Methods and apparatus for transmitting signals based on signal sampler in mobile communications
Patent Information
- Application Number
- PCT/CN2026/083294
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2025-03-14
- Filing Date
- 2026-03-13
- Publication Date
- 2026-09-17
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Figure CN2026083294_17092026_PF_FP_ABST
Abstract
Description
METHODS AND APPARATUS FOR TRANSMITTING SIGNALS BASED ON SIGNAL SAMPLER IN MOBILE COMMUNICATIONSCROSS REFERENCE TO RELATED PATENT APPLICATION (S)
[0001] The present disclosure is part of a non-provisional application claiming the priority benefit of U.S. Patent Application No. 63 / 771,696, filed 14 March 2025, the content of which herein being incorporated by reference in its entirety.TECHNICAL FIELD
[0002] The present disclosure is generally related to mobile communications and, more particularly, to transmitting signals based on signal sampler with respect to apparatus in mobile communications.BACKGROUND
[0003] Unless otherwise indicated herein, approaches described in this section are not prior art to the claims listed below and are not admitted as prior art by inclusion in this section.
[0004] In mobile communication systems, transmitted and received signals may be associated with multiple signal dimensions. Such dimensions may correspond to, for example, spatial, temporal, spectral, or other domains, depending on system configurations and application scenarios. In some scenarios, signal responses across multiple dimensions may be represented as multi-dimensional signal structures. For example, a wireless channel response is associated with one or more dimensions related to transmitting antenna elements, frequency resources, and time resources. In some scenarios, signal responses associated with sensing or environment observation may similarly span multiple dimensions corresponding to space, frequency, and time. For example, a sensing response in an Integrated Sensing And Communication (ISAC) system is associated with one or more dimensions related to spatial direction, propagation delay, Doppler frequency, or time.
[0005] However, conventional signal transmission and sampling techniques generally handle different signal dimensions in an independent manner or employ dense and regularly structured sampling over available resources. As the number of relevant dimensions increases, such techniques may result in a significant increase in transmission overhead, inefficient utilization of system resources, and increased power consumption. Furthermore, existing sampling or transmission designs that exhibit favorable spectral or correlation characteristics are typically limited to low-dimensional signal representations and do not readily provide a systematic or scalable approach for extension to higher-dimensional signal representations.
[0006] Accordingly, there is a need for improved signal transmission and sampling techniques that enable efficient representation or measurement of multi-dimensional signal responses across multiple domains.SUMMARY
[0007] The following summary is illustrative only and is not intended to be limiting in any way. That is, the following summary is provided to introduce concepts, highlights, benefits and advantages of the novel and non-obvious techniques described herein. Select implementations are further described below in the detailed description. Thus, the following summary is not intended to identify essential features of the claimed subject matter, nor is it intended for use in determining the scope of the claimed subject matter.
[0008] An objective of the present disclosure is to propose solutions or schemes that address the aforementioned issues pertaining to transmitting signals based on a signal sampler with respect to apparatus in mobile communications.
[0009] In one aspect, a method may involve an apparatus determining a signal sampler for a finite-dimensional signal tensor. The signal sampler may be determined by an outer product of a plurality of sub-samplers. The method may further involve the apparatus transmitting a plurality of signals based on the signal sampler for the finite-dimensional signal tensor.
[0010] In one aspect, a method may involve an apparatus receiving a plurality of signals. The plurality of signals may be transmitted based on a signal sampler for a finite-dimensional signal tensor, and the signal sampler may be determined by an outer product of a plurality of sub-samplers.
[0011] In one aspect, an apparatus may comprise a transceiver which, during operation, wirelessly communicates with a wireless network. The apparatus may also comprise a processor communicatively coupled to the transceiver. The processor, during operation, may perform operations comprising determining a signal sampler for a finite-dimensional signal tensor. The signal sampler may be determined by an outer product of a plurality of sub-samplers. The processor may further perform operations comprising transmitting a plurality of signals based on the signal sampler for the finite-dimensional signal tensor.
[0012] It is noteworthy that, although description provided herein may be in the context of certain radio access technologies, networks and network topologies such as Long-Term Evolution (LTE) , LTE-Advanced, LTE-Advanced Pro, 5th Generation (5G) , New Radio (NR) , Internet-of-Things (IoT) and Narrow Band Internet of Things (NB-IoT) , Industrial Internet of Things (IIoT) , and 6th Generation (6G) , the proposed concepts, schemes and any variation (s) / derivative (s) thereof may be implemented in, for and by other types of radio access technologies, networks and network topologies. Thus, the scope of the present disclosure is not limited to the examples described herein.BRIEF DESCRIPTION OF THE DRAWINGS
[0013] The accompanying drawings are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of the present disclosure. The drawings illustrate implementations of the disclosure and, together with the description, serve to explain the principles of the disclosure. It is appreciable that the drawings are not necessarily in scale as some components may be shown to be out of proportion than the size in actual implementation in order to clearly illustrate the concept of the present disclosure.
[0014] FIG. 1 is a diagram depicting an example scenario under schemes in accordance with implementations of the present disclosure.
[0015] FIG. 2 is a diagram depicting an example scenario under schemes in accordance with implementations of the present disclosure.
[0016] FIG. 3 is a diagram depicting an example scenario under schemes in accordance with implementations of the present disclosure.
