JP7543166B2 - Wireless Transmission System - Google Patents

Description

The present invention relates to a wireless transmission system that transmits data wirelessly from a transmitting device to a receiving device.

Broadcasting stations use a wireless transmission device called an FPU (Field Pickup Unit) to wirelessly relay audio and video from the site to the broadcasting station. FPUs are operated in a variety of propagation environments, including good line-of-sight environments with no obstructions between the transmitter and receiver, and poor environments where there is a lot of reflected waves outside the line of sight. FPUs are also often used for live broadcasts, and since any image breakdown caused by a transmission error would affect television viewing, transmission errors must not occur. For this reason, the transmission margin up to the transmission error must be accurately understood, and a certain margin must be secured in order to withstand sudden propagation path fluctuations such as fading, and the system is operated accordingly.

This transmission margin is calculated based on the received signal strength indicator (RSSI) and modulation error ratio (MER). MER is generally an index of modulation accuracy of a transmission signal, but is also often used to indicate the reception accuracy of a signal received via a propagation path. MER is calculated using the following formula (1). That is, if the received constellation after waveform equalization at the receiving unit is R(ω,t) (where ω represents frequency and t represents time), and the result determined based on the modulation method is assumed to be an ideal transmission signal, the mean square error between the received constellation and the determination result is the MER.

ここで、￣は平均を示し、ＤＥＣ［ ］は所定の変調方式による判定関数を示す。

Here, denotes the average, and DEC[ ] denotes a decision function according to a predetermined modulation method.

The numerical values of the indices used in wireless communication are in a wide range, such as ^10-10 to ^103. For this reason, the units are often dB (or dBm) to make numerical expressions easier to handle, and the units of the above RSSI and MER are also expressed in dBm and dB. In this way, the unit dB is easy to handle in operation, and the unit of the transmission margin is also dB.

Various inventions have been proposed so far regarding the calculation of the transmission margin. For example, Patent Document 1 discloses an invention that calculates the log-likelihood ratio for the coded bits of the error correction coding from the received signal, calculates the average mutual information for the log-likelihood ratio for the coded bits, and calculates the transmission margin from the average mutual information and the decoder input mutual information or demodulated product output mutual information that satisfies the required bit error rate.

WO 2016/186000

ARIB STD-B33 1.3 Edition Portable OFDM digital wireless transmission system for transmitting television broadcast program material ARIB STD-B71 Version 1.0 Portable microwave OFDM digital wireless transmission system for transmitting ultra-high definition television broadcasting program material

The above-mentioned transmission margin may be subject to error depending on the propagation path environment, making it difficult to calculate a highly accurate transmission margin. The margin error will be described in detail below.
If the propagation path is a completely line-of-sight environment, the main cause of transmission degradation is thermal noise generated by a low noise amplifier (Low Noise Amplifier) provided in the receiving section. Such an environment is called AWGN (Additive White Gaussian Noise). In an AWGN environment, as shown in the following formula (2), there is a one-to-one relationship between RSSI and MER and the BER (Bit Error Rate) after decoding. Therefore, by observing RSSI and MER, the BER characteristic can be uniquely estimated.

ここで、ｆｕｎｃ１（ ）はＲＳＳＩとＢＥＲを対応付ける関数であり、ｆｕｎｃ２（ ）はＭＥＲとＢＥＲを対応付ける関数である。

Here, func1( ) is a function that associates RSSI with BER, and func2( ) is a function that associates MER with BER.

However, in non-line-of-sight transmission as described above, reflected waves have a significant effect on the transmission characteristics. For example, when reflected waves are mixed in, frequency selective fading occurs, which causes a dip in the frequency band. The depth of this dip varies depending on the level of the reflected waves. When the level of the reflected waves becomes the same as that of the direct waves, there exists a frequency where the direct waves and the reflected waves are completely offset, and this frequency becomes a deep dip. This dip significantly deteriorates the demodulation characteristics of the receiver, and the amount of deterioration depends greatly on the depth of the dip.
As described above, in a reflected wave environment, it is difficult to accurately estimate the BER characteristics using a function such as that shown in equation (2), and errors occur in the transmission margin in conventional FPUs that use RSSI or MER.

