Log likelihood ratio calculation circuit and wireless receiving device

Abstract

To improve the calculation accuracy of a log-likelihood ratio and improve the error correction capability of low-density parity check.SOLUTION: A log-likelihood ratio LLRN(bit_num) based on thermal noise and a log-likelihood ratio LLRφ(bit_num) based on phase noise are multiplied by weighting coefficients WN and Wφ, respectively, and then added together to calculate a log-likelihood ratio LLRbit_num.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a log-likelihood ratio calculation circuit and a radio receiving device, and more particularly to a circuit for calculating a log-likelihood ratio used in error correction in low-density parity check decoding and a radio receiving device including said circuit. [Background technology]

[0002] Conventionally, in low density parity check (LDPC) decoding, a method for performing error correction using a log-likelihood ratio (LLR) calculated based on the distribution of thermal noise in a received signal has been known (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2013-201582 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in the high multilevel modulation method, the influence of factors other than thermal noise, such as phase noise and fading of the received signal, is large, and there is a problem that the error correction ability of the low density parity check is reduced. Specifically, in the conventional method of calculating the log likelihood ratio, it is assumed that the amplitude of the received signal fluctuates based on a normal distribution / Gaussian distribution centered on an ideal symbol point due to thermal noise of the received signal. However, this method cannot take into account the fluctuation when the phase of the symbol rotates due to phase noise and fading of the received signal. Therefore, the calculation accuracy of the log likelihood ratio deteriorates, especially in an environment where phase noise exists, and the error correction ability of the low density parity check is reduced.

[0005] Therefore, an object of the present invention is to provide a log-likelihood ratio calculation circuit and a wireless receiving device including the log-likelihood ratio calculation circuit, which can improve the calculation accuracy of the log-likelihood ratio and thereby improve the error correction capability of the low-density parity check. [Means for solving the problem]

[0006] In order to solve the above problem, the invention described in claim 1 calculates a log likelihood ratio by multiplying a log likelihood ratio based on thermal noise and a log likelihood ratio based on phase noise by a weighting factor and then adding them together. A log likelihood ratio calculation circuit , For bits of a 4-bit received signal modulated by a quadrature amplitude modulation method with a multi-level number of 16 on the transmitting side, which bits are distinguished as being 0 or 1 according to the phase angle of an ideal symbol point, the log likelihood ratio based on the phase angle of the received signal is calculated based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 according to the phase angle, and for bits that are divided into an ideal symbol point (called an "amplitude-distinguishing symbol point") which is distinguished as being 0 or 1 according to the amplitude and an ideal symbol point (called a "phase-distinguishing symbol point") which is distinguished as being 0 or 1 according to the phase angle, the phase noise-based log likelihood ratio is calculated based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 according to the phase angle, using the phase angle of the received signal; for bits that are divided into an ideal symbol point (called an "amplitude-distinguishing symbol point") which is distinguished as being 0 or 1 according to the amplitude and an ideal symbol point (called a "phase-distinguishing symbol point") which is distinguished as being 0 or 1 according to the phase angle, the amplitude of the received signal is determined as to whether the bit is the amplitude-distinguishing symbol point or the phase-distinguishing symbol point, and then the phase noise-based log likelihood ratio is calculated based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 according to the amplitude, using the amplitude of the received signal; and for the phase-distinguishing symbol point, the phase noise-based log likelihood ratio is calculated based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 according to the phase angle, using the phase angle of the received signal. The log-likelihood ratio calculation circuit is characterized in that

[0008] Claim 2 The invention described in claim 1 The log-likelihood ratio calculation circuit according to the present invention is characterized in that it calculates a log-likelihood ratio based on the phase noise of each bit according to a predetermined formula.

[0009] Claim 3 The invention described in claim 1 OR 2 A radio receiving device comprising the log-likelihood ratio calculation circuit according to any one of claims 1 to 5. Effect of the Invention

[0010] Claim 1 to Claim 2 According to the invention described in the above, the log-likelihood ratio based on thermal noise and the log-likelihood ratio based on phase noise are calculated by taking into account the degree of mutual priority between them (specifically, by multiplying each log-likelihood ratio by a weighting coefficient) and then adding them to calculate the log-likelihood ratio for each bit. This takes into account not only the influence of thermal noise but also factors such as phase noise and distribution fluctuations due to fading in the calculation of the log-likelihood ratio, making it possible to realize a low-density parity check that is robust against disturbances including phase noise.

[0011] Claim 1 to Claim 2According to the invention described in the above, the log-likelihood ratio is calculated taking into account the probability distribution when the phase of the symbol rotates or fluctuates based on a normal distribution / Gaussian distribution due to phase noise or fading of the received signal, etc., so that it is possible to improve the calculation accuracy of the log-likelihood ratio even in an environment where phase noise of the received signal is dominant, and ultimately to improve the error correction capability of the low-density parity check.

