Phase noise compensation in a receiver device

Abstract

There is provided techniques for compensating a received signal for phase noise. A method is performed by a receiver device. The method comprises receiving a signal over a channel from a transmitter device. The signal comprises pilot symbols and data symbols. The method comprises estimating phase noise of the received signal. The estimating is based on a signal model comprising an approximation of a complete version of the signal as transmitted by the transmitter device. The method comprises compensating the received signal for the estimated phase noise.

Description

[0001] PHASE NOISE COMPENSATION IN A RECEIVER DEVICE

[0002] TECHNICAL FIELD

[0003] Embodiments presented herein relate to a method, a receiver device, a computer program, and a computer program product for compensating a received signal for phase noise.

[0004] BACKGROUND

[0005] In general terms, increasing the data rate of a wireless access system can either be performed by increasing the bandwidth of the transmitted signal or by increasing the spectral efficiency of the physical layer, e.g., the modulation order of the symbols carried by the transmitted wireless signal. Since bandwidth is usually a scarce resource (e.g., since many communication systems are already installed and the frequency spectrum is often fully occupied), increasing spectral efficiency of the wireless signal is often the only possible solution. Hence, finding techniques for the wireless signal to carry more bits per consumed spectral bandwidth (in terms of bits / Hz) are of importance. Especially techniques that enable an increased rate in existing, already installed, wireless access system, even though these systems were not initially designed for high spectral efficiency.

[0006] Examples of modulation orders used in the physical layer in current wireless access systems range from 4 QAM to 256 QAM (where QAM is short for quadrature amplitude modulation), i.e., from 2 bits / sy mbol up to 8 bits / symbol. To substantially increase the spectral efficiency, modulation orders should be increased to 4096 QAM or even higher (such as 16k QAM). Such an increase of modulation order gives 12 bits / symbol (or 14 bits / symbol), i.e., an increase of 50% or even up to 75% without increasing the bandwidth of the wireless signal. However, increasing the spectral efficiency increases the sensitivity of the wireless system, such as the sensitivity to noise, and distortion might increase.

[0007] One degrading factor in wireless systems is the phase noise of local oscillators used for up and down-converting the modulated signal to / from carrier frequency. The phase noise distorts the wireless signal by phase modulating it. This might limit the possible spectral efficiency if not handled (i.e., compensated for). The phase noise can, for example, be reduced by utilizing better oscillators, but this leads to increased complexity and power consumption of the system. Sensitivity to phase noise can also be reduced by introducing signal processing which estimates and compensates for the phase noise, where such signal processing is often situated in the wireless receiver.

[0008] Signal processing for estimating phase noise in wireless communication systems commonly rely on a having few known pilot symbols embedded in the transmitted signal. It is of interest to keep the number of necessary pilot symbols to a minimum in order to limit the overhead in the transmitted signal. It is also of interest to keep the complexity of the processing to a minimum.

[0009] Reference is here made to Fig. 1(a) which schematically illustrates a communication system 10 where a transmitter (Tx) device 100 transmits a signal x over a channel H to a receiver (Rx) device 200, and where the received signal is denoted y. Further detail of the operations performed by the transmitter device 100 and the receiver device 200 and how the channel impacts the transmitted signal is illustrated in the block diagram of Fig.

[0010] 1(b).

[0011] Before transmission, the sequence of payload symbols, containing data symbols and possibly also known pilot symbols at known frequencies, is transformed into time domain, e.g., by applying in inverse discrete Fourier transform (IDFT) to the sequence of payload symbols and then the transformed sequence of payload symbols is upconverted to radio frequency using a high-frequency oscillator. This high-frequency oscillator is commonly affected by phase noise. Hence, the phase noise affects the modulated signal in the time domain. Commonly, the QAM symbols of the time domain signal are carried by N orthogonal frequency-division multiplexing (OFDM) subcarriers. The phase noise will both rotate the symbols and cause inter-carrier cross talk. In other words, QAM symbols on different OFDM subcarriers will disturb each other. The transmission to the receiver is over a channel. The channel might be a frequency selective channel and be affected by additive white gaussian noise (AWGN). The received signal is in the receiver device down-converted from radio frequency using a local oscillator. This local oscillator might be affected by phase noise. The resulting signal is transformed to the frequency domain using a discrete Fourier transform (DFT).

[0012] To achieve perfect compensation of the (frequency selective) channel, a cyclic prefix is introduced in the transmitter and removed in the receiver, where the length of the cyclic prefix corresponds to the memory of the channel.

