WO2018124950A1 - Rétroaction de corrélation de canal dans un système de communication sans fil - Google Patents

Rétroaction de corrélation de canal dans un système de communication sans fil Download PDF

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Publication number
WO2018124950A1
WO2018124950A1 PCT/SE2016/051321 SE2016051321W WO2018124950A1 WO 2018124950 A1 WO2018124950 A1 WO 2018124950A1 SE 2016051321 W SE2016051321 W SE 2016051321W WO 2018124950 A1 WO2018124950 A1 WO 2018124950A1
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WIPO (PCT)
Prior art keywords
channel correlation
coefficients
subset
correlation matrix
radio node
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PCT/SE2016/051321
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English (en)
Inventor
Sebastian FAXÉR
Svante Bergman
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Telefonaktiebolaget Lm Ericsson (Publ)
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Priority to PCT/SE2016/051321 priority Critical patent/WO2018124950A1/fr
Publication of WO2018124950A1 publication Critical patent/WO2018124950A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0634—Antenna weights or vector/matrix coefficients
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0658—Feedback reduction

Definitions

  • the present application relates generally to a wireless communication system, and more particularly relates to channel correlation feedback in such a system.
  • Precoding a transmission from a transmit antenna array involves applying a set of complex weights to the signals that are to be transmitted from the array's antenna elements, so as to independently control the signals' phase and/or amplitude.
  • This set of complex weights is referred to as a "precoder" or "precoding matrix”.
  • the transmitting radio node conventionally chooses the precoder to match the current channel conditions on the link to the receiving radio node, with the aim of maximizing the link capacity or quality. If multiple data streams are simultaneously transmitted from the array's antenna elements using spatial multiplexing, the transmitting radio node also typically chooses the precoder with the aim of orthogonalizing the channel and reducing inter-stream interference at the receiving radio node.
  • the transmitting radio node selects the precoder based on channel state information (CSI) fed back from the receiving radio node that characterizes the current channel conditions.
  • CSI channel state information
  • the transmitting radio node in this regard transmits a reference signal from each antenna element to the receiving radio node, and the receiving radio node sends back CSI based on measurement of those reference signals.
  • Transmission of the CSI feedback contributes significant overhead to precoding schemes. For example, CSI feedback consumes a significant amount of transmission resources (e.g., time-frequency resource elements in Long Term Evolution, LTE, embodiments).
  • Known approaches reduce overhead attributable to CSI feedback by limiting the usable precoders to a fixed set of precoders, i.e., a codebook.
  • Each precoder in the codebook is assigned a unique index that is known to both the transmitting node and the receiving node.
  • the receiving node determines the "best" precoder from the codebook, and feeds back the index of that precoder (often referred to as a "precoding matrix indicator", PMI) to the transmitting node as a recommendation (which the transmitting node may or may not follow).
  • Feeding back only an index, in conjunction with other CSI such as the recommended number of data streams (i.e., transmission rank) for spatial multiplexing, reduces the number of transmission resources required for transporting that CSI. This approach therefore reduces CSI feedback overhead considerably.
  • codebook-based precoding generally offers good performance for a reasonable degree of feedback overhead, it may not be flexible enough for some transmission schemes, such as multi-user multiple-input multiple-output (MIMO) and coordinated beamforming. In these cases, the optimal precoding depends on the channel matrices of other receiving nodes that the transmitting node aims to form a null against.
  • MIMO multi-user multiple-input multiple-output
  • coordinated beamforming In these cases, the optimal precoding depends on the channel matrices of other receiving nodes that the transmitting node aims to form a null against.
  • the receiving radio node may send channel correlation feedback which characterizes channel correlation between the transmit antenna array's antenna elements.
  • This feedback may take the form of a channel correlation matrix.
  • channel correlation feedback may impose a lower feedback overhead than feedback of explicit channel matrices, the overhead required to signal the channel correlation matrix's coefficients may still be too high for some applications, especially for a large transmit antenna array.
  • a radio node that receives a transmission from a transmit antenna array feeds back information characterizing channel correlation between the array's antenna elements. Rather than feeding back all coefficients of a channel correlation matrix for the array, though, the radio node feeds back a subset of those coefficients. This subset may include, for example, one coefficient per antenna element separation distance associated with the array. Feeding back such a reduced subset of coefficients proves advantageous in some contexts for reducing signaling overhead, even for large antenna arrays.
  • embodiments include a method performed by a radio node.
  • the method comprises measuring one or more reference signals transmitted from antenna elements of a transmit antenna array.
  • the method also comprises determining a subset of coefficients of a channel correlation matrix that characterizes channel correlation between two or more of the antenna elements of the transmit antenna array according to the measuring.
  • the subset includes, for each of one or more antenna element separation distances, a coefficient from which is derivable channel correlation between any of the two or more antenna elements that are separated by that distance.
  • the method further comprises transmitting the subset of coefficients as channel correlation feedback that parameterizes the channel correlation matrix.
  • determining the subset of coefficients comprises, based on the measuring, calculating an averaged correlation matrix that characterizes channel correlation between the two or more of the antenna elements of the transmit antenna array as averaged over a certain time interval and a certain frequency interval.
  • determining the subset may also comprise, for each of the two or more antenna element separation distances, calculating the coefficient to include in the subset for that distance as an average across coefficients in the averaged correlation matrix that characterize channel correlation between antenna elements that are separated by that distance.
  • Embodiments herein also include a corresponding method performed by another radio node.
  • the method comprises receiving a subset of coefficients of a channel correlation matrix as channel correlation feedback that parameterizes the channel correlation matrix.
  • the channel correlation matrix characterizes channel correlation between two or more antenna elements of a transmit antenna array from which one or more reference signals were transmitted.
  • the subset includes, for each of one or more antenna element separation distances, a coefficient from which is derivable channel correlation between any of the two or more antenna elements that are separated by that distance.
  • the method also comprises reconstructing the channel correlation matrix using the received subset of coefficients.
  • this method further comprises precoding a transmission from the transmit antenna array based on the reconstructed channel correlation matrix, and transmitting the precoded transmission.
  • the channel correlation matrix may be a Toeplitz matrix.
  • the subset of coefficients may comprise Toeplitz coefficients of the channel correlation matrix.
  • the channel correlation matrix may characterize channel correlation, in a certain spatial dimension of the transmit antenna array, between N antenna elements of the transmit antenna array, and the subset of coefficients may comprise N coefficients or N-1 coefficients.
  • the channel correlation matrix may characterize channel correlation between N antenna elements in a certain spatial dimension of the transmit antenna array.
  • the one or more antenna element separation distances may comprise N antenna element separation distances or N-1 antenna element separation distances.
  • the channel correlation matrix characterizes channel correlation, in multiple spatial dimensions of the transmit antenna array, between N*M antenna elements of the transmit antenna array.
  • the subset of coefficients comprises less than N 2 *M 2 coefficients
  • the transmit antenna array has N antenna elements in one of the multiple spatial dimensions and has M antenna elements in another one of the multiple spatial dimensions
  • each of the one or more antenna element separation distances comprises a separation distances between antenna elements in the multiple spatial dimensions of the transmit antenna array.
  • the subset of coefficients comprises 2NM - N - M + 1 coefficients.
  • the channel correlation matrix may characterize channel correlation between antenna elements with a certain polarization relation.
  • the channel correlation matrix may characterize channel correlation between the two or more of the antenna elements of the transmit antenna array as averaged over a certain time interval and a certain frequency interval.