[0012] Claim 3 According to the invention described in the above, it is possible to achieve the above-mentioned advantageous effects in a wireless receiving device that performs error correction in low-density parity check decoding using a log-likelihood ratio. [Brief description of the drawings]

[0013] [Figure 1] 1 is a functional block diagram showing a schematic configuration of a wireless receiving device according to an embodiment of the present invention, including an LLR calculation unit as a log-likelihood ratio calculation circuit. [Diagram 2] 1 is a functional block diagram showing a schematic configuration of an LLR calculation unit serving as a log-likelihood ratio calculation circuit according to an embodiment. [Diagram 3] FIG. 2 is a diagram showing an arrangement of ideal symbol points in the 16QAM system and bit strings assigned to each ideal symbol point. [Figure 4] FIG. 13 is a diagram for explaining the setting of variables related to the calculation of a log-likelihood ratio. [Diagram 5] FIG. 13 is a diagram for explaining the concept of a calculation formula for a log-likelihood ratio of the first bit, and in particular, a diagram for explaining a region where the first bit is 0 and a region where the first bit is 1. [Figure 6] 11 is a diagram for explaining the concept of a calculation formula for a log-likelihood ratio of the 1st bit. FIG. [Figure 7] FIG. 13 is a diagram for explaining the concept of a calculation formula for a log-likelihood ratio of the second bit, and in particular, a diagram for explaining a symbol having bit information in amplitude and a symbol having bit information in phase. [Figure 8] FIG. 13 is a diagram for explaining the concept of a calculation formula for a log-likelihood ratio for the second bit. [Figure 9] 1A and 1B are diagrams for explaining the concept of a weighting coefficient for a log-likelihood ratio, in which (A) is a diagram for explaining a case where a log-likelihood ratio based on thermal noise is prioritized, and (B) is a diagram for explaining a case where a log-likelihood ratio based on phase noise is prioritized. [Figure 10] 1 is a diagram for explaining problems with a conventional method for calculating a log-likelihood ratio and a countermeasure by a log-likelihood ratio calculation circuit according to the present invention; [Figure 11] FIG. 1 is a functional block diagram showing a schematic configuration of an evaluation system used in a verification example of the effectiveness of a log-likelihood ratio calculation circuit according to the present invention. [Figure 12] 13 is a diagram showing a code error rate as an evaluation result in a verification example of the effectiveness of the log-likelihood ratio calculation circuit according to the present invention. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] The present invention will be described below based on the illustrated embodiment. Note that the following describes the characteristic configuration of the present invention, and the description of the conventional mechanism for wireless communication will be omitted. In addition, in each drawing, a signal line transmitting a real part (I signal; in other words, an in-phase component, an I signal component) constituting a complex signal and a signal line transmitting an imaginary part (Q signal; in other words, a quadrature component, a Q signal component) are shown together as a single signal line. In addition, in the following description, "greater than or equal to" and "greater than" may be interchangeable, and further, "less than or equal to" and "less than" may be interchangeable.

[0015] FIG. 1 is a functional block diagram showing a schematic configuration of a wireless receiving device 1 according to an embodiment of the present invention, including an LLR calculation section 20 as a log-likelihood ratio calculation circuit according to the embodiment of the present invention.

[0016] The antenna 10 receives a signal wave sent from a radio transmitting device (not shown) and transfers the signal wave to a channel filter 11 as a received signal.

[0017] Here, the wireless transmitting device performs low-density parity check coding on the wireless frame to be transmitted, modulates it using a quadrature amplitude modulation method with a multi-level number of 16 (i.e., 16QAM method; QAM is an abbreviation for Quadrature Amplitude Modulation), and transmits it from an antenna. In other words, the wireless receiving device 1 receives a multi-level modulated signal that has been subjected to low-density parity check coding and modulated using a quadrature amplitude modulation method with a multi-level number of 16 (16QAM method).

[0018] The channel filter 11 is a filter for limiting the reception band, and specifically may be configured by, for example, a bandpass filter. The channel filter 11 receives the reception signal transferred from the antenna 10, performs band limiting processing on the reception signal, and extracts and outputs a reception signal of a desired frequency band from the reception signal.

[0019] The mixer 13 receives an input of the received signal output from the channel filter 11 and also receives an input of a local signal output from the local oscillator 12, multiplies the received signal by the local signal, and converts (specifically, down-converts) the frequency of the received signal and outputs it.

[0020] The automatic gain control unit 14 receives the received signal output from the mixer 13, performs gain adjustment processing on the received signal so that the level of the received signal becomes constant at a predetermined level, and outputs the received signal (which is an analog signal) after gain adjustment processing (in other words, after level correction).

[0021] A / D converter 15 (Analog-to-Digital converter) receives the received signal output from automatic gain control unit 14, and performs analog-to-digital conversion processing on the received signal to convert the analog signal into a digital signal. That is, A / D converter 15 outputs a digital received signal.