[0017] FIG. 4 is a diagram depicting an example scenario under schemes in accordance with implementations of the present disclosure.
[0018] FIG. 5 is a diagram depicting an example scenario under schemes in accordance with implementations of the present disclosure.
[0019] FIG. 6 is a diagram depicting an example scenario under schemes in accordance with implementations of the present disclosure.
[0020] FIG. 7 is a diagram depicting an example scenario under schemes in accordance with implementations of the present disclosure.
[0021] FIG. 8 is a block diagram of an example communication system in accordance with an implementation of the present disclosure.
[0022] FIG. 9 is a flowchart of an example process in accordance with an implementation of the present disclosure.
[0023] FIG. 10 is a flowchart of an example process in accordance with an implementation of the present disclosure. DETAILED DESCRIPTION OF PREFERRED IMPLEMENTATIONS
[0024] Detailed embodiments and implementations of the claimed subject matters are disclosed herein. However, it shall be understood that the disclosed embodiments and implementations are merely illustrative of the claimed subject matters which may be embodied in various forms. The present disclosure may, however, be embodied in many different forms and should not be construed as limited to the exemplary embodiments and implementations set forth herein. Rather, these exemplary embodiments and implementations are provided so that description of the present disclosure is thorough and complete and will fully convey the scope of the present disclosure to those skilled in the art. In the description below, details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the presented embodiments and implementations. Overview
[0025] Implementations in accordance with the present disclosure relate to various techniques, methods, schemes and / or solutions pertaining to transmitting signals based on a signal sampler with respect to apparatus in mobile communications. According to the present disclosure, a number of possible solutions may be implemented separately or jointly. That is, although these possible solutions may be described below separately, two or more of these possible solutions may be implemented in one combination or another.
[0026] In some scenarios, multi-dimensional network state information may be represented as a D-dimensional tensor. In particular, the D-dimensional tensor h may have a size of (N1, N2, …, ND) , where D denotes a number of dimensions and Nd denotes a size of the d-th dimension. Accordingly, the size of the D-dimensional tensor h may be denoted as size (h) =(N1, N2, …, ND) . A value of the tensor value at a given D-dimensional index (n1, n2, …, nD) may be expressed as h (n1, n2, …, nD) , where nd=0, 1, …Nd-1 for all d=1, …D. The tensor value h (n1, n2, …, nD) may be either real or complex.
[0027] The tensor value h (n1, n2, …, nD) may be expressed as a linear weighted sum of a number Q of D-dimensional sinusoids. Specifically, the tensor value may be represented as: where λq denotes a complex-valued weighting coefficient associated with a q-th sinusoid, and kd,q denotes a frequency index of the q-th sinusoid along a d-th dimension.
[0028] In some scenarios, a sampler sh may be used for the D-dimensional tensor h. The sampler sh may be a tensor having the same dimensionality as h. Each element of the sampler sh may have a value of either 0 or 1. In particular, for any D-dimensional index (s1, s2, …, sD) , the sampler value sh (s1, s2, …, sD) may be either 0 or 1. A sampler value of sh (s1, s2, …, sD) =1 may indicate that the corresponding tensor value h (s1, s2, …, sD) is sampled (or recorded by the sampler) . A sampler value sh (s1, s2, …, sD) =0 may indicate that the corresponding tensor value h (s1, s2, …, sD) is not sampled (or not recorded by the sampler) .
[0029] Regarding the present disclosure, a transmitter (TX) may determine a signal sampler for a finite-dimensional signal tensor. The signal sampler may be determined by an outer product of a plurality of sub-samplers. Based on the outer product of the plurality of sub-samplers, the signal sampler may have a structured and sparse finite-dimensional sampling pattern that may reduce sampling density while preserving essential signal characteristics. The TX may transmit a plurality of signals based on the signal sampler for the finite-dimensional signal tensor. A receiver (RX) may receive the plurality of signals and process the plurality of signals.
[0030] Accordingly, since the signal sampler served as a sampling mask may have the structured and sparse finite-dimensional sampling pattern that may reduce sampling density while preserving essential signal characteristics, the signal transmission overhead and resource consumption may be reduced, while maintaining reliable representation or measurement performance.
[0031] FIG. 1 illustrates an example scenario 100 under schemes in accordance with implementations of the present disclosure. Scenario 100 involves a TX and an RX, which may be a part of a wireless communication network (e.g., an LTE network, a 5G / NR network, an IoT network or a 6G network) . Scenario 100 illustrates the current network framework. The TX may communicate with the RX.
[0032] It should be noted that, for purposes of illustration and ease of explanation, in FIG. 1, the TX may include a network node, and the RX may include a User Equipment (UE) . However, such descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. Those skilled in the art will recognize that, in alternative embodiments, the TX may be implemented by the UE, and / or the RX may be implemented by the network node.
[0033] In some embodiments, the TX may determine a signal sampler for a finite-dimensional signal tensor (i.e., a finite-dimensional signal array) . In particular, the signal sampler may include another signal tensor (i.e., signal array) having the same dimension (s) as the finite-dimensional signal tensor. Each element of the signal sampler may include a first value (e.g., 1) indicating that a corresponding element of the finite-dimensional signal tensor may be sampled or a second value (e.g., 0) indicating that the corresponding element of the finite-dimensional signal tensor may not be sampled.
