Wireless communication device including a data compressor and method of operating the same

Abstract

A wireless communication device, comprising: a radio frequency integrated circuit (RFIC) configured to receive an input signal to generate a digital sampled signal from the input signal; a data compressor configured to compress the digital sampled signal according to a compression method based on a data probability distribution of the input signal, the input signal varying based on a receivable signal amplitude range of the RFIC; a data decompressor configured to decompress the compressed digital sampled signal based on a decompression method corresponding to the compression method to generate a decompressed digital sampled signal; a data transmission link configured to transmit the compressed digital sampled signal to the data decompressor; and a processor configured to process the decompressed digital sampled signal.

Description

[0001] Cross - reference to related applications

[0002] This application claims priority to Korean Patent Application No. 10 - 2019 - 0116357, filed with the Korean Intellectual Property Office on September 20, 2019, the entire contents of which are incorporated herein by reference. Technical field

[0003] The present inventive concept relates to a wireless communication device including a data compressor for compressing data and an operation method of the wireless communication device. Background art

[0004] Compared with traditional Long - Term Evolution (LTE) and LTE - Advanced (LTE - A), the fifth - generation (5G) technology applied to a wireless communication system is a new radio access technology for providing high - speed data services of several gigabits per second (Gbps) by using an ultra - wideband having a bandwidth of 100 MHz or higher. However, since it is difficult to ensure an ultra - wideband frequency of 100 MHz or higher in the frequency bands of several hundred MHz or several GHz used in LTE or LTE - A, the 5G communication system transmits signals by using a wideband in a frequency band of 6 GHz or higher.

[0005] A wireless communication device includes a data transmission link for transmitting data between its internal modules to process data received from a base station or another wireless communication device. As the transmission rate of each wireless communication device increases, the data capacity to be transmitted through the data transmission link increases. Therefore, the structure of the data transmission link is very complex, and the size of the data transmission link increases. Summary of the invention

[0006] At least one embodiment of the present inventive concept provides a wireless communication device including a data compressor for compressing data based on a compression method suitable for the communication environment or communication performance of the wireless communication device, and an operation method of the wireless communication device.

[0007] According to an exemplary embodiment of the present inventive concept, there is provided a wireless communication device including: a Radio Frequency Integrated Circuit (RFIC) configured to receive an input signal to generate a digital sampling signal from the input signal; a data compressor configured to compress the digital sampling signal according to a compression method based on a data probability distribution of the input signal, the input signal varying based on a receivable signal amplitude range of the RFIC; a data decompressor configured to decompress the compressed digital sampling signal based on a decompression method corresponding to the compression method; a data transmission link configured to transmit the compressed digital sampling signal to the data decompressor; and a processor configured to process the decompressed digital sampling signal.

[0008] According to an exemplary embodiment of the inventive concept, there is provided a wireless communication device including: a radio frequency integrated circuit (RFIC) configured to receive an input signal to generate a digital sampling signal from the input signal; a data compressor configured to select one compression method from a plurality of compression methods using a data probability distribution of the input signal and compress the digital sampling signal based on the selected compression method; a data decompressor configured to decompress the compressed digital sampling signal based on a decompression method corresponding to the selected compression method to generate a decompressed digital sampling signal; a data transmission link configured to transmit the compressed digital sampling signal to the data decompressor; and a processor configured to process the decompressed digital sampling signal.

[0009] According to an exemplary embodiment of the inventive concept, there is provided a method of operating a wireless communication device, the method of operation including: converting an analog input signal received into a digital sampling signal; compressing the digital sampling signal according to a compression method based on a data probability distribution of the input signal to generate a compressed digital sampling signal; transmitting the compressed digital sampling signal to be processed; decompressing the compressed digital sampling signal based on a decompression method corresponding to the compression method; and processing the decompressed digital sampling signal. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Embodiments of the inventive concept will be more clearly understood from the following detailed description in conjunction with the accompanying drawings, in which:

[0011] Figure 1 is a block diagram showing a wireless communication system according to an exemplary embodiment of the inventive concept;

[0012] Figures 2 to 4 is a diagram for describing an operation of a data compressor that performs floating-point conversion according to an exemplary embodiment of the inventive concept;

[0013] Figures 5A to 5C is a diagram for describing a data probability distribution of an input signal for a compression operation of a data compressor;

[0014] Figure 6A is a block diagram for describing a data compressor that performs a compression operation based on a first compression method and a data decompressor that performs a decompression operation based on a first decompression method according to an exemplary embodiment of the inventive concept, Figure 6B is for describing Figure 6A a flowchart of an operation of a data compressor;

[0015] Figure 7is a block diagram for describing a data compressor that performs a compression operation based on a second compression mode and a data decompressor that performs a decompression operation based on a second decompression mode according to an exemplary embodiment of the inventive concept;

[0016] Figure 8A Is used to describe Figure 7 A flow chart of the operation of the data compressor, Figure 8B Is used to describe Figure 7 A flow chart of the operation of the second converter;

[0017] Figure 9A and Figure 9B is used to describe an exemplary embodiment according to the inventive concept, Figure 7 A flowchart of the operation of the digital sample data group unit of the data compressor;

[0018] Figure 10 is a block diagram for describing a data compressor that performs a compression operation based on a second compression mode and a data decompressor that performs a decompression operation based on a second decompression mode according to an exemplary embodiment of the inventive concept;

[0019] Figures 11 to 13 is a diagram for describing a method of selecting a compression method according to an exemplary embodiment of the inventive concept;

[0020] Figure 14 is a block diagram illustrating a storage system according to an exemplary embodiment of the inventive concept; and

[0021] Figure 15 is a diagram illustrating a communication device including a data compressor or a data decompressor according to an exemplary embodiment of the inventive concept. DETAILED DESCRIPTION

[0022] A base station may be a master agent that communicates with a wireless communication device and allocates communication network resources to the wireless communication device, and may be at least one of a cell, a base station (BS), a NodeB (NB), an eNodeB (eNB), a next generation radio access network (NGRAN), a radio access unit, a base station controller, or a network node.

[0023] A wireless communication device may be a master agent communicating with a base station or another wireless communication device and may be referred to as a node, user equipment (UE), next generation UE (NG UE), mobile station (MS), mobile equipment (ME), device, or terminal.

