A processing unit configured to obtain a subset of frequency domain coefficients from a full bandwidth of one or more radio signals, wireless device, method, computer program product, and non-transitory computer-readable storage medium therefor

Abstract

A method (100) of obtaining a subset of frequency domain coefficients from a full bandwidth of one or more radio signals, the method comprising: receiving (110) by a wireless device, WD, (322) the one or more radio signals from one or more remote transceiver nodes, TNodes, (396, 397, 398, 399), each radio signal comprising one or more samples in a time domain; assigning (120) each of the samples to one of two or more groups; and processing (128) the samples of the two or more groups by: calculating (135) a combined vector based on a function of the samples of the two or more groups; and transforming (145) the combined vector to obtain the subset of frequency domain coefficients; or by: transforming (130) each group of samples to obtain a frequency domain subvector for each group; and calculating (140) each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector Corresponding computer program product, non- transitory computer-readable storage medium, frequency raster unit, wireless device, and chips are also disclosed.

Description

[0001] A processing unit configured to obtain a subset of frequency domain coefficients from a full bandwidth of one or more radio signals, wireless device, method, computer program product, and non-transitory computer-readable storage medium therefor

[0002] Technical field

[0003] The present disclosure relates to a processing unit configured to obtain a subset of frequency domain coefficients from a full bandwidth of one or more radio signals, a wireless device, a method, a computer program product, and a non-transitory computer-readable storage medium therefor.

[0004] More specifically, the disclosure relates to a processing unit configured to obtain a subset of frequency domain coefficients from a full bandwidth of one or more radio signals, a wireless device, a method, a computer program product, and a non-transitory computer- readable storage mediumas defined in the introductory parts of the independent claims.

[0005] Background art

[0006] Digital beamforming architectures often outperform analog counterparts in terms of performance. The main reason is that in digital beamforming the beamforming is performed based on all antenna information, whereas in analog beamforming phase coherent combining is first performed and thereafter a beam sweep is still needed for determining the direct angle of arrival (AoA).

[0007] Performing beamforming based on all antenna information means a lot of processing for a baseband (BB) processor. However, in some implementations it is possible to perform digital beamforming with only a portion of the a vaila ble / a II antenna information. As an example, WO 2023 / 153979 Al discloses that the information needed (the essential information) is captured using the fact that the AoA (i.e., the beam coherence time) is significantly slower / longer than the channel coherence time and thus as long as one sufficiently often (e.g., every 10 millisecond, ms) take a snapshot of all antenna information all essential information is captured. Yet, in some implementations, all antenna information is collected more often, and therefore there is a need for a low complexity method / apparatus (compensating for the excess antenna information). Fourier analysis converts a signal from its original domain (often time and / or space) to a representation in the frequency domain and vice versa. The Discrete Fourier Transform (DFT) is obtained by decomposing a sequence of values into components of different frequencies. This operation is useful in many implementations but computing it directly from the definition is often not fast enough to be practical. A fast Fourier transform (FFT), e.g., Radix-2 or Radix-4 FFT, such as Cooley-Tukey FFT, rapidly computes such transformations by factorizing the DFT matrix into a product of sparse (mostly zero-valued) factors. Although FFT is generally faster than DFT, in some applications, such as digital beamforming, even faster conversion from time domain to frequency domain is desirable or even needed.

[0008] US 10419849 B2 discloses first calculating means for calculating frequency domain filter weights of beam-forming filters for a predetermined frequency raster so as to obtain target frequency responses for the beam-forming filters, so that application of the beamforming filters to the transducer array approximates a desired directional selectivity.

[0009] However, the frequency raster is defined by the DFT. Thus, there may be a need for determining frequency domain coefficients for (only) a sub-set of the carriers (thus improving / increasing efficiency).

[0010] Furthermore, sparse FFT is also known. In Sparse FFT only a subset of the input data is utilized. Sparse FFT performs well when many of the frequency coefficients are zero.

[0011] US 8670506 B2 discloses performing a full time-to-frequency conversion, which is followed by entropy coding and elimination. However, the method of US 8670506 B2 has a high complexity and is time-consuming, e.g., since a full time-to-frequency conversion is performed.

[0012] Thus, it may be desirable to have a low complexity method for achieving digital beamforming performance without channel information loss. Furthermore, alternative methods / devices, faster processing, and / or methods / devices reducing the complexity is needed, e.g., when not all non-zero frequency components / frequency domain coefficients are needed. An object of the present disclosure is to mitigate, alleviate or eliminate one or more of the above-identified deficiencies and disadvantages in the prior art and / or solve at least the above-mentioned problem or other problems.

[0013] According to a first aspect there is provided a processing unit comprisable by a wireless device (WD) and configured to: receive, from a remote transceiver node (TNode), a full bandwidth of a radio signal comprising two or more samples in a time domain, or, from each of two or more remote TNodes, a full bandwidth of a radio signal, each radio signal comprising one or more samples in a time domain; assign to each of two or more groups a respective subset of the two or more samples, the respective subsets are non-overlapping subsets; and process the samples of the two or more groups to obtain a subset of a full set of frequency domain coefficients by: calculating a combined vector based on a function of the samples of the two or more groups, and transforming the combined vector to obtain the subset of frequency domain coefficients; or by: transforming each group of samples to obtain only a frequency domain subvector for each group, and calculating each frequency domain coefficient of only the subset of frequency domain coefficients based on a function of the elements of the corresponding frequency domain subvector.

[0014] According to some embodiments, the processor is configured to: derotate each sample; and assign to each of the two or more groups a respective subset of the two or more derotated samples.

[0015] According to some embodiments, the processing unit is a frequency raster unit (FRU).

[0016] According to some embodiments, the subset of frequency domain coefficients is a frequency raster.

[0017] According to some embodiments, transforming each group of samples to obtain a frequency domain subvector for each group comprises fast Fourier transforming (FFT), such as Radix- FFT, or discrete Fourier transforming (DFT).

[0018] According to some embodiments, transforming the combined vector to obtain the subset of frequency domain coefficients comprises fast Fourier transforming (FFT), such as Radix- FFT, or discrete Fourier transforming (DFT). According to some embodiments, calculating each frequency domain coefficient of the subset comprises summing all of the elements of the corresponding frequency domain subvector.

[0019] According to some embodiments, calculating a combined vector comprises summing all of the samples of the corresponding group.

[0020] According to a second aspect there is provided a wireless device (WD) comprising: a digital interface chip (DIC), the DIC comprising a processing unit according to the first aspect or to any embodiments mentioned herein; a channel analyzer (CA); a baseband (BB) processing unit; a set of transceivers; and a set of antenna units.

[0021] According to some embodiments, the WD is configured to: receive frequency raster information from one of the TNodes; select a frequency raster based on the frequency raster information; and instruct the processing unit to process the samples of the two or more groups to obtain the subset of frequency domain coefficients in accordance with the selected frequency raster.

[0022] According to some embodiments, the WD is configured to: measure channel characteristics, such as a maximum delay spread; send a measurement report comprising the measured channel characteristics to the TNode ; and the received frequency raster information is based on the measured channel characteristics.

[0023] According to some embodiments, the DIC comprises the CA and a spatio-temporal filter unit having one or more output signals, the CA comprises a first estimation unit and a (second) processing unit, the CA is connected to the (second) processing unit, the CA is connected to the spatio-temporal filter unit, the spatio-temporal filter unit is configured to receive the two or more samples, the BB processing unit is connected to the DIC, the first estimation unit is configured to receive each frequency domain coefficient of the subset of frequency domain coefficients from the (second) processing unit, the first estimation unit is configured to estimate two or more channel estimate matrices associated with one or more propagation channels for the one or more radio signals and provide the two or more channel estimate matrices to the (second) processing unit, the (second) processing unit is configured to provide spatio-temporal filter coefficients to the spatio-temporal filter unit, and the one or more output signals of the spatio-temporal filter unit are fewer than the number of antennas of the set of antenna units, thereby reducing the number of antenna streams to be feed, by the DIC to the BB processing unit.

[0024] According to a third aspect there is provided a method of obtaining a subset of frequency domain coefficients from a full bandwidth of one or more radio signals, the method comprising: receiving, by a wireless device (WD), from a remote transceiver node (TNode), a full bandwidth of a radio signal comprising two or more samples in a time domain, or, from each of two or more remote TNodes, a full bandwidth of a radio signal, each radio signal comprising one or more samples in a time domain; assigning to each of two or more groups a respective subset of the two or more samples, the respective subsets are non-overlapping subsets; and processing the samples of the two or more groups by: calculating a combined vector based on a function of the samples of the two or more groups, and transforming the combined vector to obtain the subset of frequency domain coefficients; or by: transforming each group of samples to obtain a frequency domain subvector for each group, and calculating each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector.

[0025] According to some embodiments, the method further comprises: derotating each sample; and assigning to each of two or more groups a respective subset of the two or more samples comprises assigning to each of the two or more groups a respective subset of the two or more derotated samples. According to some embodiments, the subset of frequency domain coefficients is a frequency raster.

[0026] According to some embodiments, the method further comprises: receiving, by the WD, frequency raster information from the remote TNode; and selecting, by the WD, the frequency raster based on the frequency raster information.

[0027] According to some embodiments, the method further comprises: measuring, by the WD, channel characteristics, such as a maximum delay spread; sending a measurement report comprising the measured channel characteristics from the WD to a remote transceiver node (TNode).

[0028] According to some embodiments, the received frequency raster information is based on the measured channel characteristics. According to some embodiments, the WD comprises a set of transceivers, and a set of antenna units, and receiving by the WD the one or more radio signals comprises receiving the one or more radio signals by the set of transceivers via the set of antenna units, and the received one or more radio signals are converted to one or more digital signals by a set of converter units.

[0029] According to some embodiments, transforming comprises fast Fourier transforming, FFT, such as Radix- FFT, or discrete Fourier transforming each group of samples to obtain a frequency domain subvector for each group.

[0030] According to some embodiments, calculating each frequency domain coefficient of the subset comprises summing all of the elements of the corresponding frequency domain subvector.

[0031] According to some embodiments, calculating a combined vector comprises summing all of the samples of the corresponding group or calculating a sum of all the samples of the corresponding group (for each group).

[0032] According to a fourth aspect there is provided a computer program product comprising instructions, which, when executed on at least one processor of a processing device, cause the processing device to carry out the method according to the first aspect or any of the embodiments mentioned herein.

[0033] According to a fifth aspect there is provided a non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of a processing device, the one or more programs comprising instructions which, when executed by the processing device, causes the processing device to carry out the method according to the first aspect or any of the embodiments mentioned herein.

[0034] According to a sixth aspect there is provided a chip comprising the processing unit of the first aspect.

[0035] According to a seventh aspect there is provided a method for configuring a frequency domain pilot pattern for communication between a remote transceiver node (TNode) and a wireless device (WD), the method comprising: obtaining, by the TNode, one or more channel characteristics for a channel between the Tnode and the WD; obtaining, by the TNode, a frequency domain pilot pattern based on the obtained one or more channel characteristics; and transmitting, by the TNode, pilot configuration information to the WD, the pilot configuration information comprises information associated with the obtained frequency domain pilot pattern.

[0036] According to some embodiments, the pilot (or reference symbol / signal) pattern is on a frequency raster.

[0037] According to some embodiments, obtaining, by the TNode, one or more channel characteristics for a channel between a the Tnode and the WD is based on a received signal, such as a pilot signal, transmitted from the WD.

[0038] According to some embodiments, obtaining, by the TNode, one or more channel characteristics for a channel between a the Tnode and the WD is based on a received measurement report from the WD.

[0039] According to some embodiments, the pilot configuration information is transmitted on one or more of a radio resource control (RRC) layer, a media access (MAC) layer, and a physical (PHY) layer.

[0040] According to some embodiments, the channel characteristics comprises a maximum delay spread of the radio channel between the Tnode and the WD.

[0041] According to an eighth aspect there is provided a computer program product comprising instructions, which, when executed on at least one processor of a processing device, cause the processing device to carry out the method according to the seventh aspect or any of the embodiments mentioned herein.

[0042] According to a ninth aspect there is provided a non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of a processing device, the one or more programs comprising instructions which, when executed by the processing device, causes the processing device to carry out the method according to the seventh aspect or any of the embodiments mentioned herein.

[0043] According to a tenth aspect there is provided a transceiver node (TNode) of a system, the system comprising one or more TNodes and one or more wireless devices (WDs), the

[0044] TNode is configured to: obtain one or more channel characteristics for a channel between the Tnode and one of the WDs; obtain a frequency domain pilot pattern based on the obtained one or more channel characteristics; and transmit pilot configuration information to the WD, wherein the pilot configuration information comprises information associated with the obtained frequency domain pilot pattern.

[0045] Effects and features of the second, third, fourth, fifth, sixth, seventh, eighth, ninth, and tenth aspects are fully or to a substantial extent analogous to those described above in connection with the first aspect and vice versa.

[0046] Embodiments mentioned in relation to the first aspect are fully or largely compatible with the second, third, fourth, fifth, sixth, seventh, eighth, ninth, and tenth aspect and vice versa.

[0047] An advantage of some embodiments is that low complexity is achieved for digital beamforming, e.g., without channel information loss.

[0048] Another advantage of some embodiments is that alternative methods / devices of / for processing with low complexity and / or fast processing are achieved.

[0049] A further advantage of some embodiments is that faster processing is achieved, e.g., when not all non-zero frequency components / frequency domain coefficients are needed.

[0050] Yet a further advantage of some embodiments is that methods / devices reducing the complexity (e.g., devices with less complexity) are achieved.

[0051] Yet another advantage of some embodiments is that resolution / accuracy is increased.

[0052] Other advantages are that an improved, more robust and / or more accurate beamforming may be provided and / or that the signal quality is increased.

[0053] The present disclosure will become apparent from the detailed description given below. The detailed description and specific examples disclose preferred embodiments of the disclosure by way of illustration only. Those skilled in the art understand from guidance in the detailed description that changes, and modifications may be made within the scope of the disclosure.

[0054] Hence, it is to be understood that the herein disclosed disclosure is not limited to the particular component parts of the device described or steps of the methods described since such apparatus and method may vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting. It should be noted that, as used in the specification and the appended claims, the articles "a", "an", "the", and "said" are intended to mean that there are one or more of the elements unless the context explicitly dictates otherwise. Thus, for example, reference to "a unit" or "the unit" may include several devices, and the like. Furthermore, the words "comprising", "including", "containing" and similar wordings do not exclude other elements or steps. Moreover, the term "configured" or "adapted" is intended to mean that a unit or similar is shaped, sized, connected, connectable or otherwise adjusted for a purpose.

[0055] Brief of the

[0056] The above objects, as well as additional objects, features, and advantages of the present disclosure, will be more fully appreciated by reference to the following illustrative and non-limiting detailed description of example embodiments of the present disclosure, when taken in conjunction with the accompanying drawings.

