US9270354B1 - Blind beamforming using knowledge embedded in transmitted signals - Google Patents
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
- H04B7/0837—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
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- H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
- H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
- H04B7/0617—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal for beam forming
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Definitions
- the present invention relates to a system for blind beamforming and, more particularly, to a system for blind beamforming using knowledge embedded in transmitted signals to perform signal separation and extraction.
- Beamforming is a signal processing technique used in sensor arrays for directional signal transmission or reception. Elements in a phased array are combined such that signals at particular angles experience constructive interference, while others experience destructive interference.
- Blind signal separation also known as blind source separation, is the separation of a set of source signals from a set of mixed signals, without the aid of information (or with very little information) about the source signals or the mixing process.
- the present invention relates to a system for blind beamforming and, more particularly, to a system for blind beamforming using knowledge embedded in transmitted signals to perform signal separation and extraction.
- the system comprises one or more processors and a memory having instructions such that when the instructions are executed, the one or more processors perform multiple operations.
- Initial antenna weights are assigned for a plurality of antenna elements of emitters of a beamforming system to generate a set of weighted radio-frequency (RF) signals at an output of each antenna element.
- the set of weighted RF signals are then combined to form a plurality of RF signal mixtures.
- Each RF signal mixture is processed to extract embedded information within signals of the emitters.
- the extracted embedded information is sent to an optimization module, wherein the extracted embedded information is used to perform simultaneous signal extractions for the emitters in the beamforming system.
- an objective function is calculated based on the extracted embedded information with the optimization module.
- feedback from the optimization module is used to modify antenna weights of the plurality of antenna elements toward optimal beamforming and to modify a set of demodulation parameters toward optimal information extraction.
- the optimization module estimates at least one signal extraction error value, wherein if the at least one signal extraction error value is greater than a predefined threshold value, then the antenna weights of the plurality of antenna elements are modified.
- the at least one signal extraction error value is defined as an absolute difference between one and the calculated objective function.
- the optimization module is configured to continue optimizing the antenna weights until the at least one signal extraction error value falls below the predefined threshold value.
- the plurality of antenna elements are grouped into a plurality of sub-arrays, wherein each sub-array can use a different number of antenna elements to increase or relax a resolution of antenna beam patterns produced by the beamforming system.
- the present invention also comprises a method for causing a processor to perform the operations described herein.
- the present invention also comprises a computer program product comprising computer-readable instructions stored on a non-transitory computer-readable medium that are executable by a computer having a processor for causing the processor to perform the operations described herein.
- FIG. 1 is a block diagram representation of a beamforming system that has been configured to use information embedded within signals of three emitters to extract and track all three emitter signals simultaneously according to the principles of the present invention
- FIG. 2A is an illustration of sample embedded information sequences according to the principles of the present invention.
- FIG. 2B is an illustration of signals from an emitter 1 with specific information sequences embedded in rows 5 , 10 , 15 , and 25 according to the principles of the present invention
- FIG. 2C is an illustration of signals from an emitter 2 with specific information sequences embedded in rows 5 , 10 , 15 , and 25 according to the principles of the present invention
- FIG. 2D is an illustration of signals from an emitter 3 with specific information sequences embedded in rows 5 , 10 , 15 , and 25 according to the principles of the present invention
- FIG. 3 illustrates individual antenna beam patterns of two sub-arrays and the combined antenna beam patterns for three operational scenarios according to the principles of the present invention
- FIG. 4 illustrates optimized antenna beam patterns for three operational scenarios according to the principles of the present invention
- FIG. 5 is an illustration of a data processing system according to the principles of the present invention.
- FIG. 6 is an illustration of a computer program product according to the principles of the present invention.
- the present invention relates to a system for blind beamforming and, more particularly, to a system for blind beamforming using knowledge embedded in transmitted signals to perform signal separation and extraction.
- the following description is presented to enable one of ordinary skill in the art to make and use the invention and to incorporate it in the context of particular applications. Various modifications, as well as a variety of uses, in different applications will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to a wide range of embodiments. Thus, the present invention is not intended to be limited to the embodiments presented, but is to be accorded with the widest scope consistent with the principles and novel features disclosed herein.
- any element in a claim that does not explicitly state “means for” performing a specified function, or “step for” performing a specific function, is not to be interpreted as a “means” or “step” clause as specified in 35 U.S.C. Section 112, Paragraph 6.
