WO2023106977A1

WO2023106977A1 - Receiver node and method in a wireless communications network

Info

Publication number: WO2023106977A1
Application number: PCT/SE2021/051216
Authority: WO
Inventors: Sairamesh Nammi; Torbjörn WIGREN; Leonard Rexberg; Farshid Ghasemzadeh
Original assignee: Telefonaktiebolaget Lm Ericsson (Publ)
Priority date: 2021-12-07
Filing date: 2021-12-07
Publication date: 2023-06-15

Abstract

A method performed by a receiver node for mitigation of distortion of a nonlinearity at a transmitting node in a communications network is provided. The receiver node signals (901) information to the transmitting node. The information indicates that the receiver node is capable of decoding nonlinear signals transmitted by the transmitting node. The receiver node mitigates distortion of nonlinearity at the transmitting node by jointly estimating (903) channel coefficients and coefficients of a nonlinearity of a channel received (902) from the transmitting node. The receiver node applies (904) the jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information.

Description

RECEIVER NODE AND METHOD IN A WIRELESS COMMUNICATIONS NETWORK

TECHNICAL FIELD

Embodiments herein relate to a receiver node and methods therein. In some aspects, they relate to mitigation of distortion of a nonlinearity at a transmitter node in a communications network.

BACKGROUND

In a typical wireless communication network, wireless devices, also known as wireless communication devices, mobile stations, stations (STA) and/or User Equipments (UE)s, communicate via a Wide Area Network or a Local Area Network such as a Wi-Fi network or a cellular network comprising a Radio Access Network (RAN) part and a Core Network (CN) part. The RAN covers a geographical area which is divided into service areas or cell areas, which may also be referred to as a beam or a beam group, with each service area or cell area being served by a radio network node such as a radio access node e.g., a Wi-Fi access point or a radio base station (RBS), which in some networks may also be denoted, for example, a NodeB, eNodeB (eNB), or gNB as denoted in Fifth Generation (5G) telecommunications. A service area or cell area is a geographical area where radio coverage is provided by the radio network node. The radio network node communicates over an air interface operating on radio frequencies with the wireless device within range of the radio network node.

3GPP is the standardization body for specify the standards for the cellular system evolution, e.g., including 3G, 4G, 5G and the future evolutions. Specifications for the Evolved Packet System (EPS), also called a Fourth Generation (4G) network, have been completed within the 3rd Generation Partnership Project (3GPP). As a continued network evolution, the new releases of 3GPP specifies a 5G network also referred to as 5G New Radio (NR).

Frequency bands for 5G NR are being separated into two different frequency ranges, Frequency Range 1 (FR1) and Frequency Range 2 (FR2). FR1 comprises sub-6 GHz frequency bands. Some of these bands are bands traditionally used by legacy standards but have been extended to cover potential new spectrum offerings from 410 MHz to 7125 MHz. FR2 comprises frequency bands from 24.25 GHz to 52.6 GHz. Bands in this millimeter wave range, referred to as Millimeter wave (mmWave), have shorter range but higher available bandwidth than bands in the FR1.

Multi-antenna techniques may significantly increase the data rates and reliability of a wireless communication system. For a wireless connection between a single user, such as UE, and a base station, the performance is in particular improved if both the transmitter and the receiver are equipped with multiple antennas, which results in a Multiple-Input Multiple-Output (MIMO) communication channel. This may be referred to as Single-User (SU)-MIMO. In the scenario where MIMO techniques is used for the wireless connection between multiple users and the base station, MIMO enables the users to communicate with the base station simultaneously using the same time-frequency resources by spatially separating the users, which increases further the cell capacity. This may be referred to as Multi-User (MU)-MIMO. Note that MU-MIMO may benefit when each UE only has one antenna. Such systems and/or related techniques are commonly referred to as MIMO.

Figure 1 shows a general block diagram of an adaptive wireless communication system. Input bits 11 from upper layers e.g., layer 2 such as MAC layer, are passed through baseband 12 blocks which typically comprises channel encoder, interleaver and rate matching, modulator, layer mapper, OFDM modulator etc. Once the baseband signal is generated, it needs to be passed through the RF 13 chain before it is sent to the antenna ports 14. The RF chain typically comprises Digital to Analog converter (DAC), l/Q imbalance, oscillators, and Power Amplifiers (PA). Note that the baseband signal generation depends on the scheduler decisions 15 from the upper layers e.g., layer 2 such as MAC layer. The Scheduler decisions 15 are also influenced by the contents of the feedback channel 16 from the receiver. For example, the receiver may inform what kind of modulation and code rate is suitable at any given instance. For example, when the receiver is having good signal to ratio, it might prefer higher order modulation say 256- QAM or 64-QAM, and when the receiver is having low signal to noise ratio, it might prefer low order modulation such as QPSK or 16-QAM.

It is known that MIMO systems significantly increases the data carrying capacity of wireless communication systems. For these reasons, MIMO is an integral part of the 3rd, 4th and 5th generation wireless systems. Future 6G systems will also employ MIMO systems also called massive MIMO systems comprising hundreds of antennas at the Transmitter side and/Receiver side. Typically, with a (Nt, Nr), where Nt denotes the number of transmit antennas and Nr denotes the receive antennas, the peak data rate and average data rate increases significantly with the increase of either Nt and/or Nr.

Message Sequence Chart for Downlink Data Transfer

Figure 2 shows a typical message sequence chart between a gNB and a UE for a downlink data transfer in a 5G system. From the pilot or reference signals transmitted 21 by the gNB, the UE computes 22 the channel estimates then computes 24 parameters needed for Channel-State Information (CSI) reporting 23. The CSI report e.g. comprises channel quality indicator (CQI), precoding matrix index (PMI), rank information (Rl), Channel-State Information - Reference Signals (CSI-RS) Resource Indicator (CRI) etc. The CRI is a beam indicator etc. The CSI-RS is a resource indicator when multiple CS-RS resources are configured for the UE.

The CSI report is sent to the network such as the gNB via a feedback channel either on request from the network a-periodically or configured to report periodically. The gNB scheduler uses this information in choosing parameters for scheduling of this particular UE. The gNB sends 25 the scheduling parameters to the UE in a downlink control channel. After that, actual data transfer is transmitted 26 from network to the UE.

Downlink Reference Signals

Downlink Reference Signals (RS) are predefined signals occupying specific resource elements within a downlink time-frequency grid. There are several types of downlink RS that are transmitted in different ways and used for different purposes by a receiving UE:

• CSI-RS: These reference signals are specifically intended to be used by UEs to acquire CSI and beam specific information such as beam Reference Signal Received Power (beam RSRP). In 5G CSI-RS is UE specific so it may have a significantly lower time/frequency density.

• Demodulation RS (DM-RS): These reference signals, also sometimes referred to as UE-specific reference signals, are specifically intended to be used by UEs for channel estimation for the data channel. The label “UE-specific” relates to the fact that each demodulation reference signal is intended for channel estimation by a single UE. That specific reference signal is then only transmitted within resource blocks assigned for data traffic channel transmission to that UE. Impact Due to PA Nonlinearity:

In general, a PA needs to be operated in a nonlinear region for achieving good efficiency.

Figure 3 shows the typical Amplitude (AM)/AM curve for a PA with Gallium Arsenide (GaAs)s and Complementary Metal-Oxide Semiconductor (CMOS) (CMO)s type of PAs. Note that the input/output curve is highly nonlinear. Figure 3 depicts a typical AM/AM performance of a PA. In the diagram of Figure 3, the X-axis represents the Input signal voltage, (V_in ) and the Y-axis represents the output signal voltage (V_o ).

However, when a PA operates in the nonlinear region, some of the signals are leaked to other frequency bands. Figure 4 illustrates a power spectral density with realistic PA shows a spectral regrowth due to PA nonlinearity.

The PA non-linearity induce distortion in the wanted signal/channel resulting in degraded signal quality and limits the SNR. Signal quality is measured as Error Vector Magnitude (EVM).

