Apparatus, method and computer program product for communication

Abstract

This application is titled "Frequency Offset Estimation and Reduction". This document discloses a solution for reducing frequency offset. According to one aspect, a method includes: obtaining a signal distorted by a frequency offset; estimating a frequency offset estimate that describes the frequency offset; calculating coefficients for a frequency domain filter based on a relationship between the frequency offset estimate and a combination of the frequency offset estimate and an index of the frequency domain filter; and performing frequency domain filtering of the signal by using the calculated coefficients.

Description

Technical Field

[0001] The various embodiments described herein relate to the field of radio devices, and more particularly, to estimating and correcting frequency offsets from received signals. Background Art

[0002] Frequency offset is a characteristic that distorts radio signals for communication between radio devices. The frequency offset may be caused by an offset between local oscillators of a radio transmitter and a radio receiver, or it may be caused by the Doppler effect associated with the mobility of the radio transmitter relative to the radio receiver. For example, for a multi-carrier signal, the frequency offset causes inter-carrier interference, which degrades the performance of receiver signal processing and increases the number of incorrect decoding decisions. Therefore, it is beneficial to reduce the impact of the frequency offset. Summary of the Invention

[0003] Some aspects of the invention are defined by the independent claims.

[0004] Some embodiments of the invention are defined in the dependent claims.

[0005] Embodiments and features (if any) described in this specification that do not fall within the scope of the independent claims will be construed as examples that contribute to an understanding of the various embodiments of the invention. Some aspects of the present disclosure are defined by the independent claims.

[0006] According to one aspect, there is provided an apparatus including components for performing the following: obtaining a signal distorted by a frequency offset; estimating a frequency offset estimate that describes the frequency offset; calculating coefficients for a frequency domain filter based on a relationship between the frequency offset estimate and a combination of the frequency offset estimate and an index of the frequency domain filter; and performing frequency domain filtering of the signal by using the calculated coefficients.

[0007] In one embodiment, the relationship is defined as

[0008]

[0009] In one embodiment, the component is configured to: set an upper limit value for the frequency offset estimate, and if the frequency offset estimate is greater than the upper limit value, replace the frequency offset estimate with the upper limit value in the calculation of the coefficients.

[0010] In one embodiment, the relationship is defined as

[0011]

[0012] where ε is the frequency offset estimate in normalized form, α is the upper limit value, and k is the filter index.

[0013] In one embodiment, the signal includes a plurality of subcarriers, and the component is further configured to correct, as part of another radio receiver signal processing algorithm performed on the signal, a phase rotation error caused by a frequency offset that is common to all subcarriers of the signal.

[0014] In one embodiment, the another radio receiver signal processing algorithm is a channel equalization algorithm or an interference suppression combining algorithm, and the channel equalization algorithm is configured to estimate and reduce distortion caused to the signal by a radio channel.

[0015] In one embodiment, the another radio receiver signal processing algorithm is configured to combine terms where N represents the size of a Fourier transform, and represents a frequency offset estimate.

[0016] In one embodiment, the calculated coefficient is a real algebraic number.

[0017] In one embodiment, the component includes at least one processor and at least one memory, the at least one memory includes computer program code, and the at least one memory and the computer program code are configured to cause the execution of the device together with the at least one processor.

[0018] In one embodiment, the device includes a terminal device of a cellular communication system.

[0019] According to one aspect, a method is provided, including: obtaining a signal distorted by a frequency offset; estimating a frequency offset estimate that describes the frequency offset; calculating coefficients for a frequency domain filter based on a relationship between the frequency offset estimate and a combination of the frequency offset estimate and an index of the frequency domain filter; and performing frequency domain filtering of the signal by using the calculated coefficients.

[0020] In one embodiment, the relationship is defined as

[0021]

[0022] In one embodiment, the method includes: setting an upper limit value for the frequency offset estimate, and if the frequency offset estimate is greater than the upper limit value, substituting the upper limit value for the frequency offset estimate in the calculation of the coefficients.

[0023] In one embodiment, the relationship is defined as

[0024]

[0025] where ε is the frequency offset estimate in normalized form, α is the upper limit value, and k is the filter index.

[0026] In one embodiment, the signal comprises a plurality of sub - carriers, and the method includes correcting, as part of another radio receiver signal - processing algorithm performed on the signal, a phase - rotation error caused by a frequency offset that is common to all sub - carriers of the signal.

[0027] In one embodiment, the another radio receiver signal - processing algorithm is a channel - equalization algorithm or an interference - suppression combining algorithm, and the channel - equalization algorithm is configured to estimate and reduce distortion caused to the signal by a radio channel.

[0028] In one embodiment, the another radio receiver signal - processing algorithm is configured to combine terms where N represents the size of a Fourier transform, and represents a frequency - offset estimate.

