MIMO OFDM communication system and log likelihood ratio scaling method thereof

Abstract

This application relates to a MIMO (Multi-In-Time) orthogonal frequency division multiplexing (MIMO) communication system and its log-likelihood ratio scaling method, comprising: during the preamble period, determining the channel gain of corresponding subcarriers and the average channel gain value of these subcarriers based on the preamble of the packet, and determining the average log-likelihood ratio based thereon; during the preamble period, determining a scaling ratio based on the average channel gain value, the channel gain, and a scaling parameter; during the payload period, generating an original log-likelihood ratio sequence based on the payload of the packet; adjusting the original log-likelihood ratio sequence based on the average log-likelihood ratio and the scaling parameter to generate a first log-likelihood ratio sequence; and adjusting the first log-likelihood ratio sequence based on the scaling ratio to generate a second log-likelihood ratio sequence, wherein the second log-likelihood ratio sequence is quantized and decoded to provide relevant information about the payload.

Description

Technical Field

[0001] This case concerns orthogonal frequency division multiplexing (OFDM) communication systems, particularly multiple-input multiple-output (MIMO) OFDM communication systems and their log-likelihood ratio scaling methods that can be determined using techniques such as mutual information during the packet preamble period. Background Technology

[0002] Existing communication systems use error correction coding to correct detected errors during data transmission. For example, the transmitter can use error correction coding to add parity bits, while the receiver performs error correction decoding to reduce the bit error rate. In the receiver, the input to the channel decoder is the log likelihood ratio of the coded bits. However, to reduce the complexity of the channel decoder, the word length of the input log likelihood ratio must be limited and reduced. However, directly reducing the word length will lead to message loss and degrade decoding performance. A simple solution is to multiply the log likelihood ratio by a scaling factor before reducing the word length. However, determining the scaling factor is challenging, as it must be applicable to different channel conditions and system parameters, such as modulation and coding schemes (MCS), MIMO scheme, bandwidth, etc. Finding a specific scaling factor applicable to all different situations at the receiver is extremely challenging. Summary of the Invention

[0003] In some embodiments, one of the objectives of this invention is (but not limited to) to provide a multiple-input multiple-output orthogonal frequency division multiplexing communication system and its log-likelihood ratio scaling method that can use mutual information to find the scaling ratio during the preamble of the packet, thereby improving the shortcomings of the prior art.

[0004] In some embodiments, one of the objectives of this invention is (but not limited to) to provide a multi-input multi-output orthogonal frequency division multiplexing communication system and its log-likelihood ratio scaling method that can find a suitable scaling ratio during the preamble period of the packet to account for all log-likelihood ratios fed into the channel decoder circuit during the payload period of the packet, thereby improving the shortcomings of the prior art.

[0005] In some embodiments, a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication system includes a channel gain estimation circuit, a scaling circuit, a maximum similarity detection circuit, a first scaling circuit, a second scaling circuit, a quantizer circuit, and a channel decoder circuit. The channel gain estimation circuit determines, during the preamble period of a packet, a channel gain of a corresponding subcarrier among a plurality of subcarriers and an average channel gain value of the plurality of subcarriers, and determines a log-likelihood average value based on the average channel gain value. The scaling circuit determines a scaling ratio during the preamble period based on the average channel gain value, the channel gain of the corresponding subcarrier, and a scaling parameter. The maximum similarity detection circuit generates an original log-likelihood ratio sequence based on the payload of the packet during the payload period. The first scaling circuit adjusts the original log-likelihood ratio sequence based on the average log-likelihood ratio and the scaling parameter during the payload period to generate a first log-likelihood ratio sequence. A second scaling circuit adjusts the first log-likelihood ratio sequence according to the scaling ratio during the payload period to generate a second log-likelihood ratio sequence. A quantizer circuit quantizes the second log-likelihood ratio sequence during the payload period to generate quantized data. A channel decoder circuit decodes the quantized data during the payload period to obtain relevant payload information.

[0006] In some embodiments, a log-likelihood ratio scaling method that can be performed via a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) communication system includes the following operations: during the preamble period of a packet, determining a channel gain of a corresponding subcarrier and an average channel gain value of the multiple subcarriers based on a preamble of the packet, and determining a log-likelihood ratio average based on the average channel gain value; during the preamble period, determining a scaling ratio based on the average channel gain value, the channel gain of the corresponding subcarrier, and a scaling parameter; generating an original log-likelihood ratio sequence based on a payload of the packet; adjusting the original log-likelihood ratio sequence based on the average log-likelihood ratio and the scaling parameter to generate a first log-likelihood ratio sequence; and adjusting the first log-likelihood ratio sequence based on the scaling ratio to generate a second log-likelihood ratio sequence, wherein the MIMO orthogonal frequency division multiplexing (OFDM) communication system quantizes and decodes the second log-likelihood ratio sequence to obtain relevant information about the payload.