In the diagram of Figure 4, the X-axis represents the frequency in MHz of the output signal after the Power Amplifier and the Y-axis represents the power spectral density in dB/Hz.

Adjacent Channel Leakage Ratio (ACLR) is used as a metric to measure a leakage of power spectrum from an intended channel into its adjacent channel. In Figure 4, the ACLR with ideal PA 41 is around -78.1 dBc, while with realistic PA 42 (with nonlinearity), the ACLR is around -41.1 dBc. When used herein, dBc represents decibel (dB) relative to a carrier. dBc is used e.g. to specify the power of a sideband in a modulated signal relative to the carrier.

Digital Pre-distortion techniques for mitigating a PA Nonlinearity

One method to compensate for the nonlinearity of the PA is to distort the input signal to the PA such that the output signal from the PA is transformed to be close to what it would have been if the PA would have been linear. An example of such method is called Digital Pre-distortion (DPD) Technique. In general, DPD may interchangeably be denoted as a device linearization circuitry or component or mechanism or scheme.

Figure 5 depicts a block diagram of conventional DPD technique for compensating nonlinear effects of PA. Figure 5 shows the block diagram of a transmitter with DPD 50. Let y1 be an output signal when not using any DPD parameters extraction block 53, at the output of a PA 51. Further let x1 be the output signal from a baseband 52 and z1 is the input signal to the PA 51. Note that, in this model, it is considered only the impact due to nonlinear PA, but in practical systems the PA is preceded by many other blocks such as Digital to Analog Converter (DAC), Local Oscillator (LO) etc. The output signal y1 may be expressed as: yl = /l(zl)

Where f1 (.) is a nonlinear function which characterizes the PA. With DPD, and using the above equation, the PA output signal y2 may be written as: y2 = /l(#l(xl))

Where g1(.) is the function of the output signal x1 from the baseband 52 which characterizes the DPD parameters extraction block 53. An DPD parameter extraction when used herein means a way of determining the function G1 with an appropriate algorithm. Note that the DPD extraction block 53 is ideally chosen such that: y2 = l(01(xl)) = Glxl,

In practice, the equality will be approximate since ideal linearization is not achievable in practice. Here G1 is the gain of the PA 51. If g1 , i.e. the extracted PDP parameters, are properly chosen, then the output of the PA 51 is very close to linear.

Figure 6 Power spectral density with realistic PA 61 without DPD and PA with DPD 62. In the diagram of Figure 6, the X-axis represents the frequency in MHz of the output signal and the Y-axis represents the power spectral density in dB/Hz.

It is shown in Figure 6 as an example that the spectral regrowth is decreased with the implementation of a DPD.

SUMMARY

As a part of develop embodiments herein, the inventors have identified a problem that first will be discussed. The current DPD techniques require a lot of computational resources and power and may not be useful for low complexity implementation of a transmitter. However, without DPD, when the power amplifier operates in the nonlinear region the MIMO performance gets impacted due to the nonlinearity of the PA. In these cases, the advantages of MIMO techniques, such as the diversity gain, and multiplexing gain diminishes. Figure 7 depicts a Bit Error Rate (BER) performance with a non-ideal power amplifier for a 4X4 MIMO system. In the diagram of Figure 7, the X-axis represents the ratio of Energy per Bit (Eb) to the Spectral Noise Density (No), i.e. Signal to noise ratio measured as energy per bit/noise variance (Eb/No) in dB and the Y-axis represents the BER. Thus, Figure 7 shows a BER plot of a 4x4 MIMO system, with no channel coding, and with a nonlinear power amplifier with 4-QAM as the modulation scheme. It is observed in Figure 7 that there is a significant performance loss compared to the ideal case, i.e., when the transmitter power amplifier operates in the linear region.

An object of embodiments herein is to an effective way of handling nonlinearity to improve the performance of a wireless communications network.

According to an aspect of embodiments herein, the object is achieved by a method performed by a receiver node for mitigation of distortion of a nonlinearity at a transmitting node in a communications network. The receiver node signals information to the transmitting node. The information indicates that the receiver node is capable of decoding nonlinear signals transmitted by the transmitting node. The receiver node jointly estimates channel coefficients and coefficients of nonlinearity of a channel received from the transmitting node. The receiver node applies the jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information.

According to another aspect of embodiments herein, the object is achieved by a receiver node configured to mitigate distortion of a nonlinearity at a transmitting node in a communications network. The receiver node is further configured to:

- Signal information to the transmitting node, which information is adapted to indicate that the receiver node is capable of decoding nonlinear signals transmitted by the transmitting node, - jointly estimate channel coefficients and coefficients of nonlinearity of the channel received from the transmitting node, and

- apply the jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information.

In this way the performance of the communications network, such as e.g. the MIMO performance, is improved e.g., in terms of block error rate thereby improving the receiver node 110 throughput and at the same time reducing the computational complexity at the transmitter node 120.

BRIEF DESCRIPTION OF THE DRAWINGS

Examples of embodiments herein are described in more detail with reference to attached drawings in which:

Figure 1 is a schematic block diagram illustrating prior art.

Figure 2 is a combined signaling diagram and flowchart illustrating prior art.

Figure 3 is a line chart illustrating prior art.

Figure 4 is a line chart illustrating prior art.

Figure 5 is a schematic block diagram illustrating prior art.

Figure 6 is a line chart illustrating prior art.

Figure 7 is a line chart illustrating prior art.

Figure 8 is a schematic block diagram illustrating embodiments of a wireless communications network.

Figure 9 is a flowchart illustrating embodiments of a method in a receiver nod

Figure 10 is a schematic block diagram illustrating an embodiment herein.

Figure 11 is a line chart illustrating an embodiment herein.

Figure 12 is a schematic block diagram illustrating an embodiment herein.

Figure 13a-b are schematic block diagrams illustrating embodiments of a receiver node.

Figure 14 schematically illustrates a telecommunication network connected via an intermediate network to a host computer.

Figure 15 is a generalized block diagram of a host computer communicating via a base station with a user equipment over a partially wireless connection.

Figures 16-19 are flowcharts illustrating methods implemented in a communication system including a host computer, a base station and a user equipment. DETAILED DESCRIPTION

Embodiments herein provide methods for mitigating the impact of the nonlinearity at a transmitter node without increasing the complexity at the transmitter node.

According to examples herein, embodiments herein are related to a detection scheme in the presence of transmitter nonlinearities.

Figure 8 is a schematic overview depicting a communications network 100 wherein embodiments herein may be implemented. The communications network 100 comprises one or more RANs and one or more CNs. The communications network 100 may use a number of different technologies, such as mmWave communication networks, Wi-Fi, Long Term Evolution (LTE), LTE-Advanced, 5G, NR, Wideband Code Division Multiple Access (WCDMA), Global System for Mobile communications/enhanced Data rate for GSM Evolution (GSM/EDGE), Worldwide Interoperability for Microwave Access (WiMax), or Ultra Mobile Broadband (UMB), just to mention a few possible implementations. Embodiments herein relate to recent technology trends that are of particular interest in a 5G context, however, embodiments are also applicable in further development of the existing wireless communication systems such as e.g. WCDMA and LTE.

In the communications network 100 a receiver node 110 and a transmitting node 120 operates. The receiver node 110 and the transmitting node 120 may each respectively be any suitable network entity such that the transmitting node 120 may be capable to transmit radio, such as channel and/or signals to the receiver node 110.

Any one or more out of the receiver node 110 and the transmitting node 120 may be a radio network node such as any of a NG-RAN node, a transmission and reception point e.g. a base station, a radio access network node such as a Wireless Local Area Network (WLAN) access point or an Access Point Station (AP STA), an access controller, a base station, e.g. a radio base station such as a NodeB, an evolved Node B (eNB, eNode B), a gNB, an NG-RAN node, a base transceiver station, a radio remote unit, an Access Point Base Station, a base station router, a transmission arrangement of a radio base station, a stand-alone access point or any other network unit capable of communicating with UEs, within a service area served by the receiver node 110 or transmitting node 120 depending e.g. on the first radio access technology and terminology used.

