Transmitting and receiving data to and from network nodes using grassmann constellations

Abstract

Methods and apparatus are provided. In an example, a method of communicating data to a network node is provided. The method includes selecting one of a plurality of reference signal symbol sequences based on data to be transmitted to a network node, where the reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase, the sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized. The method also includes transmitting the selected sequence of reference signal symbols to a network node.

Description

Technical Field

[0001] Example embodiments of the present disclosure relate to transmitting and / or receiving data to and / or from a network node, such as, for example, a reference signal symbol sequence. Background Art

[0002] The demand for wireless communications, such as for example according to fifth generation (5G) standards and beyond, has continued to grow, leading to the fact that communication technologies that can achieve high spectral efficiency while reducing computational complexity and energy usage will become increasingly important given the limited radio spectrum.

[0003] In some examples of wireless communications, a receiver requires channel information (also known as channel state information, CSI) to detect a data sequence transmitted from a UE. The accuracy of CSI affects the overall performance of data transmission, such as spectral efficiency. In order to obtain CSI between a base station and a UE, a training method based on reference signals has been used. In such a scenario, the UE transmits pilot (i.e., reference) symbols known by both the transmitter and the receiver, and the receiver estimates the CSI based on the pilot symbols. Although this training method results in reliable and high-precision channel estimation, the associated pilot overhead leads to a decrease in overall spectral efficiency.

[0004] To reduce pilot overhead and improve spectrum efficiency, many methods have been proposed, such as the superimposed pilot method, which simultaneously transmits pilot and data by simply adding a pilot signal to the data signal and transmitting the combination within the same time and frequency resource block. However, this superimposed pilot method is limited in terms of channel estimation accuracy.

[0005] New Radio (NR) uses CP-OFDM (Cyclic Prefix Orthogonal Frequency Division Multiplexing) in both the downlink (DL) (i.e., from the network node, gNB, or base station to the user equipment, or UE) and uplink (UL) (i.e., from the UE to the gNB). Discrete Fourier Transform (DFT)-spread OFDM is also supported in the uplink. In the time domain, the NR downlink and uplink are organized into equal-sized subframes of 1 ms each. The subframes are further divided into multiple slots of equal duration. The slot length depends on the subcarrier spacing. For a subcarrier spacing of Δf = 15 kHz, there is only one slot per subframe, and each slot consists of 14 OFDM symbols. Data scheduling in NR is typically based on slots. Figure 1 An example of an NR time domain structure with 15kHz subcarrier spacing is shown in Figure 1, which has a 14-symbol time slot, where the first two symbols contain the Physical Downlink Control Channel (PDCCH) and the remaining symbols contain the Physical Shared Data Channel, either PDSCH (Physical Downlink Shared Channel) or PUSCH (Physical Uplink Shared Channel).

[0006] Different subcarrier spacing values ​​are supported in NR. The supported subcarrier spacing values ​​(also called different parameter sets) are given by Δf = (15 × 2 μ )kHz, where μ = {0, 1, 2, 3, 4}. Δf = 15kHz is the basic subcarrier spacing. The time slot duration under different subcarrier spacing is given by given.

[0007] In the frequency domain, the system bandwidth is divided into resource blocks (RBs), each of which corresponds to 12 consecutive subcarriers. RBs are numbered starting with 0 from one end of the system bandwidth. Figure 2 An example of an NR physical time-frequency resource grid is shown in FIG, where only one resource block (RB) within a 14-symbol slot is shown. One OFDM subcarrier during one OFDM symbol interval forms one resource element (RE).

[0008] In NR Rel-15, the PDCCH can be used to dynamically schedule uplink data transmission. The UE first decodes the uplink grant in the PDCCH and then transmits data on the PUSCH based on the decoded control information in the uplink grant, such as the modulation order, coding rate, uplink resource allocation, etc.

[0009] The demodulation reference signal (DM-RS) for PUSCH consists of an UL reference signal consisting of a pseudo-random QPSK sequence for CP-OFDM or a low peak-to-average power ratio (PAPR) sequence for DFT-S-OFDM. The DM-RS is used for PUSCH demodulation, enabling the receiver (i.e., gNB) to handle time-varying and frequency-selective channels. The DM-RS is limited to the scheduled PUSCH bandwidth and duration.

[0010] The mapping of DM-RS to REs is configurable in both the frequency and time domains. In the frequency domain, there are two mapping types: Type 1 (comb-based) or Type 2 (non-comb-based). In the time domain, DM-RS can be single-symbol or dual-symbol, where the latter means that the DM-RS is mapped in pairs of two adjacent symbols. In addition, the UE can be configured with one, two, three, or four single-symbol DM-RSs and one or two dual-symbol DM-RSs. In low Doppler scenarios, one DM-RS symbol may be sufficient, while in high Doppler scenarios, additional DM-RS symbols may be required.

[0011] The frequency domain starting position of DM-RS is the same as the frequency domain starting position of PUSCH. The time domain starting position of DM-RS depends on the PUSCH mapping type:

[0012] For PUSCH mapping type A (slot-based scheduling), the first DM-RS symbol is in the third or fourth symbol of the slot (i.e., symbol 2 or 3), as configured by the higher-layer parameter DM-RS-TypeA-Position in the Master Information Block (MIB) broadcast by the gNB.

[0013] For PUSCH mapping type B (non-slot-based scheduling), the first DM-RS symbol of a slot is the same as the first PUSCH symbol of the slot.

[0014] The DM-RS for PUSCH is configured in the Radio Resource Control (RRC) through the DM-RS-UplinkConfig information element (IE) for PUSCH scheduled via Downlink Control Information (DCI) format 0_1 ​​or DCI format 0_2. According to 3GPP TS 38.331 version 16.1.0, the DM-RS for PUSCH is configured in RRC.

[0015] DM-RS for PUSCH can be configured for the following aspects:

[0016] DM-RS frequency domain mapping type (Type 1 or Type 2), configured by the RRC parameter DM-RS-Type. Type 1 is a comb based on 2 code division multiplexing (CDM) groups, while Type 2 is not a comb based on 3 CDM groups. For DFT-S-OFDM, only Type 1 is supported. Figure 3 The symbol positions of DM-RS symbols for two DM-RS types 1 and 2 in a resource block are shown. Specifically, Figure 3 (a) shows the DM-RS symbol position of a DM-RS type 1 single symbol; Figure 3 (b) shows the DM-RS symbol position of DM-RS type 1 double symbol; Figure 3 (c) shows the DM-RS symbol position of a DM-RS type 2 single symbol; and Figure 3 (d) shows the DM-RS symbol positions for DM-RS type 2 double symbols. Figure 3 In (a)-(d), the shaded resource element indicates the DM-RS symbol transmitted in that resource element. Note that each CDM group has multiple DM-RS ports, separated by frequency domain (and time domain, for dual-symbol DM-RS) orthogonal cover codes (OCC):

[0017] o For single-symbol DM-RS, there are 4 and 6 orthogonal DM-RS ports for type 1 and type 2, respectively (2 DM-RS ports per CDM group, separated by a frequency-domain orthogonal cover code FD-OCC of length 2).

[0018] For dual-symbol DM-RS, there are 8 and 12 orthogonal DM-RS ports for type 1 and type 2, respectively (4 DM-RS ports per CDM group, separated using a frequency-domain orthogonal cover code (FD-OCC) of length 2 in combination with a time-domain orthogonal cover code (TD-OCC) of length 2).

[0019] Any additional DM-RS symbols (0, 1, 2, or 3 for single-symbol DM-RS, and 0 or 1 for dual-symbol DM-RS) are configured by the RRC parameter DM-RS-AdditionalPosition. The position of the additional DM-RS depends on the PUSCH mapping type and PUSCH duration according to a predefined table. Note that it is not possible to configure TD-OCC on additional (i.e., non-contiguous) DM-RS. Figure 4 An example of the symbol position of DM-RS symbols of DM-RS type 1 with additional DM-RS symbols in a resource block is shown. Specifically, Figure 4 (a) shows the DM-RS symbol positions for DM-RS type 1 (single symbol) with two additional DM-RS symbols, and Figure 4 (b) shows the DM-RS symbol positions of DM-RS type 1 (double symbol) with one additional DM-RS symbol.

