KR101872110B1

KR101872110B1 - Method and apparatus for channel estimation in communication system

Info

Publication number: KR101872110B1
Application number: KR1020160127603A
Authority: KR
Inventors: 허헌
Original assignee: 한국산업기술대학교산학협력단
Priority date: 2016-10-04
Filing date: 2016-10-04
Publication date: 2018-07-31
Also published as: KR20180037448A; WO2018066766A1

Abstract

A method and apparatus for channel estimation in a communication system are disclosed. The wireless transmission apparatus can detect a channel environment, calculate a channel change amount based on the detected channel environment, and assign the pilot symbol to the frequency domain according to the channel change amount.

Description

METHOD AND APPARATUS FOR CHANNEL ESTIMATION IN COMMUNICATION SYSTEM FIELD OF THE INVENTION [0001]

The following description relates to a channel estimation technique using a pilot symbol among channel estimation methods of a communication system.

In wireless communication, performance degradation may occur due to multipath or fading due to movement of a terminal. Therefore, stable transmission and reception can be performed only when accurate channel estimation is performed. In the next generation mobile communication system, the channel variation due to the wide band and the high-speed movement is increased, and the importance of the channel estimation is further increased.

The transmitter according to the present invention provides an apparatus for reducing unnecessary waste of channel resources by adjusting the density of pilot symbols allocated to the frequency domain in response to channel changes and assigning pilot symbols only to necessary areas with high density.

In the present invention, the receiver needs a position of a pilot symbol allocated for channel estimation and a channel estimation using the pilot symbol. The receiver provides a device for reducing the number of samples in the time domain required for channel estimation by estimating the pilot symbol positions and channels through compression sensing utilizing an average of a plurality of samples in the time domain.

A wireless transmission apparatus using orthogonal frequency-division multiplexing (OFDM) according to an exemplary embodiment of the present invention includes a sensor for detecting a channel environment, and a controller for calculating a channel change amount based on the detected channel environment, And then allocating the pilot symbols to the frequency domain.

The processor may allocate more pilot symbols to the second frequency domain corresponding to the second channel change rate than the first channel change rate than the first frequency domain corresponding to the first channel change rate.

A channel estimation apparatus using an orthogonal frequency division multiplexing method according to an embodiment includes a receiver for receiving a plurality of OFDM symbols from a wireless transmission apparatus through a channel and a plurality of samples in a time domain included in each of the plurality of OFDM symbols Obtaining a pilot symbol vector obtained by channel-shifting a pilot symbol vector with a position of a pilot symbol while obtaining a symbol vector of a frequency domain through compression sensing with respect to the average of the plurality of samples, And estimating the channel based on the channel estimate.

The processor may average samples having the same time index included in each OFDM symbol among samples of the plurality of time domains included in each of the plurality of OFDM symbols.

The processor may use the compression sense to obtain a symbol vector of the frequency domain from an average of the samples having the same time index.

The symbol vector may be a sparse vector. An element corresponding to a data symbol occupying most of the elements of the symbol vector may be zero.

The processor may average samples with the same time index for some time index.

The processor may calculate the solution of the optimization problem based on an average of a plurality of samples in the time domain to obtain the symbol vector in the frequency domain.

The processor may obtain the symbol vector by calculating a vector having a minimum sum of absolute values of all elements of the average of the frequency-converted samples.

According to an embodiment of the present invention, there is provided a radio transmission method using an orthogonal frequency division multiplexing method, comprising: calculating a channel variation amount of an entire frequency domain based on a sensed channel environment; And allocating symbols.

The channel estimation method using the orthogonal frequency division multiplexing method according to an embodiment includes a step of averaging a plurality of samples of a time domain included in each of a plurality of OFDM symbols received through a channel from a wireless transmission apparatus for each OFDM symbol Obtaining a symbol vector of the frequency domain using compression sensing from an average of the plurality of samples, and estimating the channel based on the symbol vector.

According to an embodiment, it is possible to reduce waste of unnecessary resources by adjusting the density of pilot symbols allocated to the frequency domain corresponding to the change of the channel and allocating the pilot symbols to the required domain only at a high density.