[0007] Regarding the features, implementation, and effects of this case, the preferred embodiments are described in detail below with reference to the drawings. Attached Figure Description

[0008] Figure 1 A schematic diagram of a multiple-input multiple-output orthogonal frequency division multiplexing communication system is shown according to some embodiments of this case;

[0009] Figure 2 Drawing based on some embodiments of this case Figure 1 The operation flowchart of the channel gain estimation circuit in the diagram;

[0010] Figure 3 A flowchart of a log-likelihood ratio scaling method is provided based on some embodiments of this case; and

[0011] Figure 4 A schematic diagram of a log-likelihood ratio scaling mechanism is provided based on some embodiments of this case. Detailed Implementation

[0012] All terms used herein have their common meanings. The definitions of the terms used in commonly used dictionaries, and any examples of the use of any term discussed herein, are merely illustrative and should not be construed as limiting the scope or meaning of this document. Similarly, this document is not limited to the various embodiments shown in this specification.

[0013] As used herein, “coupled” or “connected” can refer to two or more components making direct physical or electrical contact with each other, or indirectly making direct physical or electrical contact with each other, or to two or more components operating or acting on each other. As used herein, the term “circuitry” can refer to a specific system implemented by one or more circuits, and the term “circuit” can refer to a device in which at least one transistor and / or at least one active or passive component are connected in a certain manner to process signals.

[0014] As used herein, the term "and / or" includes any combination of one or more of the listed related items. In this document, the terms first, second, third, etc., are used to describe and distinguish individual elements. Therefore, a first element in this document may also be referred to as a second element without departing from the intent of this case. For ease of understanding, similar elements in the various diagrams will be assigned the same reference numerals.

[0015] Figure 1 A schematic diagram of a Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency-Division Multiplexing (OFDM) communication system 100 is shown below, based on some embodiments of this invention. For simplicity, Figure 1The diagram primarily shows the receiver portion of the MIMO OFDM communication system 100. It should be understood that in different embodiments, the MIMO OFDM communication system 100 may also include a transmitter portion for transmitting packets or data. The MIMO OFDM communication system 100 includes a channel gain estimation circuit 110, a scaling circuit 120, a maximum similarity detection (MLD) circuit 130, a scaling circuit 140, a scaling circuit 150, a quantizer circuit 160, and a channel decoder circuit 170.

[0016] The channel gain estimation circuit 110 determines the channel response (e.g., the channel gain of the corresponding subcarrier) of multiple subcarriers (e.g., but not limited to, all subcarriers) based on the preamble symbol PS of the packet SP during the preamble symbol period, and determines an average channel gain value for these subcarriers accordingly. The channel gain estimation circuit 110 further determines the average log-likelihood ratio based on the average channel gain value. The scaling circuit 120 determines the scaling factor SF based on the average channel gain value during the preamble symbol period of the packet SP. The related operations and mathematical calculations of the channel gain estimation circuit 110 and the scaling circuit 120 will be described later.

[0017] The maximum similarity detection circuit 130 is used to generate a raw log likelihood ratio (OLR) sequence based on the payload PL of the packet SP during the payload period of the packet SP. In some embodiments, the payload PL is the data transmitted in the packet SP following the preamble PS. In some embodiments, the raw log likelihood ratio sequence OLR can be used to measure the ratio of each bit in the payload PL to possible data values ​​(typically logic 0 or logic 1, but not limited thereto). In some embodiments, the maximum similarity detection circuit 130 may generate the raw log likelihood ratio sequence OLR by performing a Sphere Decoding Algorithm, an Iterative Decoding Algorithm, and / or a Tree Search Decoding Algorithm based on the payload PL. The types of algorithms used by the maximum similarity detection circuit 130 described above are merely illustrative and are not intended to limit the scope of this invention.

[0018] Scaling circuit 140 is used to scale the average log-likelihood ratio and scaling parameter N during the payload period of packet SP. midThe original log-likelihood ratio sequence OLR is adjusted to produce the log-likelihood ratio sequence LR2. Specifically, in some embodiments, the scaling circuit 140 includes a normalization circuit 142 and a multiplier circuit 144. The normalization circuit 142 is used to normalize the original log-likelihood ratio sequence OLR based on the average log-likelihood ratio during the payload period of the packet SP to produce the log-likelihood ratio sequence LR1. The multiplier circuit 144 is used to multiply the scaling parameter N during the payload period of the packet SP. mid Multiply by the log-likelihood ratio sequence LR1 to produce the log-likelihood ratio sequence LR2.

[0019] In some embodiments, the scaling parameter N mid To determine the character length n of the OLR based on the original log-likelihood ratio sequence T It is determined that its value is approximately the average of the probability mass function P1 corresponding to the original log-likelihood ratio sequence OLR. In some embodiments, the scaling parameter N mid It can be expressed as the following formula:

[0020]

[0021] In some embodiments, such as Figure 1 As shown, the distribution of the probability mass function P1 corresponding to the original log-likelihood ratio sequence OLR is concentrated in the low-value region of the log-likelihood ratio sequence (denoted as |LLR|). In contrast, the distribution after scaling parameter N... mid The adjusted log-likelihood ratio sequence LR2 has a more evenly distributed probability mass function P2. Thus, the original log-likelihood ratio sequence OLR can be initially scaled.

