Patent Description:
The term "antenna array" refers to a geometrical arrangement of a number of antenna elements. The antenna elements can be configured as a single antenna unit to achieve a desired antenna gain and directional characteristics, such as a particular radiation pattern. A variation of this radiation pattern can be referred to as beam-forming. Antenna arrays can have applications, such as in multiple-input multiple-output (MIMO) communication systems. In particular, very large antenna arrays can be referred to as "massive MIMO arrays". Massive MIMO arrays may use several hundreds of antenna elements arranged in a single antenna unit and are considered to be a key technology component for future communication systems, such as fifth generation, <NUM>, communication. According to known technology, an up-link MIMO unit may comprise for example a radio base-station receiver, an analog-to-digital converter and automatic gain control units.

Massive MIMO can have some advantages, however, these advantages are counteracted, in practice, by an increased hardware complexity associated with having many antennas and many associated up/down conversion chains, and by an increased energy consumption due to all the hardware required for operation.

<CIT> provides a method with a complexity of using a MIMO system, while retaining some benefits as antenna selection, where a subset of size L taken from a set of N available antenna signals is selected and connected, via a switch, to L (L<N) radio-frequency (RF) chains. However, this method fails short in providing an amount of beamforming gain, and thus shows reduced or unacceptable performance, in particular, in channels with small angular spread, which typically occurs in conventional cellular systems.

In wireless communications, channel state information (CSI) refers to known channel properties of a communication link. This information describes how a signal propagates from the transmitter to the receiver and represents the combined effect of, for example, scattering, fading, and power decay with distance. The CSI makes it possible to adapt transmissions to current channel conditions for achieving reliable communication with high data rates in multi-antenna systems.

Most, conventional CSI estimation methods developed for traditional MIMO systems have a significantly higher number of transmitters and receivers used at the base station, and are not always suitable for massive MIMO channel estimation. The number of transceivers at the base station can potentially reach up to thousands when the carrier frequency moves up to the millimeter wave frequency band which makes the physical size of the antennas much smaller, e.g., comparable to the wavelength.

Document <NPL>, describes a method for channel estimation for uplink multiuser massive MIMO systems, where, in order to significantly reduce the hardware cost and power consumption, one-bit analog-to-digital converters are used at the base station to quantize the received signal. In the method an adaptive quantization approach, in which the thresholds are adaptively adjusted in a way such that the thresholds converge to the optimal thresholds, and a random quantization scheme, which randomly generates a set of non-identical thresholds based on some statistical prior knowledge of the channel, are used.

Document <NPL>, XP033001932 discloses a channel estimation method based on one-bit compressive sensing.

Document <NPL> discloses an adaptive one-bit compressed sensing scheme for channel estimation.

The above problems are solved by the subject-matter according to the independent claim. Embodiments of the present disclosure provide for devices and methods relating to the field of multiple input, multiple output (MIMO) wireless communication systems, and more particularly to channel estimation to estimate information of angle-of-departure (AoD) and angle-of-arrival (AoA) of wireless channels.

Some embodiments of the present disclosure are based on angular-domain channel estimation for massive MIMO systems with low-resolution analog-to-digital converters (ADCs) with few-bits quantization equipped at base stations in order to achieve lower power consumption and reduced hardware cost. Through experimentation, we realized that a major source of cost and energy consumption in massive multiple-input multiple-output (MIMO) antenna systems comes from digital-to-analog (DAC) and/or ADC converters. For example, due to a large number of antennas at the base stations (BSs), the hardware cost and power consumption at the BSs become simply unaffordable if each RF chain employs a power-hungry high-resolution ADC. To address this issue, some embodiments use low-resolution ADCs for the massive MIMO system, because the hardware complexity and power consumption grow exponentially with the resolution (i.e., the number of bits per measurement sample) of the ADC. In exemplar one-bit embodiment, the one-bit ADC simply compares the input analog signal with a threshold and requires minimum cost and power consumption.

In MIMO systems, a transmitter sends multiple signals by multiple transmit antennas. The transmit signals go through a matrix channel formed by various channel paths between the transmit antennas at the transmitter and the receive antennas at the receiver. Then, the receiver gets the received signal vectors of signals received by the multiple receive antennas and decodes the received signal vectors into the original information. However, the estimation of the parameters of the channel with quantized information produced by low-resolution ADCs is more difficult than with having higher-resolution information. Naturally, one bit of information per measurement produced by the one-bit ADCs is less informative that multiple bits produced by higher resolution ADCs.

Some embodiments are based on realization that one of the problems in the low in formativeness of an at least one-bit ADC, lies in the fact that the threshold for determining the value of the bit can be constant and selected to be statistically natural. For example, when the threshold is selected to be zero, the one bit of information representing a result of a comparison of the measurement with a zero-valued threshold indicates only a sign of the measurement, i.e., whether the measurements is positive or negative, but fails to report on the magnitude of the measurements.

