JP2022096722A - Interference power distribution estimation method, interference source occupancy rate estimation method, and interference power distribution estimation device - Google Patents

Abstract

To provide an interference power distribution estimation method for accurately estimating the channel occupancy rate by an interference source, an interference source occupancy rate estimation method, and an interference power distribution estimation device.SOLUTION: In an interference power distribution estimation method that receives radio waves including spread-spectrum-modulated signals for each symbol belonging to a predetermined set and estimates the distribution of interference power from the received signal, the symbol is demodulated from the received signal, a spread spectrum modulated signal is reproduced for each packet using symbol belonging to a set other than the demodulated symbol, an interference power estimation value is output on the basis of a correlation calculation between the reproduced spread spectrum modulated signal and the received signal, the interference power distribution is aggregated from the interference power estimated values related to a plurality of packets, and an error check is performed for each packet. For a packet having an error, when the interference power estimation value of the packet does not exceed a predetermined threshold value, the interference power estimation value is excluded from the target for aggregating the interference power distribution.SELECTED DRAWING: Figure 5

Description

The present disclosure discloses an interference power distribution estimation method and an interference source occupancy estimation method for determining the necessity of frequency sharing or optimizing the diffusion rate of a spectrum in an environment in which the same frequency band is used by a plurality of standards. The present invention relates to an interference power distribution estimation device.

In recent years, LPWA (Low Power Wide Area) has been attracting attention as being suitable for utilization of IoT (Internet of Things) (Non-Patent Document 1). LPWA is a communication standard that enables long-distance communication with low power consumption. Even in an environment where it is difficult to secure a power source, it can be used for a long time with a battery, so it is often used to meet the needs of IoT.

As a feature of LPWA, wireless communication systems classified into these have been independently proposed (for example, LoRa, SIGFOX, Wi-SUN). Therefore, there is a possibility that interference (CCI: Co-Channel Interference) may be received from another wireless communication system that uses the same frequency. LoRa, which is a typical example of LPWA, uses chirp modulation, which is a kind of spread spectrum technique (Patent Document 1). In this method, the resistance to interference power can be improved by increasing the diffusion rate of the signal. For example, when the frequency band of interference from another wireless communication system is relatively narrow, there is a method of removing the interference wave by a frequency mask (Patent Document 2).

Further, a method has been proposed in which the chirp pattern is reproduced from the demodulated symbol by utilizing the above-mentioned characteristics of the chirp modulation, and the interference power is estimated by comparing this with the frequency spectrum of the received signal (Non-Patent Document 2). ).

Japanese Unexamined Patent Publication No. 2019-193049 Japanese Unexamined Patent Publication No. 2009-58308

Ministry of Internal Affairs and Communications, "Trends in wireless systems related to LPWA", March 7, 2018 (https://www.somu.go.jp/main_content/0005433715.pdf) Takeshi Kobayashi, Osamu Taku, Koichi Adachi, Mai Ota, Takeo Fujii, "Distribution estimation method of noise power and interference power using chirp demodulation", Institute of Electronics, Information and Communication Engineers Society Conference, B-17-4, 2020

However, when the interference power is large and the SIR is extremely deteriorated, a bit error occurs in the demodulation symbol, and when an erroneous charp pattern is reproduced, there is a problem that an error occurs in the separation of the interference power. In Non-Patent Document 2, CRC is added to each symbol, and the influence of bit error can be suppressed by skipping the interference power separation processing and the subsequent interference power estimation processing for the symbol in which an error is detected. Although it has been proposed, the occupancy rate of the interference signal cannot be estimated correctly due to the skipping, and the estimation result used for the interference power estimation includes the condition that there is no error check, resulting in a bias in the estimated value. There was a challenge.

The interference power distribution estimation method according to one aspect of the present disclosure is an interference power distribution estimation method in which a radio wave including a spread spectrum-modulated signal for each symbol belonging to a predetermined set is received and the distribution of the interference power is estimated from the received signal. A step of demolishing a symbol from the received signal, a step of reproducing a spread spectrum modulated signal for each packet using a symbol belonging to the set other than the demodulated symbol, and the reproduced spread spectrum modulated signal. A step of outputting an estimated interference power based on the correlation calculation of the received signal and a step of summarizing the interference power distribution from the estimated interference power of a plurality of packets, and further performing an error check for each packet. For a packet including and having an error, the step of excluding the interference power estimation value from the target for totaling the interference power distribution is included when the interference power estimation value of the packet does not exceed a predetermined threshold value.