[0057] Figure 1A is a schematic drawing illustrating a wireless device according to some embodiments;

[0058] Figure IB is a flowchart illustrating some method steps according to some embodiments;

[0059] Figure 2 is a flowchart illustrating actions / method steps implemented in a wireless device and / or in a frequency raster unit according to some embodiments;

[0060] Figure 3 is a flowchart illustrating some method steps according to some embodiments;

[0061] Figure 4 is a schematic drawing illustrating a computer readable (storage) medium according to some embodiments;

[0062] Figure 5 is a schematic drawing illustrating a system comprising wireless devices and transceiver nodes according to some embodiments;

[0063] Figure 6 is a flowchart illustrating actions / method steps implemented in a transceiver node according to some embodiments; Figure 7 is a schematic drawing illustrating a channel analyzer according to some embodiments;

[0064] Figure 8 is a schematic drawing illustrating a baseband processing unit according to some embodiments;

[0065] Figure 9 is a schematic drawing illustrating a wireless device according to some embodiments;

[0066] Figure 10A is a schematic drawing illustrating a frequency raster unit according to some embodiments;

[0067] Figure 10B is a schematic drawing illustrating a frequency raster unit according to some embodiments;

[0068] Figure 10C is a schematic drawing illustrating a frequency raster unit according to some embodiments; and

[0069] Figure 11 is a schematic drawing illustrating a chip according to some embodiments.

[0070] Detailed description

[0071] The present disclosure will now be described with reference to the accompanying drawings, in which preferred example embodiments of the disclosure are shown. The disclosure may, however, be embodied in other forms and should not be construed as limited to the herein disclosed embodiments. The disclosed embodiments are provided to fully convey the scope of the disclosure to the skilled person.

[0072] Terminology

[0073] Herein is referred to a processor / processing unit. The processor may be a digital processor. Alternatively, the processor may be a microprocessor, a microcontroller, a central processing unit, a co-processor, a graphics processing unit (GPU), a digital signal processor (DSP), an image signal processor, a quantum processing unit, or an analog signal processor. The processing unit may comprise one or more processors and optionally other units, such as a control unit. Thus, the processor may be implemented as a single-processor, a dualprocessor system, or a multiprocessor system. Furthermore, the invention can also be practiced in distributed computing environments where certain tasks are performed by remote processing devices that are linked through a communications network, e.g., 5G, to one or more local processors. In a distributed computing environment, program modules can be located in both local and remote memory storage devices. Moreover, some processing (e.g., for the data plane) may be moved to a centralized node, such as a centralized transceiver node (TNode). For example, baseband processing and / or higher layer processing, such as processing at layers above the physical layer, may be moved to a cloud, such as an mmW RAN cloud (wherein processing is performed by cloud processors). Such a (mmW) cloud deployment may bring significant cost savings to the operator due to centralized processing, collaborative radio processing, and availability of cheap commodity hardware.

[0074] Herein is referred to a baseband (BB) processor / processing unit. A BB processor is a processor specifically adapted for processing baseband signals / data.

[0075] Herein is referred to millimetre Wave (mmW) utilization, mmW communication, mmW communication capability and mmW frequency range. The mmW frequency range is from 24.25 Gigahertz (GHz) to 71 GHz or more generally from 24 to 300 GHz. The mmW frequency range may also be referred to as Frequency Range 2 (FR2).

[0076] Herein is referred to centimetre Wave (emW) utilization, emW communication, emW communication capability and emW frequency range. The emW frequency range is from 10 Gigahertz (GHz) to 30 GHz.

[0077] Herein is referred to a chip. A chip is an integrated circuit (chip) or a monolithic integrated circuit (chip) and may also be referred to as an IC, or a microchip.

[0078] Herein is referred to a wireless device (WD). A wireless device is any device capable of transmitting or receiving signals wirelessly. Some examples of wireless devices are user equipment (UE), mobile phones, cell phones, smart phones, Internet of Things (loT) devices, vehicle-to-everything (V2X) devices, vehicle-to-infrastructure (V2I) devices, vehicle-to-network (V2N) devices, vehicle-to-vehicle (V2V) devices, vehicle-to-pedestrian (V2P) devices, vehicle- to-device (V2D) devices, vehicle-to-grid (V2G) devices, fixed wireless access (FWA) points, and tablets.

[0079] Herein is referred to a Transmission Configuration Indicator (TCI) State. A TCI state contains parameters for configuring a quasi-co-location relationship between one or two downlink reference signals and the Demodulation reference signal (DM-RS) ports of the physical downlink shared channel (PDSCH), the DM-RS port of physical downlink control channel (PDCCH) and / or the channel state information reference signal (CSI-RS) port(s) of a CSI-RS resource.

[0080] Herein is referred to a "transceiver node" (TNode). A TNode may be a radio unit (RU), a remote radio unit (RRU), a repeater, a wireless node, or a base station (BS), such as a radio base station (RBS), a Node B, an Evolved Node B (eNB) or a gNodeB (gNB). Thus, a TNode may be a network (NW) node. Furthermore, a TNode may be a BS for a neighbouring cell, a BS for a handover (HO) candidate cell, a radio unit (RRU), a distributed unit (DU), another WD (e.g., a remote WD) or a base station (BS) for a (active / deactivated) secondary cell (SCell) or for a serving / primary cell (PCell, e.g., associated with an active TCI state), a laptop, a wireless station, a relay, a repeater device, a reconfigurable intelligent surface, or a large intelligent surface.

[0081] Herein is referred to an antenna unit. An antenna unit may be one single antenna. However, an antenna unit may also be a dual antenna, such as a dual patch antenna with a first (e.g., horizontal) and a second (e.g., vertical) polarization, thus functioning as two separate antennas or an antenna unit having two ports. Moreover, an antenna unit may be an antenna array, e.g., if analog beamforming is performed.

[0082] The polarization of an antenna refers to the orientation of the electric field of the radio wave transmitted by it and is determined by the physical structure of the antenna and its orientation. E.g., an antenna composed of a linear conductor (such as a dipole or whip antenna) oriented vertically will result in vertical polarization; if turned on its side the same antenna's polarization will be horizontal.

[0083] Herein is referred to vectors. A vector is a mathematical vector or a tuple (and not a physical vector having a direction).

[0084] Herein is referred to a subvector. A subvector is a proper (and non-empty) subset of a mathematical vector or of a tuple. Furthermore, a subvector may be a (proper sub-) row vector or a (proper sub-) column vector.

[0085] Herein is referred to non-overlapping subsets. A subset which is non-overlapping another subset, is a subset which has no elements in common with the another subset. Le., the intersection of two non-overlapping subsets is empty. Hence, the two non-overlapping subsets are completely separate and do not share any members.

[0086] Herein is referred to "derotation" (of complex valued numbers / samples), "derotate", and "derotated". A derotation of complex valued numbers / samples is a phase rotation in the opposite direction of one direction (or a first direction), e.g., of a complex valued number / sample which has previously been phase rotated in the one direction (or the first direction).

[0087] Herein is referred to a channel, and channel characteristics. A channel is a radio channel in telecommunications, i.e., a telecommunications radio channel.

[0088] Basic concept

[0089] Many multi-antenna communication systems, such as 4G, 5G-NR, and Wi-Fi, use OFDM systems in which data is sent on sub-carriers and pilots / reference signals are sent interleaved with data on specific sub-carriers (i.e., some of the sub-carriers) as well as transferred in specific OFDM symbols (close enough together for handling the channel coherence time). Typically, I FFT / FFT processing is performed and pilots / reference signals and data transmitted on every sub-carrier is extracted. The pilots / reference signals are then utilized for estimating the radio channel and, also to compute the combining weights for optimal coherent combining of the respective received signal from each respective antenna. Since the FFT complexity is high, large bandwidth (BW) signals with many carriers and received with many antennas implies high complexity (e.g., higher than a threshold).

[0090] However, by configuring a specific subset of sub-carriers with reference signals (e.g., configuring specific sub-carriers with reference signals according to a raster, such as a (equidistant) frequency raster, the raster specifying a subset of frequency domain coefficients needed for estimating the channel characteristics between the TNode and the WD) and sending / transmitting information (e.g., raster information) about which sub-carriers have been configured with reference signals to the WD it is, thus, possible to reconstruct all channel information for the channel over the entire OFDM symbol bandwidth utilizing only the subset of sub-carriers.

[0091] Alternatively, by knowing or measuring (by a WD) a maximum (possible) delay spread of the channel (between a TNode and the WD), a specific (smallest) subset of sub-carriers needed for reconstructing the entire channel information over the entire OFDM symbol bandwidth can be determined. The subset of sub-carriers is dependent on the maximum delay spread of the (radio) channel, the smaller delay spread the smaller the subset needs to be, and the larger delay spread the larger the subset needs to be. By configuring this specific (smallest) subset of sub-carriers with reference signals (e.g., configuring specific sub-carriers with reference signals according to a raster, such as an equidistant raster, the raster specifying a, e.g., smallest, subset of frequency domain coefficients needed for estimating the channel characteristics between the TNode and the WD) it is, thus, possible to reconstruct all channel information for the channel.

[0092] Thus, a basic concept of this invention is a low complexity reference signal information extraction method, that extracts only the frequency domain (f-domain) information for specific, i.e., a subset of, sub-carriers comprising the reference signals fulfilling the requirement above (i.e., the reference signals needed for reconstructing all channel information needed). Since all channel information for all sub-carriers can be reconstructed from the reference signals comprised by the subset of sub-carriers, there is no information loss (from not extracting the frequency domain information for all other sub-carriers, e.g., since they do not contain any additional channel information). From the (channel) information obtained from the extracted frequency domain information, compression parameters compressing the number of information streams from N antenna streams to K (K < N) virtual antenna streams is computed without losing any relevant information.

[0093] Embodiments

[0094] In the following, embodiments will be described where figure 1A illustrates a wireless device according to some embodiments and figure IB illustrates some method steps according to some embodiments. Figure 1A depicts a wireless device (WD) 322. In some embodiments, the WD 322 comprises a Multi-Antenna Transmitter and Receiver Arrangement (MATARA) 400. The WD 322 and / or the MATARA 400 comprises one or more (i.e., a set of) receivers / transceivers 500, 501, ..., 515. Furthermore, the WD 322 and / or the MATARA 400 comprises one or more (i.e., a set of) antenna units / ports 700, 701, ..., 715. The one or more receivers / transceivers 500, 501, ..., 515 are configured to receive the one or more analog radio signals via the one or more antenna units / ports 700, 701, ..., 715. In some embodiments, the WD 322 and / or the MATARA 400 comprises one or more converter units 900, 901, ..., 915. Each converter unit 900, 901, ..., 915 is connected or connectable to a corresponding transceiver 500, 501, ..., 515. Each converter unit comprises an analog to digital converter (ADC) and / or a digital to analog converter (DAC). Alternatively, each converter unit 900, 901, ..., 915 comprises one ADC / DAC pair (comprising one DAC and one ADC) for each quadrature (Q) component and one ADC / DAC pair (comprising one DAC and one ADC) for each in-phase (I) component of the transceiver(s) it is connected / connectable to. The converter units 900, 901, ..., 915 are configured to convert the one or more analog radio signals into one or more (corresponding) digital, e.g., baseband, signals, and / or configured to convert the one or more digital, e.g., baseband, signals into one or more (corresponding) analog radio signals.

[0095] Furthermore, the WD 322 and / or the MATARA 400 comprises one (or more) digital interface chip (DIC) 320. Each converter unit 900, 901, ..., 915 is connected or connectable to the DIC 320. Alternatively, the DIC comprises the converter units 900, 901, ..., 915 (and optionally the one or more receivers / transceivers 500, 501, ..., 515 and / or the one or more antenna units / ports 700, 701, ..., 715). In some embodiments, the DIC 320 comprises a (first) processing unit 1100, such as a frequency raster unit (FRU). Furthermore, in some embodiments, the DIC 320 comprises a spatio-temporal filter unit 1190. The spatio-temporal filter unit 1190 comprises one or more spatio-temporal filters (or spatial filters). Furthermore, the spatio-temporal filter unit 1190 has one or more output signals. Moreover, the WD 322 and / or the MATARA 400 comprises a baseband processing unit (BB PROC) 600. The BB PROC 600 is connected or connectable to the DIC 320. Furthermore, the WD 322 and / or the MATARA 400 comprises a channel analyzer (CA) 920. In some embodiments (as shown in figure 9), the DIC 320 comprises the CA 920.

[0096] Figure IB illustrates some method steps of a method 100. The method 100 is a method for / of obtaining a (proper and / or non-empty) subset of frequency domain coefficients from a full bandwidth of one or two or more radio (frequency) signals. Le., the full (passband) bandwidth of one or two or more radio (frequency) signals comprises a (full) set of frequency domain coefficients and the (proper and / or non-empty) subset of frequency domain coefficients comprises less than all the frequency domain coefficients of the set of frequency domain coefficients. Thus, the subset of frequency domain coefficients comprises / consists of less / fewer than all frequency domain coefficients of the (full) set of frequency domain coefficients (or the subset of frequency domain coefficients comprises / consists of less / fewer frequency domain coefficients than the (full) set of frequency domain coefficients, e.g., the subset of frequency domain coefficients comprises / consists of frequency domain coefficients for one or more subcarriers, such as every M:th subcarrier, wherein M is e.g., 2, 3, 4, 5 , 6, 7, 8, 16, 32, 64 (i.e., the carrier comprises 2 or more subcarriers). The method 100 comprises receiving (110), by a wireless device (WD) 322 the one (or two) or more radio (frequency) signals from one or more remote transceiver nodes (TNodes) 396, 397, 398, 399. Alternatively, the method 100 comprises receiving 110, by the WD 322, from a remote transceiver node, TNode, (396, 397, 398, 399) a full bandwidth of a radio signal comprising two or more samples in a time domain. As another alternative, the method 100 comprises receiving 110, by the WD 322 from each of two or more remote TNodes (396, 397, 398, 399) a full bandwidth of a radio signal, each radio signal comprising one or more samples in a time domain.

