Intel Corporation

Apple Inc.

Oner Orhan

Hosein Nikopour

Shilpa Talwar

Eren Sasoglu

Wook Bong Lee

Arnaud Lucres Amadjikpe

Junyoung Nam

Stefano Pellerano

Susruth Sudhakaran

Peter Sagazio

Liang Xian

Benjamin Grewell

Claudio Da Silva

Roya Doostnejad

Brent Elliott

Navid Naderializadeh

Kameran Azadet

Bryan K Casper

Ofir Degani

Michael Genossar

Ashoke Ravi

Rotem Banin

Debabani Choudhury

Sidharth Dalmia

Albert Molina

Georgios Yorgos Palaskas

Duncan Kitchin

Saku Lahti

Igal Kushnir

Emanuel Cohen

Gadi Shor

Mikko S Komulainen

Jayprakash Thakur

Menashe Soffer

Ana M Yepes

Moshe Teplitsky

Mikhail T Galeev

Kunal Datta

Omer Asaf

Run Levinger

Eshel Gordon

Chintan S Thakkar

Erkan Alpman

Josef Hagn

Tawfiq Musah

Baljit Singh

Nebil Tanzi

Ron Pongratz

Amit Freiman

Eyal Goldberger

Yossi Tsfati

Shmuel Ravid

Kaushik Dasgupta

Eran Gerson

Noam Kogan

Marian K Verhelst

Meir Gordon

Nir Weisman

Anandaroop Chakrabarti

Miroslav Baryakh

Naftali Landsberg

Mikko M Lampinen

Lior Shakedd

Ra'anan Sover

Avi Tsarfati

Mehnaz Rahman

Shuhei Yamada

Anat Bazov

Stefano Brenna

Saeid Daneshgar Asl

Amr M Fahim

Shinwon Kang

Te Yu Kao

Resti Montoya Moreno

Nathan G Narevsky

Jing Zhu

Nageen Himayat

Yang-Seok Choi

Venkatesan Nallampatti Ekambaram

Tom Harel

Farhana Sheikh

Ehsan Aryafar

Adesoji J Sajuyigbe

Namyoon Lee

Carlos Cordeiro

Ping Wang

Bahareh Sadeghi

Christian Drewes

Hassnaa Moustafa

Feng Xue

Andreas Augustin

Stefan Mueller-Weinfurtner

Christopher Hull

Gregory W Chance

Brent R Carlton

Brandon R Davis

Peter Noest

Mustafa Akdeniz

Marcel Nassar

The present disclosure provides connection management techniques based on graph neural networks (GNN) and deep reinforcement learning (DRL) to optimize user association and load balancing. A graph structure of a communication network is considered for the GNN architecture and DRL is used to learn parameters of the GNN algorithm/model. Connection management is defined as a combinatorial graph optimization problem, and the DRL mechanism uses the underlying graph to learn weights of the GNN for an optimal user connections or associations. The connection management techniques can consider local network features to make better decisions to balance network traffic load while network throughput is also maximized. Implementations are provided based on edge computing frameworks include the Open RAN (O-RAN) architecture. Other embodiments may be described and/or claimed.

Graph neural network and reinforcement learning techniques for connection management

Millimeter-wave (mmWave) and sub-mmWave technology, apparatuses, and methods that relate to transceivers and receivers for wireless communications are described. The various aspects include an apparatus of a communication device including an antenna array and processing circuitry coupled to the antenna array. The processing circuitry is configured to initialize a beam tracking algorithm based on received signals received at the antenna array, wherein antenna phases used in the beam tracking are bound by an upper phase limit and a lower phase limit, to generate a beam tracking result. The processing circuitry is further configured to generate a calibration vector based on the beam tracking result and receive subsequent transmissions using a codebook adapted based on the calibration vector.

Beam management and antenna calibration in MIMO systems

A computing node to implement an RL management entity in an NG wireless network includes a NIC and processing circuitry coupled to the NIC. The processing circuitry is configured to generate a plurality of network measurements for a corresponding plurality of network functions. The functions are configured as a plurality of ML models forming a multi-level hierarchy. Control signaling from an ML model of the plurality is decoded, the ML model being at a predetermined level (e.g., a lowest level) in the hierarchy. The control signaling is responsive to a corresponding network measurement and at least second control signaling from a second ML model at a level that is higher than the predetermined level. A plurality of reward functions is generated for training the ML models, based on the control signaling from the MLO model at the predetermined level in the multi-level hierarchy.

Reinforcement learning (RL) and graph neural network (GNN)-based resource management for wireless access networks

Millimeter wave (mmWave) technology, apparatuses, and methods that relate to transceivers, receivers, and antenna structures for wireless communications are described. The various aspects include co-located millimeter wave (mmWave) and near-field communication (NFC) antennas, scalable phased array radio transceiver architecture (SPARTA), phased array distributed communication system with MIMO support and phase noise synchronization over a single coax cable, communicating RF signals over cable (RFoC) in a distributed phased array communication system, clock noise leakage reduction, IF-to-RF companion chip for backwards and forwards compatibility and modularity, on-package matching networks, 5G scalable receiver (Rx) architecture, among others.