To that end, some embodiments use time-varying thresholds, i.e., the thresholds allowed to have different values at different time steps. Those embodiments are based on insight that one-bit value indicating the result of the comparison of the measurements of the signal with a randomly selected threshold, as well as the value of the randomly selected threshold carries additional statistical information that can be used for channel estimation.

For example, if the result of comparison indicates that the measurement of the signal is greater than a threshold having a value, let say, three, that one bit of information indicating that the signal is greater than three carries statistically more information than one bit of information indicating that the signal is greater than zero, i.e., positive. Notably, the values of the time varying thresholds needs to be preserved in order to take advantage of the knowledge of the values of the threshold. However, the memory preserving such information can be shared across multiple RF chains and/or reused for other computational needs of the MIMO system.

Further, the low-resolution ADCs sampling the analog signals with time-varying thresholds can reduce the cost of the massive MIMO system, while allowing using multiple RF chains in recovering transmitted data and/or parameters of the wireless channel.

For example, one embodiment discloses a receiver for use in a wireless communication system to receive signals transmitted over a wireless channel. The receiver includes a plurality of antennas and a plurality of radio-frequency (RF) chains coupled the plurality of antennas. Each RF chain includes an at least one-bit ADC to convert each measurement of an analog signal received by the antenna into one bit of information representing a result of a comparison of the measurement with a randomly selected threshold to produce a sequence of bits and a corresponding sequence of thresholds. Wherein each bit in the sequence of bits represents a relative value of the measurement of the analog signal with respect to a threshold from the corresponding sequence of thresholds. A processor can be coupled to the plurality of RF chains can estimate at least some parameters of the wireless channel using the sequences of bits and the corresponding sequences of thresholds received from the plurality of RF chains.

As used herein, randomly selected thresholds are selected independently from the values of the measurements themselves. However, in various embodiments, the randomness of the threshold can be truly random, pseudo-random, as well as uniformly random or random according to a probability density function.

For example, in some embodiments, the receiver includes a random-number generator to generate a random number within a predetermined range. The predetermined range is defined by the possible values of the signal allowing the processor to select the threshold based on the random number. In one embodiment, the processor uses the random number itself as a threshold. This embodiment allows to increase the variation of the threshold selection and advantageous for MIMO system with different variations of the transmitted signals.

Further, in some embodiments the processor can use the random number to select a threshold from a set of thresholds representing the quantized space of the thresholds. Wherein this embodiment allows considering the possible values of the thresholds based on the types of the transmitted signals. For example, the set of thresholds can include more positive value than the negative to reflect the believe on distribution of the values. In another example, the set of thresholds can include at least two elements with the same value, e.g., zero values, to represent statistical tendency, which allows increasing the range of the threshold values to collect the information about measurement outliers of the transmitted signal.

Further still, in some embodiments of the present disclosure, the values of the elements in a set of thresholds can be sampled according to a probability distribution function. Wherein, in one implementation, the processor estimates a probability distribution function reflecting a density of the transmitted signal. Such probability distribution function can be estimated based on relative values of the measurements with respect to the thresholds. Selecting the thresholds using the probability distribution function can increase statistical value of the one-bit samples of the measurements.

In some embodiments, for each time step, the processor selects the same threshold for all RF chains. Wherein this embodiment can allow for sharing the same sequence of thresholds for different RF chains. Alternative embodiments, however, can select different thresholds for at least some different RF chains. For example, in one implementation, the processor selects a pattern of thresholds repeated form multiple groups of RF chains connected to neighboring antennas.

According to an embodiment of the present disclosure, a receiver for use in a wireless communication system to receive signals transmitted over a wireless channel. The receiver including a plurality of antennas. A plurality of RF chains coupled the plurality of antennas. Each RF chain includes an at least one-bit ADC to convert each measurement of an analog signal received by the antenna into at least one bit of information representing a result of a comparison of the measurement with a randomly selected threshold to produce a sequence of bits and a corresponding sequence of thresholds. Wherein each bit in the sequence of bits represents a relative value of the measurement of the analog signal with respect to a threshold from the corresponding sequence of thresholds. A processor coupled to the plurality of RF chains to estimate at least some parameters of the wireless channel using the sequences of bits and the corresponding sequences of thresholds received from the plurality of RF chains.

For example, in some embodiments the receiver may further comprise a user input provided on a surface of at least one user input interface and received by the processor, such that the user input relates to the predetermined threshold range, wherein the random-number generator generates the random number within the provided predetermined range, and the processor selects the randomly selected thresholds based on the random number.

For example, in some embodiments the processor may select a pattern of thresholds repeated from multiple groups of RF chains connected to neighboring antennas.