  • the certain time interval and the certain frequency interval are greater than a channel coherence time and a channel coherence bandwidth, respectively.
  • the antenna elements of the transmit antenna array may be virtual antenna elements.
  • an antenna element may correspond to an antenna port.
  • a separation distance between antenna elements may be a distance between phase centers of antenna ports corresponding to those antenna elements.
  • either method may be performed by a radio node that comprises either a wireless communication device or a base station.
  • Embodiments herein also include corresponding radio nodes, computer programs, carriers, and computer-readable storage mediums.
  • Figure 1 is a block diagram of a wireless communication system according to one or more embodiments.
  • Figure 2 is a combined logic flow diagram for processing performed by radio nodes according to some embodiments.
  • Figure 3 is a logic flow diagram for processing performed by a radio node for determining a subset of coefficients according to one or more embodiments.
  • Figure 4 is a logic flow diagram for processing performed by a radio node for determining a subset of coefficients according to one or more other embodiments.
  • Figure 5 is a logic flow diagram for processing performed by a radio node for determining a subset of coefficients according to still one or more other embodiments.
  • Figure 6 is a logic flow diagram for processing performed by a radio node for determining a subset of coefficients according to yet other embodiments.
  • Figures 7A-7B are block diagrams of a transmit antenna array, notated with arrows indicating correlations taken between antenna element pairs of the array according to some embodiments.
  • Figures 8A-8C are block diagrams of a transmit antenna array, notated with arrows indicating antenna element pairs or combinations with the same antenna element separation distance.
  • Figures 9A-9C are block diagrams of a transmit antenna array, notated with circles indicating antenna element pairs or combinations with the same antenna element separation distance.
  • Figure 10 is a logic flow diagram of a method performed by a radio node for transmitting channel correlation feedback according to some embodiments herein.
  • Figure 11 is a logic flow diagram of a method performed by a radio node for receiving channel correlation feedback according to some embodiments herein.
  • Figure 12 is a logic flow diagram of a method performed by a radio node for transmitting channel correlation feedback according to other embodiments herein.
  • Figure 13 is a logic flow diagram of a method performed by a radio node for receiving channel correlation feedback according to other embodiments herein.
  • Figure 14 is a logic flow diagram of a method performed by a radio node for transmitting channel correlation feedback according to still other embodiments herein.
  • Figure 15 is a logic flow diagram of a method performed by a radio node for receiving channel correlation feedback according to still other embodiments herein.
  • Figure 16 is a block diagram of a radio node for transmitting channel correlation feedback according to some embodiments herein.
  • Figure 17 is a block diagram of a radio node for transmitting channel correlation feedback according to other embodiments herein.
  • Figure 18 is a block diagram of a radio node for receiving channel correlation feedback according to some embodiments herein.
  • Figure 19 is a block diagram of a radio node for receiving channel correlation feedback according to other embodiments herein.
  • Figure 1 illustrates a wireless communication system 10 according to one or more embodiments.
  • the system 10 includes a radio node 12, shown in the form of a base station, that performs transmissions via a transmit antenna array 14.
  • the array 14 has multiple antenna elements arranged in one or more spatial dimensions.
  • Figure 1 for example shows the array 14 as including four antenna elements arranged horizontally in a row with indices 0, 1 , 2, and 3, at least with respect to one spatial dimension of the array 14.
  • the radio node 12 may perform a transmission via the array 14 by feeding one or more signals of the transmission to one or more antenna elements of the array 14, respectively.
  • the radio node 12 in some embodiments independently controls the amplitude and/or phase of the signal(s) fed to the array's antenna element(s), as part of precoding the transmission from the array 14.
  • the radio node 12 may precode a transmission from the array 14, or perform other processing, based on feedback that the radio node 12 receives describing the radio channel between the array 14 and another radio node 16 in the system 14 (shown in Figure 1 as a user equipment, UE). Towards this end, the radio node 12 in some embodiments transmits one or more reference signals 18 from antenna elements of the transmit antenna array 14.
  • the reference signal(s) 18 may for instance comprise one or more channel state information reference signals (CSI-RS), which may be transmitted periodically (e.g., every 5ms in time and every physical resource block, PRB, in frequency).
  • CSI-RS channel state information reference signals
  • radio node 16 measures the reference signal(s) 18 as received from the array's antenna elements, and transmits feedback 20 that describes the radio channel according to that measurement.
  • the feedback 20 herein constitutes channel correlation feedback which describes the radio channel in terms of channel correlation between two or more (e.g., some or all) of the antenna elements of the transmit antenna array 14. That is, the feedback 20 indicates the extent to which the radio channel associated with one antenna element is correlated with the radio channel associated with another antenna element.
  • the feedback 20 signals that channel correlation between two or more of the transmit antenna array's antenna elements is described by a channel correlation matrix R .
  • Different coefficients of the channel correlation matrix R characterize channel correlation between different pairs of antenna elements.
  • the channel correlation coefficient R Q L as shown characterizes channel correlation between antenna element 0 and antenna element 1
  • the channel correlation coefficient R 2 3 characterizes channel correlation between antenna element 2 and antenna element 3.
  • Some coefficients on the diagonal may characterize channel correlation between a pair of antenna elements in which the elements in the pair are the same. Such a coefficient therefore describes the self-correlation associated with a certain antenna element.
  • coefficient R Q 0 characterizes the channel correlation between antenna element 0 and itself, i.e., the self-correlation of antenna element 0.
  • the radio node 16 transmits a subset of those coefficients as the channel correlation feedback 20.
  • This subset of coefficients effectively compresses or parameterizes the channel correlation matrix R , in a way that enables the channel correlation matrix R to be reconstructed from that subset of coefficients. Feeding back a subset of the coefficients advantageously requires reduced signaling overhead as compared to feeding back the entire set of coefficients of the channel correlation matrix R , yet still allows the entire matrix R to be reconstructed.
  • the radio node 12 receives this "compressed" feedback 20, for instance, that radio node 12 may reconstruct the channel correlation matrix R using the received subset of coefficients.
  • the feedback 20 effectively signals the channel correlation matrix R by signaling only a subset of the matrix's coefficients, rather than all of the coefficients.
  • the radio node 12 in some embodiments may then precode a transmission 22 from the transmit antenna array 14 based on the reconstructed channel correlation matrix, and transmit that precoded transmission 22.
  • FIG. 2 generally summarizes processing by the radio nodes 12, 16 in this regard.
  • radio node 12 may transmit the one or more reference signals 18 from a transmit antenna array 14 (Step 100).
  • Radio node 16 measures these one or more reference signals 18 (Step 1 10).
  • Radio node 16 determines a subset of coefficients of a channel correlation matrix R according to that measurement (Step 120), and transmits that subset of coefficients to the radio node 12 (Step 130). That is, based on the reference signal measurement, the radio node 16 may determine to signal the channel correlation matrix R as characterizing channel correlation between the array's antenna elements.
  • the radio node 16 signals only a subset of the matrix's coefficients, e.g., on a feedback channel, such as a physical uplink shared channel (PUSCH) or physical uplink control channel (PUCCH) in Long Term Evolution (LTE) embodiments.
  • Radio node 12 uses this signaled subset of coefficients to reconstruct the channel correlation matrix R (Step 140).
  • Radio node 12 in some embodiments may then precode a transmission (e.g., of user data) based on the reconstructed channel correlation matrix R (Step 150).
  • the subset of coefficients fed back includes a coefficient for each of one or more groups of antenna element pairs. Each such group may include multiple antenna element pairs.