[0022] The digital quadrature detection unit 16 receives the digital received signal output from the A / D converter 15 and converts the received signal into a baseband signal by quadrature detection. Specifically, the digital quadrature detection unit 16 includes a multiplier that receives a cosine wave from a numerically controlled oscillator and synchronously detects an in-phase component of the received signal, and a multiplier that receives a sine wave from the numerically controlled oscillator and synchronously detects an orthogonal component of the received signal. The digital quadrature detection unit 16 performs quadrature detection of multi-level modulation by digital signal processing, and generates and outputs a complex signal (in other words, a detection signal of the in-phase component and the orthogonal component) expressed in IQ orthogonal coordinates with a real component (I signal) constituting a real part and an imaginary component (Q signal) constituting an imaginary part.

[0023] The numerically controlled oscillator of the digital quadrature detection unit 16 is an oscillator that oscillates at a frequency according to a set value, and generates a cosine wave and a sine wave whose phases differ from each other by 90°, and supplies them to each of the two multipliers.

[0024] The roll-off filter 17 receives the baseband signal (in other words, the detection signal of the in-phase component and the quadrature component) output from the digital quadrature detection unit 16, processes the in-phase component and the quadrature component of the baseband signal to remove inter-symbol interference, and shapes the spectrum waveform of the baseband signal to have a desired roll-off, and outputs the result.

[0025] The equalizer 18 receives the baseband signal output from the roll-off filter 17, performs adaptive equalization processing on each of the in-phase component and quadrature component of the baseband signal in order to remove inter-symbol interference due to frequency selective fading, and outputs a baseband signal after adaptive equalization processing (received signal).

[0026] The decoding unit 19 receives the log-likelihood ratio (LLR: abbreviation of Log-Likelihood Ratio) output from the LLR calculation unit 20, and performs low-density parity check decoding processing using the log-likelihood ratio according to, for example, a sum-product decoding method.

[0027] The LLR calculation unit 20 is a circuit that calculates a log-likelihood ratio used in error correction in low-density parity check decoding, and is incorporated in the wireless receiving device 1.

[0028] FIG. 2 is a functional block diagram showing a schematic configuration of an LLR calculation unit 20 serving as a log-likelihood ratio calculation circuit according to an embodiment.

[0029] The LLR calculation unit 20 according to the embodiment calculates a log-likelihood ratio (LLR) based on thermal noise. N(bit_num) and the log-likelihood ratio (LLRφ) based on phase noise (bit_num) and each of them has a weighting factor W N , Wφ and then summed to obtain the log-likelihood ratio (LLR) bit_num The calculation is performed as follows.

[0030] The LLR calculation unit 20 according to the embodiment further calculates a log-likelihood ratio LLRφ based on phase noise. (bit_num) The phase angle φ of the ideal symbol point of the 4-bit received signal modulated by quadrature amplitude modulation with a multi-level of 16 on the transmitting side is i For bits that are distinguished as being 0 or 1 depending on the amplitude, the phase angle xφ of the received signal is used to calculate the probability density distribution that will be 0 and the probability density distribution that will be 1 depending on the phase angle. For bits that are distinguished as being 0 or 1 depending on the amplitude (called "amplitude-distinguished symbol points") and ideal symbol points that are distinguished as being 0 or 1 depending on the phase angle (called "phase-distinguished symbol points"), whether they are amplitude-distinguished symbol points or phase-distinguished symbol points is determined using the amplitude xφ of the received signal. R Then, for the amplitude-distinguishing symbol point, the amplitude x of the received signal is R is used to calculate based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 depending on the amplitude, and for the phase-distinguished symbol points, the phase angle xφ of the received signal is used to calculate based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 depending on the phase angle.

[0031] First, the arrangement of ideal symbol points in the 16QAM system and the bit strings assigned to each ideal symbol point (in other words, the signal space diagram of 16QAM) are shown in Figure 3. i is the in-phase component of the ideal symbol constellation, and B i are the orthogonal components of the ideal symbol constellation (where i=1, 2, 3, 4).

[0032] The LLR calculation unit 20 calculates the log-likelihood ratio (LLR) of the (bit_num)th bit in accordance with the following formula 1. bit_num Calculate. (Number 1) LLR bit_num = W N ×LLR N(bit_num) +Wφ×LLRφ (bit_num) Here, bit_num: bit number (where bit_num = 1, 2, 3, 4) LLR N(bit_num) : Log-likelihood ratio based on thermal noise LLRφ (bit_num) : Log-likelihood ratio based on phase noise W N :Weighting factor of log-likelihood ratio based on thermal noise Wφ: weighting factor of log-likelihood ratio based on phase noise

[0033] Log-likelihood ratio (LLR) based on thermal noise for the (bit_num)th bit N(bit_num) Specifically, for example, is calculated according to the following formulas 2A to 2D.

number

[0034] The meanings of the symbols and variables in the above formulas 2A to 2D are as follows. LLR N1 : Log-likelihood ratio based on thermal noise at the 1st bit LLR N2 : Log-likelihood ratio based on thermal noise at the 2nd bit LLR N3 : Log-likelihood ratio based on thermal noise at the 3rd bit LLR N4: Log-likelihood ratio based on thermal noise at the 4th bit x i : In-phase component of the received signal x q : Orthogonal components of the received signal A i : In-phase components of ideal symbol point constellation (where i=1,2,3,4) B i : Orthogonal components of ideal symbol point constellation (where i=1,2,3,4) σ 2 :Noise variance

[0035] Log-likelihood ratio (LLRφ) based on phase noise of the (bit_num)th bit (bit_num) Specifically, for example, is calculated according to the following formulas 3 to 6. FIG. 4 shows the settings of variables used in the following formulas 3 to 6, which are defined for the arrangement of ideal symbol points shown in FIG.

