Abstract: A method for predefining an entryway at a virtual boundary of an XR space contained within a real environment includes: accessing a spatial mapping mesh (SMM) for the real environment, and a sealed space mesh (SSM) for the XR space; analyzing polygons in the SMM and SSM to identify first subsets representing vertical surfaces and virtual wall boundaries respectively; filtering the first subsets according to first criteria to yield second subsets; colliding polygons across the second subsets to yield a third subset of SSM polygons; defining groups of connected SSM polygons within the third subset; and selecting one group as defining the entryway. The defining of the entryway is carried out in advance of user interaction with any virtual elements in the XR environment.

Abstract: An artificial intelligence (AI) based method for calibration of a gaming ecosystem and to maximize satisfaction of a player involved in a gaming session such as single-player gaming session, multi-player online gaming session, and a videogame recommendation system is provided. The system detects the gaming session that includes an execution of a video game for a first gameplay and acquires sensor data associated with a player involved in the first gameplay. The sensor data corresponds to a duration of the detected gaming session. The system determines one or more indicators of a dissatisfaction of the player with the first gameplay based on application of one or more Artificial Intelligence (AI) models on the sensor data. The system controls the execution of the video game to modify one or more aspects associated with the first gameplay or a second gameplay of the video game that is different from the first gameplay.

Abstract: A communication circuit and protocol for a wireless local area network (WLAN) using CSMA/CA and single EDCA and/or Multiple-User (MU) EDCA. EDCA functions are configured to operate with multiple sets of operating parameters providing a range of priority levels for altering on the fly the nominal access time for a STA sending prioritized packets. The STA then must switch to a lower-priority set of parameters as recompense so that channel usage remains fair.

Abstract: An apparatus includes one or more processors and logic encoded in one or more non-transitory media for execution by the one or more processors and when executed operable to receive sensor data from a drone that travels around a target object. The logic is further operable to generate, based on the sensor data, a first three-dimensional (3D) reconstruction of the target object. The logic is further operable to estimate a direction of sunlight and a direction of spectral reflection. The logic is further operable to plan a trajectory of sensor capturing positions for the drone to capture images of the target object that reduce an amount of sunlight and an amount of specular reflection.

Abstract: Using this described protocol an AP can control multiple STAs to allow them to utilize the same scrambling seed to scramble the data in identical data units being sent on the wireless network. The AP sends a scrambling seed indication within a frame communicated to other STAs on the network. These other STAs, then use this scrambling seed indication to scramble a data field of a data unit with an identical scrambling seed, and to transmit these packets using the same modulation and coding scheme (MCS).

Abstract: Enhanced wireless protocols are described for stations (STAs) which are associated with Multiple-Link Devices (MLD). One embodiment describes overcoming replay attacks (with or without a modified Sequence Number (SN) even when protected by a Group Temporal Key (GTK) or similar. Other embodiments describe MLP operating enhancements associated with utilizing a Robust Security Network Element (RSNE), or NSTR Mobile AP MLD, or Target Beacon Transmission Time (TBTT) Information fields with Reduced Neighbor Reports (RNR), or Quiet Channel elements in an Association/Reassociation, or that use PPDU end alignment are all subject to specific shortcomings when applied to MLDs.

Abstract: Methods are described for overcoming contention issues during R-TWT SPs. In particular, enhanced mechanisms are defined in prioritizing transmissions of R-TWT TIDs during corresponding R-TWT SPs. In addition, enhanced access mechanisms are described for overcoming issues with stations accessing the channel after sensing an idle channel after a DIFS or AIFS time period.

Abstract: A wireless protocol allowing an AP to allocate time within a transmit opportunity (TXOP) to non-AP stations. The allocations are made under condition that the non-AP STA(s) will satisfy Access Class (AC) requirements communicated in a frame sent by the AP STA, such as within an MU RTS TXS Trigger frame. Upon receiving the frame, the non-AP responds on whether it can meet the conditions, such as within a Clear-To-Send (CTS) message. If the non-AP can meet the conditions, then it proceeds to transmit data (to the AP, or a peer non-AP). Otherwise, if it cannot meet the conditions, then the AP can communicate the allocation to another non-AP STA. There are also conditions for how the non-AP can aggregate data units into A-MSDUs.

Abstract: A wireless local area network (WLAN) protocol allowing a Transmit Opportunity (TXOP) holder to share the TXOP with other stations (STAs) residing in either the same Basic Service Set (BSS) of the TXOP holder, or in an other BSS (OBSS). An intent to share the TXOP is communicated to the Access Point (AP), and/or directly to other STAs. Scheduling information (time and duration) are shared with the STAs either directly, or through one or more APs. When the TXOP occurs, the STAs can access the channel at the time and for the duration specified, thus providing increased use of the TXOP to improve efficiency.

Abstract: An enhanced protocol for addressing communication issues arising from using a Remote Radio Head (RRH). An Access Point (AP), denoted as Remote Radio Head (RRH) AP, consists of a Central Unit (CU) and at least one RRH that can be located remotely. The functionalities of the Medium Access Control (MAC) and the Physical (PHY) layers of the RRH AP are split between the CU and RRH; with the CU exchanging frames between the MAC layers, and the RRH transmitting and receiving the physical signals through the channel.