[0097] Each radio signal comprises one or more samples (e.g., N1 samples) in a time domain (after digitalization or analog to digital conversion). The one or more samples in a time domain are transformable to a (full) set of frequency domain coefficients in the frequency domain. In some embodiments, N1 samples belong to a single (OFDM) symbol. Alternatively, N1 samples is needed for representing the entire bandwidth (BW) of the one or more radio signals. As another alternative, N1 frequency coefficients are needed to represent all information in the one or more radio / information signals. In some embodiments, receiving (or obtaining) 110, by the WD 322, the one or more radio signals comprises receiving 112 the one or more radio signals by the set of transceivers 500, 501, ..., 515 via the set of antenna units 700, 701, ..., 715. Furthermore, in some embodiments, the received one or more radio signals are converted to respective one or more digital signals by the one or more (i.e., a set of) converter units 900, 901, ..., 915. Furthermore, the method comprises assigning (120) each of the samples to one of two or more groups. In some embodiments, each of the samples is assigned to one of Ml groups, where Ml is smaller than Nl. Alternatively, the method 100 comprises assigning 120 to each of two or more groups a respective subset of the two or more samples. The respective subsets are proper subsets, non-empty, and / or non-overlapping subsets (of the group of samples comprising the two or more samples). Moreover, the method 100 comprises processing 128, e.g., by the processing unit 1100, the samples of the two or more groups. In some embodiments, the method 100 comprises pre-processing (i.e., calculating 135 a vector) the samples followed by transforming 145 the pre-processed samples. Alternatively, the method 100 comprises transforming 130 the samples followed by post-processing the transformed samples (i.e., calculating 140 frequency domain coefficients). Thus, in some embodiments, the method (and / or the step of processing 128) comprises transforming 130 each group of samples to obtain (only) a frequency domain subvector for each group (instead of obtaining a full frequency domain vector for each group). In some embodiments, each group of samples is transformed separately (from the other group or groups). Furthermore, in some embodiments, transforming 130, 145 comprises discrete Fourier transforming 134 each group of samples (separately) to obtain a frequency domain subvector for each group. Alternatively, transforming 130, 145 comprises fast Fourier transforming, FFT, 132, such as Radix-2 FFT, each group of samples (separately) to obtain a frequency domain subvector for each group. In some embodiments, transforming 130 each group of samples to obtain a frequency domain subvector for each group is performed without obtaining any elements of a full frequency domain vector not belonging to the frequency domain subvector. Alternatively, or additionally, transforming 130 each group of samples to obtain a frequency domain subvector for each group consists of transforming each group of samples to obtain only a frequency domain subvector for each group.

[0098] The method comprises calculating / determining 140 each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector. Furthermore, in some embodiments, calculating 140 each frequency domain coefficient of the subset of frequency domain coefficients comprises summing 142 all of the elements of the corresponding frequency domain subvector. In some embodiments, calculating 140 each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector is performed without calculating any frequency domain coefficients of the full set of frequency domain coefficients other than the frequency domain coefficients of the subset. Alternatively, or additionally, calculating 140 each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector consists of calculating each frequency domain coefficient of only the subset based on a function of the elements of the corresponding frequency domain subvector.

[0099] Alternatively (to the steps 130 and 140), the method (and / or the step of processing 128) comprises calculating 135 a combined (time domain) vector based on a function of the samples of the two or more groups. The combined (time domain) vector comprises one or two or more intermediate time domain coefficients aO, al, ..., a7 (shown in figure 10C). Thereafter, the method (and / or the step of processing 128) comprises transforming 145 the vector (or the one or two or more intermediate time domain coefficients aO, al, a7) to obtain the subset of frequency domain coefficients. Furthermore, in some embodiments, calculating 135 a combined (time domain) vector comprises summing 136 all of the samples of the corresponding group (for each group). Moreover, in some embodiments, transforming 145 comprises discrete Fourier transforming 147 the combined vector to obtain the subset of frequency domain coefficients. Alternatively, transforming 145 comprises fast Fourier transforming (FFT) 146, such as Radix-2 FFT or Radix-4 FFT, the combined vector to obtain the subset of frequency domain coefficients.

[0100] In some embodiments, the method comprises derotating 115 each sample. In some embodiments, derotating 115 is performed with a derotation frequency. In some embodiments, the derotation frequency is based on the subset of frequency coefficients. In these embodiments (the embodiments wherein derotating 115 is performed), assigning 120 each of the samples to one of two or more groups comprises assigning 125 each of the derotated samples to one of the two or more groups. Alternatively, assigning 120 to each of two or more groups a respective subset of the two or more samples comprises (or consists of) assigning 125 to each of the two or more groups a respective subset of the two or more derotated samples. Furthermore, in some embodiments, the subset of frequency domain coefficients is a frequency raster, such as an equidistant frequency raster. Alternatively, a frequency raster, such as an equidistant frequency raster, comprises the subset of frequency domain coefficients. For an equidistant frequency raster each frequency domain coefficient of the subset of frequency domain coefficients is separated by an integer multiple of a defined / predefined frequency raster size. As an example, if the defined frequency raster size is four, then every fourth frequency domain coefficient belongs to the subset of frequency domain coefficients (while all other frequency domain coefficient of the set of frequency domain coefficients do not belong to the subset of frequency domain coefficients). If the defined frequency raster size is four, every fourth frequency domain coefficient belongs to the subset of frequency domain coefficients (while all other frequency domain coefficient of the set of frequency domain coefficients do not belong to the subset of frequency domain coefficients). As another example, if the defined frequency raster size is eight, then every eighth frequency domain coefficient belongs to the subset of frequency domain coefficients (while all other frequency domain coefficient of the set of frequency domain coefficients do not belong to the subset of frequency domain coefficients). As yet another example, if the defined frequency raster size is two, then every second frequency domain coefficient belongs to the subset of frequency domain coefficients (while all other frequency domain coefficient of the set of frequency domain coefficients do not belong to the subset of frequency domain coefficients). In other words, an equidistant frequency raster having an input frequency outputs a (pre-defined) integer multiple, such as 2, 3, 4, 8, 16, of the input frequency.

[0101] Example A:

[0102] Assume a Signal

[0103] We want to determine every M th (M = 2a) frequency component starting with bin p e [0,M — 1],

[0104] That means the and hence, if we compensate for the "p" rotation, the sum will repeat itself every Nl / M samples. By summing over the M groups first and then perform FFT (linear operation) the complexity is reduced to an FFT of size Nl / M.

[0105] Algorithm A j2npn

[0106] 1. De-rotation: xd(n = e x(n), (compensate for p to translate raster to M * k)

[0107] 2. Group samples IV, = (^)Z + i, I = 0, — 1 , i = 0, . ,, M — 1) , and sum over the groups and then perform FFT(N1 / M) on the sum, to obtain f — domain suhvector Xd(i~)

[0108] As can be seen from Example A and Algorithm A, if p is selected to be Nl / M or zero, no derotation (or shifting) needs to be performed. Thus, by selecting p to be zero, complexity is reduced, time / power consumption is reduced and / or efficiency is improved / increased. Furthermore, if p is not 0 or Nl / M, compensation or derotation is performed. Le., if sample K*n, n=0, ..., n_max, is utilized as a starting point, no de-rotation is needed and if sample p is utilized as a starting point (and thereafter K*n+p), derotation with a phase proportional or equal to -p is needed / performed. In some embodiments, the method comprises measuring / estimating 111, by the WD 322, channel characteristics. As an example, the WD 322 measures the channel state information reference signals (CSI-RSs) and estimates the channel characteristics. Examples of channel characteristics measured / estimated are path loss, amplitude statistics, delay spread, and maximum delay spread. Path loss is the reduction in signal strength that occurs as a radio wave propagates through the air. Delay spread is a measure of the multipath profile of the channel between the TNode 397 and the WD 322. It is generally defined as the difference between the time of arrival of the earliest component (e.g., the line-of-sight wave if it exists) and the time of arrival of the latest / last multipath component. Maximum delay spread measures the full time extent over which the multipath arrivals are spread out, from the earliest to the latest component. The wider this spread, the more dispersion in time the channel causes. The maximum delay spread is useful because it characterizes the full dispersive effect of the channel. In some embodiments, the method comprises sending / transmitting 112 a measurement report comprising the measured channel characteristics from the WD 322 to a remote transceiver node (TNode) 397, 398, 399. In these embodiments, the method comprises receiving 113, by the WD 322, frequency raster information from the remote TNode 397, e.g., in response to the sending / transmitting 112. The frequency raster information is based on the measured channel characteristics. As an example, if the measured / estimated channel characteristics is maximum delay spread, the frequency raster information comprises a specified frequency raster size based on the maximum delay spread. The specified frequency raster size is, in some embodiments, specified as or in accordance with the smallest subset of frequency domain coefficients needed for sufficiently accurate channel estimation (according to a quality measure, e.g., based on the measured channel characteristics).

[0109] Example B:

[0110] Assume an OFDM symbol of FFT-size N1 (or an OFDM symbol having N1 samples). If the delay spread of the channel is T samples, the frequency domain channel can be reconstructed using an IFFT by using (only) the reference symbols transmitted on every N1 / (T+1) sub-carrier. Hence, T+l reference signals (on I*N1 / (T+1) +p, 1=0, ..., T subcarriers, where p can by any of p=0, ..., N1 / (T1+1)-1) is sufficient to reconstruct the frequency domain channel information using an IFFT when the delay spread of the channel is T samples long (or less / shorter). Furthermore, in these embodiments, the method comprises selecting 114, by the WD 322 (or a control unit thereof), the frequency raster based on the frequency raster information. As an example, if the frequency raster information comprises a frequency raster size, the frequency raster is selected as the frequency raster having the (by the TNode 397) specified frequency raster size. Moreover, in some embodiments, the method comprises instructing, by the WD 322 (or a control unit thereof), the processing unit 1100 (or the FRU) to process 1128 (or to perform processing 1128 of) the samples of the two or more groups to obtain the subset of frequency domain coefficients in accordance with the selected frequency raster (i.e., to instruct the processing unit 1100 or the FRU to utilize the selected frequency raster for processing 1128 the samples). As an alternative to sending 112 and receiving 113, the, by the WD 322 (during measuring / estimating 111), measured / estimated channel characteristics, is directly, by the WD 322, utilized to select a frequency raster size. As an example, the WD 322 receives general information from a TNode 396, 397, 398, 399 about possible frequency raster sizes or the WD 322 stores general information (received from a TNode 396, 397, 398, 399 at some point in time prior to the storage, pre-defined, or preset at installation) about possible frequency raster sizes. Thus, the WD 322 has information about possible frequency raster sizes (at the time of measuring / estimating 111) and from the measured / estimated channel characteristics (e.g., maximum delay spread), the WD 322 selects the smallest subset of frequency domain coefficients needed for sufficiently accurate channel estimation (according to a quality measure), e.g., the smallest subset of frequency domain coefficients which accounts for the channel characteristics (e.g., accounts for / covers the maximum delay spread). In some embodiments, the frequency raster comprises / consists of frequency domain coefficients for every M:th subcarrier (e.g., the 0thsubcarrier, the M:th subcarrier, ...; and the frequency raster does not comprise any frequency domain coefficients of any of the first to [M-l]:th subcarrier, i.e., any other frequency domain coefficients). Furthermore, in some embodiments (as shown in figure IB), the method 100 comprises repeating 150 the steps of receiving 110, assigning 120, transforming 130, and calculating 140 and optionally repeating 150 one or more of the steps of assigning 125, measuring 111, sending 112, receiving 113, selecting 114, derotating 115, assigning 125, FFT 132, and discrete Fourier transforming (DFT) 134 (as described below or above). In some embodiments, repeating 150 is performed T number of times, such as 2, 4, 8, 16, 32, or 64 number of times, (and thereafter the repeating 150 is not repeated). Alternatively, repeating 150 is performed for every frame / slot, e.g., once every frame / slot or with a periodicity, such as every Q:th slot / frame. As another alternative, or additionally, repeating 150 is performed for each subgroup of 12 subcarriers. Moreover, in some embodiments, the method 100 comprises repeating 150 the steps of receiving 110, assigning 120, transforming 130, and calculating 140 and optionally repeating 150 one or more of the steps of assigning 125, measuring 111, sending 112, receiving 113, selecting 114, derotating 115, assigning 125, FFT 132, and discrete Fourier transforming (DFT) 134 (as described below or above), every time period. The time period is, in some embodiments, from 10 - 100000 milliseconds (ms), such as 10ms, 20ms, 50ms, 100ms, 200ms, 400ms, 800ms, Is, 10s, or 50s. Alternatively, the method 100 comprises repeating 150 the steps of receiving 110, assigning 120, transforming 130, and calculating 140 and optionally repeating 150 one or more of the steps of assigning 125, measuring 111, sending 112, receiving 113, selecting 114, derotating 115, assigning 125, FFT 132, and discrete Fourier transforming (DFT) 134 (as described below or above) based on an event. An example of such an event is that / when / if the signal quality (e.g., SNR) is / goes below a signal quality threshold. Another example of such an event is that / when / if an estimated signal quality variation is / goes lower than two standard deviations below the mean value. Yet another example of such an event is that / when / if the signal quality is / goes below a signal quality threshold and an estimated signal quality variation is / goes below two standard deviations below the mean value. Yet a further example of such an event is that / when / if the signal quality is / goes below a signal quality threshold or an estimated signal quality variation is / goes lower than two standard deviations below the mean value. The signal quality is measured as a Block Error Ratio (BLER), a Signal-to-Noise ratio (SNR), a Channel Quality Indicator (CQI), or a Bit Error Ratio (BER) of the channel / link for the communication between the one or more TNodes 396, 397, 398, 399 and the WD 322, 323. The signal quality, the mean value thereof and / or the variation of the mean value is monitored by one or more of the WD 322, 323 and the one or more TNodes 397, 398, 399.

[0111] Figure 2 illustrating actions / method steps (of the method 100 described above in connection with figures 1A and IB) implemented in a wireless device (WD) 322 (or a processing unit 1100 comprised / comprisable therein) and / or in a frequency raster unit (FRU) (comprised in or comprisable by / in the WD 322; or in a processing unit thereof) according to some embodiments. In some embodiments, the actions / method steps are caused by the WD 322, a processing unit thereof (i.e., a processing unit 1100 comprised / comprisable by the WD 322), the FRU, or a processing unit thereof. The WD 322, the processing unit 1100, or the FRU is configured to receive (1110) one or more radio signals from one or more remote transceiver nodes, TNodes, 396, 397, 398, 399 (e.g., after A / D conversion by the one or more converter units 900, 901, ..., 915). Alternatively, the WD 322, the processing unit 1100, or the FRU is configured to receive 1110 from a remote transceiver node (TNode) 396, 397, 398, 399 a full bandwidth of a radio signal comprising two or more samples in a time domain. As another alternative, the WD 322, the processing unit 1100, or the FRU is configured to receive (1110) from each of two or more remote TNodes 396, 397, 398, 399 a full bandwidth of a radio signal (i.e., receive two or more radio signals), each radio signal comprising one or more samples in a time domain (or from one remote TNode 396, 397, 398, 399 a full bandwidth of two or more radio signals, each radio signal comprising one or more samples in a time domain).