[0013] The received modulated signal, affected by the (frequency selective) channel, AWGN and phase noise in both the receiver device and the transmitter device, can, using complex baseband notation, be formulated as where F and F-1are N x N matrices representing the DFT and the IDFT, respectively. The AWGN is represented by the vector w of length N. The payload (i.e., QAM-symbols) is represented by the vector x of length N. The transmitter includes a cyclic prefix. The vector e is an error term related to the cyclic filtering, where the cyclic prefix does not have the same phase noise as the corresponding part of the OFDM symbol. The diagonal matrix H contains the frequency domain channel gains for each OFDM subcarrier. The phase noise of the transmitter device and the receiver device is represented by the diagonal matrices, of dimensions N x N, where the phasor el<pis diagonal element-wise exponential of the phase noise. Each phase noise matrix carries independent realizations of the phase noise processes, where each phase noise realization is unique for each OFDM symbol. The error term e can be modeled using a diagonal matrix D of dimensions N x N, where the diagonal is 0 for the non-prefix data and 1 for prefix data. Hence, the data used for the cyclic prefix is the non-zero last part of DF~1x. The cyclic filtering modeling error related to the phase noise can be formulated as e = -Fe^ - D)F HFDel^ F x

[0014] = Fei<pRx(J - D)F~1HFD(ei$TX- e^^F^x, (2) where the phase noise matrix ei^Txis the phase noise from the previous N samples including the cyclic prefix. This formulation can be derived directly by analyzing the effects of the cyclic filtering. The part of the OFDM symbol which is used for creating a cyclic prefix does not have the same phase noise as the actual cyclic prefix. Here, equation (2) can be understood as removing the cyclic parts related to the transmitter phase noise and replacing it with the corresponding part from the actual cyclic prefix with the correct phase noise. The error term e can either be included in the processing in full or in a simplified form, be treated as an error, or even be ignored by the receiver device.

[0015] In general terms, estimating the phase noise translates to estimating the random processes represented by the matrices <Z»TxandRx, using the observed signal y'. Since the observed signal carries unknown payload symbols (but where the QAM-modulation might be known), the transmitter device and the receiver device normally rely on pilot symbols embedded in the transmitted signal x, where the number of pilots is Npi|Ot« N. That is, pilot symbols are symbols with values and locations in the transmitted signal that are assumed to be known by the receiver device.

[0016] Traditionally, the phase estimation of the received signal is based on estimating the common phase rotation of all sub-carriers of the OFDM signal, denoted common phase error (CPE). The CPE can be seen as the average phase rotation of the OFDM signal. The received signal as expressed in equation (1), can be reformulated as where the transmitter and receiver phase noise realizations have been normalized with the average phase in each realization, e10^ and el0R*, withe10= el6 / el6p / . Hence, the modified phase noise matrices, el0Txand el0Rx, contain the corresponding phase noise realizations of el0Txand el0Rx, but the mean phase in each realization is close to zero. Hence, the realizations are both centered around zero. Estimating this average phase noise, e19, can, for example, be done using least square (LS) estimation or minimum mean square error (MMSE) estimation based on knowledge of the pilot symbols of the transmitted signal. The modeling in equation (3) can in some cases be seen as a scalar rotating the signal Hx. This approximation is valid if e1^* « I and elgRx« I (where I is the identity matrix), i.e., where the phase noise process realizations are small. However, by modelling the time-varying phase noise processes with one phase value, the performance will be limited by the modeling error. This is illustrated in Fig. 2, where the sum of the transmit and receive phase noise realizations are shown together with the estimate using equation (3), and an MMSE estimate. To reduce the residual error, both the model and the corresponding estimator needs to be improved.

[0017] Current techniques to address the problem of OFDM signals affected by phase noise are based on estimating the phase noise based on only the CPE (which translates to estimating the phase scalar eiein equation (3)) or performing an interpolation between the CPE of different OFDM symbols. The majority of current techniques rely on decision feedback, in some cases including even the error correction, in order to capture the modeling limitations, this leads to complex solutions, often suffering from far from optimal performance. A pilot-based constrained LS estimator based on a simplified version of equation (1) where the receiver has been allocated all the phase noise, is disclosed in "Phase Noise Estimation in OFDM: Utilizing Its Associated Spectral Geometry,” by Pramod Mathecken, Taneli Riihonen, Stefan Werner, and Risto Wichman, IEEE Transactions On Signal Processing, Vol. 64, No. 8, April 15, 2016, and in "Constrained Phase Noise Estimation in OFDM Using Scattered Pilots Without Decision Feedback,” by Pramod Mathecken, Taneli Riihonen, Stefan Werner, and Risto Wichman, IEEE Transactions On Signal Processing, Vol. 65, No. 9, May 1, 2017. The performance with the proposed estimator is good regardless of the pilot positioning, but the complexity is significant. A simplified LS estimator is also proposed as an alternative, but with far from the performance when using an MMSE estimator.

[0018] Hence, current techniques are either of low computational complexity but far from acceptable in terms of performance accuracy or offers good performance accuracy (sometimes even close to optimal) but with significant computational complexity which makes the techniques unfeasible for implementation.

[0019] There is therefore a need for low-complexity, high-performance, techniques for estimating phase noise in a communication system where only a sparse number of pilot symbols are used in the transmitted signal.