[0020] • The associated Phase Tracking Reference Signal (PT-RS), if any, may be configured by the RRC parameter phaseTrackingRS.

[0021] • The maximum number of adjacent DM-RS symbols (1 or 2) can be configured by the RRC parameter maxLength.

[0022] If transform precoding is disabled (i.e., if the waveform is CP-OFDM), the DM-RS for PUSCH can be additionally and optionally configured for scrambling IDs 0 and 1, which are configured by the RRC parameters scramblingID0 and scramblingID1, respectively, which are used to generate pseudo-random DM-RS sequences.

[0023] DM-RS ports are mapped to resource elements within a CDM group. DM-RS ports belonging to the same CDM group are separated by an FD-OCC of length 2 (and a TD-OCC of length 2 for dual-symbol DM-RS). In NR Rel-16, DM-RS sequences are mapped to the following subcarriers (for DFT-S-OFDM, only DM-RS type 1 is supported):

[0024]

[0025] Here, k is the subcarrier index (which starts / ends at the first / last subcarrier within the scheduled PUSCH bandwidth), n∈{0,1,2,...}, k′∈{0,1} and Δ is an offset that depends on the CDM group.

[0026] In Tables 1 and 2, we show the port-specific parameters for DM-RS Type 1 and Type 2. Here, w f (k′) (where k′∈{0,1}) is FD-OCC, and w t (l') (where l' = 0 for single-symbol DM-RS and l' ∈ {0, 1} for dual-symbol DM-RS) is the TD-OCC. Note that DM-RS ports in different CDM groups are separated by different offsets, and DM-RS ports within the same CDM group are separated by coding.

[0027] Table 1: Parameters for PUSCH DM-RS configuration type 1 (copied from Table 6.4.1.1.3-1 of 3GPP TS 38.211). Here, Refers to the DM-RS port.

[0028]

[0029] Table 2: Parameters for PUSCH DM-RS configuration type 2 (copied from Table 6.4.1.1.3-2 of 3GPP TS 38.211). Here, Refers to the DM-RS port.

[0030]

[0031] From the transmitter's perspective, the number of DM-RS ports used for PUSCH transmission corresponds to the transmission rank, i.e., one DM-RS port per transmission layer. The DM-RS port mapping is signaled from the gNB to the UE via DCI. Tables 3 and 4 below show this indication for DCI 0_1, CP-OFDM, single-symbol DM-RS type 1, and for transmission ranks 1 and 2, respectively. Similar tables can be found in 3GPP TS 38.212 Version 16.10.0 for ranks 3 and 4, dual-symbol DM-RS, and DM-RS type 2. Subcarriers associated with the CDM group that are not used for DM-RS can be used for PUSCH. After layer mapping, the DM-RS and associated PUSCH are mapped to the physical antennas using precoding.

[0032] Table 3: Antenna ports for single-symbol DM-RS type 1, transform precoding disabled, rank 1 transmission (copied from Table 7.3.1.1.2-8 of 3GPP 38.212 Version 16.10.0).

[0033]

[0034] Table 4: Antenna ports for single-symbol DM-RS type 1, transform precoding disabled, rank 2 transmission (copied from Table 7.3.1.1.2-9 of 3GPP 38.212 Version 16.10.0).

[0035]

[0036] The training methods mentioned above are already used in typical wireless communication standards. For high-mobility scenarios, spectral efficiency inevitably deteriorates due to the fact that more reference symbols are required to accurately track and estimate the changing channel, which increases communication overhead. This necessitates finding methods to eliminate or reduce the overhead caused by the use of reference symbols to achieve higher spectral efficiency for 5G-advanced and beyond.

[0037] One approach to addressing pilot overhead is to use differential space-time coding (DSTC). This eliminates the need for periodic pilot symbols and supports scenarios where CSI fluctuates rapidly over time. By encoding information into the signal differences between time slots, it enables non-coherent detection. However, due to the nature of differential coding, one must tolerate a maximum 3dB loss in signal-to-noise ratio (SNR) and low spectral efficiency.

[0038] Semi-blind methods have been proposed to reduce pilot overhead. These methods first roughly estimate CSI using a short reference signal sequence and aim to improve it by utilizing data and performing joint channel and data detection. While this approach improves spectral efficiency compared to its coherent counterpart, transmitting reference signals still limits the improvement.

[0039] Another approach estimates CSI by using the second-order statistics of the received signal and algebraic properties of the symbols. The main problem with this approach is the difficulty in determining the phase of the channel response in the complex domain, resulting in poor channel estimation performance. To address this issue, pilot elements are transmitted or asymmetric constellations are used. This uses orthogonal space-time block coding (OSTBC) symbols and estimates CSI based on the covariance matrix of the received signal. This requires a long coherence time to obtain CSI, resulting in significant latency.

[0040] Finally, some methods superimpose pilot symbols onto data symbols in the complex domain. This enables simultaneous estimation of the channel and data at the receiver. In massive MIMO scenarios, superimposed pilots can effectively mitigate pilot contamination in both uplink and downlink. However, this approach reduces spectral efficiency as the transmit power allocated to data symbols decreases.

[0041] In general, the above methods are shown to be limited in terms of channel estimation performance or spectrum efficiency [1], while being incompatible with the 3GPP standard signaling structure. Summary of the Invention

[0042] Examples of the present disclosure may have certain advantages. For example, embodiments of the present disclosure may improve channel estimation performance while ensuring that symbol error rate (SER) performance is not affected or not significantly affected.

[0043] One aspect of the present disclosure provides a method for transmitting data to a network node. The method includes selecting one of a plurality of reference signal symbol sequences based on the data to be transmitted to the network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized. The method also includes transmitting the selected reference signal symbol sequence to the network node.

[0044] Another aspect of the present disclosure provides a method for receiving data from a network node. The method includes receiving a reference signal symbol sequence from a plurality of reference signal symbol sequences from the network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized. The method also includes determining data to be transmitted by the network node based on the reference signal symbol sequence.

[0045] Another aspect of the present disclosure provides a method for determining multiple reference signal symbol sequences. The method includes selecting multiple reference signal symbol sequences, wherein a first reference signal symbol sequence corresponds to a constellation point on a Grassmann manifold. The method also includes selecting phases for at least a subset of the reference signal symbol sequences to increase a sum of inner products of pairs of reference signal symbol sequences in at least the subset of the reference signal symbol sequences.

[0046] An additional aspect of the present disclosure provides an apparatus for transmitting data to a network node. The apparatus includes a processor and a memory. The memory contains instructions executable by the processor, causing the apparatus to: select one of a plurality of reference signal symbol sequences based on the data to be transmitted to the network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; and transmit the selected reference signal symbol sequence to the network node.

[0047] Another aspect of the present disclosure provides an apparatus for receiving data from a network node. The apparatus includes a processor and a memory. The memory contains instructions executable by the processor, causing the apparatus to: receive a reference signal symbol sequence from a plurality of reference signal symbol sequences from the network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; and determine data to be transmitted by the network node based on the reference signal symbol sequence.

[0048] Another aspect of the present disclosure provides an apparatus for determining a plurality of reference signal symbol sequences. The apparatus includes a processor and a memory. The memory contains instructions executable by the processor, causing the apparatus to: select a plurality of reference signal symbol sequences, wherein a first reference signal symbol sequence corresponds to a constellation point on a Grassmann manifold; and select phases for at least a subset of the reference signal symbol sequences to increase a sum of inner products of pairs of reference signal symbol sequences in at least the subset of the reference signal symbol sequences.

[0049] Yet another aspect of the present disclosure provides an apparatus for transmitting data to a network node. The apparatus is configured to: select one of a plurality of reference signal symbol sequences based on the data to be transmitted to the network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; and transmit the selected reference signal symbol sequence to the network node.