[0036] The meanings of the symbols and variables in the following Equations 3 to 7 are as follows: Note that the phase angle "φ" of the ideal symbol point in the following equations is shown as "Φ" in the drawings. xφ: Phase angle of the received signal x R : Received signal amplitude φ i : Phase angle of ideal symbol point (where φ subscript i = 0, 1, 2, . . . , 11) R i : Amplitude of ideal symbol point (where the subscript i of R = 0, 1, 2) σ 2 :Noise variance R thre1 : First amplitude threshold R thre2 : Second amplitude threshold

[0037] The log-likelihood ratio LLRφ1 based on the phase noise of the first bit is calculated according to the following Equation 3.

number

[0038] The log-likelihood ratio (LLRφ2) based on the phase noise of the second bit is the amplitude of the received signal x R is the first amplitude threshold R thre1 Above or equal to the second amplitude threshold R thre2 Below (i.e., x R ≧R thre1 or x R ≦R thre2 ) is calculated according to the following Equation 4A, and the amplitude of the received signal x R is the first amplitude threshold R thre1 Less than a second amplitude threshold R thre2 Greater than (i.e., R thre2 <x R <R thre1 ) is calculated according to the following Equation 4B.

number

[0039] The log-likelihood ratio LLRφ3 based on the phase noise of the third bit is calculated according to the following Equation 5.

number

[0040] The log-likelihood ratio (LLRφ4) based on the phase noise of the 4th bit is the amplitude of the received signal x R is the first amplitude threshold R thre1 Above or equal to the second amplitude threshold R thre2 Below (i.e., x R ≧R thre1 or x R ≦R thre2 ) is calculated according to the following Equation 6A, and the amplitude of the received signal x R is the first amplitude threshold R thre1 Less than a second amplitude threshold R thre2 Greater than (i.e., R thre2 <x R <R thre1 ) is calculated according to the following Equation 6B.

number

[0041] The above formulas 3 to 6 are based on the following concept (see FIGS. 5 to 8).

[0042] The first bit is the phase angle from -90° to +90° (in other words, from 270° to 360° / 0° to 90°; that is, the phase angle of the ideal symbol point in Figure 5 is from Φ 11 , Φ0 to Φ2) and becomes 1 when the phase angle is +90° to -90° (in other words, 90° to 270° through 180°; that is, the second and third quadrants of the IQ orthogonal coordinate system including the phase angle of the ideal symbol point Φ3 to Φ5, Φ6 to Φ8 in FIG. 5). Therefore, if it is considered that the phase of the received signal fluctuates based on a normal distribution / Gaussian distribution, the probability density of the first bit being 0 is shown as in FIG. 6A, and the probability density of the first bit being 1 is shown as in FIG. 6B. Based on this, by considering these probability density distributions as each term, the above-mentioned Equation 3 for calculating the log-likelihood ratio LLRφ1 based on the phase noise of the first bit is derived (see FIG. 6C).

[0043] The third bit is based on the same idea as the first bit; that is, the third bit is 0 when the phase angle goes from 0° to +90° to +180° (i.e., the first and second quadrants of the IQ orthogonal coordinate system including the phase angles of the ideal symbol points Φ0 to Φ5 through Φ2 and Φ3 in Fig. 5), and is 0 when the phase angle goes from +180° to +270° to 0° (i.e., the phase angles of the ideal symbol points Φ6 to Φ8 and Φ9 in Fig. 5). 11 Based on this, the above formula 5 for calculating the log likelihood ratio LLRφ3 based on the phase noise of the third bit is derived by considering the probability density distribution where the third bit is 0 and the probability density distribution where the third bit is 1 as each term.

[0044] As for the second bit, the same concept can be applied to all quadrants of the IQ orthogonal coordinate system, so the first quadrant of the IQ orthogonal coordinate system will be used as an example for explanation. As shown in Fig. 7, the second bit is divided into ideal symbol points where the amplitude determines whether it is 0 or 1 (the "symbol with bit information carried in the amplitude" in the figure; it is an amplitude-distinguishing symbol point), and ideal symbol points where the phase determines whether it is 0 or 1 (the "symbol with bit information carried in the phase" in the figure; it is a phase-distinguishing symbol point). For this reason, when the amplitude x of the received signal is R The first amplitude threshold R thre1 and a second amplitude threshold R thre2 By comparing with, it is determined whether the received signal / symbol carries bit information in amplitude or phase, and the method of calculating the log-likelihood ratio is changed accordingly. The probability density distributions of the second bit being 0 and the probability density distributions of the second bit being 1 for symbols carrying bit information in amplitude are shown in Fig. 8A, and the probability density distributions of the second bit being 0 and the probability density distributions of the second bit being 1 for symbols carrying bit information in phase are shown in Fig. 8B. Based on this, by considering these probability density distributions as each term, the above formula 4 for calculating the log-likelihood ratio LLRφ2 based on the phase noise of the second bit is derived (see Fig. 8C).

