Systems and methods of beam-training a phased array antenna

Abstract

A method for beam-training a phased array antenna, including: transmitting, from the phased array antenna, one or more probing beams; receiving, at one or more receivers, the one or more probing beams; determining, based on the received one or more probing beams, a correlation between each transmitted preamble signal and each received preamble signal; determining, based on the correlation between each transmitted preamble signal and each received preamble signal, one or more signal paths; determining a channel impulse response (CIR) value for each of the one or more signal paths; determining, based on the CIR value for each of the one or more signal paths, a direction corresponding to each of the one or more signal paths; and generating, from the phased array antenna, a subsequent beam based on a complex gain corresponding to a signal path of the one or more signal paths.

Description

SYSTEMS AND METHODS OF BEAM-TRAINING A PHASED ARRAY ANTENNACROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 644,887, filed on May 9, 2024, the entire contents of which are incorporated herein by reference.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was made with government support under grant / contract nos. 2112471, 2007581, and 2128567 awarded by the National Science Foundation. The government has certain rights in the invention.BACKGROUND

[0003] The availability of large bandwidth in mmWave frequency bands (e.g., 30-300GHz) may facilitate higher data rates. There exists a demand for high data rates, for example in virtual and augmented reality, high-definition video streaming, and remote healthcare. Communication standards like IEEE 802.11 wireless LAN and 5G networks may also incorporate mmWave technologies, thereby increasing demand.

[0004] However, the high path loss in mmWave frequency bands poses significant challenges. In mmWave communications, beamforming may at least partially compensate for high path loss. For example, a transmitter (TX) may align its beam with a receiver (RX) through a beam-training process before data transmission. Conventional beam-training methods may have drawbacks such as lower signal-to-noise ratios (SNRs), reduced beam selection (e.g., for example with discrete codebooks), larger beam-training overhead (e.g., especially in larger-scale antenna arrays, across multiple users, etc.), lack of generalizability (e.g., due to a need for specialized hardware, etc.), and / or the like. Accordingly, there is a need for beam training systems and methods that address one or more shortcomings of conventional systems / methods.SUMMARY

[0005] In some aspects, the techniques described herein relate to a method for beam-training a phased array antenna, including: transmitting, from the phased array antenna, one or more probingbeams in one or more directions, wherein each probing beam includes a preamble signal; receiving, at one or more receivers, the one or more probing beams; determining, based on the received one or more probing beams, a correlation between each transmitted preamble signal and each received preamble signal; determining, based on the correlation between each transmitted preamble signal and each received preamble signal, one or more signal paths; determining a channel impulse response (CIR) value for each of the one or more signal paths; determining, based on the CIR value for each of the one or more signal paths, a direction corresponding to each of the one or more signal paths; and generating, from the phased array antenna, a subsequent beam based on a complex gain corresponding to a signal path of the one or more signal paths.

[0006] In some aspects, the phased array antenna applies a phase shift to each probing beam of the one or more probing beams and wherein phase shifts of the one or more probing beams are randomly selected from a distribution of phase shifts. In some aspects, the distribution of phase shifts is a uniform distribution including at least 0, 7t / 2, 7t, and 3TT / 2. In some aspects, the method further includes transmitting, from the one or more receivers to the phased array antenna via a single feedback packet, the correlation between one or more transmitted preamble signals and one or more corresponding received preamble signals. In some aspects, determining the one or more signal paths includes identifying a signal path based on a time of flight (ToF). In some aspects, the correlation between each transmitted preamble signal and each received preamble signal includes a peak and wherein determining the one or more signal paths includes: sorting peaks according to their ToF; and identifying peaks from the sorted peaks that correspond to a path of the one or more signal paths. In some aspects, identifying the peaks that correspond to the path of the one or more signal paths includes: comparing a time difference between each of the peaks to a threshold; and identifying the peaks based on the comparison. In some aspects, the method further includes determining a steering vector for the phased array antenna based on an array geometry of the phased array antenna. In some aspects, the direction corresponding to each of the one or more signal paths is determined based on the CIR value for each of the one or more signal paths and the steering vector. In some aspects, the method further includes transmitting, from the phased array antenna, an additional probing beam to capture a CIR from at least one of the one or more signal paths; and identifying, from the CIR from the one or more signal paths, a CIR that captures all signal paths. In some aspects, the subsequent beam is optimized based on the complex gain. In some aspects, the direction corresponding to each of the one or more signal paths is determined using a compressive sensing (CS) algorithm.

