports transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure. The device 905 can be an example of aspects of the UE 115 as described herein. The device 905 can include a receiver 910, a transmitter 915, and a communication manager 920. The device 905 can also include a processor. Each of these components can communicate with each other (e.g., via one or more buses).

[0167] The receiver 910 may provide means for receiving information (such as packets, user data, control information, or any combination thereof) associated with various information channels (e.g., control channels, data channels, information channels related to the quality of transmitted signals of probabilistically shaped messages). The information may be passed to other components of the device 905. The receiver 910 may utilize a single antenna or a collection of multiple antennas.

[0168] The transmitter 915 may provide means for transmitting signals generated by other components of the device 905. For example, the transmitter 915 may transmit information associated with various information channels (e.g., a control channel, a data channel, an information channel related to the quality of the transmitted signal of a probabilistically shaped message), such as packets, user data, control information, or any combination thereof. In some examples, the transmitter 915 may be co-located with the receiver 910 in a transceiver module. The transmitter 915 may utilize a single antenna or a collection of multiple antennas.

[0169] The communication manager 920, the receiver 910, the transmitter 915, or various combinations thereof, or various components thereof, may be examples of means for performing various aspects of transmit signal quality of probabilistically shaped messages as described herein. For example, the communication manager 920, the receiver 910, the transmitter 915, or various combinations thereof, or components thereof, may support methods for performing one or more of the functions described herein.

[0170] In some examples, the communication manager 920, the receiver 910, the transmitter 915, or various combinations or components thereof may be implemented in hardware (e.g., in a communication management circuit). The hardware may include a processor, a digital signal processor (DSP), a central processing unit (CPU), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a microcontroller, discrete gate or transistor logic components, discrete hardware components, or any combination thereof that is configured as or otherwise supports components for performing the functions described in this disclosure. In some examples, the processor and a memory coupled to the processor may be configured to perform one or more of the functions described herein (e.g., by executing instructions stored in the memory by the processor).

[0171] Additionally or alternatively, in some examples, the communication manager 920, receiver 910, transmitter 915, or various combinations or components thereof may be implemented in code executed by a processor (e.g., as communication management software or firmware). If implemented in code executed by a processor, the functionality of the communication manager 920, receiver 910, transmitter 915, or various combinations or components thereof may be performed by a general-purpose processor (e.g., configured as or otherwise supporting means for performing the functions described in this disclosure), a DSP, a CPU, an ASIC, an FPGA, a microcontroller, or any combination of these or other programmable logic devices.

[0172] In some examples, the communication manager 920 can be configured to perform various operations (e.g., receive, obtain, monitor, output, transmit) using or otherwise cooperating with the receiver 910, the transmitter 915, or both. For example, the communication manager 920 can receive information from the receiver 910, transmit information to the transmitter 915, or be integrated with the receiver 910, the transmitter 915, or both to obtain information, output information, or perform various other operations as described herein.

[0173] The communication manager 920 can support wireless communications at a first wireless communication device according to examples as disclosed herein. For example, the communication manager 920 can be configured to or otherwise support components for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits. The communication manager 920 can be configured to or otherwise support components for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0174] Additionally or alternatively, the communication manager 920 may support wireless communication at the second wireless communication device according to examples as disclosed herein. For example, the communication manager 920 may be configured to or otherwise support components for receiving a shaped message from the first wireless communication device. The communication manager 920 may be configured to or otherwise support components for outputting a signal indicating whether a distribution closeness metric between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message satisfies a threshold.

[0175] By including or configuring a communication manager 920 according to examples as described herein, the device 905 (e.g., a processor controlling or otherwise coupled with the receiver 910, the transmitter 915, the communication manager 920, or a combination thereof) may support techniques for more efficiently utilizing communication resources.

[0176] Figure 10 A block diagram 1000 illustrates a device 1005 that supports transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure. The device 1005 may be an example of aspects of the device 905 or UE 115 as described herein. The device 1005 may include a receiver 1010, a transmitter 1015, and a communication manager 1020. The device 1005 may also include a processor. Each of these components may communicate with each other (e.g., via one or more buses).

[0177] The receiver 1010 may provide means for receiving information (such as packets, user data, control information, or any combination thereof) associated with various information channels (e.g., control channels, data channels, information channels related to the quality of transmitted signals of probabilistically shaped messages). The information may be passed to other components of the device 1005. The receiver 1010 may utilize a single antenna or a collection of multiple antennas.

[0178] The transmitter 1015 may provide means for transmitting signals generated by other components of the device 1005. For example, the transmitter 1015 may transmit information associated with various information channels (e.g., a control channel, a data channel, an information channel related to the quality of the transmitted signal of a probabilistically shaped message), such as packets, user data, control information, or any combination thereof. In some examples, the transmitter 1015 may be co-located with the receiver 1010 in a transceiver module. The transmitter 1015 may utilize a single antenna or a collection of multiple antennas.