The spread spectrum modulation is a chirp modulation, and the correlation calculation is a step of reproducing a chirp pattern for each packet using a received spectrum signal generated from the received signal and a symbol belonging to the set other than the demodulated symbol. And, the interference power estimated value may be output based on the correlation calculation of the chirp pattern and the received spectrum signal.

A step of obtaining the threshold value by Gaussian approximation of the interference power distribution obtained from the packet containing no error may be further included.

The interference source occupancy estimation method according to one aspect of the present disclosure is an interference source occupancy estimation method using the interference power distribution estimation method, in which a boundary value is set between the threshold value and the average value of the noise power distribution. The estimated occupancy may be set and the value obtained by integrating the region of the interference power distribution exceeding the boundary value may be set.

The interference power distribution estimation device according to one aspect of the present disclosure is an interference power distribution estimation device that receives radio waves including a spread spectrum-modulated signal for each symbol belonging to a predetermined set and estimates the distribution of interference power from the received signal. A unit that demolishes a symbol from the received signal, a unit that reproduces a spread spectrum modulated signal for each packet using a symbol belonging to the set other than the demodulated symbol, and the reproduced spread spectrum modulated signal. A unit that outputs an estimated interference power based on the correlation calculation of the received signal and a unit that aggregates the interference power distribution from the estimated interference power of a plurality of packets, and further performs an error check for each packet. For a packet having an error, the unit includes a unit that excludes the interference power estimation value from the target for totaling the interference power distribution when the interference power estimation value of the packet does not exceed a predetermined threshold value.

The spread spectrum modulation is a chirp modulation, and the correlation calculation unit reproduces a chirp pattern for each packet using a received spectrum signal generated from the received signal and a symbol belonging to the set other than the demodulated symbol. The module may include a module that outputs an estimated interference power based on a correlation calculation between the chirp pattern and the received spectrum signal.

According to one aspect of the present disclosure, the interference power can be accurately estimated even in an environment where the SIR is poor, and the channel occupancy rate due to the interference source can be accurately grasped.

It is explanatory drawing which shows the assumed environment of the embodiment (the present embodiment) which concerns on one aspect of this disclosure. It is explanatory drawing which shows an example of a chirp modulation. It is explanatory drawing which shows the example which increased the diffusion rate of a chirp modulation. It is explanatory drawing which shows an example of the band-compressed chirp modulation. It is a flowchart which shows the algorithm of this embodiment. It is explanatory drawing which showed the basic operation of the interference estimation in this embodiment. It is explanatory drawing which showed the operation of the power distribution estimation in this embodiment. It is explanatory drawing which shows the influence when the CRC error containing packet is simply excluded. It is explanatory drawing which showed the exclusion operation of the CRC error containing packet in this embodiment on the time axis. It is a conceptual diagram which shows the simulation model of the Example of this disclosure. It is a graph which shows the simulation result of Example 1 of this disclosure. It is a graph which shows the simulation result of Example 2 of this disclosure.

Hereinafter, an embodiment (the present embodiment) according to one aspect of the present disclosure will be described in detail with reference to the drawings. In FIG. 1, it is assumed that three types of wireless devices exist in the area 1. It is assumed that the collecting station 2 receives a radio wave transmitted from an arbitrary wireless terminal 3. Further, it is assumed that radio wave interference is received from a wireless terminal 4 other than the wireless terminal 3. The wireless terminal 3 is performing spread spectrum communication with the collection station 2. The wireless terminal 3 may be a LoRa standard sensor, and in this case, a chirp-modulated radio wave for each symbol is transmitted to the collection station 2. It is assumed that the wireless terminal 4 is a terminal having a standard different from that of the wireless terminal 3 (for example, WiSUN).

Hereinafter, chirp modulation will be briefly described as an example of spread spectrum modulation. First, it is assumed that all the symbols in the transmission data (packet) belong to a predetermined set (s ₁ , s ₂ , ..., _Sk ). k is the total number of symbols. FIG. 2 shows an example of the frequency spectrum of the chirp-modulated signal when k = 2. It is assumed that all symbols belong to a set (s ₁ , s ₂ ) represented by 1 bit, where symbol s ₁ is composed of data 0 and symbol s ₂ is composed of data 1. By assigning the corresponding chirp patterns C (s ₁ ) (up chirp) and C (s ₂ ) (down chirp), the transmission data (for example, 1100) in an arbitrary packet is gradually changed in frequency as shown in the figure. It can be transmitted as an up / down signal.