- the use of“step of” or “act of” in the claims herein is not intended to invoke the provisions of 35 U.S.C. 112, Paragraph 6.
- the labels left, right, front, back, top, bottom, forward, reverse, clockwise and counter-clockwise have been used for convenience purposes only and are not intended to imply any particular fixed direction. Instead, they are used to reflect relative locations and/or directions between various portions of an object. As such, as the present invention is changed, the above labels may change their orientation.
- the present invention has three “principal” aspects.
- the first is a system for blind beamforming.
- the system is typically in the form of a computer system, computer component, or computer network operating software or in the form of a “hard-coded” instruction set.
- This system may take a variety of forms with a variety of hardware devices and may include computer networks, handheld computing devices, cellular networks, satellite networks, and other communication devices. As can be appreciated by one skilled in the art, this system may be incorporated into a wide variety of devices that provide different functionalities.
- the second principal aspect is a method for blind beamforming.
- the third principal aspect is a computer program product.
- the computer program product generally represents computer-readable instruction means (instructions) stored on a non-transitory computer-readable medium such as an optical storage device, e.g., a compact disc (CD) or digital versatile disc (DVD), or a magnetic storage device such as a floppy disk or magnetic tape.
- a non-transitory computer-readable medium such as an optical storage device, e.g., a compact disc (CD) or digital versatile disc (DVD), or a magnetic storage device such as a floppy disk or magnetic tape.
- a non-transitory computer-readable medium such as an optical storage device, e.g., a compact disc (CD) or digital versatile disc (DVD), or a magnetic storage device such as a floppy disk or magnetic tape.
- CD compact disc
- DVD digital versatile disc
- magnetic storage device such as a floppy disk or magnetic tape.
- Other, non-limiting examples of computer-readable media include hard disks, read-only memory (ROM), and flash-type memories.
- instructions generally indicates a set of operations to be performed on a computer, and may represent pieces of a whole program or individual, separable, software modules.
- Non-limiting examples of “instructions” include computer program code (source or object code) and “hard-coded” electronics (i.e., computer operations coded into a computer chip).
- the “instructions” may be stored on any non-transitory computer-readable medium such as a floppy disk, a CD-ROM, a flash drive, and in the memory of a computer.
- the present invention uses information embedded within various emitter signals to detect, extract, and track individual emitter signals simultaneously without measuring the statistical properties of the received signal and without using a calibrated antenna array.
- Existing systems use signal properties for separation that are not affected by the encoded information. Unlike existing systems, the present invention can separate signals even if they have the same properties, because the information embedded in the signals is utilized.
- the beamforming system can be used to track multiple emitters simultaneously (it is assumed that the emitters are uncooperative) by formulating an objective function for an optimization module that maximizes the measured degree of extraction of higher information embedded in the emitter signals.
- the embedded information include known or unknown patterns, such as words, recognized speech, images (e.g., objects or textures in video), or data (e.g., specific symbol sequences).
- the objective function measures specific properties, such as the degree of match of the extracted information with known information, or it can measure more general properties of the extracted information, such as whether a recognition system can recognize any words, images, or data in it.
- FIG. 1 is a block diagram of a non-limiting representation of an aspect of the beamforming system, according to the principles of the present invention, that has been configured to use information embedded within signals of three emitters to extract and track all three emitter signals simultaneously.
- the system groups some or all antenna elements (represented by bold solid line triangles 100 , unbolded solid line triangles 102 , and dashed line triangles 104 ) of a given antenna array 106 into several smaller arrays (i.e., sub-arrays).
- the number of sub-arrays is equal to or greater than the number of signals to be extracted in a given scene, and the number of antenna elements ( 100 , 102 , and 104 ) in each sub-array is determined by the desired resolution of the respective antenna beam patterns.
- the sub-arrays can also use a different number of antenna elements to increase or relax the resolution of antenna beam patterns while tracking their respective emitters from one time instant to another.
- the beamforming method allows individual antenna elements ( 100 , 102 , 104 ) of the sub-arrays to have different antenna patterns that may have non-uniform or random shapes, and that may even vary with time.
- the system can work just as well with calibrated or uncalibrated antenna arrays 106 that may have time-varying number of antenna elements ( 100 , 102 , 104 ), randomly placed antenna elements ( 100 , 102 , 104 ), or antenna elements ( 100 , 102 , 104 ) with non-uniform, random, or time-varying antenna patterns.