[0179] Device 1005 or its various components may be examples of components for performing various aspects of transmit signal quality of probabilistically shaped messages as described herein. For example, communications manager 1020 may include probabilistic shaping manager 1025, shaped message manager 1030, quality signal manager 1035, or any combination thereof. Communications manager 1020 may be an example of various aspects of communications manager 920 as described herein. In some examples, communications manager 1020 or its various components may be configured to perform various operations (e.g., receive, obtain, monitor, output, transmit) using or otherwise cooperating with receiver 1010, transmitter 1015, or both. For example, communications manager 1020 may receive information from receiver 1010, transmit information to transmitter 1015, or be integrated with receiver 1010, transmitter 1015, or both to obtain information, output information, or perform various other operations as described herein.

[0180] The communication manager 1020 can support wireless communications at a first wireless communication device according to examples as disclosed herein. The probability shaping manager 1025 can be configured to or otherwise support means for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits. The shaped message manager 1030 can be configured to or otherwise support means for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0181] Additionally or alternatively, the communication manager 1020 may support wireless communications at the second wireless communication device according to examples as disclosed herein. The shaped message manager 1030 may be configured to or otherwise support components for receiving a shaped message from the first wireless communication device. The quality signal manager 1035 may be configured to or otherwise support components for outputting a signal indicating whether a distribution closeness metric between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message meets a threshold.

[0182] Figure 11Block diagram 1100 illustrates a communication manager 1120 that supports transmit signal quality of probabilistically shaped messages, in accordance with one or more aspects of the present disclosure. Communication manager 1120 may be an example of aspects of communication manager 920, communication manager 1020, or both, as described herein. Communication manager 1120 or its various components may be examples of means for performing various aspects of transmit signal quality of probabilistically shaped messages, as described herein. For example, communication manager 1120 may include a probability shaping manager 1125, a shaped message manager 1130, a quality signal manager 1135, an empirical probability distribution manager 1140, a modulation manager 1145, a threshold manager 1150, a maximum power reduction manager 1155, an error vector magnitude manager 1160, a distribution proximity metric manager 1165, a target probability distribution manager 1170, a demodulation manager 1175, or any combination thereof. Each of these components may communicate with each other, directly or indirectly (e.g., via one or more buses).

[0183] The communication manager 1120 may support wireless communications at a first wireless communication device according to examples as disclosed herein. The probability shaping manager 1125 may be configured to or otherwise support means for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits. The shaped message manager 1130 may be configured to or otherwise support means for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0184] In some examples, the empirical probability distribution is an empirical probability distribution of a shaped set of bits.

[0185] In some examples, empirical probability distribution manager 1140 may be configured or otherwise support components for measuring an empirical probability distribution across the transmission of one or more shaped messages within a target duration.

[0186] In some examples, modulation manager 1145 may be configured or otherwise support means for modulating a shaped set of bits to generate a set of modulated symbols, where the empirical probability distribution is an empirical probability distribution of respective amplitudes of the set of modulated symbols.

[0187] In some examples, a distribution closeness metric quantifies the difference between an empirical probability distribution and a target probability distribution.

[0188] In some examples, the distribution closeness measure is a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

[0189] In some examples, the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

[0190] In some examples, threshold manager 1150 may be configured or otherwise support components for determining thresholds based on parameters of a shaped message.

[0191] In some examples, the parameter is the number of modulation symbols in a shaped block, the number of bits in a shaped block, the shaping rate, the modulation order, or a combination thereof.

[0192] In some examples, to support sending shaped messages, maximum power reduction manager 1155 may be configured or otherwise support components for sending shaped messages according to a first MPR associated with the shaped message that is different from a second MPR associated with uniform QAM.

[0193] In some examples, error vector magnitude manager 1160 may be configured or otherwise support means for sending a shaped message according to a first EVM associated with the shaped message that is different from a second EVM associated with uniform QAM.

[0194] In some examples, error vector magnitude manager 1160 may be configured to or otherwise support means for decoding a shaped set of bits. In some examples, empirical probability distribution manager 1140 may be configured to or otherwise support means for reconstructing demodulated symbols based in part on the decoded shaped set of bits. In some examples, empirical probability distribution manager 1140 may be configured to or otherwise support means for measuring an EVM associated with a shaped message based in part on the equalized probability shaped transmit waveform and the demodulated symbols.

[0195] In some examples, distribution proximity metric manager 1165 may be configured or otherwise support components for receiving signaling indicative of a distribution proximity metric.

[0196] In some examples, target probability distribution manager 1170 may be configured or otherwise support components for receiving signaling indicating a target probability distribution.

[0197] Additionally or alternatively, the communication manager 1120 can support wireless communications at the second wireless communication device according to examples as disclosed herein. In some examples, the shaped message manager 1130 can be configured to or otherwise support components for receiving a shaped message from the first wireless communication device. The quality signal manager 1135 can be configured to or otherwise support components for outputting a signal indicating whether a distribution closeness metric between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message meets a threshold.

[0198] In some examples, the demodulation manager 1175 may be configured or otherwise support means for demodulating a shaped set of bits from a shaped message, wherein the empirical probability distribution is an empirical probability distribution of the shaped set of bits.