[0045] The fourth bit is based on the same idea as the second bit. For symbols that carry bit information in amplitude, the same applies as the second bit. For symbols that carry bit information in phase, the fourth bit is 0 when the phase angle of the ideal symbol point is Φ2, Φ3, Φ8, and Φ9, and 1 when the phase angle of the ideal symbol point is Φ0, Φ5, Φ6, and Φ 11Based on this, by considering as individual terms the probability density distribution where the fourth bit is 0 and the probability density distribution where the fourth bit is 1 for symbols carrying bit information in amplitude, and the probability density distribution where the fourth bit is 0 and the probability density distribution where the fourth bit is 1 for symbols carrying bit information in phase, the above-mentioned Equation 6 for calculating the log-likelihood ratio LLRφ4 based on the phase noise of the fourth bit can be derived.

[0046] First amplitude threshold R thre1 and the second amplitude threshold R thre2 is not limited to a specific value, and may be, for example, the first amplitude threshold R thre1 is set between the amplitudes R1 and R2 of the ideal symbol points and a second amplitude threshold R thre2 is set between the amplitudes R0 and R1 of the ideal symbol points and is appropriately set to an appropriate value while taking into consideration the fact that a symbol having bit information in its amplitude and a symbol having bit information in its phase can be easily distinguished. thre1 is set as shown in Equation 7A below, and the second amplitude threshold R thre2 It is considered that the value is set as shown in the following formula 7B. (Number 7A) R thre1 = R1+(R2-R1) / 2 (Number 7B) R thre2 = R o +(R1-R0) / 2

[0047] Then, by performing low-density parity check decoding processing using the log-likelihood ratio calculated according to the above formula 1, a log-likelihood ratio (LLR) based on the distribution of thermal noise is obtained. N Since the log-likelihood ratio LLRφ based on the distribution of phase noise is added to the sigma-based log-likelihood ratio, robustness against phase noise is improved. In addition, since the influence of phase noise varies depending on the magnitude of thermal noise and the position of the symbol, the weighting coefficient W N , Wφ controls whether the log-likelihood ratio based on thermal noise or phase noise is prioritized.

[0048] Weighting coefficient W for each log-likelihood ratioN , Wφ are not limited to specific values, but are appropriately set to appropriate values ​​taking into consideration the degree to which the log-likelihood ratio based on thermal noise or phase noise should be prioritized, taking into account that the influence of phase noise varies depending on the magnitude of thermal noise and the position of the symbol.

[0049] Weighting coefficient W for each log-likelihood ratio N , Wφ may be calculated by a predetermined formula. Specifically, for example, the weighting coefficient W of the log-likelihood ratio based on thermal noise is calculated according to the following formula 8A: N is calculated, and the weighting factor W of the log-likelihood ratio based on the phase noise is calculated according to the following Equation 8B. N may be calculated.

number

[0050] The meanings of the symbols and variables in the above formulas 8A and 8B are as follows: N: Variance of the thermal noise (i.e., √N corresponds to the average amplitude of the thermal noise) S d : Symbol spacing in QAM system α: Priority adjustment coefficient β: Equivalent adjustment coefficient

[0051] The priority adjustment coefficient α is determined by the average amplitude fluctuation due to thermal noise (i.e., √N) being the symbol interval S of the QAM system. d is a coefficient for determining the percentage below which the log-likelihood ratio LLRφ based on phase noise is prioritized.

[0052] The priority adjustment coefficient α is not limited to a specific value, and is appropriately set to an appropriate value after considering the degree of priority between thermal noise and phase noise, etc. Specifically, the priority adjustment coefficient α may be set to any value within a range of about 0.1 to 0.5, for example, as one example only.

[0053] The equal adjustment coefficient β is a coefficient for equalizing the magnitude of each log-likelihood ratio when the log-likelihood ratio due to thermal noise and the log-likelihood ratio due to phase noise have equal priorities.

[0054] The equal adjustment coefficient β is not limited to a specific value, but is appropriately set to a value that equalizes the magnitude of each log-likelihood ratio when the log-likelihood ratio due to thermal noise and the log-likelihood ratio due to phase noise have equal priority, assuming the value of the priority adjustment coefficient α.

[0055] The priority adjustment coefficient α and the equal adjustment coefficient β are set in advance in the weighting coefficient control unit 24 of the LLR calculation unit 20 .