[0022] Scaling circuit 150 adjusts the log-likelihood ratio sequence LR2 according to the scaling ratio SF during the payload period of packet SP to generate log-likelihood ratio sequence LR3. Through scaling circuits 140 and 150, the amount of data in the original log-likelihood ratio sequence OLR can be reduced (e.g., the total number of bits in log-likelihood ratio sequence LR3 is less than the total number of bits in the original log-likelihood ratio sequence OLR), thereby reducing the complexity and hardware cost of channel decoder circuit 170. In some embodiments, scaling circuit 150 may be implemented by a multiplier circuit, but this is not a limitation of the present invention. Quantizer circuit 160 can quantize the log-likelihood ratio sequence LR3 during the payload period to generate quantized data QD. Channel decoder circuit 170 can decode the quantized data QD to obtain information related to the payload PL.

[0023] Figure 2 Drawing based on some embodiments of this case Figure 1The flowchart of the channel gain estimation circuit 110 is shown. In operation S210, channel estimation and channel smoothing are performed during the preamble of the packet SP to determine the channel response H of a corresponding subcarrier (e.g., the nth subcarrier) among multiple subcarriers. n For example, the channel gain estimation circuit 110 can perform a channel estimation algorithm based on the preamble PS during the preamble period of the packet SP, thereby determining the corresponding channel response for each of the multiple subcarriers used to transmit the packet SP. In operation S220, the channel response H of the nth subcarrier is determined during the preamble period of the packet SP. n Perform sorted QR decomposition (SQRD) to obtain the corresponding triangular matrix R. n And according to the triangular matrix R n Obtain the diagonal element r corresponding to the user in the d-th spatial stream. n,d Determine the channel gain (e.g., average channel gain value) of the corresponding subcarrier.

[0024] For example, the channel gain estimation circuit 110 can estimate the channel response H of the nth subcarrier based on the preamble PS of the packet SP. n and respond to H on this channel n - Perform sorted QR decomposition to obtain the corresponding orthogonal matrix Q. n With triangular matrix R n The above operation can be expressed as the following formula:

[0025] H n ≡Q n ·R n

[0026] Among them, H n The channel response representing the nth subcarrier can be represented in matrix form, Q. n For the orthogonal matrix corresponding to the nth subcarrier, R n This is the triangular matrix corresponding to the nth subcarrier. For example, suppose... Figure 1 The MIMO OFDM communication system 100 has two transmit antennas and two receive antennas in its application environment, and it can support data transmission for two users simultaneously. Through the aforementioned sorted QR decomposition, the triangular matrix Rn can be obtained as follows:

[0027]

[0028] Wherein, the triangular matrix R n Contains multiple diagonal elements r n,1 r n,2 r n,3 and r n,4In this example, the diagonal element r n,1 and diagonal element r n,2 Corresponding to the first user, and the diagonal element r n,3 and diagonal element r n,4 Corresponding to the second user. Thus, the channel gain estimation circuit 110 can obtain multiple diagonal elements r. n,1 r n,2 r n,3 and r n,4 And based on this, calculate multiple diagonal elements r n,1 r n,2 r n,3 and r n,4 - The square value of each (i.e.) as well as In some embodiments, multiple diagonal elements r n,1 r n,2 r n,3 and r n,4 - The squared value of each can be viewed as the channel gain of the nth subcarrier for different users on different antennas. It should be understood that, in the example above, the triangular matrix R... n Since it is an upper triangular matrix, some of its elements are marked with an asterisk (*), and these elements can be any value. In other examples, the triangular matrix R... n It can also be a lower triangular matrix, and this case is not limited to this.

[0029] In some embodiments, for further simplification, the channel gain corresponding to the same subcarrier for the same user can be set to the same value. For example, the first spatial stream and the second spatial stream (which is assigned to the first user) correspond to diagonal elements r, respectively. n,1 and diagonal element r n,2- The third and fourth spatial streams (which are allocated to the second user) correspond to the diagonal element r, respectively. n,3 and diagonal element r n,4 In some embodiments, the channel gain estimation circuit 110 can configure the channel gain of a subcarrier corresponding to the same user to the same value based on the signal-to-noise ratio of the current application environment. For example, if the current signal-to-noise ratio is higher than a preset value, the channel gain estimation circuit 110 can set the channel gain of the nth subcarrier corresponding to the first user to the diagonal element r. n,1 The square value and the diagonal element r n,2 The smaller of the squared values. Alternatively, if the current signal-to-noise ratio is not higher than the preset value, the channel gain estimation circuit 110 can set the channel gain corresponding to the nth subcarrier of the first user to the diagonal element r. n,1 The square value and the diagonal element r n,2The square value is the average of the two. The above calculation can be expressed as the following formula:

[0030]

[0031] in, The channel gain corresponding to the nth subcarrier of the uth user (equivalent to the channel gain in operation S220), Let be a set of values ​​d, corresponding to the u-th user. For example, if u is 1, the values ​​of d include 1 and 2 corresponding to the first user. Accordingly, the channel gain estimation circuit 110 can obtain the channel gain of the n-th subcarrier corresponding to the u-th user.