[0199] In some examples, empirical probability distribution manager 1140 may be configured or otherwise support components for measuring an empirical probability distribution across the transmission of one or more shaped messages within a target duration.

[0200] In some examples, the empirical probability distribution is an empirical probability distribution of respective amplitudes of a set of modulated symbols of the shaped message.

[0201] In some examples, the distribution closeness measure is a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

[0202] In some examples, a distribution closeness metric quantifies the difference between an empirical probability distribution and a target probability distribution.

[0203] In some examples, the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

[0204] In some examples, threshold manager 1150 may be configured or otherwise support components for determining a threshold based at least in part on parameters of a shaped message.

[0205] In some examples, the parameter is the number of modulation symbols in a shaped block, the number of bits in a shaped block, the shaping rate, the modulation order, or a combination thereof.

[0206] In some examples, distribution proximity metric manager 1165 may be configured or otherwise support components for receiving signaling indicative of a distribution proximity metric.

[0207] In some examples, target probability distribution manager 1170 may be configured or otherwise support components for receiving signaling indicating a target probability distribution.

[0208] Figure 12 A diagram illustrating a system 1200 including a device 1205 supporting transmit signal quality of probabilistically shaped messages according to one or more aspects of the present disclosure is shown. The device 1205 may be an example of a device 905, a device 1005, or a UE 115 as described herein, or may include components of such devices. The device 1205 may communicate (e.g., wirelessly) with one or more network entities 105, one or more UEs 115, or any combination thereof. The device 1205 may include components for two-way voice and data communication, including components for sending and receiving communications, such as a communication manager 1220, an input / output (I / O) controller 1210, a transceiver 1215, an antenna 1225, a memory 1230, code 1235, and a processor 1240. These components may be in electronic communication or otherwise coupled (e.g., operatively, communicatively, functionally, electronically, electrically) via one or more buses (e.g., a bus 1245).

[0209] I / O controller 1210 can manage input and output signals for device 1205. I / O controller 1210 can also manage peripheral devices that are not integrated into device 1205. In some cases, I / O controller 1210 can represent a physical connection or port to an external peripheral device. In some cases, I / O controller 1210 can utilize an operating system such as or another known operating system. Additionally or alternatively, I / O controller 1210 may represent or interact with a modem, keyboard, mouse, touch screen, or similar device. In some cases, I / O controller 1210 may be implemented as part of a processor (such as processor 1240). In some cases, a user may interact with device 1205 via I / O controller 1210 or via hardware components controlled by I / O controller 1210.

[0210] In some cases, device 1205 may include a single antenna 1225. However, in some other cases, device 1205 may have more than one antenna 1225, which may be capable of concurrently transmitting or receiving multiple wireless transmissions. Transceiver 1215 may communicate bidirectionally via one or more antennas 1225, wired, or wireless links, as described herein. For example, transceiver 1215 may represent a wireless transceiver and may communicate bidirectionally with another wireless transceiver. Transceiver 1215 may also include a modem for modulating packets; providing the modulated packets to one or more antennas 1225 for transmission; and demodulating packets received from one or more antennas 1225. Transceiver 1215, or transceiver 1215 and one or more antennas 1225, may be examples of transmitter 915, transmitter 1015, receiver 910, receiver 1010, or any combination thereof, or components thereof, as described herein.

[0211] Memory 1230 may include random access memory (RAM) and read-only memory (ROM). Memory 1230 may store computer-readable, computer-executable code 1235 including instructions that, when executed by processor 1240, cause device 1205 to perform the various functions described herein. Code 1235 may be stored in a non-transitory computer-readable medium (such as system memory or another type of memory). In some cases, code 1235 may not be directly executable by processor 1240, but may (e.g., when compiled and executed) cause a computer to perform the functions described herein. In some cases, memory 1230 may also contain, among other things, a basic I / O system (BIOS) that controls basic hardware or software operations, such as interaction with peripheral components or devices.

[0212] The processor 1240 may include an intelligent hardware device (e.g., a general-purpose processor, a DSP, a CPU, a microcontroller, an ASIC, an FPGA, a programmable logic device, a discrete gate or transistor logic component, a discrete hardware component, or any combination thereof). In some cases, the processor 1240 may be configured to operate a memory array using a memory controller. In some other cases, the memory controller may be integrated into the processor 1240. The processor 1240 may be configured to execute computer-readable instructions stored in a memory (e.g., memory 1230) to cause the device 1205 to perform various functions (e.g., functions or tasks that support the quality of transmitted signals of probabilistically shaped messages). For example, the device 1205 or a component of the device 1205 may include a processor 1240 and a memory 1230 coupled to or coupled to the processor 1240, the processor 1240 and the memory 1230 being configured to perform the various functions described herein.