[0007] In some aspects, the techniques described herein relate to a mmWave device including: a phased array antenna; and a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the mmWave device to: transmit, from the phased array antenna, one or more probing beams in one or more directions, wherein each probing beam includes a preamble signal; receive, from one or more devices, at least one measurement corresponding to the one or more probing beams; determine, based on the at least one measurement, a correlation between each transmitted preamble signal and each received preamble signal; determine, based on (i) the correlation between each transmitted preamble signal and each received preamble signal and (ii) a time of flight (ToF) value, one or more signal paths; determine a channel impulse response (CIR) value for each of the one or more signal paths; determine, based on the CIR value for each of the one or more signal paths, a direction corresponding to each of the one or more signal paths; and determine an optimized beam usable for a subsequent transmission based on a complex gain corresponding to a signal path of the one or more signal paths, wherein the optimized beam has a signal -to-noise ratio (SNR) that is greater than an average SNR of the one or more probing beams.

[0008] In some aspects, the correlation between each transmitted preamble signal and each received preamble signal includes a peak and wherein determining the one or more signal paths includes: sorting peaks according to their ToF; and identifying peaks from the sorted peaks that correspond to a path of the one or more signal paths. In some aspects, identifying the peaks that correspond to the path of the one or more signal paths includes: comparing a time difference between each of the peaks to a threshold; and identifying the peaks based on the comparison.

[0009] In some aspects, the techniques described herein relate to a method including: determining path directions using a compressive sensing (CS) algorithm; determining complex gains for each path angle; and deriving an optimal beam.

[0010] In some aspects, the techniques described herein relate to a method, wherein the CS algorithm measures a mmWave channel by sending pseudorandom beams to send preamble signals in different directions. In some aspects, the method further includes receiving probing beams; and calculating a correlation value between a received signal and a transmitted preamble. In some aspects, per-path channel amplitude and phase are estimated by: removing a directional from a transmit beam; estimating the amplitude ak for each path; and canceling Carrier Frequency Offset (CFO) within each beam. In some aspects, the method further includes determining a time- of-flight (ToF) to distinguish paths.BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other aspects and features of the present disclosure will become more apparent to those skilled in the art from the following detailed description of the example embodiments with reference to the accompanying drawings.

[0012] FIG. 1 is a block diagram of a wireless communication network including a mmWave device, according to an exemplary embodiment.

[0013] FIG. 2 is a schematic illustration of signal propagation between a TX and an RX, according to an exemplary embodiment.

[0014] FIG. 3 is a flow diagram illustrating a method of beam training a phased array antenna, according to an exemplary embodiment.

[0015] FIG. 4A is a schematic illustration of spatial probing to sample a multipath channel, according to an exemplary embodiment.

[0016] FIG. 4B is an example illustration of identifying paths based on peaks of a channel impulse response (CIR).

[0017] FIG. 4C is an example illustration of determining path directions, determining relative complex gains among the paths, and determining an optimal beam based on the path directions.DETAILED DESCRIPTION

[0018] Referring generally to the FIGURES, described herein are systems and methods of calibrating a phased array antenna. Systems and methods of the present disclosure may facilitate determining a direction for a signal path, determining complex gains that achieve the signal path, and using these parameters to determine an optimal beam (e.g., a beam having a low SNR, etc.). Systems and methods of the present disclosure may reduce the search space for determining path parameters, thereby reducing the amount of computation and time required for beam training, especially for large antenna arrays.

[0019] A path with an angle of departure (AoD) of 9 and a complex gain of ae7^ may result in an observed channel of h =where g(9) represents the directional gain of the transmit beam. Thus, the observed channel is a function of the gain of the physical path and the directional gain of the employed beam.

[0020] In brief, systems and method of the present disclosure may (i) leverage the high sampling rate of mmWave to separate paths in time domain for each probing beam, (ii) utilize compressive sensing (CS) to identify path angles from measurements for each separated path, (iii) determine complex gains for each path angle, and / or (iv) compute an optimized beam. In various embodiments, systems and methods of the present disclosure provide one or more benefits over conventional systems. For example, systems and methods of the present disclosure may increase the speed of beam training by three or more orders of magnitude.