  • the radio node 16 may group together multiple antenna element pairs and feed back a single coefficient for that group, rather than feeding back multiple coefficients for respective ones of those pairs in the group.
  • the radio node 16 may for instance group together antenna element pairs whose channel correlation coefficients are derivable from one another, e.g., via a predefined derivation formula, process, or other operation. In this case, channel correlation between any antenna element pair within the group may be derivable from the coefficient which is fed back for that group.
  • the antenna element pairs within any given group may have approximately the same relative element separation distance. That is, the antenna elements in each pair within a group may be separated from one another by approximately the same distance.
  • the subset of coefficients fed back may include a coefficient for each of one or more antenna element separation distances.
  • the one or more antenna element separation distances may include one or more of the distances by which antenna elements in the transmit antenna array 14 are separable. Channel correlation between any antenna elements that are separated by a certain distance may be derivable from the coefficient fed back for that distance. Such embodiments may thereby exploit the
  • the antenna element separation distances by which antenna elements in the transmit antenna array 14 are separable include distances dO, d1 , d2, and d3.
  • each antenna element 0, 1 , 2, and 3 is separated from itself by a distance of dO.
  • Antenna element 0 is separated from antenna element 1 by a distance of d1 , from antenna element 2 by a distance of d2, and from antenna element 3 by a distance of d3.
  • antenna element 1 is separated from antenna element 0 by a distance of d1 , from antenna element 2 by a distance of d1 , and from antenna element 3 by a distance of d2.
  • the transmit antenna array 14 in this example is a uniform array, at least in the one spatial dimension shown.
  • the subset of coefficients fed back may include a coefficient for each of one or more of the antenna element separation distances dO, d1 , d2, and d3.
  • Figure 1 shows that the radio node 16 transmits as channel correlation feedback 20 a subset 24 of coefficients that includes a single coefficient for each of the antenna element separation distances dO, d1 , d2, and d3. Indeed, as shown, coefficients
  • R 0 1 , R 1 0 , R 1 2 , R 2 1 , R 2 3 , and R 3 2 characterize channel correlation between antenna elements that are separated by distance d1 , i.e., these coefficients are associated with distance dl Rather than feeding back all of those coefficients, the radio node 16 includes a single one of them (labeled non-specifically asR # # ) in the subset 24 of coefficients to be fed back.
  • the radio node 16 may for instance include R Q L in the subset 24 of coefficients to be fed back, to the exclusion of other coefficients associated with distance d1.
  • the rest of those coefficients which are not fed back for distance d1 may be derivable from the one coefficient that is fed back for distance d!
  • the radio node 16 feeds back a single one of the coefficients
  • R 0 2 , R 2 0 , R l 3 , and R 3 1 that characterize channel correlation between antenna elements that are separated by distance d2, and feeds back a single one of the coefficients R Q 3 and R 3 0 that characterize channel correlation between antenna elements that are separated by distance d3.
  • the radio node 16 as shown in Figure 1 may also feed back a single one of the coefficients R Q 0 , R l l , R 2 2 , and R 3 3 that characterize channel correlation between antenna elements that are separated by a distance dO.
  • the radio node 16 may not feed back any coefficient that characterizes channel correlation between antenna elements that are separated by a distance dO.
  • distance dO corresponds to self- correlation between antenna elements, for instance, such self-correlation may reflect the channel power associated with the antenna elements.
  • this self- correlation coefficient may be represented in separate feedback (e.g., indicating signal or channel quality), rather than in the channel correlation feedback 20.
  • the coefficients of the channel correlation matrix R may be normalized with the self-correlation coefficients, such that the matrix's self-correlation coefficients on the diagonal need not be fed back.
  • the radio node 16 in at least some embodiments herein forms the subset 24 of coefficients to feed back, as part of exploiting certain structural properties that the channel correlation matrix R has or is assumed to have. These structural properties make it to where coefficients associated with the same antenna element separation distance are derivable from one another.
  • the channel correlation matrix R is a Hermitian Toeplitz matrix.
  • a Hermitian matrix is a matrix that is equal to its own conjugate transpose, such that the element in the i-th row and j-th column is equal to the complex conjugate of the element in the j-th row and the i-th column, for all indices I and j.
  • a Toeplitz matrix (also known as a diagonal-constant matrix) is a matrix in which each descending diagonal from left to right is constant.
  • the channel correlation matrix R for the antenna array 14 shown in Figure 1 may be written as:
  • coefficients that are equal to one another, or are complex conjugates of one another characterize channel correlation between antenna elements that are separated by the same distance.
  • the coefficients R 0 3 and R 3 0 that are complex conjugates of one another both characterize channel correlation between antenna elements separated by a distance of d3.
  • any coefficient that characterizes channel correlation between antenna elements separated by a certain distance is derivable from another of the coefficients that also characterizes channel correlation between antenna elements separated by that same distance.
  • the coefficients associated with the same antenna element separation distance are derivable from one another.
  • the coefficient R 3 1 is derivable from the coefficient R 0 2 via a complex conjugate operation, i.e.,
  • the matrix R may equivalently be written as: where R(x) denotes a channel correlation coefficient for separation distance x .
  • R(x) denotes a channel correlation coefficient for separation distance x .
  • R(0),R(1),R(2),R(3) in the first row of R i.e., one coefficient for each separation distance x .
  • This simple example may be generalized to a channel coefficient matrix R of any size, for any number N of antenna elements in the transmit antenna array 14, by writing the matrix R as:
  • the radio node 16 forms the subset 24 of coefficients to include Toeplitz coefficients of the channel correlation matrix R .
  • the subset 24 may include for instance all N Toeplitz coefficients R(0),R(1), ..., R(N - 1) of the channel correlation matrix R .
  • the subset 24 may include N - l Toeplitz coefficients of the channel correlation matrix R , such asR(l), ..., R(N - l) (e.g., if R(0) represents channel power and is fed back separately apart from channel correlation feedback).
  • the subset 24 may include all conjugated versions of the Toeplitz coefficients, or a mix of both one or more non-conjugated Toeplitz coefficients and one or more conjugated Toeplitz coefficients.
  • the subset 24 may include for instance R(l) , but include R(2) * rather than R(2) .
  • the radio node 16 may determine the subset 24 of coefficients to feed back (e.g., in Step 120 of Figure 2) in any number of ways.
  • Figures 3-6 illustrate a few exemplary embodiments in this regard.
  • the radio node 16 may first estimate an instantaneous channel matrix H t f based on measurement of the one or more reference signals (Block 200).
  • the radio node 16 may for instance measure the one or more reference signals as received in a certain time resource t (e.g., subframe) and frequency resource / (e.g., resource block), and use those measurements to form an estimate of the instantaneous channel matrix H t f .
  • the radio node 16 may then calculate the channel correlation matrix R to be signaled as being an instantaneous channel correlation matrix R t f formed from the instantaneous channel matrix
  • the radio node 16 may for instance calculate the channel correlation matrix
  • the instantaneous channel correlation matrix R t f itself has the certain structural properties described above that make it to where coefficients associated with the same antenna element separation distance are derivable from one another. This may be the case for instance for a pure line-of-sight channel between the transmit antenna array 14 and the radio node 16.
  • the instantaneous channel correlation matrix R t f may not actually have the certain structural properties described above. In this case, coefficients in R t f that are associated with the same antenna element separation distance may not be derivable from one another. These circumstances may exist for certain types of channel s, e.g., a general propagation channel that may not be pure line-of-sight.
  • Figure 4 illustrates an alternative approach for the radio node 16 to determine the subset 24 of coefficients to feed back.