In the present embodiment, the number of stages (diffusion rate) of the up chirp and the down chirp is 4, but this diffusion rate can be set arbitrarily. For example, the diffusion rate can be expanded to 8 as shown in FIG. At this time, the signal-to-noise power ratio (SNR) and the signal-to-interference power ratio (SIR) are improved, but the communication speed is lowered.

Conversely, it is also possible to compress the band per symbol (increase the communication speed). An example of chirp modulation when k = 4 is shown in FIG. In this example, it is assumed that each symbol belongs to a set of all patterns composed of 2 bits (∈ 00, 01, 11, 10). That is, the 2-bit data 00, 01, 11, and 10 are designated as symbols s ₁ , s ₂ , s ₃ , and s ₄ , and the chirp patterns C (s ₁ ), C (s ₂ ), and C (s ₃ ) corresponding to the symbols s 1, s 2, s 3, and s 4 are used. ), C (s ₄ ). Each chirp pattern is a pattern in which the basic pattern C (s ₁ ) is cyclically shifted one step at a time. The chirp patterns are not limited to the above examples as long as they do not correlate with each other, and the frequencies may not be changed stepwise (for example, hopping).

Next, demodulation of the chirp signal will be described. First, a reception spectrum signal is obtained from the radio wave received by the collection station 2 by a time-frequency conversion process such as FFT. The chirp pattern included in this received spectrum signal is demodulated by comparing the correlation with all the patterns (C (s ₁ ) to C ( _sk )) for each symbol. For example, when k = 2, the up pattern and the down pattern may be multiplied by each of the received spectrum signals, and the magnitude of the integrated value may be compared to determine which pattern is used. Further, when k ≧ 3, all the chirp patterns may be multiplied by the received spectrum signal, and the largest one may be selected from the respective integrated values, that is, the pattern having the highest correlation may be selected.

Hereinafter, a method for estimating the desired signal power and the interference power when interference is received from the wireless terminal 4 will be described with reference to the algorithm of FIG. The algorithm may be executed by a processor built in the collection station 2. In the present embodiment, unless otherwise specified, the chirp modulation of k = 2 and the diffusion rate = 4 shown in FIG. 2 is used thereafter. The outline of the received spectrum signal at this time is shown in the upper part of FIG. Here, the wireless terminal 3 may correspond to the LoRa standard, and the transmitted radio wave may have a bandwidth of 31.25 kHz to 500 kHz. Further, the wireless terminal 4 does not have to have the same standard as the wireless terminal 3, and may have a WiSUN standard having a band of 200 kHz to 400 kHz.

First, the collecting station 2 receives a radio wave including a signal from the wireless terminal 3 (S100), and generates a received signal. Next, a received spectrum signal is generated from this received signal by a time-frequency conversion process such as FFT (S101). Next, the symbol is demodulated from this received spectrum signal (S102). The symbol may be in 1-bit units as shown by s ₂ , s ₂ , s ₁ , s ₁ (1100 in data notation) in FIG. Next, the desired signal power and the interference signal power are estimated using these demodulation symbols (S104, S105). Regarding the interference signal power, the subsequent processing is divided depending on whether the CRC error check (S103) for each packet is OK or NG. The processing related to the estimation of these interference signal powers will be described below.

Assuming that the symbols (s ₂ , s ₂ , s ₁ , s ₁ ) are demodulated correctly, the chirp pattern transmitted by the wireless terminal 3 can be accurately reproduced based on these symbols. Simultaneously with this reproduction process, in the present embodiment, a chirp pattern is generated by the symbol obtained by inverting the demodulation symbol (lower part of FIG. 6). The interference signal power ( _PI ) can be estimated by multiplying the chirp pattern by the inverted symbol and the received spectrum signal and integrating each symbol (hereinafter referred to as correlation calculation). This is because the signal components are canceled by multiplying the opposite phase chirp patterns. The estimated power includes power due to noise ( _PI + P _n ).

Further, the received spectrum signal is subjected to a correlation operation with the chirp pattern by the original (non-inverted) symbol. In this case, the component of the desired signal power ( _PD ) is enhanced. However, the estimated power at this time includes noise power ( _{P n} ) and interference signal power (PI) ( _{PD + P I +} P _n ). This is because it is considered that a correlation component is generated with almost the same probability for any of the in-phase and anti-phase chirp patterns for the interference signal. However, the estimated power (PD) can be separated by subtracting the already obtained interference signal power ( _PI + _{P n} ). Hereinafter, the noise power P _n may be omitted as appropriate.