[0112] Each radio signal comprises one or more samples in a time domain (e.g., after A / D conversion). To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a first reception unit (e.g., first receiving circuitry, a first receiver or the set of transceivers 500, 501, ..., 515 with the set of antenna units 700, 701, ..., 715). Furthermore, in some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to convert the received one or more radio signals to one or more respective digital signals. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) one or more (i.e., a set of) converter units 900, 901, ..., 915. As an example, the WD 322 or more specifically the set of transceivers 500, 501, ..., 515 receives the one or more radio signals via the set of antenna units 700, 701, ..., 715, the converter units 900, 901, ..., 915 converts the received one or more radio signals to one or more respective digital signals, and the processing unit 1100, such as the FRU, receives the (one or) two or more samples in a time domain. Furthermore, the WD 322, the processing unit 1100, or the FRU assigns or is configured to assign (1120) each of the samples to one of two or more groups. Alternatively, the WD 322, the processing unit, or the FRU assigns or is configured to assign 1120 to each of two or more groups a (respective) subset of the two or more samples. The subsets (associated with different groups) are proper, non-empty and / or non-overlapping subsets. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a first assignment unit (e.g., first assigning circuitry, or a first assigner). Moreover, the WD 322, the processing unit 1100, or the FRU processes or is configured to process 1128 the samples of the two or more groups to obtain a subset of a full set of frequency domain coefficients. In some embodiments, the processing 1128 comprises transforming 1130 each group of samples to obtain (only) a (proper and / or non-empty) frequency domain subvector for each group (instead of obtaining a full frequency domain vector for each group). In these embodiments, the WD 322, the processing unit 1100, or the FRU (transforms or) is configured to transform 1130 each group of samples to obtain (only) a (proper and / or non-empty) frequency domain subvector for each group (instead of obtaining a full frequency domain vector for each group). To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a first transformation unit (e.g., first transforming circuitry, a first transformer, the grouping and transforming unit 1101 as seen in figures 10A-10B, or a transforming unit 1103 as seen in figures 10A-10B). Furthermore, in these embodiments, the processing 1128 comprises calculating 1140 each frequency domain coefficient of (only) the subset of frequency domain coefficients based on a function of the elements of the corresponding frequency domain subvector. Thus, the WD 322, the processing unit 1100, or the FRU calculates or is configured to calculate / determine 1140 each frequency domain coefficient of (only) a subset of frequency domain coefficients from a full bandwidth of the one or more radio signals based on a function of the elements of the corresponding frequency domain subvector. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a first calculation / determination unit (e.g., first calculating / determining circuitry, a first determinator / calculator, or a combining unit 1104 as seen in figures 10A-10B). Alternatively, the processing 1128 comprises calculating 1135 a combined vector based on a function of the samples of the two or more groups; and transforming 1145 the combined vector to obtain the subset of frequency domain coefficients. In these embodiments, the WD 322, the processing unit 1100, or the FRU (calculates or) is configured to calculate 1135 a combined vector based on a function of the samples of the two or more groups. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a first calculation / determination unit (e.g., first calculating / determining circuitry, a first determinator / calculator, or a combine unit 1113 as seen in figure 10C). Furthermore, in these embodiments, the WD 322, the processing unit 1100, or the FRU (transforms or) is configured to transform 1145 the combined vector to obtain the subset of frequency domain coefficients. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a second transformation unit (e.g., second transforming circuitry, a second transformer, or a transform unit 1116 as seen in figure 10C).

[0113] In some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to receive 1112 the one or more radio signals via the set of transceivers 500, 501, ..., 515 and via the set of antenna units 700, 701, ..., 715. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) the set of transceivers 500, 501, ..., 515 and the set of antenna units 700, 701, ..., 715). Moreover, in some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to rotate / derotate 1115 each sample. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a rotation / derotation unit (e.g., first rotating / derotating circuitry, a first rotator / derotator, or a rotation / derotation processing unit). In some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to assign (1125) each of the rotated / derotated samples to one of the two or more groups. Alternatively, the WD 322, the processing unit 1100, or the FRU is configured to assign 1125 to each of the two or more groups a respective subset of the two or more derotated samples. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) the first or a second assignment unit (e.g., the first or a second assigning circuitry, or the first or a second assigner) Furthermore, in some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to fast Fourier transform (FFT) 1132, such as Radix-2 FFT, each group of samples to obtain a frequency domain subvector for each group (as part of one of the transforming 1130, 1145, i.e., one of the transforming actions 1130, 1145). To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a first FFT transformation unit (e.g., first FFT transforming circuitry, or a first FFT transformer). Moreover, in some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to discrete Fourier transforming 1134 each group of samples to obtain a frequency domain subvector for each group (as part of one of the transforming 1130, 1145, i.e., one of the transforming actions 1130, 1145). To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a first DFT transformation unit (e.g., first DFT transforming circuitry, or a first DFT transformer). In some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to sum 1136 all of the samples of the corresponding group (for each group). To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a summation unit (e.g., first summing circuitry, or a summer). In some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to sum 1142 all of the elements of the corresponding frequency domain subvector. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a / the summation unit (e.g., first / second summing circuitry, the first summer, or a second summer). Furthermore, in some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to fast Fourier transform (FFT) 1146, such as Radix-2 FFT, the combined vector to obtain the subset of frequency domain coefficients. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) an FFT transformation unit (e.g., first / second FFT transforming circuitry, or first / second FFT transformer). Alternatively, the WD 322, the processing unit, or the FRU is configured to discrete Fourier transforming 1147 the combined vector to obtain the subset of frequency domain coefficients. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) first / second DFT transformation unit (e.g., first / second DFT transforming circuitry, or first / second DFT transformer). Moreover, in some embodiments, the WD 322, the processing unit 1100, or the FRU is configured to cause repetition 1150 of the steps / actions of receive 1110, assign 1120, transform 1130, calculate 1140 and optionally the steps / actions of receive via antennas / transceivers 1112, derotate 1115, assign derotated samples 1125, FFT 1132, DFT 1134, sum 1142, and cause repetition 1150. To this end, the WD 322, the processing unit 1100, or the FRU may be associated with (e.g., operatively connectable, or connected, to) a repeating unit (e.g., repeating circuitry, a repeater, or a processor).

[0114] Figure 3 illustrates some method steps of a method 2100 according to some embodiments. The method 2100 is for configuring a frequency domain pilot pattern or a frequency domain reference symbol / signal pattern for communication between a remote transceiver node (TNode) 396, 397, 398, 399 and a wireless device (WD) 322. The method 2100 comprises obtaining 2110, by the TNode 397, one or more channel characteristics (e.g., path loss, amplitude statistics, delay spread, and / or maximum delay spread) for a channel between the Tnode 397 and the WD 322. Furthermore, the method 2100 comprises obtaining 2120, by the TNode 397, a frequency domain pilot pattern based on the obtained one or more channel characteristics. Moreover, the method 2100 comprises transmitting 2130, by the TNode 397, pilot configuration information to the WD 322. The pilot configuration information comprises information associated with the obtained frequency domain pilot pattern. In some embodiments, the pilot pattern is on a frequency raster, i.e., a frequency raster comprises / defines the pilot pattern. Furthermore, in some embodiments, obtaining 2110, by the TNode 397, one or more channel characteristics for a channel between a the Tnode 397 and the WD 322 is based on a received signal, such as a pilot / reference signal, transmitted from the WD 322. Alternatively, or additionally, obtaining 2110, by the TNode 397, one or more channel characteristics for a channel between a the Tnode 397 and the WD 322 is based on a received measurement report, comprising the measured channel characteristics from the WD 322 to the remote transceiver node (TNode) 397 (obtained by the WD 322 through one or more measurements), from the WD 322. Furthermore, in some embodiments, the pilot configuration information is transmitted on / via / over a radio resource control (RRC) layer.

[0115] Alternatively, or additionally, the pilot configuration information is transmitted on / via a media access (MAC) layer. As another alternative, or additionally (to on / via RRC and / or MAC), the pilot configuration information is transmitted on / via a physical (PHY) layer. In some embodiments, the channel characteristics comprises a maximum delay spread of the channel between the Tnode 397 and the WD 322 (or the channel characteristics is or comprises components as defined herein). Furthermore, in some embodiments, the method 2100 comprises repeating 2140 the steps of obtaining 2110, obtaining 2120, transmitting 2130, and optionally one or more other steps described herein, such as repeating 2140. In some embodiments, repeating 2140 is performed T number of times, such as 2, 4, 8, 16, 32, or 64 number of times, (and thereafter the repeating 2140 is not repeated).

[0116] In some embodiments, the method 2100 comprises repeating 2140 one or more of the steps of obtaining 2110, obtaining 2120, transmitting 2130, and optionally one or more other steps described herein, such as repeating 2140, every time period. The time period is, in some embodiments, from 10 - 100000 milliseconds (ms), such as 10ms, 20m, 50ms, 100ms, 200ms, 400ms, 800ms, Is, 10s, or 50s. Alternatively, the method 100 comprises repeating 2140 one or more of the steps of obtaining 2110, obtaining 2120, transmitting 2130, and optionally one or more other steps described herein, such as repeating 2140 based on an event. An example of such an event is that / when / if the signal quality (e.g., SNR) is / goes below a signal quality threshold. Another example of such an event is that / when / if an estimated signal quality variation is / goes lower than two standard deviations below the mean value. Yet another example of such an event is that / when / if the signal quality is / goes below a signal quality threshold and an estimated signal quality variation is / goes below two standard deviations below the mean value. Yet a further example of such an event is that / when / if the signal quality is / goes below a signal quality threshold or an estimated signal quality variation is / goes lower than two standard deviations below the mean value. The signal quality is measured as a Block Error Ratio (BLER), a Signal-to-Noise ratio (SNR), a Channel Quality Indicator (CQI), or a Bit Error Ratio (BER) of the channel / link for the communication between the one or more TNodes 396, 397, 398, 399 and the WD 322, 323. The signal quality, the mean value thereof and / or the variation of the mean value is monitored by one or more of the WD 322, 323 and the one or more TNodes 397, 398, 399.

[0117] According to some embodiments, a computer program product comprising a non- transitory computer readable medium 400, such as a punch card, a compact disc (CD-) ROM, a read only memory (ROM), a digital versatile disc (DVD), an embedded drive, a plug-in card, or a universal serial bus (USB; e.g., USB 1.x, USB 2.0, USB 3.x, or USB4) memory, is provided. Figure 4 illustrates an example computer readable medium in the form of a compact disc (CD-) ROM 400. The computer readable medium has stored thereon a computer program comprising program instructions. The computer program is loadable into a data processor (PROC) 420, which may, for example, be comprised in a computer or a computing device, a processing unit 410 associated with the WD 322, 323 or with the TNode 396, 397, 398, 399. When loaded into the data processor 420, the computer program may be stored in a memory (MEM) 430 associated with or comprised in the data processor 420. According to some embodiments, the computer program may, when loaded into and run by the data processor 420, cause execution of method steps according to, for example, the method illustrated in figure IB or the method illustrated in figure 3, both described herein. Furthermore, in some embodiments, there is provided a computer program product comprising instructions, which, when executed on at least one processor of a processing device, cause the processing device to carry out the method illustrated in figure IB or the method illustrated in figure 3, both described herein. Moreover, in some embodiments, there is provided a non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of a processing device, the one or more programs comprising instructions which, when executed by the processing device, causes the processing device to carry out the method illustrated in figure IB or the method illustrated in figure 3, both described herein.

[0118] Figure 5 illustrates a system 999. The system 999 may be a wireless / cellular communication system, a cellular network, a mobile network, a telecommunications network, a cellular radio system, a digital cellular network, a mobile phone network, a mobile phone cellular network, such as 1G, 2G (e.g, GSM, GPRS, or EDGE), 3G (e.g, UMTS or CDMA2000), 4G (e.g., LTE, WiMAX, or MBWA), 5G (e.g., 5G NR or 5G-Advanced), 6G, or an ad hoc / mesh NW, such as Bluetooth or Wi-Fi. Furthermore, the system 999 comprises one or more wireless devices (WD) 322, 323, ..., 328. Moreover, the system 999 comprises one or more transceiver nodes (TNodes) 396, 397, 398, 399, i.e., the system 999 comprises a set 395 of one or more TNodes 396, 397, 398, 399. The one or more TNodes 396, 397, 398, 399 may be base stations (gNBs, eNBs, RBS), remote radio units (RRUs), NTN units or remote wireless nodes. The WD 322 (as well as the WDs 323, ..., 328) is, in some embodiments, configured to communicate with (e.g., send / transmit and / or receive signals, such as radio (frequency; or wireless) signals, e.g., comprising baseband / information signals, to / from) one or more of the remote TNodes 396, 397, 398, 399. In some embodiments, some, or all of the communication between the WD 322 (as well as the WDs 323, ..., 328) and the remote TNodes 396, 397, 398, 399 is performed with radio signals in the mmW frequency range. Alternatively, or additionally, the communication between the WD 322 (as well as the WDs 323, ..., 328) and the remote TNodes

[0119] 396, 397, 398, 399 is performed with radio signals in the emW frequency range. As another alternative, or additionally (to mmW and emW), (some of) the communication between the WD 322 (as well as the WDs 323, ..., 328) and the remote TNodes 396, 397, 398, 399 is performed with radio signals in the FR1 frequency range. Each Tnode 396, 397, 398, 399 is, in some embodiments, connected to a central computing device via a backhaul, such as a fibrebased backhaul, a wireless point-to-point backhaul, a copper-based wireline, satellite communications and / or point-to-multipoint wireless technologies.

[0120] Figure 6 illustrates actions / method steps implemented in a transceiver node 396, 397, 398, 399 according to some embodiments. A system, e.g., the system described above in connection with figure 5, comprises one or more TNodes 395, 396, 397, 398 and one or more wireless devices, WDs, 322, 323, ..., 328. Furthermore, one or more of the TNodes 395, 396,

[0121] 397, 398 is configured to obtain 2210 one or more channel characteristics for a channel between the Tnode 397 and the WD 322, 323. To this end, the one or more TNodes 395, 396, 397, 398 may be associated with (e.g., operatively connectable, or connected, to) a first obtainment unit (e.g., first obtaining circuitry, a first obtainer, or a channel analyzer / processor, e.g., of the WD 322, 323). Moreover, the one or more of the TNodes 395,

[0122] 396, 397, 398 is configured to obtain 2220 a frequency domain pilot pattern based on the obtained one or more channel characteristics. To this end, the one or more TNodes 395, 396,

[0123] 397, 398 may be associated with (e.g., operatively connectable, or connected, to) the first or a second obtainment unit (e.g., first / second obtaining circuitry, a first / second obtainer, or a processor with an associated memory). The one or more of the TNodes 395, 396, 397, 398 is configured to transmit 2230 pilot configuration information to the WD 322. To this end, the one or more TNodes 395, 396, 397, 398 may be associated with (e.g., operatively connectable, or connected, to) a first transmitting unit (e.g., first transmitting circuitry, a first transmitter, or the set of transceivers 500, 501, ..., 515 with the set of antenna units 700, 701, ..., 715). The pilot configuration information comprises information associated with the obtained frequency domain pilot pattern. Moreover, in some embodiments, the one or more TNodes 395, 396, 397, 398 is configured to repeat or cause repetition 2240 of the steps / actions of obtain 2210, obtain 2220, transmit 2230 and optionally one or more other steps described herein, such as repeat 2240. In some embodiments, repeat 2240 is performed T number of times, such as 2, 4, 8, 16, 32, or 64 number of times, (and thereafter the repeat 2240 is not repeated).