[0029] In one embodiment, the calculated coefficients are real - valued algebraic numbers.

[0030] In one embodiment, the method is performed by a terminal device of a cellular communication system. In another embodiment, the method is performed by an access node of a cellular communication system.

[0031] According to one aspect, there is provided a computer - program product embodied on a computer - readable medium and including computer - program code readable by a computer, wherein the computer - program code configures the computer to perform a computer process including: obtaining a signal distorted by a frequency offset; estimating a frequency - offset estimate that describes the frequency offset; calculating coefficients for a frequency - domain filter based on a relationship between the frequency - offset estimate and a combination of the frequency - offset estimate and an index of the frequency - domain filter; and performing frequency - domain filtering of the signal by using the calculated coefficients. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Embodiments are described below only by way of example and with reference to the drawings, in which

[0033] Figure 1 a wireless - communication scenario in which some embodiments of the present invention can be applied is shown;

[0034] Figure 2 a process for reducing a frequency offset according to one embodiment is shown;

[0035] Figure 3 a process for reducing a scaling error according to one embodiment is shown;

[0036] Figure 4 a process for combining frequency - offset reduction of Figure 2 with another signal - processing function according to one embodiment is shown; and

[0037] Figure 5A block diagram showing the structure of a device according to an embodiment. Detailed implementation

[0038] The following embodiments are examples. Although the specification may refer to "an", "one", or "some" embodiments in several places, this does not necessarily mean that each such reference is to the same (multiple) embodiment, or that the feature applies only to a single embodiment. Individual features of different embodiments can also be combined to provide other embodiments. In addition, the words "comprising" and "including" should be understood not to limit the described embodiments to only the features that have been mentioned, and such embodiments may also include features / structures not specifically mentioned.

[0039] Below, different exemplary embodiments will be described using a radio access architecture based on Long-Term Evolution Advanced (LTE-A) or New Radio (NR, 5G) as an example of an access architecture to which the embodiments can be applied. However, the embodiments are not limited to such an architecture. Those skilled in the art will recognize that, by appropriately adjusting parameters and processes, the embodiments can also be applied to other types of communication networks having suitable components. Some examples of other options for applicable systems are Universal Mobile Telecommunications System (UMTS) Radio Access Network (UTRAN or E-UTRAN), Long-Term Evolution (LTE, the same as E-UTRA), Wireless Local Area Network (WLAN or WiFi), Worldwide Interoperability for Microwave Access (WiMAX), Personal Communication Service (PCS), Wideband Code Division Multiple Access (WCDMA), systems using Ultra-Wideband (UWB) technology, sensor networks, Mobile Ad Hoc Networks (MANET), and Internet Protocol Multimedia Subsystem (IMS) or any combination thereof.

[0040] Figure 1 An example of a simplified system architecture is described, showing only some elements and functional entities, all of which are logical units, and their implementation may be different from what is shown. Figure 1 The connections shown are logical connections; the actual physical connections may be different. It will be obvious to those skilled in the art that the system generally also includes functions and structures different from Figure 1 those shown.

[0041] However, the present embodiment is not limited to the system given as an example, and those skilled in the art can apply this solution to other communication systems provided with the necessary attributes.

[0042] Figure 1 The example of... shows a part of an example radio access network.

[0043] Figure 1 It is shown that the terminal devices or user equipments 100 and 102 are configured to be wirelessly connected to an access node (such as an (e / g)NodeB) 104 that provides the cell on one or more communication channels in the cell. The (e / g)NodeB refers to an eNodeB or a gNodeB, as defined in the 3GPP specifications. The physical link from the user equipment to the (e / g)NodeB is called the uplink or reverse link, and the physical link from the (e / g)NodeB to the user equipment is called the downlink or forward link. It should be understood that the (e / g)NodeB or their functions can be implemented by any entity such as a node, host, server, or access point suitable for such purposes.

[0044] A communication system usually includes more than one (e / g)NodeB. In this case, the (e / g)NodeB can also be configured to communicate with each other through wired or wireless links designed for this purpose. These links can be used not only for signaling purposes but also for routing data from one (e / g)NodeB to another (e / g)NodeB. The (e / g)NodeB is a computing device configured to control the radio resources of the communication system coupled thereto. The NodeB can also be referred to as a base station, access point, access node, or any other type of interface device, including a relay station capable of operating in a wireless environment. The (e / g)NodeB includes or is coupled to a transceiver. From the transceiver of the (e / g)NodeB, a connection is provided to an antenna unit that establishes a two-way radio link to the user equipment. The antenna unit can include multiple antennas or antenna elements. The (e / g)NodeB is also connected to the core network 110 (CN or Next Generation Core NGC). Depending on the system, the corresponding party on the CN side can be a Serving Gateway (S-GW that routes and forwards user data packets), a Packet Data Network Gateway (P-GW) for providing a connection from the User Equipment (UE) to an external packet data network, or a Mobility Management Entity (MME), etc.