[0021] Systems and methods of the present disclosure may address needs in various contexts such as telecommunications (e.g., in 5G and future wireless networks), virtual and augmented reality (e.g., where bandwidth and latency requirements may be high), autonomous vehicles (e.g., where real-time communication may be required for autonomous driving or vehicle-to-everything (V2X) communications, etc.), and / or remote healthcare (e.g., where remote diagnostics and patient monitoring may require high-definition video streaming and real-time data transmission, etc.).

[0022] The system and methods described herein may address one or more shortcomings of conventional systems by reducing a complexity and / or overhead (e.g., time, cost, etc.) of antenna calibration and may enable calibration in everyday communication scenarios (e.g., such as in homes, offices, or urban areas, etc.). Rather than rely on specialized calibration equipment, systems and methods of the present disclosure may enable calibration using everyday devices such as cellphones that may not necessarily have been previously calibrated themselves.

[0023] Turning now to FIG. 1, wireless communication network 100 is shown, according to an exemplary embodiment. Wireless communication network 100 may enable transmission / receipt of data between two or more systems / devices. As an example, wireless communication network 100 may be a fifth-generation (5G) network including base stations (BSs), such as a 5G base station (5G Node B (gNB)) or an enhanced Node B (eNB) for long term evolution (LTE) communication. Wireless communication network 100 may include, but is not limited to, radio access networks (RANs), a core network, a public switched telephone network (PSTN), the Internet, and other networks (e.g., private and / or public data-packet networks, corporate intranets, etc.).

[0024] Wireless communication network 100 is shown to include one or more receiving device(s) 110 and one or more mmWave device(s) 120. mmWave device(s) 120 may be, include, or form part of a BS. For example, mmWave device(s) 120 may provide wireless communication coverage to receiving device(s) 110 such that each receiving device(s) 110 can be communicatively linkedto one or more other receiving device(s) 110. Receiving device(s) 110 are configured to communicate in wireless communication network 100 by transmitting and receiving wireless signals. Receiving device(s) 110 may be or include one or more devices such as mobile phone(s) 112, vehicle(s) 114, user equipment (UE) 116, and / or loT device(s) 118. Additionally or alternatively, receiving device(s) 110 may be or include any suitable device such as a wireless transmit / receive unit, a mobile station, a fixed or mobile subscriber unit, a pager, a cellular telephone, a personal digital assistant (PDA), a smartphone, a laptop, a computer, a touchpad, a wireless sensor, wearable devices, and / or consumer electronics device.

[0025] In various embodiments, receiving device(s) 110 facilitate beam training mmWave device(s) 120. For example, receiving device(s) 110 may include one or more antennae and may be capable of establishing a connection with mmWave device(s) 120 (e.g., directly and / or indirectly such as through another network / connection) to transmit information to mmWave device(s) 120 (e.g., a measurement such as a reference signal received power (RSRP), a reference signal received quality (RSRQ), a received signal strength (RSS) measurement, measurements associated with one or more probing beams, and / or the like). In various embodiments, receiving device(s) 110 may include a processor and / or memory. The memory may have instructions stored thereon that, when executed by the processor, cause receiving device(s) 110 to perform one or more operations as described herein. For example, the instructions may cause receiving device(s) 110 to perform one or more steps of method 300.

[0026] In various embodiments, mmWave device(s) 120 are capable of beamforming (i.e., the use of multiple antennas to control the direction of a wavefront by appropriately weighting the magnitude and phase of individual antenna signals, etc.). In some embodiments, beam training increases the effectiveness of beamforming by mmWave device(s) 120 (e.g., increases a SNR, etc.).

[0027] mmWave device(s) 120 may include one or more antenna(s) 130, phase shift register(s) 140, and / or processing circuit(s) 150. Additionally or alternatively, mmWave device(s) 120 may include other components such any suitable structure for generating signals for wireless transmission (e.g., a transmitter, etc.) and / or any suitable structure for receiving and / or processing signals (e.g., a transceiver, digital signal processor, control electronics, etc.).

[0028] Antenna(s) 130 may include one or more antenna element(s) 132. One or more antenna elements of antenna element(s) 132 may be associated with a relative gain. The relative gain maybe inherent to the antenna element. The relative gain include a relative amplitude deviation and / or a relative phase deviation.