- An initial set of antenna weights 108 for various antenna elements of different sub-arrays can be chosen randomly.
- the amplitude and phase weights (i.e., antenna weights 108 ) for individual antenna elements are represented by circles in FIG. 1 .
- the system uses a switching matrix 110 to combines weighted, received radio frequency (RF) signals at the output of each antenna element 100 , 102 , and 104 of individual antenna sub-arrays in a RF signal mixing module 112 to form respective RF signal mixtures 114 , 116 , and 118 for post-processing.
- RF radio frequency
- the RF signal mixtures 114 , 116 , and 118 are down converted and demodulated in an information extraction module 120 , which involves processes of signal conditioning, signal demodulation, and information extraction for each RF signal mixture 114 , 116 , and 118 .
- Prior knowledge 122 of the properties of embedded information within an extracted baseband signal i.e., actual embedded reference information or measurements of extracted information properties
- Prior knowledge 122 of the properties of the embedded information is used by the optimization module 124 to perform simultaneous signal extractions, as described below.
- any practical information extraction process can be used which enables the antenna weights and demodulation parameters to be adapted fast enough to track the emitters.
- the data embedded in the signal is available.
- the information extraction module 120 then extracts the higher level information or properties of the information that is represented by the data.
- the system will adjust the demodulation and antenna parameters to optimize an objective function that is based on the extracted information.
- Non-limiting examples of extracted information include the sequence of symbols being transmitted by the emitters. Other properties could also be used, such as the presence of particular words or languages that can be automatically recognized, or the statistical properties of the embedded data.
- An analogy is a person tuning a radio until he hears something of interest. His objective function could be how clearly he hears a particular language.
- the optimization module 124 comprises several stages which together (1) calculate an objective function based on the extracted embedded information, (2) estimate information extraction error (i.e., the degree to which the extracted embedded information does not match pre-determined properties of the desired information), and (3) send feedback to adjust antenna weights and demodulation parameters 130 .
- the optimization module 124 can be any system that can adjust the parameters to optimize the objective function and do it fast enough to keep up with changes in the emitter, including its location.
- particle swarm optimization PSO
- genetic algorithms or other optimization algorithms could be used.
- An objective function designed using prior knowledge 122 of the properties of information embedded within signals of the n emitters, is used to evaluate the degree of mismatch between properties of the information extracted from the RF signal mixtures 114 , 116 , and 118 and the properties of the desired information. If the objective function value is greater than a predefined threshold limit (i.e., larger mismatch), a suitable heuristic optimization algorithm, non-limiting examples of which include genetic algorithms and particle swarm optimization, is used to modify both the weights of various antenna elements 100 , 102 , 104 of the sub-arrays and the demodulation parameter (i.e., send feedback to adjust antenna weights and the demodulation parameters 130 ) to reduce the objective function.
- a predefined threshold limit i.e., larger mismatch
- active feedback 132 , 134 , and 136 from the optimization module 124 guides antenna weights 108 towards optimal beamforming and the demodulation parameters towards extraction of the embedded information. Different weights are used to achieve different sensitivities. The process is repeated until the antenna pattern lobes (i.e., maxima) and nulls (i.e., signal goes to zero) are so aligned that the system is able to accurately extract signals from all n emitters simultaneously, generating extracted information from emitters 138 .
- FIG. 2A is an illustration of sample embedded information sequences according to the principles of the present invention.
- the desired property of the embedded information is the data or symbols represented by it.
- Other properties can also be used such as the presence of particular words or languages that can be automatically recognized or the statistical properties of the embedded information.
- FIGS. 2B-2D depict a non-limiting example wherein each emitter signal consists of a collection of 4800 symbols arranged in 30 rows of 160 symbols each.
- a unique sequence of 640-symbols-long information (depicted as element 122 in FIG.
- FIGS. 2A-2D illustrate three sample information sequences and baseband emitter signals with specific information subsequences embedded in rows 5 , 10 , 15 and 25 .
- FIGS. 2B , 2 C, and 2 D illustrate the signals of emitters 1 , 2 , and 3 , respectively.
- FIGS. 2B , 2 C, and 2 D are plots of signals from the three emitters, referred to as stacked signal plots.
