A multi-channel weighted gain equalizer for a distributed DC carrier communication system

Abstract

This invention proposes a multi-channel weighted gain equalizer for a distributed DC carrier communication system. The distributed DC carrier communication system includes n different DC carrier channels. The multi-channel weighted gain equalizer is added to the system, specifically by: before combining the signals from each DC carrier channel, weighting each signal with different weighting coefficients based on maximum ratio combining and channel frequency domain characteristics; and adding the multi-channel weighted gain equalizer after combining the signals. This equalizer outperforms traditional zero-breaking and minimum mean square error equalizers, and its performance improves with higher system signal-to-noise ratios. The more transmission channels the equalizer operates in, the greater the system gain, resulting in a lower bit error rate and higher system accuracy. It is also relatively easy to implement in hardware.

Description

Technical Field

[0001] This invention relates to a multi-channel weighted gain equalizer, and more particularly to a multi-channel weighted gain equalizer for a distributed DC carrier communication system. Background Technology

[0002] In distributed photovoltaic (PV) power generation communication systems, the transmission of information for monitoring, emergency response, and sudden warnings requires high precision to ensure the stability and security of the power generation system. Furthermore, because this type of power generation communication system is a multi-input single-output signal transmission system, the same signal is transmitted to the receiving end via different DC carrier channels and then combined and equalized. Traditional equalizers, such as zero-breaking and minimum mean square error equalizers, are completely inadequate to meet the system's requirements. Figure 1 The graph shows a comparison of bit error rates (BER) between a single power line carrier channel and three channels. It is clear from the graph that at a signal-to-noise ratio (SNR) of 15 dB, the single power line carrier channel system has a lower BER than the three-channel system. This conclusion also applies to minimum mean square error equalizers, such as... Figure 2 As shown.

[0003] The above results indicate that traditional equalizers have technical defects and are not suitable for the communication systems of distributed photovoltaic power plants. Summary of the Invention

[0004] Purpose of the invention: The technical problem to be solved by the present invention is to provide a multi-channel weighted gain equalizer for a distributed DC carrier communication system, which addresses the shortcomings of the prior art.

[0005] To address the aforementioned technical problems, this invention discloses a multi-channel weighted gain equalizer for a distributed DC carrier communication system. The distributed DC carrier communication system includes n different DC carrier channels. The multi-channel weighted gain equalizer, specifically comprising:

[0006] Before merging the signals in the DC carrier channel, each signal is weighted by different weighting coefficients according to the maximum ratio merging and channel frequency domain characteristics. After merging the signals, the multi-channel weighted gain equalizer is added.

[0007] Furthermore, the distributed DC carrier communication system described in step 1 specifically includes:

[0008] The distributed DC carrier communication system includes n different DC carrier channels. The input signal u, after passing through a binary phase-shift keying (BPSK) modulator, becomes signal X; signal X, after passing through an orthogonal frequency division multiplexing (OFDM) modulator, becomes signal x; signal x, after being superimposed with a cyclic prefix, enters each of the n different DC carrier channels, with frequency domain responses of H1, H2, ..., H..., respectively.n The signals in each channel are superimposed with different additive white Gaussian noise (AWGN), namely: W1, W2, ..., W n After passing through an Orthogonal Frequency Division Multiplexing (OFDM) demodulator and removing the cyclic prefix, the resulting signals are: Y1, Y2, ..., Y... n The above signals are combined and then passed through a binary phase shift keying (BPSK) demodulator to obtain the final output signal.

[0009] Furthermore, the specific method for adding a multi-channel weighted gain equalizer includes:

[0010] Before the signal combining, each signal is weighted by different coefficients based on maximum ratio combining and channel frequency domain characteristics. The weighting coefficients are: g1, g2, ..., g n The weighted signals are: R1, R2, ..., R n The above signals are added together to form a signal R; the signal R is then passed through the equalizer to obtain a signal. Ultimately, the above signals After passing through a binary phase shift keying (BPSK) demodulator, the final output signal is obtained.

[0011] Furthermore, the weighting coefficients are calculated as follows:

[0012]

[0013] Among them, g n S represents the weighting coefficient of the nth signal. n The maximum ratio combining weighting coefficient for the nth signal is given. is the multi-channel weighting coefficient of the nth signal.