[0024] In addition, the wireless communication device may include at least one of a smart phone, a tablet personal computer (PC), a mobile phone, a video phone, an e-book reader, a desktop PC, a laptop PC, a netbook, a personal digital assistant (PDA), an MP3 player, a medical device, a camera, and a wearable device. In addition, the wireless communication device may be a television (TV), a digital video disc (DVD) player, an audio player, a refrigerator, an air conditioner, a vacuum cleaner, an oven, a microwave oven, a washing machine, a dryer, an air purifier, a set-top box, a home automation control panel, a security control panel, a media box (such as Samsung HomeSync TM , Apple TV TM , or Google TV TM ), a game console (such as Xbox TM or PlayStation TM ), an electronic dictionary, an electronic key, a portable camera, and an electronic photo frame. In addition, the wireless communication device may be at least one of various medical devices (e.g., various portable medical measurement devices (e.g., a blood glucose meter, a heart rate meter, a blood pressure meter, a body temperature meter, a magnetic resonance angiography (MRA) device, a magnetic resonance imaging (MRI) device, a computed tomography (CT) device, an imaging device, or an ultrasonic device)), a navigation device, a global navigation satellite system (GNSS), an event data recorder (EDR), a flight data recorder (FDR), an in-vehicle infotainment device, a naval electronic device (e.g., a naval navigation device, a gyrocompass, etc.), an avionics device, a security device, an in-vehicle head unit, an industrial or consumer robot, an unmanned aerial vehicle, an automated teller machine (ATM), a point of sale (POS), and an Internet of Things (IoT) device (e.g., a light bulb, various sensors, a spring cooler, a fire alarm, a temperature controller, a street light pole, a toaster, a sports equipment, a hot water tank, a heater, a boiler, etc.). Additionally, the wireless communication device may include various multimedia systems for performing communication functions.

[0025] Hereinafter, exemplary embodiments of the inventive concept will be described in detail with reference to the accompanying drawings.

[0026] Figure 1 is a block diagram showing a wireless communication system 1 according to an exemplary embodiment of the inventive concept.

[0027] Referring to Figure 1 , the wireless communication system 1 includes a base station 10 and a wireless communication device 100. In Figure 1In order to facilitate the description, the wireless communication device 100 is shown as communicating with a base station 10. However, this is not limited thereto. In other embodiments, the wireless communication device 100 may communicate with multiple base stations or multiple wireless communication devices, and even in such a case, the inventive concept may be applied to the wireless communication device 100. For example, the wireless communication system 1 may be a Long-Term Evolution (LTE) system, a Fifth-Generation (5G) system, a Code Division Multiple Access (CDMA) system, a Global System for Mobile Communications (GSM) system, a Wireless Local Area Network (WLAN) system, or any wireless communication system. Hereinafter, it may be assumed that the wireless communication system 1 corresponds to a 5G communication system. However, embodiments of the inventive concept are not limited thereto.

[0028] The wireless communication network between the wireless communication device 100 and the base station 10 may support multiple users who share available network resources to communicate with each other. For example, the wireless communication network may transmit information by using various methods such as Code Division Multiple Access (CDMA), Frequency Division Multiple Access (FDMA), Time Division Multiple Access (TDMA), Orthogonal Frequency Division Multiple Access (OFDMA), and Single-Carrier Frequency Division Multiple Access (SC-FDMA).

[0029] The wireless communication device 100 and the base station 10 may communicate with each other through a downlink channel DL and an uplink channel UL. The wireless communication device 100 includes an antenna 110, a Radio Frequency Integrated Circuit (RFIC) 120, a data compressor 130, a data transmission link 140 (e.g., a link circuit), a data decompressor 150, and a processor 160. The RFIC 120 may output a digital sampling signal generated by performing analog-to-digital conversion and downsampling on an input signal received from the base station 10 through the antenna 110 to the data compressor 130. The RFIC may include an analog-to-digital converter (e.g., a circuit) for performing analog-to-digital conversion. The digital sampling signal may include a plurality of digital sampling data classified in chronological order, and the compression of the digital sampling signal may include compressing each of the multiple digital sampling data. The digital sampling data may include in-phase (I) sampling data and quadrature (Q) sampling data. The in-phase (I) sampling data and the quadrature (Q) sampling data may be generated from an amplitude-modulated sine signal. The inventive concept may be applied to compressing and decompressing the I sampling data and the Q sampling data, respectively.

[0030] According to an exemplary embodiment, the data compressor 130 compresses a digital sampling signal based on the data probability distribution of a variable input signal according to the received signal amplitude range of the RFIC 120. For example, according to the beamforming mode set in the RFIC 120, the received signal amplitude range of the RFIC 120 can be adjusted based on factors such as the gain set in each low-noise amplifier of the RFIC 120. The variance of the data probability distribution of the input signal can vary based on the received signal amplitude range of the RFIC 120, and the data compressor 130 can obtain information on the data probability distribution of the input signal suitable for the current set received signal amplitude range of the RFIC 120. In an exemplary embodiment, information on the data probability distribution of the input signal corresponding to various received signal amplitude ranges of the RFIC 120 is pre-stored in a memory (not shown) of the wireless communication device 100. This will be described in detail below with reference to Figures 5A to 5C Detailed description.

[0031] In an exemplary embodiment, the data compressor 130 performs a floating-point conversion on the digital sampling signal based on the data probability distribution of the input signal to compress the digital sampling signal. In the floating-point conversion, the data format can include a mantissa region and an exponent region. For example, the mantissa can define the non-zero part of the number (e.g., the amplitude of the digital sampling signal at a specific time), and the exponent can define how many positions the decimal point is moved. The sum of the number of bits in the mantissa region and the number of bits in the exponent region can be less than the number of bits of the digital sampling signal before the floating-point conversion, and thus, the digital sampling signal can be compressed by the floating-point conversion. Hereinafter, since the data compressor 130 can compress the digital sampling signal by performing a conversion operation on the digital sampling signal, the compression operation and the conversion operation of the data compressor 130 can be described as having the same meaning. The mantissa region can further include a sign bit.

[0032] In an embodiment, the number of bits in the mantissa region and the number of bits in the exponent region can each be preset separately as a combination for representing the minimum value of all possible values that the digital sampling signal may have. The digital sampling signal can be represented as a product of the bit data in the mantissa region and the bit data in the exponent region based on a floating-point conversion. For example, when the value of the digital sampling data is "000001000001" (or 65 in decimal), assuming that the digital sampling data of the digital sampling signal is 12 bits, the bit data in the mantissa region is 8 bits, and the bit data in the exponent region is 3 bits, the digital sampling data can be converted such that the value of the bit data in the mantissa region is "01000001" (or 65 in decimal), and the value of the bit data in the exponent region is "000" (or 0 in decimal). In this case, the value of the digital sampling data before conversion (65 in decimal) is the same as the value of the digital sampling data after conversion (65 in decimal).

[0033] When the value of the digital sampling data is "000100000001" (or 257 in decimal), the digital sampling data can be converted such that the value of the bit data in the mantissa region is "1000000" (or 64 in decimal), and the value of the bit data in the exponent region is "100" (or 4 in decimal). In this case, the value of the digital sampling data before conversion (257 in decimal) may be different from the value of the digital sampling data after conversion (256 in decimal). That is, as the range of values representing the digital sampling signal increases, the value of the bit data in the exponent region can increase to cover the range. In addition, the value resolution of the digital sampling data after conversion may decrease.

[0034] In an embodiment, the number of bits in the exponent region is determined based on the data probability distribution having the largest variance among the multiple data probability distributions of the input signal, and the data probability distribution of the input signal is based on the multiple receivable amplitude ranges of the RFIC 120. In another embodiment, the number of bits in the exponent region changes dynamically based on the variance of the data probability distribution of the input signal, and as the number of bits in the exponent region changes, the number of bits in the mantissa region can change or can remain. For example, as the variance of the data probability distribution of the input signal decreases, the number of bits in the exponent region can decrease, and the number of bits in the mantissa region can increase by the number of bits by which the exponent region decreases or can be maintained.

