Intel Corporation

University of Texas System

Samsung Electronics Co., Ltd.

Rearden Corporation

Iospan Wireless, Inc.

Huawei Technologies Co., Limited

Future Wei Technologies, Inc.

Huawei Technologies Canada Co., Ltd.

Other

Intellectual Ventures Holding 40 LLC

Iospan Wirless, Inc.

Gigabit Wireless, Inc.

Robert Wendell Heath, Jr

Arogyaswami J Paulraj

Peroor K Sebastian

Chan-Byoung Chae

Rahul Chopra

Jong-Hyung Kwun

Antonio Forenza

David J Gesbert

Rajeev Krishnamoorthy

Stephen G Perlman

Severine E Catreux

Roger Van Der Laan

John Speck

Jose Tellado

In-Soo Hwang

Kien Trung Truong

Peiying Zhu

Hosein Nikopour

Tao Wu

David Mazzarese

Takao Inoue

Ali Yazdan Panah

Jianglei Ma

Ming Jia

Shilpa Talwar

Hongseok Kim

Sung-hyun Cho

Eun-Seok Ko

Seijoon Shim

Sang-hyun Kim

Eun Seok Ko

Sei-Joon Shim

Taiwen Tang

Gustavo De Veciana

Manish Airy

Jihoon Choi

Helmut B&ouml;lcskei

Jeff Andrews

Jin-Sam Kwak

A method for improved efficiency for massive MIMO adaptation. In an embodiment, method for operating a network component in a massive MIMO network includes obtaining, by the network component, one or more network parameters; determining, by the network component, a number of active antennas in a massive MIMO AP to use for transmitting in one time frame according to the one or more network parameters, the number of active antennas selected being less than a total number of antennas available in the massive MIMO AP; and serving one or more UEs using the determined number of active antennas. Other embodiments reduce the number of beamformers utilized according to network parameters. In still other embodiments, a number of data streams to transmit and a corresponding number of users to be served in a time frame by a massive MIMO AP is reduced.

Systems and methods for massive MIMO adaptation

A method for compressive channel estimation in a massive multiple input, multiple output (MIMO) system using sectored random beams is provided. In an embodiment, a method in a massive multiple input, multiple output (MIMO) transceiver for channel estimation includes obtaining a sector. The sector includes less than a complete coverage area of the transceiver. The method also includes transmitting, by the transceiver, a plurality of random beams to a user equipment (UE) in the sector.

Sectored random beams for compressive channel estimation in massive MIMO

Method and apparatus for downlink (DL) channel estimation in massive MIMO are provided. A base station (BS) support massive MIMO may select a dictionary for a user equipment (UE) in its cell and transmit information for constructing the dictionary to the UE. The UE constructs the dictionary based on the information received and performs compressed sensing (CS)-based DL channel estimation for the BS. The UE also sends feedback information to the BS, which include information that is useful for determination of the dictionary by the BS.

Method and apparatus for downlink channel estimation in massive MIMO

It is possible to reduce the overhead associated with downlink channel estimation in massive Multiple-Input-Multiple-Output (MIMO) networks by processing training sequences according to a transformation matrix. The transformation matrix maps a generic dictionary to a non-generic dictionary associated with an antenna geometry of a MIMO antenna array. The transformation matrix can be computed based on the two dictionaries. In one embodiment, the training reference signal is precoded to obtain a precoded training reference signal, which is then transmitted over a MIMO antenna array. The training precoder used to precode the training reference signal is designed according to the transformation matrix to mitigate a dependence that the training reference signal transmission has on the antenna geometry.

System and method for downlink channel estimation in massive multiple-input-multiple-output (MIMO)

The present invention provides methods and apparatus for implementing spatial multiplexing in conjunction with the one or more multiple access protocols during the broadcast of information in a wireless network. One example includes transmitting a first and a second data signal to a remote unit from a respective first and a second spatially separate antenna of a base station so that the first and second data signals have a first spatial configuration, determining that the first and the second data signals are not spatially separated by the remote unit, reconfiguring the (spatial multiplexing logic) spatial configuration of the first and second data signals to a second spatial configuration, and transmitting a third and fourth data signal to the remote unit from a second different antenna configuration according to the second spatial configuration.