According to one embodiment, by using the average of the samples in some time domain using the compression sense, it is possible to estimate the complexity of the implementation of the time domain sampling system and the calculation amount for the sample average by estimating the frequency domain pilot symbol positions and channels have.

FIG. 1 is a diagram illustrating a general configuration of a system for allocating pilot symbols and estimating channels according to an embodiment. Referring to FIG.
2 is a diagram illustrating an example of allocating pilot symbols according to a rate of change of a channel according to an embodiment.
3 is a diagram illustrating an example of an assigned pilot symbol according to one embodiment.
4A is a diagram showing a correspondence relationship of OFDM symbols with respect to frequency and time.
4B is a diagram illustrating a structure in which one OFDM symbol including a CP is analyzed in a time domain.
5 is a flowchart of a wireless transmission method according to an embodiment.
6 is a flowchart of a channel estimation method according to an embodiment.

Specific structural or functional descriptions of embodiments are set forth for illustration purposes only and may be embodied with various changes and modifications. Accordingly, the embodiments are not intended to be limited to the particular forms disclosed, and the scope of the present disclosure includes changes, equivalents, or alternatives included in the technical idea.

The terms first or second, etc. may be used to describe various elements, but such terms should be interpreted solely for the purpose of distinguishing one element from another. For example, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

It is to be understood that when an element is referred to as being "connected" to another element, it may be directly connected or connected to the other element, although other elements may be present in between.

The singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, the terms "comprises ", or" having ", and the like, are used to specify one or more of the described features, numbers, steps, operations, elements, But do not preclude the presence or addition of steps, operations, elements, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the meaning of the context in the relevant art and, unless explicitly defined herein, are to be interpreted as ideal or overly formal Do not.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS In the following description of the present invention with reference to the accompanying drawings, the same components are denoted by the same reference numerals regardless of the reference numerals, and a duplicate description thereof will be omitted.

FIG. 1 is a diagram illustrating a general configuration of a system for allocating pilot symbols and estimating channels according to an embodiment. Referring to FIG.

1 illustrates a situation where a transmitter 110 transmits data to a receiver 120 in a wireless communication environment. According to one embodiment, the transmitter 110 may include a processor 111 and a sensor 112. For example, the sensor 112 may be an initial channel measurement block for initial channel measurement. According to one embodiment, the receiver 120 may include a receiver 121 and a processor 122. For example, the transmitter 110 may be a base station and the receiver 120 may be a terminal. According to one embodiment, the transmitter 110 may transmit data to the receiver 120 using an orthogonal frequency-division multiplexing (OFDM) scheme.

OFDM is a communication scheme that uses multi-carrier for high-speed data transmission. OFDM is a method of dividing a wideband signal into a plurality of orthogonal subcarriers and transmitting them in parallel. OFDM has the effect that the frequency selective fading channel characteristic of a wide band is changed to the frequency flat fading channel characteristic of a narrow band per subcarrier. In addition, the transmission symbols are modulated with a plurality of orthogonal subcarriers having different frequencies and transmitted at the same time, so that the transmission symbols are longer than the original data period, and the influence of ISI (Inter Symbol Interference) can be greatly reduced.

Thus, while OFDM has robust features for frequency selective attenuation, modulated symbols may experience attenuation of magnitude and phase due to channel traversal. Particularly, in the next generation wireless communication system, since the broadband band is used and the high-speed movement is frequent, the influence of the attenuation is large, and the change of the channel is more severe.

The receiver 120 may estimate and compensate for the attenuation experienced by the channel. Accurate channel estimation and compensation play an important role in improving the performance of OFDM systems. The transmitter 110 may utilize a pilot symbol for channel estimation of the receiver 120. When the transmitter 110 transmits the pilot symbol to the receiver 120, the receiver 120 may obtain the output value of the channel corresponding to the pilot symbol and estimate the channel using the output value of the channel.