[0029] Phase shift register(s) 140 may be configured to impart a phase shift on a signal transmitted from antenna element(s) 132. In various embodiments, each antenna element of antenna element(s) 132 is associated with a phase shift register of phase shift register(s) 140. The phase shift imparted by phase shift register(s) 140 may correspond to a value stored in an / / -bit register. For example, a 2 -bit register may store values corresponding to a phase shift of 0, pi / 2, pi, and / or 3pi / 2. A signal transmitted from each antenna element of antenna element(s) 132 may be the product of a complex weight (e.g., as determined based on the phase shift applied by each phase shift register(s) 140, etc.) and a relative gain. The complex weight may include an amplitude and / or a phase shift. The phase shift may be controlled by phase shift register(s) 140. The amplitude may be controlled by a signal generator such as a transmitter. Phase shift register(s) 140 may be configured to individually control the phase shift applied to each of antenna element(s) 132.

[0030] Processing circuit(s) 150 may include one or more processor(s) 152 and / or one or more memory(s) 154. Processor(s) 152 may implement various processing operations of mmWave device(s) 120. For example, processor(s) 152 can perform signal coding, data processing, power control, input / output processing, antenna calibration, or any other functionality enabling mmWave device(s) 120 to operate in a wireless communication system. Processor(s) 152 can include any suitable processing or computing device configured to perform one or more operations. For example, processor(s) 152 can include a microprocessor, microcontroller, digital signal processor, field programmable gate array, or application-specific integrated circuit.

[0031] Memory(s) 154 can include any suitable volatile and / or non-volatile storage and retrieval device, and any suitable type of memory can be used, such as random-access memory (RAM), read-only memory (ROM), hard disk, optical disc, subscriber identity module (SIM) card, memory stick, secure digital (SD) memory card, and the like. In various embodiments, memory(s) 154 having instructions stored thereon that, when executed by processor(s) 152, cause processing circuit(s) 150 to perform one or more operations as described herein. For example, the instructions may cause processing circuit(s) 150 to perform one or more steps of method 300.

[0032] Turning now to FIG. 2, a schematic illustration of signal propagation between a TX and an RX are shown, according to an exemplary embodiment. The TX may include a phased array antenna having N elements. The TX may apply various complex gains, including phase shifts andamplitudes, to each antenna element to form a beam in a specific direction. As used herein, the combination of complex gains is referred to as a beam. The transmitted signals may travel through the wireless channel and may reflect off one or more obstacles to arrive at the RX. The RX may include a phased array antenna. The RX may apply a receive beam to the antenna to boost the received signal. For example, the received signal at the RX may be represented as: y ~ a** Hvx 4- u n where v represents the transmit beam, u represents the receive beam, y represents the received signal at the RX, x represents the transmitted signal from the TX, n represents noise, and H represents the mmWave channel. A CIR may be represented as:where |p2| represents the received signal strength (RSS). Systems and methods of the present disclosure may facilitate increasing and / or maximizing the RSS by optimizing v to the optimal beam. The optimal beam may be determined according to:

[0033] In various embodiments, determining the optimal beam includes (i) determining path directions and (ii) determining the optimal beam based, at least in part, on the path directions.

[0034] In various embodiments, systems and methods of the present disclosure facilitate determining uffH (i.e., the transmitting channel viewed by the TX). The transmitting channel may be represented as a set of elements along paths between the TX and RX:where K represents the number of paths, ht represents the channel complex gain along the k&path, g,() represents the steering vector function at the TX, and gf() represents the steering vector function at the RX. The AoA for the k^ path may be determined by (i / >z,and the AoD for the A111path may be determined by (0^z, 0^). In various embodiments, the RX uses a fixed beam u during TX beam training.

[0035] Turning now to FIG. 3, method 300 of beam training a phased array antenna is shown, according to an exemplary embodiment. In various embodiments, one or more components of wireless communication network 100 perform method 300. For example, receiving device(s) 110 and / or mmWave device(s) 120 may perform one or more steps of method 300.

[0036] At step 310, method 300 may include transmitting, from an antenna, one or more probing beams. For example, mmWave device(s) 120 may transmit the one or more probing beams. In various embodiments, the one or more probing beams are pseudorandom beams. For example, mmWave device(s) 120 may transmit preamble signals in different directions. As used herein, preamble signals refer to pre-defined signals that are known to both TX and RX. The mthprobing beam may be set as:where [0™, 0™, ..., 0™^] represents the phase shifts. In various embodiments, the phase shifts are independent and identically distributed random variables from a uniform distribution. For example, the phase shifts may be distributed random variables from a uniform distribution on {0, pi / 2, pi, 3pi / 2}. FIG. 4Aillustrates an example of probing beams. In various embodiments, probing overhead is bounded by O KlogN), which scales logarithmically with the number of antenna elements (N) and linearly with the number of paths (X), which may enable fast beam training for large antenna arrays.