[0034] In some implementations, the signal sampler may be determined by an outer product of a plurality of sub-samplers. In particular, the signal sampler may be constructed by the composition of a plurality of lower-dimensional sub-samplers corresponding to respective signal dimensions, thereby enabling efficient construction and application of a higher-dimensional sampling pattern. In these implementations, each sub-sampler may have desirable spectral or correlation characteristics so that the signal sampler determined by the outer product of the plurality of sub-samplers may inherit corresponding spectral or correlation characteristics across multiple dimensions.
[0035] In some cases, the outer product of the plurality of sub-samplers may be preconfigured at the TX, and the signal sampler may be determined based on the preconfigured outer product. In some cases, the outer product of the plurality of sub-samplers may be calculated by the TX, and the signal sampler may be determined in real time.
[0036] For example, a two-dimensional signal sampler is constructed from an outer product of two one-dimensional sub-samplers. A three-dimensional signal sampler is constructed from an outer product of a two-dimensional sub-sampler and a one-dimensional sub-sampler. A four-dimensional signal sampler is constructed from an outer product of two two-dimensional sub-samplers.
[0037] For another example, a one-dimensional signal sampler is constructed from an outer product of a one-dimensional sub-sampler and a trivial one sub-sampler (i.e., a sub-sampler having a single element equal to one) . A two-dimensional signal sampler may be constructed from an outer product of a two-dimensional sub-sampler and a trivial one sub-sampler (i.e., a sub-sampler having a single element equal to one) .
[0038] In some implementations, based on the outer product of the plurality of sub-samplers, the signal sampler may have a structured and sparse finite-dimensional sampling pattern that may reduce sampling density while preserving essential signal characteristics. More specifically, efficient sampling of the finite-dimensional signal tensor may be achieved by designing a distribution of sampling mask values (i.e., the first value or the second value) in the signal sampler such that sampled values of the finite-dimensional signal tensor provide a representative approximation of the original finite-dimensional signal tensor, while minimizing a number of non-zero elements (i.e., the elements having the first values) in the signal sampler.
[0039] Then, the TX may transmit a plurality of signals based on the signal sampler for the finite-dimensional signal tensor. The RX may receive the plurality of signals and process the plurality of signals.
[0040] In some implementations, the finite-dimensional signal tensor may include multi-dimensional network state information. In particular, the finite-dimensional signal tensor may include a channel response or a sensing response in an Integrated Sensing and Communication (ISAC) system. In some cases, the channel response may be associated with at least one of the following dimensions: horizontal TX antenna, vertical TX antenna, frequency, and time. In some cases, the sensing response may be associated with at least one of the following dimensions: spatial direction, propagation delay, Doppler frequency, and time.
[0041] FIG. 2 illustrates an example scenario 200 under schemes in accordance with implementations of the present disclosure. For example, the finite-dimensional signal tensor is a D-dimensional tensor. Elements in the D-dimensional tensor represent responses of a Multiple-Input Multiple-Output (MIMO) channel. The D-dimensional tensor corresponds to fthe ollowing four dimensions: (1) Azimuth angle of Departure (AoD) from the network node φ, (2) Elevation angle of Departure (ZoD) from the network node θ (3) Path delay τ, and (4) Doppler shift ν. In an Orthogonal Frequency Division Multiplexing (OFDM) system, the MIMO channel observed by a single receive antenna can be expressed as a four-dimensional tensor h (i, j, m, n) as follows: where i, j, m, n are integer indices within respective ranges. Specifically, i denotes an azimuth antenna index, j denotes an elevation antenna index, m denotes a frequency index defined with respect to a pre-specified unit δf (e.g., a sub-carrier spacing or a multiple thereof) , n denotes a time index defined with respect to a pre-specified unit δt (e.g., an OFDM symbol or a multiple thereof) , and λq denotes a complex channel gain associated with the q-th propagation path.
[0042] In this example, the signal sampler indicates transmission of a constant-amplitude complex modulation symbol from an antenna element at a time and a frequency corresponding to the indices of the elements having the first values in the sampler. More specifically, the signal sampler defines a structured and sparse set of antenna, time, and frequency indices at which the constant-amplitude complex modulation symbols are transmitted, thereby enabling efficient sampling and representation of the four-dimensional MIMO channel tensor while reducing transmission overhead.
[0043] In some implementations, some samplers exhibiting desirable structural or spectral characteristics may be available for a one-dimensional tensor or a two-dimensional tensor. Samplers with comparable characteristics for higher-dimensional tensors may be more difficult to obtain. Accordingly, a higher-dimensional sampler may be efficiently constructed by forming an outer product of a plurality of lower-dimensional samplers.
[0044] In particular, a signal sampler of h may be represented as: where denotes the outer product of two sub-samplers (i.e., two corresponding tensors) , denotes a D1-dimensional sub-sampler having denotes a D2-dimensional sub-sampler having sh denotes a D-dimensional sampler having size (h) = (N1, N2, …, ND) , and D=D1+D2.
[0045] In some implementations, the plurality of sub-samplers may include a one-dimensional sub-sampler and / or a two-dimensional sub-sampler. In particular, the one-dimensional sub-sampler / two-dimensional sub-sampler may have a size. A Discrete Fourier Transform (DFT) of the one-dimensional sub-sampler / two-dimensional sub-sampler may have a peak-to-maximum-sidelobe ratio greater than a threshold. It should be noted that the peak-to-maximum-sidelobe ratio may be defined as a ratio between a magnitude of a main spectral peak and a maximum magnitude of sidelobes in a spectral representation. Therefore, when the DFT is applied to the one-dimensional sub-sampler / two-dimensional sub-sampler, the peak-to-maximum-sidelobe ratio may be defined based on DFT coefficients corresponding to a main lobe and sidelobes.