[0056] Weighting coefficient W for each log-likelihood ratio N , Wφ is calculated according to the above Equation 8A and Equation 8B, so that the average amplitude √N of the thermal noise is the same as the symbol interval S of the QAM system, as shown in FIG. d If the weighting factor W for the log-likelihood ratio based on thermal noise is greater than α×100[%], N becomes larger (specifically, larger than 1), and conversely, the weighting factor Wφ for the log-likelihood ratio based on the phase noise becomes smaller (specifically, smaller than 1). In other words, the log-likelihood ratio based on the thermal noise is prioritized, and the final log-likelihood ratio LLR bit_num In FIG. 9, α is set to 0.5 as an example.

[0057] On the other hand, as shown in Fig. 9B, the average amplitude of the thermal noise, √N, is smaller than the symbol interval S of the QAM system. d When the weighting factor Wφ for the log-likelihood ratio based on phase noise is large (specifically, becomes 1 or more), the weighting factor Wφ for the log-likelihood ratio based on thermal noise becomes large (specifically, becomes 1 or more). N becomes small (specifically, becomes less than 1), which means that the log-likelihood ratio based on the phase noise is prioritized and the final log-likelihood ratio LLR bit_num is calculated.

[0058] Note that Equation 8 is a weighting factor W for the log-likelihood ratio based on the thermal noise (in other words, the thermal noise is used as a variable). N and a weighting factor Wφ for the log-likelihood ratio based on phase noise are calculated. Based on the magnitude of the phase noise (in other words, using the phase noise as a variable), the weighting factor Wφ for the log-likelihood ratio based on thermal noise is calculated. N and a weighting factor Wφ for the log-likelihood ratio based on the phase noise may be calculated.

[0059] The thermal noise LLR calculation unit 21 of the LLR calculation unit 20 receives the baseband signal (received signal) output from the equalizer 18, and calculates the in-phase component x of the received signal from the baseband signal. i and the quadrature component of the received signal x q and obtain the thermal noise-based log-likelihood ratio (LLR) of the (bit_num)th bit according to the above Equations 2A to 2D. N(bit_num) Calculate and output.

[0060] The phase noise LLR calculation unit 22 receives the baseband signal (received signal) output from the equalizer 18, and calculates from the baseband signal the phase angle xφ of the received signal and the amplitude x of the received signal. R and obtaining the amplitude x of the received signal. R and the first amplitude threshold R thre1 and the second amplitude threshold R thre2 Taking into consideration the magnitude relationship between and , the log-likelihood ratio LLRφ based on the phase noise of the (bit_num)th bit is calculated according to the above Equations 3 to 6. (bit_num) Calculate and output.

[0061] The thermal noise power estimator 23 receives the baseband signal (received signal) output from the equalizer 18, estimates the thermal noise power in the wireless receiving device 1 based on the baseband signal, and outputs an estimated amount of the thermal noise power.

[0062] The weighting factor control unit 24 receives the baseband signal (received signal) output from the equalizer 18, and also receives the estimated amount of thermal noise power output from the thermal noise power estimating unit 23, and uses the baseband signal and the estimated amount of thermal noise power (specifically, calculates the variance N of the thermal noise) to calculate a weighting factor W of the log-likelihood ratio based on thermal noise according to the above-mentioned Equation 8A. N and also calculates and outputs a weighting coefficient Wφ of the log-likelihood ratio based on the phase noise according to the above equation 8B.

[0063] The first multiplier 25 multiplies the log-likelihood ratio (LLR) based on the thermal noise output from the thermal noise LLR calculation unit 21. N(bit_num) and a weighting coefficient W based on the log-likelihood ratio output from the weighting coefficient control unit 24. N The thermal noise-based log-likelihood ratio (LLR) is N(bit_num) and the weighting factor W of the log-likelihood ratio based on the thermal noise N Multiply and multiply the result (i.e., W N ×LLR N(bit_num) ) to output.

[0064] The second multiplier 26 multiplies the log-likelihood ratio LLRφ based on the phase noise output from the phase noise LLR calculation unit 22. (bit_num) and receives an input of a weighting coefficient Wφ of a log-likelihood ratio based on phase noise output from a weighting coefficient control unit 24, and calculates the log-likelihood ratio LLRφ based on the phase noise. (bit_num) and the weighting coefficient Wφ of the log-likelihood ratio based on the phase noise, and the result of the multiplication (i.e., Wφ×LLRφ (bit_num) ) to output.

[0065] The adder 27 receives the multiplication result (i.e., W N ×LLR N(bit_num) ) and the multiplication result (i.e., Wφ×LLRφ) output from the second multiplier 26. (bit_num) ), and adds up the multiplication results according to the above formula 1. The sum is the log-likelihood ratio (LLR) for the (bit_num)th bit. bit_num (=W N×LLR N(bit_num) +Wφ×LLRφ (bit_num) ) to output.

[0066] Then, the decoder 19 calculates the log-likelihood ratio (LLR) output from the LLR calculator 20. bit_num The log-likelihood ratio (LLR) is calculated by: bit_num is used to perform low density parity check decoding processing, for example, according to the sum-product decoding method.