Any one or more out of the receiver node 110 and the transmitting node 120 may also be UE, which may also refer to a wireless device, an loT device, a mobile station, a non-access point (non-AP) STA, a STA, a user equipment and/or a wireless terminals, and may be configured to communicate via one or more Access Networks (AN), e.g. RAN, to one or more core networks (CN). It should be understood by the skilled in the art that “UE” is a non-limiting term which means any terminal, wireless communication terminal, user equipment, Machine Type Communication (MTC) device, Device to Device (D2D) terminal, or node e.g., smart phone, laptop, mobile phone, sensor, relay, mobile tablets or even a small base station communicating within a cell.

The receiver node 110 and the transmitting node 120 are capable of communicating with each other. According to embodiments herein, the transmitting node 120 transmits e.g. data to the receiving node 110 e.g. by means of a MIMO system.

As an example, in some embodiments herein, the transmitting node 120 may be a UE, and the receiver node 110 may be a network node serving the transmitted node 120 in a cell. As another example the transmitting node 120 may be a network node, and the receiver node 110 may be a UE, e.g., served in a cell by the transmitting node 120.

Methods herein may be performed by the receiver node 110. As an alternative, a Distributed Node (DN) and functionality, e.g. comprised in a cloud 135 as shown in Figure 8, may be used for performing or partly performing the methods herein.

A number of embodiments will now be described, some of which may be seen as alternatives, while some may be used in combination.

An example idea of the embodiments herein, is to identify the nonlinearity of the transmitter node 110 at the receiver node 110 and use the identified nonlinearity, e.g. in formulating receiver weight metrics, for example log likelihood ratio or receiver weights in a MIMO detector at the receiver node 110. Or to formulate receiver weight metrics in a MIMO detector at the receiver node 110.

To log likelihood ratio when used herein means the ratio of probability of the received bit equal to 0 to probability of the received bit equal to 1.. To log receiver weights when used herein means the finite impulse response filter tap weights.

In this way the performance of the communications network is improved in terms of the block error rate thereby improving the receiver node 110 throughput at the same time reducing the computational complexity at the transmitter node 120.

Embodiments herein will first be described in a general way together with Figure 9, then below, they will be exemplified and explained more in detail.

Figure 9 shows example embodiments of a method performed by the receiver node 110 for mitigation of distortion of a nonlinearity at the transmitting node 120 in the communications network 100.

In some embodiments, the method performed by the receiver node 110 is applied for to any one out of:

- Downlink transmissions wherein the receiver node 110 is a UE and the transmitter node 120 is e.g. a radio network node, or

- uplink transmissions wherein the receiver node 110 is a radio network node and the receiver node 110 is e.g. a UE.

The method comprises the following actions, which actions may be taken in any suitable order. Optional actions are referred to as dashed boxes in Figure 9.

Action 901

The receiver node 110 signals information to the transmitting node 120. The information indicates that the receiver node 110 is capable of decoding nonlinear signals transmitted by the transmitting node 120. This may be to inform the transmitter node 120 that the transmitter node 120 need not to take any specific action to unravel distortion of the nonlinearity at the transmitting node 120. This is since according to embodiments herein, the receiver node 110 will take actions for this and is therefore capable of decoding nonlinear signals transmitted by the transmitting node 120.

In some embodiments, the method is applied for downlink transmissions and wherein the receiver node 110 is a UE, and the transmitting node 120 is a radio network node. In some of these embodiments, the information comprises an indication indicating that the receiver node 110 performs estimation of the nonlinearity of the transmitting node 120.

In some embodiments, the method is applied for uplink transmissions wherein the receiver node 110 is a radio network node, and the transmitting node 120 is a UE. In some of these embodiments, the information signaled to the transmitting node 120 may further comprise an indication indicating any one or more out of:

- To not power back off a PA of the transmitting node 120 operating in the nonlinear region.

- That the receiver node 110 is capable of compensating for nonlinearity of the transmitting node 120.

Action 902

In an example scenario, the receiver node 110 receives a signal e.g. of a channel from the transmitting node 120.

A channel may be an abstraction of the physical properties of radio propagation, resulting in a momentary gain, e.g., the complex channel gain, from the transmitter to the receiver. Since some pilot signals are known at both ends, this complex channel gain may be estimated. The estimated channel is hence characterized by this complex channel gain, or for MIMO a channel gain matrix.

Action 903

The receiver node 110 jointly estimates channel coefficients and coefficients of the nonlinearity of the channel received from the transmitting node 120.

In some embodiments, the jointly estimating of the channel coefficients and coefficients of the nonlinearity is performed by, e.g. means, iterating the channel estimation and estimation of the nonlinearity of the transmitting node 120, to obtain the jointly estimated channel coefficients and coefficients of the nonlinearity. This may be performed until a stopping criterion is fulfilled.

To jointly estimate the channel coefficients and coefficients of the nonlinearity when used herein e.g. comprises:

Estimating the channel coefficients and then estimate the coefficients of the nonlinearity, based on the estimated channel coefficients.

This is repeated iteratively by: Estimating the channel coefficients based on the latest estimated coefficients of the nonlinearity and then estimating the coefficients of the nonlinearity, based on the latest estimated channel coefficients.

The jointly estimating of the channel coefficients and coefficients of the nonlinearity when used herein may e.g. be modelled as a Finite Impulse Response (FIR) filter and the weights factors of a nonlinear polynomial.

Channel coefficients when used herein e.g. means tap weights of channel modelled as FIR filter.

Coefficients of the nonlinearity when used herein e.g. means weight factors of nonlinear polynomial equation e.g. means, in a special case when describing the nonlinearity as a polynomial, the coefficients of that polynomial or series expansion of the non-linear function.

A stopping criterion when used herein e.g. means the condition at which the iterations between the channel estimation coefficients and the coefficients of the nonlinear polynomial are stopped.

The iterating of the channel estimation and estimation of the nonlinearity of the transmitting node 120 to obtain estimated channel coefficients and coefficients of the nonlinearity, until a stopping criterion is fulfilled, may be performed according to the example in the following Steps 1-4.

Step 1 : Based on assuming that a signal received from the transmitting node 120 is linearly generated, the receiver node 110 estimates the channel using least squares estimation from the received signal.

Step 2: The receiver node 110 estimates the nonlinearity from the received signal based on the estimated channel and based on reference symbols of the received signal.

Step 3: Based on the estimated nonlinearity, the receiver node 110 re-estimates the channel to reduce the effect of the nonlinearity from the received signal.

Step 4: The receiver node 110 repeats iterations of the estimating of the nonlinearity from the received signal, e.g. Step 2, and the re-estimating of the channel to reduce the effect of the nonlinearity from the received signal based on the estimated nonlinearity, e.g. Step 3, until the stopping criterion is fulfilled.

In some embodiments, the stopping criterion to be fulfilled is represented by a convergence criterion. This is advantageous since otherwise the iteration may continue unnecessarily, resulting in an increased computational effort. A convergence criterion when used herein e.g. means that a measure of the estimation error is compared to a predetermined threshold that represents an acceptable remaining error, and to a predetermined maximum number of iterations that stop further iterations irrespective of if the remaining error is to large.

In some embodiments, mitigating the distortion of the nonlinearity at the transmitting node 120, is performed by DPD Technique, at the receiver node 110.

Action 904

The receiver node 110 applies the jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information, such as from the received signal. Soft bit information when used herein e.g. means .log likelihood ratio of the bits..

In some embodiments, the obtained jointly estimated channel coefficients, and coefficients of the nonlinearity to detect soft bit information are applied for detecting data transmitted by the transmitting node 120, according to any one out of Method 1 and Method 2, wherein:

Method 1 comprises passing the received signal from a linear finite impulse response filter, where filter weights are computed based on a minimum mean square criteria and passing the output of the filter to received DPD, which received DPD depends on the estimated coefficients of the nonlinearity and obtaining the soft bit information.

Method 2 comprises generating the soft bit information from the received signal, the estimated channel coefficients, and coefficients of the nonlinearity by using a maximum aPosteriori probability criteria.