[0213] The communication manager 1220 may support wireless communications at a first wireless communication device according to examples as disclosed herein. For example, the communication manager 1220 may be configured to or otherwise support components for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits. The communication manager 1220 may be configured to or otherwise support components for sending a shaped message generated based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0214] Additionally or alternatively, the communication manager 1220 may support wireless communication at the second wireless communication device according to examples as disclosed herein. For example, the communication manager 1220 may be configured to or otherwise support components for receiving a shaped message from the first wireless communication device. The communication manager 1220 may be configured to or otherwise support components for outputting a signal indicating whether a distribution closeness metric between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message satisfies a threshold.

[0215] By including or configuring a communications manager 1220 according to examples as described herein, the device 1205 can support techniques for improving communications reliability, reducing latency, more efficiently utilizing communications resources, and improving coordination between devices.

[0216] In some examples, the communication manager 1220 can be configured to perform various operations (e.g., receive, monitor, transmit) using or otherwise coordinating with the transceiver 1215, one or more antennas 1225, or any combination thereof. For example, the communication manager 1120 can be configured to receive or transmit messages or other signaling as described herein via the transceiver 1215. Although the communication manager 1220 is illustrated as a separate component, in some examples, one or more functions described with reference to the communication manager 1220 can be supported or performed by the processor 1240, the memory 1230, the code 1235, or any combination thereof. For example, the code 1235 can include instructions that can be executed by the processor 1240 to cause the device 1205 to perform various aspects of the transmit signal quality of the probabilistically shaped message as described herein, or the processor 1240 and the memory 1230 can be otherwise configured to perform or support such operations.

[0217] Figure 13 A flow chart illustrating a method 1300 for supporting transmit signal quality of a probabilistically shaped message according to one or more aspects of the present disclosure is illustrated. The operations of the method 1300 may be implemented by a network entity or UE or components thereof as described herein. For example, the operations of the method 1300 may be implemented by a network entity or UE or components thereof as described herein. Figures 1 to 8 The network entity described or as referenced Figures 1 to 4 and Figures 9 to 12 The described UE 115 performs. In some examples, a network entity or UE may execute an instruction set to control the functional elements of the network entity or UE to perform the described functions. Additionally or alternatively, the network entity or UE may use dedicated hardware to perform various aspects of the described functions.

[0218] At 1305, the method may include performing probability shaping on the set of information bits according to the target probability distribution to generate a set of shaped bits. The operations of 1305 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1305 may be performed as described in reference to Figure 7 and Figure 11 The described probability shaping manager 725 or probability shaping manager 1125 performs. Additionally or alternatively, means for performing 1305 may, but need not necessarily, include, for example, antenna 815, transceiver 810, communication manager 820, memory 825 (including code 830), processor 835, and / or bus 840.

[0219] At 1310, the method may include sending a shaped message generated based on the shaped bit set to a second wireless communication device, wherein a distribution closeness metric between an empirical probability distribution of the shaped message and a target probability distribution satisfies a threshold. In some examples, the sending device may be expected to ensure that the distribution closeness metric between the empirical probability distribution and the target probability distribution satisfies the threshold when generating the shaped signal. The operations of 1310 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1310 may be performed as described in reference to Figure 7 and Figure 11 The described shaped message manager 730 or shaped message manager 1130 performs. Additionally or alternatively, means for performing 1310 may, but need not necessarily, include, for example, antenna 815, transceiver 810, communication manager 820, memory 825 (including code 830), processor 835, and / or bus 840.

[0220] Figure 14 A flow chart illustrating a method 1400 for supporting transmit signal quality of a probabilistically shaped message according to one or more aspects of the present disclosure is illustrated. The operations of the method 1400 may be implemented by a network entity or UE or components thereof as described herein. For example, the operations of the method 1400 may be implemented by a network entity or UE or components thereof as described herein. Figures 1 to 8 The network entity described or as referenced Figures 1 to 4 and Figures 9 to 12The described UE 115 performs. In some examples, a network entity or UE may execute an instruction set to control the functional elements of the network entity or UE to perform the described functions. Additionally or alternatively, the network entity or UE may use dedicated hardware to perform various aspects of the described functions.

[0221] At 1405, the method may include performing probability shaping on the set of information bits according to the target probability distribution to generate a set of shaped bits. The operations of 1405 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1405 may be performed as described in reference to Figure 7 and Figure 11 The described probability shaping manager 725 or probability shaping manager 1125 performs. Additionally or alternatively, means for performing 1305 may, but need not necessarily, include, for example, antenna 815, transceiver 810, communication manager 820, memory 825 (including code 830), processor 835, and / or bus 840.

[0222] At 1410, the method may include sending a shaped message generated based on the shaped bit set to a second wireless communication device, wherein a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold. The operations of 1410 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1410 may be performed as described in reference to Figure 7 and Figure 11 The described shaped message manager 730 or shaped message manager 1130 performs. Additionally or alternatively, means for performing 1305 may, but need not necessarily, include, for example, antenna 815, transceiver 810, communication manager 820, memory 825 (including code 830), processor 835, and / or bus 840.