The same can be considered when one symbol has a multi-bit (m (≧ 2) bit) configuration. In this case, K = 2 ^m > 2, and there are a plurality of patterns (K-1) other than the reproduced chirp pattern. In such a case, the correlation calculation may be performed on a plurality of (K-1) patterns, and the correlation values may be averaged and output. Further, the correlation value that becomes the maximum value may be selected and output.

ここでＮはパケットを構成するシンボル数である。 The power _PI due to interference is further integrated for each packet, and if the demodulation symbol is completely error-free and the correlation calculation is performed without error, the estimation result is indicated by the interference signal estimated power ^ PI (in equation ( ₁ ), it is overlined. ).

Here, N is the number of symbols constituting the packet.

The interference signal estimated power ^ PI thus obtained can be used to determine the diffusion rate of the _chirp of the next packet. For example, when the interference signal estimated power ^ _PI exceeds a predetermined value, the collecting station 2 may send an instruction to increase the diffusion rate to the wireless terminal. At this time, it may be switched to use a chirp having a large diffusion rate as shown in FIG. By this operation, SIR can be improved and the occurrence of communication error due to interference from other systems can be reduced. Further, the interference signal estimation power ^ _PI can be used to estimate the occupancy rate of the channel by the radio terminal 4 which is the source of the interference wave. This will be described later.

As in the case of the interference signal estimated power ^ _PI , if the desired signal power _PD is integrated for each packet as in equation (2), the desired signal estimated power ^ _PD (indicated by an overline in equation (2)). Can be obtained.

In the above description, it is assumed that the symbol is correctly demodulated from the received spectrum signal of FIG. 6, but an error may actually occur. In particular, the higher the interference (the worse the SIR), the higher the frequency of errors. When an error occurs in the symbol (for example, where it should be 1 is 0), the reproduced chirp pattern is reversed, canceling the estimated value of the desired signal power and increasing the estimated value of the interference signal power. Therefore, as one of the countermeasures, it is conceivable to utilize the CRC (Cyclic Redundancy Check) code attached to each packet and invalidate the estimation result for the packet in which the CRC error is detected. By doing so, the influence of the symbol demodulation error can be suppressed to some extent.

However, when the frequency of CRC errors increases, the above method may hinder the determination of the diffusion rate and, in particular, the estimation of the channel occupancy rate by other terminals, which is the object of the present disclosure. That is, when the packet in which the CRC error is detected is discarded each time, the number of packets for which the interference signal power can be estimated decreases, and as a result, the channel occupancy rate by other terminals may be estimated to be small. In addition, since CRC errors occur frequently when high interference signal power is generated, if all of these are excluded, high interference signal power cannot be estimated instantaneously, which is a statistical tendency of interference signal power. The estimation accuracy of the average value and distribution is greatly reduced.

Therefore, in the present embodiment, two processes are provided for estimating the desired signal power and the interference signal power, depending on whether the error check (S103) by CRC is OK or NG. First, when the CRC error check is OK, the interference signal estimated power ^ PI and the desired signal estimated power ^ P _D are obtained by the equations ( ₁ ) and (2) (S104), and the respective power distribution estimation processes (S110). After that, the occupancy rate estimation process (S111) is executed.

On the other hand, for the packet (i) for which the CRC error check is NG, after obtaining the interference signal estimated power and the desired signal estimated power by the equations (1) and (2) (S105), the interference signal estimated power ( _PIi ) is calculated. It is determined whether or not the threshold value (P _th ) has been exceeded (S106), and if not, the packet is removed from the aggregation target (S107). However, when the interference signal estimated power ( _PIi ) exceeds the threshold value (P _th ), the power distribution is estimated together with the desired signal power and the estimated value of the interference signal power (S104) when the CRC error check is OK. Used for processing (S110).

The above processing and the channel occupancy estimation processing (S111) will be further described with reference to FIG. 7. FIG. 7A schematically shows how an interference signal appears intermittently at a ratio of 50:50 with respect to noise (^ _Pn ), and FIG. 7B schematically shows the power distribution at that time. .. The power distribution is obtained by sampling a predetermined number of interference signal estimated powers ^ _PI and plotting the estimated powers into a histogram on the horizontal axis. Here, assuming that no error has occurred when estimating the interference signal power, the sampled estimated values correspond to the period in which the interference exists and the period in which the interference does not exist (^ PI ₌ 0). , The power distribution of the lid mountain with almost equal area can be obtained (Fig. 7 (b)). The width of each power distribution is related to the noise power P _n .