[0020] SUMMARY

[0021] An object of embodiments herein is to address the above issues and provide efficient estimation of phase noise in a communication system with low computational complexity but high performance accuracy.

[0022] A particular object is to provide efficient estimation of phase noise in a communication system where only a sparse number of pilot symbols are used in the transmitted signal.

[0023] According to a first aspect there is presented a method for compensating a received signal for phase noise. The method is performed by a receiver device. The method comprises receiving a signal over a channel from a transmitter device. The signal comprises pilot symbols and data symbols. The method comprises estimating phase noise of the received signal. The estimating is based on a signal model comprising an approximation of a complete version of the signal as transmitted by the transmitter device. The method comprises compensating the received signal for the estimated phase noise.

[0024] According to a second aspect there is presented a receiver device for compensating a received signal for phase noise. The receiver device comprises processing circuitry. The processing circuitry is configured to cause the receiver device to receive a signal over a channel from a transmitter device. The signal comprises pilot symbols and data symbols. The processing circuitry is configured to cause the receiver device to estimate phase noise of the received signal. The estimating is based on a signal model comprising an approximation of a complete version of the signal as transmitted by the transmitter device. The processing circuitry is configured to cause the receiver device to compensate the received signal for the estimated phase noise.

[0025] According to a third aspect there is presented a computer program for compensating a received signal for phase noise. The computer program comprises computer code which, when run on processing circuitry of a receiver device, causes the receiver device to perform actions. One action comprises the receiver device to receive a signal over a channel from a transmitter device. The signal comprises pilot symbols and data symbols. One action comprises the receiver device to estimate phase noise of the received signal. The estimating is based on a signal model comprising an approximation of a complete version of the signal as transmitted by the transmitter device. One action comprises the receiver device to compensate the received signal for the estimated phase noise.

[0026] According to a fourth aspect there is presented a computer program product comprising a computer program according to the third aspect and a computer readable storage medium on which the computer program is stored. The computer readable storage medium could be a non-transitory computer readable storage medium.

[0027] Advantageously, these aspects provide efficient estimation of phase noise in a communication system with low computational complexity but high performance accuracy.

[0028] Advantageously, these aspects provide efficient estimation of phase noise in a communication system where only a sparse number of pilot symbols are used in the transmitted signal.

[0029] Advantageously, these aspects enable the phase noise to be estimated with high accuracy, for example in an MMSE sense.

[0030] Advantageously, these aspects enable accurate estimation of the phase noise since the phase error can be minimized in an MMSE sense using pilot symbols. This is due to the fact that the model is reformulated compared to existing techniques and due to the fact that the estimation can consider all statistics. Advantageously, the model considers both phase noise in the transmitter device and in the receiver device and enables the phase noise to be jointly estimated using only pilot symbols. In this way, the cases of phase noise only in the transmitter device or only in the receiver device, are thereby also covered.

[0031] Other objectives, features and advantages of the enclosed embodiments will be apparent from the following detailed disclosure, from the attached dependent claims as well as from the drawings.

[0032] Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to "a / an / the element, apparatus, component, means, module, step, etc." are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, module, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated.

[0033] BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The inventive concept is now described, by way of example, with reference to the accompanying drawings, in which:

[0035] Fig. 1a is a schematic diagram illustrating communications systems according to embodiments;

[0036] Fig. 1b is a schematic diagram illustrating a transmitter device, a receiver device and how a signal transmitted therebetween is impacted according to embodiments;

[0037] Fig. 2 shows simulation results according to an example;

[0038] Figs. 3 and 4 are flowcharts of methods according to embodiments;

[0039] Fig. 5 shows simulation results according to an embodiment;

[0040] Fig. 6 is a schematic diagram showing structural units of a receiver device according to an embodiment;

[0041] Fig. 7 is a schematic diagram showing functional modules of a receiver device according to an embodiment; and

[0042] Fig. 8 shows one example of a computer program product comprising computer readable storage medium according to an embodiment.

[0043] DETAILED DESCRIPTION

[0044] The inventive concept will now be described more fully hereinafter with reference to the accompanying drawings, in which certain embodiments of the inventive concept are shown. This inventive concept may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided by way of example so that this disclosure will be thorough and complete, and will fully convey the scope of the inventive concept to those skilled in the art. Like numbers refer to like elements throughout the description. Any step or feature illustrated by dashed lines should be regarded as optional.

[0045] The embodiments disclosed herein relate to techniques for compensating a received signal for phase noise. In order to obtain such techniques, there is provided a receiver device 200, a method performed by the receiver device 200, a computer program product comprising code, for example in the form of a computer program, that when run on a receiver device 200, causes the receiver device 200 to perform the method. In some embodiments, the receiver device 200 can be any wired or wireless receiver capable of receiving OFDM modulated signals experiencing phase noise. In some embodiments, the receiver device 200 is, or is part of, a network equipment, an access node, or a user equipment.