For example, in some embodiments the processor may estimate the parameters of the wireless channel according to a maximum likelihood criterion <MAT> wherein zm is a quantized I/Q signals at a m-th receiving antenna, <MAT> denotes an m-th row of the matrix Γ which is a function of a pilot symbol, an angle-of-departure, an angle-of-arrival, and an antenna geometry, h is a vector that contains a real and imaginary parts of a complex channel path gains, λm. is the threshold used at the m-th receiving antenna at a given time instance, σ is a noise standard deviation, Φ(·) is a cumulative density function (CDF) of a standard Gaussian random variable, K is a number of pilot symbols, Nr is a number of receiving antennas, and ψ groups all unknown wireless channel statistics including an angle-of-departure, an angle-of-arrival, a complex channel path gain, and their angular spreads.

According to an embodiment of the present disclosure, a symbol detector for use in a communication system to receive signals transmitted over a wireless channel. The symbol detector including a plurality of antennas. A plurality of RF chains coupled the plurality of antennas, each RF chain includes an at least one-bit ADC to convert each measurement of an analog signal received by the antenna into at least one bit of information representing a result of a comparison of the measurement with a randomly selected threshold to produce a sequence of bits and a corresponding sequence of thresholds. Wherein each bit in the sequence of bits represents a relative value of the measurement of the analog signal with respect to a threshold from the corresponding sequence of thresholds. A processor in communication with a memory, coupled to the plurality of RF chains to detect a sequence of symbols sent from multiple transmitters from the quantized measurements from multiple receivers, aided by an estimated channel state information (CSI).

For example, in some embodiments the symbol detector may further comprise a random-number generator to generate a random number within a predetermined range, such that the processor selects the randomly selected thresholds based on the random number.

For example, in some embodiments the memory may have stored thereon, a set of randomly selected thresholds, wherein values of the elements in set of randomly selected thresholds are uniformly sampled, or are sampled according a probability distribution function, such that the processor selects the randomly selected threshold from the set of randomly selected thresholds, based on the random number.

For example, in some embodiments, for each time step, the processor may select different thresholds for at least some different RF chains, such that the processor selects a pattern of thresholds repeated from multiple groups of RF chains connected to neighboring antennas.

According to an embodiment of the present disclosure, a decoder for use in a communication system to receive signals transmitted over a wireless channel. The decoder including a plurality of antennas. A plurality of RF chains coupled the plurality of antennas. Each RF chain includes an at least one-bit ADC to convert each measurement of an analog signal received by the antenna into at least one bit of information representing a result of a comparison of the measurement with a randomly selected threshold to produce a sequence of bits and a corresponding sequence of thresholds. Wherein each bit in the sequence of bits represents a relative value of the measurement of the analog signal with respect to a threshold from the corresponding sequence of thresholds. A processor in communication with a memory, coupled to the plurality of RF chains to estimate at least some parameters of the wireless channel using the sequences of bits and the corresponding sequences of thresholds received from the plurality of RF chains. Such that the at least some parameters include a two-dimensional channel matrix having one or combination of angles-of-departure, angles-of-arrival, and channel path gains.

In some embodiments, the selection of the randomly selected thresholds may be correlated to a number of antennas of a massive MIMO system, completely irrelevant to the channel statistics or based on available prior knowledge on the channel statistics from past measurements, the geometry of the scene, and other knowledge sources.

While the above-identified drawings set forth presently disclosed embodiments, other embodiments are also contemplated, as noted in the discussion. This disclosure presents illustrative embodiments by way of representation and not limitation.

The following description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the following description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing one or more exemplary embodiments. Contemplated are various changes that may be made in the function and arrangement of elements without departing from the scope of the subject matter disclosed as set forth in the appended claims. Specific details are given in the following description to provide a thorough understanding of the embodiments. However, understood by one of ordinary skill in the art can be that the embodiments may be practiced without these specific details. For example, systems, processes, and other elements in the subject matter disclosed may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known processes, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments. Further, like reference numbers and designations in the various drawings indicated like elements.

Also, individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. A process may be terminated when its operations are completed, but may have additional steps not discussed or included in a figure. Furthermore, not all operations in any particularly described process may occur in all embodiments. A process may correspond to a method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, the function's termination can correspond to a return of the function to the calling function or the main function.

Embodiments of the present disclosure provide for devices and methods relating to multiple input, multiple output (MIMO) wireless communication systems, in particular, to channel estimation to estimate information of angle-of-departure (AoD) and angle-of-arrival (AoA) of wireless channels.

