KR20170022360A - Communication mode identification method for performing the wireless apparatus - Google Patents

Abstract

The present invention relates to a communication mode identification method. Particularly, the communication mode identification method includes analyzing a received signal generated in an ISM band to determine whether a specific channel is currently being used or a WS channel, and determining whether the radio signal of an active channel indicates an OFDM signal or a Bluetooth signal. After that, the communication mode identification method includes identifying a communication mode by using the frequency component of the radio signal when the determined radio signal is the OFDM signal. So, it is possible to identify WLAN, Bluetooth and white space used in a particular band of 2.4 GHz and 5 GHz.

Description

[0001] COMMUNICATION MODE IDENTIFICATION METHOD FOR PERFORMING THE WIRELESS APPARATUS [0002]

The present invention relates to a communication method identification method performed by a wireless device, and more particularly, to a method of identifying a wireless signal using a difference between spectrum signals generated in an ISM band and identifying a communication method according to the wireless signal .

The ISM band (Industrial Scientific Medical band) represents the frequency bands available in industrial, scientific and medical devices. In recent years, as the ISM band is used as a communication frequency band, communication devices that do not require permission use a corresponding communication frequency band. However, it is easy to interfere with the ISM equipment using the ISM band and the communication equipment using the communication frequency band.

Generally, unlicensed telecommunication equipment uses the 2.4 GHz and 5 GHz ISM bands heavily. Here, there are a variety of transmission methods used in the 2.4 GHz and 5 GHz ISM bands, but typical examples thereof include transmission methods such as IEEE WLAN (wireless LAN) and Bluetooth. Spectrum sensing and identification methods for these signals are needed to understand the frequency utilization of the frequency band.

Specifically, spectrum sensing is a technique for determining whether there is a primary user signal in an arbitrary frequency space. Spectrum sensing provides an opportunity for a secondary user to use the frequency space without damaging the user first. Which in turn improves utilization efficiency for frequency resources.

Spectrum identification is a technique for determining the modulation method of a signal in addition to spectrum sensing. Spectrum identification identifies any frequency band usage in more detail.

In addition, the communication equipment can distinguish transmission methods used in the 2.4 GHz and 5 GHz ISM bands through the above-described spectrum sensing and identification methods. However, there are IEEE 802.11a and IEEE 802.11n schemes among the WLAN (WLAN) schemes using the ISM band. These two schemes are important transmission parameters of the OFDM transmission scheme such as the effective symbol interval width and the CP (cyclic prefix) It is difficult to distinguish them practically.

Therefore, there is a need for a method for identifying the above two methods through the spectrum sensing and identification method for the ISM band.

The present invention can provide a communication method identification method for identifying WLAN, Bluetooth and white space used in a specific band of 2.4 GHz and 5 GHz by analyzing a received signal generated in the ISM band.

The present invention can provide a communication method identification method for performing spectrum identification using bandwidth differences of radio signals of IEEE 802.11a and 802.11n, respectively.

A method of identifying a communication method according to an exemplary embodiment includes analyzing a received signal generated in an ISM band to determine whether a channel having a specific band is used; Determining whether a radio signal of the channel represents an OFDM signal or a Bluetooth signal when a signal using the channel exists; Determining that the wireless channel is a WS channel when the OFDM signal or the Bluetooth signal is not determined, and there is no signal using the channel; And identifying a communication scheme corresponding to the frequency component using the frequency component of the OFDM signal if the radio signal is an OFDM signal, wherein identifying the communication scheme comprises: It is possible to identify the communication method by using the size of the communication method.

A method of identifying a communication method according to an exemplary embodiment may spectrum-sense a received signal generated in an ISM band to identify WLAN, Bluetooth, and white space.

A method of identifying a communication method according to an exemplary embodiment may identify a short distance communication method for IEEE802.11a and IEEE802.11n using a bandwidth difference of a received signal generated in an ISM band.

1 is a diagram for explaining a communication method identification method according to an embodiment.
2 is a diagram for explaining a configuration for determining a radio signal of a channel in use according to an embodiment.
3 is a view for explaining a configuration for identifying a communication method using a frequency component of a radio signal according to an embodiment.
4 is a graph for explaining a configuration for designing a bandpass filter for identifying a communication method according to an embodiment.
5 is a graph for explaining a configuration for setting a reference threshold value for identifying a communication method according to an embodiment.
6 is a graph illustrating performance of identifying a communication method through a communication method identification method according to an exemplary embodiment.
7 is a flowchart of a communication method identification method according to an exemplary embodiment.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram for explaining a communication method identification method according to an embodiment.