[0046] The modified model in equation (3) can be simplified using a first-order Taylor expansion into since the phase noise realization over the OFDM symbol can be considered small with the normalization e1® factored out. The error e has, for illustrative purposes and without loss of generality, been ignored to simplify all expressions hereinafter. The error e can, if necessary, be included if deemed beneficial when estimating the phase noise. The normalization of the phase noise can be performed in several different ways, resulting in similar performance. The estimation of the phase noise can still be performed without this approximation. However, with the approximation, the resulting estimator becomes significantly simpler with respect to that the model becomes linear with the respect to the unknown parameters. The approximate received signal y, is similar to the original received signal y', as the approximation error normally is insignificant.

[0047] Since the phase noise matrices, 0Txand 0^, are diagonal, they correspond to performing an element-wise multiplication of the following vector (i.e., the vector these matrices are multiplied with). This can be reformulated by using a diagonal matrix containing the time domain signal and a vector containing the phase noise as follows: y = e‘®Hx + iei®HFRx0Tx+ iei®FRHx9Rx+ w, (5) where the diagonal matrices Rxand RHxcontain the time-domain vectors F- 1x and F-1Hx, respectively. The vectors 0Txand 0Rxare the diagonals of 0Txand 0Rx. An estimate of the channel, H, is normally available. If the transmitted signal x would have been known, an accurate estimate of the phase noise, as represented by 0Txand 0Rx, together with the unknown phase rotation, e‘® , as based on equation (5) can, for example, be performed according to state of the art (see, for example, Section 15.8 in "Statistical Signal Processing: Estimation Theory,” by Steven M Kay, Prentice Hall PTR, 20thedition, 2013). For example, one way of estimating these parameters is to first estimate the phasor, e1®, and based on this estimate, estimate the phase noise realizations 0Txand 0Rx.

[0048] However, most part of the vector x is unknown due to the unknown payload. This can be visualized by reformulating x as x = xpHot+ xpay|oad, where the vector xpi|Otcontains the pilot symbols in the pilot position and zeros where the payload symbols are situated, and where the vector xpay|oadcontains the payload (i.e., data) symbols in the payload position and zeros where the pilot symbols are situated. Hence, the pilot and payload vectors are orthogonal to each other; xp|Otxpay|oad= 0. Using this notation, equation (5) can be formulated as noise, u

[0049] Since the payload part is unknown to the receiver device, it could by the receiver device 200 be treated as a noise (here denoted u) during the phase noise estimation.

[0050] The phase noise can be mapped onto two different (orthogonal) subspaces, represented by the matricesRxpiiot / RHxpilotand RXpayload / RHxpayload. The sparse pilot subspace, represented by the matrices RXpi|ot / RHXpilot, has a rank (i.e., degrees of freedom) which is significantly lower than the size of the OFDM symbol, and the rank is Npiiot « Npay|oad< N. The phase noise has N degrees of freedom (i.e., it can only be uniquely represented by a vector of length N), and when mapping it on the rank Npi|Otmatrices RXpi|ot / RHXpi|ot, information is lost. In other words, when mapping the phase noise onto RXpi|ot / RHXpi|ot, the resulting mapped phase noise will have Npi|Otdegrees of freedom, even though the resulting vector is of length N, and the information lost in the mapping using the model (as given by equation (6)), cannot be recovered.

[0051] One way to understand the aspects of equation (6) is to view the Npi|Otphase modulated pilot symbols as being embedded in strong noise coming from xpay|oad. All phase modulation ending up in the payload frequency slots will be lost since it drowns in the strong unknown payload (represented by u in equation (6)). If the pilot symbols are distributed, an estimator will be unable to estimate the phase noise over a wide bandwidth, and a trend and average of the actual phase noise would be the resulting estimate regardless of the number of pilot symbols. If the pilot symbols are, instead, placed consecutive in frequency, the estimator would perform better, but still far from having high accuracy. The performance of a phase noise estimator should therefore not rely on the positioning of the pilot symbols. The herein disclosed embodiments are based on finding a better model to avoid the aforementioned phase noise mapping.

[0052] In more detail, at least some of the herein disclosed embodiments are based on including an approximation, or estimate, of the complete transmitted signal in the signal model. In other words, all transmitted QAM symbols, x, of which most have unknown values to the receiver device are used in the modeling. The resulting approximation, estimation error, has statistics that can be derived.

[0053] Fig. 3 is a flowchart illustrating embodiments of methods for compensating a received signal for phase noise. The methods are performed by the receiver device 200. The methods are advantageously provided as computer programs.

[0054] S102: The receiver device 200 receives a signal y. The signal y is received over a channel H. The channel H could be a wireless channel, an optical fiber channel, or other type of wired channel. The signal y is received from a transmitter device 100. The signal comprises pilot symbols and data symbols.