Some embodiments of the present disclosure are based on angular-domain channel estimation for massive MIMO systems with one-bit analog-to-digital converters (ADCs) equipped at base stations in order to achieve lower power consumption and reduced hardware cost. Through experimentation, we realized a major source of cost and energy consumption in massive multiple-input multiple-output (MIMO) antenna systems comes from digital-to-analog (DAC) and/or analog-to-digital (ADC) converters. For example, due to a large number (hundreds or even thousands) of antennas at the base stations (BSs), the hardware cost and power consumption at the BSs become simply unaffordable if each RF chain employs a power-hungry high-resolution ADC. To address this issue, some embodiments use low-resolution ADCs for the massive MIMO system, because the hardware complexity and power consumption grow exponentially with the resolution (i.e., the number of bits per measurement sample) of the ADC. In exemplar one-bit embodiment, the one-bit ADC simply compares the input analog signal with a threshold and requires minimum cost and power consumption.

Some embodiments are based on realization that one of the problems in the low in formativeness of the one-bit ADC, lies in the fact that the threshold for determining the value of the bit can be constant and selected to be statistically natural. For example, when the threshold is selected to be zero, the one bit of information representing a result of a comparison of the measurement with a zero-valued threshold indicates only a sign of the measurement, i.e., whether the measurements is positive or negative, but fails to report on the magnitude of the measurements.

For example, if the result of comparison indicates that the measurement of the signal is greater than a threshold having a value, let say, three, that one bit of information indicating that the signal is greater than three carries statistically more information than one bit of information indicating that the signal is greater than zero, i.e., positive. Notably, the values of the time varying thresholds needs to be preserved in order to take advantage of the knowledge of the values of the threshold. However, the memory preserving such information can be shared across multiple RF chains and/or reused for other computational needs of the MIMO system. Further, the one-bit ADCs sampling the analog signals with time-varying thresholds can reduce the cost of the massive MIMO system, while allowing using multiple RF chains in recovering transmitted data and/or parameters of the wireless channel.

For example, one embodiment discloses a receiver for use in a wireless communication system to receive signals transmitted over a wireless channel. The receiver includes a plurality of antennas and a plurality of radio-frequency (RF) chains coupled the plurality of antennas. Each RF chain includes a one-bit analog-to-digital converter (ADC) to convert each measurement of an analog signal received by the antenna into one bit of information representing a result of a comparison of the measurement with a randomly selected threshold to produce a sequence of bits and a corresponding sequence of thresholds. Wherein each bit in the sequence of bits represents a relative value of the measurement of the analog signal with respect to a threshold from the corresponding sequence of thresholds. A processor can be coupled to the plurality of RF chains can estimate at least some parameters of the wireless channel using the sequences of bits and the corresponding sequences of thresholds received from the plurality of RF chains. As used herein, randomly selected thresholds are selected independently from the values of the measurements themselves. However, in various embodiments, the randomness of the threshold can be truly random, pseudo-random, as well as uniformly random or random according to a probability density function.

Further, in some embodiments the processor can use the random number to select a threshold from a set of thresholds representing the quantize space of the thresholds. Wherein this embodiment allows considering the possible values of the thresholds based on the types of the transmitted signals. For example, the set of thresholds can include more positive value than the negative to reflect the believe on distribution of the values. In another example, the set of thresholds can include at least two elements with the same value, e.g., zero values, to represent statistical tendency, which allows increasing the range of the threshold values to collect the information about measurement outliers of the transmitted signal.

Further still, in some embodiments of the present disclosure, the values of the elements in set of thresholds can be sampled according to a probability distribution function. Wherein, in one implementation, the processor estimates a probability distribution function reflecting a density of the transmitted signal. Such probability distribution function can be estimated based on relative values of the measurements with respect to the thresholds. Selecting the thresholds using the probability distribution function can increase statistical value of the one-bit samples of the measurements.

<FIG> shows a block diagram of method steps of an embodiment for a wireless communication system in accordance with one embodiment of the present disclosure. The computer implemented method <NUM> is for decoding a symbol transmitted over a wireless MIMO channel by a first communication device, and begins with step <NUM> of <FIG>, that includes a second communication device <NUM> receiving a test symbol transmitted over the wireless channel.

Step <NUM> of <FIG> for method <NUM> includes the communication device <NUM> estimating the channel state information (CSI) of the wireless MIMO channel from quantized test symbol according to an angular-domain channel model with statistics on multi-dimensional paths including an angle of departure (AoD), angle of arrival (AoA), the channel path gain, the channel spread, propagating in the wireless MIMO channel.

Step <NUM> of <FIG> for method <NUM> includes encoding a symbol received over the wireless MIMO channel by a receiver using the CSI.

<FIG> shows a schematic of a wireless communication system <NUM> in accordance with one embodiment of the present disclosure. The communication system <NUM> includes the first communication device <NUM> able to communicate with the second communication device <NUM> over a communication channel <NUM>. The communication channel <NUM> is a wireless MIMO channel. The channel can cover a wide frequency spectrum from <NUM> GigaHertz (GHz) to <NUM> or beyond <NUM>. For example, the first communication device <NUM> and/or the second communication device <NUM> can communicate with each other in accordance with the <NUM>. 11ad standard.