[0067] According to the LLR calculation unit 20 serving as a log-likelihood ratio calculation circuit according to the embodiment, the log-likelihood ratio (LLR) based on thermal noise is calculated. N(bit_num) and the log-likelihood ratio (LLRφ) based on phase noise (bit_num) Taking into account the degree of mutual priority between N(bit_num) Weighting factor W N and multiplying the log-likelihood ratio LLRφ (bit_num) (multiplying by the weighting coefficient Wφ) and adding these together to obtain the log-likelihood ratio (LLR) for each bit. bit_num By calculating the above, the log-likelihood ratio is calculated taking into account the effects of phase noise and distribution fluctuations due to fading in addition to the effects of thermal noise, so that a low-density parity check that is robust against disturbances including phase noise can be realized.

[0068] According to the LLR calculation unit 20 serving as a log-likelihood ratio calculation circuit of the embodiment, the log-likelihood ratio is calculated taking into consideration the probability distribution when the phase of the symbol rotates or fluctuates based on a normal distribution / Gaussian distribution due to phase noise or fading of the received signal, etc., so that it is possible to improve the calculation accuracy of the log-likelihood ratio even in an environment where phase noise of the received signal is dominant, and ultimately to improve the error correction capability of the low-density parity check.

[0069] Specifically, as shown in Fig. 10, the conventional method of calculating the log likelihood ratio is premised on the assumption that the amplitude of the received signal fluctuates based on a normal distribution / Gaussian distribution centered on an ideal symbol point due to thermal noise of the received signal (see dashed circle Cf in the figure). Therefore, if there is a fluctuation (see circular arc arrow Fp in the figure) when the phase of the symbol rotates due to the phase noise of the received signal, the signal Sf determined to have a high probability of being received will differ from the actual transmission signal Ss. In contrast, the LLR calculation unit 20 as the log likelihood ratio calculation circuit according to the embodiment is designed to take into account the distribution of fluctuations due to the phase noise of the received signal, that is, to calculate the log likelihood ratio while also considering the situation in which the symbol fluctuates on the envelope E due to the phase noise of the received signal. Therefore, even if there is a fluctuation (see circular arc arrow Fp in the figure) when the phase of the symbol rotates due to the phase noise of the received signal, the signal determined to have a high probability of being received will match the actual transmission signal Ss, making it possible to improve the error correction ability of the low density parity check.

[0070] An example of verifying the effectiveness of the log-likelihood ratio calculation circuit according to the present invention will be described below.

[0071] In this verification example, an evaluation system shown in Fig. 11 was used for the purpose of comparing the calculation accuracy of the log likelihood ratio between a conventional method for calculating a log likelihood ratio and the log likelihood ratio calculation circuit according to the present invention in an environment where thermal noise and phase noise are present. The evaluation system in this verification example was configured as a system for comparing the calculation accuracy of the log likelihood ratio between a conventional method (reference number 34) that calculates a log likelihood ratio based on the distribution of thermal noise of a received signal, and the log likelihood ratio calculation circuit according to the present invention (reference number 20) that calculates a log likelihood ratio while also taking into account the phase noise of the received signal, after modulating a predetermined sample signal by the 16QAM method (reference number 31 in the figure) and adding phase noise and thermal noise (reference numbers 32 and 33).

[0072] The evaluation conditions for this verification example were set as follows: Modulation method: 16QAM method Carrier-to-noise ratio (CNR): 15-25dB Phase noise level: -60dBc (at 1kHz offset) Symbol spacing S in QAM format d :2 Priority adjustment coefficient α: 0.125 Equivalent adjustment coefficient β: 100

[0073] Here, the log-likelihood ratio takes a positive value when the probability that the transmitted bit is 0 is high, and takes a negative value when the probability that the transmitted bit is 1 is high. Using this, the actual transmitted bit is compared with the sign of the log-likelihood ratio calculated by the conventional method (reference number 34 in FIG. 9) to count the number of times the sign is incorrect (reference number 35), and the actual transmitted bit is compared with the sign of the log-likelihood ratio calculated by the log-likelihood ratio calculation circuit (reference number 20) according to the present invention to count the number of times the sign is incorrect (reference number 36).

[0074] As a result of the evaluation system shown in Fig. 11, it was confirmed that the log-likelihood ratio calculation circuit according to the present invention had a smaller code error rate at each carrier-to-noise ratio as shown in Fig. 12. It was also confirmed that the higher the carrier-to-noise ratio and the more dominant the phase noise, the greater the improvement rate achieved by the log-likelihood ratio calculation circuit according to the present invention. From this result, it was confirmed that the code error rate is reduced by the log-likelihood ratio calculation circuit according to the present invention compared to the conventional method of calculating a log-likelihood ratio.

[0075] Although the embodiment of the present invention has been described above, the specific configuration is not limited to the above embodiment, and even if there are design changes and the like within the scope of the gist of the present invention, they are included in the present invention.