The receiver 120 may estimate the channel using a pattern of pilot symbols assigned by the transmitter 110. The transmitter 110 must transmit information on the pattern of the pilot symbol to the receiver 120 through the control channel, so that the communication resource called the control channel must be allocated for the information transmission of the pilot symbol. In order to limit the amount of information to be transmitted through the control channel, an equal interval pilot symbol pattern is generally used, and the channel estimation may become inaccurate in a region where the channel change is severe.

According to one embodiment, the transmitter 110 may detect the channel environment and allocate the pilot symbols differently according to the channel variation amount in the frequency domain. As described above, the transmitter 110 can increase the accuracy of the channel estimation of the receiver 120 by densely allocating the pilot symbols to the frequency domain having a large channel variation amount.

A pattern of pilot symbols of various patterns can be formed according to the change of the channel. In this case, since the amount of information on the pilot symbol pattern can be very large, the receiver 120 can estimate the channel in a blind manner instead of receiving information on the pattern of the pilot symbol through the control channel. Even when the blind scheme is used, the calculation amount may be large if a discrete fourier transform (DFT) is performed for every OFDM symbol. The receiver 120 according to an exemplary embodiment can reduce a calculation amount by estimating a channel by compressed sensing.

2 is a diagram illustrating an example of allocating pilot symbols according to a rate of change of a channel according to an embodiment.

The graph 201 shows the shape of a channel in which channel changes are not severe. In the case of the graph 201 allocated to the frequency range of the available bandwidth, since the channel variation is not so large, the pilot symbols can be allocated to the frequency domain at regular intervals. The pattern 203 shows a case where the pilot symbols are allocated to the frequency domain at regular intervals. In this case, the channel estimation for the subcarrier to which the pilot symbol is allocated may be performed first, and then the channel estimation for the subcarrier to which the pilot symbol is not allocated may be performed by interpolation.

The graph 205 shows the shape of the channel in which the channel changes significantly. In the case of the graph 205, since the change of the channel is significant, when the pilot symbols are allocated to the frequency domain at regular intervals as in the graph 201, the channel estimation for the remaining frequency domain to which no pilot symbol is allocated can be performed through interpolation none. In addition, when the pilot symbols are arranged closely without interpolation, waste of resources is increased.

According to one embodiment, the transmitter 110 of FIG. 1 may adjust the density of pilot symbols allocated to the frequency domain in response to a change in channel. The pattern 207 shows a case where the density of the pilot symbol is adjusted according to the change of the channel. As described above, by allocating the pilot symbols at a high density only to the required region, the transmitter 110 can reduce unnecessary resource waste.

According to one embodiment, the sensor 112 included in the transmitter 110 may sense the channel environment. Here, the channel environment may refer to elements of the wireless communication environment that affect the amount of channel change and initial information of the channel provided from the terminal.

According to one embodiment, the processor 111 included in the transmitter 110 of FIG. 1 may calculate the amount of channel change based on the channel environment sensed by the sensor 112. The processor 111 may allocate the pilot symbols to the frequency domain according to the amount of channel variation. The processor 111 can provide more channel information for the corresponding frequency domain to the receiver 120 of FIG. 1 by assigning the pilot symbols with higher density to the frequency domain having a larger channel change amount.

In the graph 205, a portion with a large degree of curvature is referred to as a second frequency region, and a portion with a small degree of curvature may be referred to as a first frequency region. In this case, the processor 111 allocates more pilot symbols to the second frequency region corresponding to the second channel change rate, which is larger than the first channel change rate, than the first frequency change region corresponding to the first channel change rate, Can be adjusted.

3 is a diagram illustrating an example of an assigned pilot symbol according to one embodiment.

In FIG. 3, a channel environment of a frequency domain with a high pilot symbol density is high, and a channel environment of a frequency domain with a low pilot symbol density is small. As described above, by allocating the pilot symbols at a high density only to the required region, the transmitter 110 can reduce unnecessary resource waste.

According to one embodiment, the receiver 120 of FIG. 1 may perform channel estimation for the frequency domain to which the pilot symbol is allocated, and perform channel estimation for the frequency domain to which the pilot symbol is not allocated by interpolation . Even if the interpolation is performed with respect to the frequency domain where the channel variation is large, the interpolation accuracy can be maintained at a level higher than the predetermined quality because the density of the pilot symbol is high.