[0055] S104: The receiver device 200 estimates phase noise 0Tx, 0Rxof the received signal. The estimation is based on a signal model. The signal model comprises an approximation x of a complete version of the signal x as transmitted by the transmitter device 200.

[0056] S106: The receiver device 200 compensates the received signal for the estimated phase noise.

[0057] Thereby, by reformulating the observed signal model in equation (1) to use an approximation of the transmitted signal, x, the phase noise can be accurately estimated using available low-complexity estimation methods, regardless of the positions of the pilot symbols in the received signal.

[0058] Embodiments relating to further details of compensating a received signal for phase noise as performed by the receiver device 200 will now be disclosed.

[0059] In general terms, since the transmitted signal only comprises a few pilot symbols, most transmitted symbols (i.e., the data symbols) are treated as unknown in the modelling. In some embodiments, in the signal model, the data symbols are treated as having unknown values.

[0060] In some aspects, the unknown symbols are replaced with something that has limited noise. In some examples, the unknown symbols are replaced with estimates of the data symbols. That is, in some embodiments, in the signal model and as part of estimating the phase noise, the data symbols are replaced by an estimate of the data symbols based on the received signal.

[0061] Since the signal model comprises an approximation x of the complete version of the signal x as transmitted by the transmitter device 200, the positions of the pilot signals in the transmitted signal x becomes irrelevant. Correspondingly, in some embodiments, the signal model is transparent with respect to locations of the pilot symbols in the received signal.

[0062] Further, since the signal model comprises an approximation x of the complete version of the signal x as transmitted by the transmitter device 200, the phase noise and the unknown phase can hereby be accurately estimated using standard methods. In some embodiments, the phase noise is estimated using a minimum mean square error estimator. For example, a linear MMSE estimator could be based on the known statistics of the phase noise (normally known), the known statistics of the AWGN, and the derived statistics of the approximation error.

[0063] In some aspects, the model uses statistics of the phase noise, statistics of the AWGN, and statistics of the approximation error. In particular, some embodiments, in the signal model, the received signal further is modeled to be a function of statistics of the phase noise, statistics of noise of the channel, and statistics of approximation error of the approximation x. In some examples, the statistics of the estimation error is modelled as zero. In further detail, as disclosed above, the herein disclosed embodiments are based on finding a better model to avoid the aforementioned phase noise mapping. In some aspects, this boils down to replacing the low rank matrices RXpi|otand RHxpi|Otwith some appropriate full rank matrices. This can be achieved by using approximations of the transmitted signal x. By observing the model in equation (5), an approximation (unbiased estimation) of x and Hx is H-1y and y (assuming that both the AWGN and the phase noise have zero mean). Using the estimates, denoted x and Hx, equation (5), can be reformulated as by adding and subtracting the terms containing the estimates, i.e., no additional modeling approximations and the equality still holds. The resulting model can be expressed as

[0064] Therefore, in some embodiments, in the signal model, the received signal y is modeled as in equation (8), where e1® represents a mean value of the phase noise, H is a frequency domain representation of the channel, x is the signal as transmitted, Rs= diag{F-1x}, 0Txrepresents the phase noise as caused by the transmitter device 100, RH£ = diag{HF- 1x}, 0Rxrepresents the phase noise as caused by the receiver device 200, n represents an approximation error of the approximation x, w represents noise of the channel, F is a forward discrete Fourier transform, and F-1is an inverse discrete Fourier transform. Here, diag{z} is a diagonal matrix, where the elements on the diagonal are given by the vector z.

[0065] The statistics of the approximation error n can be derived using, for example, equation (7).

[0066] Using an approximation, x, of the transmitted signal, the phase noise is mapped without losing any degrees of freedom since the matrices Rsand RHSare full rank N. That is, in some embodiments, Rsand RHSare full rank matrices. In some aspects, equation (8) can be seen as a system of N equations, where any number of equations can be used for estimating the phase noise. The used number of equations can, for example, be the number of pilot symbols, Npi|Ot. Therefore, in some embodiments, the received signal comprises Npi|Otnumber of pilot signals, the signal model is representable by a system of equations, and the phase noise is estimated from Npi|Otof the equations.

[0067] Further aspects, embodiments, and examples of how to estimate the phase noise as in step S104 (i.e., based on ae signal model that comprises an approximation x of a complete version of the signal x as transmitted by the transmitter device 200) will be disclosed next with reference to the flowchart of Fig. 4.

[0068] S104-2: The receiver device 200 estimates the transmitted signal x. This estimate is represented by the approximation x.

[0069] S104-4: The receiver device 200 formulates statistics of the approximation error (i.e., of the error between x and x. Hence, in some embodiments, in the signal model and as part of estimating the phase noise, an approximation error of the approximation x is iteratively estimated. Only statistics can be estimated, derived, or otherwise formulated since the transmitted signal x comprises data symbols that per se are not known to the receiver device 200.