For example, the device <NUM> includes Ntx antennas <NUM> and the device <NUM> includes Nrx antennas <NUM> to transmit a single data stream over the channel <NUM> by a single antenna or over multiple antennas using beamforming and/or spatial multiplexing. The single data stream can be split into multiple sub-data streams that are then individually and simultaneously transmitted over the same communication channel such as channel <NUM> from the multiple antennas. Although the scope of the present disclosure is not limited in this respect, types of antennas used by various embodiments for antennas <NUM> and/or <NUM> include but are not limited to internal antenna, dipole antenna, omni-directional antenna, a monopole antenna, an end fed antenna, a circularly polarized antenna, a micro-strip antenna, a diversity antenna and the like.

The communication device <NUM> includes a transmitter <NUM> to transmit a beam-formed transmission by transmitting the data stream via Ntx antennas <NUM>, respectively. The communication device <NUM> includes a receiver <NUM> to receive the data stream over the channel <NUM> via the Nrx antennas <NUM>. The received signal may include symbols corresponding, for example, to symbols of the signal transmitted by transmitter <NUM>.

In some embodiments, the receiver <NUM> includes a front end <NUM> and/or a transformer <NUM>. The front end <NUM> can include any suitable front end module to convert a time-domain signal received from antenna <NUM> into a time-domain signal of a format suitable for transformer <NUM>. Transformer <NUM> may transform the signal into a plurality of different types of signals that are suitable for a decoder <NUM> or a channel estimator <NUM>. For example, the frond end can convert the received signal into a symbol suitable for the decoding.

The receiver <NUM> also includes a channel estimator <NUM> to generate a signal representing channel estimation. The receiver <NUM> can also include a decoder <NUM> to decode the received signal and to generate signal representing an estimation of the signal transmitted by the device <NUM>. The channel estimator <NUM> uses a probabilistic model in the environment of the channel <NUM>.

<FIG> shows a block diagram of a method for decoding a symbol transmitted over the wireless channel according to one embodiment of the present disclosure. The method receives <NUM> a test symbol <NUM> transmitted over the wireless channel, quantizes <NUM> the test symbol into a few bits or just <NUM> bit in the extreme case, and estimates <NUM> state information <NUM> of the wireless channel on the quantized test symbol <NUM>. The value of the test symbol is known and the estimation is performed according to an angular-domain model of the wireless channel that includes statistics on paths, gain and spread of the wireless propagation channel. When the method receives <NUM> a symbol <NUM>, e.g., a data symbol, the method detects <NUM> the symbol <NUM> using the state information <NUM> of the wireless channel. The steps of the method can be performed by a processor of a receiver.

<FIG> shows a schematic of the wireless MIMO system of <FIG> according to some embodiments of the present disclosure; Step 110A and Step 110B send the sequence of bits into the wireless channel. Step 112A and Step 112B receive the propagated wireless signals from the receiving antenna array. Step 116A and Step 116B include the RF components such as low-noise amplifiers which pre-process the received analogy waveforms. Step <NUM> and Step <NUM> of <FIG> form the I/Q channels of the received signal by using the Hilbert transform. Step 128A and Step 128B quantize the analog baseband signals of the I/Q channels using low-resolution ADCs. One low-resolution ADC is used for one receiving antenna or one RF chain. Step <NUM> includes all the baseband signal processing on the quantized I/Q signals.

<FIG> shows a schematic of the quantization of the I/Q baseband signals with a fixed threshold at zero, including an I-channel waveform compared with Threshold λ<NUM>), and a Q-channel waveform compared with Threshold λ<NUM>, according to some embodiments of the present disclosure.

Step 282A compares the input waveform of the I channel with the fixed threshold at <NUM> to output <NUM> bit: +<NUM> if the input waveform is positive or -<NUM> if the input waveform is negative.

Step 282B compares the input waveform of the Q channel with the fixed threshold at <NUM> to output <NUM> bit: +<NUM> if the input waveform is positive or -<NUM> if the input waveform is negative.

<FIG> show graphs illustrating an example of the I/Q channel quantization with a fixed threshold at zero. From these figures, it is shown that the fixed threshold quantization at <NUM> produces the same quantized bits for two signals with the amplitude of one signal is twice larger than the amplitude of the other signal. In other words, the fixed threshold quantization at <NUM> can indicate only a sign of the measurement, i.e., whether the measurements is positive or negative, but fails to report on the magnitude of the measurements.

<FIG> show graphs illustrating an example of the I channel quantization with a fixed threshold at zero, <FIG> shows an example of the analog I-channel baseband waveform of <FIG>, <FIG> is comparing the analog I-channel baseband waveform with Threshold λ<NUM> of <FIG>, according to some embodiments of the present disclosure.

<FIG> shows an analogy I-channel baseband signal of 257A with the x-axis denoting the time and the y-axis denoting the signal amplitude. <FIG> shows the quantized bits of 258A by comparing the analogy signal of 257A with zeros.