[0050] Another aspect of the present disclosure provides an apparatus for receiving data from a network node. The apparatus is configured to: receive a reference signal symbol sequence from a plurality of reference signal symbol sequences, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; and determine data transmitted by the network node based on the reference signal symbol sequence.

[0051] Additional aspects of the present disclosure provide an apparatus for determining a plurality of reference signal symbol sequences. The apparatus is configured to: select a plurality of reference signal symbol sequences, wherein a first reference signal symbol sequence corresponds to a constellation point on a Grassmann manifold; and select phases for at least a subset of the reference signal symbol sequences to increase a sum of inner products of pairs of reference signal symbol sequences in at least the subset of the reference signal symbol sequences. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] For a better understanding of examples of the present disclosure, and to more clearly show how the same may be implemented, reference will now be made, by way of example only, to the following drawings, in which:

[0053] Figure 1 An example of an NR time domain structure with 15kHz subcarrier spacing is shown;

[0054] Figure 2 An example of an NR physical time-frequency resource grid is shown;

[0055] Figure 3 The symbol positions of DM-RS symbols for DM-RS types 1 and 2 in a resource block are shown;

[0056] Figure 4 An example of symbol positions of DM-RS symbols in a resource block for DM-RS type 1 with additional DM-RS symbols is shown;

[0057] Figure 5 is a flow chart of an example of a method of transmitting data to a network node;

[0058] Figure 6 is a flow chart of an example of a method of receiving data from a network node;

[0059] Figure 7 Examples of single-symbol and dual-symbol Type 1 Grassman DM-RS are shown;

[0060] Figure 8 An example of repetition of a Grassmann-based DM-RS sequence in the frequency domain is shown;

[0061] Figure 9 An example of a Grassmann-based DM-RS sequence is shown, which is divided into groups for DM-RS ports while utilizing consecutive OFDM symbols;

[0062] Figure 10 An example of the use of both a conventional DM-RS and a DM-RS according to the present disclosure is shown;

[0063] Figure 11 shows examples of the normalized mean square error (NMSE) performance of different Grassmann constellations when used for data transmission;

[0064] Figure 12 shows examples of symbol error rate (SER) performance when different Grassmann constellations are used for data transmission;

[0065] Figure 13 is a flow chart of an example of a method of determining a plurality of reference signal symbol sequences;

[0066] Figure 14 Scatter plot showing examples of inner products of different Grassmann codeword pairs for the case of non-phase aligned Grassmann constellations;

[0067] Figure 15 Scatter plot showing examples of inner products of different Grassmann codeword pairs in the case of phase-aligned ManOpt Grassmann constellations;

[0068] Figure 16 Another example of the normalized mean square error (NMSE) performance of different Grassmann constellations for data transmission is shown;

[0069] Figure 17 Another example of the symbol error rate (SER) performance of different Grassmann constellations for data transmission is shown;

[0070] Figure 18 is a schematic diagram of an example of an apparatus 1800 for transmitting data to a network node;

[0071] Figure 19 is a schematic diagram of an example of an apparatus 1900 for receiving data from a network node; and

[0072] Figure 20 is a diagram illustrating an example of an apparatus 2000 for determining a plurality of reference signal symbol sequences. DETAILED DESCRIPTION

[0073] For the purpose of explanation and not limitation, specific details, such as specific embodiments or examples, are described below. Those skilled in the art will appreciate that, in addition to these specific details, other examples may also be used. In some instances, detailed descriptions of well-known methods, nodes, interfaces, circuits, and devices are omitted to avoid obscuring the description with unnecessary details. Those skilled in the art will appreciate that hardware circuits (e.g., analog and / or discrete logic gates, application-specific integrated circuits (ASICs), programmable logic arrays (PLAs), etc., interconnected to perform dedicated functions) and / or software programs and data may be used in conjunction with one or more digital microprocessors or general-purpose computers to implement the described functions in one or more nodes. Nodes communicating using an air interface also have suitable radio communication circuits. In addition, where appropriate, the technology may additionally be considered to be fully embodied in any form of computer-readable memory, such as solid-state memory, magnetic disks, or optical disks, containing an appropriate set of computer instructions that will cause a processor to execute the technology described herein.

[0074] Hardware implementations may include or comprise, but are not limited to, digital signal processor (DSP) hardware, a reduced instruction set processor, hardware (e.g., digital or analog) circuitry, including but not limited to application specific integrated circuit(s) (ASICs) and / or field programmable gate array(s) (FPGA(s)), and, where appropriate, state machines capable of performing such functionality.

[0075] As indicated above, example embodiments of the present disclosure may enable improvements in spectral efficiency by replacing reference signals (e.g., DM-RS in NR) with codewords (such as, for example, codewords from a Grassmann manifold), where each codeword may convey a data bit. Example embodiments may also reduce the impact of overhead from reference signals such as DM-RS. This may be particularly beneficial in networks such as, for example, 5G and 6G networks, which may have very small amounts of data to transmit and, therefore, the overhead caused by reference signal symbols may be significant. It is assumed that in the future, networks may need to be adapted to transmit smaller chunks of data, such as, in some examples, a data chunk that may be carried by only one symbol of a resource block (RB). Therefore, reducing the impact of reference signals is particularly useful, such as in the example methods of the present disclosure, which may utilize reference signal symbols to transmit data.

[0076] Figure 5 5 is a flow chart of an example of a method 500 for transmitting data to a network node. In some examples, the network node is a radio access network (RAN) node, such as a base station, gNodeB, eNodeB, etc. In such examples, the method 500 may be performed by a user equipment (UE). Alternatively, in some examples, the network node is a UE, and the method 500 may be performed by a RAN node, such as a base station, gNodeB, eNodeB, etc.

[0077] The method 500 includes, in step 502, selecting one of a plurality of reference signal symbol sequences based on data to be transmitted to a network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized. Step 504 of the method includes transmitting the selected reference signal symbol sequence to the network node. In some examples, the transmitted selected reference signal symbol sequence can be a pilot signal or a demodulation reference signal (DM-RS), or another reference signal.

[0078] In some examples, each reference signal symbol sequence is associated with a different value of data. Thus, for example, transmission of a selected symbol sequence of reference signal symbols conveys data via the selected particular sequence. In a specific example, there are n reference signal symbols in the sequence, and the number of reference signal symbol sequences from which the transmitted reference signal symbols are selected is 2. B , where B is the number of bits encoded in the reference signal symbol sequence. In some examples, selecting one of the multiple reference signal symbol sequences in step 502 may include selecting from 2 B reference signal symbol sequences and / or 2 B Reference signal symbol sequences or constellation points are selected from constellation points B, where B is the number of data bits encoded by each reference signal symbol sequence or constellation point.

[0079] In some examples, the Grassmann manifold can be at least a 2n-dimensional manifold, where n is the number of reference signal symbols. Thus, for example, each reference signal symbol transmitted in step 504 can convey a two-dimensional constellation point on the Grassmann manifold.

[0080] In some examples, the reference signal symbol sequence can be repeated, such as, for example, in the same resource block, time slot, mini-time slot, subframe, and / or frame. Method 500 can therefore include transmitting the selected reference signal symbol sequence in a plurality of first resource elements and repeating the reference signal symbols in a plurality of second resource elements. The first plurality of resource elements are within a first frequency range, and the second plurality of resource elements can be, for example, within a second frequency range that does not overlap with the first frequency range. The first and second plurality of resource elements can overlap, partially overlap, or not overlap in time. The first resource element and the second resource element can be, for example, within a resource block, time slot, mini-time slot, subframe, and / or frame.

[0081] In some examples, the selected reference signal symbol sequence may correspond to the first antenna port. In such examples, method 500 may include, for each of one or more additional antenna ports, transmitting an additional reference signal symbol sequence to the network node (e.g., in the same resource block, slot, mini-slot, subframe, and / or frame as the plurality of reference signal symbols selected in step 502). Method 500 may also include, for each of the one or more additional antenna ports, selecting an additional reference signal symbol sequence based on corresponding additional data to be transmitted to the network node. This may be selected in a manner similar to the reference signal symbol sequence selected in step 502 described above, e.g., from a plurality of symbol sequences corresponding to constellation points on a Grassmann manifold. Alternatively, for example, the additional reference symbols may include conventional reference signal symbols.