[0037] In some embodiments, method 300 includes receiving, at one or more receivers (e.g., receiving devices such as mobile phone(s) 112, etc.), the one or more probing beams. Additionally or alternatively, method 300 may include measuring a value / parameter of the one or more probing beams. For example, a receiving device may measure a CIR of the one or more probing beams and may transmit the measured CIR to mmWave device(s) 120. In some embodiments, a receiver may calculate the correlation value between the received signal and the transmitted preamble. The correlation value may be a measure of the CIR, where peaks in the CIR represent paths as shown in FIG. 4B. In various embodiments, method 300 includes transmitting from the one or more receivers to the antenna, the correlation peaks as feedback. For example, a receiver may transmit correlation peaks of XlogX beams via a feedback packet of an IEEE 802. Had beam-training protocol.

[0038] At step 320, method 300 may include determining, based on one or more measurements corresponding to the one or more probing beams, one or more correlations. For example, step 320may include determining the correlation value between the received signal and the transmitted preamble as described above.

[0039] At step 330, method 300 may include determining, based on the one or more correlations, one or more signal paths. In various embodiments, step 330 includes sorting the correlation peaks according to their ToF and / or grouping the peaks that belong to the same path. In various embodiments, grouping the peaks includes determining a time difference between peaks and comparing the time difference to a threshold. If the time difference is less than the threshold then the peaks may be grouped as belonging to the same path.

[0040] At step 340, method 300 may include determining a CIR value for each of the one or more signal paths. For example, the CIR value may be determined as shown in FIG. 4C.

[0041] At step 350, method 300 may include determining, based on the CIR value for each of the one or more signal paths, a direction corresponding to each of the one or more signal paths. For example, step 350 may include applying a compressive sensing (CS) algorithm to each path to estimate its direction. For an antenna element in the rthrow and cthcolumn, its contribution to the TX steering vector may be a 2D sinusoid determined based on:where d represents the antenna spacing, represents the wavelength of the central frequency, R represents the number of antenna elements in each row, C represents the number of antenna elements in each column, and N = R x C. In various embodiments, the direction of the A111path is determined by maximizing:where (■) is the inner product operation, vmrepresents the mlhprobing beam, M=K\o N represents the total number of probes, p(m,k) represents the correlation peak of the A111path determined for the mlhprobing beam. In various embodiments, system and methods of the present disclosure do not require phase coherence across probing beams.

[0042] At step 360, method 300 may include determining an optimized beam based on a complex gain corresponding to a signal path of the one or more signal paths. In various embodiments, step360 includes determining the complex gains of each path. In various embodiments, determining the complex gains of each path includes selecting a CIR that captures all paths. For example, method 300 may include amplifying the RF energy in the identified path directions and sending an additional probing beam to capture the CIR for these paths. In various embodiments, the complex gain along the A111path is determined according to:where vzrepresents the zthprobing beam that provides the selected CIR and p(Z,k) represents the selected CIR for the A111path. In various embodiments, the optimal beam is determined according to:

[0043] At step 370, method 300 may include generating, from the antenna, a subsequent beam based on the optimized beam. For example, a phased array antenna may use the previously determined complex gains to perform beamforming to transmit information to a user device.

[0044] As utilized herein with respect to numerical ranges, the terms “approximately,” “about,” “substantially,” and similar terms generally mean+ / -10% of the disclosed values, unless specified otherwise. As utilized herein with respect to structural features (e.g., to describe shape, size, orientation, direction, relative position, etc.), the terms “approximately,” “about,” “substantially,” and similar terms are meant to cover minor variations in structure that may result from, for example, the manufacturing or assembly process and are intended to have a broad meaning in harmony with the common and accepted usage by those of ordinary skill in the art to which the subject matter of this disclosure pertains. Accordingly, these terms should be interpreted as indicating that insubstantial or inconsequential modifications or alterations of the subject matter described and claimed are considered to be within the scope of the disclosure as recited in the appended claims.

[0045] It should be noted that the term “exemplary” and variations thereof, as used herein to describe various embodiments, are intended to indicate that such embodiments are possibleexamples, representations, or illustrations of possible embodiments (and such terms are not intended to connote that such embodiments are necessarily extraordinary or superlative examples).