[0223] At 1415, the method may include measuring an empirical probability distribution across the transmission of one or more shaped messages within a target duration. The operations of 1415 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1415 may be performed as described in reference to Figure 7 and Figure 11 The described empirical probability distribution manager 735 or the empirical probability distribution manager 1140 performs. Additionally or alternatively, means for performing 1305 may, but need not necessarily, include, for example, antenna 815, transceiver 810, communication manager 820, memory 825 (including code 830), processor 835, and / or bus 840.

[0224] Figure 15A flow chart illustrating a method 1500 for supporting transmit signal quality of a probabilistically shaped message according to one or more aspects of the present disclosure is illustrated. The operations of the method 1500 may be implemented by a UE or components thereof as described herein. For example, the operations of the method 1500 may be implemented by a UE or components thereof as described herein. Figures 1 to 4 and Figures 9 to 12 The UE 115 described herein performs. In some examples, the UE may execute an instruction set to control the functional elements of the UE to perform the described functions. Additionally or alternatively, the UE may use dedicated hardware to perform various aspects of the described functions.

[0225] At 1505, the method may include receiving a shaped message from a first wireless communication device. The operations of 1505 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1505 may be performed as described with reference to Figure 11 The described shaped message manager 1130 performs. Additionally or alternatively, means for performing 1405 may, but need not necessarily, include, for example, an antenna 1225, a transceiver 1215, a communications manager 1220, a memory 1230 (including code 1235), a processor 1240, and / or a bus 1245.

[0226] At 1510, the method may include outputting a signal indicating whether a distribution closeness measure between the empirical probability distribution of the shaped message and the target probability distribution of the shaped message satisfies a threshold. The operations of 1510 may be performed according to examples as disclosed herein. In some examples, aspects of the operations of 1510 may be performed as described in reference to Figure 11 The described quality signal manager 1135 performs. Additionally or alternatively, means for performing 1405 may, but need not necessarily, include, for example, antenna 1225, transceiver 1215, communication manager 1220, memory 1230 (including code 1235), processor 1240, and / or bus 1245.

[0227] The following provides an overview of various aspects of the disclosure:

[0228] Aspect 1: A method for wireless communication at a first wireless communication device, the method comprising: performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits; and sending a shaped message generated at least in part based on the shaped set of bits to a second wireless communication device, wherein a distribution closeness measure between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

[0229] Aspect 2: The method of aspect 1, wherein the empirical probability distribution is an empirical probability distribution of the shaped bit set.

[0230] Aspect 3: The method according to any one of aspects 1 to 2, further comprising: measuring the empirical probability distribution across transmissions of one or more shaped messages within a target duration.

[0231] Aspect 4: The method according to any one of aspects 1 and 3, further comprising: modulating the set of shaped bits to generate a set of modulated symbols, wherein the empirical probability distribution is an empirical probability distribution of corresponding amplitudes of the set of modulated symbols.

[0232] Aspect 5: The method according to any one of aspects 1 to 4, wherein the distribution closeness metric quantifies the difference between the empirical probability distribution and the target probability distribution.

[0233] Aspect 6: The method according to aspect 5, wherein the distribution closeness measure is Kullback-Leibler divergence score, entropy difference, total variation distance, Hellinger distance or statistical distance.

[0234] Aspect 7: The method according to any one of aspects 1 to 4, wherein the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

[0235] Aspect 8: The method according to any one of aspects 1 to 7, further comprising: determining the threshold based at least in part on a parameter of the shaped message.

[0236] Aspect 9: The method according to aspect 8, wherein the parameter is the number of modulation symbols in a shaped block, the number of bits in a shaped block, the shaping rate, the modulation order, or a combination thereof.

[0237] Aspect 10: The method of any one of aspects 1 to 9, wherein sending the shaped message comprises sending the shaped message according to a first MPR associated with the shaped message, the first MPR being different from a second MPR associated with uniform QAM.

[0238] Aspect 11: The method of any one of aspects 1 to 10, further comprising sending the shaped message according to a first EVM associated with the shaped message, the first EVM being different from a second EVM associated with uniform QAM.

[0239] Aspect 12: The method of any one of Aspects 1 to 11, further comprising: decoding the shaped bit set; reconstructing demodulation symbols based in part on the decoded shaped bit set; and measuring the EVM associated with the shaped message based in part on the equalized probability shaped transmit waveform and the demodulation symbols.

[0240] Aspect 13: The method according to any one of aspects 1 to 12, further comprising: receiving signaling indicating the distribution proximity metric.

[0241] Aspect 14: The method according to any one of aspects 1 to 13, further comprising: receiving signaling indicating the target probability distribution.

[0242] Aspect 15: A method for wireless communication at a second wireless communication device, the method comprising: receiving a shaped message from a first wireless communication device; and outputting a signal indicating whether a distribution closeness measure between an empirical probability distribution of the shaped message and a target probability distribution of the shaped message satisfies a threshold.

[0243] Aspect 16: The method of aspect 15, further comprising: demodulating a shaped set of bits from the shaped message, wherein the empirical probability distribution is an empirical probability distribution of the shaped set of bits.