[0082] In some examples, method 500 may further include transmitting additional reference signal symbols to the network node, where the additional reference signal symbols correspond to legacy reference signals (e.g., in the same resource block, slot, mini-slot, subframe, and / or frame as the plurality of reference signal symbols selected in step 502). Thus, for example, the resource block, slot, mini-slot, subframe, and / or frame may include both legacy reference signal symbols and reference signal symbols conveying data, as selected in step 502 of method 500.

[0083] Figure 6 6 is a flow chart of an example of a method 600 for receiving data from a network node. In some examples, the network node is a radio access network (RAN) node, such as a base station, gNodeB, eNodeB, etc. In such examples, the method 600 may be performed by a user equipment (UE). Alternatively, in some examples, the network node is a UE, and the method 600 may be performed by a RAN node, such as a base station, gNodeB, eNodeB, etc. In some examples, the network node from which the data is received performs the above-mentioned method 600.

[0084] Method 600 includes, at step 602, receiving a reference signal symbol sequence from a network node from a plurality of reference signal symbol sequences, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized. Step 604 of method 600 includes determining data transmitted by the network node based on the reference signal symbol sequences. For example, each reference signal symbol sequence may be associated with a different value of the data.

[0085] In some examples, there may be at least 2 B different reference signal symbol sequences and / or at least 2 B constellation points, where B is the number of data bits encoded by each reference signal symbol sequence. In some examples, determining the data to be transmitted by the network node in step 604 may include determining that the plurality of reference signal symbols comprise one of the constellation points, where each constellation point represents a different reference signal symbol sequence and / or a different value of the data. Additionally or alternatively, in some examples, the Grassmann manifold is at least a 2n-dimensional manifold, where n is the number of reference signal symbols in each reference signal symbol sequence.

[0086] In some examples, determining the data transmitted by the network node includes determining that the received reference signal symbol sequence corresponds to one of a plurality of codewords in a codebook. Thus, for example, the data can be determined by matching the received reference signal symbol sequence with one of the codewords, and the transmitted data corresponds to the value of the data associated with the matched codeword.

[0087] In some examples, reference signal symbols may repeat. Method 600 may therefore include receiving reference signal symbols in a first plurality of resource elements and receiving repetitions of the reference signal symbols in a second plurality of resource elements. The first plurality of resource elements may be within a first frequency range, and the second plurality of resource elements may be, for example, within a second frequency range that does not overlap with the first frequency range. The first and second plurality of resource elements may overlap, partially overlap, or not overlap in time. The first resource elements and the second resource elements may be, for example, within a resource block, a time slot, a mini-time slot, a subframe, and / or a frame.

[0088] In some examples, the plurality of reference signal symbols corresponds to the first antenna port. In such examples, method 600 may include, for each of the one or more additional antenna ports, receiving a corresponding additional reference signal symbol sequence from the network node (e.g., in the same resource block, slot, mini-slot, subframe, and / or frame as the plurality of reference signal symbols selected in step 502). Method 600 may also include, for each of the one or more additional antenna ports, determining corresponding additional data transmitted by the network node based on the additional reference signal symbol sequence. This may be determined in a manner similar to step 604 of method 600 described above, e.g., from a plurality of symbol sequences, from a plurality of constellation points, or from a plurality of constellation points on a Grassmann manifold. Alternatively, the additional reference symbols may include, for example, conventional reference signal symbols.

[0089] In some examples, method 600 may further include receiving additional reference signal symbols from the network node, where the additional reference signal symbols correspond to legacy reference signals (e.g., in the same resource block, slot, mini-slot, subframe, and / or frame as the plurality of reference signal symbols selected in step 502). Thus, for example, the resource block, slot, mini-slot, subframe, and / or frame may include both legacy reference signal symbols that do not convey data and the reference signal symbols determined in step 604 of method 600 that convey data.

[0090] As indicated above, in examples of the present disclosure, a Grassmann constellation can be used to select symbols for DM-RSs that carry data, e.g., instead of conventional DM-RSs. The Grassmann manifold can be used to construct DM-RS symbols that can carry data compared to conventional DM-RS symbols. In some examples, the Grassmann-based DM-RS can be configured in a user equipment by a network node (e.g., a base station, eNodeB, gNodeB) via radio resource control (RRC) signaling.

[0091] A specific example based on the use of Grassmann manifolds is now described, although the concepts described may also be applied to other examples using other Grassmann-based constellations and / or symbol sequences.

[0092] Some non-coherent transmission methods based on Grassmann have been reported, among which several multi-dimensional Grassmann constellations have been proposed. Despite such Grassmann constellation designs, there is no prior art proposal to use the Grassmann constellation to replace the reference signal in the 5G NR configuration.

[0093] Transmission based on Grassmann manifolds

[0094] Consider a UE with M antennas transmitting to a gNB with N antennas. The received signals are concatenated over time length T, where T > M. The received signal model can be given by:

[0095] Y=XH+V, (1)

[0096] in is the received signal matrix, is the transmitted matrix constructed from the T-dimensional Grassmann manifold [1], is the effective channel matrix consisting of the precoding matrix, receiver filter, and fading channel matrix, and is the noise matrix. Next, possible methods for estimating the transmitted matrix X and the channel matrix H are described.

[0097] Estimate of the transmitted matrix X

[0098] To estimate the channel matrix, we first estimate the transmitted matrix X, where X is one of the discrete points represented by the predefined MT-dimensional Grassmann manifold. Although any reasonable detection method can be considered to detect the transmitted matrix X, the generalized likelihood ratio test (GLRT) is proposed here to solve the following maximization problem:

[0099]

[0100] in is an estimate of the transmitted matrix X, and is a set of discrete points in the MT-dimensional space defined by a predetermined Grassmann manifold. Due to the discreteness of , digital data symbols can be encoded at each discrete point in the MT-dimensional space. The difference from digital modulation is that, unlike the complex space of digital modulation schemes such as QAM or PSK (i.e., )compared to, The discrete points are defined in multidimensional space.

[0101] The estimated matrix H is transmitted

[0102] Given an estimate The channel matrix H can also be estimated by any channel estimation method that assumes knowledge of the matrix X. For example, in the case of a zero-forcing method, the estimate of H is given by:

[0103]

[0104] Alternatively, assuming that the covariance matrix Cov(V) of the receiver noise is available, the estimate H of the minimum mean square error (MMSE) estimator is given by:

[0105]

[0106] In a similar embodiment, joint detection of the matrix H and the matrix X may be considered.

[0107] In some examples, a method is provided for applying a Grassmann manifold-based DM-RS to demodulation of transmitted symbols in an NR system. Although in the following examples, the method is described for uplink NR transmission from a user equipment (UE) to a gNodeB (gNB), the method (and other methods of the present disclosure) can be applied to any general wireless communication system, including uplink, downlink, direct link, peer-to-peer, and other, as well as wireless communication systems between any two network nodes. Furthermore, in this example, PUSCH data symbols are transmitted using DM-RS, although in other examples, any reference signal or other signal can be used to transmit any data.

[0108] Unlike conventional DM-RS, data such as PUSCH data symbols in the examples of this disclosure are superimposed on the Grassmann-based DM-RS, resulting in higher spectral efficiency. Therefore, consider a user equipment (UE) with υ DM-RS antenna ports serving a gNB. Considering that the DM-RS sequences for the ports are distributed over N s The received signal of the DM-RS port transmitted on the same OFDM symbol but different subcarriers (given by Given), it can be given by the following formula:

[0109] Y u =X u H u +V u , (5)

[0110] in is the received signal matrix, is a block diagonal matrix such that in is N transmitted via the i-th DM-RS port s dimensional Grassmann manifold[1], is the effective channel matrix containing the precoding matrix, receiver filter, and propagation channel matrix, and is the noise matrix. At the gNB, the transmitted matrix and the channel matrix can be estimated in a similar way to that described above. Note that although a Grassmann manifold is used in this example to describe joint pilot and data transmission, the general principle applies to any multidimensional constellation on which data symbols (PUSCH / PDSCH) can be carried.