Spatial multiplexing in a cellular network

A wireless communications system is presented that adapts its mode of operation between spatial and non-spatial multiplexing in response to transmission-specific variables. Mode determination logic determines, in response to a received signal, if spatial or non-spatial multiplexing should be used to transmit a subscriber datastream between the BTS and the UE. The mode determination logic receives a measure of a transmission characteristic of the signal, compares the transmission characteristic to a transmission characteristic threshold and selects either spatial or non-spatial multiplexing in response to the comparison. The transmission characteristic includes at least one of delay spread, post-processing signal-to-noise ratio, CRC failure, residual inter-symbol interference, mean square error, coherence time, and path loss.

Wireless communications system that supports multiple modes of operation

Embodiments of a base transceiver station and method for transmitting are described herein. In some embodiments, data is transmitted over a downlink channel in accordance with a selected one of a plurality of transmission modes. The base transceiver station may be configurable to transmit data in accordance with each of the transmission modes. One of the transmissions modes may be selected for the data transmission based at least in part on feedback reported by a subscriber unit. The transmission modes include at least a single antenna mode, a transmit diversity mode, and a spatial multiplexing mode.

The present invention provides methods and apparatus for implementing spatial multiplexing in conjunction with the one or more multiple access protocols during the broadcast of information in a wireless network. A subscriber unit for use in a cellular system is disclosed. The subscriber unit includes: spatially separate receivers, a spatial processor, and a combiner. The spatially separate receivers receive the assigned channel composite signals resulting from the spatially separate transmission of the subscriber downlink datastream(s). The spatial processor is configurable in response to a control signal transmitted by the base station to separate the composite signals into estimated substreams based on information obtained during the transmission of known data patterns from at least one of the base stations. The spatial processor signals the base stations when a change of a spatial transmission configuration is required. The combiner combines the estimated substreams into a corresponding subscriber datastream.

Techniques for transmitting data over a communications channel are generally described. A value of a property of an inverse of a channel matrix corresponding to the communications channel may be calculated and compared to a threshold value. If the value of the property a first one of greater than or less than the threshold value, at least one transmit message may be altered using a vector perturbation technique to generate data symbols and the data symbols may be precoded using a channel inversion technique to generate precoded data symbols. If the value of the property is the other of greater than or less than the threshold value, the at least one transmit message may be precoded using a channel inversion technique to generate precoded data symbols.

Transmitting data over a communications channel

Examples are generally described that include methods for selecting a transmit mode in a communications system. An example method may include calculating a first transmission rate for data in a multiple-input multiple-output mode of the communications system and calculating a second transmission rate for the data in a single-input multiple-output mode of the communications system. A mode may be selected from the group consisting of the multiple-input multiple-output mode and the single-input multiple-output mode based, at least in part, on an energy consumption of the first and second transmission rates. Data may be transmitted from a transceiver in the communications system using the selected mode.

Methods and communication systems having adaptive mode selection

Techniques are generally described here for communicating channel state information using predictive vector quantization. In some examples, a method may include measuring channel state information based, at least in part, on signals received over a communications channel. An error vector may be calculated between the measured channel state information and predicted channel state information. The error vector may be quantized, and subsequent channel state information may be predicted based, at least in part, on the quantized error vector.

Communicating channel state information using predictive vector quantization

A system and method is proposed for progressively quantizing channel state information for application in a MIMO (multiple input multiple output) communication system. A method includes computing an estimate of a communications channel between a subscriber unit and a base station, quantizing the estimate with a first codebook, thereby producing a first quantized estimate, quantizing an (n&#x2212;1)-th quantized estimate with an n-th codebook, thereby producing an n-th quantized estimate, where n is an integer value ranging from 2 to R, R is a total number of quantizations of the estimate, wherein the n-th codebook is a localized codebook. The method also includes incrementing n, repeating the quantizing an (n&#x2212;1)-th quantized estimate until n=R, and transmitting information based on the R quantized estimates to the base station.

Progressive feedback for high resolution limited feedback wireless communication

Examples are generally described that include transmission methods including inserting at least a portion of data from a first data stream into a second data stream to be transmitted over a communications channel. On receipt of the two data streams, examples of receiving methods include receiving the replicated data, decoding the replicated data using an estimated channel matrix, and generating an updated estimate of the channel matrix based, at least in part, on the replicated data.

Inserting and decoding replicated data symbols in wireless communications

Growing community of inventors

Austin, TX, United States of America

Robert Wendell Heath, Jr