[0032] In operation S230, the above operation is repeated until the channel gain of all subcarriers is obtained, and the average channel gain value is determined based on the channel gain of all subcarriers. For example, by repeating the above operation multiple times, the channel gain estimation circuit 110 can obtain the channel gain of all subcarriers corresponding to the u-th user, and the average channel gain of all subcarriers over the frequency (e.g., averaging over all subcarriers) can obtain the average channel gain value corresponding to the u-th user. The above calculation can be expressed as the following formula:

[0033]

[0034] in, This corresponds to the average channel gain value for the u-th user. In operation S240, the average log-likelihood ratio is determined based on the average channel gain value. For example, the channel gain estimation circuit 110 can obtain the average log-likelihood ratio by calculating the following equation (1):

[0035]

[0036] In some embodiments, LLR in equation (1) can be the log-likelihood ratio generated by the maximum similarity detection circuit 130 based on the preceding symbol PS of the packet SP (e.g., it can be, but is not limited to, the symbol in the long training field). In equation (1), Let R be a triangular matrix n The diagonal elements (e.g., diagonal element r) in the text n,1 r n,2 r n,3 and r n,4 The square of ), where n is the guide number of the subcarrier (e.g., n can be 1 to N). SC , where the value N SC (where d is the total number of subcarriers), and d is the triangular matrix R. n The number of rows (i.e., d = 1, 2, 3, 4) and K is a preset parameter, which can be expressed as: Where α is the normalization factor for quadrature amplitude modulation (QAM), and Δ can be the minimum distance between signal constellation points, and Let be the noise power on the preamble PS, and t be the guide for the preamble PS. In some embodiments, parameters α and Δ in equation (1) can be parameters known during the system design phase, while the noise power... The noise power can be estimated by other circuits in the system. For example, in some embodiments, the MIMO OFDM communication system 100 may include a noise estimation circuit (not shown) that can perform operations such as the Maximum Likelihood Estimation (MSE) algorithm and the Minimum Mean-square Error (MMSE) algorithm based on the preamble PS of the packet SP to estimate the noise power. However, this case is not limited to this.

[0037] According to equation (1), the channel gain estimation circuit 110 can calculate the average log-likelihood ratio based on the squares of the multiple diagonal elements of the triangular matrix and a preset parameter K. In some embodiments, for further simplification, the channel gain estimation circuit 110 can use the aforementioned average channel gain value. The squares of the diagonal elements in the triangular matrix Rn in equation (1) are replaced. Therefore, based on the average channel gain value And the preset parameter K determines the average log-likelihood ratio (i.e., in equation (1)). In this way, a higher channel gain can be used for calculation when the signal-to-noise ratio is relatively low, thereby avoiding excessive distortion in the final estimated log-likelihood ratio.

[0038] In some embodiments, the derivation concept of equation (1) is briefly explained as follows. The log-likelihood ratio corresponding to the i-th bit in the m-th layer can be expressed as:

[0039]

[0040] This can be represented as the difference between the received signal y and the hypothetical signal (bit 0 and bit 1 respectively) at a specific bit. Further, the received signal y can be represented as:

[0041] y = H·x + N

[0042] Where x is the transmitted signal, H is the channel response, and N is the noise (e.g., it can have a mean of 0 and a variation of σ). 2The additive white Gaussian noise (CBD) is used. In cases of high signal-to-noise ratio (SNR), the signal power is much higher than the noise power, causing the distance between the received signal y and the hypothetical signal to be primarily determined by the minimum distance between the signal constellation points (i.e., the aforementioned parameter Δ). Taking constellation point X0 as an example, the aforementioned distance can be expressed as:

[0043]

[0044] Therefore, from the above equation, it can be seen that the average value of the log-likelihood ratio is proportional to the square of the parameter Δ. On the other hand, generally speaking, if the noise power of noise N... The larger the value, the smaller the log-likelihood ratio will be; that is, the mean of the log-likelihood ratio is usually inversely proportional to the noise power. Therefore, if we comprehensively consider normalization, parameter Δ, and noise power... After considering factors such as the guidance of each subcarrier, the average log-likelihood ratio approximated by equation (1) can be derived.