Incidentally, in conventional FPUs as shown in Non-Patent Document 1, convolutional codes are used in the error correction method. As shown in Fig. 2, the convolutional code shows a gentle curve of CNR vs. BER characteristics, and it is known that if the BER after convolutional decoding is ^10-4 or less, the following RS decoding will make it pseudo-error-free. Therefore, the transmission margin with many errors using RSSI or MER is used as a reference value, and the BER after convolutional decoding is used to accurately grasp the transmission margin until transmission failure.

However, in the new FPU standard shown in Non-Patent Document 2, LDPC (Low Density Parity Check) is used as the error correction code. As shown in Figure 2, LDPC has a steep BER characteristic curve, and the system remains error-free until it is on the verge of a transmission failure, at which point it suddenly falls into a transmission failure. Thus, with advanced error correction methods such as LDPC and turbo codes, there is the problem that it is difficult to operate while monitoring the BER characteristics.

The present invention was made in consideration of the above-mentioned conventional circumstances, and aims to provide a wireless transmission system that can calculate a transmission margin with high accuracy.

In order to achieve the above object, in the present invention, a wireless transmission system is configured as follows.
That is, in a wireless transmission system in which data is transmitted wirelessly from a transmitting device to a receiving device, the receiving device pre-stores a correspondence between the reflected wave intensity and characteristic data of the transmission margin, calculates the reflected wave intensity based on the result of the transmission path estimation, and calculates the transmission margin based on the characteristic data corresponding to the calculated reflected wave intensity.

Here, the characteristic data of the transmission margin is data showing the relationship between the transmission margin and any one of the indices of the received signal strength, the modulation error ratio, and the mutual information, and the receiving device may calculate the transmission margin by calculating any one of the indices of the received signal strength, the modulation error ratio, and the mutual information, and referring to the calculated indices and the characteristic data corresponding to the calculated reflected wave intensity.

The receiving device may also calculate the reflected wave intensity in the time domain, or the reflected wave intensity in the frequency domain.

The present invention provides a wireless transmission system that can calculate a transmission margin with high accuracy.

1 is a diagram illustrating an example of the configuration of a wireless transmission system according to an embodiment of the present invention. FIG. 1 is a diagram showing the CNR vs. BER characteristics of convolutional codes and LDPC. FIG. 1 is a diagram showing the characteristics of MER versus transmission margin. FIG. 13 is a diagram showing the characteristics of mutual information MI versus margin. FIG. 13 is a diagram illustrating an example of a delay profile.

An embodiment of the present invention will be described with reference to the drawings.
1 shows an example of the configuration of a wireless transmission system according to an embodiment of the present invention. The wireless transmission system of this example is implemented as an FPU including a transmitting device and a receiving device. The transmitting device (FPU transmitting unit) has an error correction code unit 1, a modulation unit 2, and a transmitting high frequency unit 3. The receiving device (FPU receiving unit) has a receiving high frequency unit 4, an RSSI calculation unit 5, a transmission path estimation unit 6, a reflected wave intensity calculation unit 7, a demodulation unit 8, a MER calculation unit 9, an error correction decoding unit 10, an MI calculation unit 11, a margin calculation unit 12, and a reception support function unit 13.

The FPU mainly transmits video and audio. The encoded video and audio data is input to the error correction coding unit 1 in the FPU transmission unit. The error correction coding unit 1 performs error correction coding processing such as convolutional coding, LDPC, and turbo coding. The error correction coded data is input to the modulation unit 2. The modulation unit 2 performs modulation processing such as single carrier and OFDM to generate a modulated signal. The modulated signal is then converted to a carrier frequency by the transmission high frequency unit 3 and sent out as radio waves from the antenna.

The radio waves sent from the FPU transmitter propagate towards the receiving antenna of the FPU receiver. At this time, the radio waves received by the receiving antenna may contain a direct wave component that reaches the receiving antenna directly, and a reflected wave component that is reflected off a building or other object and travels a different propagation path from the direct wave component, reaching the receiving antenna with a delay time due to the path difference. As mentioned above, in non-line-of-sight environments, the proportion of reflected wave components is often high.