- the time series of symbols representing the signal have been divided into segments, and the segments are stacked vertically to form a two-dimensional representation of the long, one-dimensional signal.
- the marked rows, as indicated by a square surrounding the row number, contain the information sequence being transmitted; the rest of the signal is noise.
- each unique, emitter-specific 160-symbols-long information sequence can be mapped into a corresponding 640-bits-long information subsequence.
- the antenna elements of the antenna array are divided into three sub-arrays, and each sub-array is tasked to track and extract an information signal from one of the three emitter signals.
- the objective function for each sub-array is designed such that each sub-array steers an antenna pattern lobe on the particular emitter of interest while forming deep antenna pattern nulls on the other two emitters.
- the objective function ( FIG. 1 , optimize objective function based on extracted embedded information 126 ) in this example can be calculated as the weighted dot product (i.e., normalized cross-correlation) of the prior knowledge (depicted in FIG. 1 as element 122 ) of the predefined embedded reference information sequence and one of the extracted 640-bits-long information sequences.
- the objective function can be augmented to first calculate weighted dot products of all four embedded reference information subsequences and extracted information-bit-sequence pairs (corresponding to rows 5 , 10 , 15 , and 25 in FIGS. 2B-2D ) followed by averaging of all four dot products.
- this objective function will calculate a value of one for each emitter.
- FIG. 3 shows antenna beam pattern simulation results demonstrating how the blind beamforming system and method according to the principles of the present invention can be used to simultaneously track multiple emitters.
- the beamforming system was configured to simultaneously track two emitters and an interferer.
- the antenna array of the system was divided into two sub-arrays, with each sub-array tracking one of the two emitters.
- the plots in different rows of FIG. 3 show results corresponding to different simulation test cases.
- the plots in the first and second columns of each row show antenna beam patterns of individual sub-arrays, and the plots in the third column show the combined antenna beam pattern for both sub-arrays for the particular simulation test case in a given row.
- the system described herein was used to extract signals from emitter pairs 1 and 2 (E 1 and E 2 , respectively) simultaneously while also completely blocking any signal from emitter 3 (E 3 ).
- antenna pattern lobes were steered to extract signals from emitter pairs 1 and 3 (E 1 and E 3 , respectively), and 2 and 3 (E 2 and E 3 , respectively).
- all antenna patterns in FIG. 3 were normalized so that the antenna gain ranged between 1 and 0.
- the plot in the first row 300 of the first column 302 of FIG. 3 shows the final antenna beam pattern of the first sub-array of the beamforming system.
- the sub-array uses particle swarm optimization to optimize weights of its antenna elements to steer an antenna pattern lobe on emitter 1 (E 1 ) and antenna pattern nulls on emitters 2 and 3 (E 2 and E 3 , respectively).
- the plot in the first row 300 of the second column 304 shows the final antenna beam pattern of the second sub-array of the beamforming system. This sub-array steers an antenna beam lobe on E 2 and antenna pattern nulls on E 1 and E 3 .
- the effective combined antenna beam pattern can be calculated using optimized weights of all antenna elements of both sub-arrays.
- This resulting pattern, for the first simulation test case, is shown in the plot in the first row 300 of the third column 306 .
- the deep null on E 3 (indicated by the E 3 point being in a dark blue area of the plot representing no signal) and prominent antenna pattern lobes on E 1 and E 2 (indicated by the E 1 and E 2 points being in red areas of the plot representing maxima) enable the blind beamforming system to successfully extract signals from E 1 and E 2 simultaneously.
- the optimization function is designed such that all elements of the antenna array are used to simultaneously steer multiple antenna pattern lobes on various emitters in the scene while forming deep antenna pattern nulls on the interferers.
- a number of different objective functions can be formed using the unique 640-bits-long information sequences of the two emitters.
- the individual embedded information bit sequences i.e., FIG. 1 , prior knowledge 122
- the objective function can be as simple as the weighted dot product of the new reference and one of the extracted 1280-bits-long information sequences, or it can be augmented to first calculate the weighted dot product of all four reference and extracted information bit sequence pairs (corresponding to rows 5 , 10 , 15 , and 25 ) followed by averaging of all four dot products.
- the optimization module (depicted in FIG. 1 as element 124 ) of the beamforming system continues optimizing antenna weights until the signal extraction error value falls below a predefined threshold value ( FIG. 1 , estimate demodulation parameters and antenna weight adjustments 128 ).