[0046] In some implementations, the one-dimensional sub-sampler may be associated with the Circular Golomb Ruler (CGR) . In particular, a size of the one-dimensional sub-sampler may be defined as n=k· (k-1) +1, where k denotes a number of elements having the first value (i.e., 1) in the one-dimensional sub-sampler. The one-dimensional sub-sampler associated with CGR may have the property that exactly ‘x’ (e.g., 1) coincidence of marker positions occurs between the one-dimensional sub-sampler and any of its cyclically shifted copies.
[0047] Specifically, modular differences mod (li-lj, n) for all i≠j span a set {1, 2, …, n-1} , and therefore such a structure may be referred to as a ruler (or a perfect difference set) , where l0,l1, …, lk-1 denote indices of the k markers (i.e., 1) in the ruler (i.e., the one-dimensional sub-sampler) .
[0048] FIG. 3 illustrates an example scenario 300 under schemes in accordance with implementations of the present disclosure. For example, the size of the one-dimensional sub-sampler is defined as n=4· (4-1) +1=13, where the number k of elements having the first value (i.e., 1) in the one-dimensional sub-sampler is 4. In this example, the one-dimensional sub-sampler sh (0, 1, …, 12) is represented as (1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1) corresponding to marker indices l0, l1, l2, l3 equal to 0, 2, 8, and 12, respectively. Alternatively, the one-dimensional sub-sampler is represented as a row vector [1 0 1 0 0 0 0 0 1 0 0 0 1] . The one-dimensional sub-sampler associated with CGR has the property that exactly one coincidence of marker positions occurs between the one-dimensional sub-sampler and any of its cyclically shifted copies.
[0049] Based on the foregoing disclosure, the CGR associated one-dimensional sub-sampler sh[l] may be used to sample a frequency response of a channel, where l=0, 1, …, n-1, and the size n is defined as n=k· (k-1) +1. In this context, a (scaled) cyclic autocorrelation function of the CGR associated one-dimensional sub-sampler in a time domain may be examined as: where denotes an Inverse Discrete Fourier Transform (IDFT) . The cyclic autocorrelation function may exhibit a constant peak-to-sidelobe ratio equal to k2 / (k-1) .
[0050] From this perspective, the CGR associated one-dimensional sub-sampler may be regarded as an effective one-dimensional sampler for a channel frequency response, since its cyclic autocorrelation function in the time domain approximates a Dirac delta function, thereby providing low sidelobe levels and reduced ambiguity in the sampling process.
[0051] In some implementations, the one-dimensional sub-sampler may be associated with a combinatorial difference set. In particular, indices of the elements having the first values in the one-dimensional sub-sampler may include the combinatorial difference set associated with the size of the one-dimensional sub-sampler, a number of non-zero elements of the one-dimensional sub-sampler and a value greater than or equal to one.
[0052] More specifically, the combinatorial difference set may be represented as an (n, k, λ) difference set. l0, l1, …, lk-1 denote the indices of the k number of elements having the first value (i.e., 1) in the one-dimensional sub-sampler of size n. The one-dimensional sub-sampler generated by the (n, k, λ) difference set, denoted as sh [l] , l=0, 1, …, n-1, may have the following properties.
[0053] In particular, every integer value in a set {1, 2, …, n-1} may be expressed as mod(li-lj, n) for some i≠j in exactly λ ways, or equivalently, mod (li-lj, n) for all i≠j spans {1, 2, …, n-1} λ times. In some cases, the one-dimensional sub-sampler may be non-cyclic or cyclic. More specifically, a non-cyclic difference set, in which a modulo operation is not applied when calculating pair-wise differences, may also be used as a one-dimensional sampler. Such a non-cyclic difference set may be sub-optimal in certain aspects when compared to a cyclic difference set. In addition, for the (n, k, λ) difference set, the parameters n, k, and λ may satisfy a relationship given by k2-k= (n-1) ·λ.
[0054] Therefore, a (scaled) cyclic autocorrelation function of the one-dimensional sub-sampler determined from the (n, k, λ) difference set may be examined as: The cyclic autocorrelation function may exhibit a constant peak-to-sidelobe ratio equal to For example, a (13, 9, 6) difference set is used to construct the one-dimensional sub-sampler sh= [1 1 1 1 0 1 1 1 0 0 1 0 1] .
[0055] In some implementations, the two-dimensional sub-sampler may be non-cyclic or cyclic. In some cases, the two-dimensional sub-sampler may be associated with a Perfect Periodic Costas Array (PPCA) . In particular, indices of the elements having the first values in the two-dimensional sub-sampler may include the PPCA associated with the size of the two-dimensional sub-sampler.