  • the radio node 16 calculates the channel correlation matrix R to be signaled as being an averaged channel correlation matrix R , rather than an instantaneous channel correlation matrixR ⁇ (Block 300).
  • This averaged channel correlation matrix R may characterize channel correlation between antenna elements of the array 14 as averaged over a certain time interval At and frequency interval Af (e.g., an interval of time resources and an interval of frequency resources).
  • the radio node 16 in some embodiments is preconfigured with or autonomously determines a certain time interval At and frequency interval Af over which to perform averaging. In other embodiments, though, the radio node 16 may be dynamically or semi-statically configured, e.g., via measurement restriction signaling, by radio node 12 or some other node with the particular time interval At and frequency interval Af to use for averaging.
  • averaging channel correlation over time and frequency in this way may infuse the structural properties described above into the averaged channel correlation matrix R , despite the instantaneous channel correlation matrixR ⁇ not having those structural properties. Indeed, the longer the instantaneous channel correlation matrixi ⁇ f is averaged over time and frequency, the closer the resulting averaged channel correlation matrix R comes to having the structural properties described, e.g., the closer the coefficients associated with the same antenna element separation distance come to being equivalent to one another, complex conjugates of one another, or otherwise derivable from one another.
  • the radio node 16 averages channel correlation over a time interval and frequency interval that are greater than the channel coherence time and channel coherence bandwidth, respectively.
  • the averaged channel correlation matrix R may not have the certain structural properties described above that make it to where coefficients associated with the same antenna element separation distance are derivable from one another. For example, practical limitations on the time interval and/or frequency interval over which to average channel correlation may limit how closely the averaged channel correlation matrix R may come to having those structural properties. In this case, coefficients associated with the same antenna element separation distance may only be approximately equal to one another, or may only be approximately complex conjugates of one another. This approximate nature of the coefficients means that the averaged channel correlation matrix R may not itself have structure for the radio node 16 to exploit in order to form a reduced subset 24 of coefficients to feed back.
  • the radio node 16 uses the averaged channel correlation matrix R to calculate a structured channel correlation matrix R that indeed has structure for the radio node 16 to exploit for forming the reduced subset 24 of coefficients to feed back.
  • Figure 5 illustrates one such embodiment.
  • the radio node 16 calculates the averaged channel correlation matrix R as described above (Block 400). The radio node 16 then calculates the channel correlation matrix R to be signaled as being a structured channel correlation matrix R (i.e.,
  • R R ) (Block 410).
  • the radio node 16 next extracts the subset 24 of coefficients to feed back from the channel correlation matrix R calculated (Block 420).
  • this structured channel correlation matrix R may be formed based on the averaged channel correlation matrix R .
  • the radio node 16 modifies the averaged channel correlation matrix R as little as needed for coefficients in the resulting structured channel correlation matrix R that are associated with the same antenna element separation distance to be derivable from one another. For instance, coefficients in the averaged channel correlation matrix R that are associated with the same antenna element separation distance may only be approximately equal to one another, or may only be
  • the radio node 16 may modify those corresponding coefficients in the structured channel correlation matrix R so that they are actually equal to one another, or actually complex conjugates of one another.
  • the radio node 16 may average coefficients in the averaged channel correlation matrix R that characterize channel correlation between antenna elements separated by the same distance.
  • the structured channel correlation matrix R is a Hermitian Toeplitz matrix, for instance, the radio node 16 may calculate Toeplitz coefficients
  • R(n) denotes a channel correlation coefficient for separation distance n .
  • the radio node 16 calculates the channel correlation matrix R to signal as being a structured matrix R that approximates the averaged channel correlation matrix R , but that has certain structural properties which are exploited to reduce signaling overhead. Stated differently, the radio node 16 may exploit the fact that the averaged channel correlation matrix R approximately resembles a structured matrix R , in order to simply signal the structured matrix R with a subset of the structured matrix's coefficients, rather than having to signal the averaged channel correlation matrix R with more coefficients.
  • the radio node 16 calculates the entire channel correlation matrix R to signal and then extracts a subset of the matrix's coefficients to actually feed back.
  • the radio node 16 in other embodiments need not calculate the entire channel correlation matrix R . Instead, the radio node 16 may selectively calculate or otherwise determine the subset of the matrix's coefficients to feed back, without calculating or determining the matrix's other coefficients.
  • Figure 6 illustrates one example.
  • the radio node 16 calculates the averaged channel correlation matrix R as described above (Block 500). Based on this averaged channel correlation matrix R , the radio node 16 calculates a subset of coefficients of a structured channel correlation matrix R . It is this structured channel correlation matrix R that the radio node 16 will signal as the channel correlation matrix R . In this approach, therefore, the radio node 16 directly and selectively calculates the subset 24 of coefficients to feed back, without calculating other coefficients that will not be fed back.
  • the radio node 16 may for example use equation (1) to selectively calculate the subset 24 of coefficients to be fed back, and not use equation (1) to calculate any other coefficients that will not be fed back.
  • the radio node 16 in some embodiments may determine the subset 24 of coefficients to feed back after estimating all or part of the channel correlation matrix R to signal. In other embodiments, though, the radio node 16 may effectively determine the subset 24 of coefficients to feed back as part of estimating the channel correlation matrix R ; that is, the radio node 16 imposes the structure of the channel correlation matrix R in the process of estimating that matrix.
  • the extent to which the radio node 16 knowingly exploits certain structural properties of the channel correlation matrix R may thereby vary in different embodiments. Similarly, the extent to which the radio node 16 knowingly feeds back a coefficient for each antenna element separation distance may vary in different embodiments.
  • the radio node 16 actually has knowledge of the antenna element separation distances at the transmit antenna array 14; that is, the radio node 16 knows the distance(s) by which antenna elements of the array 14 are separable. With this knowledge, the radio node 16 may actively form the subset 24 to include one coefficient for each of one or more antenna element separation distances, e.g., by knowingly differentiating coefficients on the basis of the separation distance with which they are associated.
  • the radio node 16 does not actually have knowledge of the antenna element separation distances at the transmit antenna array 14.
  • the radio node 16 in this case may be configured to simply calculate certain coefficients to include in the subset 24 to be fed back, while remaining naive to the fact that the resulting subset includes one coefficient for each of one or more antenna element separation distances.
  • the radio node 16 simply knows that the channel correlation matrix R to be signaled has the certain structural properties described above (e.g., Hermitian Toeplitz). In this case, which coefficients are associated with which antenna element separation distances may be inherent in or an artifact of the known structural properties of the channel correlation matrix R .
  • the radio node 16 may form the subset 24 to include one coefficient for each index delta value and thereby effectively form the subset 24 to include one coefficient for each antenna element separation distance.
  • the radio node 16 may form the subset 24 to include one coefficient R 0 l for an index delta value of 1 (i.e., since the coefficient characterizes channel correlation between the antenna element designated with index 0 and the antenna element designated with index 1).
  • This delta value of 1 may be representative of a particular antenna element separation distance, e.g., dl
  • the radio node 16 may form the subset 24 to include one coefficient R 0 2 for an index delta value of 2 (i.e., since the coefficient characterizes channel correlation between the antenna element designated with index 0 and the antenna element designated with index 2).
  • This delta value of 2 may be representative of a particular antenna element separation distance, e.g., d2.
  • the radio node 16 determines and transmits such a subset 24 of coefficients. And whether or not the radio node 16 knows the antenna element separation distances, the subset 24 transmitted indeed includes a coefficient for each of one or more antenna element separation distances.