[0045] A user device (also known as UE, user equipment, user terminal, terminal device, etc.) illustrates a type of device to which resources on the air interface are allocated and assigned. Thus, any feature described herein regarding a user equipment can be implemented using a corresponding device, such as a relay node. An example of such a relay node is a layer 3 relay (self-backhaul relay) towards a base station. The 5G specification supports at least the following relay operation modes: out-of-band relay, where different carriers and / or RATs (radio access technologies) can be defined for the access link and the backhaul link; and in-band relay, where the same carrier frequency or radio resources are used for the access and backhaul links. In-band relay can be considered as the baseline relay scenario. The relay node is called an integrated access and backhaul (IAB) node. It also has built-in support for multiple relay hops. The IAB operation employs a so-called split architecture that has a CU and multiple DUs. The IAB node contains two separate functions: the DU (distributed unit) part of the IAB node facilitates the gNB (access node) function in the relay cell, i.e., it acts as the access link; and the MT (mobile terminal) part of the IAB node contributes to the backhaul connection. The donor node (DU part) communicates with the MT part of the IAB node, and it has a wired connection to the CU, which in turn is connected to the core network. In a multi-hop scenario, the MT part (sub-IAB node) communicates with the DU part of the parent IAB node.

[0046] A user equipment generally refers to a portable computing device, including wireless mobile communication devices that operate with or without a subscriber identity module (SIM), including but not limited to the following types of devices: mobile stations (mobile phones), smartphones, personal digital assistants (PDAs), cellular phones, devices using a wireless modem (alarm or measurement devices, etc.), laptop computers and / or touchscreen computers, tablet computers, gaming consoles, notebooks, and multimedia devices. It should be understood that a user equipment can also be an almost exclusively uplink-only device, an example of which is a camera or video camera that uploads images or video clips to the network. A user equipment can also be a device capable of operating in an Internet of Things (IoT) network, which is a scenario where objects are provided with the ability to transfer data over a network without human-to-human or human-to-computer interaction. A user equipment can also utilize the cloud. In some applications, a user equipment may include small portable devices with radio components (such as watches, headphones, or glasses), and the computing is performed in the cloud. A user equipment (or in some embodiments, a layer 3 relay node) is configured to perform one or more user equipment functions. A user equipment can also be referred to as a user unit, mobile station, remote terminal, access terminal, user terminal, or user equipment (UE), to name just a few names or devices.

[0047] The various techniques described herein can also be applied to cyber-physical systems (CPSs), which are systems in which collaborative computing elements control physical entities. CPSs can implement and utilize a large number of interconnected ICT devices (sensors, actuators, processor microcontrollers, etc.) embedded in physical objects at different locations. Mobile cyber-physical systems, in which the physical systems under discussion have inherent mobility, are a subclass of cyber-physical systems. Examples of mobile physical systems include mobile robots and electronic products transported by humans or animals.

[0048] Additionally, although the apparatus is described as a single entity, different units, processors, and / or memory units can be implemented ( Figure 1 not all shown in

[0049] 5G supports the use of multiple-input multiple-output (MIMO) antennas, a much larger number of base stations or nodes than LTE (the so-called small cell concept), including macro sites that cooperate with smaller base stations, and employs various radio technologies depending on service requirements, use cases, and / or available spectrum. 5G mobile communications supports a wide range of use cases and related applications, including video streaming, augmented reality, different ways of data sharing, and various forms of machine type applications such as (massive) machine type communications (mMTC), including vehicle safety, different sensors, and real-time control. 5G is expected to have multiple radio interfaces, namely below 6 GHz, cmWave, and mmWave, and is also capable of integrating with existing traditional radio access technologies such as LTE. At least in the early stages, the integration with LTE can be achieved as a system in which macro coverage is provided by LTE while 5G radio interface access comes from small cells by aggregating to LTE. In other words, 5G is planned to support inter-RAT operability (e.g., LTE-5G) and inter-RI operability (inter-radio interface operability, e.g., below 6 GHz–cmWave, below or at 6 GHz–cmWave–mmWave). One of the concepts considered for use in 5G networks is network slicing, in which multiple independent and dedicated virtual subnets (network instances) can be created in the same infrastructure to run services with different requirements for latency, reliability, throughput, and mobility.