[0111] In the example, with length N s The Grassmann sequence of each port of can be mapped to resource elements (REs) in a manner similar to the conventional type 1 DM-RS mapping described above, giving two DM-RS ports. Furthermore, in the time domain, the DM-RS can be as follows Figure 3 (a)-(d) as shown in single or double symbols. Figure 7 As shown in Two and four Grassmann-based DM-RS ports may have one and two time-domain DM-RS symbols, respectively. Figure 7 (a) shows an example of a single symbol Type 1 Grassman DM-RS, and Figure 7 (b) shows an example of a dual-symbol Type 1 Glassman DM-RS. In a related example, the Glassman-based DM-RS can be used for conventional DM-RS. Figure 3 (c) and (d) show that the type 2 pattern is mapped to REs. Note that the Grassmann-based DM-RS can be configured with arrangements other than types 1 and 2 because they can carry PUSCH thereon.

[0112] Although in the above examples, the DM-RS port for each frequency and time resource (i.e., the same subcarrier and time resource (e.g., (one or more) the same resource elements)) is limited to one, in some examples, code division multiplexing (CDM) using orthogonal cover codes (OCC) can be mapped onto the Glassman-based DM-RS to transmit more than one DM-RS port using the same frequency and time resources in some examples. In another example, where the DM-RS is a dual symbol such as type 2 mentioned above, one OFDM symbol in the dual symbol can be a traditional DM-RS, and the other OFDM symbol can be a DM-RS carrying data according to the present disclosure, such as, for example, a Glassman-based DM-RS.

[0113] In some examples of the present disclosure, the accuracy of the channel estimation depends on the frequency selectivity of the channel. For frequency-flat channels, the channels across the allocated bandwidth are equivalent, giving accurate channel estimates. However, as the frequency selectivity increases, the accuracy of the channel estimation may decrease in some examples of Grassmann-based DM-RS. In addition, the decoding complexity may increase with the length N of the Grassmann-based DM-RS sequence. s Therefore, in some examples, N s Can be divided into smaller equal length Make Therefore, the shorter based The Grassmann DM-RS sequence is repeated 1 times to cover N s subcarriers, as proposed above with reference to method 500 or 600. This may, for example, allow estimation over a smaller bandwidth with lower frequency selectivity, while having lower complexity for each smaller sequence. As an example, in Figure 8 The above embodiment is shown in FIG, which shows an example of repetition of a DM-RS sequence based on Grassmann in the frequency domain. Specifically, Figure 8 (a) shows an example of a Grassmann-based DM-RS sequence divided into groups for DM-RS ports, where each group occupies a type 1 arrangement. subcarriers, and Figure 8 (b) shows a type 2 arrangement subcarriers.

[0114] In a related example, if a more accurate channel estimate is required, then The Grassmann-based DM-RS sequence is transmitted on two or more consecutive OFDM symbols, resulting in Modifications and:

[0115]

[0116] where T is the number of consecutive OFDM symbols, and is N transmitted through the i-th DM-RS port at the t-th OFDM symbol s dimensional Grassmann manifold [1]. This can allow more accurate channel estimation for high-frequency selective channels by exploiting the time domain. Figure 9 An example of this is shown in , where the Grassmann-based DM-RS sequences are divided into groups for DM-RS ports while utilizing T = 2 consecutive OFDM symbols.

[0117] Specifically, Figure 9 (a) shows an example of a single symbol Type 1 Grassman DM-RS, and Figure 9(b) shows an example of a single symbol type 2 Glassman DM-RS. This example involves a front-loaded PUSCH with a duration of 14 symbols (i.e., PUSCH mapping type A). The Glassman-based DM-RS sequence is divided into groups for DM-RS ports, where each group occupies a type 1 and type 2 arrangement, respectively. subcarriers and These figures show two such groups for resource blocks, ie i=1,2.

[0118] The frequency domain and time domain starting positions of the DM-RS according to the present disclosure (such as, for example, a Glassman-based DM-RS or any other example of a data-carrying DM-RS) can follow a configuration similar to that of the conventional DM-RS described above. In low Doppler scenarios, similar to conventional DM-RS, one Glassman-based DM-RS symbol may be sufficient, while in high Doppler scenarios, additional Glassman-based DM-RS symbols may be useful or required in some examples.

[0119] Although in some examples, traditional DM-RS can have the advantages of higher channel estimation accuracy and low decoding complexity, the DM-RS according to the present disclosure (e.g., Glassman-based DM-RS) can impart additional spectral efficiency by superimposing PUSCH on the Glassman-based DM-RS sequence. Therefore, in some examples, both traditional DM-RS and DM-RS according to the present disclosure can be used (e.g., in resource blocks, time slots, mini-time slots, subframes and / or frames) to achieve the advantages of both traditional DM-RS and DM-RS according to the present disclosure. For example, in a high Doppler scenario, the first DM-RS symbol in a resource block can be a traditional DM-RS, and subsequent DM-RS can be a DM-RS according to the present disclosure, such as, for example, a Glassman-based DM-RS. In Figure 10 An example is shown in . Specifically, for a single symbol DM-RS, Figure 10 (a) shows an example of configuring one additional DM-RS position for Type 1, and Figure 10 (b) shows an example of configuring one additional DM-RS position for type 2. This example involves a preamble PUSCH with a duration of 14 symbols (i.e., PUSCH mapping type A). The first DM-RS symbol uses a legacy sequence, while the two additional DM-RS symbols in the slot use a Grassman-based DM-RS.

[0120] In some examples, the use of one or both of the legacy DM-RS and / or the DM-RS according to the present disclosure may be signaled to a network node (such as a UE) by another network node (such as a gNB). This may be accomplished, for example, through higher-layer RRC signaling by including additional information elements in the DM-RS-config parameter structure (discussed in Section 2.1.2.1). Examples of additional parameters may include one or more of the following:

[0121] 'DM-RS-Sequence' may signal the use of legacy DM-RS, DM-RS according to the present disclosure, or both,

[0122] ● 'DM-RS-AdditionalSequence' signals a bit sequence equal to the number of DM-RS symbols in a slot to indicate the use of legacy DMRS or DM-RS according to the present disclosure in each DM-RS symbol position, where the positions of legacy DM-RS and / or DM-RS according to the present disclosure may be signaled by the gNB over the RRC connection using the DM-RS-AdditionalPosition information element in the DM-RS-config parameter structure.

[0123] In a related example, where a phase tracking reference signal (PT-RS) is configured in a time slot, the PT-RS may be signaled to occupy subcarriers and OFDM symbols such that they do not overlap with DM-RS (e.g., a DM-RS according to the present disclosure, such as a Glassman-based DM-RS), if used in the time slot. Alternatively, the DM-RS may be configured to not overlap with the PT-RS REs.

[0124] As disclosed herein, the challenge of constructing a Grassmann constellation for an example of Grassmann-based reference signal and data transmission is the tradeoff between the estimation performance of the reference signal X and the channel H. More specifically, for example, in Figure 11 and Figure 12 The normalized mean square error (NMSE) and symbol error rate (SER) performance of different Grassmann constellations for data transmission are shown in Figure 2, where the NMSE and SER performance are shown relative to the signal-to-noise ratio (SNR). The constellations for which performance is shown are Exponential Mapping [1], Cube-Split [2], and ManOpt, while the NMSE performance of the Zadoff-Chu sequence (ZCS) is included as a baseline. Figure 11Note that ZCS is a conventional reference signaling method and may not transmit data, unlike the Grassmann sequences used in this paper; therefore, it can be considered as a channel estimation performance baseline, for example. The ManOpt constellation is a numerically optimized Grassmann constellation for which the performance is demonstrated using the publicly available optimization solver "Pymanopt."