[0035] In an embodiment, the data compressor 130 performs a floating-point conversion on the digital sampled data based on the point at which the value of the digital sampled data included in the digital sampling signal lies in the data probability distribution of the input signal. In an exemplary embodiment, the data compressor 130 adjusts the value of the bit data in the exponential region that determines the resolution based on the data probability corresponding to the value of the digital sampled data to perform the floating-point conversion.

[0036] In an embodiment, the data compressor 130 compresses the digital sampled data based on various compression methods. In a first compression method, the data compressor 130 performs least significant bit (LSB) truncation on the digital sampled data to generate truncated sampled data, and performs a floating-point conversion on the truncated sampled data based on the point at which the value of the truncated sampled data corresponding to the result of the performed floating-point conversion lies in the data probability distribution of the input signal. The following will refer to Figure 6A and Figure 6B for a detailed description of the first compression method. In a second compression method, when the magnitude of the value of the digital sampled data is greater than a threshold, the data compressor 130 selects a first conversion method from a plurality of conversion methods, and when the magnitude of the value of the digital sampled data is equal to or less than the threshold, the data compressor 130 selects a second conversion method from a plurality of conversion methods. Then, the data compressor 130 can convert the digital sampled data based on the selected conversion method. In an exemplary embodiment, when the magnitude of the value of the I sampled data or the magnitude of the value of the Q sampled data in the digital sampled data is greater than the threshold, the data compressor 130 selects a first conversion method from a plurality of conversion methods, and when the magnitude of the value of the I sampled data and the magnitude of the value of the Q sampled data are equal to or less than the threshold, the data compressor 130 selects a second conversion method from a plurality of conversion methods. The threshold can be set based on the first conversion method or the second conversion method. For example, the second conversion method can be a conversion method with a higher resolution than the resolution of the first conversion method. That is, when the magnitude of the value of the digital sampled data is greater than the threshold, the first conversion method with a wide range of convertible values is applied despite having a low resolution, and when the magnitude of the value of the digital sampled data is equal to or less than the threshold, the second conversion method with a narrow range of convertible values is applied despite having a high resolution. The following will refer to Figures 7 to 10 for a detailed description of the second compression method. In a third compression method, the data compressor 130 performs compression on the digital sampled data based on a combination of the first compression method and the second compression method. In addition to the above first compression method to third compression method, the data compressor 130 can also perform compression on the digital sampling signal based on various compression methods according to the data probability distribution of the input signal. Hereinafter, for the sake of convenience of description, examples using the first compression method to third compression method will be mainly described, however, the inventive concept is not limited thereto.

[0037] In an embodiment, the data compressor 130 may be implemented to support only one of the first to third compression methods described above, or may be implemented to support all of the first to third compression methods. When the first to third compression methods can be supported, the data compressor 130 may select an optimal compression method from the first to third compression methods based on the current communication environment, current operation mode, and current desired performance value of the wireless communication device 100. Then, the data compressor operates based on the selected optimal compression method. In an exemplary embodiment, the data compressor 130 selects a compression method from the first to third compression methods based on the degree of loss caused by compression and decompression based on the first to third compression methods. A detailed description will be given below with reference to Figures 11 to 13 This will be described in detail.

[0038] The data transmission link 140 transmits the compressed digital sampling signal received from the data compressor 130 to the data decompressor 150. In an exemplary embodiment, the data transmission link 140 includes a plurality of transmission lines for transmitting the compressed digital sampling signal. The data compressor 130 may be arranged adjacent to the output terminal of the RFIC 120, and the data decompressor 150 may be arranged adjacent to the input terminal of the processor 160. Therefore, the data transmission link 140 may transmit the digital sampling signal received from the RFIC 120 so that the processor 160 processes the digital sampling signal.

[0039] The data decompressor 150 decompresses the compressed digital sampling signal based on a decompression method corresponding to the compression method of the data compressor 130 to generate a decompressed digital sampling signal, and provides the decompressed digital sampling signal to the processor 160. The processor 160 may process the decompressed digital sampling signal.

[0040] Each of the data compressor 130 and the data decompressor 150 may be a hardware block including analog circuits and / or digital circuits, or may be a software block including a plurality of instructions run by another processor. In addition, each of the data compressor 130 and the data decompressor 150 may be implemented differently by a combination of hardware and software.

[0041] The wireless communication device 100 according to the exemplary embodiment performs compression on the digital sampling signal based on the data probability distribution of the input signal, and thus, the communication conditions or environment of the wireless communication device 100 can be reflected in the compression. Therefore, optimal compression can be performed, the structure of the data transmission link for transmitting the digital sampling signal can be simplified, and the size of the data transmission link or the wireless communication device can be reduced.

[0042] Figures 2 to 4It is a diagram for describing the operation of a data compressor 130 that performs floating-point conversion according to an exemplary embodiment of the inventive concept. Figures 5A to 5C It is a diagram for describing the data probability distribution of an input signal for the compression operation of a data compressor.

[0043] Refer to Figure 2 , the data compressor 130 includes a floating-point converter 131, and the floating-point converter 131 performs floating-point conversion on K-bit (where K is an integer greater than or equal to 1) digital sampled data DSD to output the converted digital sampled data DSD_Comp. The converted digital sampled data DSD_Comp includes an N-bit (where N is an integer greater than or equal to 1) mantissa region M_R and an M-bit (where M is an integer greater than or equal to 1) exponent region E_R, and the sum of N and M can be set to be less than K. The values of N and M can be preset based on the range of values that the digital sampled data DSD can have. The range of values that the digital sampled data DSD can have can vary based on the received signal amplitude range of an RFIC ( Figure 1 of 120), and in another embodiment, the values of N and M can be preset based on the received signal amplitude range of an RFIC ( Figure 1 of 120).

[0044] Further refer to Figure 3 , in terms of the characteristics of wireless communication, a wireless communication device ( Figure 1The data probability distribution of the input signal (where the X-axis represents the data value and the Y-axis represents the probability value P(X) corresponding to the data value) of 100) may be a Gaussian distribution, and based on the data probability distribution of the input signal, the floating-point converter 131 may perform a floating-point conversion on the digital sampled data DSD. For example, when the value of the digital sampled data DSD is between "An" and "Ap", the floating-point converter 131 determines the value of the bit data in the exponent region E_R as the first value V1, and based on the first value V1 of the bit data in the exponent region E_R, determines the value of the bit data in the mantissa region M_R, thereby performing a conversion operation. When the value of the digital sampled data DSD is between "Bn" and "An" or between "Ap" and "Bp", the floating-point converter 131 determines the value of the bit data in the exponent region E_R as the second value V2, and based on the second value V2 of the bit data in the exponent region E_R, determines the value of the bit data in the mantissa region M_R, thereby performing a conversion operation. When the value of the digital sampled data DSD is between "Cn" and "Bn" or between "Bp" and "Cp", the floating-point converter 131 determines the value of the bit data in the exponent region E_R as the third value V3, and based on the third value V3 of the bit data in the exponent region E_R, determines the value of the bit data in the mantissa region M_R, thereby performing a conversion operation. As described above, based on the data probability distribution of the input signal, the floating-point converter 131 determines a small value of the bit data in the exponent region E_R associated with the digital sampled data DSD that is expected to be received more frequently. Therefore, a conversion can be performed such that the value of the digital sampled data DSD is maximally equal to the value of the compressed digital sampled data DSD_Comp. In addition, the floating-point converter 131 may determine a maximum value of the bit data in the exponent region E_R associated with the digital sampled data DSD that is expected to be received less frequently. Therefore, the value of the digital sampled data DSD can be covered.