Method 1 and Method 2 will be described more in detail below.

Action 905

In some embodiments, the receiver node 110 signals information to the transmitting node 120. The information indicates said applying, e.g. as in Action 904 above, of the obtained jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information.

In this way, embodiments herein provide better performance of the communication system especially improving the bit or block error rate at the same time reduced processing at transmitter node 120.

The above embodiments will now be further explained and exemplified below. The embodiments below may be combined with any suitable embodiment above. Example of embodiments herein provide an improved MIMO system applicable when the transmitter node 120 operates in a nonlinear region. Example of embodiments herein is e.g. implemented in the receiver node 110, and may in some embodiments be summarized as:

A method in the receiver node 110 of identifying the nonlinearity at the transmitter node 120, for example at the output of a PA at the output of DAC etc., of the transmitter node 120. The example method may comprise one or more out of the following:

- Determining nonlinearity of the transmitter node 120 from a signal received from the transmitter node 120.

- Determining nonlinear coefficients of a set of basis functions such as e.g. polynomial basis functions, from the received signal. This may be applicable in and combined with Action 903 described above.

- Using iterative estimation techniques to jointly estimate the channel between the transmitter node 120 and the receiver node 110, and the nonlinearity of the transmitter node 120. This may be applicable in and combined with Action 904 described above.

- Applying the determined coefficients and use linearization techniques at the receiver node 110 before passing it to a detector in the receiver node 110. This may be applicable in and combined with Action 904 described above.

- Applying these coefficients and the channel estimation in a metric computation, e.g. computing the Log Likelihood Ratio (LLR) for the bits, of the MIMO detector. This may be applicable in and combined with Action 904 described above.

- Applying these coefficients and the channel estimation in a Minimum Mean Square Error (MMSE)- Interference Rejection Combiner (IRC) weight computation. This may be applicable in and combined with Action 904 described above.

It should be noted that embodiments herein are explained by considering the nonlinearities of the PA of the transmitter node 120 as an example, however, the same principle may be applied to each block of a transmitter chain, for example nonlinearities due to crest factor reduction techniques etc.

As mentioned above, the receiver node 110 receives a signal from the transmitting node 120. In an example scenario, consider a MIMO system with Nt transmit antenna branches in the transmitter node 120 and Nr is the number of receive branches in the receiver node 110. Then the received signal vector r of the received signal may be written as below MIMO system Equation (1).

(1) r = HPu + n

The size of the receiving vector r is N_r x1 , H is the complex channel matrix of size N_r x N_t, P is the precoding matrix of size N_t x Ni_, where NL is the number of transmission layers, also referred to as Rank, u is the transmission vector of size NL x1 and n is the noise vector of size N_r x1.

In the above equation, the transmission vector u is computed at the output of the power amplifier of the transmitter node 120. The power amplifier is characterized by below equation. u = f(x) where x is the symbol vector before PA (s) and f (.) is a nonlinear function of the PA. PA (s) is the same size as that of the input vector. Hence the size of the received signal vector r of the received signal of MIMO system equation (1) may be written as below equation (2).

(2) r = HPf(x) + n

Note that, herein, vectors and matrices are represented with bold symbols. ...

As mentioned above in Action 902, the receiver node 110 receives a channel from the transmitting node 120.

Assume that the receiver node 110 estimates the received channel channel H_est, and the nonlinearity f_estas will be described below. This relates to and may be combined with Actions 903 and 904 described above.

In some embodiments as mentioned above, the obtained jointly estimated channel coefficients and coefficients of the nonlinearity to detect soft bit information are applied for detecting data transmitted by the transmitting node 120 according to any one out of Method 1 and Method 2.

Method 1

A block diagram of Method 1 is shown in Figure 10. As mentioned above, in the Method 1 the receiver node 110 passes the received signal 1001 from a linear finite impulse response filter, where filter weights are computed based on a minimum mean square criterion. The receiver node 110 then passes the output of the filter to the received DPD 1004. The received DPD when used herein may be a digital predistortion implemented at the receiver DPD1004 which can compensate the non-hneanties of the input signal. The received DPD 1004 depends on the estimated coefficients of the nonlinearity and obtaining the soft bit information 1005.

Method 1 relates to how the actual signal is detected when the nonlinearity is known.

The receiver node 110 e.g. uses a linear MMSE-IRC or an MMSE detector 1002. When an MMSE detector is used then the output z 1003 of the MMSE detector is given by z = Af(x) + W,

Where z 1003 is the output of the MMSE detector, A is the amplitude of the signal, W, is the Gaussian noise, x is the symbol vector before PA (s) and f (.) is a nonlinear function of the PA. Then according to Method 1 , the received signal is passed through the received DPD where the channel coefficients in this example the DPD coefficients, (g1) are derived from the estimated 1005 nonlinearity f_est.

Then the output of the received DPD may be written as

Z_o = gl z)

Which can be written by

Z_o = gl(Af(x) + W) g1(f(x) is the composition of the two functions g1 and f(x). If g1(f(x) is designed such that the composition is the unity of the function, i.e. they are each other’s inverse and should return x, and assuming that the power of w is small, then

Z_o = Ax +w2, where w2 is noise term.

It should be observed that this is like the term when the transmitted signal is linear. Hence, the nonlinearity introduced at the transmitter can be removed.

Receiver DPD of the receiver node 110: As explained above the receiver DPD 1004 g1() is designed such that the composition g1(f_est())is unity.

Thus, once the nonlinearity of the transmitter is estimated, receiver DPD can compute g1 and process the MMSE-IRC 1002 output signals z 1003. That is g1(z).

Method 2

As mentioned above, in the Method 2 the receiver node 110 generates the soft bit information from the received signal, the estimated channel coefficients and coefficients of the nonlinearity by using a maximum a Posteriori probability criterion.

The Method 2 is performed at the receiver node 110 for detecting signals such as Ml MO signals transmitted by said nonlinear transmitter of the transmitter node 120. In these embodiments the receiver node 110 may use the estimated nonlinearity in the detection process itself.

In this method the data symbols of the transmitted signal are chosen, which gives the smallest Euclidian distance between the received vector r and the hypothesized message Hdfest(x), where Hd is the estimated channel on the data subcarriers. In general, it is obtained as an interpolation from the estimated channel on the reference symbols. Mathematically this may be written as

X_ML = arg min||r - H_df_est(x) || ²

Note that that in the above equation arg min is computed over f_est(x) , i.e. , all the combination of x.

Figure 11 shows a BER plot with perfect estimation of f (.). It should be observed that the performance loss due to the nonlinearity at the transmission side is reduced significantly. In other words, Figure 11 illustrates a comparison of BER performance with the Method 2 referred to as Proposed method in Figure 11.

In general, all practical communication systems use a channel encoder and decoder to improve the bit error rate performance. It is well known that most of the channel decoders are either soft input and soft output Do not use SISO it is the standard abbreviation for single input single output or soft input hard output. Hence the channel detector needs to input soft input information to the channel decoder. Therefore, in some embodiments herein, the receiver node 110 uses information about the nonlinear function to compute the soft information.

Soft Ml MO detector

Soft MIMO detector tells us how likely it is that a given bit in a symbol vector is a one or zero. To begin with, the symbol vector is explicitly denoted as:

The symbol vector x may be viewed as a bitstring. Knowing this the Soft-MIMO

Detection problem can be defined as the a posteriori Log-Likelihood ratio

!(W = log

This is interpreted as the Log-Likehhood ratio of the tth bit being equal to one or zero given r. This can further be expanded as:

!(W = log

The notation E&_z(x)=i denotes the sum over all possible vectors x in which the tth bit is equal to 1. It is noted that b^x) = 1 and /^(x) = 0 are both subspaces of x^Nt. It is also noted that the two subsets are disjoint. For simplicity the subspace b^x) = 0 is denoted as B_o and b^x) = 1 as B_x.

In general, the max-log approximation is used in order to re-write the above equation as:

Note that in the above equation No corresponds to the noise + covariance estimation. In general, it is estimated from the received signal and the estimated channel.