[0244] Aspect 17: The method according to any one of aspects 15 to 16, further comprising: measuring the empirical probability distribution across transmissions of one or more shaped messages within a target duration.

[0245] Aspect 18: The method according to any one of aspects 15 and 17, wherein the empirical probability distribution is an empirical probability distribution of respective amplitudes of a set of modulated symbols of the shaped message.

[0246] Aspect 19: The method according to any one of aspects 15 to 18, wherein the distribution closeness metric quantifies the difference between the empirical probability distribution and the target probability distribution.

[0247] Aspect 20: The method according to aspect 19, wherein the distribution closeness measure is a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

[0248] Aspect 21: The method according to any one of aspects 15 to 18, wherein the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

[0249] Aspect 22: The method according to any one of aspects 15 to 21, further comprising: determining the threshold based at least in part on a parameter of the shaped message.

[0250] Aspect 23: The method according to aspect 22, wherein the parameter is the number of modulation symbols in a shaped block, the number of bits in a shaped block, the shaping rate, the modulation order, or a combination thereof.

[0251] Aspect 24: The method according to any one of aspects 15 to 23, further comprising: receiving signaling indicative of the distribution proximity metric.

[0252] Aspect 25: The method according to any one of aspects 15 to 24, further comprising: receiving signaling indicating the target probability distribution.

[0253] Aspect 26: An apparatus for wireless communication at a first wireless communication device, the apparatus comprising: a processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform a method according to any one of Aspects 1 to 14.

[0254] Aspect 27: An apparatus for wireless communication at a first wireless communication device, the apparatus comprising at least one means for performing the method according to any one of aspects 1 to 14.

[0255] Aspect 28: A non-transitory computer-readable medium storing code for wireless communication at a first wireless communication device, the code comprising instructions executable by a processor to perform the method according to any one of aspects 1 to 14.

[0256] Aspect 29: An apparatus for wireless communication at a second wireless communication device, the apparatus comprising: a processor; a memory coupled to the processor; and instructions stored in the memory and executable by the processor to cause the apparatus to perform a method according to any one of Aspects 15 to 25.

[0257] Aspect 30: An apparatus for wireless communication at a second wireless communication device, the apparatus comprising at least one means for performing the method according to any one of aspects 15 to 25.

[0258] Aspect 31: A non-transitory computer-readable medium storing code for wireless communication at a second wireless communication device, the code comprising instructions executable by a processor to perform the method according to any one of aspects 15 to 25.

[0259] It should be noted that the methods described herein describe possible implementations, and that the operations and steps may be rearranged or otherwise modified and that other implementations are possible. Furthermore, aspects from two or more methods may be combined.

[0260] Although aspects of LTE, LTE-A, LTE-A Pro, or NR systems may be described for example purposes, and LTE, LTE-A, LTE-A Pro, or NR terminology may be used throughout much of the description, the techniques described herein may also be applicable to networks other than LTE, LTE-A, LTE-A Pro, or NR networks. For example, the techniques described may be applicable to various other wireless communication systems, such as Ultra Mobile Broadband (UMB), Institute of Electrical and Electronics Engineers (IEEE) 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), IEEE 802.20, Flash-OFDM, and other systems and radio technologies not explicitly mentioned herein.

[0261] The information and signals described herein may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips referred to throughout the description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.

[0262] The various illustrative blocks and components described in conjunction with the disclosure herein may be implemented or executed using a general purpose processor, a DSP, an ASIC, a CPU, an FPGA or other programmable logic device, discrete gate or transistor logic components, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices (e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration).

[0263] The functions described herein may be implemented using hardware, software executed by a processor, firmware, or any combination thereof. If implemented using software executed by a processor, the functions may be stored as one or more instructions or codes of a computer-readable medium, or sent using one or more instructions or codes of a computer-readable medium. Other examples and implementations are within the scope of this disclosure and the appended claims. For example, due to the nature of software, the functions described herein may be implemented using software executed by a processor, hardware, firmware, hard wiring, or a combination of any of these. Features that implement the functions may also be physically located at different locations, including being distributed so that various parts of the functions are implemented at different physical locations.

[0264] Computer readable medium includes both non-transient computer storage medium and communication medium, and this communication medium includes any medium that promotes computer program to be transferred from one location to another location.Non-transient storage medium can be any available medium that can be accessed by general or special-purpose computer.By way of example and not limitation, non-transient computer readable medium can include RAM, ROM, electrically erasable programmable ROM (EEPROM), flash memory, compact disc (CD) ROM or other optical disc storage, disk storage or other magnetic storage device or can be used for carrying or storing desired program code components and any other non-transient medium that can be accessed by general or special-purpose computer or general or special-purpose processor in the form of instruction or data structure.In addition, any connection is appropriately referred to as computer readable medium.For example, if software is to be sent from website, server or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL) or wireless technology such as infrared, radio and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL or wireless technology such as infrared, radio and microwave are included in the definition of computer readable medium. As used herein, disks and optical discs include CDs, laser discs, optical discs, digital versatile discs (DVDs), floppy disks, and Blu-ray discs. Magnetic disks can reproduce data magnetically, and optical discs can reproduce data optically using lasers. Combinations of the above are also included within the scope of computer-readable media.

