WO2023249521A1

WO2023249521A1 - Iterative channel estimation and hardware impairment estimation in a radio transceiver device

Info

Publication number: WO2023249521A1
Application number: PCT/SE2022/050610
Authority: WO
Inventors: Hamed FARHADI
Original assignee: Telefonaktiebolaget Lm Ericsson (Publ)
Priority date: 2022-06-21
Filing date: 2022-06-21
Publication date: 2023-12-28

Abstract

There is provided techniques for iterative channel estimation and hardware impairment estimation in a radio transceiver device. A method comprises receiving, over a radio channel to be estimated, a pilot signal from another radio transceiver device. The method comprises iteratively and alternately estimating the radio channeland estimating hardware impairment for the radio transceiver device by, in each iteration round, first obtaining a channel estimate and then obtaining a hardware impairment estimate.

Description

ITERATIVE CHANNEL ESTIMATION AND HARDWARE IMPAIRMENT ESTIMATION IN A RADIO TRANSCEIVER DEVICE

TECHNICAL FIELD

Embodiments presented herein relate to a method, a radio transceiver device, a computer program, and a computer program product for iterative channel estimation and hardware impairment estimation in the radio transceiver device.

BACKGROUND

Communication systems in which advanced antenna systems (AASs) are used can benefit from diversity gain, or multiplexing gain. This further requires the application of proper precoding at the transmitter side and signal detection at the receiver side for multi-antenna transmission and reception.

Imperfections in radio frequency (RF) hardware in the transmitter and the receiver contribute to distortions in the transmitted signal and the received signal. The overall RF impairments are typically measured using distortion measures, such as any of the error-vector-magnitude (EVM), Adjacent Channel Leakage Ratio (ACLR), and Intermodulation Distortion (IMD). Distortions due to RF hardware impairments impact the quality of both payload data transmissions and control signal transmissions.

Reference is next made to Fig. 1(a) for an illustration of how RF hardware impairments impact the quality of payload data transmission.

In general terms, RF hardware impairments introduce distortions to transmitted signals for data communication and degrades the quality of the received signal at the receiver and hence reduce data throughput. In Fig. 1(a) is shown the data throughput of a multi-antenna system comprising a two-antenna network node and a two- antenna user equipment. The data throughput is shown for the downlink in the presence of RF hardware impairments. It can be seen that hardware impairments degrade throughput, and the impact is more severe in the high-SNR regime (where SNR is short for signal to noise ratio).

Reference is next made to Fig. 1(b) for an illustration of how RF hardware impairments impact the quality of control signal transmissions. In general terms, RF hardware impairments introduce distortions to transmitted reference signals, e.g., demodulation reference signals (DMRS) are used for channel estimation. RF hardware impairments hence degrade the quality of channel estimation at the receiver. In Fig. 1(b) is shown the quality of channel estimation measured in terms of mean square error (MSE) versus SNR in the same downlink scenario as in Fig. 1(a) for different hardware qualities as measured according to the EVM. It can be seen that in the high-SNR regime, the channel estimation error increases by the level of RF hardware impairments being increased.

Channel state information is needed for precoding and/or detection of signals in multi-antenna systems. Channel state information can be acquired by applying different types of channel estimation techniques. Imperfect channel estimation generally leads to channel estimation errors that could degrade the performance of the multi-antenna system.

Channel estimation might therefore be regarded as an important aspect for the operation of any multi-antenna systems, and the quality of the channel estimation might impact the performance of the advance antenna systems. This was shown in Fig. 2(b). However, existing channel estimation techniques are mainly assuming that the underlying RF hardware is ideal (i.e., not impaired) and hence that reference signals (as well as other signals) are transmitted and received without distortion. This degrades the performance of existing channel estimation techniques. The performance degradation is more severe especially in scenarios in which RF hardware impairments are more severe, e.g., transmission at high frequency bands where there is high phase noise, or energy efficient transmissions for which the power amplifier is required to operate in nonlinear operating point. Another example is in coverage limited scenarios, where the transmit power needs to be increased, hence leading to nonlinear operation of the power amplifiers. Yet another example concerns the use of low cost transmitters with low resolution digital-to-analog converters that contribute to distortion due to the quantization noise.