[0045] Accordingly, the scaling estimation circuit 120 can estimate the scaling parameter N during the preamble period of the packet SP. mid Average channel gain and the channel gain of the nth subcarrier The scaling factor SF is determined based on the channel gain of the nth subcarrier. For example, the scaling factor estimation circuit 120 can determine the scaling factor SF based on the channel gain of the nth subcarrier. For average channel gain value Perform normalization and multiply the normalized result by the scaling parameter N. mid This generates a gain parameter, and the scaling factor SF is determined based on the mutual information between this gain parameter and the output of the quantizer circuit 160. The aforementioned calculation for determining the gain parameter can be expressed as follows:

[0046]

[0047] in, This is the average channel gain value. Let be the channel gain of the nth subcarrier, and The gain parameter is as described above.

[0048] It should be understood that, in order to reduce the implementation complexity of the channel decoder circuit 170, the desired goal is to maximize the mutual information between the output of the quantizer circuit 160 and the signal before scaling by the scaling factor SF (i.e., the input of the scaling circuit 150). That is, the scaling factor SF maximizes the amount of information about the input of the scaling circuit 150 obtained by observing the output of the quantizer circuit 160 (equivalent to minimizing the information loss of the signal after scaling by the scaling factor SF). This mutual information can be expressed as follows:

[0049]

[0050] Q(βx)=y β

[0051] Where I(x,y) β ) represents mutual information, x is the input of the scaling circuit 150, β is the scaling ratio SF, and y β For the output of quantizer circuit 160, P r (x n Let P be the probability mass function of x. r (y m,β ) is y β The probability mass function, P r (x n ,y m,β ) for x and y β The joint probability mass function of the two, Q(βx), is the quantization function of the quantizer circuit 160.

[0052] As mentioned earlier, the desired goal is to find the mutual information I(x,y) that allows the aforementioned information to be obtained. β The scaling factor SF with the maximum value can be expressed as follows:

[0053]

[0054] in SF represents the estimated scaling factor.

[0055] To further simplify the circuit implementation, the aforementioned equations will be simplified using mathematical concepts. First, the aforementioned joint probability mass function P can be... r (x n ,y m,β (Expanded as follows:)

[0056]

[0057] Where δ[k] is the Kronecker delta function, which outputs 1 when k equals 0 and 0 when k is not equal to 0.SC This represents the total number of subcarriers. Furthermore, u<a,b> For generating unsigned digits (e.g., C, which can be x in the above formula) n or y m,β The operator ), where the value 'a' is the number of digits in the integer part and the value 'b' is the number of digits in the fractional part, and the function... This is used to shift C to an integer part that has no decimal part. It is a numerical value The number of times it appears in set x, and N y [y m,β ] is the numerical value y m,β The number of times it appears in set y.

[0058] The joint probability mass function P after the above expansion r (x n ,y m,β Substitute the aforementioned mutual information I(x,y) β From this, we can deduce the following:

[0059]

[0060] From the above formula, it can be seen that in order to make the mutual information I(x,y) β To maximize the value, the factor to the right of the minus sign in the above formula should have the minimum value. Therefore, based on the above information, the scaling factor SF can be rewritten as follows:

[0061]

[0062] in,

[0063] Therefore, it should be understood that the scaling factor SF (i.e., β in the above formula) should make the function J x,y (β) has a minimum value, which can be expressed as follows (2):

[0064]

[0065] in, L y Let L be the total number of quantization levels corresponding to set x, and L y Let y be the total number of quantization levels corresponding to set y.

[0066] Accordingly, the proportional estimation circuit 120 can estimate the aforementioned gain parameter. Let the signal x in the aforementioned equation (2) be defined. n(Equivalent to the input x of scaling circuit 150), and set the scaling ratio SF (equivalent to β in equation (2)) to a specific value, and record the number of quantization levels mapped to the output of quantizer circuit 160. Thus, by repeating the above steps, the scaling ratio SF that minimizes the value of equation (2) is found. In other words, according to equation (2), the scaling estimation circuit 120 can determine the scaling ratio SF based on the gain parameter. The mutual information between the output of the quantizer circuit 160 and the output of the quantizer circuit 160 (equivalent to the aforementioned I(x,y)) β The scaling factor SF is determined by the scaling factor.

[0067] For example, suppose the character length of the log-likelihood ratio corresponding to the input of the scaling circuit 150 is set to 11, and the character length of the log-likelihood ratio corresponding to the output of the quantizer circuit 160 is set to 6. Under this condition, if the decoding mechanism of the channel decoder circuit 170 is based on low-density parity-check (LDPC) code, the total number of quantization levels L that the channel decoder circuit 170 needs to process is... y It can be set to 32. Alternatively, if the decoding mechanism of the channel decoder circuit 170 is based on binary convolutional code (BCC), the total number of quantization levels L that the channel decoder circuit 170 needs to process is... y It can be set to 16. This will increase the total number of quantization levels L. y Taking a setting of 32 as an example, during the preamble period of the packet SP, the proportional estimation circuit 120 can estimate the gain parameter. The input is sent to the scaling circuit 150, which sets the scaling ratio SF to the first value. A counter records how many of the 32 quantization levels are mapped. The number of quantization levels recorded is N in the above formula (2). y [m]. Next, the scaling factor SF can be set to a second value and the number of quantization levels can be recorded again. In this way, the scaling factor SF can be found by repeating the above operation to make equation (2) have the minimum value.