[0056] More specifically, the two-dimensional sub-sampler may be configured for compressive sampling of a signal composed of a sum of multiple two-dimensional complex sinusoids. The two dimensions of the two-dimensional sub-sampler may correspond to, for example, time-and-frequency, space-and-frequency, space-and-time, or space-and-space domains, such as azimuth and elevation. When the two-dimensional sub-sampler is associated with the PPCA, the two-dimensional sub-sampler may exhibit a property that exactly ‘x’ (e.g., 1) coincidence occurs between the two-dimensional sub-sampler and any of its two-dimensional cyclically shifted versions. It should be noted that exceptions may include purely vertical or purely horizontal cyclic shifts, for which no coincidence occurs. Such properties may provide favorable correlation characteristics for two-dimensional sampling.
[0057] FIG. 4 illustrates an example scenario 400 under schemes in accordance with implementations of the present disclosure. For example, the size of the two-dimensional sub-sampler is defined as 7 by 6. As shown in FIG. 4, the two-dimensional sub-sampler has a property that exactly one coincidence occurs between the two-dimensional sub-sampler and any of its two-dimensional cyclically shifted versions.
[0058] In some cases, the two-dimensional sub-sampler may be non-cyclic. In particular, a non-cyclic Costas array may also be used as the two-dimensional sub-sampler. Such a non-cyclic Costas array may be sub-optimal in some aspects when compared to a PPCA.
[0059] In some cases, the two-dimensional sub-sampler |sh [k, l] | may be constructed based on a periodic extension of a Welch construction of a Costas array. In particular, the two-dimensional sub-sampler |sh [k, l] | may be configured as an (n2+1) by n array, in which exactly one element having the first value (i.e., 1) is present in each column. For a given integer n such that n2+1 is a prime number, the two-dimensional sub-sampler |sh [k, l] | may be defined as:
[0060] The row index kl may be determined according to: kl=mod (αl, n2+1) -1 for l=0, …, n2-1 where α denotes a primitive root of a Galois Field GF (n+1) . It should be noted that the primitive root α in a Galois Field GF (pd) refers to an element of the field for which the set consists of distinct elements and spans all non-zero elements of the field.
[0061] FIG. 5 illustrates an example scenario 500 under schemes in accordance with implementations of the present disclosure. For example, regarding the two-dimensional sub-sampler, (n2+1) is 23 and α is 5. kl=mod (5l, 23) -1 which is a set of: {0, 4, 1, 9, 3, 19, 7, 16, 15, 10, 8, 21, 17, 20, 12, 18, 2, 14, 5, 6, 11, 13}
[0062] For another example, the indices [k, l] corresponds to frequency and time variables, respectively, such as sub-carrier indices and OFDM symbol indices in an OFDM system. For the two-dimensional sampler generated based on a PPCA, denoted as |sh [k, l] | and having a dimension of (n2+1) by n2, a cyclic ambiguity function of a time-domain sequence defined by sh[k, l] is characterized by a two-dimensional DFT of |sh [k, l] |2.
[0063] In particular, a squared magnitude of the cyclic ambiguity function χs [τ, ν] is represented as: where l corresponds to time, ν corresponds to Doppler, k corresponds to frequency, and τcorresponds to delay. |χs [τ, ν] |2 satisfies the following properties:
[0064] Accordingly, the two-dimensional sampler based on the PPCA may exhibit a near-constant peak-to-maximum-sidelobe ratio on the order of From this perspective, a PPCA may serve as an effective two-dimensional sampler for signals defined over frequency and time dimensions.
[0065] FIG. 6 illustrates an example scenario 600 under schemes in accordance with implementations of the present disclosure. For example, a signal sampler is determined by an outer product of two one-dimensional sub-samplers and
[0066] FIG. 7 illustrates an example scenario 700 under schemes in accordance with implementations of the present disclosure. For example, a signal sampler is determined by an outer product of one two-dimensional sub-sampler and one one-dimensional sub-sampler Illustrative Implementations
[0067] FIG. 8 illustrates an example communication system 800 having an example TX apparatus 810 and an example RX apparatus 820 in accordance with an implementation of the present disclosure. Each of TX apparatus 810 and RX apparatus 820 may perform various functions to implement schemes, techniques, processes and methods described herein pertaining to transmitting signals based on a signal sampler with respect to TX and RX in mobile communications, including scenarios / schemes described above as well as processes 900 and 1000 described below.
[0068] TX apparatus 810 / RX apparatus 820 may be a part of an electronic apparatus, which may be a UE such as a portable or mobile apparatus, a wearable apparatus, a wireless communication apparatus or a computing apparatus. For instance, TX apparatus 810 / RX apparatus 820 may be implemented in a smartphone, a smartwatch, a personal digital assistant, a digital camera, or a computing equipment such as a tablet computer, a laptop computer or a notebook computer. TX apparatus 810 / RX apparatus 820 may also be a part of a machine type apparatus, which may be an IoT, NB-IoT, or IIoT apparatus such as an immobile or a stationary apparatus, a home apparatus, a wire communication apparatus or a computing apparatus. For instance, TX apparatus 810 / RX apparatus 820 may be implemented in a smart thermostat, a smart fridge, a smart door lock, a wireless speaker or a home control center.
[0069] TX apparatus 810 / RX apparatus 820 may be a part of a network apparatus, which may be a network node such as a satellite, a base station, a small cell, a router or a gateway. For instance, TX apparatus 810 / RX apparatus 820 may be implemented in an eNodeB in an LTE network, in a gNB in a 5G / NR, IoT, NB-IoT or IIoT network or in a satellite or base station in a 6G network.