An example method for channel estimation in the presence of hardware nonlinearity is proposed in the paper “Channel Estimation in Massive MIMO under Hardware Non-Linearities: Bayesian Methods versus Deep Learning” by Ozlem Tugfe Demir and Emil Bjornson as available at https://arxiv.org/pdf/1911.07316.pdf as per 5 June 2022. The proposed method is limited to hardware nonlinearity. Other hardware impairments are not considered.

Hence, there is still a need for improved techniques for channel estimation in the presence of hardware impairments.

SUMMARY

An object of embodiments herein is to address the above issues and provide efficient techniques for channel estimation in the presence of hardware impairments.

According to a first aspect there is presented a method for iterative channel estimation and hardware impairment estimation in a radio transceiver device. The method comprises receiving, over a radio channel to be estimated, a pilot signal from another radio transceiver device. The method comprises iteratively and alternately estimating the radio channel and estimating hardware impairment for the radio transceiver device by, in each iteration round, first obtaining a channel estimate and then obtaining a hardware impairment estimate. The channel estimate for a current iteration round is a function of (ia) a first estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device, and of (ib) knowledge of the pilot signal. For an initial iteration round the first estimate of the pilot signal further is based on a given hardware impairment estimate, and for any other iteration round further is based on the hardware impairment estimate for a previous iteration round. The hardware impairment estimate for the current iteration round is a function of (iia) a second estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device, and of (iib) the knowledge of the pilot signal. The second estimate of the pilot signal further is based on the channel estimate for the current iteration round.

According to a second aspect there is presented a radio transceiver device for iterative channel estimation and hardware impairment estimation. The radio transceiver device comprises processing circuitry. The processing circuitry is configured to cause the radio transceiver device to receive, over a radio channel to be estimated, a pilot signal from another radio transceiver device. The processing circuitry is configured to cause the radio transceiver device to iteratively and alternately estimate the radio channel and estimate hardware impairment for the radio transceiver device by, in each iteration round, first obtaining a channel estimate and then obtaining a hardware impairment estimate. The channel estimate for a current iteration round is a function of (ia) a first estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device, and of (ib) knowledge of the pilot signal. For an initial iteration round the first estimate of the pilot signal further is based on a given hardware impairment estimate, and for any other iteration round further is based on the hardware impairment estimate for a previous iteration round. The hardware impairment estimate for the current iteration round is a function of (iia) a second estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device, and of (iib) the knowledge of the pilot signal. The second estimate of the pilot signal further is based on the channel estimate for the current iteration round.

According to a third aspect there is presented a radio transceiver device for iterative channel estimation and hardware impairment estimation. The radio transceiver device comprises a receive module configured to receive, over a radio channel to be estimated, a pilot signal from another radio transceiver device. The radio transceiver device comprises estimate modules configured to iteratively and alternately estimate the radio channel and estimate hardware impairment for the radio transceiver device by, in each iteration round, first obtaining a channel estimate and then obtaining a hardware impairment estimate. The channel estimate for a current iteration round is a function of (ia) a first estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device, and of (ib) knowledge of the pilot signal. For an initial iteration round the first estimate of the pilot signal further is based on a given hardware impairment estimate, and for any other iteration round further is based on the hardware impairment estimate for a previous iteration round. The hardware impairment estimate for the current iteration round is a function of (iia) a second estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device, and of (iib) the knowledge of the pilot signal. The second estimate of the pilot signal further is based on the channel estimate for the current iteration round.

According to a fourth aspect there is presented a computer program for iterative channel estimation and hardware impairment estimation in a radio transceiver device, the computer program comprising computer program code which, when run on the radio transceiver device, causes the radio transceiver device to perform a method according to the first aspect.

According to a fifth aspect there is presented a computer program product comprising a computer program according to the fourth 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.

Advantageously, these aspects provide accurate channel estimation in the presence of hardware impairments.

Advantageously, these aspects improve the quality of channel estimation compared to state of the art. As a result thereof, these aspects can be used to improve the spectral efficiency and throughput of multi-antenna systems.