[0050] The current architecture in LTE networks is fully distributed in the radio and typically fully centralized in the core network. Low-latency applications and services in 5G require bringing content closer to the radio, which gives rise to local breakout and multi-access edge computing (MEC). 5G enables analytics and knowledge generation to occur at the data source. This approach requires leveraging resources that may not be continuously connected to the network, such as laptops, smartphones, tablets, and sensors. MEC provides a distributed computing environment for hosting applications and services. It is also capable of storing and processing content closer to cellular users to accelerate response times. Edge computing encompasses a wide range of technologies, such as wireless sensor networks, mobile data collection, mobile signature analysis, collaborative distributed peer-to-peer networking and processing, and can also be classified as local cloud / fog computing and grid / mesh computing, dew point computing, mobile edge computing, thin cloud, distributed data storage and retrieval, self-healing autonomous networks, remote cloud services, augmented and virtual reality, data caching, Internet of Things (massive connectivity and / or latency-critical), mission-critical communications (autonomous vehicles, traffic safety, real-time analytics, time-critical control, medical applications).

[0051] The communication system is also capable of communicating with other networks 112, such as the public switched telephone network or the Internet, or leveraging services provided by them. The communication network is also capable of supporting the use of cloud services, for example, at least a portion of the core network operations can be performed as cloud services (which is depicted by the "cloud" 114 in Figure 1 ). The communication system may also include a central control entity, etc., to facilitate cooperation among networks of different operators, for example, in spectrum sharing.

[0052] The edge cloud can be brought into the radio access network (RAN) by leveraging network function virtualization (NFV) and software-defined network (SDN). Using the edge cloud may mean performing access node operations at least partially in a server, host, or node that is operably coupled to a remote radio head or base station including a radio portion. The node operations may also be distributed among multiple servers, nodes, or hosts. The application of the cloud RAN architecture enables the RAN real-time functions to be executed on the RAN side (in the distributed unit DU 105) and the non-real-time functions to be executed in a centralized manner (in the centralized unit CU 108).

[0053] It should also be understood that the functional distribution between core network operations and base station operations may be different from that of LTE or may not even exist. Some other technological advancements that may be used are big data and all-IP, which may change the way the network is built and managed. 5G (or new radio NR) networks are designed to support multiple hierarchies, where MEC servers can be placed between the core and the base station or node B (gNB). It should be understood that MEC can also be applied to 4G networks.

[0054] 5G can also utilize satellite communication to enhance or supplement the coverage of 5G services, for example, by providing backhaul. Possible use cases are to provide service continuity for machine-to-machine (M2M) or Internet of Things (IoT) devices or in-vehicle passengers, or to ensure service availability for critical communications and future railway, maritime, and / or aviation communications. Satellite communication can utilize geostationary orbit (GEO) satellite systems, but can also utilize low Earth orbit (LEO) satellite systems, especially megaconstellations (systems in which hundreds of (nano)satellites are deployed). Each satellite 109 in a megaconstellation can cover several network entities that support satellites for creating terrestrial cells. Terrestrial cells can be created by terrestrial relay nodes or by gNBs located on the ground or in satellites.

[0055] It will be apparent to those skilled in the art that the depicted system is only an example of a part of a radio access system, and in practice, the system may include multiple (e / g)NodeBs, user equipment may have access to multiple radio cells, and the system may also include other devices, such as physical layer relay nodes or other network elements, etc. At least one of the (e / g)NodeBs or may be a home (e / g)NodeB. Additionally, in the geographical area of a radio communication system, multiple different types of radio cells and multiple radio cells may be provided. Radio cells can be macrocells (or umbrella cells), which are large cells, typically having a diameter of up to several tens of kilometers, or smaller cells, such as microcells, femtocells, or picocells. Figure 1 The (e / g)NodeBs can provide any of these cells. A cellular radio system can be implemented as a multi-layer network including multiple types of cells. Typically, in a multi-layer network, one access node provides one or more types of cells, so multiple (e / g)NodeBs are required to provide such a network structure.

[0056] To meet the needs for the deployment and performance of improved communication systems, the concept of "plug-and-play" (e / g)NodeBs has been introduced. Generally, in addition to home (e / g)NodeBs (H(e / g)NodeBs), a network capable of using "plug-and-play" (e / g)NodeBs also includes a home node B gateway, or HNB-GW ( Figure 1 not shown in the figure). The HNB gateway (HNB-GW), which is typically installed in the operator's network, can aggregate traffic from a large number of HNBs back to the core network.

