Apple Inc.

Nxp USA, Inc.

Freescale Semiconductor,inc.

Other

Nxp B.v.

Wisconsin Alumni Research Foundation

Jayakrishnan Cheriyath Mundarath

Jayesh H Kotecha

Leo G Dehner

James Wesley McCoy

Peter Zahariev Rashev

Ning Chen

Eric J Jackowski

Mir Adeel Masood

Michael Andrew Fischer

Ryan Haoyun Wu

Kevin B Traylor

Maik Brett

Oded Yishay

Barry Van Veen

Robert Bahary

Sili Lu

Kevin Bruce Traylor

Pornchai Pawawongsak

Ahmed Hossny Anis Elsamadouny

Parmeswaran Ramanathan

Zhiyu Cheng

James W Mccoy

James Mccoy

A wireless communication system non-collaborative, multiple input, multiple output (MIMO) space division multiple access (SDMA) system determines subscriber station combining and weighting vectors that yield a high average signal-to-interference plus noise ratio (SINR). Each subscriber station independently transmits information to a base station that allows the base station to determine a weight vector wfor each subscriber station using the determined combining vector of the subscriber station. The icombining vector corresponds to a right singular vector corresponding to a maximum singular value of a channel matrix between a base station and the isubscriber station. Each subscriber station transmits signals using a weight vector, which corresponds to a left singular vector corresponding to a maximum singular value of a channel matrix between the isubscriber station and the base station. The base station uses the weight vector wto determine the signal transmitted by the isubscriber station.

Beamforming for non-collaborative, space division multiple access systems

A millimeter-wave wireless multiple antenna system () and method () are provided in which a UE () uses a multi-antenna subsystem () to identify a plurality of m strongest transmit beams () from the base station () based on power measurements of a plurality of synchronization signal blocks (SSBs) transmitted on a corresponding plurality of transmit beams by the base station (), and to generate a composite uplink random access channel (RACH) preamble () that is sent () to the base station () to identify the plurality of m strongest transmit beams and relative weights for each of the plurality of m strongest transmit beams which are used by the base station () to generate an optimal downlink transmit beam for use in sending a RACH response to the UE ().

Optimal beamforming in millimeter-wave cellular networks using a single composite random access preamble

Embodiments are disclosed that for synthetic aperture radar (SAR) systems and methods that process radar image data to generate radar images using vector processor engines, such as single-instruction-multiple-data (SIMD) processor engines. The vector processor engines can be further augmented with accelerators that vectorize element selection thereby expediting memory accesses required for interpolation operations performed by the vector processor engines.

Systems and methods for synthetic aperture radar with vector processing

Various methods of allocating uplink control channels in a communication system are implemented at a resource scheduler or a user equipment (UE). In one method the scheduler reserves resources for a downlink data channel and signals a corresponding downlink data channel grant and also reserves resources for a persistent uplink control channel for a longer duration than the data channel grant. Signaling overhead associated with a grant for this persistent uplink control channel is reduced over a full dynamic grant. A predetermined rule can be used at the scheduler and at the UE to avoid overhead signaling associated with a grant for this persistent control channel. Predetermined rules at the UE and scheduler can also be used to reserve appropriate resources and select appropriate MCS levels for control information and the control information and uplink data can be transported over a common uplink channel when a time overlap occurs between an uplink data channel and the persistent control channel.

Uplink control channel allocation in a communication system and communicating the allocation

A processor including a pointer storage that stores pointer descriptors each including addressing information, an arithmetic logic unit (ALU) configured to execute an instruction which includes operand indexes each identifying a corresponding pointer descriptor, multiple address generation units (AGUs), each configured to translate addressing information from a corresponding pointer descriptors into memory addresses for accessing corresponding operands stored in a memory, and a smart cache. The smart cache includes a cache storage, and uses the memory addresses from the AGUs to retrieve and store operands from the memory into the cache storage, and to provide the stored operands to the ALU when executing the instruction. The smart cache replaces a register file used by a conventional processor for retrieving and storing operand information. The pointer operands include post-update capability that reduces instruction fetches. Wasted memory cycles associated with cache speculation are avoided.