Advantageously, these aspects enable the allocated radio resources for pilot signal transmission can be reduced, leading to improved spectral efficiency and energy efficiency.

Advantageously, with reference again to Figs. 1(a) and 1(b), these aspects improve the performance in Fig. 1(b) which in turn improves the performance in Fig. 1(a). this is since more accurate channel estimate will lead to better selection of modulation and coding scheme, etc., which, in turn, will improve the throughput.

Advantageously, these aspects enable accurate channel estimation in scenarios with major RF hardware impairments, e.g., for:

- transmissions at high frequency bands with high phase noise,

- energy efficient transmission with power amplifier operating at nonlinear operating points, e.g., with no or very limited back-off,

- energy efficient transmission with high quantization noise due to low resolution digital-to-analog conversion of baseband signals, e.g., in high frequency bands, such as millimeter wave (mmWave) or THz communications, where low-cost hardware components would be used for data conversions with limited precision (e.g., using a i-bit digital-to-analog converter), and - transmission at coverage limited scenarios that require transmit power to be increased, hence enabling the power amplifier to operate at a (more) nonlinear operating point.

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.

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.

BRIEF DESCRIPTION OF THE DRAWINGS

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

Fig. 1 show simulation results according to examples;

Fig. 2 is a schematic diagram illustrating a communications network according to embodiments;

Fig. 3 is a flowchart of methods according to embodiments;

Fig. 4 schematically illustrates iterative channel estimation and hardware impairment estimation in a radio transceiver device according to an embodiment;

Fig. 5 is a schematic diagram showing functional units of a radio transceiver device according to an embodiment;

Fig. 6 is a schematic diagram showing functional modules of a radio transceiver device according to an embodiment; and

Fig. 7 shows one example of a computer program product comprising computer readable storage medium according to an embodiment. DETAILED DESCRIPTION

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.

Fig. 2 is a schematic diagram illustrating a communication network loo where embodiments presented herein can be applied. The communication network 100 could be a third generation (3G) telecommunications network, a fourth generation (4G) telecommunications network, a fifth (5G) telecommunications network, a sixth (6G) telecommunications network, and support any third generation partnership project (3GPP) telecommunications standard.

The communication network 100 comprises a transmission and reception point 140 configured to provide network access to user equipment 150 in an (radio) access network no over a radio channel 160. The access network no is operatively connected to a core network 120. The core network 120 is in turn operatively connected to a service network 130, such as the Internet. The user equipment 150 is thereby, via the transmission and reception point 140, enabled to access services of, and exchange data with, the service network 130.

Operation of the transmission and reception point 140 is controlled by a network node. The network node might be part of, collocated with, or integrated with the transmission and reception point 140. Examples of network nodes are (radio) access network nodes, radio base stations, base transceiver stations, Node Bs (NBs), evolved Node Bs (eNBs), gNBs, access points, access nodes, and integrated access and backhaul nodes. Examples of user equipment 150 are wireless devices, mobile stations, mobile phones, handsets, wireless local loop phones, smartphones, laptop computers, tablet computers, network equipped sensors, network equipped vehicles, and so-called Internet of Things devices. Each of the transmission and reception point 140 and the user equipment 150 comprises a respective radio transceiver device 200a, 200b. Hence, in some examples, each radio transceiver device 200a, 200b is part of a transmission and reception point 140 or a user equipment 150. However, the herein disclosed embodiments are not limited to the configuration of the communication network 100. As a first alternative example, each radio transceiver device 200a, 200b might part of a respective transmission and reception point 140. As a second alternative example, each radio transceiver device 200a, 200b might part of a respective user equipment 150. Radio transceiver device 200a might be referred to as a first radio transceiver device and radio transceiver device 200b might be referred to as a second radio transceiver device. However, this does not imply any hierarchical relation between the radio transceiver devices 200a, 200b.

As noted above, there is still a need for improved techniques for channel estimation in the presence of hardware impairments.