[0057] As described in the background art, frequency offset requires compensation in a device for a radio receiver. Nowadays, radio communication is based on multi-carrier transmission, such as orthogonal frequency division multiplexing (OFDM) or single-carrier frequency division multiple access (SC-FDMA). 5G networks employ various variants of OFDM. Although SC-FDMA is ultimately a single-carrier signal, it employs multi-carrier transmission and received signal processing functions and is thus sometimes referred to as a virtual multi-carrier transmission scheme. In some designs, frequency offset compensation is divided into common phase rotation compensation and (sub) carrier interference (ICI) compensation. In common phase rotation compensation, the phase rotation common to all sub-carriers of each OFDM symbol in a multi-carrier signal is compensated for each terminal device. In ICI compensation, a frequency domain filter is applied to compensate for the inter-carrier interference (ICI) caused by frequency offsets that may be different for each sub-carrier. ICI compensation is particularly effective for high data rate modulation and coding schemes and for large frequency offsets. The smaller the frequency offset, the smaller the impact of ICI and is canceled out by the sub-carrier spacing, while low data rate modulation and coding schemes (such as quadrature phase shift keying (QPSK)) tolerate this ICI. The embodiments described below focus on ICI compensation. The purpose of ICI compensation is to reduce ICI and thus improve the decoding of data included in the received multi-carrier signal subject to ICI compensation. In other words, after ICI compensation according to any of the embodiments described below, the received signal may be subject to other signal processing tasks including decoding.

[0058] Figure 2 An embodiment of a process for reducing frequency offset and the resulting ICI is illustrated. The process may be performed by a device for an access node (e.g., DU or CU), or it may be performed by a device for a terminal device 100 or 102. Refer to Figure 2 , the process includes: obtaining (block 200) a signal distorted by a frequency offset; estimating (block 202) a frequency offset estimate that describes the frequency offset; calculating (block 204) the coefficients of a frequency domain filter based on the frequency offset estimate and the relationship between the frequency offset estimate and the index of the frequency domain filter; and performing (block 206) frequency domain filtering of the multi-carrier signal by using the calculated coefficients.

[0059] The frequency domain filter performs ICI filtering by using the calculated coefficients. The use of the relationship between the frequency offset estimate and the combination of the frequency offset estimate and the filter coefficient index achieves a reduction in computational complexity because it performs the calculation by using algebraic real numbers, in other words, omits the calculation with complex values. As a result, the power consumption is also reduced. Another characteristic of using real numbers is related to an embodiment in which the filter coefficients are pre-calculated and pre-stored in a memory. Using real numbers instead of complex values reduces the memory requirement by a factor of 2.

[0060] The signal can be a multi-carrier signal, such as an OFDM signal. However, ICI may also exist in single-carrier signals that are subject to the fast Fourier transform (FFT). ICI observed in the frequency domain is caused by the windowing of the finite-length FFT.

[0061] The frequency offset can be calculated by using any estimation algorithm known in the art. Dozens of different methods are given in the literature to estimate the frequency offset caused by Doppler or the offset between the local oscillators of the transmitter and the receiver, and those skilled in the art are able to select a suitable estimation method based on the design of the radio receiver. The embodiments described herein focus on how the frequency offset estimation is used to calculate the coefficients for ICI compensation (reduction). Generally, ICI compensation is performed by using a frequency-domain filter that is applied to the frequency-domain samples of the subcarriers via a convolution operation. The filter is usually limited to the required length, for example, it can be five taps or seven taps or nine taps or eleven taps. The filter can be applied in a cyclic manner, which means that the subcarrier samples are cyclically arranged for the convolution operation. Thus, for a filter with five taps, the subcarrier with the lowest subcarrier index becomes convolved with all the filter coefficients having tap indices k = [-2, -1, 0, 1, 2]. The same principle applies to other filter lengths F, and the general rule for the tap indices can be defined as k = [-(F - 1) / 2,..., 0,..., (F - 1) / 2].

[0062] Then let us describe the mathematics and logic of the process that causes Figure 2 Let us first define as the normalized frequency offset estimate for the i-th terminal device, and let N define the size of the FFT, as described above. The normalized frequency offset can be understood as

[0063]

[0064] The coefficients for the frequency-domain filter can then be written in the following form, as known in the literature.

[0065]

[0066] where k represents the filter coefficient index within the FOC. It is obvious that when k, the coefficients have complex values. This also shows that the magnitude of the filter coefficients within the FOC follows the well-known sinc function. Next, let us reorganize the coefficient definition as

[0067]

[0068] where defines the magnitude scaling of the filter. Now, focusing on Ci Redefinition of (k), noting the term is independent of the filter coefficient index k and is thus common to all subcarriers. This means that this term can be removed from the definition of the frequency-domain filter coefficients without any loss of performance. This term can be incorporated into the common phase rotation compensation or into another receiver signal processing task that involves phase rotation of a phase common to all subcarriers. In cases where the receiver signal processing task involves algorithms that easily perform common phase rotation, such as the interference rejection combining (IRC) process or the maximum ratio combining (MRC) process, this term can be ignored. In such cases, the same filter coefficients can be used to correct the channel estimate and the data symbols, and the IRC / MRC equalization compensates for the common phase error from the equalized data symbols.