[0014] Furthermore, the maximum ratio weighting coefficient is calculated as follows:

[0015]

[0016] in, Let S be the signal-to-noise ratio of the nth signal, and the above equation satisfies: S1 + S2 + ... + S n =1.

[0017] Furthermore, the signal-to-noise ratio of the nth signal is estimated using a second-order or fourth-order matrix method.

[0018] Furthermore, the multi-channel weighting coefficients are calculated as follows:

[0019] Based on channel estimation techniques, the estimated frequency domain responses of n channels are:

[0020] Calculate the conjugate matrix of the above frequency domain response estimates to obtain:

[0021] in, This refers to the multi-channel weighting coefficient of the nth signal.

[0022] Furthermore, the calculation method for the value of the multi-channel weighted gain equalizer is as follows:

[0023]

[0024] Wherein, G is the value of the multi-channel weighted gain equalizer.

[0025] Furthermore, in the distributed DC carrier communication system, after adding a multi-channel weighted gain equalizer, the signal input and output are represented as follows:

[0026]

[0027] Where X is the signal input, It is a signal output. That's the noise part.

[0028] Furthermore, the specific hardware implementation method of the multi-channel weighted gain equalizer includes:

[0029] The output signal is obtained by multiplying the weighting coefficients of the equalizer (calculated from the channel estimates and the signal-to-noise ratios of each channel) with the input signal, and then dividing the sum of the conjugate products of the channel estimates.

[0030] Each received signal first passes through a multiplier with a value equal to the maximum ratio combining weighted product and the multi-channel weighted product; then, the conjugate product of the estimated values ​​of each channel is used to perform an inverse estimation algorithm and is used as a multiplier to equalize the received signal.

[0031] Beneficial effects:

[0032] 1. This invention presents a novel equalizer designed using the maximum ratio combining technique based on multi-channel frequency response weighted gain (MRC). Its performance is superior to traditional zero-breaking and minimum mean square error equalizers. Simulation results show that the better the effect is in environments with a higher system signal-to-noise ratio.

[0033] 2. The more transmission channels the equalizer proposed in this invention is in, the greater the gain of the system, and consequently the lower the bit error rate and the higher the system accuracy.

[0034] 3. The hardware of this invention is relatively easy to implement. The gain of the output signal can be expressed mathematically as the output signal passing through a known amplifier. Attached Figure Description

[0035] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments, and the advantages of the present invention in the above and / or other aspects will become clearer.

[0036] Figure 1 This is a diagram showing the performance comparison between single-input and multi-input zero-breaking equalizers.

[0037] Figure 2 This is a diagram showing the performance comparison between single-input and multi-input methods for a minimum mean square error equalizer.

[0038] Figure 3 This is a schematic diagram of a system model that includes an equalizer.

[0039] Figure 4 This is a schematic diagram comparing the bit error rate and signal-to-noise ratio of the present invention with those of the prior art when the noise amplitude coefficient is 0.03.

[0040] Figure 5 This is a schematic diagram comparing the bit error rate and signal-to-noise ratio of the present invention with those of the prior art when the noise amplitude coefficient is 0.05.

[0041] Figure 6 This is a schematic diagram comparing the bit error rate and signal-to-noise ratio of the present invention with those of the prior art when the noise amplitude coefficient is 0.1. Detailed Implementation

[0042] Based on the characteristics of multi-channel systems, this invention proposes a novel equalizer designed using multi-channel frequency domain response characteristics in conjunction with maximum ratio combining technology, and applies it to the communication system of a distributed photovoltaic power station. This improves the accuracy of received signals and system performance to meet the needs of photovoltaic power station systems.

[0043] Maximum ratio combining (MRC) is widely used as the optimal solution for diversity combining techniques, offering better performance than selection combining and equal-gain combining. This technique involves applying varying degrees of gain coefficients to the input signals of different channels, with the specific coefficients related to the signal-to-noise ratio (SNR) ratios of the input signals across all channels. Furthermore, by combining the frequency domain response characteristics of different channels in a distributed photovoltaic power station communication system with MRC weighting coefficients, weighted gains are applied to the transmitted data of each channel, further reducing the impact of channel fading and noise on the system and resulting in better bit error rate characteristics.