[0045] As Figure 3 shown, criteria (such as Ap, Bp, Cp, An, Bn, and Cn) for determining the value of the bit data in the exponent region E_R may be preset based on the data probability distribution of the input signal and based on the variance of the data probability distribution of the input signal. The criteria may be set to be the same or different. Figure 3 The Gaussian distribution is merely an example for describing the exemplary embodiment, and the inventive concept is not limited thereto.

[0046] Further referring to Figure 4, in operation S100, the number of bits in the mantissa region and the number of bits in the exponent region are respectively set. The number of bits in the mantissa region and the number of bits in the exponent region can each be preset to a combination of the minimum values for representing all possible values that the digital sampled data may have. In an exemplary embodiment, based on the data probability distribution with the largest variance among the multiple data probability distributions of the input signal according to the multiple receivable amplitude ranges of the RFIC 120, the number of bits in the exponent region is determined. That is, as the variance of the data probability distribution increases, the range of values that the digital sampled data may have increases, and thus, the number of bits in the exponent region can be set based on this. In another exemplary embodiment, the number of bits in the exponent region changes dynamically based on the variance of the data probability distribution of the input signal, and thus, the number of bits in the mantissa region can change or can be maintained.

[0047] To assist in understanding the description of operation S100, further reference is made to Figures 5A to 5C , the RFIC 120 can be set to receive an input signal IS1 having an amplitude within a first signal amplitude range R1, as Figure 5A shown, or can be set to receive an input signal IS2 having an amplitude within a second signal amplitude range R2 that is wider than the first signal amplitude range R1, as Figure 5B shown. As described above, the receivable signal amplitude range of the RFIC 120 can be adjusted based on factors such as a predetermined beamforming method and the gain set in the low-noise amplifier. As Figure 5C shown, the data probability distribution of the first input signal IS1 can correspond to a first probability distribution function PDF1 having a first variance, and the data probability distribution of the second input signal IS2 can correspond to a second probability distribution function PDF2 having a second variance, and the second variance is greater than the first variance. The number of bits in the mantissa region and the number of bits in the exponent region can be set or can change to suit the data probability distribution characteristics of the input signal.

[0048] In operation S110, the floating-point converter 131 performs a floating-point conversion on the digital sampled data to have a data format suitable for the number of bits in the mantissa region and the number of bits in the exponent region set in operation S100.

[0049] Figure 6A is a block diagram of a data compressor 130a that performs a compression operation based on a first compression method and a data decompressor 150a that performs a decompression operation based on a first decompression method for describing an exemplary embodiment according to the inventive concept, Figure 6B is for describing Figure 6A the operation of the data compressor 130a. The data compressor 130a can be used to implement Figure 1 the data compressor 130. The data decompressor 150a can be used to implement Figure 1data decompressor 150.

[0050] Reference Figure 6A , the data compressor 130a compresses the digital sampled data based on the first compression method. That is, the data compressor 130a performs LSB truncation on the digital sampled data to generate truncated sampled data, and performs floating-point conversion on the truncated sampled data to generate compressed digital sampled data. The LSB truncation may include setting the LSB bit of the digital sampled data to 0, setting the lowest two LSB bits of the digital sampled data to 0, setting the lowest three LSB bits of the digital sampled data to 0, etc. The LSB truncation may include removing the LSB bit of the digital sample, removing the lowest two LSB bits of the digital sampled data, removing the lowest three LSB bits of the digital sampled data, etc. In an exemplary embodiment, the data compressor 130a includes a shifter 133a (e.g., a shift circuit) and a floating-point converter 131a (e.g., a logic circuit). The shifter 133a shifts the digital sampled data received from the RFIC ( Figure 1 of 120) by a specific number of bits in one direction to generate shifted data, and the floating-point converter 131a performs floating-point conversion on the shifted data output from the shifter 133a to generate compressed digital sampled data. For example, the shifter 133a may perform a one-bit right shift, a two-bit right shift, a three-bit right shift, etc. The data transmission link 140 transmits the digital sampled data compressed by the data compressor 130a to the data decompressor 150a. The data decompressor 150a decompresses the digital sampled data compressed by the first decompression method corresponding to the first compression method. In an exemplary embodiment, the data decompressor 150a includes a fixed-point converter 151a (e.g., a logic circuit) and a shifter 153a. The fixed-point converter 151a performs an operation of converting the floating-point data format to the fixed-point data format on the compressed digital sampled data received from the data transmission link 140, and the shifter 153a shifts the fixed-point converted digital sampled data by a specific number of bits in the other direction. For example, if the shifter 133a shifts the input data two bits to the right, the shifter 153a shifts the input data two bits to the left. The digital sampled data decompressed by the data decompressor 150a may be output to the processor ( Figure 1 of 160). For ease of description, Figure 6A the embodiments correspond to exemplary configurations. However, the present embodiments are not limited thereto. Various embodiments of compressing digital sampled data by using the above first compression method and decompressing digital sampled data by using the above first decompression method may be applied to the data compressor 130a and the data decompressor 150a. The number of bits that can be shifted by the shifter 153a may vary based on the device or system to which the inventive concept is applied, and the floating-point representation range may be reduced through the shifting operation of the shifter 153a, thereby improving the compression efficiency.

[0051] Further referring to Figure 6B , in operation 200a, the data compressor 130a performs LSB truncation on the digital sampled data received from the RFIC ( Figure 1 120) to generate truncated sampled data. Subsequently, in operation 210a, the data compressor 130a performs floating-point conversion on the truncated sampled data based on the data probability distribution of the input signal to generate compressed digital sampled data. Subsequently, the data transmission link 140 transmits the digital sampled data compressed by the data compressor 130a to the data decompressor 150a. In an exemplary embodiment, the data decompressor 150a performs inverse conversions corresponding to each of operation 200a and operation 210a to decompress the compressed digital sampled data.

[0052] Figure 7 is a block diagram for describing a data compressor 130b that performs a compression operation based on a second compression method and a data decompressor 150b that performs a decompression operation based on a second decompression method according to an exemplary embodiment of the inventive concept. The data compressor 130b and the data decompressor 150b may be respectively used to implement Figure 1 the data compressor 130 and the data decompressor 150.