It is here assumed that hardware impairments are present in one of the radio transceiver device 200a, 200b, and in particular in the radio transceiver device 200a, 200b receiving a pilot signal from the other radio transceiver device 200b, 200a. A turbo-like receiver technique is proposed for a radio transceiver device 200a, 200b to provide iterative channel estimation and hardware imperfection estimation. The proposed technique can be used to improve the quality of channel estimation in the presence of RF hardware imperfections in the radio transceiver device 200a, 200b.

The embodiments disclosed herein in particular relate to techniques for iterative channel estimation and hardware impairment estimation in a radio transceiver device 200a, 200b. In order to obtain such techniques, there is provided a radio transceiver device 200a, 200b, a method performed by the radio transceiver device 200a, 200b, a computer program product comprising code, for example in the form of a computer program, that when run on a radio transceiver device 200a, 200b, causes the radio transceiver device 200a, 200b to perform the method.

Parallel reference will next be made to Fig. 3 and Fig. 4. Fig. 3 is a flowchart illustrating embodiments of methods for iterative channel estimation and hardware impairment estimation in a radio transceiver device 200a, 200b. The methods are performed by the radio transceiver device 200a, 200b. The methods are advantageously provided as computer programs 720.

In Fig. 4 is shown a block diagram of the (first) radio transceiver device 200a, 200b according to an embodiment. The radio transceiver device 200a, 200b comprises a channel estimation block 410 and a hardware estimation block 420. Signals and estimates shown in the Fig. 4 will be defined and explained below in conjunction with a description of the operations for iterative channel estimation and hardware impairment estimation in the radio transceiver device 200a, 200b.

Another (second) radio transceiver device 200b, 200a is assumed to send a pilot signal that is known to the (first) radio transceiver device 200a, 200b. The radio transceiver device 200a, 200b is thus assumed to know the structure of the pilot signal as well as in which time/frequency resources the pilot signal is transmitted. The pilot signal might be transmitted either in the uplink, or in the downlink, or over a sidelink, depending on the implementation of each of the radio transceiver devices 200a, 200b. Hence, the radio transceiver device 200a, 200b is configured to perform step S102.

S102: The radio transceiver device 200a, 200b receives, over the radio channel 160 to be estimated, a pilot signal from the radio transceiver device 200b, 200a.

S104, S108: The radio channel and the hardware impairment for the radio transceiver device 200a, 200b are iteratively and alternately estimated.

In general terms, in each iteration round, the channel estimation is updated based on an estimate of the hardware impairment and the hardware impairment estimation is updated based on an estimate of the radio channel. In particular, in each iteration round, a channel estimate is first obtained, and a hardware impairment estimate is then obtained.

The channel estimate for a current iteration round is a function of (ia) a first estimate of the pilot signal as based on the pilot signal received from the other radio transceiver device 200b, 200a, and of (ib) knowledge of the pilot signal.

The knowledge of the pilot signal refers to the fact that the radio transceiver device 200a, 200b is assumed to know which pilot signal is transmitted from the radio transceiver device 200b, 200a. Hence, all the properties (such as which time/frequency resource the pilot signal occupies, which transmission power is used for the pilot signal, etc.) of the pilot signal as transmitted from the radio transceiver device 200b, 200a is known by the radio transceiver device 200a, 200b.

For the initial iteration round, the first estimate of the pilot signal further is based on a given hardware impairment estimate. For any other iteration round, the first estimate of the pilot signal further is based on the hardware impairment estimate for a previous iteration round.

The hardware impairment estimate for the current iteration round is a function of (iia) a second estimate of the pilot signal as based on the pilot signal received from the other radio transceiver device 200b, 200a, and of (iib) the knowledge of the pilot signal. The second estimate of the pilot signal further is based on the channel estimate for the current iteration round.

Hence, in each iteration round, two estimates of the pilot signal are used. The first estimate of the pilot signal is used for the channel estimate whereas the second estimate of the pilot signal is used for the hardware impairment estimate.

For the initial iteration round the radio transceiver device 200a, 200b thus performs channel estimation assuming that its hardware is ideal and there are no hardware impairments. The receiver in the radio transceiver device 200a, 200b can apply techniques such as a least square (LS) estimator, or a linear minimum mean squared error (LMMSE) estimator to estimate the radio channel based on the known pilot signals.