  • the channel correlation matrix R parameterized and signaled by the subset 24 of coefficients may characterize channel correlation between all or only some antenna elements of the transmit antenna array 14.
  • the signaled channel correlation matrix R may in fact characterize channel correlation between all elements of the array 14.
  • the transmit antenna array 14 is a dual-polarized array with different elements having different polarization directions
  • the signaled channel correlation matrix R may characterize channel correlation between antenna elements with a certain polarization relation (e.g., co-polarized or
  • the radio node 16 may signal different channel correlation matrices R for characterizing channel correlation between antenna elements with different polarization relations.
  • the overall channel correlation matrix R' for a dual-polarized array may have the block form: where R A , R B , R ⁇ , and R D characterize channel correlation between antenna elements with different polarization relations.
  • the radio node 16 signals each of R A , R B , R c , and R D using the techniques described above for signaling a single matrix R . That is, the radio node 16 signals four subsets of coefficients for respectively parameterizing R A , R B , R c , and R D .
  • R A , R B , R c , and R D are Hermitian Toeplitz matrices, this may mean that the radio node 16 signals 4N coefficients, comprising the N Toeplitz coefficients for each of R A , R B , R c , and R D .
  • R B and R c are assumed to be zero matrices (i.e., channel correlation between cross-polarized antenna elements is assumed to be zero). In this case, only two subsets of coefficients may be fed back for signaling R A and R D . In still other embodiments, R A and R D are assumed to be equal, in which case only one subset of coefficients may be fed back.
  • the signaled channel correlation matrix R may in fact characterize channel correlation between all elements of the array 14.
  • the transmit antenna array 14 is a multi-dimensional array with different elements arranged in different spatial dimensions
  • the signaled channel correlation matrix R may characterize channel correlation between antenna elements arranged in a certain spatial dimension (e.g., in a horizontal dimension or in a vertical dimension).
  • the radio node 16 may signal different channel correlation matrices R for characterizing channel correlation in different spatial dimensions of the array 14.
  • the radio node 16 signals each of R H and R v using the techniques described above for signaling a single matrix R . That is, the radio node 16 signals two subsets of coefficients for respectively parameterizing R H and R v .
  • R is a perturbation of R' .
  • the nearest Kronecker product problem may be solved by a singular value decomposition (SVD) of R .
  • the Toeplitz coefficients for R H and R v may be calculated using the previously described method for calculating the Toeplitz coefficient for a single-polarized linear array.
  • the antenna element separation distances herein may be distances by which antenna elements are separable in a particular spatial dimension, even where the antenna array 14 has elements arranged in multiple spatial dimensions.
  • the antenna element separation distances may be distances by which antenna elements are separable in multiple spatial dimensions.
  • the antenna array 14 is a planar array with N antenna elements in the horizontal dimension and M antenna elements in the vertical dimension
  • the antenna element separation distances may be two-dimensional distances in the horizontal and vertical dimensions.
  • the antenna element separation distance for a pair of antenna elements may have a horizontal distance component and a vertical distance component.
  • the radio node 16 may still form the subset 24 of coefficients to include one coefficient for each of one or more antenna element separation distances.
  • a signaled channel correlation matrix R may characterize channel correlation, in multiple spatial dimensions of the transmit antenna array 14, between N*M antenna elements of that array 14.
  • the signaled channel correlation matrix R in these embodiments has N 2 *M 2 coefficients R nl n2 ml m2 characterizing channel correlation between different pairs of antenna elements, where n1 and ml are indices of one antenna element in a pair in different dimensions, and n2 and m2 are indices of the other antenna element in the pair in the different dimensions, for indices 0,1 ,... N and 0, 1 , ... M.
  • the subset 24 of coefficients fed back for parameterizing that matrix R may comprise less than N 2 *M 2 coefficients.
  • the subset 24 in this regard may include one coefficient for each of one or more two-dimensional antenna element separation distances.
  • the subset 24 of coefficients need not include coefficients for all multi-dimensional distances by which antenna elements are separable in the array 14. For example, not all combinations of horizontal distance components and vertical distance components may be needed to fully parameterize a signaled channel correlation matrix R that characterizes channel correlation in the horizontal and vertical dimensions of the array 14. Instead, according to some embodiments, the subset 24 of coefficients has 2NM - N - M + 1 coefficients.
  • the transmit antenna array 14 is a single-polarized uniform planar array (UPA).
  • UPA uniform planar array
  • antenna element separation distances of the array correspond to different possible combinations of An and Aw , where A « e ⁇ -(N - l), -(N- 2), ..., 0, ..., (N - 2), (N - l) ⁇ and
  • coefficients are not needed for all combinations of An and Am values in order to parameterize the channel correlation matrix R . Instead, coefficients are only needed for 2NM - N - M + 1 combinations of An and Am values.
  • R signaled for the UPA may be fully parameterized by one of two different possible subsets of coefficients.
  • One possible subset to feed back includes coefficients R An Am where An ⁇ 0 and Am ⁇ 0 and coefficients R An Am where An > 0 and Am ⁇ 0. With this subset of coefficients fed back, the remaining coefficients may be derived by taking the complex conjugate of the fed back coefficients.
  • these remaining coefficients may be fed back in the alternative as the other possible subset; that is, the other possible subset to feed back includes coefficients R An Am where An ⁇ 0 and Am ⁇ 0 and coefficients R An Am where An ⁇ 0 and Am ⁇ 0.
  • the coefficients R An Am where An ⁇ 0 and Am ⁇ 0 may comprise coefficients that characterize the correlation between the bottom- leftmost antenna element of the antenna array 14 and all the other antenna elements. This is visually illustrated in Figure 7A for a 3x3 UPA. This thus requires NM coefficients.
  • the coefficients R An Am where An > 0 and Am ⁇ 0 may comprise coefficients that characterize correlation between the top-leftmost antenna element of the antenna array 14 and the antenna elements in the subarray formed by excluding the first column and first row of the array. This is illustrated in Figure 7B for the 3x3 UPA, with the subarray shown in dotted lines.
  • the radio node 16 may calculate this subset of coefficients as described in Figure 5 or Figure 6. That is, the channel correlation matrix R signaled by this subset of coefficients may actually be a structured version R of an averaged channel correlation matrix R , whereby the structuring makes it to where coefficients associated with the same antenna element separation distance are derivable from one another.
  • the radio node 16 may for instance average coefficients in the averaged channel correlation matrix R that characterize channel correlation between antenna elements separated by the same distance. For a UPA, this may mean that the radio node 16 averages coefficients R An Am associated with the same combination of An and Am values, as well corresponding conjugate values.
  • Figures 8A-8C illustrate one example of this for a dual-polarized 3x3 UPA.
  • antenna element (0,0) and antenna element (1 ,0) are separated by a two-dimensional distance corresponding to the antenna element index delta (An, Am) of (1 ,0).
  • Figure 8B shows that there are 6 pairs/combinations of antenna elements in the UPA with that same antenna element index delta (An, Am) of (1 ,0).
  • antenna element (0, 1) and antenna element (2,2) in Figure 8A are separated by a two-dimensional distance corresponding to the antenna element index delta (An, Am) of (2, 1).
  • Figure 8C shows that there are only 2 pairs/combinations of antenna elements in the UPA with that same antenna element index delta (An, Am) of (2, 1).
  • Figures 9A-9C illustrate these pairs/combinations of antenna elements circled. Accordingly, averaging of coefficients in the averaged channel correlation matrix R may occur across the 2 coefficients for the 2 pairs of antenna elements with an antenna element index delta (An, Am) of (2,1), but occur across the 6 coefficients for the 6 pairs of antenna elements with an antenna element index delta (An, Am) of (1 ,0).