[0125] Compare Figure 11 and Figure 12 From the SER and NMSE performance shown in

[15] , it can be seen that there is a clear trade-off between SER and NMSE. In other words, exponential mapping is the best of the methods shown in terms of channel estimation performance, but the worst in terms of SER performance. Similarly, the Cube-Split and ManOpt methods are shown to perform better than exponential mapping in terms of SER, but at the expense of worse channel estimation performance. In view of the above, the Grassmann constellation method, which addresses this trade-off (i.e., improving channel estimation NMSE performance while maintaining SER performance), is the focus of example embodiments of the present disclosure.

[0126] The disclosed method proposes to improve the Grassmann constellation by optimizing the phase of each codeword of the Grassmann constellation and utilize such a constellation with certain properties in data transmission, such as in the above-mentioned methods 500 and 600. An example of a method for constructing or modifying a Grassmann-based constellation according to an embodiment of the present disclosure is provided below.

[0127] For example, let us define C = {X1,X2,…,X L} is the Grassmann constellation (i.e., codewords X1, X2, ..., X L ), where is the codeword matrix as shown in equation (1), where l∈{1,2,…,L}. In addition, let us define C p ={x 1p ,x 2p ,…,x Lp} is a set of vectors, which includes all X with l∈{1,2,…,L} and p∈{1,2,…,M} l The pth column vector of , and define For C p The associated phase alignment coefficient set, whose elements (i.e., θ lp ) is the variable to be optimized.

[0128] The channel estimation accuracy (i.e., NMSE) can be written as:

[0129]

[0130] where the numerator computes the actual Euclidean distance between the estimated channel matrix and the true channel matrix, while the denominator is used for normalization purposes.

[0131] Assume that the estimate of the reference signal X is as shown above After equilibrium, the nominator can be expressed as:

[0132]

[0133] where V′ is the effective noise matrix after equalization, and we exploit the fact that due to the properties of the Grassmann manifold,

[0134] From the above equation, it is clear that if and only if we minimize (Right now, becomes the identity matrix), NMSE is minimized, which is the estimated However, it is inevitable that the estimated may be different from the transmitted reference signal X (e.g., due to noise). Different from the reference signal X, the coefficient It is not the identity matrix, which causes NMSE degradation.

[0135] However, in this case, the NMSE degradation can be mitigated by optimizing the phases of at least some Grassmann codewords, constellation points, or associated symbol sequences so that Become as close as possible to the identity matrix I M , which is the main idea of ​​the exemplary embodiments of the present disclosure. In other words, in some examples, the phase alignment coefficients can be optimized so that the Grassmann constellation set C p The inner product between one or more pairs of Grassmann codeword / point / symbol sequences in becomes 1 (ie, a diagonal element of the identity matrix) or closer to 1 (eg, maximized).

[0136] Without loss of generality, we assume Where l∈{1,2,…,L}. To this end, in some examples, the phase alignment coefficient E for all p can be optimized p , so that the sum of all possible inner products is maximized, that is:

[0137]

[0138] This can be solved via a sequential quadratic programming solver such as SLSQP, for example. Finally, the optimized phase alignment coefficients can be multiplied by the original set of Grassmann constellations, or the set of points, codewords, or symbol sequences. For example, the phase-aligned Grassmann constellation subset can be given by In some examples, by merging all subsets C' of p p to construct the phase-aligned Grassmann C'.

[0139] In some examples, phase alignment does not change the geometry of the original Grassmann constellation, thus improving NMSE performance compared to the original Grassmann constellation while maintaining the same symbol estimation error. In some examples, the phase-aligned Grassmann constellation can be calculated offline and, for example, signaled between the transmitter and receiver prior to channel and data communication. Alternatively, the optimized phase-aligned Grassmann constellation can be provided in the specification, explicitly agreed upon via bilateral vendor agreement, or otherwise predefined. For example, in 5G / 6G communications for downlink (DL), such a phase-aligned or phase-optimized Grassmann constellation can be part of the 3GPP specification and / or explicitly agreed upon via bilateral vendor agreement, where the phase-aligned Grassmann constellation is calculated by the transmitter or receiver vendor, or jointly by the vendors. The gNB can then signal the use of such a constellation for reference signals (e.g., DMRS) via RRC signaling or downlink control information (DCI).

[0140] Figure 13 is a flow chart of an example of a method 1300 for determining a plurality of reference signal symbol sequences. The method 1300 includes, in step 1302, selecting a plurality of reference signal symbol sequences, wherein a first reference signal symbol sequence corresponds to a constellation point on a Grassmann manifold. Next, step 1304 of the method 1300 includes selecting a phase for at least a subset of the reference signal symbol sequences to increase a sum of inner products of pairs of reference signal symbol sequences in at least the subset of the reference signal symbol sequences. Thus, in some examples, the method 1300 may include a method for modifying the reference signal symbol sequences. The reference signal symbol sequences for which the phases are selected may be used in embodiments of the present disclosure, such as, for example, in the above-described methods 500 and 600. For example, the method 1300 may include transmitting one or more of the reference signal symbol sequences, and / or receiving one or more of the reference signal symbol sequences.

[0141] In some examples, increasing the sum of inner products of sequence pairs in the subset can improve NMSE performance while maintaining or substantially maintaining SER performance. In some examples, method 1300 can include selecting a phase for at least a subset of the reference signal symbol sequences to maximize the sum of inner products of reference signal symbol sequence pairs in at least the subset of the reference signal symbol sequences.

[0142] In some examples, method 1300 may include sending information identifying multiple modified reference signal symbol sequences (or their phases) to a transmitter transmitting one or more of the second reference signal symbol sequences. Additionally or alternatively, in some examples, method 1300 may include sending information identifying multiple modified reference signal symbol sequences (or their phases) to a receiver receiving one or more of the second reference signal symbol sequences. Thus, for example, the transmitter and receiver may learn the reference signal symbol sequences by sharing the sequences or their phases.

[0143] In some examples, each reference signal symbol sequence may be associated with a different value of a data bit. For example, there may be 2 B reference signal symbol sequences and / or 2 B constellation points, where B is the number of data bits encoded by each reference signal symbol sequence. Additionally or alternatively, for example, there may be 2 B constellation points, where B is the number of data bits encoded by each constellation point. In some examples, the Grassmann manifold can be at least a 2n-dimensional manifold, where n is the number of reference signal symbols in each reference signal symbol sequence.

[0144] The reference signal symbol sequence may be, for example, a pilot signal or a demodulation reference signal (DM-RS).

[0145] In some examples, method 1300 may include selecting a phase for at least a subset of the reference signal symbol sequences to maximize a sum of inner products of pairs of reference signal symbol sequences in at least the subset of the reference signal symbol sequences.

[0146] Next, consider the performance of an example embodiment of the present disclosure. However, the presented results can be extended to many different scenarios and parameters, and the disclosed method may not be limited to the cases simulated herein.

[0147] Figure 14 The inner products (i.e., x) of different Grassmann codeword pairs are shown for a non-phase-aligned Grassmann constellation (e.g., a Grassmann constellation obtained by the ManOpt method without any changes). lp and x ip The inner product between , where i≠l) is a scatter plot of examples. Figure 14 As shown in , the inner products are uniformly distributed and most of them are far away from 1, which leads to poor NMSE performance, as explained in equation (6) above and Figure 12 That is, the ManOpt method provides the reference signal symbol sequence with the worst NMSE performance among the examined methods.

[0148] In contrast, Figure 15The inner products of different Grassmann codeword pairs (i.e., x lp and x ip , where i≠l). For example, we can Figure 13 The method 1300 shown in determines the phase or modifies the ManOpt Grassmann constellation (or the associated reference signal symbol sequence), and / or the reference signal sequence may have the properties indicated in methods 500 and 600, i.e., each of the reference signal symbol sequences has a phase such that the sum of the inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized. In particular, in Figure 15 In the example shown in , the sum of the inner products is the maximum value of the entire sequence of symbols. Figure 15 As shown in , the scatter points tend to be as close to 1 as possible, thus, Figure 14 Compared to the example shown in , better NMSE performance can be expected.