Figure 12 shows the block diagram of Method 2. From the received baseband signal 1201 the channel and the nonlinearity of the transmitter can be estimated iteratively 1202 as explained below. Once these parameters are estimated the soft MIMO detectori 203 may be used to detect the soft bit information 1204 based on criteria which maximizes the posterior probability.

Signaling capability of decoding nonlinear signals

This relates to and may be combined with Action 901 described above.

It should be noted that that above method performed by the receiver node 110 to blindly estimating the nonlinearity of the transmitter node 120 and applying the result to the received signal may be performed at a UE for downlink transmission or it may be applied at a base station for uplink transmission from the UE. Blind means detection/estimation without knowing what bits were transmitted

In some embodiments for downlink data transmission wherein the receiver node 110 is a radio network node, and the transmitting node 120 is a UE, the UE may indicate to the radio network node that it uses any one of these methods where the nonlinearity of the transmitter is estimated, and that it can compensate the nonlinearity e.g. as explained in methods 1 or 2. For example this may be part of the UE capability or UE category. Once the transmitter node 120, in this example the radio network node, knows about this capability, it may relax the DPD operation for example, it may use not computationally intensive DPD or no DPD at the transmitter node 120 when transmitting to the receiver node 110 in this example the UE, which has this kind of receiver.

In some other embodiments for uplink data transmissions wherein the receiver node 110 is a radio network node, and the transmitting node 120 is a UE, the radio network node may indicate to the UE to not power back off so that the UE PA operates in the nonlinear region, and that the receiver node 110, in this example the radio network node is capable of compensate nonlinearity. These embodiments provide an increase in coverage as the UE can avoid power backoff.

Jointly estimating channel coefficients and coefficients of nonlinearity of the channel.

This may be applicable in and be combined with Action 903 described above. This relates to how to estimate the nonlinearity and the channel.

Note that for the above methods to work the receiver node 110 may need to estimate the channel and the nonlinearity of the transmitter node 120, e.g. the transmitter of the transmitter node 120. However, the jointly estimation of channel and the nonlinearity is a non-convex problem and there is no closed form solution available. A non-convex problem, in general have no unique minimum point which may mean that the initialization of the search algorithm is particularly important. However, these coefficients, the channel coefficients and the coefficients of nonlinearity, may be estimated serially, e.g. with an exhaustive search. By instead using an iterative process they may be estimated by using convex optimization as in the example embodiments described below in Steps 1-4. Convex optimization when used herein e.g. means that convex optimization methods that solve an associated problem is applied repeatedly, where the convex optimization methods have unique solutions that are more easily computed than for a non-convex problem.

Step 1 : As mentioned above, based on assuming that a signal received from the transmitter node 120 is linearly generated, the receiver node 110 estimates the channel using least squares estimation from the received signal in Step 1. This may be performed according to the following: Assume that the reference signal is linear and estimate the channel by using least squares estimation from the received signal i.e.:

Hest — r * Xpi

Where H_est is the estimated channel, r is the received signal vector, x_Pj is the pseudo inverse of x, and x is the is the symbol vector before PA (s).

Step 2: As mentioned above, the receiver node 110 estimates the nonlinearity from the received signal based on the estimated channel and based on reference symbols of the received signal in step 2. This may be performed according to the following:

From the estimated channel H_est, and from the reference symbols of the received channel estimate the nonlinearity f_est from the received signal, i.e. choose f_est such that, min || r - H_estf(x)||²

Where f(x) is the model of the nonlinearity and where the optimization is performed over the parameters of said nonlinearity.

Step 3: Based on the estimated nonlinearity, the receiver node 110 re-estimates the channel to reduce the nonlinearity from the received signal in Step 3, as mentioned above. This may be performed according to the following:

With the estimated nonlinearity f_est, re-estimate the channel which may minimize such that

Where f_est(x) is the nonlinear function causing distortion.

Step 4: As mentioned above, in step 4, the receiver node 110 then repeats iterations of the estimating (Step 2) of the nonlinearity from the received signal and the re- estimating (Step 3) of the channel to reduce the effect of the nonlinearity from the received signal based on the estimated nonlinearity a few iterations or until the stopping criterion is fulfilled, e.g. until a convergence criterion is met.

In some other embodiments, to improve the convergence, the nonlinearity of the signal may be initialized to a known value, e.g. by performing blind estimation from the received signal or to a previously known value. To perform the method actions above, the receiver node 110 is configured to mitigate distortion of a nonlinearity at the transmitting node 120 in the communications network 100. The receiver node 110 may comprise an arrangement depicted in Figures 13a and 13b.

The receiver node 110 may comprise an input and output interface 1300 configured to communicate with network entities such as e.g. the transmitting node 120. The input and output interface 300 may comprise a wireless receiver (not shown) and a wireless transmitter (not shown).

The receiver node 110 may further be configured to, e.g. by means of a signalling unit 1301 comprised in the receiver node 110, signal information to the transmitting node 120, which information is adapted to indicate that the receiver node 110 is capable of decoding nonlinear signals transmitted by the transmitting node 120.

The receiver node 110 may further be configured to, e.g. by means of the signalling unit 1301 comprised in the receiver node 110, signal information to the transmitting node 120, which information is adapted to indicate said applying of the obtained jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information.

The receiver node 110 may further be configured to, e.g. by means of a mitigating unit 1305 comprised in the receiver node 110, jointly estimate e.g. by means of an estimating unit 1302 comprised in the receiver node 110, channel coefficients and coefficients of nonlinearity of a channel received, e.g. by means of a receiving unit 1303 comprised in the receiver node 110, from the transmitting node 120.

The receiver node 110 may further be configured to, e.g. by means of the estimating unit 1302 comprised in the receiver node 110, jointly estimate the channel coefficients and the coefficients of the nonlinearity by iterating, e.g. by means of an iterating unit 1307 comprised in the receiver node 110, the channel estimation and estimation of the nonlinearity of the transmitting node 120, to obtain the jointly estimated channel coefficients and coefficients of the nonlinearity, until a stopping criterion is fulfilled.

The receiver node 110 may further be configured to, e.g. by means of the iterating unit 1307 comprised in the receiver node 110, iterate the channel estimation and estimation of the nonlinearity of the transmitting node 120, to obtain estimated channel coefficients and coefficients of the nonlinearity, until a stopping criterion is fulfilled, by: based on an assumption that a signal received from the transmitting node 120 is linearly generated, estimate, e.g. by means of the estimating unit 1302 comprised in the receiver node 110, the channel using least squares estimation from the received signal, estimate, e.g. by means of the estimating unit 1302 comprised in the receiver node 110, the nonlinearity from the received signal based on the estimated channel, and based on reference symbols of the received signal, based on the estimated nonlinearity, re-estimate, e.g. by means of a re-estimating unit 1306 comprised in the receiver node 110, the channel to reduce the nonlinearity from the received signal, repeat iterations of the estimation of the nonlinearity from the received signal and the re-estimation of the channel to reduce the effect of the nonlinearity from the received signal based on the estimated nonlinearity until the stopping criterion is fulfilled.

The receiver node 110 may further be configured to, e.g. by means of an applying unit 1304 comprised in the receiver node 110, apply the jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information.

In some embodiments, the stopping criterion to be fulfilled is adapted to be represented by a convergence criterion.

In some embodiments, the obtained jointly estimated channel coefficients and coefficients of the nonlinearity to detect soft bit information are arranged to be applied for detecting data transmitted by the transmitting node 120, according to any one out of Method 1 and Method 2, wherein:

Method 1 is arranged to comprise: passing the received signal from a linear finite impulse response filter, where filter weights are arranged to be computed based on a minimum mean square criteria, passing the output of the filter to received Digital Predistortion, DPD, which received DPD is adapted to depend on the estimated coefficients of the nonlinearity, and obtaining the soft bit information, and

Method 2 is arranged to comprise: generating the soft bit information from the received signal, the estimated channel coefficients and coefficients of the nonlinearity by using a maximum a Posteriori probability criteria.