- FIG. 4 shows optimized antenna beam patterns for three operational scenarios: (1) signals of interest transmitted by an emitter 1 - 2 pair (first row 400 ), (2) emitter 1 - 3 pair (second row 402 ), and (3) emitter 2 - 3 pair (third row 404 ).
- the simulation results in FIG. 4 demonstrate how the second embodiment of the blind beamforming system and method can be used to simultaneously track multiple emitters.
- the beamforming system was configured to use all elements of the antenna array (i.e., no formation of sub-arrays) to simultaneously track two emitters and an interferer.
- the plots in the first column 406 of FIG. 4 show optimized antenna patterns corresponding to different simulation test cases, represented by different rows (first row 400 , second row 402 , and third row 404 ).
- the plots in the second column 408 and third column 410 of a row show the depth and finer details of the antenna pattern null formed on the interferer in that scene.
- the beamforming system is used to extract signals from emitter pairs 1 (E 1 ) and 2 (E 2 ) simultaneously, while also completely blocking any signal from emitter 3 (E 3 ).
- antenna pattern lobes are steered to extract signals from emitter pairs 1 and 3 , and 2 and 3 , respectively.
- all antenna patterns in the first column 406 of FIG. 4 are normalized to respective minimum gain levels.
- the color scale shows normalized gain levels in decibels (dB).
- the system steers two different antenna pattern lobes on the two emitters, E 1 and E 2 , while simultaneously forming a deep antenna pattern null on the interferer E 3 .
- the antenna pattern gain values at the location of the two emitters (E 1 and E 2 ), relative to the gain value at the location of the interferer, are 21.8 and 22.1 dB, respectively.
- the system steers a single antenna-pattern-lobe on the two emitters, E 2 and E 3 , while forming a deep antenna pattern null on the interferer E 1 .
- the relative antenna pattern gain values at the location of the two emitters are 23.1 and 23.1 dB, respectively.
- the present invention comprises dynamic interference rejection, high system performance, and the use of uncalibrated antenna arrays.
- the optimization module (depicted as element 124 in FIG. 1 ) of the present invention dynamically steers high gain lobes and nulls to quickly arrive at an antenna pattern that allows the system to retrieve information embedded within the desired signal, completely and accurately. In doing so, the system automatically rejects all of the interfering signals irrespective of their locations relative to the emitter, even if their statistical properties are similar to those of the emitter signal.
- the present invention utilizes active feedback from the high-level system (that actually uses the extracted signal) to intelligently govern the signal separation and extraction process, thereby improving overall performance of the system.
- the present invention can work just as well with calibrated or uncalibrated antenna arrays that may have a time-varying number of antenna elements, randomly placed antenna elements, or antenna elements with non-uniform, random, or time-varying antenna patterns.
- existing blind source separation systems such as antenna beamformers, separate signals on the basis of properties of the signals, including angle of arrival, statistical independence, or type of modulation.
- the system according to the principles of the present invention separates signals based on higher level information encoded in the signals, non-limiting examples of which include recognized speech, objects or textures in video, and specific symbol sequences.
- Existing systems use signal properties for separation that are not affected by the encoded information.
- the present invention can separate signals even if they have the same properties, because the information embedded in the signals is utilized.
- the invention described herein provides advantages in the areas of inter-vehicular communications, vehicle-to-infrastructure communications, collision warning, collision avoidance, and other active safety applications.
- FIG. 5 An example of a computer system 500 in accordance with one aspect is shown in FIG. 5 .
- the computer system 500 is configured to perform calculations, processes, operations, and/or functions associated with a program or algorithm.
- certain processes and steps discussed herein are realized as a series of instructions (e.g., software program) that reside within computer readable memory units and are executed by one or more processors of the computer system 500 . When executed, the instructions cause the computer system 500 to perform specific actions and exhibit specific behavior, such as described herein.
- the computer system 500 may include an address/data bus 502 that is configured to communicate information. Additionally, one or more data processing units, such as a processor 504 , are coupled with the address/data bus 502 .
- the processor 504 is configured to process information and instructions.
- the processor 504 is a microprocessor. Alternatively, the processor 504 may be a different type of processor such as a parallel processor, or a field programmable gate array.
- the computer system 500 is configured to utilize one or more data storage units.