Processor with smart cache in place of register file for providing operands

A wireless multiple antenna system () uses a multi-antenna subsystem () to generate a composite sample waveform by continuously sweeping a plurality of receive beams (RX-RXM) during each SSB transmission in a plurality of transmit beams (TX-TX), generating a composite received signal strength metric value from a batch of samples collected over the plurality of receive beams to determine the presence of the SSB, and then jointly searching the composite sample waveform for an optimal receive beam and an SSB frequency of any detected SSB that are used by the UE () to perform a cell search which matches a transmit beam from the base station () to the optimal receive beam.

Fast and robust cell search for 5G and millimeter-wave wireless communication systems using joint frequency raster and receive beam search

A millimeter-wave wireless multiple antenna system () and method () are provided in which a UE () uses a multi-antenna subsystem () to identify a plurality of m strongest transmit beams () from the base station () based on power measurements of a plurality of synchronization signal blocks (SSBs) transmitted on a corresponding plurality of transmit beams by the base station (), and to generate multiple uplink random access channel (RACH) preambles () that is sent () to the base station () to identify the plurality of m strongest transmit beams and relative weights for each of the plurality of m strongest transmit beams which are used by the base station () to generate an optimal downlink transmit beam for use in sending a RACH response to the UE ().

Optimal beamforming in millimeter-wave cellular networks using multiple random access preambles

A method and apparatus (A) are provided for multiplexing data and uplink control bitstreams on a 5G-NR uplink by generating a multiplexing configuration structure with one or more processors () and supplying the data and uplink control bitstreams to a multiplexing engine () which includes an index calculation logic circuit () and multiplex selector circuit (), where the index calculation logic circuit is configured with the multiplexing configuration structure (CONFIG) to execute an iterative data-control multiplexing algorithm which generates ordered selection indices in sequential order (MUX_SEL), and where the multiplex selector circuit receives and selects m-bit sequences from the data bitstream and one or more uplink control bitstreams for output into a multiplexed output stream according to the ordered selection indices generated by the index calculation unit, where m is an integer greater than or equal to 1.

Efficient engine and algorithm for control and data multiplexing/demultiplexing in 5G NR devices

A mechanism is provided for detecting and decoding a primary broadcast channel transmitted by a base station at a user equipment device. Embodiments improve performance and robustness over prior methods for detecting and decoding by determining a channel differential metric for channel estimates derived based on each candidate demodulation reference symbol (DMRS) sequence and selecting a set of top DMRS sequence candidates using the associated channel differential metrics. From the set of top DMRS candidates, a best DMRS candidate, and consequently, the three least significant bits of the beam index, can be determined.

Efficient detection of primary broadcast channel in 5G-NR

A base station is configured to provides a beam change feedback channel for a user equipment to communicate unsolicited beam change feedback to the base station. If the user equipment determines that a beam other than the beam to which the user equipment is tuned has a stronger signal, the user equipment initiates a transmission on the beam change feedback channel to the base station indicating a beam change. The base station uses the feedback from the user equipment to update the beam to the user equipment.

Beam tracking in wireless communication

A millimeter-wave wireless multiple antenna system () is provided in which a UE () uses a multi-antenna subsystem () to sweep a plurality of receive beams (RX-RXM) during each transmit beam in a plurality of transmit beams (TX-TX) used by the base station () to transmit an SSB, and then generates, for each receive beam, a received signal strength indicator (RSSI) value from samples of each transmitted SSB measured in said receive beam, thereby generating a plurality of RSSI values from which an optimal receive beam is selected based on a ranking of the RSSI values and then used to lock the UE () onto the optimal receive beam to perform a cell search which matches a transmit beam from the base station () to the optimal receive beam.

Method and apparatus for fast and robust cell search for 5G and millimeter-wave wireless communication systems

In accordance with at least one embodiment, a processor system is disclosed having a SIMD processor device that has a plurality of subsidiary processing elements that are controlled to process multiple data concurrently. In accordance with at least one embodiment, the SIMD processor is a vector processor (VPU) having a plurality of vector Arithmetic Units (AUs) as subsidiary processing elements, and the VPU executes an instruction to transfer table information from a global memory of the VPU to a plurality of local memories accessible by each AU. The VPU also executes an instruction that results in each processing element performing a table lookup from a table stored at its local memory. In response to the instruction, this table lookup uses a portion of a lookup value to access information from the table, and uses another portion of the lookup information to calculate an interpolated resultant based upon the accessed information.

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Austin, TX, United States of America

Jayakrishnan Cheriyath Mundarath