[0076] Specifically, in the above embodiment, the log-likelihood ratio calculation circuit according to the present invention is incorporated as an LLR calculation unit 20 in the wireless receiving device 1 whose schematic configuration is shown in FIG. 1. However, the configuration of the wireless device in which the log-likelihood ratio calculation circuit according to the present invention can be incorporated is not limited to the wireless receiving device 1 whose schematic configuration is shown in FIG. 1. The log-likelihood ratio calculation circuit according to the present invention may be incorporated in a wireless device having another configuration.

[0077] In the above embodiment, the log-likelihood ratio (LLR) based on thermal noise is N(bit_num) is calculated according to the above-mentioned Equation 2A to Equation 2D, but the log-likelihood ratio (LLR) based on thermal noise is calculated according to the above-mentioned Equation 2A to Equation 2D. N(bit_num) The calculation formula / calculation method is not limited to Formula 2A to Formula 2D. In the above embodiment, the log-likelihood ratio LLRφ based on phase noise is (bit_num) is calculated according to the above-mentioned formulas 3 to 6, but the log-likelihood ratio LLRφ based on the phase noise is (bit_num) The calculation formula / calculation method is not limited to the formulas 3 to 6. That is, the gist of the present invention is the log-likelihood ratio (LLR) based on thermal noise. N(bit_num) and the log-likelihood ratio (LLRφ) based on phase noise (bit_num) Taking into account the degree of mutual priority between N(bit_num) Weighting factor W N and multiplying the log-likelihood ratio LLRφ (bit_num) (multiplying by the weighting coefficient Wφ) and adding these together to obtain the log-likelihood ratio (LLR) for each bit. bit_num The log-likelihood ratio (LLR) based on thermal noise is calculated. N(bit_num) and the log-likelihood ratio (LLRφ) based on phase noise (bit_num) Other configurations including the calculation formula / calculation method are not limited to a specific configuration. [Explanation of symbols]

[0078] 1 Radio receiving device 10 Antennas 11 Channel Filters 12 Local Oscillator 13 Mixer 14 Automatic Gain Control 15 A / D Converter 16 Digital quadrature detection section 17 Roll-off Filter 18 Equalizer 19 Decoding section 20 LLR calculation unit 21 Thermal noise LLR calculation section 22 Phase noise LLR calculation section 23 Thermal noise power estimator 24 Weighting factor control section 25 First Multiplier 26 Second Multiplier 27 Adder

Claims

1. a log likelihood ratio calculation circuit that calculates a log likelihood ratio by multiplying a log likelihood ratio based on thermal noise and a log likelihood ratio based on phase noise by a weighting factor and then adding the weighting factors, The log-likelihood ratio based on the phase noise is Of the 4-bit received signals modulated by quadrature amplitude modulation with a multi-level of 16 on the transmitting side, For bits that are differentiated as 0 or 1 depending on the phase angle of the ideal symbol point, using a phase angle of the received signal, calculating based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 according to the phase angle; Regarding bits that can be divided into ideal symbol points that are distinguished as being 0 or 1 depending on the amplitude (called "amplitude-distinguishing symbol points") and ideal symbol points that are distinguished as being 0 or 1 depending on the phase angle (called "phase-distinguishing symbol points"), determining whether the symbol point is the amplitude-distinguishing symbol point or the phase-distinguishing symbol point based on the amplitude of the received signal; calculating the amplitude-distinguishing symbol point based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 according to the amplitude using the amplitude of the received signal; calculating the phase-distinguishing symbol point based on a probability density distribution that becomes 0 and a probability density distribution that becomes 1 according to the phase angle using a phase angle of the received signal; A log-likelihood ratio calculation circuit comprising:

2. A log-likelihood ratio based on phase noise is calculated for a first bit, which is a bit that is distinguished as being 0 or 1 depending on a phase angle of the ideal symbol point, according to the following Equation 1, and a log-likelihood ratio based on phase noise is calculated for a third bit, according to the following Equation 3, A log likelihood ratio based on phase noise is calculated for the second bit, which is a bit that is divided into the amplitude distinguishing symbol point and the phase distinguishing symbol point, according to the following Equation 2, and a log likelihood ratio based on phase noise is calculated for the fourth bit, according to the following Equation 4 (where x R ≧R thre1 or x R ≦R thre2 Formula 2A and Formula 4A are used when R thre2 <x R <R thre1 Formula 2B and Formula 4B are used when [0010] [0025] [0030] [0045] Here, xφ: Phase angle of the received signal x R : Amplitude of the received signal φ i : Phase angle of ideal symbol point (where φ subscript i = 0, 1, 2, ..., 11) R i : Amplitude of ideal symbol point (where the subscript i of R = 0, 1, 2) σ 2 : noise variance R thre1 : first amplitude threshold R thre2 : second amplitude threshold 2. The log-likelihood ratio calculation circuit according to claim 1 .

3. A log-likelihood ratio calculation circuit according to claim 1 or 2, A radio receiving device comprising:

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