The radio transceiver device 200a, 200b uses the channel estimate to obtain an estimate of the transmitted signal, subject to hardware impairments, where the transmitted signal is the pilot signal as impacted by the hardware impairment in the radio transceiver device 200a, 200b. Different examples of hardware impairment will be disclosed below. An estimate of the pilot signal subject to hardware impairment will thus be obtained. The radio channel is assumed to be equal to the previous channel estimate. An LS estimator or LMMSE estimator, or similar techniques, can be applied to obtain an estimate of the distorted transmitted signal. The radio transceiver device 200a, 200b compares the estimated pilot signal and the transmitted pilot signal (which the radio transceiver device 200a, 200b has knowledge pf) to obtain an estimate of distortion due to the hardware impairment.

The hardware impairment estimate is then for the next iteration round used when updating the channel estimation. In more detail, for the second, third, fourth, etc. iteration round, the radio transceiver device 200a, 200b performs channel estimation assuming based on the hardware impairment estimate for the previous iteration round.

Embodiments relating to further details of iterative channel estimation and hardware impairment estimation in a radio transceiver device 200a, 200b as performed by the radio transceiver device 200a, 200b will now be disclosed.

Let x_p denote the transmitted pilot signal as affected by the hardware impairment. Then, x_p can be expressed as a function of the transmitted pilot signal x_p as x_p = f(Xp), where the function f characterizes the hardware impairment. In particular, in some embodiments, the initial hardware impairment estimate is given by a parametric function. Coefficients of the parametric function are determined as a function of the hardware impairment. The parametric function maps the pilot signal to the initial hardware impairment estimate. The parametric function might, e.g., be a polynomial function where the coefficients of the polynomial can be computed as function of characteristics describing the hardware impairment.

There could be different types of hardware impairments. In some non-limiting examples, the hardware impairment pertains to any, or any combination of: power amplifier nonlinearity, oscillator phase noise, digital-to-analog converter quantization noise, filter ripples, inphase/ quadrature (I/Q) imbalance in the radio transceiver device 200a, 200b.

There could be different types of channel estimates. In some non-limiting examples, the channel estimate is represented by estimated channel state information.

In general terms, the pilot signal as received from the other radio transceiver device 200b, 200a is expressed as y_p = Hx_p + n where H is a channel matrix representing the radio channel 160 between the radio transceiver device 200a, 200b and the other radio transceiver device 200a, 200b, where n is receiver noise, and where (as disclosed above) x_p is the pilot signal x_p as distorted due to hardware impairment. That is, without any hardware impairment,

In some aspects, for the initial iteration round, the radio transceiver device 200a, 200b, for the given received signal y_p and known transmitted pilot x_p, assumes that the pilot signal is not distorted, i.e., that x_p = x_p, and finds a channel estimate H that minimizes a certain cost function using e.g., an LS estimator or an LMMSE estimator. In particular, in some embodiments, the channel estimate for the initial iteration round is obtained by estimating H from y_p = Hx_p + n and assuming that x_p = x_p, where the estimate of H is denoted H. In some aspects, it is for the initial iteration round, instead assumed that x_p = x_p, where x_p is the initial estimate of the distorted pilot signal based on a priori knowledge of the hardware impairment.

In some aspects, the radio transceiver device 200a, 200b, for the thus estimated channel estimate H, then estimates the hardware impairment. In particular, in some embodiments, the hardware impairment estimate for the current iteration round is obtained by estimating x_p from y_p = Hx_p + n, where the estimate of x_p is denoted Xp.

This completes the first iteration round. For the second, third, fourth, etc. iteration rounds the following aspects apply.

The radio transceiver device 200a, 200b might, for the current iteration round, updates the channel estimate H for the thus estimated hardware impairment. In further detail, the radio transceiver device 200a, 200b, for the given received signal y_p, and estimatedx_p, assumes that the transmitted pilot signal is x_p and finds an updated channel estimate H that minimizes a certain cost function. Hence, in some embodiments, the channel estimate for the current iteration round is obtained by estimating H from y_p = H x_p + n, where x_p is the estimate of x_p from the previous iteration round and where the estimate of H is denoted H. The radio transceiver device 200a, 200b might, for the current iteration round, estimate the hardware impairment for the thus updated channel estimate H for the same iteration round. That is, in some embodiments, the hardware impairment estimate for the current iteration round is obtained by estimating x_p from y_p = Hx_p + n, where the estimate of x_p is denoted x_p, and where H is the estimate of H for the current iteration round.