The signal that reaches the receiving antenna via such a propagation path is converted from the carrier frequency to an intermediate frequency by the receiving high frequency unit 4. In addition, the AGC (Automatic Gain Controller) provided in the receiving high frequency unit 4 measures the received power RSSI and adjusts the amplification so that the signal power is appropriate. The RSSI calculation unit 5 calculates this received power as RSSI. Generally, dBm is used as the unit of RSSI.

The received signal output from the receiving high frequency unit 4 is input to the transmission path estimation unit 6 and used to estimate the transmission path characteristics between the transmitter and the receiver. In OFDM, the transmission path characteristics can be estimated by interpolating pilot carriers inserted in the signal band in the frequency and time directions, or by calculating the cross-correlation between a known preamble signal added to the beginning of the frame and the received preamble. The transmission path characteristics differ depending on time and frequency. Here, the transmission path estimation result is defined as H^(ω,t). Here, ^ (hat) means estimation, ω represents frequency, and t represents time.

The transmission channel estimation result H^(ω,t) is input to the reflected wave intensity calculation unit 7 and the demodulation unit 8. The reflected wave intensity calculation unit 7 will be described later. The demodulation unit 8 performs demodulation processing to estimate the transmission signal based on the received signal X(ω,t) and the transmission channel estimation result H^(ω,t). In the demodulation processing, the transmission signal is estimated using the ZF (Zero Forcing) method or the MMSE (Minimum Mean Square Error) method, and the transmission code is estimated from the estimation result. For example, the ZF method calculates the reception constellation R(ω,t) from the received signal X(ω,t) and the estimated transmission channel characteristic H^(ω,t) as shown in the following equation (3).

Besides ZF and MMSE, there is also the MLD (Maximum Lilelihood Detection) method. As shown in the following formulas (4) and (5), the MLD method detects a received signal replica X^min(ω,t) that minimizes the square error L(ω,t) between the received signal X(ω,t) and _a received replica X^ _i (ω,t) calculated from an estimated transmission channel characteristic H^(ω,t), and performs demodulation based on the result.

The demodulator 8 estimates the transmission code using equation (3) or equation (5). As an estimation result of the transmission code, LLR (Log Likelihood Ratio), which indicates the likelihood that the received signal is code "0" or code "1", is often used. The larger the absolute value of the LLR, the more likely it is.

The LLR calculated by the demodulation unit 8 is input to the error correction decoding unit 10. The error correction decoding unit 10 corrects the code errors that occurred in the propagation path from the input LLR using an error correction decoding method corresponding to the error correction coding unit 1. The error correction decoding unit 10 outputs the reproduced audio and video code data. In this way, wireless transmission by the FPU is realized.

Next, a description will be given of the MER calculation unit 9 and the MI calculation unit 11. The MER calculation unit 9 and the MI calculation unit 11 both calculate an index indicating reception characteristics and provide it to the margin calculation unit 12.
The MER calculation unit 9 calculates the MER by the calculation formula shown in formula (1) using the reception constellation R(ω,t). Alternatively, the MER may be calculated by the calculation formula shown in formula (6) below using the minimum reception replica distance L(ω,t) of formula (4).

ＭＥＲは、受信ＣＮＲに近い値となるため、伝送マージンを算出するための指標として用いられている。

Since the MER is close to the received CNR, it is used as an index for calculating the transmission margin.

Next, the MI calculation unit 11 uses the LLR input to the error correction decoding unit 10 to calculate the mutual information MI (Mutual Information) according to the following formula (7).

The mutual information MI calculated based on the LLR indicates the reliability of the demodulated received signal, and is an index expressed in the range of "0" to "1." A mutual information MI of "0" indicates a state in which there are many code errors and no information is obtained from the received signal, while a value of "1" indicates a state in which there are no code errors at all. The mutual information MI is closely related to the decoding characteristics of error-correcting codes, and the required mutual information to become error-free can be calculated by using an analytical method called the EXIT (EXtrinsic Information Transfer) chart.

In this way, there is a one-to-one relationship between the mutual information MI and the BER, and this relationship coincides with a high degree of accuracy, so that it can be used as an index for calculating the transmission margin.
The RSSI calculated by the RSSI calculation unit 5, the MER calculated by the MER calculation unit 9, and the mutual information MI calculated by the MI calculation unit 11 described above are all indices indicating reception characteristics, and are input to the margin calculation unit 12 and used to calculate the transmission margin. However, as described above, when these indices are used as margins in dB units, the slopes differ between the AWGN environment and the cluttered wave environment.