[0068] In some embodiments, the scaling factor SF has a predetermined numerical range, and the scaling factor estimation circuit 120 can sequentially set the scaling factor SF to different values ​​within this predetermined numerical range to perform the above-described operation. In some embodiments, the aforementioned predetermined numerical range can be determined by circuit simulation and / or prior measurement, but this invention is not limited thereto.

[0069] Through the aforementioned operations, the MIMO OFDM communication system 100 can determine a suitable scaling factor SF during the preamble period of the packet SP, thereby reducing the character length of the original log-likelihood ratio sequence OLR and maintaining the maximum data correlation as much as possible (e.g., to maximize the aforementioned mutual information). This reduces the circuit complexity and hardware cost of the channel decoder circuit 170 (e.g., by reducing the length of data to be processed and the number of buffers used), while maintaining reliable data decoding performance. Accordingly, it should be understood that finding an appropriate scaling factor SF can significantly improve circuit applications in the OFDM communication field.

[0070] Figure 3 A flowchart of a log-likelihood ratio scaling method 300 is provided according to some embodiments of this invention. In some embodiments, the log-likelihood ratio scaling method 300 may be transmitted via a multiple-input multiple-output orthogonal frequency division multiplexing communication system (e.g., it may be, but is not limited to, [other systems]). Figure 1 The MIMO OFDM communication system 100 is executed.

[0071] In operation S310, during the preamble period of the packet, the channel gain of a corresponding subcarrier among multiple subcarriers and the average channel gain value of the multiple subcarriers are determined based on the preamble of the packet, and the average log-likelihood ratio is determined based on the average channel gain value. In operation S320, during the preamble period, the scaling ratio is determined based on the average channel gain value. In operation S330, during the payload period of the packet, an original log-likelihood ratio sequence is generated based on the payload of the packet. In operation S340, during the payload period, the original log-likelihood ratio sequence is adjusted based on the average log-likelihood ratio and the scaling parameter to generate a first log-likelihood ratio sequence. In operation S350, during the payload period, the first log-likelihood ratio sequence is adjusted based on the scaling ratio to generate a second log-likelihood ratio sequence, wherein the multiple-input multiple-output orthogonal frequency division multiplexing communication system quantizes and decodes the second log-likelihood ratio sequence to obtain relevant information of the payload.

[0072] The above-described operations can be referred to the descriptions in the foregoing embodiments, and therefore will not be repeated here. The multiple operations and / or steps in the log-likelihood ratio scaling method 300 are merely examples and are not limited to being performed in the order shown in these examples. Without departing from the operational mode and scope of the embodiments of this application, the related operations and / or steps in the above figures may be appropriately added, replaced, omitted, or performed in a different order. Alternatively, the related operations in the log-likelihood ratio scaling method 300 may be performed simultaneously or partially simultaneously.

[0073] Figure 4A schematic diagram of a log-likelihood ratio scaling mechanism 400 is provided according to some embodiments of this invention. In some embodiments, the log-likelihood ratio scaling mechanism 400 may be derived from... Figure 1 The MIMO OFDM communication system 100 is executed, but this case is not limited to it. The log-likelihood ratio scaling mechanism 400 includes a channel estimation and smoothing module 405, a matrix decomposition module 410, a frequency-wise gain calculation module 415, an average gain calculation module 420, a scaling module 425, a normalization module 430, a scaling ratio determination module 435, a maximum similarity detection module 440, a normalization module 445, a scaling module 450, a scaling module 455, a quantization module 460, and a decoder module 465. The operations of the channel estimation and smoothing module 405, matrix factorization module 410, frequency-wise gain calculation module 415, average gain calculation module 420, scaling module 425, normalization module 430, and scaling ratio determination module 435 are performed during the preamble of the packet SP, while the operations of the maximum similarity detection module 440, normalization module 445, scaling module 450, scaling module 455, quantization module 460, and decoder module 465 are performed during the payload of the packet SP.

[0074] The channel estimation and smoothing module 405, matrix decomposition module 410, frequency-wise gain calculation module 415, average gain calculation module 420, and scaling module 425 can correspond to Figure 1 The channel gain estimation circuit 110. The channel estimation and smoothing module 405 can estimate the channel response H of the nth subcarrier based on the preamble PS of the packet SP during the preamble period. n The matrix factorization module 410 can respond to the channel response H of the nth subcarrier during the preamble period. n Perform the aforementioned sorting QR decomposition to obtain the triangular matrix R. n The frequency-by-frequency gain calculation module 415 can calculate the gain based on the triangular matrix R during the preamble period. n Obtain the channel gain corresponding to each subcarrier (For example, it can be, but is not limited to, a triangular matrix R) n (The square of the diagonal elements). The average gain calculation module 420 can calculate the average gain based on the channel gain of each subcarrier during the preamble code period. Determine the average channel gain value The scaling module 425 can adjust the average channel gain value according to the aforementioned preset parameter K during the preamble period. This determines the log-likelihood ratio to the mean. In some embodiments, the channel gain estimation circuit 110 may be implemented by at least one digital signal processing circuit or microcontroller circuit having processing capabilities sufficient to perform the relevant operations of the above-described modules, but this application is not limited thereto.