Once the power distribution due to interference is clarified, the occupancy rate in the channel can be estimated based on this (S111). For example, the ratio of the area of the power distribution due to interference to the total area may be obtained. In this case, if the interference ratio of the wireless terminal 4 is 50:50, the occupancy rate is estimated to be 50%. Although the power distribution is drawn on the lid in FIG. 7B, it may be difficult to clearly draw a line in the actual power distribution because the bases overlap. Therefore, it is preferable to perform the power distribution estimation process (S110) as a preliminary step to the occupancy rate estimation process (S111). In the same process, for example, each distribution may be approximated by a Gaussian distribution and the respective areas may be compared. Further, the mixed normal distribution may be estimated by using an EM (Expectation Maximization) algorithm.

Here, the case where the CRC error cannot be ignored will be described below. As described above, if the packet in which the CRC error occurs is skipped unconditionally, it will not be counted as the interference signal power by that amount. FIG. 8 schematically shows this situation from the viewpoint of power distribution. As shown in the figure, the power distribution at the time of interference is detected as a smaller distribution than it actually is. As a result, the estimated average interference signal power is evaluated to be small, and the occupancy due to interference is estimated to be smaller than the actual value.

Therefore, in the present embodiment, as described above, even if the CRC error check (S103) is an NG packet (i), if the interference signal estimated power ( _PIi ) exceeds the threshold value (P _th ), the CRC error check is performed. Will be used for the power distribution estimation process (S110) together with the OK packet. This situation is schematically shown in FIG. In the figure, CRC error check OK is represented by ◯, and CRC error check NG is represented by ×.

There are two factors that cause an error in the demodulated symbol, one is due to noise and the other is due to interference. However, since the charp modulation is originally resistant to interference, the error due to interference is actually in one packet even if the CRC error check is NG. It often stays at one to several bits. Therefore, it is considered that the estimation error does not occur so much even if the chirp pattern is reproduced and used for the interference wave estimation without excluding the packet whose CRC error check is NG due to the interference wave. This demonstration result will be described in the following examples.

Here, a method for determining the threshold value P _th will be described. In the present embodiment, the distribution of the interference power (including the noise power) when the CRC error check is OK is estimated (S108), and the threshold value _Pth is determined from this (S109). Specifically, the power value at the saddle (minimum value) of the mountain pass may be used as a threshold value. Further, the power value at which the Gaussian functions that approximate each distribution intersect may be used as the threshold value. It may be an average value obtained by an EM algorithm from the distribution of interference power. At this time, as described later, the interference power may be designed as a new boundary value including the adjustment coefficient Δ.

Although the method of estimating the interference power distribution has been described in the above embodiments, the present disclosure discloses hardware such as an ASIC constructed with a unit or a module corresponding to each step in the flowchart shown in FIG. It may be an interference power distribution estimation device realized by a program on hardware or a microprocessor. Further, the interference power distribution estimation device may be incorporated in the collection station 2 as a function.

Hereinafter, examples of the present disclosure will be described. This embodiment relates to a simulation in which the interference signal power and the channel occupancy are estimated using the algorithm shown in FIG. 5 and the result thereof.

First, FIG. 10 shows a simulation model in this embodiment. The collection station (FC) 2 is located in the center of the area 1, and the wireless terminal 3 (LoRa Sensor) and the wireless terminal 4 (WiSUN Sensor) are located 700 m away from the collection station 2. .. Table 1 shows other simulation conditions, and Table 2 shows the assumed propagation environment.

(Example 1)
Table 3 and FIG. 11 show the simulation results when the WiSUN sensor (interference) power is 18 dBm. The signal: interference mixing ratio is 30:70.

In Table 3, the original data represents the set values (average, dispersion, mixing ratio) of the power distribution of the signal transmitted by the wireless terminal 3 and the power distribution of the interference transmitted by the wireless terminal 4 (the left side is the desired signal power and the right side). Is the interference signal power). When the method of this embodiment using the algorithm of FIG. 5 was used, the mixing ratio was 0.29: 0.71, which is extremely close to 0.30: 0.70 of the original data, and is estimated almost accurately. .. On the other hand, in the method of excluding the estimated value of the interference signal power when the CRC error occurs, the interference signal power ratio is erroneously estimated as 0.06. In the estimation method using all packets including errors without using CRC, an error occurs in the direction in which the interference signal power increases conversely.