In some embodiments, the channel estimate and the hardware impairment estimate are iteratively and alternately obtained until a stop criterion is reached.

There could be different types of stop criteria. In some non-limiting examples, the stop criterion is defined by any of: convergence of the channel estimate, convergence of a first quality estimate of the channel estimate, convergence of a second quality estimate of the hardware impairment estimate, or by a predetermined number of iteration rounds.

Aspects of the first quality estimate of the channel estimate will be disclosed next.

The quality of the channel estimation might be measured using a metric, e.g., the mean square error (MSE), to quantify the difference of the actual radio channel and the estimated radio channel. In some aspects, the quality of the channel estimation can be measured using, for example, the MSE, where the MSE is defined as the mean of the squared error between the true and the estimated channel coefficients. For a given channel estimation method, e.g., for the least square (LS) estimator or the minimum mean square error (MMSE) estimator, the MSE can be determined using the second order statistics of the pilot signals and the receiver noise. Hence, the MSE can be determined without the need for true radio channel to be known at the radio transceiver device 200a, 200b. In particular, in some embodiments, the method further comprises step Sio6.

Sio6: The first quality estimate, pertaining to quality of the channel estimate per each iteration round, is obtained from second order statistics of the pilot signal and receiver noise of the radio transceiver device 200a, 200b.

Aspects of the second quality estimate of the hardware impairment estimate will be disclosed next. The quality of the hardware impairment estimation can be quantified using a measure e.g., the MSE, to quantify the difference of the actual distorted pilot signal and the estimated distorted pilot signal. In some aspects, the quality of the hardware impairment estimation can be measured using, for example, the MSE defined as the mean of the squared error between the true and the estimated pilot signal. For a given hardware estimation method, e.g., for an LS estimator or an MMSE estimator, the MSE can be determined using the second order statistics of the radio channel and the receiver noise. Hence, the MSE can be determined without the need for true radio channel to be known at the radio transceiver device 200a, 200b. In particular, in some embodiments, the method further comprises step Sno.

Sno: The second quality estimate, pertaining to quality of the hardware impairment estimate per each iteration round, is obtained from second order statistics of the radio channel 160 and receiver noise of the radio transceiver device 200a, 200b.

Fig. 5 schematically illustrates, in terms of a number of functional units, the components of a radio transceiver device 200a, 200b 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 710 (as in Fig. 7), 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).

Particularly, the processing circuitry 210 is configured to cause the radio transceiver device 200a, 200b 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 maybe configured to retrieve the set of operations from the storage medium 230 to cause the radio transceiver device 200a, 200b to perform the set of operations. The set of operations may be provided as a set of executable instructions.

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 radio transceiver device 200a, 200b may further comprise a communications interface 220 at least configured for communications with other entities, functions, nodes, and devices, such as another radio transceiver device 200b, 200a. 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 radio transceiver device 200a, 200b 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 radio transceiver device 200a, 200b are omitted in order not to obscure the concepts presented herein.

Fig. 6 schematically illustrates, in terms of a number of functional modules, the components of a radio transceiver device 200a, 200b according to an embodiment. The radio transceiver device 200a, 200b of Fig. 6 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 an estimate module 2iod configured to perform step S108. The radio transceiver device 200a, 200b of Fig. 6 may further comprise a number of optional functional modules, such as any of an obtain module 210c configured to perform step S106, and an obtain module 2ioe configured to perform step S110. In general terms, each functional module 2ioa:2ioe 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 radio transceiver device 200a, 200b perform the corresponding steps mentioned above in conjunction with Fig 8. 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 2ioa:2ioe 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 2ioa:2ioe and to execute these instructions, thereby performing any steps as disclosed herein. The radio transceiver device 200a, 200b maybe provided as a standalone device or as a part of at least one further device. For example, as disclosed above, the radio transceiver device 200a, 200b maybe provided as part of a transmission and reception point 140 or a user equipment 150.