[0124] Figure 7 illustrates a channel analyzer (CA) 920 according to some embodiments. The DIG 320 (shown in figures 1A and 9) comprises the CA 920. The CA 920 comprises a first estimation unit 922 and a (second) processing unit 924. Furthermore, the CA 920 is connected or connectable to the processing unit 1100 (or the FRU) (shown in figures 1A and 9). Moreover, the CA 920 is connected or connectable to the spatio-temporal filter unit 1190 (shown in figures 1A and 9). The spatio-temporal filter unit 1190 is configured to receive the one or more samples in the time domain (comprised by the received one or more radio signals, e.g., after A / D conversion thereof). The CA 920, and more specifically the first estimation unit 922 thereof is configured to receive each frequency domain coefficient of the subset of frequency domain coefficients from the processing unit 1100 (or the FRU) (or from a calculation / processing unit thereof). Furthermore, from the received frequency domain coefficients of the subset of frequency domain coefficients, the first estimation unit 922 is configured to obtain / estimate two or more channel estimate matrices Hl, H2, HK associated with one or more propagation channels for the (received) one or more radio signals. Moreover, the first estimation unit 922 is configured to provide the two or more channel estimate matrices Hl, H2, HK to the (second) processing unit 924. The (second) processing unit 924 is configured to receive the two or more channel estimate matrices Hl, H2, ..., HK from the first estimation unit 922. Moreover, the (second) processing unit 924 is configured to provide the spatio-temporal filter coefficients to the spatio-temporal filter unit 1190. In some embodiments, the (second) processing unit 924 (e.g., together with the first estimation unit 922) is configured to determine the spatio-temporal filter coefficients by utilizing linear detection, such as Minimum Mean Square Error (MMSE) or Zero-Forcing (ZF). ZF (or null-steering) precoding is a method of spatial signal processing by which a multiple antenna transmitter can null the multi-user interference in a multi-user MIMO wireless communication system. If the transmitter knows the downlink channel state information (CSI) perfectly, ZF-precoding can achieve almost the system capacity when the number of users is large. Alternatively, the (second) processing unit 924 (e.g., together with the first estimation unit 922) is configured to determine the spatio-temporal filter coefficients by utilizing maximum-ratio combining (MRC; also known as ratio-squared combining or predetection combining). MRC is a method of diversity combining in which the signals from each channel are added together, the gain of each channel is made proportional to the root mean square (rms) signal level and inversely proportional to the mean square noise level in that channel, different proportionality constants are used for each channel. MRC is the optimum combiner for independent additive white Gaussian noise channels. Furthermore, MRC has the advantage of producing an output with acceptable SNR even when none of the individual signals are themselves acceptable. As another alternative (or additionally to MMSE, ZF, or MRC), the (second) processing unit 924 is configured to provide the full set of spatio-temporal filter coefficients to the spatio-temporal filter unit 1190. As yet another alternative (or additionally to MMSE, ZF, or MRC), the (second) processing unit 924 is configured to provide a reduced set of spatio-temporal filter coefficients to the spatio-temporal filter unit 1190 (as described below). Furthermore, the spatio-temporal filter unit 1190 is configured to reduce the number of antenna streams (one stream from each antenna unit 700, 701, ..., 715) from N (e.g., 16, 32, or 64) antenna streams to K (e.g., 1, 2, 4, or 8) virtual antenna streams. In some embodiments, the reduction from N antenna streams to K virtual antenna streams is performed by configuring the spatio-temporal filter unit 1190 to have N inputs and K outputs. In some embodiments, the number (K) of outputs is predetermined. As an example, the baseband processing unit (BB proc) 600 is adapted (or able) to receive K inputs. Thus, the number of outputs from the spatio-temporal filter unit 1190 has been selected / predetermined to be K. Alternatively, the number (K) of outputs is determined in dependence or according to the reduced set of spatio-temporal filter coefficients. As an example, the reduced set of spatio-temporal filter coefficients comprises M2 vectors of spatial filter coefficients. Thus, the number (K) of outputs is selected / determined to be M2. As another alternative, the number (K) of outputs is dependent on the number of spatiotemporal filters of (comprised by) the spatio-temporal filter unit 1190, e.g., if the spatiotemporal filter unit 1190 comprises K spatio-temporal filters, the number of outputs will be (or is selected to be) K.

[0125] In some embodiments, the one or more digital signals (i.e., the A / D converted analog radio signals or the one or more samples in the time domain) are obtained from one or more (or a first plurality, i.e., NRX, of) frequency-division multiplexed (FDM) signals received by the WD 322, 323 (i.e., the one or more analog radio signals are FDM signals). In some embodiments, the FDM signals are orthogonal frequency-division multiplexed (OFDM) signals. Alternatively, the FDM signals are non-orthogonal frequency-division multiplexed (N-OFDM) signals. As another alternative, the FDM signals comprises a mix of OFDM signals and N-OFDM signals, i.e., the FDM signals comprises one or more OFDM signals and one or more N-OFDM signals. In some embodiments, the WD 322, 323 receives the one or more FDM signals (transmitted from / by one or more, e.g., NTX, transmit antenna ports of a transmitting device, i.e., a TNode 396, 397, 398, 399). In some embodiments, the WD 322, 323 receives information (from the transmitting device) about the number (NTX) of transmit antenna ports of the transmitting device (utilized for transmitting the FDM signals). Furthermore, in some embodiments, the method 100 comprises obtaining, by the WD 322, 323 (or by analog to digital converters 900, 901, ..., 915 thereof), one or more digital signals from the received one or more FDM signals (e.g., one digital signal for each received FDM signal). In some embodiments, the WD 322, 323 or more specifically the CA 920 (and / or the first estimation unit 922 thereof) is configured to obtain one or two or more channel estimate matrices Hl, H2, ... HK associated with (one or two or more) propagation channels for / associated with the FDM signals. The propagation channels are, in some embodiments, the channels over which the one or more FDM signals are transmitted from the NTX (or a second plurality of) transmit (antenna) ports of a transmitting / sending device (e.g., one of the TNodes 396, 397, 398, 399, such as a base station, BS) to the NRX / N (first plurality of) antennas / antenna ports of the WD 322, 323. In some embodiments, estimation / obtainment (by the first estimation unit 922) of one or more channel estimate matrices comprises estimation of one or more channel estimate matrices per subcarrier, e.g., per one or more (i.e., a subgroup) of 12 subcarriers.

[0126] Alternatively, estimation / obtainment (by the first estimation unit 922) of one or more channel estimate matrices comprises estimation of one or more channel estimate matrices per resource block. As another alternative, estimation / obtainment (by the first estimation unit 922) of one or more channel estimate matrices comprises estimation of one or more channel estimate matrices per frequency range. The frequency ranges may vary over the system bandwidth (i.e., the span of a frequency range may be different from a span of another frequency range). This may be useful for highly dispersive channels, i.e., an improved performance may be achieved for highly dispersive channels. Some (e.g., a first and / or second) frequency ranges may cover only one or a few subcarriers, while other (e.g., a third and or fourth) frequency ranges may cover one or more resource blocks.

[0127] Furthermore, in some embodiments (the alternative with provision of the full set of spatio-temporal filter coefficients or the alternative with provision of the reduced set of spatio-temporal filter coefficients), the CA 920 or more specifically the (second) processing unit 924 is configured to apply a function F to the two or more channel estimate matrices Hl, H2, ... HK to obtain a resulting matrix RM. The resulting matrix RM is the matrix resulting from the applying. In some embodiments, the function F is a quadratic function QF. An example of such a QF is HkHk, where H is Hermitian transpose, a.k.a. conjugate transpose. Furthermore, in some embodiments, the function F is a polynomial, such as a linear polynomial, a quadratic polynomial, a cubic polynomial, a quartic polynomial (of degree four) or a quintic polynomial (of degree five). In some embodiments, the function F is a positive- definite function. Moreover, in some embodiments (the alternative with provision of the full set of spatio-temporal filter coefficients or the alternative with provision of the reduced set of spatio-temporal filter coefficients), obtainment of one or more channel estimate matrices comprises determination of at a first time instant t the two or more channel estimate matrices Hk(t) and determination of at a second time instant t-T the two or more channel estimate matrices Hk(t — T). In these embodiments, the function F is a function of the two or more channel estimate matrices at the first time instant squared Hkt Hk(t) and the two or more channel estimate matrices at the second time instant squared — T). Furthermore, in some embodiments, the function F comprises weights. In these embodiments, application of a function F comprises configuration of the weights per subcarrier (SC). Alternatively, or additionally application of a function F comprises configuration of the weights per resource block. As another alternative, or additionally, application of a function F comprises configuration of the weights per frequency range ak. As yet another alternative, or additionally, application of a function F comprises configuration of the weights per transmit / TX (antenna) port Q. Moreover, in some embodiments (e.g., the alternative with provision of the reduced set of spatio-temporal filter coefficients), the (second) processing unit 924 is configured to matrix-decompose (e.g., utilizing matrix decomposition) the resulting matrix RM into a first decomposition matrix U and a second decomposition matrix A. The first decomposition matrix U comprises (one or two or more) first vectors of coefficients Ul, U2, ..., UN (or a first set of vectors of coefficients Ul, U2, ..., UN). In some embodiments, the first vectors of coefficients Ul, U2, ..., UN are the column vectors UC1, UC2, ..., UCM of the first decomposition matrix U. The second decomposition matrix A is different from the first decomposition matrix U. In some embodiments, the second decomposition matrix A is a diagonal matrix. Furthermore, the second decomposition matrix A comprises (one or two or more) second vectors of coefficients Al, A2, ..., AN (or a second set of vectors of coefficients Al, A2, ..., AN). In some embodiments, each second vector (or each vector of the second set of vectors) comprises zero or one non-zero coefficient (i.e., all coefficients or all but one coefficient of each second vector are zero-valued). Thus, in these embodiments, each second vector is / comprises either a single non-zero coefficient / value (e.g., an eigenvalue) or no non-zero coefficients / values. Moreover, the first decomposition matrix U is a unitary eigenvector matrix comprising one or two or more eigenvectors. In some embodiments, the second decomposition matrix A is a diagonal matrix, and the diagonal elements of the diagonal matrix are the eigenvalues corresponding to the one or two or more eigenvectors (i.e., the diagonal matrix comprises eigenvalues corresponding to the one or two or more eigenvectors). In some embodiments, the (second) processing unit 924 is configured to, from the first vectors of coefficients Ul, U2, ..., UN, determine vectors of spatial filter coefficients Tl, T2, ..., TN. In some embodiments, the vectors of spatial filter coefficients Tl, T2, ..., TN are determined directly from the first vectors of coefficients Ul, U2, ..., UN and / or determined from the first vectors of coefficients Ul, U2, ..., UN only. Alternatively, the vectors of spatial filter coefficients Tl, T2, ..., TN are determined directly from the first vectors of coefficients Ul, U2, UN without consulting any second vector of coefficients Al, A2, AN. In some embodiments, determination of vectors of spatial filter coefficients Tl, T2, ..., TN comprises selection, e.g., by the (second) processing unit 924, of the vectors of spatial filter coefficients Tl, T2, ..., TN as one or two or more column vectors of the first decomposition matrix U. Alternatively, determination of vectors of spatial filter coefficients Tl, T2, ..., TN comprises selection, e.g., by the (second) processing unit 924, of the vectors of spatial filter coefficients Tl, T2, ..., TN as one or two or more row vectors of the first decomposition matrix U. Furthermore, in some embodiments (the alternative with provision of the reduced set of spatio-temporal filter coefficients), the (second) processing unit 924 is configured to select a subset Tl, ..., TM (comprising M2 elements / vectors) of the vectors of spatial filter coefficients Tl, T2, ..., TN (comprising N2 elements / vectors, wherein N2 is larger than M2). The (selected) subset Tl, ..., TM is associated with (e.g., one or more of) the (e.g., 4) most dominant eigenvectors of the first decomposition matrix U and therefore also associated with the most dominant eigenvalues of the second decomposition matrix (since each eigenvector of the first decomposition matrix has a corresponding eigenvalue of the second decomposition matrix A). In some embodiments, the (selected) subset Tl, ..., TM is associated with one or more of the 1, 2, 3 or 4 most dominant eigenvectors of the first decomposition matrix U (and with one or more of the 1, 2, 3 or 4 most dominant eigenvalues of the second decomposition matrix A). As an example, the subset Tl, ..., TM is associated with the most dominant eigenvector / eigenvalue, the second most dominant eigenvector / eigenvalue, the third most dominant eigenvector / eigenvalue and the fourth most dominant eigenvector / eigenvalue (and optionally one or more other eigenvectors / eigenvalues of the, e.g., 10 or 20, most dominant eigenvectors / eigenvalues) of the first / second decomposition matrix U / A. As another example, the subset Tl, ..., TM is associated with the second most dominant eigenvector / eigenvalue, the third most dominant eigenvector / eigenvalue, the fourth most dominant eigenvector / eigenvalue, and the fifth most dominant eigenvector / eigenvalue (and optionally one or more other eigenvectors / eigenvalues of the, e.g., 10 or 20, most dominant eigenvectors / eigenvalues) of the first / second decomposition matrix U / A. As yet another example, the subset Tl, ..., TM is associated with the most dominant eigenvector / eigenvalue, and the second most dominant eigenvector / eigenvalue (and optionally one or more other eigenvectors / eigenvalues of the, e.g., 5, 10 or 20, most dominant eigenvectors / eigenvalues) of the first / second decomposition matrix U / A. As a further example, the subset Tl, ..., TM is associated with the second most dominant eigenvector / eigenvalue, and the third most dominant eigenvector / eigenvalue (and optionally one or more other eigenvectors / eigenvalues of the, e.g., 5, 10, or 20, most dominant eigenvectors / eigenvalues) of the first / second decomposition matrix U / A. As another further example, the subset Tl, ..., TM is associated with the most dominant eigenvector / eigenvalue, and the third most dominant eigenvector / eigenvalue (and optionally one or more other eigenvectors / eigenvalues of the, e.g., 5, 10, or 20, most dominant eigenvectors / eigenvalues) of the first / second decomposition matrix U / A. As a further another example, the subset Tl, ..., TM is associated with the most dominant eigenvector / eigenvalue, the second most dominant eigenvector / eigenvalue, the third most dominant eigenvector / eigenvalue, and / or the fourth most dominant eigenvector / eigenvalue (and optionally one or more other eigenvectors / eigenvalues of the, e.g., 5, 10, or 20, most dominant eigenvectors / eigenvalues) of the first / second decomposition matrix U / A.