The receiver node 110 may e.g. be configured to perform any one of above- mentioned Method 1 and Method 2 e.g., when applying the jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information. In some embodiments, the configurations of the receiver node 110 are arranged to be applied for to any one out of: downlink transmissions wherein the receiver node 110 is arranged to be a UE, or uplink transmissions wherein the receiver node 110 is arranged to be a radio network node.

In some embodiments, the configurations of the receiver node 110 are arranged to be applied for downlink transmissions wherein the receiver node 110 is arranged to be a UE, and the transmitting node 120 is arranged to be a radio network node, and wherein the information signalled to the transmitting node 120, further is adapted to comprise an indication indicating that the receiver node 110 is arranged to perform estimation of the nonlinearity of the transmitting node 120.

In some embodiments, the receiver node 110 is configured to mitigate e.g. by means of the mitigation unit 1305 comprised in the receiver node 110, the distortion of the nonlinearity at the transmitting node 120, by a DPD Technique, at the receiver node 110.

In some embodiments, the configurations of the receiver node 110 are arranged to be applied for uplink transmissions wherein the receiver node 110 is arranged to be a radio network node, and the transmitting node 120 is arranged to be a UE, wherein the information signaled to the transmitting node 120, further is adapted to comprise an indication indicating any one or more out of:

- to not power back off a PA of the transmitting node 120 operating in the nonlinear region, and

The embodiments herein may be implemented through a processor or one or more processors, such as the processor 1350 of a processing circuitry in the receiver node 110 depicted in Figure 13a, together with computer program code for performing the functions and actions of the embodiments herein. The program code mentioned above may also be provided as a computer program product, for instance in the form of a data carrier carrying computer program code for performing the embodiments herein when being loaded into the receiver node 110. One such carrier may be in the form of a CD ROM disc. It is however feasible with other data carriers such as a memory stick. The computer program code may furthermore be provided as pure program code on a server and downloaded to the receiver node 110. The receiver node 110 may further comprise a memory 1360 comprising one or more memory units. The memory 1360 comprises instructions executable by the processor in the receiver node 110. The memory 1360 is arranged to be used to store e.g. information, indications, symbols, data, configurations, and applications to perform the methods herein when being executed in the receiver node 110.

In some embodiments, a computer program 1370 comprises instructions, which when executed by the respective at least one processor 1370, cause the at least one processor of the receiver node 110 to perform the actions above.

In some embodiments, a respective carrier 1380 comprises the respective computer program 1370, wherein the carrier 1380 is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

With reference to Figure 14, in accordance with an embodiment, a communication system includes a telecommunication network 3210, such as a 3GPP-type cellular network, e.g. the wireless communications network 100, which comprises an access network 3211, such as a radio access network, and a core network 3214. The access network 3211 comprises a plurality of base stations 3212a, 3212b, 3212c, e.g. the receiver node 110 or transmitting node 120, such as AP STAs NBs, eNBs, gNBs or other types of wireless access points, each defining a corresponding coverage area 3213a, 3213b, 3213c. Each base station 3212a, 3212b, 3212c is connectable to the core network 3214 over a wired or wireless connection 3215. A first user equipment (UE), e.g. the receiver node 110 or transmitting node 120, such as a Non-AP STA 3291, located in coverage area 3213c is configured to wirelessly connect to, or be paged by, the corresponding base station 3212c. A second UE 3292 e.g. the UE 122, such as a Non-AP STA in coverage area 3213a is wirelessly connectable to the corresponding base station 3212a. While a plurality of UEs 3291, 3292 are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole UE is in the coverage area or where a sole UE is connecting to the corresponding base station 3212.

The telecommunication network 3210 is itself connected to a host computer 3230, which may be embodied in the hardware and/or software of a standalone server, a cloud- implemented server, a distributed server or as processing resources in a server farm. The host computer 3230 may be under the ownership or control of a service provider, or may be operated by the service provider or on behalf of the service provider. The connections 3221, 3222 between the telecommunication network 3210 and the host computer 3230 may extend directly from the core network 3214 to the host computer 3230 or may go via an optional intermediate network 3220. The intermediate network 3220 may be one of, or a combination of more than one of, a public, private or hosted network; the intermediate network 3220, if any, may be a backbone network or the Internet; in particular, the intermediate network 3220 may comprise two or more sub-networks (not shown).

The communication system of Figure 14 as a whole enables connectivity between one of the connected UEs 3291 , 3292 and the host computer 3230. The connectivity may be described as an over-the-top (OTT) connection 3250. The host computer 3230 and the connected UEs 3291 , 3292 are configured to communicate data and/or signaling via the OTT connection 3250, using the access network 3211 , the core network 3214, any intermediate network 3220 and possible further infrastructure (not shown) as intermediaries. The OTT connection 3250 may be transparent in the sense that the participating communication devices through which the OTT connection 3250 passes are unaware of routing of uplink and downlink communications. For example, a base station 3212 may not or need not be informed about the past routing of an incoming downlink communication with data originating from a host computer 3230 to be forwarded (e.g., handed over) to a connected UE 3291. Similarly, the base station 3212 need not be aware of the future routing of an outgoing uplink communication originating from the UE 3291 towards the host computer 3230.

Example implementations, in accordance with an embodiment, of the UE, base station and host computer discussed in the preceding paragraphs will now be described with reference to Figure 15. In a communication system 3300, a host computer 3310 comprises hardware 3315 including a communication interface 3316 configured to set up and maintain a wired or wireless connection with an interface of a different communication device of the communication system 3300. The host computer 3310 further comprises processing circuitry 3318, which may have storage and/or processing capabilities. In particular, the processing circuitry 3318 may comprise one or more programmable processors, application-specific integrated circuits, field programmable gate arrays or combinations of these (not shown) adapted to execute instructions. The host computer 3310 further comprises software 3311 , which is stored in or accessible by the host computer 3310 and executable by the processing circuitry 3318. The software 3311 includes a host application 3312. The host application 3312 may be operable to provide a service to a remote user, such as a UE 3330 connecting via an OTT connection 3350 terminating at the UE 3330 and the host computer 3310. In providing the service to the remote user, the host application 3312 may provide user data which is transmitted using the OTT connection 3350.

The communication system 3300 further includes a base station 3320 provided in a telecommunication system and comprising hardware 3325 enabling it to communicate with the host computer 3310 and with the UE 3330. The hardware 3325 may include a communication interface 3326 for setting up and maintaining a wired or wireless connection with an interface of a different communication device of the communication system 3300, as well as a radio interface 3327 for setting up and maintaining at least a wireless connection 3370 with a UE 3330 located in a coverage area (not shown) served by the base station 3320. The communication interface 3326 may be configured to facilitate a connection 3360 to the host computer 3310. The connection 3360 may be direct or it may pass through a core network (not shown) of the telecommunication system and/or through one or more intermediate networks outside the telecommunication system. In the embodiment shown, the hardware 3325 of the base station 3320 further includes processing circuitry 3328, which may comprise one or more programmable processors, application-specific integrated circuits, field programmable gate arrays or combinations of these (not shown) adapted to execute instructions. The base station 3320 further has software 3321 stored internally or accessible via an external connection.

The communication system 3300 further includes the UE 3330 already referred to. Its hardware 3335 may include a radio interface 3337 configured to set up and maintain a wireless connection 3370 with a base station serving a coverage area in which the UE 3330 is currently located. The hardware 3335 of the UE 3330 further includes processing circuitry 3338, which may comprise one or more programmable processors, applicationspecific integrated circuits, field programmable gate arrays or combinations of these (not shown) adapted to execute instructions. The UE 3330 further comprises software 3331, which is stored in or accessible by the UE 3330 and executable by the processing circuitry 3338. The software 3331 includes a client application 3332. The client application 3332 may be operable to provide a service to a human or non-human user via the UE 3330, with the support of the host computer 3310. In the host computer 3310, an executing host application 3312 may communicate with the executing client application 3332 via the OTT connection 3350 terminating at the UE 3330 and the host computer 3310. In providing the service to the user, the client application 3332 may receive request data from the host application 3312 and provide user data in response to the request data. The OTT connection 3350 may transfer both the request data and the user data. The client application 3332 may interact with the user to generate the user data that it provides. It is noted that the host computer 3310, base station 3320 and UE 3330 illustrated in Figure 15 may be identical to the host computer 3230, one of the base stations 3212a, 3212b, 3212c and one of the UEs 3291 , 3292 of Figure 14, respectively. This is to say, the inner workings of these entities may be as shown in Figure 15 and independently, the surrounding network topology may be that of Figure 14.