Fig. 7 shows one example of a computer program product 710 comprising computer readable storage medium 730. On this computer readable storage medium 730, a computer program 720 can be stored, which computer program 720 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 720 and/or computer program product 710 may thus provide means for performing any steps as herein disclosed.

In the example of Fig. 7, the computer program product 710 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 710 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 720 is here schematically shown as a track on the depicted optical disk, the computer program 720 can be stored in any way which is suitable for the computer program product 710.

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

1. A method for iterative channel estimation and hardware impairment estimation in a radio transceiver device (200a, 200b), the method comprising: receiving (S102), over a radio channel (160) to be estimated, a pilot signal from another radio transceiver device (200b, 200a); and iteratively and alternately estimating (S104) the radio channel and estimating (S108) hardware impairment for the radio transceiver device (200a, 200b) by, in each iteration round, first obtaining a channel estimate and then obtaining a hardware impairment estimate, wherein the channel estimate for a current iteration round is a function of (ia) a first estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device (200b, 200a), and of (ib) knowledge of the pilot signal, wherein for an initial iteration round the first estimate of the pilot signal further is based on a given hardware impairment estimate, and for any other iteration round further is based on the hardware impairment estimate for a previous iteration round, and wherein the hardware impairment estimate for the current iteration round is a function of (iia) a second estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device (200b, 200a), and of (iib) the knowledge of the pilot signal, and wherein the second estimate of the pilot signal further is based on the channel estimate for the current iteration round.

2. The method according to claim 1, wherein the pilot signal as received from said another radio transceiver device (200b, 200a) is expressed as y_p = Hx_p + n where H is a channel matrix representing the radio channel (160) between the radio transceiver device (200a, 200b) and said another radio transceiver device (200a, 200b), where n is receiver noise, and where x_p is the pilot signal x_p as distorted due to hardware impairment.

3. The method according to claim 2, wherein the channel estimate for the initial iteration round is obtained by estimating H from y_p = Hx_p + n and assuming that x_p = x_p, where the estimate of H is denoted H.

4. The method according to claim 2, wherein the channel estimate for the initial iteration round is obtained by estimating H from y_p = Hx_p + n and assuming that x_p = x_p, where the estimate of H is denoted H, and where x_p is an initial estimate of the pilot signal as distorted based on a priori knowledge of the hardware impairment.

5. The method according to claim 3 or 4, wherein the hardware impairment estimate for the current iteration round is obtained by estimating x_p from y_p = Hx_p + n, where the estimate of x_p is denoted x_p.

6. The method according to claim 5, wherein the channel estimate for the current iteration round is obtained by estimating H from y_p = H x_p + n, where x_p is the estimate of x_p from the previous iteration round and where the estimate of H is denoted H.

7. The method according to any preceding claim, wherein the channel estimate and the hardware impairment estimate are iteratively and alternately obtained until a stop criterion is reached.

8. The method according to claim 7, wherein the stop criterion is defined by either convergence of the channel estimate, or a first quality estimate of the channel estimate, or a second quality estimate of the hardware impairment estimate, or a predetermined number of iteration rounds.

9. The method according to claim 8, wherein the method further comprises: obtaining (S106) the first quality estimate pertaining to quality of the channel estimate per each iteration round from second order statistics of the pilot signal and receiver noise of the radio transceiver device (200a, 200b). io. The method according to claim 8, wherein the method further comprises: obtaining (Sno) the second quality estimate pertaining to quality of the hardware impairment estimate per each iteration round from second order statistics of the radio channel (160) and receiver noise of the radio transceiver device (200a, 200b).

11. The method according to any preceding claim, wherein the initial hardware impairment estimate is given by a parametric function, wherein coefficients of the parametric function are determined as a function of the hardware impairment, and wherein the parametric function maps the pilot signal to the initial hardware impairment estimate.