[0046] The term “coupled” and variations thereof, as used herein, means the joining of two members directly or indirectly to one another. Such joining may be stationary (e.g., permanent or fixed) or moveable (e.g., removable or releasable). Such joining may be achieved with the two members coupled directly to each other, with the two members coupled to each other using a separate intervening member and any additional intermediate members coupled with one another, or with the two members coupled to each other using an intervening member that is integrally formed as a single unitary body with one of the two members. If “coupled” or variations thereof are modified by an additional term (e.g., directly coupled), the generic definition of “coupled” provided above is modified by the plain language meaning of the additional term (e.g., “directly coupled” means the joining of two members without any separate intervening member), resulting in a narrower definition than the generic definition of “coupled” provided above. Such coupling may be mechanical, electrical, or fluidic.

[0047] References herein to the positions of elements (e.g., “top,” “bottom,” “above,” “below”) are merely used to describe the orientation of various elements in the figures. It should be noted that the orientation of various elements may differ according to other exemplary embodiments, and that such variations are intended to be encompassed by the present disclosure.

[0048] The present disclosure contemplates methods, systems, and program products on any machine-readable media for accomplishing various operations. The embodiments of the present disclosure may be implemented using existing computer processors, or by a special purpose computer processor for an appropriate system, incorporated for this or another purpose, or by a hardwired system. Embodiments within the scope of the present disclosure include program products comprising machine-readable media for carrying or having machine-executable instructions or data structures stored thereon. Such machine-readable media can be any available media that can be accessed by a general purpose or special purpose computer or other machine with a processor. By way of example, such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer or other machine with a processor. Combinations of the above are also included within the scope of machine-readable media. Machine-executableinstructions include, for example, instructions and data which cause a general -purpose computer, special purpose computer, or special purpose processing machines to perform a certain function or group of functions.

[0049] Although the figures and description may illustrate a specific order of method steps, the order of such steps may differ from what is depicted and described, unless specified differently above. Also, two or more steps may be performed concurrently or with partial concurrence, unless specified differently above. Such variation may depend, for example, on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations of the described methods could be accomplished with standard programming techniques with rule-based logic and other logic to accomplish the various connection steps, processing steps, comparison steps, and decision steps.

[0050] The term “client or “server” include all kinds of apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, a system on a chip, or multiple ones, or combinations, of the foregoing. The apparatus may include special purpose logic circuitry, e.g., a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC). The apparatus may also include, in addition to hardware, code that creates an execution environment for the computer program in question (e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of them). The apparatus and execution environment may realize various different computing model infrastructures, such as web services, distributed computing and grid computing infrastructures.

[0051] The systems and methods of the present disclosure may be completed by any computer program. A computer program (also known as a program, software, software application, script, or code) may be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and it may be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment. A computer program may, but need not, correspond to a file in a file system. A program may be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code). A computer program may be deployed to be executed on onecomputer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

[0052] The processes and logic flows described in this specification may be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input data and generating output. The processes and logic flows may also be performed by, and apparatus may also be implemented as, special purpose logic circuitry (e.g., an FPGA or an ASIC).

[0053] Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read only memory or a random-access memory or both. The essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data (e.g., magnetic, magneto-optical disks, or optical disks). However, a computer need not have such devices. Moreover, a computer may be embedded in another device (e.g., a vehicle, a Global Positioning System (GPS) receiver, etc.). Devices suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD ROM and DVD-ROM disks). The processor and the memory may be supplemented by, or incorporated in, special purpose logic circuitry.

[0054] To provide for interaction with a user, implementations of the subject matter described in this specification may be implemented on a computer having a display device (e.g., a CRT (cathode ray tube), LCD (liquid crystal display), OLED (organic light emitting diode), TFT (thin- film transistor), or other flexible configuration, or any other monitor for displaying information to the user. Other kinds of devices may be used to provide for interaction with a user as well; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback).

[0055] Implementations of the subject matter described in this disclosure may be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g.,a client computer) having a graphical user interface or a web browser through which a user may interact with an implementation of the subject matter described in this disclosure, or any combination of one or more such back end, middleware, or front end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a LAN and a WAN, an inter-network (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks).