  • the channel correlation matrix in such a context may be described as a block matrix similarly as noted above for a double-polarized ULA.
  • the embodiments described for the double-polarized ULA may therefore be equally extended to a double-polarized UPA.
  • a channel correlation matrix has the structural properties described above under certain circumstances.
  • a pure line-of-sight channel between a single-polarized uniform linear array (ULA) with N antenna elements and a single receive antenna.
  • channel may be modeled as a single ray whose directional properties may be described by the ⁇ and ⁇ are the zenith and azimuth angles of
  • the channel matrix for a specific time-frequency resource element may then be described as
  • the channel matrix as a function of time tand frequency / may be expressed as:
  • the UPA is characterized by the antenna position vector vectors:
  • At least some embodiments herein therefore exploit the actual or assumed structural properties of a long-term correlation matrix for a ULA or U PA in order to effectively compress explicit channel correlation feedback.
  • the correlation matrix is compressed by exploiting the Toeplitz-like structure of the matrix (e.g., as averaged in time and/or frequency), so that only a reduced set of correlation coefficients needs to be fed back.
  • an antenna element of a transmit antenna array is any physical or virtual radiating component used to transmit a radio wave from the transmit antenna array.
  • an antenna element separation distance herein refers to the distance by which physical antenna elements are separated, or the distance by which virtual antenna elements are separated in terms of their phase centers. That is, with regard to virtual antenna elements, the antenna element separation distance corresponds to the distance between the phase centers of the virtual antenna elements.
  • an antenna element herein may also be referred to as an antenna port, in the sense that an antenna element may correspond to an antenna port.
  • An antenna port may likewise be a physical port or a virtual port.
  • an antenna element separation distance may refer to the distance by which physical antenna ports are separated, or the distance by which virtual antenna ports are separated, in terms of their phase centers.
  • the array's ports may correspond in some embodiments to either a one-dimensional or a two-dimensional port layout with equal distance between the phase centers of the antenna ports per dimension, i.e., that the plurality of antenna ports form a (virtual) ULA or UPA.
  • the channel correlation matrix R discussed herein may characterize channel correlation between antenna elements of the transmit antenna array 14, with or without also characterizing channel correlation between receive-side antenna element(s).
  • the channel correlation matrix R is simply a transmit (TX) correlation matrix.
  • the channel correlation matrix R may be a vectorized channel correlation matrix that contains both a transmit correlation matrix and a receive correlation matrix; that is, R may also characterize channel correlation between antenna elements of a receive antenna array.
  • the channel correlation matrix R may be calculated as, or
  • which type of correlation matrix the radio node 16 is to signal may be dynamically signaled by radio node 12, e.g., using radio resource control (RRC) signaling or as part of a channel state information (CSI) request on a control channel.
  • RRC radio resource control
  • CSI channel state information
  • the type of correlation matrix may be predefined, e.g., by the applicable standard.
  • Radio node 12 in the form of a base station and radio node 16 in the form of a UE, such need not be the case.
  • Radio node 12 in other embodiments may be a UE and radio node 16 may be a base station. Accordingly,
  • embodiments herein may be applicable for characterizing channel correlation in either the uplink or downlink direction. Even further, embodiments herein may also be used for machine-to- machine communication, e.g., both radio nodes 12, 16 are UEs.
  • Figure 1 illustrates radio node 16 as transmitting feedback 20 to the same radio node 14 from which the reference signal(s) were received, such need not be the case.
  • the radio node 16 may transmit feedback 20 to a different radio node.
  • coefficients in the subset fed back may be quantized
  • coefficients e.g., so that the coefficients may be encoded into a string of bits.
  • each coefficient is quantized using uniform quantization of the real and imaginary component, respectively.
  • the uniform quantization is done on the absolute value and phase, respectively, of each coefficient.
  • embodiments herein are applicable to any type of wireless communication system 10. Indeed, embodiments may use any of one or more communication protocols known in the art or that may be developed, such as IEEE 802. xx, CDMA, WCDMA, GSM, LTE, UTRAN, WiMax, or the like. Accordingly, although sometimes described herein in the context of LTE or 5G, the principles and concepts discussed herein are applicable to other systems as well.
  • a radio node as used herein is therefore any type node capable of communicating with another radio node wirelessly over radio signals.
  • a radio node may for example be a radio network node, e.g., in a radio access network (RAN) or core network (CN) of the system 10.
  • the radio network node may for instance be a base station, a relay node, a core network node, or the like.
  • a radio node may be a wireless device and may therefore refer to a user equipment (UE), a mobile station, a laptop, a smartphone, a machine-to-machine (M2M) device, a machine-type communications (MTC) device, a narrowband Internet of Things (loT) device, etc. That said, although a radio node in the form of a wireless device may be a UE, it should be noted that the wireless device does not necessarily have a "user" in the sense of an individual person owning and/or operating the device.
  • M2M machine-to-machine
  • MTC machine-type communications
  • LoT narrowband Internet of Things
  • a wireless device may also be referred to as a wireless communication device, a radio device, a radio communication device, a wireless terminal, or simply a terminal - unless the context indicates otherwise, the use of any of these terms is intended to include device-to-device UEs or devices, machine-type devices or devices capable of machine-to-machine communication, sensors equipped with a wireless device, wireless-enabled table computers, mobile terminals, smart phones, laptop-embedded equipped (LEE), laptop-mounted equipment (LME), USB dongles, wireless customer-premises equipment (CPE), etc.
  • M2M machine-to-machine
  • MTC machine- type communication
  • wireless sensor and sensor may also be used. It should be understood that these devices may be UEs, but may be generally configured to transmit and/or receive data without direct human interaction.
  • a wireless device as described herein may be, or may be comprised in, a machine or device that performs monitoring or measurements, and transmits the results of such monitoring measurements to another device or a network.
  • machines are power meters, industrial machinery, or home or personal appliances, e.g.
  • a wireless communication device as described herein may be comprised in a vehicle and may perform monitoring and/or reporting of the vehicle's operational status or other functions associated with the vehicle.
  • Figure 10 illustrates a method 600 performed by radio node 16 according to some embodiments.
  • the method 600 may comprise measuring one or more reference signals 18 transmitted from antenna elements of a transmit antenna array 14 (Block 610).
  • the method may also comprise determining a subset of coefficients of a channel correlation matrix that characterizes channel correlation between two or more of the antenna elements of the transmit antenna array 14 according to the measuring (Block 620).
  • This channel correlation matrix may characterize channel correlation between all or only some of the antenna elements in the transmit antenna array, and/or may characterize channel correlation in all or only some of the spatial dimensions or polarization relations for the transmit antenna array 14.
  • the channel correlation matrix may be, or may be based on, (i) R' as the overall channel correlation matrix for the array, (ii) R H characterizing channel correlation in the horizontal dimension, (iii) R v characterizing channel correlation in the vertical dimension, (iv) R A , R B , R c , or R D
  • the determined subset includes, for each of one or more antenna element separation distances, a coefficient from which is derivable channel correlation between any of the two or more antenna elements that are separated by that distance.
  • the method 600 then comprises transmitting the subset of coefficients as channel correlation feedback 20 that parameterizes the channel correlation matrix (Block 630).
  • the determining in Block 620 may be based on an averaged correlation matrix.