[0053] Referring to Figure 7 , the data compressor 130b compresses digital sampled data based on a second compression method. That is, the data compressor 130b selects one conversion method from a plurality of conversion methods with different resolutions based on the amplitude of the value of the digital sampled data included in the digital sampling signal, and performs the selected conversion on the digital sampled data. In an exemplary embodiment, when the amplitude of the value of the digital sampled data is greater than a threshold, the data compressor 130b selects a first conversion method from the plurality of conversion methods, and when the amplitude of the value of the digital sampled data is equal to or less than the threshold, the data compressor 130b selects a second conversion method from the plurality of conversion methods. In an exemplary embodiment, the second conversion method is a conversion method having a higher resolution than the resolution of the first conversion method. For example, the first conversion method may be a floating-point conversion method, and the second conversion method may be a fixed-point conversion method. Additionally, assuming that the digital sampled data includes I sampled data and Q sampled data, each of the I sampled data and the Q sampled data before compression is K bits, the mantissa region corresponding to the data format of the floating-point conversion method is N bits, and the exponent region corresponding to the data format in the floating-point conversion method is N bits, the conversion method may be selected based on the following equation (1).

[0054]

[0055] In Equation (1), max(|I|, |Q|) can determine whether the maximum value of the absolute value |I| of the I sampled data and the absolute value |Q| of the Q sampled data is greater than the threshold value. N can represent the number of bits in the mantissa region, M can represent the number of bits in the exponent region, and can represent (a value corresponding to the limit obtained by dividing M by 2). However, the threshold value of Equation (1) is merely an example because embodiments of the inventive concept are not limited thereto, and furthermore, it can be a standard for selecting a conversion method and can be set differently.

[0056] The data compressor 130b can select a conversion method based on the maximum value among multiple digital sampled data included in a specific digital sampled data group. The digital sampled data group can include multiple digital sampled data and can be a unit that performs a conversion operation based on the selected conversion method. For example, when the first digital sampled data group includes first I sampled data, first Q sampled data, second I sampled data, and second Q sampled data, the data compressor 130b selects a conversion method based on the first I sampled data having the maximum value and performs a conversion on the first I sampled data, first Q sampled data, second I sampled data, and second Q sampled data based on the selected conversion method. Subsequently, the data compressor 130b can select a conversion method corresponding to the second digital sampled data group and can perform a conversion on the second digital sampled data based on the selected conversion method. In an exemplary embodiment, the number of digital sampled data included in the digital sampled data group can vary based on the communication environment or communication conditions of the wireless communication device including the data compressor 130b. For example, the number of digital sampled data included in the digital sampled data group can be determined based on the variance of the data probability distribution of the input signal. Specifically, it can be set such that as the variance of the data probability distribution of the input signal increases, the number of data included in the digital sampled data group decreases. That is, in the case where the variance of the data probability distribution of the input signal is large, as the variance of the data probability distribution of the input signal increases, it may be difficult to apply the same conversion method to the digital sampled data group. Therefore, based on the variance, the digital sampled data group can be set to have an appropriate number of multiple data. However, this is merely an exemplary embodiment, and the number of data in the digital sampled data group can be set based on various methods and standards.

[0057] The data compressor 130b includes a determination circuit 134b, a first converter 131b (e.g., a logic circuit), a second converter 132b (e.g., a logic circuit), and an indication bit adder 135b (e.g., an addition circuit). The first converter 131b can perform a conversion operation based on a first conversion method (e.g., a floating-point conversion method), and the second converter 132b can perform a conversion operation based on a second conversion method (e.g., a fixed-point conversion method). The determination circuit 134b can compare the magnitudes of the I-sampled data value and the Q-sampled data value of the digital sampled data with the threshold value of Equation (1) to select a conversion method. When the maximum value of the absolute value |I| of the I-sampled data and the absolute value |Q| of the Q-sampled data is greater than the threshold value, the determination circuit 134b can select the first conversion method to activate the first converter 131b. When the maximum value of the absolute value |I| of the I-sampled data and the absolute value |Q| of the Q-sampled data is equal to or less than the threshold value, the determination circuit 134b can select the second conversion method to activate the second converter 132b.

[0058] When the first converter 131b is activated, the first converter 131b can perform a conversion operation on each of the I-sampled data and the Q-sampled data based on the first conversion method, and when the second converter 132b is activated, the second converter 132b can perform a conversion operation on each of the I-sampled data and the Q-sampled data based on the second conversion method. In an embodiment, as described above, the first converter 131b can perform a floating-point conversion on each of the I-sampled data and the Q-sampled data corresponding to a predetermined number of bits in the mantissa region and a predetermined number of bits in the exponent region based on the data probability distribution of the input signal. Additionally, the second converter 132b can additionally allocate some bits in the exponent region associated with each of the I-sampled data and the Q-sampled data to a predetermined number of bits in the mantissa region, and then, based on this, the second converter 132b can perform a fixed-point conversion. In an embodiment, some bits in the exponent region that are additionally allocated to the number of bits in the mantissa region can be determined as the For example, when the predetermined number of bits in the mantissa region is 8 bits and the number of bits in the exponent region is 3 bits, the second converter 132b can additionally allocate some bits (e.g., bits) to the number of bits in the mantissa region, and can perform a fixed-point conversion on each of the I-sampled data and the Q-sampled data of a total of 9 bits.

[0059] In an exemplary embodiment, the indication bit adder 135b receives the converted I sampled data and the converted Q sampled data from the first converter 131b or the second converter 132b, and adds an indication bit indicating the conversion method to at least one of the converted I sampled data and the converted Q sampled data. For example, when the digital sampled data is converted by the first converter 131b, the indication bit adder 135b may add 1-bit data with a value of "0", and when the digital sampled data is converted by the second converter 132b, the indication bit adder 135b may add 1-bit data with a value of "1". The indication bit adder 135b may receive information about the selected conversion method from the determination circuit 134b.

[0060] The data transmission link 140 may transmit the digital sampled data compressed by the data compressor 130b to the data decompressor 150b. The data decompressor 150b may perform decompression on the compressed digital sampled data by a second decompression method corresponding to the second compression method. In an exemplary embodiment, the data decompressor 150b includes a determination circuit 154b, a third converter 151b (e.g., a logic circuit), and a fourth converter 152b (e.g., a logic circuit). The determination circuit 154b activates one of the third converter 151b and the fourth converter 152b based on the indication bit of the compressed digital sampled data. In an embodiment, the third converter 151b corresponds to the first converter 131b, and the fourth converter 152b may correspond to the second converter 132b. That is, the third converter 151b may perform conversion based on the inverse conversion method of the above first conversion method (e.g., the floating-point conversion method) to decompress the compressed digital sampled data, and the fourth converter 152b may perform conversion based on the inverse conversion method of the above second conversion method (e.g., the fixed-point conversion method) to decompress the compressed digital sampled data. The digital sampled data decompressed by the data decompressor 150b may be output to the processor ( Figure 1 of 160). For ease of description, Figure 7 The embodiments correspond to the exemplary configurations. However, the embodiments of the present embodiment are not limited thereto. Various implementation embodiments for compressing digital sampled data by using the above second compression method and decompressing digital sampled data by using the above second decompression method may be applied to the data compressor 130b and the data decompressor 150b.

[0061] Figure 8A is a flowchart for describing the operation of the data compressor 130b according to an exemplary embodiment of the present inventive concept, Figure 7 and is a flowchart for describing the operation of the second converter 132b Figure 8B of. Hereinafter, a description will be given with reference to Figure 7 the following. Figure 7 will be given.