[0044] The present invention proposes a multi-channel weighted gain equalizer for a distributed DC carrier communication system, the specific technical solution of which is as follows:

[0045] (1) Communication system model of distributed photovoltaic power station

[0046] like Figure 3 As shown, in the communication system of a distributed photovoltaic power station, n different channels are set with different transmission modes. The input information signal u becomes signal X after passing through a binary phase shift keying (BPSK) modulator.

[0047] After the above signal is modulated by orthogonal frequency division multiplexing (OFDM), the signal is x;

[0048] After being superimposed with a cyclic prefix, the above signals enter n different power line carrier channels, with frequency domain responses of H1, H2, ..., H1, respectively. n And add n different additive white Gaussian noise (AWGN), i.e., W1, W2, ..., W n ;

[0049] After OFDM demodulation, each signal is weighted by different coefficients g1, g2, ..., g n (This weighting coefficient is related to the maximum ratio combining and the channel frequency domain characteristics), and then they are added together;

[0050] The combined signal R is then passed through an equalizer (G) to obtain the signal. Finally, the above signal is demodulated by a (BPSK) demodulator to recover the output signal.

[0051] (2) Maximum ratio combining gain

[0052] For maximum ratio combining, finding appropriate weights for gain is crucial. For multi-channel maximum ratio combining, the weighting coefficients for each channel (S1:S2:...:S...) are also important. n The signal-to-noise ratio (SNR) of each channel before merging is determined according to equation (1):

[0053]

[0054] To facilitate hardware implementation, this invention employs a second-order and fourth-order matrix method for estimating the signal-to-noise ratio of each signal. The second-order matrix of the i-th received signal can be expressed as equation (2):

[0055]

[0056] A fourth-order matrix can be represented as equation (3):

[0057]

[0058] Where Y i (m) represents the m-th output signal of the i-th channel. *Represented as a conjugate matrix, Let be the square of the amplitude value of the i-th signal. Let be the variance of the additive white Gaussian noise of the i-th signal. The signal-to-noise ratio of this signal can be expressed as equation (4):

[0059]

[0060] Combining equations (2), (3), and (4), we can obtain the estimated value of the signal-to-noise ratio as shown in equation (5):

[0061]

[0062] And according to Equation (1), the weighting coefficients for each path can be obtained.

[0063] In practical systems, the second-order and fourth-order matrices can be calculated from the average value of the received signals. The estimated value of the second-order and fourth-order moments of the i-th signal can be expressed as:

[0064]

[0065]

[0066] Where M is the symbol length of the signal, and m = 1, 2, ..., M.

[0067] (3) Multi-channel weighting

[0068] This invention derives frequency domain response estimates for n channels based on channel estimation techniques (such as preamble detection and pilot interpolation). Add the conjugate matrix of this estimate to each output signal. As weighting coefficients in a multi-channel system, the output signal of each channel before summing all signals is:

[0069]

[0070]

[0071] ...

[0072]

[0073] R i Let Y be the output signal of the i-th channel (i = 1, 2, ..., n). i Y is the output signal of the i-th demodulator. i =X i H i +W i X iThe original signal after passing through the modulator, since multiple channels share a unified input, can be directly represented by X. H i W represents the channel frequency domain response of the i-th path. i It is Gaussian white noise in the i-th path.

[0074] After combining the output signals from each channel, the equalizer value is obtained by summing the characteristics of the entire channel based on the characteristics of each channel, as shown in equation (11).

[0075]

[0076] The integrated signal output by the equalizer for:

[0077]

[0078] Organizing can yield

[0079]

[0080] In equation (11), Approaching a certain value, equation (11) can be written as:

[0081]

[0082] Output signal It equals the input signal X plus the noise component. The proportion of each noise source before combining depends on the gain coefficient (S) of the maximum ratio combining. i (And because in equation (14), both the numerator and denominator have conjugate matrix factors of multi-channel frequency domain response) Therefore, the proportion of noise mainly depends on (S) i Furthermore, as shown in equation (1), the higher the single-channel signal-to-noise ratio, the larger the maximum ratio combining gain coefficient, and the smaller the noise of that channel. Therefore, through this weighted gain equalizer, the influence of noise on the original signal is minimized. Thus, better performance can be obtained.

[0083] In terms of hardware implementation, the weighting coefficients of the equalizer of this invention can be calculated based on channel estimation and the signal-to-noise ratio coefficients of each channel, and the corresponding hardware functions can be realized by performing a corresponding multiplier on the received signal at the receiving end.