  • the determining may comprise, based on the measuring, calculating an averaged correlation matrix that characterizes channel correlation between the two or more of the antenna elements of the transmit antenna array 14 as averaged over a certain time interval and a certain frequency interval.
  • the determining may further comprise, for each of the two or more antenna element separation distances, calculating the coefficient to include in the subset for that distance as an average across coefficients in the averaged correlation matrix that characterize channel correlation between antenna elements that are separated by that distance.
  • Figure 11 illustrates a corresponding method 700 performed by radio node 12 according to some embodiments.
  • the method 700 comprises receiving a subset of coefficients of a channel correlation matrix as channel correlation feedback that parameterizes the channel correlation matrix (Block 710).
  • the channel correlation matrix characterizes channel correlation between two or more antenna elements of a transmit antenna array from which one or more reference signals were transmitted.
  • this channel correlation matrix may characterize channel correlation between all or only some of the antenna elements in the transmit antenna array, and/or may characterize channel correlation in all or only some of the spatial dimensions or polarization relations for the transmit antenna array 14.
  • the subset includes, for each of one or more antenna element separation distances, a coefficient from which is derivable channel correlation between any of the two or more antenna elements that are separated by that distance.
  • the method 700 further includes reconstructing the channel correlation matrix using the received subset of coefficients (Block 720).
  • the method 700 also includes precoding a transmission 22 from the transmit antenna array 14 based on the reconstructed channel correlation matrix, and transmitting the precoded transmission (Block 730). Moreover, although not required, the method 700 may further include the radio node 12 transmitting the one or more reference signals from the transmit antenna array 14.
  • the channel correlation matrix in Figures 10 and 1 1 is a Toeplitz matrix, and the subset of coefficients comprises Toeplitz coefficients of the channel correlation matrix.
  • Figures 12 and 13 illustrate methods performed by radio nodes 12, 16 according to other embodiments.
  • the method 800 may comprise measuring one or more reference signals 18 transmitted from antenna elements of a transmit antenna array 14 (Block 810).
  • the method may also comprise determining a subset of coefficients of a channel correlation matrix that characterizes channel correlation between two or more of the antenna elements of the transmit antenna array 14 according to the measuring (Block 820).
  • this channel correlation matrix may characterize channel correlation between all or only some of the antenna elements in the transmit antenna array, and/or may characterize channel correlation in all or only some of the spatial dimensions or polarization relations for the transmit antenna array 14.
  • the determined subset comprises Toeplitz coefficients of the channel correlation matrix.
  • the method 800 then comprises transmitting the subset of coefficients as channel correlation feedback 20 that parameterizes the channel correlation matrix (Block 830).
  • the determining in Block 820 may be performed based on an averaged correlation matrix, as described above with respect to Figure 10.
  • the determining may entail, for each of the Toeplitz coefficients, determining the Toeplitz coefficient by averaging coefficients of the averaged correlation matrix which would be the same, or complex conjugates thereof, if the averaged correlation matrix was a purely Hermitian Toeplitz matrix.
  • Figure 13 illustrates a corresponding method 900 performed by radio node 12 according to some embodiments.
  • the method 900 comprises receiving a subset of coefficients of a channel correlation matrix as channel correlation feedback that parameterizes the channel correlation matrix (Block 910).
  • the channel correlation matrix characterizes channel correlation between two or more antenna elements of a transmit antenna array from which one or more reference signals were transmitted.
  • this channel correlation matrix may characterize channel correlation between all or only some of the antenna elements in the transmit antenna array, and/or may characterize channel correlation in all or only some of the spatial dimensions or polarization relations for the transmit antenna array 14.
  • the subset comprises Toeplitz coefficients of the channel correlation matrix.
  • the method 900 further includes reconstructing the channel correlation matrix using the received subset of coefficients (Block 920).
  • the method 900 also includes precoding a transmission 22 from the transmit antenna array 14 based on the reconstructed channel correlation matrix, and transmitting the precoded transmission (Block 930). Moreover, although not required, the method 900 may further include the radio node 12 transmitting the one or more reference signals from the transmit antenna array 14.
  • Figures 14 and 15 illustrate methods performed by radio nodes 12, 16 according to other embodiments.
  • the method 1000 may comprise measuring one or more reference signals 18 transmitted from antenna elements of a transmit antenna array 14 (Block 1010).
  • the method may also comprise determining a subset of coefficients of a channel correlation matrix that characterizes channel correlation between two or more of the antenna elements of the transmit antenna array 14 according to the measuring (Block 1020).
  • this channel correlation matrix may characterize channel correlation between all or only some of the antenna elements in the transmit antenna array, and/or may characterize channel correlation in all or only some of the spatial dimensions or polarization relations for the transmit antenna array 14.
  • the determined subset includes, for each of one or more groups of antenna element pairs, a coefficient from which is derivable channel correlation between any antenna element pair within the group.
  • each of the one or more groups of antenna element pairs includes antenna element pairs having the same relative element separation distance.
  • the method may further comprise determining each of the one or more groups of antenna element pairs, as including antenna element pairs for which channel correlation is approximately the same.
  • the method 1000 then comprises transmitting the subset of coefficients as channel correlation feedback 20 that parameterizes the channel correlation matrix (Block 1030).
  • the determining in Block 1020 may be performed based on an averaged correlation matrix, as described above with respect to Figure 10.
  • Figure 15 illustrates a corresponding method 1100 performed by radio node 12 according to some embodiments.
  • the method 1 100 comprises receiving a subset of coefficients of a channel correlation matrix as channel correlation feedback that parameterizes the channel correlation matrix (Block 1 110).
  • the channel correlation matrix characterizes channel correlation between two or more antenna elements of a transmit antenna array from which one or more reference signals were transmitted.
  • this channel correlation matrix may characterize channel correlation between all or only some of the antenna elements in the transmit antenna array, and/or may characterize channel correlation in all or only some of the spatial dimensions or polarization relations for the transmit antenna array 14.
  • the subset includes, for each of one or more groups of antenna element pairs, a coefficient from which is derivable channel correlation between any antenna element pair within the group.
  • each of the one or more groups of antenna element pairs includes antenna element pairs having the same relative element separation distance.
  • the method may further comprise determining each of the one or more groups of antenna element pairs, as including antenna element pairs for which channel correlation is approximately the same.
  • the method 1100 further includes reconstructing the channel correlation matrix using the received subset of coefficients (Block 1 120).
  • the method 1 100 also includes precoding a transmission 22 from the transmit antenna array 14 based on the reconstructed channel correlation matrix, and transmitting the precoded transmission (Block 1130). Moreover, although not required, the method 1100 may further include the radio node 12 transmitting the one or more reference signals from the transmit antenna array 14.
  • a radio node 16 as described above may perform any of the processing herein by implementing any functional means or units.
  • the radio node 16 comprises respective circuits or circuitry configured to perform the steps shown in any of Figures 2-6, 10, 12, and 14.
  • the circuits or circuitry in this regard may comprise circuits dedicated to performing certain functional processing and/or one or more microprocessors in conjunction with memory.
  • memory which may comprise one or several types of memory such as read-only memory (ROM), random-access memory, cache memory, flash memory devices, optical storage devices, etc.
  • the memory stores program code that, when executed by the one or more processors, carries out the techniques described herein.
  • FIG 16 illustrates a radio node 16 in accordance with one or more embodiments.
  • the radio node 16 includes processing circuitry 1200 and communication circuitry 1210.
  • the communication circuitry 1210 e.g., radio circuitry
  • the communication circuitry 1210 is configured to transmit and/or receive information to and/or from one or more other nodes, e.g., via any communication technology.