[0069] Next, look at the remaining exponential term This term depends on the filter coefficient index k and the FFT size N. Considering modern communication systems such as 4G LTE and 5G NR, we know that the smallest FFT size typically used corresponds to N = 128. This means that if we approximate the maximum error will only be 0.8%. Thus, we can make this approximation with a relatively small impact on performance. What remains is the term e -jπk , which is a phase rotator that provides values of -1 or +1 depending on the value of k, since the phase jumps in steps of π radians. Thus, this term can be rewritten as e -jπk = (-1) k . Thus, the (algebraic) real-valued filter coefficients are now defined as

[0070]

[0071] Then, by noting that typically and N >> k, we can use the simplification N >> x to simplify the denominator. This simplification is again particularly effective for modern communication systems that employ large N values. The simplified real-valued filter coefficients are now defined as

[0072]

[0073] Additionally, the numerator can also be simplified to the following form, based on the well-known sine function property sin(x + y) = [sin(x)cos(y) + cos(x)sin(y)]:

[0074]

[0075] By assuming that the normalized frequency offset estimate is small enough to satisfy the relation This coefficient can be further simplified:

[0076] where if then C i (0) = 1. (6)

[0077] Therefore, in one embodiment, the relationship between the frequency offset estimate and the combination of the frequency offset estimate and the filter coefficient index is the ratio described in equation (6), i.e., the carrier frequency offset estimate and the carrier frequency offset estimate and the sum of the filter coefficient index k. It should be understood that in some embodiments, additional factors are incorporated into the calculation of block 204, such as a scaling factor and / or a bias (offset) factor.

[0078] Compared with using equation (1), using equation (6) to calculate the coefficient reduces the number of calculation operations. The calculation of the coefficient based on equation (1) would rely on using a table to calculate trigonometric functions. By eliminating the trigonometric functions via the above approximation, the need for the table is also eliminated, thus reducing the memory resources required to calculate the coefficient. Another significant feature of the simplified calculation is that the coefficient is an algebraic real value and does not depend on the FFT size. Another feature of the simplified calculation is the irrational number π (3.141592....).

[0079] It should be understood that equation (6) can be processed into several mathematically equivalent solutions, such as the following alternative representations:

[0080]

[0081] It should be noted that although the representation given by equation (7) does not directly highlight the relationship between the frequency offset estimate and the combination of the frequency offset estimate and the filter coefficient index, this formula is mathematically equivalent to equation (6), and thus, the same relationship still exists. In addition, the representation of equation (6) is more efficient in terms of computational complexity because it only involves half of the division operations of the alternative representation, and thus is preferred from an implementation perspective.

[0082] For large frequency offsets, the above approximation to achieve the relationship of equation (6) may cause some scaling errors, and some embodiments for reducing the scaling errors are given below. In one embodiment, an upper limit value (in the numerator of equation (6)) for the frequency offset estimate is defined, and if the frequency offset estimate is larger than the upper limit value, the frequency offset estimate is replaced by the upper limit value in the calculation of the coefficient. Figure 3 Such a process is shown. Referring to Figure 3 , the upper limit value is denoted by α. This process can be performed between block 202 and 204 or at another point before block 204. Referring to Figure 3, frequency offset estimation in block 300 is compared with an upper bound value α. If the frequency offset estimation is greater than (or optionally equal to) the upper bound value α, the process proceeds to block 302, where the frequency offset estimation is replaced by the upper bound value α. Then, block 204 is calculated by using the upper bound value α as the frequency offset estimation.

[0083] Figure 3 The effect plot using the upper bound value is also shown. Figure 3 The solid line in represents the magnitude of the coefficient calculated by using Equation (1) (without approximation) as a function of the (normalized) frequency offset estimation, and the dashed line represents the magnitude of the coefficient calculated by using Equation (6) as a function of the (normalized) frequency offset estimation. In the best case, the dashed line would follow the solid line. It can be seen that the approximation causes the line to deviate at higher frequency offsets, e.g., above 0.3. Therefore, the upper bound value α is used to limit the frequency offset estimation, which also effectively limits the magnitude of the filter coefficient and "turns" the dashed line to follow Figure 3 the solid line in, so that better results can be obtained even when the frequency offset is between 0.3 and 0.5. As a result, one embodiment provides the following relationship as an improvement to Equation (6) to cover the entire frequency offset range

[0084]