[0084] Specifically, the output signal is obtained by multiplying the weighting coefficients of the equalizer (calculated from the channel estimates and the signal-to-noise ratios of each channel) with the input signal, and then dividing the sum of the conjugate products of the channel estimates. The hardware design requires that each received signal first pass through a multiplier containing the maximum ratio combining weighted and multi-channel weighted products. Secondly, the reciprocal estimation algorithm is applied to the sum of the conjugate products of the channel estimates, and this result is used as a multiplier to equalize the received signal. This estimation algorithm is the method used in conventional hardware systems to find the reciprocal.

[0085] The key point of this invention is a novel equalizer designed based on the characteristics of a wired multi-channel, multi-input, single-output system formed during the transmission process from multiple transmit / receive combiner boxes to the inverter in a distributed photovoltaic power station. This system features multiple channels simultaneously transmitting the same information signal. Given the stringent requirements for monitoring sudden events during photovoltaic power station communication and the extremely high demands for real-time and accurate handling of such events, traditional equalizers, especially in multi-channel systems, exhibit poor performance due to their weak signal processing capabilities. This invention addresses this issue by designing a novel weighted equalizer technology based on the maximum ratio combining technique (MRC) for multi-channel frequency response weighted gain coordination in concurrent systems. Specifically, this technique utilizes the frequency domain responses of conjugate channels obtained from the multi-channel characteristics and the output signal of each channel to calculate the corresponding signal-to-noise ratio. The calculated maximum ratio combining gain coefficient of each output signal is then used as the weighting gain for a single output signal. After combining all output signals, equalization is performed using the sum of the products of the conjugate matrices of the frequency domain responses of all channels. This significantly improves the gain performance compared to single-channel equalizers. Furthermore, if a certain frequency domain response value becomes extremely skewed (maximum or minimum), the channel fading and noise ratio under that channel will also be adjusted accordingly, with the relationship being inversely proportional. This makes the system generally present a smooth state, reduces the system's suddenness and randomness, increases the accuracy and real-time performance of the received signal, improves the system's stability and security, and provides the greatest possible communication guarantee for the distributed photovoltaic power generation system.

[0086] Based on channel characteristics, the system model simulates zero-breaking equalizers and minimum mean square error equalizers as comparison objects to test the performance of multi-channel weighted equalizers under maximum ratio combining. To distinguish noise differences, the simulation program establishes three Gaussian distributed random noises under three channels respectively. Furthermore, to observe the performance of different equalizers under different noise influences, this invention establishes three Gaussian white noises with different amplitude coefficients on the simulation model for comparison. The simulation results are shown in the following three figures.

[0087] in, Figure 4 This is a comparison of the BER (Bit Error Rate) and SNR (Signal-Noise Ratio) (dB) of the three equalizers mentioned above when the noise amplitude coefficient is 0.03.

[0088] Figure 5 This is a comparison of the BER and SNR (dB) of the three equalizers mentioned above when the noise amplitude coefficient is 0.05.

[0089] Figure 6 This is a comparison of the BER and SNR (dB) of the three equalizers mentioned above when the noise amplitude coefficient is 0.1.

[0090] All three results show that, at the same signal-to-noise ratio (SNR), the bit error rate of the multi-channel weighted equalizer is lower than that of the other two equalizers, and the advantage increases with the increase of SNR. Furthermore, comparing the three figures reveals that the performance of the multi-channel weighted equalizer improves as the noise amplitude increases.

[0091] In its specific implementation, this application provides a computer storage medium and a corresponding data processing unit. The computer storage medium is capable of storing a computer program, which, when executed by the data processing unit, can run the invention's content regarding a multi-channel weighted gain equalizer for a distributed DC carrier communication system, as well as some or all of the steps in various embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0092] Those skilled in the art will clearly understand that the technical solutions in the embodiments of the present invention can be implemented using computer programs and their corresponding general-purpose hardware platforms. Based on this understanding, the technical solutions in the embodiments of the present invention, or the parts that contribute to the prior art, can be embodied in the form of computer programs, i.e., software products. These computer program software products can be stored in a storage medium and include several instructions to cause a device containing a data processing unit (which may be a personal computer, server, microcontroller, MUU, or network device, etc.) to execute the methods described in various embodiments or certain parts of the embodiments of the present invention.