In Figure 15, the OTT connection 3350 has been drawn abstractly to illustrate the communication between the host computer 3310 and the use equipment 3330 via the base station 3320, without explicit reference to any intermediary devices and the precise routing of messages via these devices. Network infrastructure may determine the routing, which it may be configured to hide from the UE 3330 or from the service provider operating the host computer 3310, or both. While the OTT connection 3350 is active, the network infrastructure may further take decisions by which it dynamically changes the routing (e.g., on the basis of load balancing consideration or reconfiguration of the network).

The wireless connection 3370 between the UE 3330 and the base station 3320 is in accordance with the teachings of the embodiments described throughout this disclosure. One or more of the various embodiments improve the performance of OTT services provided to the UE 3330 using the OTT connection 3350, in which the wireless connection 3370 forms the last segment. More precisely, the teachings of these embodiments may improve the RAN effect: data rate, latency, power consumption and thereby provide benefits such as corresponding effect on the OTT service: reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime.

A measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve. There may further be an optional network functionality for reconfiguring the OTT connection 3350 between the host computer 3310 and UE 3330, in response to variations in the measurement results. The measurement procedure and/or the network functionality for reconfiguring the OTT connection 3350 may be implemented in the software 3311 of the host computer 3310 or in the software 3331 of the UE 3330, or both. In embodiments, sensors (not shown) may be deployed in or in association with communication devices through which the OTT connection 3350 passes; the sensors may participate in the measurement procedure by supplying values of the monitored quantities exemplified above, or supplying values of other physical quantities from which software 3311, 3331 may compute or estimate the monitored quantities. The reconfiguring of the OTT connection 3350 may include message format, retransmission settings, preferred routing etc.; the reconfiguring need not affect the base station 3320, and it may be unknown or imperceptible to the base station 3320. Such procedures and functionalities may be known and practiced in the art. In certain embodiments, measurements may involve proprietary UE signaling facilitating the host computer’s 3310 measurements of throughput, propagation times, latency and the like. The measurements may be implemented in that the software 3311, 3331 causes messages to be transmitted, in particular empty or ‘dummy’ messages, using the OTT connection 3350 while it monitors propagation times, errors etc.

Figure 16 is a flowchart illustrating a method implemented in a communication system, in accordance with one embodiment. The communication system includes a host computer, a base station such as a AP STA, and a UE such as a Non-AP STA which may be those described with reference to Figure 15 and Figure 14. For simplicity of the present disclosure, only drawing references to Figure 16 will be included in this section. In a first step 3410 of the method, the host computer provides user data. In an optional substep 3411 of the first step 3410, the host computer provides the user data by executing a host application. In a second step 3420, the host computer initiates a transmission carrying the user data to the UE. In an optional third step 3430, the base station transmits to the UE the user data which was carried in the transmission that the host computer initiated, in accordance with the teachings of the embodiments described throughout this disclosure. In an optional fourth step 3440, the UE executes a client application associated with the host application executed by the host computer.

Figure 17 is a flowchart illustrating a method implemented in a communication system, in accordance with one embodiment. The communication system includes a host computer, a base station such as a AP STA, and a UE such as a Non-AP STA which may be those described with reference to Figure 15 and Figure 14. For simplicity of the present disclosure, only drawing references to Figure 17 will be included in this section. In a first step 3510 of the method, the host computer provides user data. In an optional substep (not shown) the host computer provides the user data by executing a host application. In a second step 3520, the host computer initiates a transmission carrying the user data to the UE. The transmission may pass via the base station, in accordance with the teachings of the embodiments described throughout this disclosure. In an optional third step 3530, the UE receives the user data carried in the transmission.

Figure 18 is a flowchart illustrating a method implemented in a communication system, in accordance with one embodiment. The communication system includes a host computer, a base station such as an AP STA, and a UE such as a Non-AP STA which may be those described with reference to Figure 15 and Figure 14. For simplicity of the present disclosure, only drawing references to Figure 18 will be included in this section. In an optional first step 3610 of the method, the UE receives input data provided by the host computer. Additionally or alternatively, in an optional second step 3620, the UE provides user data. In an optional substep 3621 of the second step 3620, the UE provides the user data by executing a client application. In a further optional substep 3611 of the first step 3610, the UE executes a client application which provides the user data in reaction to the received input data provided by the host computer. In providing the user data, the executed client application may further consider user input received from the user. Regardless of the specific manner in which the user data was provided, the UE initiates, in an optional third substep 3630, transmission of the user data to the host computer. In a fourth step 3640 of the method, the host computer receives the user data transmitted from the UE, in accordance with the teachings of the embodiments described throughout this disclosure.

Figure 19 is a flowchart illustrating a method implemented in a communication system, in accordance with one embodiment. The communication system includes a host computer, a base station such as a AP STA, and a UE such as a Non-AP STA which may be those described with reference to Figure 15 and Figure 14. For simplicity of the present disclosure, only drawing references to Figure 19 will be included in this section. In an optional first step 3710 of the method, in accordance with the teachings of the embodiments described throughout this disclosure, the base station receives user data from the UE. In an optional second step 3720, the base station initiates transmission of the received user data to the host computer. In a third step 3730, the host computer receives the user data carried in the transmission initiated by the base station.

When using the word "comprise" or “comprising” it shall be interpreted as nonlimiting, i.e. meaning "consist at least of". The embodiments herein are not limited to the above described preferred embodiments. Various alternatives, modifications and equivalents may be used.

Abbreviation Explanation

MIMO Multiple input multiple output

NR New Radio

Tx Transmitter

HSDPA High Speed Downlink Packet Access

DCI Downlink control Index

HARQ Hybrid automatic repeat request

CRC Cyclic redundancy check

NAK Non-acknowledgement

ACK Acknowledgement

UE User Equipment

CQI Channel quality information

MMSE Minimum Mean Square Error

ML Maximum Likelihood

MAP Maximum Aposteriori Probability

TTI Transmit Time Interval

PCI Precoding control index

BS Base Station

D2D Device-to-Device

HD Half Duplex

M2M Machine-To-Machine

MTC Machine-Type Communication

UE User Equipment eNB Evolved Node B, base station

E-UTRAN Evolved universal terrestrial radio access network

E-UTRA Evolved universal terrestrial radio access

E-UTRA FDD E-UTRA frequency division duplex

E-UTRA TDD E-UTRA time division duplex

LTE Long term evolution

RAT Radio Access Technology

RRC Radio resource control

TDD Time division duplex BSC Base station Controller

HSPA High Speed Packet Access

GSM Global system for mobile communication

UTRA Universal terrestrial radio access

UTRA FDD UTRA frequency division duplex

UTRA TDD UTRA time division duplex

WLAN Wireless Local Area Network

GERAN GSM EDGE Radio Access Network

EDGE Enhanced Data rates for GSM Evolution

CDMA2000 Code division multiple access 2000

HRPD High rate packet data

DL Downlink

PDCCH Physical Downlink Control Channel

PCFICH Physical Control format Indicator

PDSCH Physical Downlink Shared Channel

PHICH Physical Hybrid ARQ Indicator Channel

RE Resource Element

RB Resource Block

RS Reference signal

SINR Signal-to-lnterference Ratio

DPD Digital Predistortion

Claims

1 . A method performed by a receiver node (110) for mitigation of distortion of a nonlinearity at a transmitting node (120) in a communications network (100), the method comprising: signalling (901) information to the transmitting node (120), which information indicates that the receiver node (110) is capable of decoding nonlinear signals transmitted by the transmitting node (120), jointly estimating (903) channel coefficients and coefficients of nonlinearity of a channel received (902) from the transmitting node (120), and applying (904) the jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information.