Wireless communication technology, apparatuses, and methods

A receiver circuit associated with a communication device is disclosed. The receiver circuit comprises a digital data compression circuit configured to receive a plurality of digital receive signals derived from a plurality of analog receive signals respectively associated with the receiver circuit. The digital data compression circuit is further configured to compress the plurality of digital receive signals to form one or more compressed digital data signals based thereon, to be provided to an input output (I/O) interface associated therewith. In some embodiments, a compressed digital signal dimension associated with the one or more compressed digital data signals is less than a digital signal dimension associated with the plurality of digital receive signals.

Low power mmWave receiver architecture with spatial compression interface

An apparatus, method and computer readable medium for special thermal density reduction by antenna thinning. A system comprises N transmit/receive (TX/RX) chains, where each TX/RX chain comprises an RFFE and each RFFE comprises one or more thermal sensors configured to measure heat in the RFFE. An antenna array coupled to the plurality of TX/RX chains. A codebook that comprises a plurality of code words configured to respond to real-time heat measurements from the thermal sensors in each TX/RX chain is configured to switch off selected TX/RX chains to reduce thermal density at the antenna array while maintaining M RFFEs switched on, where M<N and the desired beamforming gain is 10 log 10(M).

Spatial thermal density reduction for MMWAVE antenna arrays

A transmitter for chip to chip communication may include a modulator and a transmit frequency converter. The modulator may modulate a first received signal according to a first modulation scheme. The modulator may also modulate a second received signal according to a second modulation scheme. The transmit frequency converter may center the first received signal on a first frequency that does not comprise a phase within a radio frequency (RF) domain to generate a first centered signal. The transmit frequency converter may also center the second received signal on a second frequency that comprises a phase within the frequency band to generate a second centered signal. The second centered signal may be orthogonal to the first centered signal. A frequency gap may be positioned between the first centered signal and the second centered signal within the frequency band.

Wireless chip to chip communication with selective frequency multiplexing with different modulation schemes

A communication device including one or more processors configured to determine a first signal component of a received modulated signal; determine a second signal component of the received modulated signal; generate a phase shift of the first signal component; generate a phase shift of the second signal component; compare the phase shift of the first signal component and the phase shift of the second signal component with each other; and generate a plurality of constellation points, wherein each of the plurality of constellation point is based on the determination of the first signal component, the determination of the second signal component, and the comparison.

Methods and devices for signal demodulation

Millimeter-wave (mmWave) and sub-mmWave technology, apparatuses, and methods that relate to transceivers and receivers for wireless communications are described. The various aspects include an apparatus of a communication device including one or more antennas configured to receive an RF signal and an ADC system. The ADC system includes a 1-bit ADC configured to receive the RF signal, and an ADC controller circuitry configured to measure a number of positive samples in the received RF signal for a plurality of thresholds of the 1-bit ADC, estimate receive signal power associated with the received RF signal based on the measured number of positive samples, determine a direct current (DC) offset in the received RF signal using the estimated received signal power, and adjust the received RF signal based on the determined DC offset.

Equalization and estimation processing in wireless devices

A mobile communication device that is configured to cancel interference within received millimeter wave band signals. The device includes a receiver circuit that is configured to receive a millimeter wave band signal, adjust gain provided to the millimeter wave band signal at a first amplifier, cancel interference in millimeter wave band signal after gain is adjusted by the first amplifier, and adjust gain provided to the millimeter wave band signal at a second amplifier after interference is cancelled.

Millimeter wave (mmWave) system and methods

Apparatuses of a user equipment (UE), a cellular base station, and radio access network (RAN) nodes are disclosed. An apparatus of a wireless communication device includes circuitry configured to measure reference signals received from a plurality of antennas of an other wireless communication device, and circuitry configured to cause one or more antennas of the wireless communication device to transmit information regarding the received reference signals back to the other wireless communication device to enable the other wireless communication device to estimate a utility function for different transmit parameter sets.

Management of MIMO communication systems

Millimeter wave (MMWAVE) system and methods

Aspects of mmWave beam tracking and beam sweeping are described, for example, spatial searching operations, directional beam forming, complex channel measurement operations, and adaptive power savings. Some aspects include using priori information for mmWave beam tracking and beam sweeping. Some aspects include using priori information to modify a superset of beam criteria to obtain a subset of beam criteria, select a spatial region according to the subset of beam criteria, and initiate a spatial searching operation within the spatial region for establishing a communication link. Some aspects include obtaining complex channel measurements of beams and combining the measurements with priori information to determine a beam for use in a communication link. Some aspects include providing signals from Nover Kinput/output (IO) links and receiving signals over KIO links, and combining signals received over the KIO links, using a compression matrix, to generate signals over K IO links.

Millimeter wave beam tracking and beam sweeping

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San Jose, CA, United States of America

Oner Orhan