- the computer system 500 may include a volatile memory unit 506 (e.g., random access memory (“RAM”), static RAM, dynamic RAM, etc.) coupled with the address/data bus 502 , wherein a volatile memory unit 506 is configured to store information and instructions for the processor 504 .
- RAM random access memory
- static RAM static RAM
- dynamic RAM dynamic RAM
- the computer system 500 further may include a non-volatile memory unit 508 (e.g., read-only memory (“ROM”), programmable ROM (“PROM”), erasable programmable ROM (“EPROM”), electrically erasable programmable ROM “EEPROM”), flash memory, etc.) coupled with the address/data bus 502 , wherein the non-volatile memory unit 508 is configured to store static information and instructions for the processor 504 .
- the computer system 500 may execute instructions retrieved from an online data storage unit such as in “Cloud” computing.
- the computer system 500 also may include one or more interfaces, such as an interface 510 , coupled with the address/data bus 502 .
- the one or more interfaces are configured to enable the computer system 500 to interface with other electronic devices and computer systems.
- the communication interfaces implemented by the one or more interfaces may include wireline (e.g., serial cables, modems, network adaptors, etc.) and/or wireless (e.g., wireless modems, wireless network adaptors, etc.) communication technology.
- the computer system 500 may include an input device 512 coupled with the address/data bus 502 , wherein the input device 512 is configured to communicate information and command selections to the processor 500 .
- the input device 512 is an alphanumeric input device, such as a keyboard, that may include alphanumeric and/or function keys.
- the input device 512 may be an input device other than an alphanumeric input device.
- the computer system 500 may include a cursor control device 514 coupled with the address/data bus 502 , wherein the cursor control device 514 is configured to communicate user input information and/or command selections to the processor 500 .
- the cursor control device 514 is implemented using a device such as a mouse, a track-ball, a track-pad, an optical tracking device, or a touch screen.
- the cursor control device 514 is directed and/or activated via input from the input device 512 , such as in response to the use of special keys and key sequence commands associated with the input device 512 .
- the cursor control device 514 is configured to be directed or guided by voice commands.
- the computer system 500 further may include one or more optional computer usable data storage devices, such as a storage device 516 , coupled with the address/data bus 502 .
- the storage device 516 is configured to store information and/or computer executable instructions.
- the storage device 516 is a storage device such as a magnetic or optical disk drive (e.g., hard disk drive (“HDD”), floppy diskette, compact disk read only memory (“CD-ROM”), digital versatile disk (“DVD”)).
- a display device 518 is coupled with the address/data bus 502 , wherein the display device 518 is configured to display video and/or graphics.
- the display device 518 may include a cathode ray tube (“CRT”), liquid crystal display (“LCD”), field emission display (“FED”), plasma display, or any other display device suitable for displaying video and/or graphic images and alphanumeric characters recognizable to a user.
- CTR cathode ray tube
- LCD liquid crystal display
- FED field emission display
- plasma display or any other display device suitable for displaying video and/or graphic images and alphanumeric characters recognizable to a user.
- the computer system 500 presented herein is an example computing environment in accordance with one aspect.
- the non-limiting example of the computer system 500 is not strictly limited to being a computer system.
- the computer system 500 represents a type of data processing analysis that may be used in accordance with various aspects described herein.
- other computing systems may also be implemented.
- the spirit and scope of the present technology is not limited to any single data processing environment.
- one or more operations of various aspects of the present technology are controlled or implemented using computer-executable instructions, such as program modules, being executed by a computer.
- program modules include routines, programs, objects, components and/or data structures that are configured to perform particular tasks or implement particular abstract data types.
- one aspect provides that one or more aspects of the present technology are implemented by utilizing one or more distributed computing environments, such as where tasks are performed by remote processing devices that are linked through a communications network, or such as where various program modules are located in both local and remote computer-storage media including memory-storage devices.
- FIG. 6 An illustrative diagram of a computer program product embodying the present invention is depicted in FIG. 6 .
- the computer program product is depicted as either a floppy disk 600 or an optical disk 602 .
- the computer program product generally represents computer readable code (i.e., instruction means or instructions) stored on any compatible non-transitory computer readable medium.
Abstract
Description
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CN114978253A (en) * | 2021-02-26 | 2022-08-30 | 中国电信股份有限公司 | Method, apparatus and storage medium for broadcast beam optimization |
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