[0070] Alternatively, TX apparatus 810 / RX apparatus 820 may be implemented in the form of one or more integrated-circuit (IC) chips such as, for example and without limitation, one or more single-core processors, one or more multi-core processors, one or more reduced-instruction set computing (RISC) processors, or one or more complex-instruction-set-computing (CISC) processors. TX apparatus 810 / RX apparatus 820 may include at least some of those components shown in FIG. 8 such as a processor 812 / 822, for example. TX apparatus 810 / RX apparatus 820 may further include one or more other components not pertinent to the proposed scheme of the present disclosure (e.g., internal power supply, display device and / or user interface device) , and, thus, such component (s) of TX apparatus 810 / RX apparatus 820 are neither shown in FIG. 8 nor described below in the interest of simplicity and brevity.
[0071] In one aspect, each of processor 812 and processor 822 may be implemented in the form of one or more single-core processors, one or more multi-core processors, or one or more CISC processors. That is, even though a singular term “aprocessor” is used herein to refer to processor 812 and processor 822, each of processor 812 and processor 822 may include multiple processors in some implementations and a single processor in other implementations in accordance with the present disclosure. In another aspect, each of processor 812 and processor 822 may be implemented in the form of hardware (and, optionally, firmware) with electronic components including, for example and without limitation, one or more transistors, one or more diodes, one or more capacitors, one or more resistors, one or more inductors, one or more memristors and / or one or more varactors that are configured and arranged to achieve specific purposes in accordance with the present disclosure. In other words, in at least some implementations, each of processor 812 and processor 822 is a special-purpose machine specifically designed, arranged and configured to perform specific tasks including transmitting signals based on a signal sampler in a device (e.g., as represented by TX apparatus 810 / RX apparatus 820) and a network (e.g., as represented by TX apparatus 810 / RX apparatus 820) in accordance with various implementations of the present disclosure.
[0072] In some implementations, TX apparatus 810 / RX apparatus 820 may also include a transceiver 816 / 826 coupled to processor 812 / 822 and capable of wirelessly transmitting and receiving data. In other words, processor 812 / 822 may transceive the data such as configuration, message, signal, information, indicator, etc. via transceiver 816 / 826. In some implementations, TX apparatus 810 / RX apparatus 820 may further include a memory 814 / 824 coupled to processor 812 / 822 and capable of being accessed by processor 812 / 822 and storing data therein. Accordingly, TX apparatus 810 and RX apparatus 820 may wirelessly communicate with each other via transceiver 816 and transceiver 826, respectively. To aid better understanding, the following description of the operations, functionalities and capabilities of each of TX apparatus 810 and RX apparatus 820 is provided in the context of a mobile communication environment in which TX apparatus 810 / RX apparatus 820 is implemented in or as a communication apparatus or a UE and TX apparatus 810 / RX apparatus 820 is implemented in or as a network node of a communication network.
[0073] In some implementations, each of memory 814 and memory 824 may include a type of random-access memory (RAM) such as dynamic RAM (DRAM) , static RAM (SRAM) , thyristor RAM (T-RAM) and / or zero-capacitor RAM (Z-RAM) . Alternatively, or additionally, each of memory 814 and memory 824 may include a type of read-only memory (ROM) such as mask ROM, programmable ROM (PROM) , erasable programmable ROM (EPROM) and / or electrically erasable programmable ROM (EEPROM) . Alternatively, or additionally, each of memory 814 and memory 824 may include a type of non-volatile random-access memory (NVRAM) such as flash memory, solid-state memory, ferroelectric RAM (FeRAM) , magnetoresistive RAM (MRAM) and / or phase-change memory. Illustrative Processes
[0074] FIG. 9 illustrates an example process 900 in accordance with an implementation of the present disclosure. Process 900 may be an example implementation of above scenarios / schemes, whether partially or completely, with respect to transmitting signals based on a signal sampler of the present disclosure. Process 900 may represent an aspect of implementation of features of TX apparatus 810. Process 900 may include one or more operations, actions, or functions as illustrated by one or more of blocks 910 and 920. Although illustrated as discrete blocks, various blocks of process 900 may be divided into additional blocks, combined into fewer blocks, or eliminated, depending on the desired implementation. Moreover, the blocks of process 900 may be executed in the order shown in FIG. 9 or, alternatively, in a different order. Process 900 may be implemented by TX apparatus 810 or any suitable UE, network node or machine type devices. Solely for illustrative purposes and without limitation, process 900 is described below in the context of TX apparatus 810. Process 900 may begin at block 910.
[0075] At block 910, process 900 may involve processor 812 of TX apparatus 810 determining a signal sampler for a finite-dimensional signal tensor. The signal sampler may be determined by an outer product of a plurality of sub-samplers. Process 900 may proceed from block 910 to block 920.
[0076] At block 920, process 900 may involve processor 812 of TX apparatus 810 transmitting a plurality of signals based on the signal sampler for the finite-dimensional signal tensor.
[0077] In some implementations, the signal sampler may include another signal tensor having the same dimension as the finite-dimensional signal tensor. Each element of the signal sampler may include: (1) a first value indicating that a corresponding element of the finite-dimensional signal tensor may be sampled, or (2) a second value indicating that the corresponding element of the finite-dimensional signal tensor may not be sampled.
[0078] In some implementations, the plurality of sub-samplers may include a one-dimensional sub-sampler.