4A is a diagram showing a correspondence relationship of OFDM symbols with respect to frequency and time. 4B is a diagram illustrating a structure in which one OFDM symbol is analyzed in the time domain.

In the OFDM scheme, frequency utilization is relatively high because adjacent carriers maintain orthogonality with each other. Modulation and demodulation of OFDM symbols may be implemented with simple signal processing, e.g., IFFT and FFT.

In Fig. 4A, one OFDM symbol is composed of a plurality of subcarriers in relation to the frequency domain. Since each subcarrier is arranged at a minimum interval that can maintain orthogonality with each other, utilization of the available frequency band is high. Subcarriers may be referred to as subcarriers. The available frequency band may be referred to as the channel bandwidth.

In addition, the OFDM symbol has a time-dispersive characteristic. Each OFDM symbol is composed of samples of N time domains with respect to the time domain. The OFDM scheme uses a plurality of OFDM symbols in a time domain, and interference between OFDM symbols can be minimized by inserting guard intervals between OFDM symbols.

4B is a diagram showing an OFDM symbol in a time domain in more detail. For example, one OFDM symbol includes N time-domain samples and may include L CPs (cyclic prefix) to mitigate inter-symbol interference. Here, L CPs can constitute the guard interval of FIG. 4A. Samples of each time domain included in each OFDM symbol may correspond to a time index from 0 to N-1.

One of the samples in the time domain of FIG. 4B

And the frequency domain

Can have a relationship as shown in Equation (1). Equation (1)

Of an inverse discrete fourier transform (IDFT).

According to one embodiment, the receiver 120 of FIG. 1 includes samples of each time domain included in one OFDM symbol

Take the DFT for

Can be obtained. The receiver 120

The channel can be estimated on the sub-carrier to which the pilot symbol is allocated. The receiver 120 can perform channel estimation using interpolation or the like for a frequency region corresponding to the remaining subcarriers except the subcarriers on which channel estimation is performed. Here, when the channel estimation is performed on all the OFDM symbols, the calculation amount increases.

According to one embodiment, the processor 122 may perform frequency translation on the average of a plurality of samples in the time domain to obtain a symbol vector in the frequency domain. Specifically, the processor 122 may use a compression sensing technique to obtain a symbol vector of the frequency domain, and estimate the channel based on the symbol vector. Based on the fact that the result of the DFT when averaging a plurality of samples of an OFDM symbol in the time domain is a sparse vector, the processor 122 in accordance with one embodiment uses compression sensing to estimate The number of samples can be drastically reduced in the time domain. Here, the symbol vector may be referred to as the result of the DFT.

A sparse vector means a case where most of the elements constituting the vector are zero.

According to one embodiment, the receiver 121 of FIG. 1 may receive a plurality of OFDM symbols from a transmitter 110 via a channel. According to one embodiment, the processor 122 may average a plurality of samples of the time domain contained in each of the plurality of OFDM symbols, for each OFDM symbol. The processor 122 may average samples having the same time index included in each OFDM symbol among the samples of the plurality of time domains included in each of the plurality of OFDM symbols. The processor 122 may make the result of the DFT a sparse vector by averaging samples of the same index of the time domain contained in each OFDM symbol.

Processor 122 may be configured for each OFDM symbol

And does not perform IDFT on the OFDM symbol,

&Lt; / RTI > in the time domain

Can be obtained. The processor 122 uses Equation 2

Therefore, IDFT can be performed only once. here,

Is an average value of symbols located on the same subcarrier.

The mean value of the symbols located in the subcarriers to which the pilot symbols are allocated has a value of the symbol itself, not 0, but the average value of the symbols located in the subcarriers to which the arbitrary data symbols are allocated becomes zero.

Equation (2) can be expressed in the form of a matrix as shown in Equation (3). Equation (3)

Wow

And

Using the expressed

. For example, if a pilot symbol is assigned

Carrier indexes of 0, 5, and 20 (20 < = N-1)

The average value of the symbols located in the remaining subcarriers of the subcarrier becomes 0.