[0128] Moreover, in some embodiments, the DIC 320 and more specifically the spatiotemporal filter unit 1190 is configured to compress the one or more (or first plurality of, i.e., NRX) digital signals utilizing only the subset Tl, ..., TM. Thus, in some embodiments, the one or more (or first plurality of, i.e., NRX) digital signals is compressed by utilizing the subset Tl, ..., TM (only) as coefficients in / for / of the spatio-temporal filters of the spatio-temporal filter unit 1190. The subset Tl, ..., TM is a reduced set of spatio-temporal filter coefficients. In some embodiments, the one or more (or first plurality of) FDM signals are transmitted from one or more (or a second plurality, i.e., NTX, of) transmit (antenna) ports (and / or transmitters) of a transmitting device / TNode (and received by NRX / first plurality of / one or more receiving antennas / antenna ports of the WD 322, 323, which may be spatially distributed). In these embodiments, compression may comprise conversion, e.g., by the DIC 320 or more specifically the spatio-temporal filter unit 1190, the one or more (or first plurality of, i.e., NRX) digital signals into one or more (or a third plurality, i.e., NS, of) virtual antenna streams. In some embodiments, the third plurality is larger than the second plurality. Thus, in some embodiments, the number of virtual antenna streams is larger than the number of transmit antenna ports (NS>NTX). Moreover, in some embodiments, the WD 322, 323 (i.e., the receiving device) receives information from the transmitting device, e.g., TNode 397, 398, 399 (or from an intermediary device, e.g., TNode 396) about the number of transmit antenna ports of the transmitting device. In some embodiments (e.g., if the receiving device has received information about the number of transmit antenna ports of the transmitting device from the transmitting device), the number of virtual antenna streams is selected, by the receiving device (i.e., the WD 322, 323; or by the processing unit 924), to be larger than the number of transmit antenna ports. In some embodiments, the conversion is a lossy conversion (e.g., by utilizing only a subset of the vectors of spatial filter coefficients), and thus the one or more (or plurality of) digital signals is compressed into one or more (or a plurality) of virtual antenna streams. Alternatively, the conversion is a non-lossy conversion.

[0129] Furthermore, in some embodiments, compression comprises disregarding all other eigenvectors of the first decomposition matrix and / or disregarding all vectors of spatial filter coefficients Tl, T2, ..., TN other than the subset Tl, ..., TM, i.e., disregarding the vectors of spatial filter coefficients TM+1, ..., TN not belonging to the subset Tl, ..., TM. By compressing the one or more (or first plurality of) digital signals utilizing only the subset Tl, ..., TM, it is guaranteed that the most dominant components (of the resulting matrix) are utilized. Furthermore, by compressing the one or more (or first plurality of) digital signals utilizing only the subset Tl, ..., TM complexity is reduced. Moreover, in some embodiments, the method 100 comprises sending the one or more (or third plurality, i.e., NS, of) virtual antenna streams to the BB PROC 600 for further processing / beamforming. In some embodiments, the one or more (or third plurality, i.e., NS) is a known parameter, e.g., user-defined, standard-defined, or system-defined. In these embodiments, the method 100 may comprise splitting the one or more (or third plurality, i.e., NS, of) virtual antenna streams into a first subset and a second subset (e.g., before obtainment of one or more channel estimate matrices). Furthermore, in some embodiments, one or more of obtainment of one or more channel estimate matrices, application of a function F, matrix-decomposition, determination of vectors of spatial filter coefficients Tl, T2, ..., TN, selection of the vectors of spatial filter coefficients Tl, T2, ..., TN, and compression is performed for each of the first and second subsets. As an example, splitting may be utilized if there are two transmit (TX) ports (first and second TX ports). A user (or the system) may then define two spatial filters for receiving from the first TX port and another two (different) spatial filters for receiving from the second TX port. Alternatively, splitting is not utilized, and a user (or the system) defines four spatial filters to be utilized when receiving regardless of if receiving from the first or the second TX port. By utilizing splitting, receiving and / or transmitting is adapted to be performed with a specific TX port (only), e.g., when communicating in a multiple transmission and reception points (multi-TRP) case. Furthermore, in some embodiments, the vectors of spatial filter coefficients Tl, T2, ..., TN and / or the vectors of the subset Tl, ..., TM thereof are selected to be orthonormal vectors of spatial filter coefficients.

[0130] In some embodiments, the (second) processing unit 924 is configured to provide only a subset Tl, ..., TM (comprising M2 elements) of the vectors of spatial filter coefficients Tl, T2, ..., TN (comprising N2 elements, wherein N2 is larger than M2) as spatio-temporal filter coefficients to the spatio-temporal filter unit 1190. Furthermore, the spatio-temporal filter unit 1190 has one or more output signals. In some embodiments, the one or more output signals of the spatio-temporal filter unit 1190 are fewer than the number of antennas of the set of antenna units 700, 701, ..., 715 (i.e., receiving antennas). Thus, the number of antenna streams to be feed, by the DIC 320 to the BB PROC 600 is reduced (i.e., the number of virtual antenna streams to be feed, by the DIC 320 to the BB PROC 600, is smaller than the number of actual antennas / antenna streams utilized for receiving the one or more radio signals). Thus, complexity is reduced.

[0131] Figure 8 illustrates a baseband processing unit (BB proc) 600 according to some embodiments. The BB proc 600 is connected or connectable to the DIC 320 (shown in figures 1 and 9). Furthermore, the BB proc 600 comprises an FFT unit 602. The FFT unit 602 is, in some embodiments, a Radix-2 FFT, such as Cooley-Tukey FFT (or a regular FFT). Thus, the FFT unit 602 is, in some embodiments, not an FRU 1100. Instead, the FFT unit 602 is a full FFT unit, receiving the one or more samples in a time domain, and providing / outputting all or a (full) set of frequency domain coefficients. However, in some embodiments, the BB proc 600 is configured to receive a reduced number of (virtual) antenna streams from the DIC 320. Since the number of antenna streams is reduced, the FFT-processing is less complex, less timeconsuming and / or less power-consuming (than if FFT processing was performed for all antenna streams). Moreover, the BB proc 600 comprises a second estimation unit 604. The BB proc 600 comprises a BB combining unit (e.g., a processor) 606. The second estimation unit 604 receives or is configured to receive a (full) set of frequency domain coefficients. Furthermore, the second estimation unit 604 is configured to estimate two or more channel estimate matrices Hl, H2, HK associated with one or more propagation channels for the one or more radio signals (e.g., as described above for the first estimation unit 922). Moreover, the second estimation unit 604 provides / outputs the two or more channel estimate matrices Hl, H2, ..., HK to the BB combining unit 606. In some embodiments, MIMO is utilized. In these embodiments, two or more layers (L) are utilized and the BB combining unit 606 is configured to combine the reduced number of (virtual) antenna streams into one stream per layer (wherein L is equal to or smaller than K). Alternatively, the BB combining unit 606 is configured to combine the reduced number of (virtual) antenna streams into one (single) antenna stream. Thus, in some embodiments, the BB combining unit 606 comprises / includes a spatio-temporal filter unit. Furthermore, in some embodiments, the BB combining unit 606 is configured in the same or a similar manner as the (second) processing unit 924 (described above; e.g., configured to determine the spatio-temporal filter coefficients by utilizing MMSE, ZF, or MRC) and / or the spatio-temporal filter unit (included / comprised by the BB combining unit 606) is implemented similarly to the spatio-temporal filter unit 1190 (but with only one or L output / antenna streams and / or with only a reduced set of inputs, e.g., virtual antenna streams). Furthermore, in some embodiments, the BB proc 600 is configured to post-process and / or decode one or more information signals from the single antenna stream (or from the L antenna streams).

[0132] Figure 9 illustrates a wireless device (WD) 323 according to some embodiments. The (second) WD 323 comprises the same components as the (first) WD 322 described above in connection with figure 1A. The only difference between the (first) WD 322 and the (second) WD 323 is that the DIC 320 of the (second) WD 323 comprises the CA 920. Thus, complexity is reduced and / or faster processing is achieved.

[0133] Figures 10A-10C illustrate a frequency raster unit (FRU) 1100 according to some embodiments. In some embodiments, the processing unit 1100 (or the FRU) comprises a grouping and transforming unit 1101 (figs. 10A-10B). Furthermore, the processing unit 1100 (or the FRU) and / or the grouping and transforming unit 1101 comprises a grouping unit (e.g., a processor) 1102 and a transforming unit (e.g., an FFT unit) 1103. Moreover, the processing unit 1100 (or the FRU) comprises a combining unit (e.g., a processor) 1104. The processing unit 1100 (or the FRU) receives or is configured to receive one or more samples xO, xl, ..., x7 in the time domain (comprised by the received one or more radio signals; e.g., after A / D conversion by the converter units 900, 901, ..., 915 of the WD 322, 323). Furthermore, the processing unit 1100 (or the FRU) and / or the grouping unit 1102 assigns or is configured to assign 1120 each of the samples to one of two or more groups. As an example, the samples xO, xl, x2, x3 are assigned to a first group, and the samples x4, x5, x6, x7 are assigned to a second group (different from the first group). Moreover, the groups of samples are provided to the transforming unit 1103, i.e., the transforming unit 1103 receives or is configured to receive the groups of samples. The transforming unit 1103 transforms or is configured to transform the groups of samples (separately) into one or two or more intermediate frequency components E0, ... E3, OO, ..., 03. The one or two or more intermediate frequency components E0, ... E3, OO, ..., 03 are fewer than the one or more samples xO, xl, ..., x7 (since each frequency domain subvector does not comprise all intermediate frequency components because data transmitted on every sub-carrier does not need to be extracted for reconstructing the entire channel information over the entire OFDM symbol bandwidth as described above). As an example (shown in figure 10A), the one or more samples xO, xl, ..., x7 are grouped into two groups (first and second as indicated above) and thereafter transformed into two intermediate frequency components EO, OO (as seen in figure 10). Alternatively (shown in figure 10B), the one or more samples xO, xl, ..., x7 are grouped into two groups (first and second as indicated above) and thereafter transformed into four intermediate frequency components EO, El, OO, 01. Thus, the transforming unit 1103 transforms or is configured to transform each of the groups of samples into a frequency domain subvector for each group. As an example, the transforming unit 1103 transforms the first group of samples into a frequency domain subvector consisting of the intermediate frequency component EO and the second group of samples into a frequency domain subvector consisting of the intermediate frequency component OO (as seen in figure 10A). As another example, the transforming unit 1103 transforms the first group of samples into a frequency domain subvector consisting of the intermediate frequency components EO and El and the second group of samples into a frequency domain subvector consisting of the intermediate frequency components OO and 01 (as seen in figure 10B). Furthermore, the grouping and transforming unit 1101 and / or (more specifically) the transforming unit 1103 provides or is configured to provide the one or two or more frequency domain subvectors to the combining unit 1104, i.e., the combining unit 1104 receives or is configured to receive the one or two or more frequency domain subvectors. Moreover, the combining unit 1104 calculates / determines or is configured to calculate / determine 1140 each frequency domain coefficient of (only) the subset of frequency domain coefficients from a full bandwidth of the one or more radio signals based on a function of the elements of the corresponding frequency domain subvector. In some embodiments, each frequency domain coefficient of (only) the subset of frequency domain coefficients is calculated / determined by applying a function comprising addition and / or subtraction and optionally twiddle factors, to (each set of) corresponding intermediate frequency components of each frequency domain subvector.

[0134] As an example (seen in figure 10A), the combining unit 1104 calculates / determines or is configured to calculate / determine only the frequency domain coefficients X0 and X4 (since in this example the frequency domain coefficients X0 and X4 are the only frequency domain coefficients needed to be extracted for reconstructing the entire channel information over the entire OFDM symbol bandwidth), although one or more or all of the frequency domain coefficients XI, X2, X3, X5, X6, and X7 comprises information (e.g., are non-zero). As another example (seen in figure 10B), the combining unit 1104 calculates / determines or is configured to calculate / determine only the frequency domain coefficients X0, XI, X4 and X5 (since in this example the frequency domain coefficients X0, XI, X4 and X5 are the only frequency domain coefficients needed to be extracted for reconstructing the entire channel information over the entire OFDM symbol bandwidth), although one or more or all of the frequency domain coefficients X2, X3, X6, and X7 comprises information (e.g., are non-zero). Thus, complexity of the combining unit 1104 (fewer combining operations) and / or the time / power required for combining is reduced (due to fewer combining operations). As an example, seen in figure 10A, only two combining operations (solid lines) are performed instead of eight combining operations (solid and dashed lines).

[0135] In some embodiments (figure 10C), the processing unit 1100 (or the FRU) comprises a grouping unit 1111, a combine unit 1113, and a transform unit 1116. The FRU 1100 receives or is configured to receive one or more samples xO, xl, ..., x7 in the time domain (comprised by the received one or more radio signals; e.g., after A / D conversion by the converter units 900, 901, ..., 915 of the WD 322, 323). Furthermore, the processing unit 1100 (or the FRU) and / or the grouping unit 1111 assigns or is configured to assign 1120 each of the samples to one of two or more groups. As an example, the samples xO, xl, x2, x3 are assigned to a first group, and the samples x4, x5, x6, x7 are assigned to a second group (different from the first group). Alternatively, the samples xO, xl are assigned to a first group, the samples x2, x3 are assigned to a second group (different from the first group), the samples x4, x5 are assigned to a third group (different from the first and second groups), and the samples x6, x7 are assigned to a fourth group (different from the first, second, and third groups). As another alternative (shown in figure 10C), the samples xO, x2, x4, x6 are assigned to a first group, and the samples xl, x3, x5, x7 are assigned to a second group (different from the first group). Moreover, the groups of samples are provided to the combine unit 1113, i.e., the combine unit 1113 receives or is configured to receive the groups of samples. In some embodiments, the combine unit 1113 calculates / determines or is configured to calculate / determine fewer intermediate time domain coefficients (aO, al, ..., a7) than the samples (xO, xl, ..., x7) received (i.e., the combine unit 1113 calculates / determines or is configured to calculate / determine a combined vector comprising fewer intermediate time domain coefficients (aO, al, ..., a7) than the samples (xO, xl, ..., x7) received. As an example (seen in figure 10C), the combine unit 1113 calculates / determines or is configured to calculate / determine (a combined vector comprising) only the intermediate time domain coefficients aO and a4 (since in this example the frequency domain coefficients XO and X4 corresponding to the intermediate time domain coefficients aO and a4 are the only frequency domain coefficients needed to be extracted for reconstructing the entire channel information over the entire OFDM symbol bandwidth), although one or more other or all of the frequency domain coefficients Xl, X2, X3, X5, X6, and X7 and / or one or more other or all of the intermediate time domain coefficients aO, al, ..., a7 comprises information (e.g., are non-zero). In some embodiments, the samples of each group are summed together (by one or more summers). As an example (shown in figure 10C), the samples xO, x2, x4, x6 of the first group are summed together (i.e., aO = xO + x2 + x4+ x6) and the samples xl, x3, x5, x7 of the second group are summed together (i.e., a4 = xl + x3 + x5+ x7). Furthermore, in some embodiments, the combine unit 1113 is one single unit. Alternatively, the combine unit 1113 is two (or more) units (e.g., first and second combine units) as indicated by the dashed line in figure 10C, wherein the first group of samples xO, x2, x4, x6 are received and summed by a first combine unit to compute a first intermediate time domain coefficients aO and the second group of samples xl, x3, x5, x7 are received and summed by a second combine unit to compute a second intermediate time domain coefficients a4.