[0062] Reference Figure 8A , in operation 200b, the data compressor 130b selects a conversion method based on the magnitude of the values of the digital sample data. Subsequently, in operation 210b, the data compressor 130b converts the digital sample data based on the selected conversion method. In operation S220b, the data compressor 130b generates an indication bit indicating the selected conversion method and adds the indication bit to the converted digital sampled data. Subsequently, the data transmission link 140 transmits the digital sampled data compressed by the data compressor 130b to the data decompressor 150b, and the data decompressor 150b can perform an inverse conversion corresponding to operation 210b based on the indication bit to decompress the digital sampled data.

[0063] Reference Figure 8B , in operation 211b after operation 200b ( Figure 8A ), at least one of the M bits of the M-bit mantissa region corresponding to the N-bit mantissa region previously set by the first converter 131b for floating-point conversion is further assigned to the N-bit exponent region in a data format for the second converter 132b to perform fixed-point conversion. In operation 212b, the second converter 132b performs fixed-point conversion on the digital sample data based on the converted data format. Subsequently, operation 220b ( Figure 8A ) can be performed.

[0064] Figure 9A And Figure 9B are flowcharts for describing the operation of the digital sampled data group unit of the data compressor 130b according to an exemplary embodiment of the inventive concept. Hereinafter, a description will be given with reference to Figure 7 . Figure 7 as follows.

[0065] Reference Figure 9A , in operation 220c, the data compressor 130b selects a conversion method based on the maximum value among multiple pieces of digital sample data included in the digital sample data group. In operation 210c, the data compressor 130b converts the digital sample data group based on the selected conversion method. In operation 220c, the data compressor 130b generates an indication bit indicating the selected conversion method, which is commonly applied to the digital sample data group, and adds the indication bit to the converted digital sample data group. Subsequently, the data transmission link 140 transmits the digital sample data group compressed by the data compressor 130b to the data decompressor 150b, and the data decompressor 150b performs an inverse conversion corresponding to operation 210c based on the indication bit to decompress the compressed digital sample data group.

[0066] Reference Figure 9B, in operation 230c, the data compressor 130b sets the number of data items in the digital sampling data group based on the data probability distribution of the input signal. In an exemplary embodiment, the data compressor 130b sets the number of data items in the digital sampling data group based on the variance of the data probability distribution of the input signal. Subsequently, operation 200c ( Figure 9A ) can be performed.

[0067] Figure 10 is a block diagram for describing a data compressor 130c that performs a compression operation based on a second compression method and a data decompressor 150c that performs a decompression operation based on a second decompression method according to an exemplary embodiment of the present invention.

[0068] Refer to Figure 10 , the data compressor 130c compresses the digital sampling data based on the second compression method. In an exemplary embodiment, when the magnitude of the value of the digital sampling data is greater than the threshold, the data compressor 130c selects a floating-point conversion method to perform conversion on the digital sampling data, and when the magnitude of the value of the digital sampling data is less than the threshold, the data compressor 130c outputs the digital sampling data without separate conversion. For example, the data compressor 130c can output the digital sampling data as it is or with increased bits to indicate that it has not been converted. The threshold has been referred to above in Figure 7 , and thus, its detailed description is omitted.

[0069] In an exemplary embodiment, the data compressor 130c includes a determination circuit 134c, a first converter 131c (e.g., a logic circuit), and an indication bit adder 135c (e.g., an adder circuit). The first converter 131c can perform a conversion operation based on the floating-point conversion method. The determination circuit 134c can compare the magnitude of the I-sampling data value and the magnitude of the Q-sampling data value of the digital sampling data with the threshold of Equation (1) to select a conversion method. When the maximum value of the absolute value |I| of the I-sampling data and the absolute value |Q| of the Q-sampling data is greater than the threshold, the determination circuit 134c can select the floating-point conversion method to activate the first converter 131c, and can output the I-sampling data and the Q-sampling data to the first converter 131c. When the maximum value of the absolute value |I| of the I-sampling data and the absolute value |Q| of the Q-sampling data is equal to or less than the threshold, the determination circuit 134c can output the I-sampling data and the Q-sampling data to the indication bit adder 135c without separate conversion.

[0070] When the first converter 131c is activated, the first converter 131c performs a conversion operation on each of the I sampled data and the Q sampled data based on a floating-point conversion method. In an embodiment, as described above, the first converter 131c may perform a floating-point conversion on each of the I sampled data and the Q based on the data probability distribution of the input signal, corresponding to a predetermined number of bits in the mantissa region and a predetermined number of bits in the exponent region.

[0071] The indication bit adder 135c receives the converted I sample data and the converted Q sample data from the first converter 131c, or receives the bypassed I sampled data and Q sampled data, and may generate an indication bit indicating whether a conversion operation is performed on the I sampled data and the Q sampled data. The indication bit adder 135c may add the generated indication bit to the received digital sampled data.

[0072] The data transmission link 140 transmits the digital sampled data output from the data compressor 130c to the data decompressor 150c. The data decompressor 150c may process the digital sampled data compressed by the data compressor 130c or bypassed. For example, processing the compressed digital sampled data or the original data input to the determination circuit 134c. Hereinafter, the digital sampled data received by the data decompressor 150c is referred to as received data.

[0073] In an exemplary embodiment, the data decompressor 150c includes a determination circuit 154c and a third converter 151c (e.g., a logic circuit). The determination circuit 154c may activate the third converter 151c based on the indication bit of the received data. In an embodiment, the third converter 151c corresponds to the first converter 131b, and the third converter 151c performs a conversion operation on the received data based on an inverse conversion method of the floating-point conversion method, and may output the converted received data to the processor ( Figure 1 160). Moreover, the determination circuit 154c may bypass the received data on which a separate conversion operation is not performed, and may output the received data to the processor ( Figure 1 160). For example, if the received data is not compressed, the determination circuit 154c outputs the received data to the processor without outputting it to the third converter 151c. For ease of description, Figure 10 the embodiments correspond to exemplary configurations. However, the embodiments of the present embodiment are not limited thereto. Various implementation embodiments for compressing digital sampled data by using the above second compression method and decompressing digital sampled data by using the above second decompression method may be applied to the data compressor 130c and the data decompressor 150c.

[0074] Figures 11 to 13 is a diagram for describing a method of selecting a compression method according to an exemplary embodiment of the inventive concept.

[0075] Reference Figure 11 , the data compressor 200 includes a compression mode (CM) selector 210 (e.g., a selection circuit, a multiplexer, etc.), first compression logic 221 to third compression logic 223 (e.g., logic circuits), and a generation circuit 230. The first compression logic 221 to the third compression logic 223 compress digital sampled data based on different compression modes. For example, the first compression logic 221 may compress digital sampled data based on the first compression mode described above with reference to Figure 6A , the second compression logic 222 may compress digital sampled data based on the second compression mode described above with reference to Figure 7 or Figure 10 , and the third compression logic 223 may compress digital sampled data based on a third compression mode that combines the first compression mode and the second compression mode. However, this is only an exemplary embodiment, and the inventive concept is not limited thereto. The first compression logic 221 to the third compression logic 223 may be implemented to perform compression operations based on different compression modes other than the above-mentioned compression modes. In addition, the data compressor 200 may include more or fewer compression logics. Additionally, in Figure 11 , the first compression logic 221 to the third compression logic 223 are shown as separate logics, however, the first compression logic 221 to the third compression logic 223 may share some elements.