[0079] In some implementations, the one-dimensional sub-sampler may have a size. A DFT of the one-dimensional sub-sampler may have a peak-to-maximum-sidelobe ratio greater than a threshold.
[0080] In some implementations, indices of the elements having the first values in the one-dimensional sub-sampler may include a combinatorial difference set associated with the size of the one-dimensional sub-sampler, a number of non-zero elements of the one-dimensional sub-sampler and a value greater than or equal to one.
[0081] In some implementations, the combinatorial difference set may include an (n, k, λ) combinatorial difference set, while n is the size, k is the number, λ is the value, and k2-k= (n-1) ·λ is satisfied.
[0082] In some implementations, the one-dimensional sub-sampler may be cyclic or non-cyclic.
[0083] In some implementations, the plurality of sub-samplers may include a two-dimensional sub-sampler.
[0084] In some implementations, the two-dimensional sub-sampler may have a size. A DFT of the two-dimensional sub-sampler may have a peak-to-maximum-sidelobe ratio greater than a threshold.
[0085] In some implementations, indices of the elements having the first values in the two-dimensional sub-sampler may include a PPCA associated with the size of the two-dimensional sub-sampler.
[0086] In some implementations, the size may be n+1 by n while n+1 is a prime number. The indices of elements having the first values may be (mod (αl, n+1) , l) for l=0, …, n-1, where α is a primitive element of a Galois Field GF (n+1) .
[0087] In some implementations, the two-dimensional sub-sampler may be cyclic or non-cyclic.
[0088] In some implementations, the plurality of sub-samplers may include a trivial one sub-sampler.
[0089] In some implementations, the finite-dimensional signal tensor may include a channel response.
[0090] In some implementations, the channel response is associated with at least one of dimensions of horizontal TX antenna, vertical TX antenna, frequency and time.
[0091] In some implementations, the signal sampler may indicate transmission of a constant-amplitude complex modulation symbol from an antenna element at a time and a frequency corresponding to the indices of the elements having the first values in the sampler.
[0092] In some implementations, a frequency unit associated with the channel response may include a sub-carrier spacing or a multiple thereof. A time unit associated with the channel response may include an OFDM symbol duration or a multiple thereof.
[0093] FIG. 10 illustrates an example process 1000 in accordance with an implementation of the present disclosure. Process 1000 may be an example implementation of above scenarios / schemes, whether partially or completely, with respect to transmitting signals based on a signal sampler of the present disclosure. Process 1000 may represent an aspect of implementation of features of RX apparatus 820. Process 1000 may include one or more operations, actions, or functions as illustrated by block 1000. Although illustrated as discrete block, various blocks of process 1000 may be divided into additional blocks, combined into fewer blocks, or eliminated, depending on the desired implementation. Moreover, the blocks of process 1000 may be executed in the order shown in FIG. 10 or, alternatively, in a different order. Process 1000 may be implemented by RX apparatus 820 or any suitable UE, network node or machine type devices. Solely for illustrative purposes and without limitation, process 1000 is described below in the context of RX apparatus 820. Process 1000 may begin at block 1010.
[0094] At block 1010, process 1000 may involve processor 822 of RX apparatus 820 receiving a plurality of signals. The plurality of signals may be transmitted based on a signal sampler for a finite-dimensional signal tensor, and the signal sampler may be determined by an outer product of a plurality of sub-samplers. Additional Notes
[0095] The herein-described subject matter sometimes illustrates different components contained within, or connected with, different other components. It is to be understood that such depicted architectures are merely examples, and that in fact many other architectures can be implemented which achieve the same functionality. In a conceptual sense, any arrangement of components to achieve the same functionality is effectively "associated" such that the desired functionality is achieved. Hence, any two components herein combined to achieve a particular functionality can be seen as "associated with" each other such that the desired functionality is achieved, irrespective of architectures or intermedial components. Likewise, any two components so associated can also be viewed as being "operably connected" , or "operably coupled" , to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being "operably couplable" , to each other to achieve the desired functionality. Specific examples of operably couplable include but are not limited to physically mateable and / or physically interacting components and / or wirelessly interactable and / or wirelessly interacting components and / or logically interacting and / or logically interactable components.
[0096] Further, with respect to the use of substantially any plural and / or singular terms herein, those having skill in the art can translate from the plural to the singular and / or from the singular to the plural as is appropriate to the context and / or application. The various singular / plural permutations may be expressly set forth herein for sake of clarity.