[0136] The combine unit 1113 provides or is configured to provide the one or two or more intermediate time domain coefficients (i.e., the combined vector) to the transform unit 1116, i.e., the transform unit 1116 receives or is configured to receive the one or two or more intermediate time domain coefficients (i.e., the combined vector). In some embodiments, i.e., optionally, twiddle factors are applied to one or more of the intermediate time domain coefficients aO, al, ..., a7, e.g., by the combine unit before providing the one or two or more of the intermediate time domain coefficients aO, al, ..., a7 to the transform unit 1116. The transform unit 1116 transforms or is configured to transform the received one or two or more intermediate time domain coefficients aO, al, a7 into one or two or more frequency domain coefficients X0, XI, ... X7. As an example (shown in figure 10C), the transform unit 1116 receives (only) the intermediate time domain coefficients aO and a4. Furthermore, the transform unit 1116 transforms the received intermediate time domain coefficients aO and a4 into corresponding frequency domain coefficients X0, X4 by performing e.g., DFT or FFT. Since, pre-processing (i.e., calculating 135 a vector) has been performed, the number of inputs to the transform unit has been reduced, thus a simpler / smaller transform unit can be / is utilized, and therefore complexity is reduced and / or the processing unit 1100 (or the FRU) is faster / more efficient (e.g., since the pre-processing together with the utilized transform unit 1116 comprises fewer operations than a transform unit without pre-processing would need to perform).

[0137] Furthermore, complexity of the transforming / transform unit 1103, 1116 (fewer transforming operations) and / or the time / power required for transforming is reduced (due to fewer transforming operations). Moreover, as can be seen from figures 10A, 10B and 10C, the effects / advantages mentioned above (reduced complexity / time / power) are present or will arise both when the calculated / determined (i.e., the subset of) frequency domain coefficients are not on a frequency raster (figure 10B) and when the calculated / determined frequency domain coefficients are on a frequency raster (figure 10A). However, with a frequency raster, the effects / advantages are improved / increased compared to without utilizing a frequency raster (i.e., the complexity / time / power is further reduced).

[0138] Figure 11 illustrates a chip 990 according to some embodiments. The chip 990 comprises the processing unit 1100 (or the FRU). Furthermore, in some embodiments, the chip 900 comprises the DIC 320 (and / or one or more of the components thereof) described in connection with figures 1A and 9.

[0139] As described above, weighting or weights may be applied when deriving spatial filters or coefficients thereof. Thus, the spatial characteristics of some subcarriers (SCs) are given lower weights than other subcarriers. In one non-limiting example, a weight 0<a_k<l may be applied per subcarrier when forming the matrix to be decomposed, i.e., each subcarrier SCI, SC2, ..., SCk may be associated with a respective weight al, a2, ..., ak and each weight al, a2, ..., ak has a value in the range from 0 to 1. The value of each weight al, a2, ..., ak may depend on the signal-to-noise-plus-interference ratio (SINR) of / associated with the corresponding subcarrier SCI, SC2, ..., SCk, the rank of / associated with the corresponding subcarrier SCI, SC2, ..., SCk, the importance of a subband manifested as a range of subcarriers, and / or the interference received in a subband. If it is desirable that a specific subcarrier SCn contributes more to the spatial filter(s), the value of the corresponding weight an for the specific subcarrier SCn is increased and if it is desirable that a specific subcarrier Scm contributes less to the spatial filter(s), the value of the corresponding weight am for the specific subcarrier is decreased.

[0140] Furthermore, weighting or weights may be applied when deriving the spatial filters, by giving / setting different weights to the spatial characteristics for different Tx ports, i.e., by configuring the weights per TX port (Q). In a non-limiting example, a diagonal weight matrix Q of size NTX times NTX is used. The diagonal elements of the diagonal weight matrix Q are all from 0 to 1. All other elements of the diagonal weight matrix Q are zero. Furthermore, the p:th diagonal element constitutes the weight imposed on the contribution by the p:th Tx port when forming the resulting matrix, i.e., the matrix to be decomposed. Thus, a lower value gives less influence, and a larger value gives more influence on the spatial filters. It is recognized that other forms of weighing can be carried out. For instance, different diagonal matrices can be used for different subcarriers to allow different weighting in different parts of the spectrum. This is merely one example of weighting. It is recognized that weighting may be carried out in many different ways. Regardless of approach, the desirable net effect is to deemphasize some subcarriers over others when deriving the spatial filters.

[0141] In some embodiments, the decomposition carried out (during matrix-decomposition) for deriving spatial filters at one time instant t is based on information from one or more previous time instants at which channel estimates across all Nrxreceive (Rx) antennas have been computed and / or one or more previous time instants t-rl, t-c2, ..., t-rk at which spatial filters have been derived. As an example, the decomposition is based on a weighted average, 0 < ( < 1,

[0142] As another example, the decomposition is based on a recursive equation / algorithm,

[0143] 0 < ? < 1, M(t < 0) = 0 M(t) = (1 (Nrxx Nrx). k

[0144] The above examples are merely two examples of how to include information / statistics from one or more previous time instants when deriving spatial filters. Regardless of approach, the desirable net effect is to have previous spatial characteristics to have some influence (through a weighting factor (3) when deriving the spatial filters based on the current spatial characteristics. One reason to do so is to account for a higher variability of the radio channel than observed during a single time instant when deriving the spatial filters. Another reason is to reduce the noise in channel estimates by averaging across two or more time instants. Whether to include information from previous time instant(s) may depend on whether the Transmission Configuration Indicator (TCI) state at a previous time instant is the same as for the current time instant. If the TCI state at a previous time instant is not the same as for the current time instant, one may choose to derive the spatial filters solely based on spatial characteristics from the current time instant, i.e., no inclusion of information from previous time instant(s).

[0145] Whether to include information from previous time instant(s) depends, in some embodiments, on the time between the current and the previous time instant T. In some embodiments, if T is larger than a time threshold, e.g., 200 ms, the spatial filter(s) are selected solely based on spatial characteristics from the current time instant (i.e., without inclusion of information from previous time instants) and if T is smaller than the time threshold, e.g., 200 ms, the spatial filter(s) are selected based on spatial characteristics from the current time instant as well as spatial characteristics from one or more previous time instants. Alternatively, instead of having a fixed time threshold (value), the time threshold (value) depends on acquired / measured / detected channel characteristics, e.g., the less variability the radio channel has (over time), the larger the time threshold is.

[0146] Alternatively, or additionally, whether to include information from previous time instant(s) depends on the (instantaneous) SINR of received reference signals, synchronization signals, or otherwise known signals used for channel estimation, e.g., when forming Hk. If SINR is lower than a SINR threshold, e.g., OdB, information from previous time instant(s) is included, whereas if SINR is higher than the SINR threshold, information from previous time instant(s) is not included. The derived spatial filters may, in some embodiments, be only nearly orthogonal rather than completely orthogonal as a result of mapping the derived filter coefficients to spatial filter coefficients in a fixed-point representation with limited number of integer and fractional bits. The key essence of the invention is the way of deriving the spatial filters based on the principal spatio-spectral components. Then necessary engineering considerations such as mapping results to representations in fixed and potentially a smaller number of bits, with floating or fixed point, may lead to minor inaccuracies due to quantization and adaptation to fixed-point arithmetic. Therefore, in some embodiments, the (derived) spatial filters are scaled, e.g., mutually orthogonally and / or mutually orthonormally. In some embodiments, the (derived) spatial filters are scaled mutually orthogonally (but not necessarily orthonormally), i.e., so that the scaled spatial filters are mutually orthogonal (but not necessarily orthonormal). Furthermore, in some embodiments, due to finite precision and / or fixed-point representations, orthogonal (base) vectors derived / obtained are not absolute orthogonal but only nearly orthogonal. By scaling (e.g., mutually orthogonally) the spatial filters, an improved fixed-point representation of the filter coefficients may be achieved.

[0147] Although described above that a one or more (or a third plurality of, i.e., NS) filters is derived from the spatio-spectral characteristics of all Tx ports, in some (alternative) embodiments, the Tx ports are divided into subsets, and for each subset of Tx ports, a corresponding subset of filters is derived. Furthermore, in some (alternative) embodiments, subcarriers are divided into subsets, and for each subset of subcarriers, a corresponding subset of filters is derived.

[0148] A (nonzero) vector v of dimension 0 is an eigenvector of a square O x O matrix A if it satisfies a linear equation of the form

[0149] Av = Av for some scalar A. Then the scalar (A) is called the eigenvalue corresponding to v (i.e., each eigenvector has a corresponding eigenvalue). Geometrically speaking, the eigenvectors of A are the vectors that A merely shrinks or elongates, and the amount that they shrink / elongate by is the eigenvalue. The above equation is called the eigenvalue equation or the eigenvalue problem. Furthermore, the columns UC1, UC2, ..., UCM of the resulting unitary eigenvector matrix U (i.e., the eigenvectors) are associated with the Nseigenvalues. Thus, each column (or eigenvector) of the resulting unitary eigenvector matrix is associated with (or has) a corresponding eigenvalue.

[0150] In some embodiments, the method 100 comprises obtaining one or more snapshots (SS) of the one or more radio (or FDM) signals (after conversion to digital signals by the converter units 900, 901, ..., 915) to obtain full channel information. Such snapshots may be obtained / taken every 10-20 milliseconds (ms). By utilizing the processing unit 1100 (or the FRU) described herein, the snapshot rate may be increased. By increasing the snapshot rate resolution / accuracy is improved / increased. In some embodiments, the processing unit 1100 (or the FRU) is configured to receive the one or more samples in the time domain more often than the spatio-temporal filter unit 1190 (e.g., twice or thrice as often).

[0151] List of examples (processor, WD and method thereof):

[0152] Example 1. A method (100) of obtaining a subset of frequency domain coefficients from a full bandwidth of one or more radio signals, the method comprising: receiving (110) by a wireless device, WD, (322, 323) the one or more radio signals from one or more remote transceiver nodes, TNodes, (396, 397, 398, 399), each radio signal comprising one or more samples in a time domain; assigning (120) each of the samples to one of two or more groups; and processing (128) the samples of the two or more groups by: calculating (135) a combined vector based on a function of the samples of the two or more groups; and transforming (145) the combined vector to obtain the subset of frequency domain coefficients; or by: transforming (130) each group of samples to obtain a frequency domain subvector for each group; and calculating (140) each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector. Example 2. The method of example 1, further comprising: derotating (115) each sample; and wherein assigning (120) each of the samples to one of two or more groups comprises assigning (125) each of the derotated samples to one of the two or more groups.

[0153] Example 3. The method of example 1 or example 2, wherein the subset of frequency domain coefficients is a frequency raster.

[0154] Example 4. The method of example 3, further comprising: receiving (113), by the WD (322, 323), frequency raster information from the remote TNode (397); and selecting (114), by the WD (322, 323), the frequency raster based on the frequency raster information.

[0155] Example 5. The method of example 4, further comprising: measuring (111), by the WD (322, 323), channel characteristics, such as a maximum delay spread; sending (112) a measurement report comprising the measured channel characteristics from the WD (322, 323) to a remote transceiver node, TNode, (397); and wherein the received frequency raster information is based on the measured channel characteristics.

[0156] Example 6. The method of any of examples 1-5, wherein the WD (322, 323) comprises a set of transceivers (500, 501, ..., 515) and a set of antenna units (700, 701, ..., 715), and wherein receiving (110) by the WD (322, 323) the one or more radio signals comprises receiving (112) the one or more radio signals by the set of transceivers (500, 501, ..., 515) via the set of antenna units (700, 701, ..., 715), and wherein the received one or more radio signals are converted to digital signals by a set of converter units (900, 901, ..., 915).

[0157] Example 7. The method of any of examples 1-6, wherein transforming (130, 145) comprises fast Fourier transforming, FFT, (132), such as Radix-2 FFT, or discrete Fourier transforming (134) and / or wherein calculating (140) each frequency domain coefficient of the subset comprises summing (142) all of the elements of the corresponding frequency domain subvector and / or wherein calculating (135) a combined vector comprises summing (142) all of the samples of the corresponding group.

[0158] Example 8. A computer program product comprising instructions, which, when executed on at least one processor of a processing device, cause the processing device to carry out the method of any of examples 1-7.

[0159] Example 9. A non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of a processing device, the one or more programs comprising instructions which, when executed by the processing device, causes the processing device to carry out the method according to any one of examples 1-7.

[0160] Example 10. A frequency raster unit (1100) comprisable by a wireless device, WD, (322, 323) and configured to: receive (1110) one or more radio signals from one or more remote transceiver nodes, TNodes, (396, 397, 398, 399), each radio signal comprising one or more samples in a time domain; assign (1120) each of the samples to one of two or more groups; and process (1128) the samples of the two or more groups by: calculating (1135) a combined vector based on a function of the samples of the two or more groups; and transforming (1145) the combined vector to obtain the subset of frequency domain coefficients; or by: transforming (1130) each group of samples to obtain a frequency domain subvector for each group; and calculating (1140) each frequency domain coefficient of only a subset of frequency domain coefficients from a full bandwidth of the one or more radio signals based on a function of the elements of the corresponding frequency domain subvector.

[0161] Example 11. A wireless device (322, 323), comprising: a digital interface chip, DIC, (320), the DIC (320) comprising a frequency raster unit, FRU, (1100) according to example 10; a channel analyzer, CA, (920); a BB processing unit (600); a set of transceivers (500, 501, ..., 515); and a set of antenna units (700, 701, ..., 715).

[0162] Example 12. The wireless device of example 11, wherein the DIC (320) comprises the CA (920) and a spatio-temporal filter unit (1190) having one or more output signals, wherein the CA (920) comprises a first estimation unit (922) and a processing unit (924), wherein the CA (920) is connectable to the FRU (1100), wherein the CA (920) is connectable to the spatiotemporal filter unit (1190), wherein the spatio-temporal filter unit (1190) is configured to receive the one or more samples, wherein the BB processing unit (600) is connectable to the DIC (320), wherein the first estimation unit (922) is configured to receive each frequency domain coefficient of the subset of frequency domain coefficients from the FRU (1100), wherein the first estimation unit (922) is configured to estimate two or more channel estimate matrices (Hl, H2, ..., HK) associated with one or more propagation channels for the one or more radio signals and provide the two or more channel estimate matrices (Hl, H2, ..., HK) to the processing unit (924), wherein the processing unit (924) is configured to provide spatiotemporal filter coefficients to the spatio-temporal filter unit (1190), and wherein the one or more output signals of the spatio-temporal filter unit (1190) are fewer than the number of antennas of the set of antenna units (700, 701, ..., 715), thereby reducing the number of antenna streams to be feed, by the DIC (320) to the BB processing unit (600). List of examples (TNode and method thereof):

[0163] Example 21. A method (2100) for configuring a frequency domain pilot pattern for communication between a remote transceiver node, TNode, (397) and a wireless device, WD, (322, 323), the method comprising: obtaining (2110), by the TNode (397), one or more channel characteristics for a channel between the Tnode (397) and the WD (322, 323). obtaining (2120), by the TNode (397), a frequency domain pilot pattern based on the obtained one or more channel characteristics; and transmitting (2130), by the TNode (397), pilot configuration information to the WD (322, 323), wherein the pilot configuration information comprises information associated with the obtained frequency domain pilot pattern.