[0076] The compression mode selector 210 may select an optimal compression mode from the first to the third compression modes based on at least one of the communication environment, operation mode, and desired performance value of the wireless communication device including the data compressor 200, and then may operate based on the selected optimal compression mode. In an exemplary embodiment, the compression mode selector 210 selects a compression mode based on the error vector magnitude (EVM) representing the degree of loss caused by compression and decompression. The EVM may be defined according to the following equation (2).

[0077]

[0078] In equation (2), P avg may represent the average power corresponding to the input signal, x k may represent the k-th original digital sampled data, may represent the k-th decompressed digital sampled data, and N S may represent the number of digital sampled data for measuring the EVM. The digital sampled data for measuring the EVM may be referred to as test sampled data.

[0079] In an embodiment, the generation circuit 230 measures the EVM of each of the first compression logic 221 to the third compression logic 223 by using a plurality of test sampling data to generate information about the EVM. Moreover, the generation circuit 230 may predict the EVM of each of the first compression logic 221 to the third compression logic 223 to generate information about the EVM. In an exemplary embodiment, the generation circuit 230 predicts the EVM of each of the first compression logic 221 to the third compression logic 223 based on the compression-decompression loss parameter corresponding to each of the first compression mode to the third compression mode and the variance parameter of the data probability distribution of the input signal. The compression-decompression loss parameter may be defined to represent the degree of compression-decompression loss, which is predetermined for each compression mode based on various communication environments or communication conditions of the wireless communication device. The various communication environments or communication conditions may include the target signal-to-noise ratio (SNR) of the wireless communication device, the internal data transfer speed, the desired compression ratio, the total number of allowable transmitted bits, and the target system performance. The variance parameter of the data probability distribution of the input signal may represent the variance degree of the data probability distribution of the input signal.

[0080] The compression mode selector 210 may receive information about the EVM from the generation circuit 230 and may select a compression mode based on the information about the EVM. For example, the compression mode selector 210 may refer to the information about the EVM to select the compression mode corresponding to the minimum EVM.

[0081] In an embodiment, the generation circuit 230 selects a compression mode by further using the information about the EVM and the target SNR and the allowable SNR loss required by the wireless communication device. The target SNR, the allowable SNR loss, and the EVM may be defined according to the following equation (3).

[0082]

[0083] In equation (3), SNR loss may represent the allowable SNR loss, and SNR target may represent the target SNR.

[0084] In an embodiment, the compression mode selector 210 is based on whether the value obtained by the arithmetic operation based on the EVM and the target SNR "SNR target " is the same as the predetermined allowable SNR loss "SNR lossselect a compression method that matches the conditions within. Also, when there are multiple compression methods for an EVM that satisfy the conditions of Equation (3), the compression method selector 210 may select the compression method with the highest compression ratio from among the multiple compression methods. However, this is merely an exemplary embodiment, and the inventive concept is not limited thereto. In addition to Equation (3), various metrics for selecting an optimal compression method may be set.

[0085] The compression method selector 210 and the generation circuit 230 may each include a computing circuit that measures or predicts the EVM and performs arithmetic operations required to select a compression method. In some embodiments, the compression method selector 210 and the generation circuit 230 may be implemented as one block.

[0086] The compression method selector 210 selects one compression method from among the first to third compression methods and activates the compression logic corresponding to the selected compression method among the first to third compression logics 221 to 223, thereby allowing the activated compression logic to perform a compression operation on the digital sampled data. Subsequently, the digital sampled data compressed by the selected compression logic may be decompressed based on the decompression method corresponding to the selected compression logic and provided to the processor.

[0087] Reference Figure 12 In operation S300, the compression method selector 210 selects one compression method from among multiple compression methods. As described above with reference to Figure 11 , the compression method selector 210 may select a compression method based on the degree of loss caused by compression and decompression corresponding to each of the multiple compression methods, or may select a compression method currently suitable for the wireless communication device by using various methods such as selecting a compression method that satisfies Equation (3). In operation S310, the compression logic selected by the compression method selector 210 compresses the digital sampled data based on the selected compression method.

[0088] Further reference Figure 13 In operation S301, the generation circuit 301 generates the degree of loss caused by compression and decompression corresponding to each of the multiple compression methods. For example, the generation circuit 301 may generate an EVM representing the degree of loss caused by compression and decompression. In operation S302, the compression method selector 210 may select one compression method from among the multiple compression methods based on the degree of loss caused by compression and decompression of each compression method. Subsequently, operation S310 ( Figure 12 ) may be performed.

[0089] Figure 14 is a block diagram showing a storage system 1000 according to an exemplary embodiment of the inventive concept.

[0090] Reference Figure 14 , the storage system 1000 includes a host 1100 (e.g., a host device) and a storage device 1200. The storage device 1200 can send a signal SGL to the host 1100 or receive the signal SGL from the host 1100 through a signal connector, and can be powered by PWR through a power connector. In an exemplary embodiment, the storage device 1200 includes a controller 1210 (e.g., a control circuit), an auxiliary power supply 1220, and a plurality of storage devices 1230, 1240, and 1250.

[0091] The controller 1210 includes a data compressor 1215 to which the embodiments are applied, and the data compressor 1215 can compress data based on an appropriate compression method according to the environment or data transmission / reception state between the host 1100 and the storage device 1200, and can provide the compressed data to the storage devices 1230, 1240, and 1250 through channels Ch1 to Chn. Any one of the data compressors 130, 130a, 130b, 130c, or 200 can be used to implement the data compressor 1215. In addition, based on the state of each of the channels Ch1 to Chn, the data compressor 1215 can change the compression method for each storage device and can perform a compression operation on the data. Additionally, although not shown in Figure 14 , the controller 1210 or each of the memory devices 1230, 1240, and 1250 may further include a data decompressor (not shown) corresponding to the data compressor 1215, and can perform a data decompression operation. For example, the data decompressor can be implemented by any one of the data decompressors 150, 150a, 150b, 150c.

[0092] Figure 15 is a diagram showing a communication device including a data compressor or a data decompressor according to an exemplary embodiment of the inventive concept.

[0093] Reference Figure 15 , the home gadget 2100, the home appliance 2120, the entertainment device 2140, and the access point (AP) 2200 may each include a data compressor or a data decompressor according to the above embodiments. In some embodiments, the home gadget 2100, the home appliance 2120, the entertainment device 2140, and the AP 2200 may configure an Internet of Things (IoT) network system. Figure 15 The communication device shown is only an exemplary embodiment. Therefore, it should be understood that a wireless communication device according to an embodiment may be included in Figure 15 other communication devices not shown.

[0094] Although the inventive concept has been specifically shown and described with reference to embodiments of the present invention, it should be understood that various changes in form and detail may be made without departing from the spirit and scope of the inventive concept.