[0085] where sign represents the sign operation, min represents taking the minimum value, and α is the limit having The upper limit value of the design parameter for the scaling error of the large absolute value (|.|). The range of α can be restricted between 0 and 0.5, and in one embodiment, between 0.2 and 0.4. In some designs, α = 0.3 provides good performance, but this value can be further optimized for the desired implementation. For different designs, the optimal upper limit value can assume different values. As described above, the idea is to use the upper limit value to align the magnitudes of the approximate filter coefficients of Equation (6) to more accurately follow the magnitudes of the filter coefficients calculated by using Equation (1). Those skilled in the art can experiment with different values and find a suitable upper limit value for each implementation. For example, those skilled in the art can test various communication scenarios with different operating parameters and conditions, and discover the deviation in magnitude caused by the calculation of the frequency offset estimate via Equation (1) and Equation (6), and thus find the upper limit value that provides the maximum or at least an acceptable correlation between the amplitudes of the coefficients calculated via Equation (1) and the magnitudes of the coefficients calculated via Equation (6) or another embodiment described above, where the magnitude is a function of the frequency offset estimate. If the system design only supports normalized frequency offsets up to the upper limit value, e.g., i.e., high frequency offsets are not anticipated, Equation (6) can be used instead of Equation (8) to reduce complexity. Such a system design may involve, for example, static scenarios where the transmitter and receiver have low mobility. Those skilled in the art can experiment with the maximum achievable frequency offset for each system design and use Equation (6) to select a less complex embodiment for low mobility scenarios or an improved embodiment of Equation (8) for high mobility scenarios.

[0086] An alternative solution for eliminating or reducing the scaling error associated with high frequency offsets is to use another scaling function that reduces the scaling error. For example, the scaling can be handled in MRC / IRC processing, where the same magnitude scaling can be applied to both the channel estimate (reference / pilot symbols) and the data symbols. Another alternative is to implement the scaling directly into the filter coefficients as part of power normalization or another function that controls the magnitude of the filter coefficients. Figure 4 Illustrates such an embodiment.

[0087] Refer to Figure 4, the receiver signal processing may include blocks 200 to 204 according to any of the above embodiments. Additionally, the apparatus performing the receiver signal processing may perform other receiver signal processing functions, such as IRC, MRC, and / or channel equalization. Such functions are common for radio receivers and aim to compensate for the effects on signals communicated through a wireless channel, such as interference from other signals on the same frequency band, noise, multipath propagation, and non-uniform attenuation. For example, there is a large body of literature on IRC receiver algorithms, and a person skilled in the art can select a suitable receiver algorithm for each design. This also applies to MRC and channel equalization algorithms. Block 400 may include the common phase rotation compensation described above. In this case, the compensation may incorporate the above terms to improve the performance of frequency offset compensation. Block 400 may be performed after, before, or even in parallel with blocks 200 to 206. Thus, the phase rotation error caused by a frequency offset common to all subcarriers of a multi-carrier is reduced as part of another radio receiver signal processing algorithm (different from block 204) performed on the received multi-carrier signal. Such another radio receiver signal processing algorithm may be or include IRC, MRC, or a channel equalization algorithm configured to estimate and reduce the distortion introduced on the multi-carrier signal in a wireless channel.

[0088] As described above, the frequency offset estimation may be normalized such that its value is restricted between -0.5 and 0.5.

[0089] Figure 5 An apparatus is illustrated, including processing circuitry 50, such as at least one processor, and at least one memory 60, the at least one memory 60 including computer program code (software) 64, wherein the at least one memory and the computer program code (software) are configured, together with the at least one processor, to cause the apparatus to perform Figure 2 the process or any of its above embodiments. The apparatus may be used in a terminal device 100 or in an access node, for example, for a DU or a CU. The apparatus may be a circuit system or an electronic device in a terminal device or an access node implementing some embodiments of the present invention. The apparatus performing the above functions may thus be included in such a device, for example, the apparatus may include circuitry (such as a chip, a chipset, a processor, a microcontroller), or a combination of such circuitry for a terminal device or an access node. In other embodiments, the apparatus is generally used in a radio device, such as a radio device or a circuit system operating in or designed to operate in a radio device.

[0090] Memory 60 may be implemented using any suitable data storage technology, such as semiconductor-based memory devices, flash memory, magnetic memory devices and systems, optical memory devices and systems, fixed memory, and removable memory.

[0091] In one embodiment, the apparatus further includes a radio transceiver 62 optionally having a plurality of antenna elements and a plurality of parallel transmitter chains and receiver chains. The processing circuitry 50 may include receiver (RX) signal processing circuitry 52 configured to perform baseband signal processing functions on data received via the radio transceiver 62, such as Figure 2 the processes. The receiver signal processing circuitry 52 may include frequency-domain frequency offset filtering circuitry 54 configured to operate on real-valued (algebraic) numbers to provide the reduced computational complexity described above. Additionally, the receiver signal processing circuitry 52 may include one or more other receiver signal processing circuitries 56 coupled to the circuitry 54 to implement, for example Figure 4 the processes.

[0092] In this application, the term "circuitry" refers to one or more of the following: (a) an implementation of pure hardware circuitry, such as an implementation of only analog and / or digital circuitry; (b) a combination of circuitry with software and / or firmware, such as (where applicable): (i) a combination of (one or more) processors or processor cores; (ii) a portion of (one or more) processors / software, including (one or more) digital signal processors, software, and at least one memory, which work together to cause a device to perform a particular function; and (c) circuitry, such as a portion of (one or more) microprocessors or (one or more) microprocessors, which requires software or firmware to operate even if the software or firmware is not physically present.