<FIG> show graphs illustrating an example of the Q-channel quantization with a fixed threshold at zero, <FIG> shows an example of the analog Q-channel baseband waveform of <FIG>, and <FIG> is comparing the analog Q-channel baseband waveform with Threshold λ<NUM> of <FIG>, wherein the outputs are +<NUM> if the signal is larger than zero (<FIG>), and -<NUM> if the signal is less than zero (<FIG>), according to some embodiments of the present disclosure.

<FIG> shows an analogy Q-channel baseband signal of 257B with the x-axis denoting the time and the y-axis denoting the signal amplitude. <FIG> shows the quantized bits of 258B by comparing the analogy signal of 257B with zeros.

<FIG> shows a graph illustrating the same analog I-channel baseband signal of <FIG>, except the amplitude is multiplied by <NUM>. <FIG> shows the quantized I-channel baseband signal by comparing the <FIG> graph with the zero, according to some embodiments of the present disclosure.

<FIG> shows an analogy I-channel baseband signal of 267A which is the same with respect to the signal 257A in <FIG> except the amplitude is multiplied by <NUM>. <FIG> shows the quantized bits of 268A by comparing the analogy signal of 267A with zeros. The quantized bits in 268A are the exactly same as the quantized bits in 258A in <FIG>, although the input waveforms are different in amplitudes.

<FIG> shows a graph illustrating the same analog Q-channel baseband signal of <FIG>, except the amplitude is multiplied by <NUM>. <FIG> shows the quantized Q-channel baseband signal by comparing the <FIG> graph with the zero, according to some embodiments of the present disclosure.

<FIG> shows an analogy Q-channel baseband signal of 267B which is the same with respect to the signal 257B in <FIG> except the amplitude is multiplied by <NUM>. <FIG> shows the quantized bits of 268B by comparing the analogy signal of 267B with zeros. The quantized bits in 268B are the exactly same as the quantized bits in 258B in <FIG>, although the input waveforms are different in amplitudes.

It is seen that graphs 268A of <FIG> and 268B of <FIG> is the same as graphs 258A of <FIG> and 258B of <FIG>, because the multiplication of <NUM> does not change the positive or negative sets of the signal.

<FIG> shows a schematic of the quantization of the analog I/Q-channel baseband signals with a randomly selected threshold from a candidate set, including an I-channel waveform compared with Threshold λ<NUM>), and a Q-channel waveform compared with Threshold λ<NUM>), according to some embodiments of the present disclosure;.

Step 380A randomly generates an integer l which is between <NUM> and the length of a threshold candidate set Ω. Step 381A determines the threshold by indexing the l-th element of the candidate set Ω. Step 382A compares the input waveform for the I channel with the selected threshold to output <NUM> bit, i.e., +<NUM> or -<NUM>, i.e., comparing the I channel waveform with Threshold λ<NUM>.

Step 380B randomly generates an integer m which is between <NUM> and the length of a threshold candidate set Ω<NUM>. Step 381B determines the threshold by indexing the m-th element of the candidate set Ω<NUM>. Step 382B compares the input waveform for the Q channel with the selected threshold to output <NUM> bit, i.e., +<NUM> or -<NUM>, i.e., comparing the Q channel waveform with Threshold λ<NUM>.

<FIG> is a graph illustrating an example of the I channel quantization with the time-varying thresholds, showing the randomly generated integers for all sampling time instances for the I channel, including a candidate set of randomly selected thresholds for the I channel, according to some embodiments of the present disclosure.

Specifically, <FIG> shows an example of the I channel quantization with the time-varying thresholds 371A, in particular, showing the randomly generated integers for all sampling time instances for the I channels. In this example, the size of the threshold candidate set is <NUM>, 372A. As a result, the random integers are in between <NUM> and <NUM>.

<FIG> is a graph illustrating an example of the Q channel quantization with the time-varying thresholds 371B, showing the randomly generated integers for all sampling time instances for the Q channel, including a candidate set of randomly selected thresholds for the Q channel, according to some embodiments of the present disclosure.

Specifically, <FIG> shows an example of the Q channel quantization with the time-varying thresholds 371B, in particular, showing the randomly generated integers for all sampling time instances for the Q channels. In this example, the size of the threshold candidate set is <NUM>, 372B. As a result, the random integers are in between <NUM> and <NUM>.

Regarding <FIG> and <FIG>, the graphs show that two threshold candidate sets for the I channel (372A) and the Q channel (372B), in this specific example, the two sets are the same with <NUM> numbers between -<NUM> and <NUM>.

<FIG> is a graph illustrating the selected time-varying thresholds for the I channel by indexing the randomly generated integers from <FIG>, in the threshold set of 372A of <FIG>, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the selected time-varying thresholds for the Q channel by indexing the randomly generated integers from <FIG>, in the threshold set of 372B of <FIG>, according to some embodiments of the present disclosure.