[0075] The normalization module 430 and the scaling factor determination module 435 can correspond to Figure 1 The proportional estimation circuit 120. The normalization module 430 can adjust the channel gain corresponding to each subcarrier. For average channel gain value Perform normalization and multiply the normalized result by the scaling parameter N. mid To determine the aforementioned gain parameters The scaling factor determination module 435 can be based on the gain parameter. and quantization module 460 (which can correspond to Figure 1 The scaling factor SF is determined by the mutual information between the outputs of the quantizer circuit 160. In some embodiments, the scaling factor estimation circuit 120 may be implemented by at least one digital signal processing circuit or microcontroller circuit having sufficient processing power to perform the relevant operations of the above modules, but this application is not limited thereto.

[0076] The maximum similarity detection module 440 can correspond to Figure 1 The maximum similarity detection circuit 130 can generate the original log-likelihood ratio sequence OLR based on the payload PL during the payload period of the packet SP. The normalization module 445 can correspond to... Figure 1 The normalization circuit 142 can adjust the average channel gain value during the effective load period. The original log-likelihood ratio sequence OLR is normalized to produce the log-likelihood ratio sequence LR1. The scaling module 450 can correspond to... Figure 1 The multiplier circuit 144 can multiply the scaling parameter N during the effective load period. mid And the log-likelihood ratio sequence LR1, to generate the log-likelihood ratio sequence LR2. The scaling module 455 can correspond to... Figure 1 The scaling circuit 150 can multiply the scaling factor SF and the log-likelihood ratio sequence LR2 during the payload period to produce the log-likelihood ratio sequence LR3. The quantization module 460 can correspond to... Figure 1 The quantizer circuit 160 can quantize the log-likelihood ratio sequence LR3 during the payload period to generate quantized data QD. The decoder module 465 can correspond to... Figure 1 The channel decoder circuit 170 can decode the quantized data QD during the payload period to provide relevant information about the payload PL.

[0077] In some embodiments, Figure 4 The various modules shown can be implemented by one or more digital circuits. Alternatively, in other embodiments, Figure 4 The various modules shown can be implemented as at least one piece of software, and the software is executed via at least one digital signal processing circuit to realize the corresponding operation flow.

[0078] In summary, the MIMO OFDM communication system and its log-likelihood ratio scaling method provided in some embodiments of this invention can find a suitable scaling ratio during the packet preamble period using relevant information to reduce the log-likelihood ratio sequence. This significantly reduces overall system power consumption, thereby improving energy efficiency.

[0079] Although the embodiments of this case are described above, these embodiments are not intended to limit this case. Those skilled in the art can make changes to the technical features of this case based on the explicit or implicit content of this case. All such changes may fall within the scope of patent protection sought in this case. In other words, the scope of patent protection in this case shall be determined by the scope of the patent application in this specification.

[0080] [Symbol Explanation]

[0081] 100: Multiple-Input Multiple-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) Communication System

[0082] 110: Channel Gain Estimation Circuit

[0083] 120: Proportional Estimation Circuit

[0084] 130: Maximum Similarity Detection Circuit

[0085] 140: Scaling circuit

[0086] 142: Normalized Circuit

[0087] 144: Multiplier Circuit

[0088] 150: Scaling circuit

[0089] 160: Quantizer Circuit

[0090] 170: Channel Decoder Circuit

[0091] 300: Log-likelihood ratio scaling method

[0092] 400: Log-likelihood ratio scaling mechanism

[0093] 405: Channel Estimation and Smoothing Module

[0094] 410: Matrix Decomposition Module

[0095] 415: Frequency-by-Frequency Gain Calculation Module

[0096] 420: Average Gain Calculation Module

[0097] 425, 450, 455: Scaling modules

[0098] 430, 445: Normalization module

[0099] 435: Scaling ratio determines the module

[0100] 440: Maximum Similarity Detection Module

[0101] 460: Quantization Module

[0102] 465: Decoder Module

[0103] LR1, LR2, LR3: Log-likelihood ratio sequences

[0104] N mid Scaling parameters

[0105] OLR: Original log-likelihood ratio sequence; P1, P2: Probability mass function

[0106] PL: Payload

[0107] PS: Prefix code

[0108] QD: Quantitative Data

[0109] S210, S220, S230, S240, S250: Operation; S310, S320, S330, S340, S350: Operation; SF: Scaling ratio.

[0110] SP: Packet

[0111] K: Preset parameters Log-likelihood ratio to mean

[0112] H n Channel response

[0113] R n Triangular matrix

[0114] Channel gain Average channel gain Gain parameter.