Figure 3 shows the MER versus transmission margin characteristics. The required MER for the margin to become "0" differs between an AWGN environment with no reflected waves and a reflected wave environment, and the slope also differs.

As in Figure 3, Figure 4 shows the characteristics of mutual information MI versus margin. In the case of mutual information MI, the margin is "0" at the required mutual information regardless of whether or not there is a reflected wave. However, as the reflected wave strength increases, the slope becomes steeper. However, the required mutual information differs depending on the characteristics of the error correcting code.

As shown in Figures 3 and 4, the value at which the margin becomes "0" and the slope of the curve for the margin vary depending on the intensity of the reflected wave. Therefore, in the system of this example, the margin curve (Figures 3 and 4) to be used for margin calculation is selected based on the reflected wave intensity calculated by the reflected wave intensity calculation unit 7. The reflected wave intensity calculation unit 7 is described below.

The reflected wave intensity calculation unit 7 receives the transmission path characteristic H^(ω,t) estimated by the transmission path estimation unit 6. The basic concept of calculating the reflected wave intensity MS (Multipath Strength) can be expressed as in the following equation (8). That is, if the greatest signal power is the direct wave component P _D and the total power P _R of the other reflected wave components is the reflected wave power, the ratio of the direct wave component P _D to the total power P _R of the reflected wave components becomes the reflected wave intensity MS.

ここで、Ｐ_Riは、ｉ番目の反射波電力を示している。

Here, P _Ri indicates the power of the i-th reflected wave.

Regarding the method of calculating the direct wave component P _D and the reflected wave component P _R , two methods of calculation in the time domain and in the frequency domain will be mentioned, but other methods may also be used.
First, the calculation method of the time domain will be explained. Figure 5 shows a delay profile. The delay profile shows the relationship between signal power and delay time. The direct wave component P _D in the time domain is the largest signal power component. The reflected wave component P _R in the time domain is the sum of signal powers that exceed a threshold value for distinguishing from disturbance components due to noise. However, the time resolution at which paths can be separated in the time domain is about 2 to 4 times the reciprocal of the bandwidth, and there is a problem in that it is difficult to separate reflected waves with delay times shorter than that.

Next, a calculation method in the frequency domain will be described. Here, for simplicity of explanation, time t will be omitted. The direct wave component P _D in the frequency domain is the root mean square of the estimated transmission path characteristic H^(ω) as shown in the following equation (9).

Moreover, the reflected wave component P _R in the frequency domain is the square root of the mean square of the value obtained by subtracting the direct wave component P _D from the square of the transmission path characteristic H^(ω), as shown in the following equation (10). In equation (9), the mean square of the transmission path characteristic H^(ω) is calculated as the direct wave component P _D , and in equation (10), the standard deviation is calculated as the reflected wave component P _R.

When calculating in the frequency domain, the reflected wave intensity MS can be calculated with high accuracy even when reflected waves with short delays are mixed in as compared to the time domain.
The reflected wave intensity MS is calculated by the above processing, and the margin characteristic for MS as shown in FIG. 3 and FIG. 4 is selected, and the transmission margin is calculated from MER and MI.

The margin characteristics as shown in Figures 3 and 4 can be calculated offline, such as by simulation before the system is put into operation, and the data of the calculation results is set in the memory table of the receiving device. The memory table stores characteristic data such as the margin characteristics for MER (Figure 3) and the margin characteristics for MI (Figure 4) in association with the value of the reflected wave intensity MS, for example. Therefore, when the system is in operation, the transmission margin can be easily calculated by referring to the memory table based on MER and MS, or MI and MS. Note that while the above explanation refers to MER and MI, the same applies to the RSSI obtained by the RSSI calculation unit 5. Furthermore, although the above explanation uses dB as the unit of margin, units other than dB may be used.

The transmission margin calculated by the margin calculation unit 12 is input to the reception support function unit 13. The reception support function unit 13 issues an alarm to the operator before a transmission failure occurs according to the input transmission margin. The alarm may be issued in the form of visual or auditory information, or electronic information such as switching the transmission path if the margin falls below a specified margin.