[0093] This definition of "circuitry" applies to the use of the term in this application. As a further example, as used in this application, the term "circuitry" will also cover an implementation of only a processor (or processors) or a portion of a processor, such as a core of a multi-core processor, and its (or their) accompanying software and / or firmware. The term "circuitry" will also cover (e.g., if applicable to a particular element) a baseband integrated circuit, an application specific integrated circuit (ASIC), and / or a field programmable gate array (FPGA) circuit for a device according to embodiments of the present invention. Figure 3The processes or methods described herein, or any embodiments thereof, may also be performed in the form of one or more computer processes defined by one or more computer programs. The (multiple) computer programs may be in source code form, object code form, or some intermediate form, and it may be stored in some carrier, which may be any entity or device capable of carrying the program. Such carriers include transient and / or non-transitory computer media, such as recording media, computer memories, read-only memories, electrical carrier signals, telecommunication signals, and software distribution packages. Depending on the required processing power, the computer program may be executed in a single electronic digital processing unit or distributed among multiple processing units.

[0094] The embodiments described herein are applicable to the wireless networks defined above, but also applicable to other wireless networks. The protocols used, the specifications of the wireless networks, and their network elements are evolving rapidly. Such developments may require additional changes to the described embodiments. Therefore, all words and expressions should be construed broadly and they are intended to illustrate rather than limit the embodiments. It will be apparent to those skilled in the art that, as technology advances, the inventive concept can be implemented in various ways. The embodiments are not limited to the above examples, but may vary within the scope of the claims.

Claims

1. A device for communication, comprising: a device for obtaining a signal distorted by a frequency offset; a device for estimating a frequency offset estimate that describes the frequency offset; a device for calculating coefficients for the frequency-domain filter based on a relationship between the frequency offset estimate and a combination of the frequency offset estimate and an index of the frequency-domain filter, wherein the relationship is defined as a device for performing frequency-domain filtering of the signal by using the calculated coefficients.

2. The device according to claim 1, wherein the device is configured to: set an upper limit value for the frequency offset estimate, and if the frequency offset estimate is greater than the upper limit value, substitute the upper limit value for the frequency offset estimate in the calculation of the coefficients.

3. The device according to claim 2, wherein the relationship is defined as where ε is the frequency offset estimate in normalized form, α is the upper limit value, and k is the filter index.

4. The device according to any one of claims 1 to 3, wherein the signal includes a plurality of subcarriers, and wherein the device is further configured to: as part of another radio receiver signal processing algorithm performed on the signal, correct a phase rotation error caused by the frequency offset that is common to all subcarriers of the signal.

5. The device according to claim 4, wherein the another radio receiver signal processing algorithm is a channel equalization algorithm or an interference suppression combination algorithm, and the channel equalization algorithm is configured to estimate and reduce distortion caused to the signal by a radio channel.

6. The apparatus according to claim 4, wherein the other radio receiver signal processing algorithm is configured to combine terms where N represents the size of the Fourier transform, and represents the frequency offset estimate.

7. The device according to claim 1, wherein the calculated coefficients are real algebraic numbers.

8. The device according to claim 1, wherein the device includes a terminal device of a cellular communication system.

9. A method of communication, comprising: obtaining a signal distorted by a frequency offset; estimating a frequency offset estimate that describes the frequency offset; calculating coefficients for the frequency-domain filter based on a relationship between the frequency offset estimate and a combination of the frequency offset estimate and an index of the frequency-domain filter, wherein the relationship is defined as performing frequency-domain filtering of the signal by using the calculated coefficients.

10. The method according to claim 9, further comprising: setting an upper limit value for the frequency offset estimate, and if the frequency offset estimate is greater than the upper limit value, substituting the upper limit value for the frequency offset estimate in the calculation of the coefficients.

11. The method according to claim 10, wherein the relationship is defined as where ε is the frequency offset estimate in normalized form, α is the upper limit value, and k is the filter index.

12. A computer program product, embodied on a computer-readable medium and including computer program code readable by a computer, wherein the computer program code configures the computer to execute a computer process, comprising: obtaining a signal distorted by a frequency offset; estimating a frequency offset estimate that describes the frequency offset; Based on the relationship between the frequency offset estimate and the combination of the frequency offset estimate and the index of the frequency domain filter, calculate the coefficients for the frequency domain filter, where the relationship is defined as and Perform frequency domain filtering of the signal by using the calculated coefficients.

13. A device for communication, comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code being configured to, with the at least one processor, cause the device to at least perform the method according to any one of claims 9 to 11.

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