[0070] S104-6: The receiver device 200 estimates the phase noise (with or without decisions).

[0071] Here, the decision is on the payload symbols (i.e., on the data symbols of the received signal), as an example, equation (8) can be reformulated such that the vector x contains pilots, decisions, and payload; x = xpi|Ot+xdec +xpayioad' Since the payload symbols are corrupted by noise, the decisions might be incorrect. To overcome this, the decision-based approach can, for example, be implemented using a sequential approach, where several (optional) possible decisions can be made for each data symbol. Hence, in some embodiments, a sequence of decisions is taken on at least some of the data symbols when the data symbols are iteratively estimated. The different decisions can be modeled as a tree, where the branches in the tree with the best performance criteria becomes the (final) decision. Hence, in some embodiments, the sequence of decisions is represented by branches in a tree structure, where each branch in the tree structure represents one of the decisions, and, in the signal model and as part of estimating the phase noise, the data symbols are represented by the branches, that according to a performance criterion, yield best performance. One such performance criterion for evaluating the different branches is the error signal created by the difference between the compensated input signal and the symbol decisions related to the compensated signal. Another such performance criterion is the error signal created by the difference between the compensated received signal and the pilot symbols, where the difference is evaluated only for the pilot symbols. Step S104-2 can then be entered again, where a new estimation of the transmitted signal x is performed based on the phase noise as estimated. Alternatively, step S104-2 is only entered again after the compensation of the received signal has been performed in step S106 such that the new estimation of the transmitted signal x can be performed based on the received signal as compensated. Hence, in some embodiments, in the signal model and as part of estimating the phase noise, the data symbols are iteratively estimated.

[0072] Fig. 5 shows the sum of the transmit and receive phase noise realizations together with the estimate using equations (6) and (8). It can be seen that the performance is better than in Fig. 2. The performance is better in the sense that the estimated phase noise becomes closer to the true phase noise.

[0073] Fig. 6 schematically illustrates, in terms of a number of structural units, the components of a receiver device 200 according to an embodiment. Processing circuitry 210 is provided using any combination of one or more of a suitable central processing unit (CPU), multiprocessor, microcontroller, digital signal processor (DSP), etc., capable of executing software instructions stored in a computer program product 810 (as in Fig. 8), e.g. in the form of a storage medium 230. The processing circuitry 210 may further be provided as at least one application specific integrated circuit (ASIC), or field programmable gate array (FPGA).

[0074] Particularly, the processing circuitry 210 is configured to cause the receiver device 200 to perform a set of operations, or steps, as disclosed above. For example, the storage medium 230 may store the set of operations, and the processing circuitry 210 may be configured to retrieve the set of operations from the storage medium 230 to cause the receiver device 200 to perform the set of operations. The set of operations may be provided as a set of executable instructions.

[0075] Thus the processing circuitry 210 is thereby arranged to execute methods as herein disclosed. The storage medium 230 may also comprise persistent storage, which, for example, can be any single one or combination of magnetic memory, optical memory, solid state memory or even remotely mounted memory. The receiver device 200 may further comprise a communications (comm.) interface 220 at least configured for communications with other entities, functions, nodes, and devices, such as the transmitter device 100. As such the communications interface 220 may comprise one or more transmitters and receivers, comprising analogue and digital components. The processing circuitry 210 controls the general operation of the receiver device 200 e.g. by sending data and control signals to the communications interface 220 and the storage medium 230, by receiving data and reports from the communications interface 220, and by retrieving data and instructions from the storage medium 230. Other components, as well as the related functionality, of the receiver device 200 are omitted in order not to obscure the concepts presented herein.

[0076] Fig. 7 schematically illustrates, in terms of a number of functional modules, the components of a receiver device 200 according to an embodiment. The receiver device 200 of Fig. 7 comprises a number of functional modules; a receive module 210a configured to perform step S102, an estimate module 210b configured to perform step S104, and a compensate (Comp.) module 210c configured to perform step S106. The receiver device 200 of Fig. 7 may further comprise a number of optional functional modules, as represented by functional module 21 Od. In general terms, each functional module 210a:21 Od may in one embodiment be implemented only in hardware and in another embodiment with the help of software, i.e., the latter embodiment having computer program instructions stored on the storage medium 230 which when run on the processing circuitry makes the receiver device 200 perform the corresponding steps mentioned above in conjunction with Fig 7. It should also be mentioned that even though the modules correspond to parts of a computer program, they do not need to be separate modules therein, but the way in which they are implemented in software is dependent on the programming language used. Preferably, one or more or all functional modules 210a:21 Od may be implemented by the processing circuitry 210, possibly in cooperation with the communications interface 220 and / or the storage medium 230. The processing circuitry 210 may thus be configured to from the storage medium 230 fetch instructions as provided by a functional module 210a:210d and to execute these instructions, thereby performing any steps as disclosed herein.