[0149] Figure 16 Another example of the normalized mean square error (NMSE) performance with respect to SNR when different Grassmann constellations are used for data transmission is shown. Figure 11 The same method, as well as the ManOpt method for phase adjustment, for example according to Figure 13 Method 1300 is phase-adjusted and / or has the properties indicated in methods 500 and 600. Phase-aligned ManOpt constellations have improved NMSE performance compared to non-phase-aligned ManOpt constellations because phase alignment tends to make all possible inner products of any codeword pair as close to 1 as possible (e.g., maximize the sum of the inner products of all codeword pairs).

[0150] Figure 17 Another example of the symbol error rate (SER) performance of different Grassmann constellations for data transmission is shown. Figure 12 The same method, as well as the ManOpt method for phase adjustment, for example according to Figure 13 The method 1300 is phase-adjusted and / or has the properties indicated in methods 500 and 600. It can be seen that the SER performance of the phase-aligned Manopt constellation / symbol sequence is the same as that of the non-phase-aligned Manopt method.

[0151] Figure 1818 is a schematic diagram of an example of a device 1800 for transmitting data to a network node. Device 1800 includes processing circuitry 1802 (e.g., one or more processors) and memory 1804 in communication with processing circuitry 1802. Memory 1804 contains instructions, such as computer program code 1810, executable by processing circuitry 1802. Device 1800 also includes an interface 1806 in communication with processing circuitry 1802. Although interface 1806, processing circuitry 1802, and memory 1804 are shown as being connected in series, these may alternatively be interconnected in any other manner, such as via a bus.

[0152] In one embodiment, the memory 1804 contains instructions executable by the processing circuit 1802, so that the device 1800 is operable / configured to: select one of a plurality of reference signal symbol sequences based on data to be transmitted to the network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold and each of the reference signal symbol sequences has a phase such that the sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; and transmit the selected reference signal symbol sequence to the network node. In some examples, the device 1800 is operable / configured to perform the above reference Figure 5 Method 500 is described.

[0153] Figure 19 1 is a schematic diagram of an example of a device 1900 for receiving data from a network node. Device 1900 includes processing circuitry 1902 (e.g., one or more processors) and memory 1904 in communication with processing circuitry 1902. Memory 1904 contains instructions, such as computer program code 1910, executable by processing circuitry 1902. Device 1900 also includes an interface 1906 in communication with processing circuitry 1902. Although interface 1906, processing circuitry 1902, and memory 1904 are shown as being connected in series, these may alternatively be interconnected in any other manner, such as via a bus.

[0154] In one embodiment, the memory 1904 contains instructions executable by the processing circuit 1902, so that the device 1900 is operable / configured to: receive a reference signal symbol sequence from a plurality of reference signal symbol sequences from a network node, wherein the reference signal symbol sequence corresponds to a constellation point on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; and determine data transmitted by the network node based on the reference signal symbol sequence. In some examples, the device 1900 is operable / configured to perform the above reference signal symbol sequence. Figure 6 Method 600 is described.

[0155] Figure 20 2 is a schematic diagram of an example of an apparatus 2000 for determining a plurality of reference signal symbol sequences. The apparatus 2000 includes a processing circuit 2002 (e.g., one or more processors) and a memory 2004 in communication with the processing circuit 2002. The memory 2004 contains instructions executable by the processing circuit 2002, such as computer program code 2010. The apparatus 2000 also includes an interface 2006 in communication with the processing circuit 2002. Although the interface 2006, the processing circuit 2002, and the memory 2004 are shown as being connected in series, these may alternatively be interconnected in any other manner, such as via a bus.

[0156] In one embodiment, the memory 2004 contains instructions executable by the processing circuit 2002 such that the device 2000 is operable / configured to: select a plurality of reference signal symbol sequences, wherein a first reference signal symbol sequence corresponds to a constellation point on a Grassmann manifold; and select a phase for at least a subset of the reference signal symbol sequences to increase the sum of inner products of pairs of reference signal symbol sequences in at least the subset of the reference signal symbol sequences. In some examples, the device 2000 is operable / configured to perform the above reference Figure 13 Method 1300 is described.

[0157] It should be noted that the examples mentioned above illustrate rather than limit the present invention, and those skilled in the art will be able to design many alternative examples without departing from the scope of the appended claims. The word "comprising" does not exclude the existence of elements or steps other than those listed in the claims, and "a or an" does not exclude multiple, and a single processor or other unit can implement the functions of several units described in the following statements. When using the terms "first", "second", etc., they should only be understood as labels that are convenient for identifying specific features. In particular, unless otherwise expressly stated, they should not be interpreted as describing the first or second feature (that is, the first or second of such features that occur in time or space) of multiple such features. Unless otherwise expressly stated, the steps in the method disclosed herein can be performed in any order. Any reference symbols in the statement should not be interpreted as limiting its scope.

[0158] References

[0159] 1. I. Kammoun, A.M. Cipriano, and J.C. Belfore, “Non-coherent codes over the Grassmannian,” IEEE Transactions on Wireless Communications, vol. 6, no. 10, October 2007.

[0160] 2. K.H.N. Go, A.Decurninge, M.Guillaud, and S.Yang, “Transmitter and receiver communication apparatus for non-coherent communication,” U.S. Patent No. US11258649B2, February 2022.

Claims

1. A method (500) for transmitting data to a network node, the method comprising: selecting (502) one of a plurality of reference signal symbol sequences based on the data to be transmitted to the network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of the reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; and The selected reference signal symbol sequence is transmitted (504) to the network node.

2. The method according to claim 1, wherein Each sequence of reference signal symbols is associated with a different value of the data.

3. The method according to claim 1 or 2, wherein: Selecting (502) one of a plurality of reference signal symbol sequences includes selecting from 2 B reference signal symbol sequences and / or 2 B Reference signal symbol sequences are selected from constellation points, where B is the number of data bits encoded by each reference signal symbol sequence.

4. The method according to any one of claims 1 to 3, wherein Selecting (502) one of a plurality of reference signal symbol sequences includes selecting from 2 B constellation points, where B is the number of data bits encoded by each constellation point.

5. The method according to any one of claims 1 to 4, wherein The Grassmann manifold is at least a 2n-dimensional manifold, where n is the number of reference signal symbols in each reference signal symbol sequence.

6. The method according to any of claims 1 to 5, comprising transmitting (504) the selected sequence of reference signal symbols across a plurality of first resource elements.

7. The method of claim 6, comprising repeating transmission of the selected sequence of reference signal symbols across a plurality of second resource elements.

8. The method according to claim 7, wherein: The first plurality of resource elements are in a first frequency range and the second plurality of resource elements are in a second frequency range that does not overlap with the first frequency range.

9. The method according to claim 7 or 8, wherein The first resource element and the second resource element are within a resource block, a time slot, a mini-time slot, a subframe and / or a frame.

10. The method according to any one of claims 1 to 9, wherein The selected reference signal symbol sequence is transmitted to the network node in one or more time-domain symbol periods.

11. The method according to any one of claims 1 to 10, comprising transmitting at least one additional reference signal symbol sequence to the network node, wherein The at least one additional reference signal symbol sequence corresponds to a legacy reference signal.

12. The method according to any one of claims 1 to 11, wherein The selected reference signal symbol sequence transmitted is a pilot signal or a demodulation reference signal (DM-RS).

13. The method according to any one of claims 1 to 12, wherein The network node comprises a user equipment (UE).

14. The method according to claim 13, wherein: The method is performed by a Radio Access Node (RAN).

15. The method according to any one of claims 1 to 12, wherein The network nodes include radio access nodes (RAN).

16. The method according to claim 15, wherein The method is performed by a user equipment (UE).

17. The method according to any one of claims 1 to 16, wherein The reference signal symbol sequence and / or the constellation point are determined according to the method of any one of claims 38 to 46.