Claims

1. A multiple-input multiple-output orthogonal frequency division multiplexing communication system, comprising: A channel gain estimation circuit is used to determine a channel gain of a corresponding subcarrier and an average channel gain value of the multiple subcarriers based on a preamble of the packet during a preamble of the packet, and to determine a log-likelihood average value based on the average channel gain value. A scaling estimation circuit is used to determine a scaling ratio during the preamble period based on the average channel gain value, the channel gain of the corresponding subcarrier, and a scaling parameter. A maximum similarity detection circuit is used to generate an original log-likelihood ratio sequence based on a payload of the packet during a payload period of the packet; A first scaling circuit is configured to adjust the original log-likelihood ratio sequence based on the average log-likelihood ratio and the scaling parameter during the effective load period to generate a first log-likelihood ratio sequence. A second scaling circuit is used to adjust the first log-likelihood ratio sequence according to the scaling ratio during the effective load period to generate a second log-likelihood ratio sequence. A quantizer circuit for quantizing the second log-likelihood ratio sequence during the effective load period to generate quantized data; and A single-channel decoder circuit is used to decode the quantized data during the payload period to obtain relevant information about the payload.

2. The multiple-input multiple-output orthogonal frequency division multiplexing communication system according to claim 1, wherein, The channel gain estimation circuit is used to determine a channel response of the corresponding subcarrier based on the preamble during the preamble period, perform a sorted QR decomposition based on the channel response to obtain a triangular matrix, determine the channel gain of the corresponding subcarrier based on the multiple diagonal elements of the triangular matrix, and determine the average channel gain value accordingly.

3. The multiple-input multiple-output orthogonal frequency division multiplexing communication system according to claim 1, wherein, The first scaling circuit includes: A normalization circuit is used to normalize the original log-likelihood ratio sequence based on the average log-likelihood ratio during the effective load period to generate a third log-likelihood ratio sequence; and A multiplier circuit is used to multiply the scaling parameter and the third log-likelihood ratio sequence during the effective load period to produce the second log-likelihood ratio sequence.

4. The multiple-input multiple-output orthogonal frequency division multiplexing communication system according to claim 1, wherein, The scaling parameter is determined based on the character length of the original log-likelihood ratio sequence.

5. The multiple-input multiple-output orthogonal frequency division multiplexing communication system according to claim 1, wherein, The scaling estimation circuit normalizes the average channel gain value based on the channel gain of the corresponding subcarrier, multiplies the normalized result by the scaling parameter to generate a gain parameter, and determines the scaling ratio based on a mutual information between the gain parameter and the output of the quantizer circuit.

6. The multiple-input multiple-output orthogonal frequency division multiplexing communication system according to claim 5, wherein, The scaling factor is used to give the mutual information a maximum value.

7. A log-likelihood ratio scaling method, executed via a multiple-input multiple-output orthogonal frequency division multiplexing communication system, the log-likelihood ratio scaling method comprising: During a preamble of a packet, a channel gain of a corresponding subcarrier and an average channel gain value of the multiple subcarriers are determined based on the preamble of the packet, and a log-likelihood average is determined based on the average channel gain value. During the preamble period, a scaling ratio is determined based on the average channel gain value, the channel gain of the corresponding subcarrier, and a scaling parameter. During a payload period of the packet, a sequence of original log-likelihood ratios is generated based on a payload of the packet. During the payload period, the original log-likelihood ratio sequence is adjusted according to the average log-likelihood ratio and the scaling parameter to generate a first log-likelihood ratio sequence; and During the payload period, the first log-likelihood ratio sequence is adjusted according to the scaling ratio to generate a second log-likelihood ratio sequence. The multiple-input multiple-output orthogonal frequency division multiplexing communication system quantizes and decodes the second log-likelihood ratio sequence to obtain relevant information about the payload.

8. The log-likelihood ratio scaling method according to claim 7, wherein, During the preamble period of the packet, the average channel gain value of multiple subcarriers is determined based on the preamble of the packet, and the average log-likelihood ratio is determined based on the average channel gain value, including: The preamble code determines the channel response of a corresponding subcarrier among the plurality of subcarriers; Perform a sorted QR decomposition based on the channel response to obtain a triangular matrix; as well as The channel gain of the corresponding subcarrier is determined by the multiple diagonal elements of the triangular matrix, and the average channel gain value is determined accordingly.

9. The log-likelihood ratio scaling method according to claim 7, wherein, The second log-likelihood ratio sequence is quantized via a quantizer circuit in the multiple-input multiple-output quadrature frequency division multiplexing communication system, and the scaling factor determined based on the average channel gain value during the preamble period includes: The average channel gain value is normalized according to the channel gain of the corresponding subcarrier, and the normalized result is multiplied by the scaling parameter to produce a gain parameter; and The scaling factor is determined based on the mutual information between the gain parameter and the output of the quantizer circuit.

10. The log-likelihood ratio scaling method according to claim 9, wherein, The scaling factor is used to give the mutual information a maximum value.

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