[0077] The receiver device 200 may be provided as a standalone device or as a part of at least one further device. For example, as disclosed above, the receiver device 200 might be, or be part of, a network equipment, an access node, or a user equipment. In case the receiver device 200 is, or is part of, a network equipment or an access node, the network equipment or an access node, may either be part of the same network part (such as the radio access network or the core network) or may be spread between at least two such network parts. In general terms, instructions that are required to be performed in real time may be performed in a device, or node, operatively closer to the cell than instructions that are not required to be performed in real time. A first portion of the instructions performed by the receiver device 200 may be executed in a first device, and a second portion of the of the instructions performed by the receiver device 200 may be executed in a second device; the herein disclosed embodiments are not limited to any particular number of devices on which the instructions performed by the receiver device 200 may be executed. Hence, the methods according to the herein disclosed embodiments are suitable to be performed by a receiver device 200 residing in a cloud computational environment. Therefore, although a single processing circuitry 210 is illustrated in Fig. 6 the processing circuitry 210 may be distributed among a plurality of devices, or nodes. The same applies to the functional modules 210a:21 Od of Fig. 7 and the computer program 820 of Fig. 8.

[0078] Some (radio) access network architectures define network nodes (or gNBs) comprising multiple component parts or nodes: a central unit (CU), one or more distributed units (DUs), and one or more radio units (RUs). Here, the receiver device 200 could be implemented either in the CU, the Dus, or the RUs. The protocol layer stack of the network node is divided between the CU, the DUs and the RUs, with one or more lower layers of the stack implemented in the RUs, and one or more higher layers of the stack implemented in the CU and / or DUs. The CU is coupled to the DUs via a fronthaul higher layer split (HLS) network; the CU / DUs are connected to the RUs via a fronthaul lower-layer split (LLS) network. The DU may be combined with the CU in some embodiments, where a combined DU / CU may be referred to as a CU or simply a baseband unit. A communication link for communication of user data messages or packets between the RU and the baseband unit, CU, or DU is referred to as a fronthaul network or interface. Messages or packets may be transmitted from the network node in the downlink (i.e., from the CU to the RU) or received by the network node in the uplink (i.e., from the RU to the CU).

[0079] Fig. 8 shows one example of a computer program product 810 comprising computer readable storage medium 830. On this computer readable storage medium 830, a computer program 820 can be stored, which computer program 820 can cause the processing circuitry 210 and thereto operatively coupled entities and devices, such as the communications interface 220 and the storage medium 230, to execute methods according to embodiments described herein. The computer program 820 and / or computer program product 810 may thus provide means for performing any steps as herein disclosed.

[0080] In the example of Fig. 8, the computer program product 810 is illustrated as an optical disc, such as a CD (compact disc) or a DVD (digital versatile disc) or a Blu-Ray disc. The computer program product 810 could also be embodied as a memory, such as a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), or an electrically erasable programmable read-only memory (EEPROM) and more particularly as a non-volatile storage medium of a device in an external memory such as a USB (Universal Serial Bus) memory or a Flash memory, such as a compact Flash memory. Thus, while the computer program 820 is here schematically shown as a track on the depicted optical disk, the computer program 820 can be stored in any way which is suitable for the computer program product 810.

[0081] The inventive concept has mainly been described above with reference to a few embodiments. However, as is readily appreciated by a person skilled in the art, other embodiments than the ones disclosed above are equally possible within the scope of the inventive concept, as defined by the appended patent claims.

Claims

CLAIMS1. A method for compensating a received signal for phase noise, the method being performed by a receiver device (200), the method comprising: receiving (S102) a signal y over a channel H from a transmitter device (100), the signal comprising pilot symbols and data symbols; estimating (S104) phase noise 0Tx, 0Rxof the received signal, wherein the estimating is based on a signal model comprising an approximation % of a complete version of the signal x as transmitted by the transmitter device (200); and compensating (S106) the received signal for the estimated phase noise.

2. The method according to claim 1 , wherein, in the signal model, the data symbols are treated as having unknown values.

3. The method according to claim 1 , wherein, in the signal model and as part of estimating the phase noise, the data symbols are replaced by an estimate of the data symbols based on the received signal.

4. The method according to claim 1 , wherein the signal model is transparent with respect to locations of the pilot symbols in the received signal.

5. The method according to claim 1 , wherein, in the signal model, the received signal further is modeled to be a function of statistics of the phase noise, statistics of noise of the channel, and statistics of approximation error of the approximation x.

6. The method according to claim 1 , wherein the received signal comprises Npi|Otnumber of pilot signals, wherein the signal model is representable by a system of equations, and wherein the phase noise is estimated from JVpjiot of the equations.

7. The method according to claim 1 , wherein, in the signal model and as part of estimating the phase noise, the data symbols are iteratively estimated.

8. The method according to claim 7, wherein a sequence of decisions is taken on at least some of the data symbols when the data symbols are iteratively estimated.