Claims

1. A wireless communication device, comprising: a radio frequency integrated circuit (RFIC) configured to receive an input signal to generate a digital sampling signal from the input signal; a data compressor configured to compress the digital sampling signal according to a compression method based on a data probability distribution of the input signal, wherein the data probability distribution of the input signal varies based on a receivable signal amplitude range of the RFIC; a data decompressor configured to decompress the compressed digital sampling signal based on a decompression method corresponding to the compression method to generate a decompressed digital sampling signal; a data transmission link configured to transmit the compressed digital sampling signal to the data decompressor; and a processor configured to process the decompressed digital sampling signal, wherein the data compressor is configured to perform a floating-point conversion on digital sampling data based on a point at which the value of the digital sampling data included in the digital sampling signal lies in the data probability distribution of the input signal, wherein the data compressor is further configured to select a data probability distribution corresponding to the receivable signal amplitude range of the RFIC from a plurality of data probability distributions.

2. The wireless communication device according to claim 1, wherein the data compressor is configured to adjust a value of an exponent region that determines a resolution based on a data probability corresponding to the value of the digital sampling data to perform the floating-point conversion.

3. The wireless communication device according to claim 1, wherein based on a plurality of receivable signal amplitude ranges in the RFIC, a number of bits corresponding to the exponent region in the floating-point conversion is determined based on a data probability distribution having a maximum variance among a plurality of data probability distributions of the input signal.

4. The wireless communication device according to claim 1, wherein the data compressor is configured to perform least significant bit (LSB) truncation on the digital sampling data to generate truncated sampling data, and perform a floating-point conversion on the truncated sampling data based on a point at which the value of the truncated sampling data lies in the data probability distribution of the input signal.

5. The wireless communication device according to claim 1, wherein the data compressor is configured to select one of a floating-point conversion and a fixed-point conversion based on an amplitude of the value of the digital sampling data included in the digital sampling signal, and perform the selected conversion on the digital sampling data.

6. The wireless communication device according to claim 5, wherein the digital sampling data includes in-phase (I) sampling data and quadrature (Q) sampling data, and the data compressor is configured to select one of a floating-point conversion and a fixed-point conversion based on the sampling data having the maximum value among the I sampling data and the Q sampling data, and perform the selected conversion on the I sampling data and the Q sampling data together.

7. The wireless communication device according to claim 5, wherein the data compressor is configured to perform a floating-point conversion on the digital sampling data based on a data format including N bits corresponding to a mantissa region and M bits corresponding to an exponent region when an amplitude of the value of the digital sampling data is greater than a threshold, where N and M are integers of 1 or greater.

8. The wireless communication device according to claim 7, wherein The data compressor is configured to perform a fixed-point conversion on the digital sampled data based on a data format in which at least one of M bits is further allocated to N bits when the magnitude of the value of the digital sampled data is equal to or less than a threshold value.

9. The wireless communication device according to claim 5, wherein, the data compressor is configured to generate an indication bit that indicates a conversion selected from among a floating-point conversion and a fixed-point conversion, and the data decompressor is configured to decompress the converted digital sampled data based on the indication bit and a decompression method corresponding to the selected conversion.

10. The wireless communication device according to claim 1, wherein, the data compressor is configured to select a conversion from among a floating-point conversion and a fixed-point conversion based on the maximum value among a plurality of pieces of digital sampled data included in a digital sampled data group of a digital sampled signal, and perform the selected conversion on the digital sampled data group.

11. The wireless communication device according to claim 1, wherein, the data compressor is configured to perform least significant bit (LSB) truncation on the digital sampled data included in the digital sampled signal to generate truncated sampled data, select a conversion from among a floating-point conversion and a fixed-point conversion based on the magnitude of the value of the truncated sampled data, and perform the selected conversion on the truncated sampled data.

12. A wireless communication device, comprising: a radio frequency integrated circuit (RFIC) configured to receive an input signal to generate a digital sampled signal from the input signal; a data compressor configured to select a compression method from among a plurality of compression methods using a data probability distribution of the input signal, and compress the digital sampled signal based on the selected compression method; a data decompressor configured to decompress the compressed digital sampled signal based on a decompression method corresponding to the selected compression method to generate a decompressed digital sampled signal; a data transmission link configured to transmit the compressed digital sampled signal to the data decompressor; and a processor configured to process the decompressed digital sampled signal, wherein the data compressor is configured to determine the number of bits in an exponent region and the number of bits in a mantissa region based on a point at which the value of the digital sampled data included in the digital sampled signal is in the data probability distribution of the input signal, and perform a floating-point conversion on the digital sampled data of the digital sampled signal to have a data format suitable for the number of bits in the mantissa region and the number of bits in the exponent region.

13. The wireless communication device according to claim 12, wherein, the data compressor is configured to select a compression method from among the plurality of compression methods based on a loss degree caused by compression and decompression of each of the plurality of compression methods.

14. The wireless communication device according to claim 13, further comprising: a generation circuit configured to perform an arithmetic operation on a difference between a plurality of pieces of original digital sampled data and a plurality of pieces of decompressed digital sampled data for each of the plurality of compression methods using the data compressor and the data decompressor to generate a loss degree caused by compression and decompression.

15. The wireless communication device according to claim 13, further comprising: A generation circuit, configured to predict, for each of the multiple compression methods, the degree of loss caused by compression and decompression based on the compression-decompression loss parameter corresponding to each of the multiple compression methods and the variance parameter of the data probability distribution of the input signal.

16. The wireless communication device according to claim 12, wherein, the data compressor is configured to, when a first compression method is selected from the multiple compression methods, perform least significant bit (LSB) truncation on the digital sampling data included in the digital sampling signal to generate truncated sampling data, and perform floating-point conversion on the truncated sampling data based on the point at which the value of the truncated sampling data corresponding to the execution result lies in the data probability distribution of the input signal.

17. The wireless communication device according to claim 12, wherein, the data compressor is configured to, when a first compression method is selected from the multiple compression methods, select one conversion from floating-point conversion and fixed-point conversion based on the magnitude of the value of the digital sampling data included in the digital sampling data, and perform the selected conversion on the digital sampling data.

18. An operation method of a wireless communication device, the operation method comprising: converting an input signal received into a digital sampling signal through analog-to-digital conversion; compressing the digital sampling signal according to a compression method based on the data probability distribution of the input signal to generate a compressed digital sampling signal; transmitting the compressed digital sampling signal to be processed; decompressing the compressed digital sampling signal based on a decompression method corresponding to the compression method; and processing the decompressed digital sampling signal, wherein compressing the digital sampling signal includes: setting the number of bits of the mantissa region and the number of bits of the exponent region based on the variance of the data probability distribution; and performing floating-point conversion on the digital sampling data based on the setting result, wherein compressing the digital sampling signal includes: selecting a data probability distribution corresponding to the receivable signal amplitude range of the wireless communication device from multiple data probability distributions.

19. The operation method according to claim 18, wherein, compression of the digital sampling signal further includes: determining the point at which the value of the digital sampling data included in the digital sampling signal lies in the data probability distribution of the input signal; and performing floating-point conversion on the digital sampling data based on the determination result.

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