18. A method (600) of receiving data from a network node, the method comprising: receiving (602) a reference signal symbol sequence from a plurality of reference signal symbol sequences from the network node, wherein the reference signal symbol sequences correspond to constellation points on a Grassmann manifold and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of the reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; and The data transmitted by the network node is determined (604) based on the reference signal symbol sequence.

19. The method according to claim 18, wherein Each sequence of reference signal symbols is associated with a different value of the data.

20. The method according to claim 18 or 19, wherein Existence 2 B reference signal symbol sequences and / or 2 B constellation points, where B is the number of data bits encoded by each reference signal symbol sequence.

21. The method according to any one of claims 18 to 20, wherein Determining (604) the data transmitted by the network node includes determining that the plurality of reference signal symbols comprises one of the constellation points, wherein each constellation point represents a different sequence of reference signal symbols.

22. The method according to claim 21, wherein Existence 2 B constellation points, where B is the number of data bits encoded by each constellation point.

23. The method according to any one of claims 18 to 22, wherein The Grassmann manifold is at least a 2n-dimensional manifold, where n is the number of reference signal symbols in each reference signal symbol sequence.

24. The method according to any of claims 18 to 23, comprising receiving (602) the sequence of reference signal symbols across a plurality of first resource elements.

25. The method of claim 24, comprising receiving repetitions of the reference signal symbol sequence across a plurality of second resource elements.

26. The method according to claim 25, wherein The first plurality of resource elements are in a first frequency range and the second plurality of resource elements are in a second frequency range that does not overlap with the first frequency range.

27. The method according to claim 25 or 26, wherein The first resource element and the second resource element are within a resource block, a time slot, a mini-time slot, a subframe and / or a frame.

28. The method according to any one of claims 18 to 27, wherein The reference signal symbol sequence is received in one or more time-domain symbol periods.

29. A method according to any one of claims 18 to 28, comprising using the reference signal symbols to perform channel estimation.

30. The method according to any one of claims 18 to 29, comprising receiving at least one additional reference signal symbol sequence from the network node, wherein The additional reference signal symbol sequence corresponds to a legacy reference signal.

31. The method according to any one of claims 18 to 30, wherein The reference signal symbol sequence is a pilot signal or a demodulation reference signal (DM-RS).

32. The method according to any one of claims 18 to 31, wherein The network node comprises a user equipment (UE).

33. The method according to claim 32, wherein The method is performed by a Radio Access Node (RAN).

34. The method according to any one of claims 18 to 31, wherein The network nodes include radio access nodes (RAN).

35. The method according to claim 34, wherein The method is performed by a user equipment (UE).

36. A method according to any one of claims 18 to 35, wherein Determining (604) the data transmitted by the network node based on the reference signal symbol sequence includes determining data represented by the reference signal symbol sequence.

37. A method according to any one of claims 18 to 36, wherein The reference signal symbol sequence and / or the constellation point are determined according to the method of any one of claims 18 to 36.

38. A method (1300) for determining a plurality of reference signal symbol sequences, the method comprising: selecting (1302) a plurality of reference signal symbol sequences, wherein a first reference signal symbol sequence corresponds to a constellation point on a Grassmann manifold; and A phase is selected (1304) for at least a subset of the reference signal symbol sequences to increase a sum of inner products of pairs of the reference signal symbol sequences in at least the subset of the reference signal symbol sequences.

39. The method of claim 38, comprising: sending information identifying the plurality of reference signal symbol sequences to a transmitter, the transmitter being configured to transmit one or more of the second reference signal symbol sequences; and / or Information identifying the plurality of reference signal symbol sequences is sent to a receiver, the receiver being configured to receive one or more of the second reference signal symbol sequences.

40. The method according to claim 38 or 39, comprising: transmitting one or more of the reference signal symbol sequences; and / or One or more of the reference signal symbol sequences are received.

41. The method according to any one of claims 38 to 40, wherein Each sequence of reference signal symbols is associated with a different value of a data bit.

42. The method according to claim 41, wherein Existence 2 B reference signal symbol sequences and / or 2 B constellation points, where B is the number of data bits encoded by each reference signal symbol sequence.

43. The method according to claim 41 or 42, wherein Existence 2 B constellation points, where B is the number of data bits encoded at each constellation point.

44. The method according to any one of claims 38 to 43, wherein The Grassmann manifold is at least a 2n-dimensional manifold, where n is the number of reference signal symbols in each reference signal symbol sequence.

45. The method according to any one of claims 38 to 44, wherein The reference signal symbol sequence includes a pilot signal or a demodulation reference signal (DM-RS).

46. ​​The method of any one of claims 38 to 45, comprising selecting the phase for at least a subset of the reference signal symbol sequences to maximize the sum of inner products of the reference signal symbol sequence pairs in the at least subset of the reference signal symbol sequences.

47. An apparatus (1800) for transmitting data to a network node, the apparatus comprising a processor (1802) and a memory (1804), the memory containing instructions executable by the processor such that the apparatus is operable to: Based on the data to be transmitted to the network node, one of a plurality of reference signal symbol sequences is selected (502), wherein The reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of the reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; as well as The selected reference signal symbol sequence is transmitted (504) to the network node.

48. The apparatus of claim 47, wherein The memory (1804) contains instructions executable by the processor (1802) such that the apparatus is operable to perform the method (500) according to any one of claims 2 to 17.

49. An apparatus (1900) for receiving data from a network node, the apparatus comprising a processor (1902) and a memory (1904), the memory containing instructions executable by the processor such that the apparatus is operable to: A reference signal symbol sequence from a plurality of reference signal symbol sequences is received (602) from the network node, wherein The reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of the reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; as well as The data transmitted by the network node is determined (604) based on the reference signal symbol sequence.

50. The apparatus of claim 49, wherein The memory (1904) contains instructions executable by the processor (1902) such that the apparatus is operable to perform the method (600) according to any one of claims 19 to 37.

51. An apparatus (2000) for determining a plurality of reference signal symbol sequences, the apparatus comprising a processor (2002) and a memory (2004), the memory containing instructions executable by the processor such that the apparatus is operable to: A plurality of reference signal symbol sequences are selected (1302), wherein: The first reference signal symbol sequence corresponds to a constellation point on the Grassmann manifold; as well as A phase is selected (1304) for at least a subset of the reference signal symbol sequences to increase a sum of inner products of pairs of the reference signal symbol sequences in at least the subset of the reference signal symbol sequences.

52. The apparatus of claim 51, wherein The memory (2004) contains instructions executable by the processor (2002) such that the apparatus is operable to perform the method (1300) according to any one of claims 39 to 46.

53. An apparatus for transmitting data to a network node, the apparatus being configured to: Based on the data to be transmitted to the network node, one of a plurality of reference signal symbol sequences is selected (502), wherein The reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of the reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; as well as The selected reference signal symbol sequence is transmitted (504) to the network node.

54. The apparatus of claim 53, wherein The device is configured to perform a method (500) according to any one of claims 2 to 17.

55. An apparatus for receiving data from a network node, the apparatus being configured to: A reference signal symbol sequence from a plurality of reference signal symbol sequences is received (602) from the network node, wherein The reference signal symbol sequences correspond to constellation points on a Grassmann manifold, and each of the reference signal symbol sequences has a phase such that a sum of inner products of pairs of the reference signal symbol sequences in at least a subset of the reference signal symbol sequences is maximized; as well as The data transmitted by the network node is determined (604) based on the reference signal symbol sequence.

56. The apparatus of claim 55, wherein The device is configured to perform a method (600) according to any one of claims 19 to 37.

57. An apparatus for determining a plurality of reference signal symbol sequences, the apparatus being configured to: A plurality of reference signal symbol sequences are selected (1302), wherein: The first reference signal symbol sequence corresponds to a constellation point on the Grassmann manifold; and A phase is selected (1304) for at least a subset of the reference signal symbol sequences to increase a sum of inner products of pairs of the reference signal symbol sequences in at least the subset of the reference signal symbol sequences.

58. The apparatus of claim 57, wherein The device is configured to perform a method (1300) according to any one of claims 39 to 46.

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