Claims

WHAT IS CLAIMED IS:

1. A method for beam-training a phased array antenna, comprising: transmitting, from the phased array antenna, one or more probing beams in one or more directions, wherein each probing beam comprises a preamble signal; receiving, at one or more receivers, the one or more probing beams; determining, based on the received one or more probing beams, a correlation between each transmitted preamble signal and each received preamble signal; determining, based on the correlation between each transmitted preamble signal and each received preamble signal, one or more signal paths; determining a channel impulse response (CIR) value for each of the one or more signal paths; determining, based on the CIR value for each of the one or more signal paths, a direction corresponding to each of the one or more signal paths; and generating, from the phased array antenna, a subsequent beam based on a complex gain corresponding to a signal path of the one or more signal paths.

2. The method of claim 1, wherein the phased array antenna applies a phase shift to each probing beam of the one or more probing beams and wherein phase shifts of the one or more probing beams are randomly selected from a distribution of phase shifts.

3. The method of claim 2, wherein the distribution of phase shifts is a uniform distribution comprising at least 0, 7t / 2, 7t, and 3TC / 2.

4. The method of claim 1, further comprising, transmitting, from the one or more receivers to the phased array antenna via a single feedback packet, the correlation between one or more transmitted preamble signals and one or more corresponding received preamble signals.

5. The method of claim 1, wherein determining the one or more signal paths comprises identifying a signal path based on a time of flight (ToF).

6. The method of claim 5, wherein the correlation between each transmitted preamble signal and each received preamble signal comprises a peak and wherein determining the one or more signal paths comprises: sorting peaks according to their ToF; and identifying peaks from the sorted peaks that correspond to a path of the one or more signal paths.

7. The method of claim 6, wherein identifying the peaks that correspond to the path of the one or more signal paths comprises: comparing a time difference between each of the peaks to a threshold; and identifying the peaks based on the comparison.

8. The method of claim 1, further comprising determining a steering vector for the phased array antenna based on an array geometry of the phased array antenna.

9. The method of claim 8, wherein the direction corresponding to each of the one or more signal paths is determined based on the CIR value for each of the one or more signal paths and the steering vector.

10. The method of claim 1, further comprising: transmitting, from the phased array antenna, an additional probing beam to capture a CIR from at least one of the one or more signal paths; and identifying, from the CIR from the one or more signal paths, a CIR that captures all signal paths.

11. The method of claim 10, wherein the subsequent beam is optimized based on the complex gain.

12. The method of claim 1, wherein the direction corresponding to each of the one or more signal paths is determined using a compressive sensing (CS) algorithm.

13. A mmWave device comprising: a phased array antenna; and a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the mmWave device to: transmit, from the phased array antenna, one or more probing beams in one or more directions, wherein each probing beam comprises a preamble signal; receive, from one or more devices, at least one measurement corresponding to the one or more probing beams; determine, based on the at least one measurement, a correlation between each transmitted preamble signal and each received preamble signal; determine, based on (i) the correlation between each transmitted preamble signal and each received preamble signal and (ii) a time of flight (ToF) value, one or more signal paths; determine a channel impulse response (CIR) value for each of the one or more signal paths;determine, based on the CIR value for each of the one or more signal paths, a direction corresponding to each of the one or more signal paths; and determine an optimized beam usable for a subsequent transmission based on a complex gain corresponding to a signal path of the one or more signal paths, wherein the optimized beam has a signal -to-noise ratio (SNR) that is greater than an average SNR of the one or more probing beams.

14. The mmWave device of claim 13, wherein the correlation between each transmitted preamble signal and each received preamble signal comprises a peak and wherein determining the one or more signal paths comprises: sorting peaks according to their ToF; and identifying peaks from the sorted peaks that correspond to a path of the one or more signal paths.

15. The mmWave device of claim 14, wherein identifying the peaks that correspond to the path of the one or more signal paths comprises: comparing a time difference between each of the peaks to a threshold; and identifying the peaks based on the comparison.

16. A method comprising: determining path directions using a compressive sensing (CS) algorithm; determining complex gains for each path angle; and deriving an optimal beam.

17. The method of claim 16, wherein the CS algorithm measures a mmWave channel by sending pseudorandom beams to send preamble signals in different directions.

18. The method of claim 17, further comprising: receiving probing beams; and calculating a correlation value between a received signal and a transmitted preamble.

19. The method of claim 17, wherein per-path channel amplitude and phase are estimated by: removing a directional from a transmit beam; estimating the amplitude ak for each path; and canceling Carrier Frequency Offset (CFO) within each beam.

20. The method of claim 16, further comprising determining a time-of-fhght (ToF) to distinguish paths.

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