Abstract: Enhanced Multi-Link Operation (MLO) is performed in this protocol in which non-simultaneous transmit/receive (NSTR) Multi-Link Devices (MLDs) cooperate with each other in sharing a portion of their available Transmit Opportunity (TXOP) toward reducing contention and competition for channel access across the group of cooperating MLDs. The shared TXOP is performed at an MLD level after all links for an NSTR MLD are obtained by stations which do not need to be in part of the same NSTR MLD, thus synchronized transmissions and receptions are performed which eliminate in-device coexistence (IDC) interference in any single NSTR MLD. The time gap while awaiting for all links to be obtained, is also made use of for performing transmission(s) toward increasing data throughput.

Abstract: The Double Actor Critic (DAC) reinforcement-learning algorithm affords stable policy improvement and aggressive neural-net optimization without catastrophic overfitting of the policy. DAC trains models using an arbitrary history of data in both offline and online learning and can be used to smoothly improve on an existing policy learned or defined by some other means. Finally, DAC can optimize reinforcement learning problems with discrete and continuous action spaces.

Abstract: Enhanced TID-to-UP mapping is performed which allows multiple TIDs to be mapped to the UPs of the same AC. Thus, a first STA can set TID-to-UP mapping for a second STA, whereby TID-to-UP mapping can differentiate the MSDUs or A-MSDUs that are transmitted. In addition, an MSDU / A-MSDU can be classified by TID first, then use TID-to-UP mapping to map it to the corresponding UP. In addition, an SCS traffic stream can assign a TID and a UP to that SCS traffic stream. The use of these enhanced mechanism can enhance low latency performance.

Abstract: Systems and methods use deep, convolutional neural networks over exponentially long history windows to learn alphabets for context tree weighting (CTW) for prediction. Known issues of depth and breadth in conventional context tree weighting predictions are addressed by the systems and methods. To deal with depth, the history can be broken into time windows, permitting the ability to look exponentially far back while having less information the further one looks back. To deal with breadth, a deep neural network classifier can be used to learn to map arbitrary length histories to a small output symbol alphabet. The sequence of symbols produced by such a classifier over the history windows would then become the input sequence to CTW.

Abstract: A method for quasi-random placement of a virtual item in an XR space includes: accessing a previously generated spatial mapping mesh (SMM) of the XR space; compiling a record from the SMM of open spaces between surfaces of physical elements in the XR space, with corresponding positions and dimensions; selecting from the open spaces: a spawn position for a virtual character, and a random set of other positions, filtering the random set to form a subset. The method then performs a collision analysis to assign a score to each position in the subset partly based on accessibility to that position for the virtual character beginning from the spawn position; and places the virtual item at a position in the subset having a score as high or higher than all other positions in the subset. The method is carried out before user interaction with any virtual element in the XR space.

Abstract: Stations (STAs) in the network transmit broadcast frames which incorporate sharing information about specific parameter settings in the basic service set (BSS). Updates are transmitted to the other STAs when parameter settings change, which include version information about the parameter settings. A STA receiving an update records version information, which is incorporated in any response or broadcast back to the transmitting station to indicate that the specific update was properly received. The transmitting STA can indicate which other STAs are to provide feedback to the update information. The sharing information, or indicated portions thereof, may be shared with overlapping BSS STAs as well.

Abstract: An artificial intelligent agent can act as a player in a video game, such as a racing video game. The game can be completely external to the agent and can run in real time. In this way, the training system is much more like a real world system. The consoles on which the game runs for training the agent are provided in a cloud computing environment. The agents and the trainers can run on other computing devices in the cloud, where the system can choose the trainers and agent compute based on proximity to console, for example. Users can choose the game they want to run and submit code which can be built and deployed to the cloud system. A resource management service can monitor game console resources between human users and research usage and identify experiments for suspension to ensure enough game consoles for human users.

Abstract: An adaptive set of RTA Adaptive EDCA rules and structures are provided to allow non-AP STAs to transmit RTA packets inside a R-TWT SP. The RTA Adaptive EDCA Parameter Set can be selected in response to receiving a trigger from the associated AP, or by pre-configuration. Non-AP STAs, as R-TWT member or non-member of the current R-TWT SP, can switch from using the regular EDCA parameters to the new RTA Adaptive EDCA parameters inside the R-TWT SP. Various rules are described for duration of use, while the AP can prevent STAs from using the new RTA Adaptive EDCA at any time inside of the R-TWT SP.

Abstract: A method for optimization of alignment of pixels of X different types on a sensor array for the performance of N different camera tasks, where X and N are integers greater than 1, includes obtaining an output of each of the X types of pixel on the sensor array for an input image; evaluating the quality of the output for each of the N different camera tasks; and obtaining an optimal pixel alignment pattern by adjustment of a potential pixel alignment pattern with respect to performance of the N different camera tasks subject to a user-determined balance of priorities among the N different camera tasks.

Abstract: In a MU-RTS TXS based P2P access allocation, there can be frames sent in legacy format (such as control frames in non-HT format) that do not carry a Basic Service Set Identification (BSSID) in its address fields. The Duration setting of the frames may cause a next station to be scheduled to set the basic NAV because the next station categorizes these frames as inter-BSS PPDUs. To prevent the next station from not responding to the AP's next allocation, the Duration setting of the frames are set so that they are not greater than the end time of the P2P allocation that occurs prior to the next allocation.