9. The method according to claim 8, wherein the sequence of decisions is represented by branches in a tree structure, where each branch in the tree structure represents one of the decisions, and wherein, in the signal model and as part of estimating the phase noise, the data symbols are represented by the branches, that according to a performance criterion, yield best performance.

10. The method according to claim 1, wherein, in the signal model and as part of estimating the phase noise, an approximation error of the approximation x is iteratively estimated.11 . The method according to claim 1 , wherein the phase noise is estimated using a minimum mean square error estimator.

12. The method according to claim 1, wherein, in the signal model, the received signal y is modeled as:where ei0represents a mean value of the phase noise, H is a frequency domain representation of the channel, x is the signal as transmitted, Rx= diag{F-1%}, 0Txrepresents the phase noise as caused by the transmitter device (100), RHx= diag{HF-1%}, 0Rxrepresents the phase noise as caused by the receiver device (200), n represents an approximation error of the approximation x, w represents noise of the channel, F is a forward discrete Fourier transform, and F-1is an inverse discrete Fourier transform.

13. The method according to claim 12, wherein Rxand RHxare full rank matrices.

14. The method according to any preceding claim, wherein the receiver device (200) is, or is part of, a network equipment, an access node, or a user equipment.

15. A receiver device (200) for compensating a received signal for phase noise, the receiver device (200) comprising processing circuitry (210), the processing circuitry being configured to cause the receiver device (200) to: receive a signal y over a channel H from a transmitter device (100), the signal comprising pilot symbols and data symbols; estimate phase noise 0Tx, 0Rxof the received signal, wherein the estimating is based on a signal model comprising an approximation x of a complete version of the signal x as transmitted by the transmitter device (200); and compensate the received signal for the estimated phase noise.

16. The receiver device (200) according to claim 15, wherein, in the signal model, the data symbols are treated as having unknown values.

17. The receiver device (200) according to claim 15, wherein, in the signal model and as part of estimating the phase noise, the data symbols are replaced by an estimate of the data symbols based on the received signal.

18. The receiver device (200) according to claim 15, wherein the signal model is transparent with respect to locations of the pilot symbols in the received signal.

19. The receiver device (200) according to claim 15, wherein, in the signal model, the received signal further is modeled to be a function of statistics of the phase noise, statistics of noise of the channel, and statistics of approximation error of the approximation x.

20. The receiver device (200) according to claim 15, wherein the received signal comprises Npi|Otnumber of pilot signals, wherein the signal model is representable by a system of equations, and wherein the phase noise is estimated from Npi|Otof the equations.

21. The receiver device (200) according to claim 15, wherein, in the signal model and as part of estimating the phase noise, the data symbols are iteratively estimated.

22. The receiver device (200) according to claim 21 , wherein a sequence of decisions is taken on at least some of the data symbols when the data symbols are iteratively estimated.

23. The receiver device (200) according to claim 22, wherein the sequence of decisions is represented by branches in a tree structure, where each branch in the tree structure represents one of the decisions, and wherein, in the signal model and as part of estimating the phase noise, the data symbols are represented by the branches, that according to a performance criterion, yield best performance.

24. The receiver device (200) according to claim 15, wherein, in the signal model and as part of estimating the phase noise, an approximation error of the approximation x is iteratively estimated.

25. The receiver device (200) according to claim 15, wherein the phase noise is estimated using a minimum mean square error estimator.

26. The receiver device (200) according to claim 15, wherein, in the signal model, the received signal y is modeled as:where eierepresents a mean value of the phase noise, H is a frequency domain representation of the channel, x is the signal as transmitted, Rx= diag{F-1%}, 0Txrepresents the phase noise as caused by the transmitter device (100), RHx= diag{HF-1%}, 0Rxrepresents the phase noise as caused by the receiver device (200), n represents an approximation error of the approximation x, w represents noise of the channel, F is a forward discrete Fourier transform, and F-1is an inverse discrete Fourier transform.

27. The receiver device (200) according to claim 26, wherein R* and RHxare full rank matrices.

28. The receiver device (200) according to any of claims 15 to 27, wherein the receiver device (200) is, or is part of, a network equipment, an access node, or a user equipment.

29. A computer program (820) for compensating a received signal for phase noise, the computer program comprising computer code which, when run on processing circuitry (210) of a receiver device (200), causes the receiver device (200) to: receive (S102) a signal y over a channel H from a transmitter device (100), the signal comprising pilot symbols and data symbols; estimate (S104) phase noise 0Tx, 0Rxof the received signal, wherein the estimating is based on a signal model comprising an approximation % of a complete version of the signal x as transmitted by the transmitter device (200); and compensate (S106) the received signal for the estimated phase noise.

30. A computer program product (810) comprising a computer program (820) according to claim 29, and a computer readable storage medium (830) on which the computer program is stored.

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