[0093] This invention provides a concept and method for a multi-channel weighted gain equalizer in a distributed DC carrier communication system. Many methods and approaches exist for implementing this technical solution; the above description is merely a preferred embodiment of the invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention. All components not explicitly stated in this embodiment can be implemented using existing technologies.

Claims

1. A multi-channel weighted gain equalizer for a distributed DC carrier communication system, wherein the distributed DC carrier communication system includes n different DC carrier channels, characterized in that, In the distributed DC carrier communication system, a multi-channel weighted gain equalizer is added, specifically including: Before merging the signals in the DC carrier channel, each signal is weighted by different weighting coefficients according to the maximum ratio merging and channel frequency domain characteristics. After merging the signals, the multi-channel weighted gain equalizer is added. The weighting coefficients are calculated as follows: Among them, g n S represents the weighting coefficient of the nth signal. n The maximum ratio combining weighting coefficient for the nth signal is given. The multi-channel weighting coefficients are the values ​​for the nth signal. The multi-channel weighting coefficients are calculated as follows: Based on channel estimation techniques, the estimated frequency domain responses of n channels are: Calculate the conjugate matrix of the above frequency domain response estimates to obtain: in, That is, the multi-channel weighting coefficient of the nth signal; The calculation method for the value of the multi-channel weighted gain equalizer is as follows: Wherein, G is the value of the multi-channel weighted gain equalizer; The distributed DC carrier communication system described in step 1 specifically includes: The distributed DC carrier communication system includes n different DC carrier channels. The input signal u, after passing through a binary phase-shift keying (BPSK) modulator, becomes signal X; signal X, after passing through an orthogonal frequency division multiplexing (OFDM) modulator, becomes signal x; signal x, after being superimposed with a cyclic prefix, enters each of the n different DC carrier channels, with frequency domain responses of H1, H2, ..., H..., respectively. n The signals in each channel are superimposed with different additive white Gaussian noise (AWGN), namely: W1, W2, ..., W n After passing through an Orthogonal Frequency Division Multiplexing (OFDM) demodulator and removing the cyclic prefix, the resulting signals are: Y1, Y2, ..., Y... n The above signals are combined and then passed through a binary phase shift keying (BPSK) demodulator to obtain the final output signal.

2. The multi-channel weighted gain equalizer for a distributed DC carrier communication system according to claim 1, characterized in that, The specific method for adding a multi-channel weighted gain equalizer includes: Before the signal combining, each signal is weighted by different coefficients based on maximum ratio combining and channel frequency domain characteristics. The weighting coefficients are: g1, g2, ..., g n The weighted signals are: R1, R2, ..., R n The above signals are added together to form a signal R; the signal R is then passed through the equalizer to obtain a signal. Ultimately, the above signals After passing through the binary phase shift keying (BPSK) demodulator, the final output signal is obtained.

3. The multi-channel weighted gain equalizer for a distributed DC carrier communication system according to claim 1, characterized in that, The maximum ratio weighting coefficient is calculated as follows: in, Let S be the signal-to-noise ratio of the nth signal, and the above equation satisfies: S1 + S2 + ... + S n =1.

4. The multi-channel weighted gain equalizer for a distributed DC carrier communication system according to claim 1, characterized in that, The signal-to-noise ratio of the nth signal is estimated using a second-order or fourth-order matrix method.

5. A multi-channel weighted gain equalizer for a distributed DC carrier communication system according to claim 1, characterized in that, In the distributed DC carrier communication system, after adding a multi-channel weighted gain equalizer, the signal input and output are represented as follows: Where X is the signal input, It is a signal output. That's the noise part.

6. A multi-channel weighted gain equalizer for a distributed DC carrier communication system according to claim 1, characterized in that, The specific hardware implementation method of the multi-channel weighted gain equalizer includes: The output signal is obtained by multiplying the weighting coefficients of the equalizer (calculated from the channel estimates and the signal-to-noise ratios of each channel) with the input signal, and then dividing the sum of the conjugate products of the channel estimates. Each received signal first passes through a multiplier with a value equal to the maximum ratio combining weighted product and the multi-channel weighted product; then, the conjugate product of the estimated values ​​of each channel is used to perform an inverse estimation algorithm and is used as a multiplier to equalize the received signal.

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