Regarding <FIG> and <FIG>, the graphs show that the selected thresholds are different between the I channel (<FIG>) and Q channel <FIG>).

<FIG> is a graph illustrating the same I signal of graph 267A of <FIG>, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the same quantized I signal of graph 268A of <FIG>, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the same Q signal of graph 267B of <FIG>, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the same quantized Q signal of graph 268B of <FIG>, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the same I signal of graph 257A of <FIG>, but with the time-varying thresholds, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the same Q signal of graph 257B of <FIG>, but with the time-varying thresholds, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the quantized I signal by comparing the signal of graph 357AA of <FIG>, with the thresholds in graph 373A of <FIG>, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the quantized Q signal by comparing the signal of graph 357BB of <FIG>, with the thresholds in graph 373B of <FIG>, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the same I signal of graph 267A of <FIG>, but with the time-varying thresholds, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the same Q signal of graph 267B of <FIG>, but with the time-varying thresholds, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the quantized I signal by comparing the signal of graph 367AA of <FIG>, with the thresholds in graph 373A of <FIG>, according to some embodiments of the present disclosure.

<FIG> is a graph illustrating the quantized Q signal by comparing the signal of graph 367BB of <FIG>, with the thresholds in graph 373B of <FIG>, according to some embodiments of the present disclosure.

It is seen that, in contrast to the quantized signals in <FIG>, <FIG>, <FIG> and <FIG>, which are the same, the quantized signals in <FIG>, <FIG>, are different due to the time-varying thresholds.

<FIG> shows a block diagram of some method steps for the quantization of the I/Q baseband signals with a randomly selected threshold which is not chosen from a threshold candidate set, according to some embodiments of the present disclosure.

Step 580A randomly generates a real number which may be limited in an interval due to physical constraints for the I channel waveform. Step 582A compares the input waveform for the I channel with the selected threshold to output <NUM> bit, i.e., +<NUM> or -<NUM>.

Step 580B randomly generates a real number which may be limited in an interval due to physical constraints for the Q channel waveform. Step 582B compares the input waveform for the Q channel with the selected threshold to output <NUM> bit, i.e., +<NUM> or -<NUM>.

<FIG> shows a block diagram of some method steps for the quantization of the I/Q baseband signals with a randomly selected threshold which uses some prior knowledge about the wireless channel, e.g., the long-term channel statistics, according to some embodiments of the present disclosure.

Step 586A represents the prior knowledge from past measurement(s), geometry and other knowledge sources for the I channel waveform. Step 580A randomly generates a real number which may be limited in an interval due to physical constraints and utilizes the prior knowledge for the I channel waveform. Step 582A compares the input waveform for the I channel with the selected threshold to output <NUM> bit, i.e., +<NUM> or -<NUM>.

Step 580B represents the prior knowledge from past measurement(s), geometry and other knowledge sources for the Q channel waveform. Step 580B randomly generates a real number which may be limited in an interval and utilizes the prior knowledge due to physical constraints for the Q channel waveform. Step 582B compares the input waveform for the Q channel with the selected threshold to output <NUM> bit, i.e., +<NUM> or -<NUM>.

<FIG> shows a schematic illustrating principles of propagation in the wireless channel employed by various embodiments, according to some embodiments of the present disclosure. For example, a signal sent from the transmitter <NUM> reaches the receiver <NUM> via channel paths <NUM>, <NUM> and <NUM>. The objects <NUM>, <NUM> bounce off the wireless waves, the arrivals at the receiver via the reflected paths <NUM>, <NUM>. The channel paths can be sparse, i.e., a few paths if the millimeter wave is used for propagation. The channel paths can spread over the angle of departure from the transmitter and the angle of arrival to the receiver.

<FIG> shows a schematic of various metrics of statistics in the space of propagation of the wireless channel according to some embodiments of the present disclosure. For example, the space of propagation of the wireless signal can be represented as a Carterisan product of the set of possible angles of the directions of departure (DoD) of and angles of the directions of arrivals (DoA). The virtual angular-domain channel model can be pictorially represented as a two-dimensional grid <NUM>, in which the DoA and DoD are represented with angles of arrival (AoA) <NUM> and angles of departure (AoD) <NUM> along the axis. A non-zero patch of energy <NUM> at, for example, AoA θ<NUM> <NUM> and AoD φ<NUM> <NUM>, indicates that there is a path in the wireless channel such that a signal transmitted in the beam in the direction φ<NUM> reaches receiver from the direction of θ<NUM>.

<FIG> is a block diagram of illustrating the method of <FIG>, that can be implemented using an alternate controller, according to embodiments of the present disclosure. The controller <NUM> includes a processor <NUM>, computer readable memory <NUM>, storage <NUM> and user interface <NUM> with display <NUM> and keyboard <NUM>, which are connected through bus <NUM>. For example, the user interface <NUM> in communication with the processor <NUM> and the computer readable memory <NUM>, acquires and stores the data in the computer readable memory <NUM> upon receiving an input from a surface, keyboard surface, of the user interface <NUM> by a user.