[0265] As used herein (including in the claims), "or" used in a list of items (e.g., a list of items followed by a phrase such as "at least one of" or "one or more of") indicates an inclusive list, so that, for example, a list of at least one of A, B, or C means A or B or C or AB or AC or BC or ABC (i.e., A and B and C). In addition, as used herein, the phrase "based on" should not be interpreted as a reference to a closed set of conditions. For example, an example step described as "based on condition A" can be based on both condition A and condition B without departing from the scope of this disclosure. In other words, as used herein, the phrase "based on" should be interpreted in the same manner as the phrase "based at least in part on."

[0266] The term "determining" encompasses a variety of actions, and thus, "determining" may include calculating, computing, processing, deriving, investigating, looking up (such as via looking up in a table, database, or other data structure), ascertaining, etc. Furthermore, "determining" may include receiving (e.g., receiving information), accessing (e.g., accessing data stored in a memory), etc. Furthermore, "determining" may include parsing, retrieving, selecting, choosing, establishing, and other such similar actions.

[0267] In the drawings, similar components or features may have the same reference label. In addition, various components of the same type may be distinguished by following the reference label with a dash and a second label to distinguish between similar components. If only the first reference label is used in the specification, the description can apply to any of the similar components having the same first reference label, regardless of the second reference label or other subsequent reference labels.

[0268] The description set forth herein in conjunction with the accompanying drawings describes example configurations and does not represent all examples that may be implemented or within the scope of the claims. The term "example" as used herein means "serving as an example, instance, or illustration," rather than "preferred" or "having advantages over other examples." The detailed description includes specific details to provide an understanding of the described techniques. However, these techniques can be practiced without these specific details. In some cases, known structures and devices are shown in block diagram form to avoid obscuring the concepts of the described examples.

[0269] The description herein is provided to enable one of ordinary skill in the art to make or use the present disclosure. Various modifications to the present disclosure will be apparent to those of ordinary skill in the art, and the general principles defined herein may be applied to other variations without departing from the scope of the present disclosure. Thus, the present disclosure is not limited to the examples and designs described herein, but should be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An apparatus for wireless communication at a first wireless communication device, the apparatus comprising: Memory; and at least one processor of the first wireless communication device, the at least one processor being coupled to the memory and configured to: performing probability shaping on the set of information bits according to a target probability distribution to generate a set of shaped bits; as well as A shaped message generated based at least in part on the shaped set of bits is sent to a second wireless communication device, wherein a distribution closeness metric between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

2. The device of claim 1, wherein the empirical probability distribution is an empirical probability distribution of the shaped set of bits.

3. The apparatus of claim 1 , wherein the at least one processor is further configured to: The empirical probability distribution is measured across transmissions of one or more shaped messages over a target duration.

4. The apparatus of claim 1 , wherein the at least one processor is further configured to: The shaped set of bits is modulated to generate a set of modulated symbols, wherein the empirical probability distribution is an empirical probability distribution of respective amplitudes of the set of modulated symbols. The apparatus of claim 1 , wherein the distribution closeness metric quantifies the difference between the empirical probability distribution and the target probability distribution. 6 . The apparatus of claim 5 , wherein the distribution closeness measure is a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

7. The apparatus of claim 1, wherein the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

8. The apparatus of claim 1 , wherein the at least one processor is further configured to: The threshold is determined based at least in part on a parameter of the shaped message.

9. The apparatus of claim 8, wherein the parameter is the number of modulation symbols in a shaped block, the number of bits in a shaped block, a shaping rate, a modulation order, or a combination thereof.

10. The apparatus of claim 1 , wherein the at least one processor configured to send the shaped message is further configured to: The shaped message is sent according to a first maximum power reduction associated with the shaped message that is different from a second maximum power reduction associated with uniform quadrature amplitude modulation.

11. The apparatus of claim 1 , wherein the at least one processor is further configured to: The shaped message is sent according to a first error vector magnitude associated with the shaped message that is different from a second error vector magnitude associated with uniform quadrature amplitude modulation.

12. The apparatus of claim 1 , wherein the at least one processor is further configured to: decoding the shaped set of bits; reconstructing demodulated symbols based in part on the decoded shaped set of bits; and An error vector magnitude associated with the shaped message is measured based in part on the equalized probability shaped transmit waveform and the demodulated symbols.

13. The apparatus of claim 1 , wherein the at least one processor is further configured to: Signaling indicative of the distribution closeness metric is received.

14. The apparatus of claim 1 , wherein the at least one processor is further configured to: Signaling indicating the target probability distribution is received.

15. An apparatus for wireless communication at a second wireless communication device, the apparatus comprising: Memory; transceiver; and at least one processor of the second wireless communication device, the at least one processor coupled to the memory and the transceiver and configured to: receiving, via the transceiver, a shaped message from a first wireless communication device; and A signal is outputted indicating whether a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution of the shaped message satisfies a threshold.