The average value of the symbols located in a small number of subcarriers is not zero and the average value of the remaining subcarriers is zero. As such, the element corresponding to the data symbol among the elements of the symbol vector can be zero.

The processor 122

The number of samples averaged in the time domain for channel estimation can be drastically reduced by using the compression sensing based on the fact that the signal is a sparse vector. The processor 122

And only some elements are arbitrarily acquired by the compression sensing technique

Can be restored.

Compression sensing is a theory that a sparse vector can be obtained with only a signal with a small amount of information. According to compression sensing,

In vector

Is a rare vector,

To save

All elements of < RTI ID = 0.0 >

If you only use

Can be restored. Where P is the number of pilot symbols, N is the size of the whole vector, and N is a very small value compared to P.

A vector composed of the mean of samples in the time domain

Vector that takes only m random elements from

, And in the DFT matrix

Made by taking m rows corresponding to the element of

Matrix

We can obtain the simultaneous equations as shown in Equation (4).

In Equation (4), since m is a very small value compared to N, the number of samples to be averaged in the time domain becomes small. Thus, the processor 122 can reduce the average number of samples required to greatly reduce the amount of computation.

According to one embodiment, the processor 122 may calculate a solution to the optimization problem based on an average of a plurality of frequency-translated samples to obtain a symbol vector. For example, processor 122 may use Equation 5 to calculate

Can be obtained. Equation (5) represents the L1 optimization problem.

Using equation (5), the processor 122 can compute a vector with the smallest sum of the absolute values of all the elements of the average of the frequency-converted samples, and obtain the symbol vector.

5 is a flowchart of a wireless transmission method according to an embodiment.

According to one embodiment, the transmitter 110 of FIG. 1 may perform wireless transmission using an orthogonal frequency division multiplexing scheme. In step 501, the transmitter 110 may calculate the channel variation amount of the entire frequency domain based on the sensed channel environment. In step 502, the transmitter 110 may allocate more pilot symbols to the portion of the entire frequency domain where the channel variation is larger. As described above, the transmitter 110 can increase the accuracy of channel estimation of the receiver 120 of FIG. 1 by densely allocating pilot symbols to a frequency region having a large channel change amount.

6 is a flowchart of a channel estimation method according to an embodiment.

According to one embodiment, the receiver 120 may perform channel estimation using an orthogonal frequency division multiplexing scheme. In step 601, the receiver 120 may average a plurality of samples of the time domain contained in each of the plurality of OFDM symbols received via the channel from the wireless transmission apparatus, for each OFDM symbol. At step 603, the receiver 120 may obtain the symbol vector of the frequency domain from the average of some samples of the time domain using compression sensing. In step 605, the receiver 120 may estimate the channel based on the pilot symbol of the symbol vector. As such, the receiver 120 can estimate the channel using the compression sensing, thereby reducing the complexity of the implementation.

The embodiments described above may be implemented in hardware components, software components, and / or a combination of hardware components and software components. For example, the devices, methods, and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, such as an array, a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be permanently or temporarily embodied in a transmitted signal wave. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer readable medium may include program instructions, data files, data structures, and the like, alone or in combination. Program instructions to be recorded on a computer-readable medium may be those specially designed and constructed for an embodiment or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

Although the embodiments have been described with reference to the drawings, various technical modifications and variations may be applied to those skilled in the art. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

110: Transmitter
111: Processor
112: sensor
120: receiver
121: Receiver
122: Processor

Claims

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A channel estimation apparatus using an orthogonal frequency division multiplexing method,
A receiver for receiving a plurality of OFDM symbols from a wireless transmission device via a channel; And
Averaging a plurality of samples of the time domain included in each of the plurality of OFDM symbols for each OFDM symbol and performing frequency conversion on the average of the plurality of samples to obtain a symbol vector of the frequency domain, A channel estimation method using a compression sensing technique,
Lt; / RTI >
Wherein the processor averages samples having the same time index included in each OFDM symbol among samples of the plurality of time domains included in each of the plurality of OFDM symbols,
Wherein the symbol vector is a scalar vector.

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