  • the communication circuitry 1210 may do so for instance via one or more antennas, which may be internal or external to the radio node 16.
  • the processing circuitry 1200 is configured to perform processing described above, e.g., in Figures 2-6, 10, 12, and/or 14, such as by executing instructions stored in memory 1220.
  • the processing circuitry 1200 in this regard may implement certain functional means, units, or modules.
  • FIG. 17 illustrates a radio node 16 in accordance with one or more other
  • the radio node 16 implements various functional means, units, or modules, e.g., via the processing circuitry 1200 in Figure 16 and/or via software code.
  • These functional means, units, or modules, e.g., for implementing the method in Figures 2-6, 10, 12, and/or 14, include for instance a measuring unit or module 1300 for measuring one or more reference signals 18 transmitted from antenna elements of a transmit antenna array 14.
  • a determining unit or module 1310 for, determining the subset of coefficient of a channel correlation matrix, as described above.
  • a transmitting unit or module 1320 for transmitting the subset of coefficients as channel correlation feedback that
  • a radio node 12 as described above may perform any of the processing herein by implementing any functional means or units.
  • the radio node 12 comprises respective circuits or circuitry configured to perform the steps shown in any of Figures 2, 11 , 13, and 15.
  • the circuits or circuitry in this regard may comprise circuits dedicated to performing certain functional processing and/or one or more microprocessors in conjunction with memory.
  • memory which may comprise one or several types of memory such as read-only memory (ROM), random-access memory, cache memory, flash memory devices, optical storage devices, etc.
  • the memory stores program code that, when executed by the one or more processors, carries out the techniques described herein.
  • FIG 18 illustrates a radio node 12 in accordance with one or more embodiments.
  • the radio node 12 includes processing circuitry 1400 and communication circuitry 1410.
  • the communication circuitry 1410 e.g., radio circuitry
  • the communication circuitry 1410 is configured to transmit and/or receive information to and/or from one or more other nodes, e.g., via any communication technology.
  • the communication circuitry 1410 may do so for instance via one or more antennas, which may be internal or external to the radio node 12.
  • the processing circuitry 1400 is configured to perform processing described above, e.g., in Figures 2, 11 , 13, and/or 15, such as by executing instructions stored in memory 1420.
  • the processing circuitry 1400 in this regard may implement certain functional means, units, or modules.
  • FIG. 19 illustrates a radio node 12 in accordance with one or more other
  • the radio node 12 implements various functional means, units, or modules, e.g., via the processing circuitry 1400 in Figure 18 and/or via software code.
  • These functional means, units, or modules, e.g., for implementing the method in Figures 2, 11 , 13, and/or 15, include for instance a receiving unit or module 1500 for receiving the subset of coefficients of a channel correlation matrix as described above. Also included is a reconstructing unit or module 1510 for reconstructing the channel correlation matrix using the received subset of coefficients.
  • a precoding unit or module 1520 is also included for precoding a transmission 22 from the transmit antenna array based on the reconstructed channel correlation matrix.
  • a transmitting unit or module 1500 may be included for transmitting the precoded transmission.
  • a computer program comprises instructions which, when executed on at least one processor of a radio node 12 or 16, cause the radio node 12 or 16, to carry out any of the respective processing described above.
  • a computer program in this regard may comprise one or more code modules corresponding to the means or units described above.
  • Embodiments further include a carrier containing such a computer program.
  • This carrier may comprise one of an electronic signal, optical signal, radio signal, or computer readable storage medium.
  • subset is used herein in its general sense to refer to a part or portion of a larger set. This contrasts with the mathematical or technical sense of the term in which a subset may be the same as the set.
  • a “subset” as used herein is really a "proper subset.” Accordingly, a "subset of coefficients of a channel correlation matrix” as used herein refers to a portion of the larger set of coefficients of the channel correlation matrix.

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Abstract

La présente invention concerne un nœud radio (16) qui mesure un ou plusieurs signaux de référence (18) transmis par des éléments d'antenne d'un réseau d'antennes d'émission (14). Le nœud radio (16) détermine un sous-ensemble de coefficients d'une matrice de corrélation de canal qui caractérise une corrélation de canal entre au moins deux des éléments d'antenne du réseau d'antennes d'émission (14) selon la mesure. Ce sous-ensemble comprend, pour une distance de séparation d'éléments d'antenne ou pour chacune des distances de séparation d'éléments d'antenne, un coefficient duquel peut être dérivée une corrélation de canal entre l'un quelconque des deux ou plus de deux éléments d'antenne qui sont séparés par cette distance. Le nœud radio (16) transmet ensuite le sous-ensemble de coefficients sous la forme d'une rétroaction de corrélation de canal (20) qui établit le paramètre de la matrice de corrélation de canal.
PCT/SE2016/051321 2016-12-28 2016-12-28 Rétroaction de corrélation de canal dans un système de communication sans fil WO2018124950A1 (fr)

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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111294080A (zh) * 2019-01-31 2020-06-16 展讯通信（上海）有限公司 天线模块选择方法及装置、终端设备、计算机可读存储介质
CN111294121A (zh) * 2019-01-31 2020-06-16 展讯通信（上海）有限公司 基于AiP结构的波束调整方法及装置、计算机可读存储介质
WO2020156038A1 (fr) * 2019-01-31 2020-08-06 展讯通信（上海）有限公司 Procédé et dispositif de détection de faisceau, procédé et dispositif d'ajustement de faisceau, procédé et dispositif de sélection de module d'antenne et support de stockage lisible par ordinateur
CN114665998A (zh) * 2022-03-22 2022-06-24 北京大学 空时一致性下的三重非平稳无线通信信道建模方法
CN115580326A (zh) * 2022-10-12 2023-01-06 东南大学 一种利用双极化数据相关性的信道信息压缩反馈方法
US20240297686A1 (en) * 2023-03-02 2024-09-05 Qualcomm Incorporated Identifying los using channel correlation matrix

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CN111294080A (zh) * 2019-01-31 2020-06-16 展讯通信（上海）有限公司 天线模块选择方法及装置、终端设备、计算机可读存储介质
CN111294121A (zh) * 2019-01-31 2020-06-16 展讯通信（上海）有限公司 基于AiP结构的波束调整方法及装置、计算机可读存储介质
WO2020156038A1 (fr) * 2019-01-31 2020-08-06 展讯通信（上海）有限公司 Procédé et dispositif de détection de faisceau, procédé et dispositif d'ajustement de faisceau, procédé et dispositif de sélection de module d'antenne et support de stockage lisible par ordinateur
CN111294080B (zh) * 2019-01-31 2021-03-23 展讯通信（上海）有限公司 天线模块选择方法及装置、终端设备、计算机可读存储介质
CN111294121B (zh) * 2019-01-31 2021-04-02 展讯通信（上海）有限公司 基于AiP结构的波束调整方法及装置、计算机可读存储介质
US11664872B2 (en) 2019-01-31 2023-05-30 Spreadtrum Communications (Shanghai) Co., Ltd. Beam detection method and device, beam adjusting method and device, antenna module selection method and device, and computer readable storage media
CN114665998A (zh) * 2022-03-22 2022-06-24 北京大学 空时一致性下的三重非平稳无线通信信道建模方法
CN115580326A (zh) * 2022-10-12 2023-01-06 东南大学 一种利用双极化数据相关性的信道信息压缩反馈方法
US20240297686A1 (en) * 2023-03-02 2024-09-05 Qualcomm Incorporated Identifying los using channel correlation matrix

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