16. The apparatus of claim 15, wherein the at least one processor is further configured to: A shaped set of bits is demodulated from the shaped message, wherein the empirical probability distribution is an empirical probability distribution of the shaped set of bits.

17. The apparatus of claim 15, wherein the at least one processor is further configured to: The empirical probability distribution is measured across transmissions of one or more shaped messages over a target duration.

18. The apparatus of claim 15, wherein the empirical probability distribution is an empirical probability distribution of respective amplitudes of a set of modulated symbols of the shaped message.

19. The apparatus of claim 15, wherein the distribution closeness metric quantifies a difference between the empirical probability distribution and the target probability distribution.

20. The apparatus of claim 19, wherein the distribution closeness measure is a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

21. The apparatus of claim 15, wherein the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

22. The apparatus of claim 15, wherein the at least one processor is further configured to: The threshold is determined based at least in part on a parameter of the shaped message.

23. The apparatus of claim 22, wherein the parameter is the number of modulation symbols in a shaped block, the number of bits in a shaped block, a shaping rate, a modulation order, or a combination thereof.

24. The apparatus of claim 15, wherein the at least one processor is further configured to: Signaling indicative of the distribution closeness metric is received.

25. The apparatus of claim 15, wherein the at least one processor is further configured to: Signaling indicating the target probability distribution is received.

26. A method for wireless communication at a first wireless communication device, the method comprising: performing probability shaping on the set of information bits according to a target probability distribution to generate a set of shaped bits; as well as A shaped message generated based at least in part on the shaped set of bits is sent to a second wireless communication device, wherein a distribution closeness metric between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

27. The method of claim 26, wherein the empirical probability distribution is an empirical probability distribution of the shaped set of bits.

28. The method according to claim 26, further comprising: The empirical probability distribution is measured across transmissions of one or more shaped messages over a target duration.

29. The method according to claim 26, further comprising: The shaped set of bits is modulated to generate a set of modulated symbols, wherein the empirical probability distribution is an empirical probability distribution of respective amplitudes of the set of modulated symbols.

30. The method of claim 26, wherein the distribution closeness metric quantifies the difference between the empirical probability distribution and the target probability distribution.

31. The method of claim 30, wherein the distribution closeness measure is a Kullback-Leibler divergence score, an entropy difference, a total variation distance, a Hellinger distance, or a statistical distance.

32. The method of claim 26, wherein the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

33. The method of claim 26, further comprising: The threshold is determined based at least in part on a parameter of the shaped message, wherein the parameter is a number of modulation symbols in a shaped block, a number of bits in a shaped block, a shaping rate, a modulation order, or a combination thereof.

34. The method of claim 26, wherein sending the shaped message comprises: The shaped message is sent according to a first maximum power reduction associated with the shaped message that is different from a second maximum power reduction associated with uniform quadrature amplitude modulation.

35. The method of claim 26, further comprising: The shaped message is sent according to a first error vector magnitude associated with the shaped message that is different from a second error vector magnitude associated with uniform quadrature amplitude modulation.

36. The method of claim 26, further comprising: decoding the shaped set of bits; reconstructing demodulated symbols based in part on the decoded shaped set of bits; as well as An error vector magnitude associated with the shaped message is measured based in part on the equalized probability shaped transmit waveform and the demodulated symbols.

37. A method for wireless communication at a second wireless communication device, the method comprising: receiving a shaped message from a first wireless communication device; as well as A signal is outputted indicating whether a distribution closeness metric between the empirical probability distribution of the shaped message and the target probability distribution of the shaped message satisfies a threshold.

38. The method of claim 37, wherein the distribution closeness metric quantifies the difference between the empirical probability distribution and the target probability distribution.

39. The method of claim 37, wherein the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

40. An apparatus for wireless communication at a first wireless communication device, the apparatus comprising: means for performing probability shaping on a set of information bits according to a target probability distribution to generate a shaped set of bits; and Means for sending a shaped message generated based at least in part on the shaped set of bits to a second wireless communication device, wherein a distribution closeness metric between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

41. The apparatus of claim 40, wherein the distribution closeness metric quantifies the difference between the empirical probability distribution and the target probability distribution.

42. The apparatus of claim 40, wherein the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

43. A non-transitory computer-readable medium storing code for wireless communication at a first wireless communication device, the code comprising instructions executable by a processor to: performing probability shaping on the set of information bits according to a target probability distribution to generate a set of shaped bits; and A shaped message generated based at least in part on the shaped set of bits is sent to a second wireless communication device, wherein a distribution closeness metric between an empirical probability distribution of the shaped message and the target probability distribution satisfies a threshold.

44. The non-transitory computer-readable medium of claim 43, wherein the distribution closeness metric quantifies a difference between the empirical probability distribution and the target probability distribution.

45. The non-transitory computer-readable medium of claim 43, wherein the distribution closeness metric quantifies the difference between corresponding moments of one or more orders of the empirical probability distribution and the target probability distribution.

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