(Example 2)
Table 4 and FIG. 12 show the simulation results when the WiSUN sensor (interference) power is 8 dBm. The mixing ratio is 30:70 as in Example 1, but the interference signal power is 10 dB smaller than that in Example, and the bases of the power distributions of the two peaks overlap, so when calculating the occupancy rate from the power distribution due to interference. Errors are likely to occur.

In Table 4, when the threshold value _pth is the average value of interference + noise power when the CRC error check obtained by the EM algorithm is OK as in Example 1, the estimated mixing ratio is 0.43: 0.57. , Some error occurred. Therefore, when the adjustment coefficient (Δ) was added to the threshold value and the boundary value (= threshold value + Δ) was set slightly closer to the noise distribution (Example (after optimization)), the estimated mixing ratio was 0.30: 0. It improved considerably to 70. In this embodiment, the adjustment coefficient (Δ) takes a negative value, and the boundary value is located between the threshold value _pth and the average value of the noise power distribution.

The embodiments and examples of the present disclosure have been described above. In each case, the radio device on the side of sending a signal uses chirp modulation, but the present invention is not limited to chirp modulation, and the present invention can be applied to other spread spectrum communication methods.

The present invention is not limited to LPWAs, but can be used for communication systems of 5G or later, particularly fields related to IoT, such as connected cars, smart meters, wearable monitors, and the like.

1 Area 2 Collection station 3 Wireless terminal 4 Wireless terminal (interference source)

Claims (6)

It is an interference power distribution estimation method that receives radio waves including spread-spectrum-modulated signals for each symbol belonging to a predetermined set and estimates the distribution of interference power from the received signals.
The step of demodulating the symbol from the received signal and
A step of reproducing a spread spectrum modulated signal for each packet using symbols belonging to the set other than the demodulated symbols, and
The step of outputting the interference power estimated value based on the correlation calculation between the reproduced spread spectrum modulation signal and the received signal, and
Includes a step to aggregate the interference power distribution from the interference power estimates for multiple packets.
Further, it includes a step of performing an error check for each packet, and for a packet having an error, the interference power estimated value is aggregated with the interference power distribution when the interference power estimated value of the packet does not exceed a predetermined threshold value. Interference power distribution estimation method that includes steps to exclude from the target. The spread spectrum modulation is a chirp modulation, and the correlation calculation is a step of reproducing a chirp pattern for each packet using a received spectrum signal generated from the received signal and a symbol belonging to the set other than the demodulated symbol. The interference power distribution estimation method according to claim 1, wherein an interference power estimated value is output based on a correlation calculation between the chirp pattern and the received spectrum signal. The interference power distribution estimation method according to claim 1, further comprising a step of obtaining the threshold value by approximating the interference power distribution obtained from an error-free packet by Gaussian approximation. An interference source occupancy rate estimation method using the interference power distribution estimation method according to any one of claims 1 to 3, wherein a boundary value is set between the threshold value and the average value of the noise power distribution. A method for estimating the interference source occupancy rate, which includes a step in which the value obtained by integrating the region exceeding the boundary value in the interference power distribution is used as the estimated occupancy rate. It is an interference power distribution estimation device that receives radio waves including spread-spectrum-modulated signals for each symbol belonging to a predetermined set and estimates the distribution of interference power from the received signals.
A unit that demodulates a symbol from the received signal, and
A unit that reproduces a spread spectrum modulation signal for each packet using symbols belonging to the set other than the demodulated symbols, and
A unit that outputs an estimated interference power based on the correlation calculation between the reproduced spread spectrum modulation signal and the received signal.
Includes a unit that aggregates the interference power distribution from the interference power estimates for multiple packets.
Further, for a packet having an error, which includes a unit that performs an error check for each packet, the interference power estimated value is aggregated with the interference power distribution when the interference power estimated value of the packet does not exceed a predetermined threshold value. Interference power distribution estimator that includes units to exclude. The spread spectrum modulation is a chirp modulation, and the correlation calculation unit reproduces a chirp pattern for each packet using a received spectrum signal generated from the received signal and a symbol belonging to the set other than the demodulated symbol. The interference power distribution estimation device according to claim 1, further comprising a module and a module that outputs an estimated interference power value based on a correlation calculation between the chirp pattern and the received spectrum signal.

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