[0164] Example 22. The method of example 21, wherein the pilot pattern is on a frequency raster.

[0165] Example 23. The method of example 21 or example 22, wherein obtaining (2110), by the TNode (397), one or more channel characteristics for a channel between a the Tnode (397) and the WD (322, 323) is based on a received signal, such as a pilot signal, transmitted from the WD (322, 323).

[0166] Example 24. The method of example 21 or example 22, wherein obtaining (2110), by the TNode (397), one or more channel characteristics for a channel between a the Tnode (397) and the WD (322, 323) is based on a received measurement report from the WD (322, 323).

[0167] Example 25. The method of any of examples 21-24, wherein the pilot configuration information is transmitted on one or more of a radio resource control, RRC, layer, a media access, MAC, layer, and a physical, PHY, layer.

[0168] Example 26 The method of any of examples 21-24, wherein the channel characteristics comprises a maximum delay spread of the channel between the Tnode (397) and the WD (322, 323).

[0169] Example 27. A computer program product comprising instructions, which, when executed on at least one processor of a processing device, cause the processing device to carry out the method of any of examples 21-26. Example 28. A non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of a processing device, the one or more programs comprising instructions which, when executed by the processing device, causes the processing device to carry out the method according to any one of examples 21-26.

[0170] Example 29. A transceiver node, TNode, (397) of a system (999), the system comprising one or more TNodes (395, 396, 397, 398) and one or more wireless devices, WDs, (322, 323, ..., 328), the TNode (397) configured to: obtain (2210) one or more channel characteristics for a channel between the Tnode (397) and one of the WDs (322, 323). obtain (2220) a frequency domain pilot pattern based on the obtained one or more channel characteristics; and transmit (2230) pilot configuration information to the WD (322, 323), wherein the pilot configuration information comprises information associated with the obtained frequency domain pilot pattern.

[0171] Generally, all terms used herein are to be interpreted according to their ordinary meaning in the relevant technical field, unless a different meaning is clearly given and / or is implied from the context in which it is used. Reference has been made herein to various embodiments. However, a person skilled in the art would recognize numerous variations to the described embodiments that would still fall within the scope of the claims. For example, the method embodiments described herein discloses example methods through steps being performed in a certain order. However, it is recognized that these sequences of events may take place in another order without departing from the scope of the claims. Furthermore, some actions / method steps may be performed in parallel even though they have been described as being performed in sequence. Thus, the steps of any methods disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step and / or where it is implicit that a step must follow or precede another step. In the same manner, it should be noted that in the description of embodiments, the partition of functional blocks into particular units is by no means intended as limiting. Contrarily, these partitions are merely examples. Functional blocks described herein as one unit may be split into two or more units. Furthermore, functional blocks described herein as being implemented as two or more units may be merged into fewer e.g., a single) unit. Any feature of any of the embodiments / aspects disclosed herein may be applied to any other embodiment / aspect, wherever suitable. Likewise, any advantage of any of the embodiments may apply to any other embodiments, and vice versa. Hence, it should be understood that the details of the described embodiments are merely examples brought forward for illustrative purposes, and that all variations that fall within the scope of the claims are intended to be embraced therein.

[0172] List of some acronyms and abbreviations that may appear in the description

[0173] 3GPP - 3rd Generation Partnership Project

[0174] 5G - fifth generation

[0175] 5G - NR (5G - New Radio) is a new RAT developed by 3GPP for the 5G mobile network

[0176] ADC - analog-to-digital converter

[0177] AGC - automatic gain controller

[0178] BB - baseband

[0179] BF - beamforming

[0180] BW - bandwidth

[0181] BWP - bandwidth part emW - centimetre Wave

[0182] CSI-RS - channel state information reference signal

[0183] CU - control unit

[0184] DAC - digital-to-analog converter

[0185] DCI - downlink control information

[0186] DIC - Digital Interface Chip

[0187] DL-PRS - downlink positioning reference signal

[0188] DM-RS - demodulation reference signal

[0189] DS - down-sampling

[0190] FDM - frequency-division multiplexing

[0191] FFT - Fast Fourier Transform

[0192] FR1 - Frequency Range 1 FR1.5 - Frequency Range 1.5

[0193] FR2 - Frequency Range 2

[0194] Fe - Front end

[0195] FWA - Fixed Wireless Access

[0196] GNSS - Global navigation satellite system

[0197] GPS - Global Positioning System

[0198] IF - intermediate frequency

[0199] IFFT - Inverse Fast Fourier Transform

[0200] I / O - input / output

[0201] LI - Layer 1

[0202] LNA - Low Noise Amplifier

[0203] LO - Local Oscillator

[0204] LoS - Line of Sight

[0205] LTE - Long-Term Evolution

[0206] MAC - Medium Access Control

[0207] MATARA - multi-antenna transmitter and receiver arrangement

[0208] MIMO - multiple input, multiple output

[0209] MMSE - Minimum Mean Squared Error mmW - millimetre wave

[0210] MRC - maximum ratio combining

[0211] NAS - Non-access Stratum nLoS - non-Line of Sight NRX - Number of received signals

[0212] NS - Number of Streams

[0213] NTX - Number of transmitting ports

[0214] OFDM - orthogonal frequency-division multiplexing

[0215] PA - power amplifier

[0216] PBCH - Physical Broadcast Channel

[0217] PCB - printed circuit board

[0218] PCell - primary cell

[0219] PDCCH - physical downlink control channel

[0220] PDP - Power delay profile

[0221] PDSCH - physical downlink shared channel

[0222] PHY - Physical Layer

[0223] PLL - phase locked loop

[0224] PSCell - primary secondary cell

[0225] PSS - primary synchronization signal

[0226] PT-RS - Phase Tracking Reference signal

[0227] PUCCH - physical uplink control channel

[0228] PUSCH - physical uplink shared channel

[0229] QCL - quasi co-located

[0230] QoS - quality of service

[0231] RAT - radio access technology

[0232] RRC - radio resource control RSRP - Reference Signal Received Power

[0233] RSRQ - Reference Signal Received Quality

[0234] RSSI - Received Signal Strength Indicator

[0235] SCell - Secondary Cell SNR - Signal-to-noise ratio

[0236] SSB - Synchronization Signal Block

[0237] SRS - sounding reference signal

[0238] SSS - secondary synchronization signal

[0239] STEF - spatio-temporal filter STF - spatial transmission filter

[0240] TCI - Transmission Configuration Indicator

[0241] TNode - transceiver node

[0242] VGA - variable gain amplifier

[0243] WD - wireless device

Claims

CLAIMS1. A processing unit comprisable by a wireless device, WD, (322, 323) and configured to: receive (1110) from a remote transceiver node, TNode, (396, 397, 398, 399) a full bandwidth of a radio signal comprising two or more samples in a time domain, or from each of two or more remote TNodes (396, 397, 398, 399) a full bandwidth of a radio signal, each radio signal comprising one or more samples in a time domain; assign (1120) to each of two or more groups a respective subset of the two or more samples, wherein the respective subsets are non-overlapping subsets; and process (1128) the samples of the two or more groups to obtain a subset of a full set of frequency domain coefficients by: calculating (1135) a combined vector based on a function of the samples of the two or more groups, and transforming (1145) the combined vector to obtain the subset of frequency domain coefficients; or by: transforming (1130) each group of samples to obtain only a frequency domain subvector for each group, and calculating (1140) each frequency domain coefficient of only the subset of frequency domain coefficients based on a function of the elements of the corresponding frequency domain subvector.

2. The processor of claim 1, further configured to: derotate (1115) each sample; and assign (1125) to each of the two or more groups a respective subset of the two or more derotated samples.

3. The processing unit of claim 1 or claim 2, wherein the processing unit (1100) is a frequency raster unit, FRU, and wherein the subset of frequency domain coefficients is a frequency raster.

4. The processing unit of claim 3, wherein transforming (1130) each group of samples to obtain a frequency domain subvector for each group comprises fast Fourier transforming, FFT, (1132), such as Radix-2 FFT, or discrete Fourier transforming (1134), or wherein transforming (1145) the combined vector to obtain the subset of frequency domain coefficients comprises fast Fourier transforming, FFT, (1146), such as Radix-2 FFT, or discrete Fourier transforming (1147).

5. The processing unit of any of claims 3-4, wherein calculating (1140) each frequency domain coefficient of the subset comprises summing (1142) all of the elements of the corresponding frequency domain subvector.

6. The processing unit of any of claims 3-5, wherein calculating (1135) a combined vector comprises summing all of the samples of the corresponding group.

7. A wireless device, WD, (322, 323), comprising: a digital interface chip, DIC, (320), the DIG (320) comprising a processing unit (1100) according to any of claims 3-6; a channel analyzer, CA, (920); a BB processing unit (600); a set of transceivers (500, 501, ..., 515); and a set of antenna units (700, 701, ..., 715).

8. The WD of claim 7, configured to: receive frequency raster information from one of the TNodes (397); and select a frequency raster based on the frequency raster information; and instruct the processing unit (1100) to process (1128) the samples of the two or more groups to obtain the subset of frequency domain coefficients in accordance with the selected frequency raster.

9. The WD of claim 8, configured to: measure channel characteristics, such as a maximum delay spread;send a measurement report comprising the measured channel characteristics to theTNode (397); and wherein the received frequency raster information is based on the measured channel characteristics.

10. The wireless device of claim 9, wherein the DIG (320) comprises the CA (920) and a spatio-temporal filter unit (1190) having one or more output signals, wherein the CA (920) comprises a first estimation unit (922) and a processing unit (924), wherein the CA (920) is connected to the processing unit (1100), wherein the CA (920) is connected to the spatiotemporal filter unit (1190), wherein the spatio-temporal filter unit (1190) is configured to receive the one or more samples, wherein the BB processing unit (600) is connected to the DIC (320), wherein the first estimation unit (922) is configured to receive each frequency domain coefficient of the subset of frequency domain coefficients from the processing unit (1100), wherein the first estimation unit (922) is configured to estimate two or more channel estimate matrices (Hl, H2, ..., HK) associated with one or more propagation channels for the one or more radio signals and provide the two or more channel estimate matrices (Hl, H2, ..., HK) to the processing unit (924), wherein the processing unit (924) is configured to provide spatiotemporal filter coefficients to the spatio-temporal filter unit (1190), and wherein the one or more output signals of the spatio-temporal filter unit (1190) are fewer than the number of antennas of the set of antenna units (700, 701, ..., 715), thereby reducing the number of antenna streams to be feed, by the DIC (320) to the BB processing unit (600).

11. A method (100) of obtaining a subset of frequency domain coefficients from a full bandwidth of one or more radio signals, the method comprising: receiving (110) by a wireless device, WD, (322, 323) from a remote transceiver node, TNode, (396, 397, 398, 399) a full bandwidth of a radio signal comprising two or more samples in a time domain, or from each of two or more remote TNodes (396, 397, 398, 399) a full bandwidth of a radio signal, each radio signal comprising one or more samples in a time domain; assigning (120) to each of two or more groups a respective subset of the two or more samples, wherein the respective subsets are non-overlapping subsets; and processing (128) the samples of the two or more groups by:calculating (135) a combined vector based on a function of the samples of the two or more groups, and transforming (145) the combined vector to obtain the subset of frequency domain coefficients; or by: transforming (130) each group of samples to obtain a frequency domain subvector for each group, and calculating (140) each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector.

12. The method of claim 11, further comprising: derotating (115) each sample; and wherein assigning (120) to each of two or more groups a respective subset of the two or more samples comprises assigning (125) to each of the two or more groups a respective subset of the two or more derotated samples.

13. The method of claim 11 or claim 12, wherein the subset of frequency domain coefficients is a frequency raster.

14. The method of claim 13, further comprising: receiving (113), by the WD (322, 323), frequency raster information from the remote TNode (397); and selecting (114), by the WD (322, 323), the frequency raster based on the frequency raster information.

15. The method of claim 14, further comprising: measuring (111), by the WD (322, 323), channel characteristics, such as a maximum delay spread; sending (112) a measurement report comprising the measured channel characteristics from the WD (322, 323) to a remote transceiver node, TNode, (397); andwherein the received frequency raster information is based on the measured channel characteristics.

16. The method of any of claims 11-15, wherein the WD (322, 323) comprises a set of transceivers (500, 501, ..., 515) and a set of antenna units (700, 701, ..., 715), and wherein receiving (110) by the WD (322, 323) the one or more radio signals comprises receiving (112) the one or more radio signals by the set of transceivers (500, 501, ..., 515) via the set of antenna units (700, 701, ..., 715), and wherein the received one or more radio signals are converted to digital signals by a set of converter units (900, 901, ..., 915).

17. The method of any of claims 11-16, wherein transforming (130, 145) comprises fast Fourier transforming, FFT, (132), such as Radix-2 FFT, or discrete Fourier transforming (134) or wherein calculating (140) each frequency domain coefficient of the subset comprises summing (142) all of the elements of the corresponding frequency domain subvector or wherein calculating (135) a combined vector comprises summing (136) all of the samples of the corresponding group.

18. The method of any of claims 11-17, wherein transforming (130) each group of samples to obtain a frequency domain subvector for each group is performed without obtaining any elements of a full frequency domain vector not belonging to the frequency domain subvector, and / or wherein calculating (140) each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector is performed without calculating any frequency domain coefficients of the full set of frequency domain coefficients other than the frequency domain coefficients of the subset.

19. The method of any of claims 11-17, wherein transforming (130) each group of samples to obtain a frequency domain subvector for each group consists of transforming each group of samples to obtain only a frequency domain subvector for each group and / or wherein calculating (140) each frequency domain coefficient of the subset based on a function of the elements of the corresponding frequency domain subvector consists of calculating each frequency domain coefficient of only the subset based on a function of the elements of the corresponding frequency domain subvector.

20. A computer program product comprising instructions, which, when executed on at least one processor of a processing device, cause the processing device to carry out the method of any of claims 11-19.

21. A non-transitory computer-readable storage medium storing one or more programs configured to be executed by one or more processors of a processing device, the one or more programs comprising instructions which, when executed by the processing device, causes the processing device to carry out the method according to any one of claims 11-19.

Images