2. The method according to claim 1 , wherein jointly estimating (903) channel coefficients and coefficients of the nonlinearity is performed by iterating the channel estimation and estimation of the nonlinearity of the transmitting node (120), to obtain the jointly estimated channel coefficients and coefficients of the nonlinearity, until a stopping criterion is fulfilled.

3. The method according to claim 2, wherein the iterating of the channel estimation and estimation of the nonlinearity of the transmitting node (120), to obtain estimated channel coefficients and coefficients of the nonlinearity, until a stopping criterion is fulfilled, is performed by: based on assuming that a signal received from the transmitting node (120) is linearly generated, estimating (Step 1) the channel using least squares estimation from the received signal, estimating (Step 2) the nonlinearity from the received signal based on the estimated channel, and based on reference symbols of the received signal, based on the estimated nonlinearity, re-estimating (Step 3) the channel to reduce the effect of nonlinearity from the received signal, repeating (Step 4) iterations of the estimating (Step 2) of the nonlinearity from the received signal and the re-estimating (Step 3) of the channel to reduce the effect of the nonlinearity from the received signal based on the estimated nonlinearity until the stopping criterion is fulfilled.

4. The method according to any of the claims 1-3, wherein the stopping criterion to be fulfilled is represented by a convergence criterion.

5. The method according to any of the claims 1-4, further comprising: signalling (905) information to the transmitting node (120), which information indicates said applying (904) of the obtained jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information.

6. The method according to any of the claims 1-5, wherein the obtained jointly estimated channel coefficients and coefficients of the nonlinearity to detect soft bit information are applied (904) for detecting data transmitted by the transmitting node (120), according to any one out of Method 1 and Method 2, wherein:

Method 1 comprises passing the received signal from a linear finite impulse response filter, where filter weights are computed based on a minimum mean square criteria, and passing the output of the filter to received Digital Predistortion, DPD, which received DPD depends on the estimated coefficients of the nonlinearity, and obtaining the soft bit information, and

Method 2 comprises generating the soft bit information from the received signal, the estimated channel coefficients and coefficients of the nonlinearity by using a maximum aPosteriori probability criteria.

7. The method according to any of the claims 1-6, wherein the method performed by a receiver node (110) is applied for to any one out of: downlink transmissions wherein the receiver node (110) is a User Equipment, UE, or uplink transmissions wherein the receiver node (110) is a radio network node.

8. The method according to any of the claims 1-7, wherein the method is applied for downlink transmissions wherein the receiver node (110) is a UE, and the transmitting node (120) is a radio network node, and wherein the information signalled (901) to the transmitting node (120), further comprises an indication indicating that the receiver node (110) performs estimation of the nonlinearity of the transmitting node (120).

9. The method according to any of the claims 1-8, wherein: the jointly estimating (903) of the channel coefficients and coefficients of nonlinearity of a channel received (902) from the transmitting node (120) at the transmitting node (120), is performed by DPD Technique, at the receiver node (110).

10. The method according to any of the claims 1-9, wherein the method is applied for uplink transmissions wherein the receiver node (110) is a radio network node, and the transmitting node (120) is a UE, the method further comprising: wherein the information signalled (901) to the transmitting node (120), further comprises an indication indicating any one or more out of:

- to not power back off a Power Amplifier, PA, of the transmitting node (120) operating in the nonlinear region, and that the receiver node (110) is capable of compensating for nonlinearity of the transmitting node (120).

11. A computer program (1370) comprising instructions, which when executed by a processor (1350), causes the processor to perform actions according to any of the claims 1-10.

12. A carrier (1380) comprising the computer program (1370) of claim 11, wherein the carrier is one of an electronic signal, an optical signal, an electromagnetic signal, a magnetic signal, an electric signal, a radio signal, a microwave signal, or a computer-readable storage medium.

13. A receiver node (110) configured to mitigate distortion of a nonlinearity at a transmitting node (120) in a communications network (100), the receiver node (110) further being configured to: signal information to the transmitting node (120), which information is adapted to indicate that the receiver node (110) is capable of decoding nonlinear signals transmitted by the transmitting node (120), jointly estimating channel coefficients and coefficients of nonlinearity of a channel received from the transmitting node (120), and apply the jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information. The receiver node (110) according to claim 13, further configured to: jointly estimate the channel coefficients and the coefficients of the nonlinearity by iterating the channel estimation and estimation of the nonlinearity of the transmitting node (120), to obtain the jointly estimated channel coefficients and coefficients of the nonlinearity, until a stopping criterion is fulfilled. The receiver node (110) according to claim 14, further configured to: iterate the channel estimation and estimation of the nonlinearity of the transmitting node (120), to obtain estimated channel coefficients and coefficients of the nonlinearity, until a stopping criterion is fulfilled, by: based on an assumption that a signal received from the transmitting node (120) is linearly generated, estimate (Step 1) the channel using least square estimation from the received signal, estimate (Step 2) the nonlinearity from the received signal based on the estimated channel, and based on reference symbols of the received signal, based on the estimated nonlinearity, re-estimate (Step 3) the channel to reduce the effect of nonlinearity from the received signal, repeat (Step 4) iterations of the estimation (Step 2) of the nonlinearity from the received signal and the re-estimation (Step 3) of the channel to reduce the effect of the nonlinearity from the received signal based on the estimated nonlinearity until the stopping criterion is fulfilled. The receiver node (110) according to any of the claims 13-15, wherein the stopping criterion to be fulfilled is adapted to be represented by a convergence criterion. The receiver node (110) according to any of the claims 13-16, further configured to: signal information to the transmitting node (120), which information is adapted to indicate said applying of the obtained jointly estimated channel coefficients and the coefficients of the nonlinearity to detect soft bit information. The receiver node (110) according to any of the claims 13-17, wherein the obtained jointly estimated channel coefficients and coefficients of the nonlinearity to detect soft bit information are arranged to be applied for detecting data transmitted by the transmitting node (120), according to any one out of Method 1 and Method 2, wherein:

Method 1 is arranged to comprise: passing the received signal from a linear finite impulse response filter, where filter weights are arranged to be computed based on a minimum mean square criteria, passing the output of the filter to received Digital Pre-distortion, DPD, which received DPD is adapted to depend on the estimated coefficients of the nonlinearity, and obtaining the soft bit information, and

Method 2 is arranged to comprise: generating the soft bit information from the received signal, the estimated channel coefficients and coefficients of the nonlinearity by using a maximum a posteriori probability criteria. The receiver node (110) according to any of the claims 13-18, wherein the configurations of the receiver node (110) are arranged to be applied for to any one out of: downlink transmissions wherein the receiver node (110) is arranged to be a User Equipment, UE, or uplink transmissions wherein the receiver node (110) is arranged to be a radio network node. The receiver node (110) according to any of the claims 13-19, wherein the configurations of the receiver node (110) are arranged to be applied for downlink transmissions wherein the receiver node (110) is arranged to be a UE, and the transmitting node (120) is arranged to be a radio network node, and wherein the information signalled to the transmitting node (120), further is adapted to comprise an indication indicating that the receiver node (110) is arranged to perform estimation of the nonlinearity of the transmitting node (120). The receiver node (110) according to any of the claims 13-20, wherein: the receiver node (110) is configured to the jointly estimate of the channel coefficients and coefficients of nonlinearity of a channel received (902) from the transmitting node (120) by using DPD Technique, at the receiver node (110, by a DPD Technique, at the receiver node (110). The receiver node (110) according to any of the claims 13-21, wherein the configurations of the receiver node (110) are arranged to be applied for uplink transmissions wherein the receiver node (110) is arranged to be a radio network node, and the transmitting node (120) is arranged to be a UE, wherein the information signalled to the transmitting node (120), further is adapted to comprise an indication indicating any one or more out of:

- to not power back off a Power Amplifier, PA, of the transmitting node (120) operating in the nonlinear region, and

- that the receiver node (110) is capable of compensating for nonlinearity of the transmitting node (120).