12. The method according to any preceding claim, wherein the hardware impairment pertains to any, or any combination of: power amplifier nonlinearity, oscillator phase noise, digital-to-analog converter quantization noise, filter ripples, inphase/quadrature imbalance in the radio transceiver device (200a, 200b).

13. The method according to any preceding claim, wherein the channel estimate is represented by estimated channel state information.

14. The method according to any preceding claim, wherein the radio transceiver device (200a, 200b) is part of a transmission and reception point (140) or a user equipment (150).

15. A radio transceiver device (200a, 200b) for iterative channel estimation and hardware impairment estimation, the radio transceiver device (200a, 200b) comprising processing circuitry (210), the processing circuitry being configured to cause the radio transceiver device (200a, 200b) to: receive, over a radio channel (160) to be estimated, a pilot signal from another radio transceiver device (200b, 200a); and iteratively and alternately estimate the radio channel and estimate hardware impairment for the radio transceiver device (200a, 200b) by, in each iteration round, first obtaining a channel estimate and then obtaining a hardware impairment estimate, wherein the channel estimate for a current iteration round is a function of (ia) a first estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device (200b, 200a), and of (ib) knowledge of the pilot signal, wherein for an initial iteration round the first estimate of the pilot signal further is based on a given hardware impairment estimate, and for any other iteration round further is based on the hardware impairment estimate for a previous iteration round, and wherein the hardware impairment estimate for the current iteration round is a function of (iia) a second estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device (200b, 200a), and of (iib) the knowledge of the pilot signal, and wherein the second estimate of the pilot signal further is based on the channel estimate for the current iteration round.

16. A radio transceiver device (200a, 200b) for iterative channel estimation and hardware impairment estimation, the radio transceiver device (200a, 200b) comprising: a receive module (210a) configured to receive (S102), over a radio channel (160) to be estimated, a pilot signal from another radio transceiver device (200b, 200a); and estimate modules (210b, 2iod) configured to iteratively and alternately estimate the radio channel and estimate hardware impairment for the radio transceiver device (200a, 200b) by, in each iteration round, first obtaining a channel estimate and then obtaining a hardware impairment estimate, wherein the channel estimate for a current iteration round is a function of (ia) a first estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device (200b, 200a), and of (ib) knowledge of the pilot signal, wherein for an initial iteration round the first estimate of the pilot signal further is based on a given hardware impairment estimate, and for any other iteration round further is based on the hardware impairment estimate for a previous iteration round, and wherein the hardware impairment estimate for the current iteration round is a function of (iia) a second estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device (200b, 200a), and of (iib) the knowledge of the pilot signal, and wherein the second estimate of the pilot signal further is based on the channel estimate for the current iteration round.

17. The radio transceiver device (200a, 200b) according to claim 15 or 16, further being configured to perform the method according to any of claims 2 to 14.

18. A computer program (720) for iterative channel estimation and hardware impairment estimation in a radio transceiver device (200a, 200b), the computer program comprising computer code which, when run on processing circuitry (210) of the radio transceiver device (200a, 200b), causes the radio transceiver device (200a, 200b) to: receive (S102), over a radio channel (160) to be estimated, a pilot signal from another radio transceiver device (200b, 200a); and iteratively and alternately estimate (S104) the radio channel and estimate (S108) hardware impairment for the radio transceiver device (200a, 200b) by, in each iteration round, first obtaining a channel estimate and then obtaining a hardware impairment estimate, wherein the channel estimate for a current iteration round is a function of (ia) a first estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device (200b, 200a), and of (ib) knowledge of the pilot signal, wherein for an initial iteration round the first estimate of the pilot signal further is based on a given hardware impairment estimate, and for any other iteration round further is based on the hardware impairment estimate for a previous iteration round, and wherein the hardware impairment estimate for the current iteration round is a function of (iia) a second estimate of the pilot signal as based on the pilot signal received from said another radio transceiver device (200b, 200a), and of (iib) the knowledge of the pilot signal and, and wherein the second estimate of the pilot signal further is based on the channel estimate for the current iteration round.

19. A computer program product (710) comprising a computer program (720) according to claim 18, and a computer readable storage medium (730) on which the computer program is stored.