Contemplated is that the memory <NUM> can store instructions that are executable by the processor, historical data, and any data to that can be utilized by the methods and systems of the present disclosure. The processor <NUM> can be a single core processor, a multi-core processor, a computing cluster, or any number of other configurations. The processor <NUM> can be connected through a bus <NUM> to one or more input and output devices. The memory <NUM> can include random access memory (RAM), read only memory (ROM), flash memory, or any other suitable memory systems.

Still referring to <FIG>, a storage device <NUM> can be adapted to store supplementary data and/or software modules used by the processor. For example, the storage device <NUM> can store historical data and other related data as mentioned above regarding the present disclosure. Additionally, or alternatively, the storage device <NUM> can store historical data similar to data as mentioned above regarding the present disclosure. The storage device <NUM> can include a hard drive, an optical drive, a thumb-drive, an array of drives, or any combinations thereof.

The system can be linked through the bus <NUM> optionally to a display interface (not shown) adapted to connect the system to a display device (not shown), wherein the display device can include a computer monitor, camera, television, projector, or mobile device, among others.

The controller <NUM> can include a power source <NUM>, depending upon the application the power source <NUM> may be optionally located outside of the controller <NUM>. Linked through bus <NUM> can be a user input interface <NUM> adapted to connect to a display device <NUM>, wherein the display device <NUM> can include a computer monitor, camera, television, projector, or mobile device, among others. A printer interface <NUM> can also be connected through bus <NUM> and adapted to connect to a printing device <NUM>, wherein the printing device <NUM> can include a liquid inkjet printer, solid ink printer, large-scale commercial printer, thermal printer, UV printer, or dye-sublimation printer, among others. A network interface controller (NIC) <NUM> is adapted to connect through the bus <NUM> to a network <NUM>, wherein data or other data, among other things, can be rendered on a third party display device, third party imaging device, and/or third party printing device outside of the controller <NUM>.

Still referring to <FIG>, the data or other data, among other things, can be transmitted over a communication channel of the network <NUM>, and/or stored within the storage system <NUM> for storage and/or further processing. Further, the data or other data may be received wirelessly or hard wired from a receiver <NUM> (or external receiver <NUM>) or transmitted via a transmitter <NUM> (or external transmitter <NUM>) wirelessly or hard wired, the receiver <NUM> and transmitter <NUM> are both connected through the bus <NUM>. Further, a GPS <NUM> may be connected via bus <NUM> to the controller <NUM>. The controller <NUM> may be connected via an input interface <NUM> to external sensing devices <NUM> and external input/output devices <NUM>. The controller <NUM> may be connected to other external computers <NUM>. An output interface <NUM> may be used to output the processed data from the processor <NUM>.

The above-described embodiments of the present disclosure can be implemented in any of numerous ways. For example, the embodiments may be implemented using hardware, software or a combination thereof. Use of ordinal terms such as "first," "second," in the claims to modify a claim element does not by itself connote any priority, precedence, or order of one claim element over another or the temporal order in which acts of a method are performed, but are used merely as labels to distinguish one claim element having a certain name from another element having a same name (but for use of the ordinal term) to distinguish the claim elements.

Claim 1:
A receiver (<NUM>) for use in a wireless communication system (<NUM>) to receive signals transmitted over a wireless channel (<NUM>), the receiver comprising:
a plurality of antennas (<NUM>);
a plurality of radio-frequency, RF, chains coupled the plurality of antennas (<NUM>), each RF chain includes a one-bit analog-to-digital converter, ADC, (<NUM>) configured to convert each measurement of an analog signal received by the antenna (<NUM>) into one bit of information representing a result of a comparison of the measurement with a randomly selected threshold to produce a sequence of bits and a corresponding sequence of thresholds, wherein each bit in the sequence of bits represents a relative value of the measurement of the analog signal with respect to a threshold from the corresponding sequence of thresholds;
a processor (<NUM>, <NUM>) coupled to the plurality of RF chains and configured to estimate at least some parameters of the wireless channel (<NUM>) using the sequences of bits and the corresponding sequences of thresholds received from the plurality of RF chains; and
a random-number generator,
characterized in that
the random-number generator is configured to generate a random number within a predetermined range, the processor (<NUM>, <NUM>) is configured to select the randomly selected threshold, based on the random number, for each time step, the processor (<NUM>, <NUM>) is configured to select different thresholds for at least some different RF chains, and the parameters of the wireless channel (<NUM>) estimated by the processor (<NUM>, <NUM>) include a two-dimensional channel matrix including angles-of-departure, angles-of-arrival, and channel path spreads.