[0097] Moreover, it will be understood by those skilled in the art that, in general, terms used herein, and especially in the appended claims, e.g., bodies of the appended claims, are generally intended as “open” terms, e.g., the term “including” should be interpreted as “including but not limited to, ” the term “having” should be interpreted as “having at least, ” the term “includes” should be interpreted as “includes but is not limited to, ” etc. It will be further understood by those within the art that if a specific number of an introduced claim recitation is intended, such an intent will be explicitly recited in the claim, and in the absence of such recitation no such intent is present. For example, as an aid to understanding, the following appended claims may contain usage of the introductory phrases "at least one" and "one or more" to introduce claim recitations. However, the use of such phrases should not be construed to imply that the introduction of a claim recitation by the indefinite articles "a" or "an" limits any particular claim containing such introduced claim recitation to implementations containing only one such recitation, even when the same claim includes the introductory phrases "one or more" or "at least one" and indefinite articles such as "a" or "an, " e.g., “a” and / or “an” should be interpreted to mean “at least one” or “one or more; ” the same holds true for the use of definite articles used to introduce claim recitations. In addition, even if a specific number of an introduced claim recitation is explicitly recited, those skilled in the art will recognize that such recitation should be interpreted to mean at least the recited number, e.g., the bare recitation of "two recitations, " without other modifiers, means at least two recitations, or two or more recitations. Furthermore, in those instances where a convention analogous to “at least one of A, B, and C, etc. ” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention, e.g., “asystem having at least one of A, B, and C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, etc. In those instances where a convention analogous to “at least one of A, B, or C, etc. ” is used, in general such a construction is intended in the sense one having skill in the art would understand the convention, e.g., “asystem having at least one of A, B, or C” would include but not be limited to systems that have A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, etc. It will be further understood by those within the art that virtually any disjunctive word and / or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase “A or B” will be understood to include the possibilities of “A” or “B” or “A and B. ”
[0098] From the foregoing, it will be appreciated that various implementations of the present disclosure have been described herein for purposes of illustration, and that various modifications may be made without departing from the scope and spirit of the present disclosure. Accordingly, the various implementations disclosed herein are not intended to be limiting, with the true scope and spirit being indicated by the following claims.
Claims
A method, comprising:determining, by a processor of an apparatus, a signal sampler for a finite-dimensional signal tensor, wherein the signal sampler is determined by an outer product of a plurality of sub-samplers; andtransmitting, by the processor, a plurality of signals based on the signal sampler for the finite-dimensional signal tensor.The method of Claim 1, wherein the signal sampler includes another signal tensor having the same dimension as the finite-dimensional signal tensor, and each element of the signal sampler includes a first value indicating that a corresponding element of the finite-dimensional signal tensor is sampled or a second value indicating that the corresponding element of the finite-dimensional signal tensor is not sampled.The method of Claim 2, wherein the plurality of sub-samplers includes a one-dimensional sub-sampler.The method of Claim 3, wherein the one-dimensional sub-sampler has a size, and a Discrete Fourier Transform (DFT) of the one-dimensional sub-sampler has a peak-to-maximum-sidelobe ratio greater than a threshold.The method of Claim 4, wherein indices of the elements having the first values in the one-dimensional sub-sampler include a combinatorial difference set associated with the size of the one-dimensional sub-sampler, a number of non-zero elements of the one-dimensional sub-sampler and a value greater than or equal to one.The method of Claim 5, wherein the combinatorial difference set includes an (n,k, λ) combinatorial difference set while n is the size, k is the number, λ is the value, and k2-k= (n-1) ·λ is satisfied.The method of Claim 3, wherein the one-dimensional sub-sampler is cyclic or non-cyclic.The method of Claim 2, wherein the plurality of sub-samplers includes a two-dimensional sub-sampler.The method of Claim 8, wherein the two-dimensional sub-sampler has a size, and a Discrete Fourier Transform (DFT) of the two-dimensional sub-sampler has a peak-to-maximum-sidelobe ratio greater than a threshold.The method of Claim 9, wherein indices of the elements having the first values in the two-dimensional sub-sampler include a Perfect Periodic Costas Array (PPCA) associated with the size of the two-dimensional sub-sampler.The method of Claim 10, wherein the size is n+1 by n while n+1 is a prime number, and the indices of elements having the first values are (mod (αl, n+1) , l) for l=0, …, n-1, where α is a primitive element of a Galois Field GF (n+1) .The method of Claim 8, wherein the two-dimensional sub-sampler is cyclic or non-cyclic.The method of Claim 2, wherein the plurality of sub-samplers includes a trivial one sub-sampler.The method of Claim 2, wherein the finite-dimensional signal tensor includes a channel response.The method of Claim 14, wherein the channel response is associated with at least one of dimensions of horizontal transmitting (TX) antenna, vertical TX antenna, frequency and time.The method of Claim 14, wherein the signal sampler indicates transmission of a constant-amplitude complex modulation symbol from an antenna element at a time and a frequency corresponding to the indices of the elements having the first values in the sampler.The method of Claim 14, wherein a frequency unit associated with the channel response includes a sub-carrier spacing or a multiple thereof, and a time unit associated with the channel response includes an Orthogonal Frequency Division Multiplexing (OFDM) symbol duration or a multiple thereof.A method, comprising:receiving, by a processor of an apparatus, a plurality of signals, wherein the plurality of signals is transmitted based on a signal sampler for a finite-dimensional signal tensor, and the signal sampler is determined by an outer product of a plurality of sub-samplers.An apparatus, comprising:a transceiver which, during operation, wirelessly communicates with a wireless network; anda processor communicatively coupled to the transceiver such that, during operation, the processor performs operations comprising:determining a signal sampler for a finite-dimensional signal tensor, wherein the signal sampler is determined by an outer product of a plurality of sub-samplers; andtransmitting, via the transceiver, a plurality of signals based on the signal sampler for the finite-dimensional signal tensor.The apparatus of Claim 19, wherein the signal sampler includes another signal tensor having the same dimension as the finite-dimensional signal tensor, and each element of the signal sampler includes a first value indicating that a corresponding element of the finite-dimensional signal tensor is sampled or a second value indicating that the corresponding element of the finite-dimensional signal tensor is not sampled.