As described above, in the wireless transmission system of this example, the receiving device (FPU receiving unit) is configured to previously associate and store the reflected wave intensity with the characteristic data of the transmission margin (Figures 3 and 4), and the reflected wave intensity calculation unit 7 calculates the reflected wave intensity MS based on the result of the transmission path estimation, and the margin calculation unit 12 calculates the transmission margin based on the characteristic data corresponding to the calculated reflected wave intensity MS. In this way, by calculating the transmission margin based on the characteristic data corresponding to the reflected wave intensity, it is possible to calculate a highly accurate transmission margin. Therefore, even if the BER characteristic of the error correction is steep, it is possible to accurately grasp the transmission margin until transmission failure without referring to the BER characteristic.

Here, data showing the relationship between the transmission margin and indexes such as RSSI, MER, and MI can be used as the characteristic data of the transmission margin. Note that in addition to RSSI, MER, and MI, other indexes whose relationship with the transmission margin changes depending on the reflected wave intensity may be used, or a combination of these may be used. Also, the reflected wave intensity may be calculated in the time domain or in the frequency domain. Also, the reflected wave intensity may be calculated using other methods, or a combination of these may be used.

The present invention has been described above based on one embodiment, but it goes without saying that the present invention is not limited to the configuration described here and can be widely applied to systems with other configurations.
Furthermore, the present invention can also be provided as, for example, a method including technical procedures related to the above-mentioned processing, a program for causing a processor to execute the above-mentioned processing, or a storage medium for storing such a program in a computer-readable manner.

The scope of the present invention is not limited to the exemplary embodiments shown and described, but includes all embodiments that achieve equivalent effects to those intended by the present invention. Furthermore, the scope of the present invention can be defined by any desired combination of specific features among all the respective features disclosed.

The present invention can be used in a wireless transmission system that transmits data wirelessly from a transmitting device to a receiving device.

1: Error correction coding unit, 2: Modulation unit, 3: Transmission high frequency unit, 4: Reception high frequency unit, 5: RSSI calculation unit, 6: Transmission path estimation unit, 7: Reflected wave intensity calculation unit, 8: Demodulation unit, 9: MER calculation unit, 10: Error correction decoding unit, 11: MI calculation unit, 12: Margin calculation unit, 13: Reception support function unit

Claims (5)

In a wireless transmission system for wirelessly transmitting data from a transmitting device to a receiving device,
The receiving device pre -stores characteristic data that associates, for each of a plurality of different reflected wave intensities, a change in one of the indices of received signal strength, modulation error ratio, or mutual information in the environment in which the reflected wave intensity is obtained with a change in transmission margin, and calculates the reflected wave intensity based on the result of transmission path estimation , selects characteristic data corresponding to the calculated reflected wave intensity, calculates one of the indices, and calculates the transmission margin by comparing it with the selected characteristic data, characterized in that the wireless transmission system. 2. The wireless transmission system according to claim 1,
The characteristic data is data in which a change in mutual information and a change in transmission margin in an environment in which a corresponding reflected wave intensity is obtained are associated with each other ,
The wireless transmission system is characterized in that the receiving device calculates mutual information , and calculates a transmission margin by comparing the calculated mutual information with characteristic data corresponding to the calculated reflected wave intensity. 3. The wireless transmission system according to claim 1,
The wireless transmission system is characterized in that the receiving device calculates the reflected wave intensity in the time domain. 3. The wireless transmission system according to claim 1,
The wireless transmission system is characterized in that the receiving device calculates the reflected wave intensity in the frequency domain. A wireless transmission method for wirelessly transmitting data from a transmitting device to a receiving device, comprising:
The wireless transmission method is characterized in that the receiving device pre-stores characteristic data that associates, for each of a plurality of different reflected wave intensities, a change in one of the indices, namely, received signal strength, modulation error ratio, or mutual information, in the environment in which the reflected wave intensity is obtained, with a change in the transmission margin, calculates the reflected wave intensity based on the result of transmission path estimation , selects characteristic data corresponding to the calculated reflected wave intensity, and calculates one of the indices and compares it against the selected characteristic data to calculate the transmission margin.

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