Referring to FIG. 1, a wireless device can identify an OFDM signal, a Bluetooth signal, and a WS channel using a received signal generated in the ISM band. At this time, based on the OFDM signal detection method, the periodic steady state analysis, and the power spectrum analysis result, the wireless device can determine whether the channel is used by the first user or the WS channel. Then, the wireless device can determine which of the OFDM signal and the Bluetooth (BT) signal the corresponding channel is present, if there is a wireless signal currently being used. Also, the wireless device can determine that the wireless channel is a WS channel if the wireless signal is not an OFDM signal or a Bluetooth signal, and there is no signal using the channel.

When the OFDM signal is using a channel, the wireless device can distinguish whether the received signal is 802.11a or 802.11n by taking advantage of the bandwidth of the OFDM signal. More specifically, the wireless device can use a spectrum sensing scheme and a spectrum identification scheme to identify OFDM signals, Bluetooth signals, and WS channels based on the received signals.

Here, the spectrum sensing method is a technique for determining whether there is a priority user signal of a corresponding frequency band. In other words, the spectrum sensing method can extract characteristics of a received signal based on a matched filter method, an energy detection method, and a feature detection method. At this time, the spectrum sensing method can extract the characteristics of the signal based on the cyclostationarity indicated by the received signal. The spectrum sensing method can determine whether a channel of a specific band is used by a primary user.

As a result, the wireless device can determine whether a channel having a specific band is used by applying a spectral sensing method to a reception signal generated in the ISM band using a spectrum sensing scheme. For example, as shown in FIG. 1, the wireless device may sense whether 'channel 2' is currently being used by the priority user in response to a received signal occurring in the ISM band.

When the channel is used, the wireless device can determine which of the OFDM signal and the Bluetooth signal the wireless signal of the channel represents. At this time, the wireless device can determine whether or not the received signal includes the OFDM signal by using the OFDM signal detection method based on the generalized likelihood ratio (GLRT) method. Also, the wireless device can determine whether the received signal includes the Bluetooth signal according to the comparison result between the maximum value of the power spectrum and the detection threshold value based on the power spectrum analysis method. And, the wireless device can more easily distinguish the OFDM signal and the Bluetooth signal by utilizing the periodic steadiness as well as the OFDM signal detection method and the power spectrum analysis.

Here, the wireless device can determine whether it is an OFDM signal, a Bluetooth signal, or a WS channel based on Table 1. [

GLRT Periodic normality Power spectrum Judgment Y Y * OFDM * N Y IT N Y * WS * N N WS

The Y symbol shown in Table 1 may be a symbol indicating that the result of sensing the received signal by the spectrum sensing method is "signal present". Conversely, the N symbol may be a symbol representing "no signal ". In addition, the symbol * may be a symbol indicating that it is not related to the judgment of the result of sensing by the spectral sensing method. BT is a word indicating a Bluetooth signal, and WS is a frequency band that is not used, that is, a frequency band in which the sensing result is determined as " no signal ". If the received signal is analyzed as an OFDM signal, the wireless device can determine whether the OFDM signal uses 802.11a or 802.11n.

2 is a diagram for explaining a configuration for determining a radio signal of a channel in use according to an embodiment.

Referring to FIG. 2, when there is a radio signal in a channel in use, the radio device can determine whether a radio signal of the channel represents an OFDM signal or a Bluetooth signal. And, the wireless device can distinguish each signal using different methods.

(1) OFDM signal

The wireless device can determine whether the received signal includes an OFDM signal using an OFDM signal detection scheme based on the GLRT scheme. Here, the OFDM signal may mean a signal in which one data is divided into a plurality of carriers in order to increase the frequency utilization efficiency. An OFDM signal can use a cyclic prefix (CP) to remove inter-symbol interference and ensure orthogonality of subcarriers. At this time, it is assumed that the OFDM signal uses N subcarriers, and the length of the CP is L samples. This can be represented as shown in Fig.

The structure shown in FIG. 2 shows the structure of an OFDM symbol. The CP may be the same as the latter L sample of the OFDM symbol. Since the OFDM signal has the same signal within a single OFDM symbol at predetermined time intervals, the second order correlation function for the OFDM signal may have a different form from the second order correlation function for the noise have.

Therefore, the wireless device can formulate the problem of hypothesis testing that the secondary correlation characteristic is different depending on the presence or absence of the signal of the first user in an environment where noise power and signal power are unknown. Then, the wireless device can determine the presence or absence of a signal of the following priority user by applying a generalized likelihood ratio test (GLRT) as a solution thereto. Equation (1) may include an equation for determining the presence or absence of a signal of the user by applying the GLRT method.

는 OFDM 심볼의 동기화 오차를 가리키는 양으로서, 측정한 수신 샘플이 CP의 시작 위치에서 얼마나 떨어져 있는가를 나타낼 수 있다. 그리고,

은 CP에 속하는 수신 샘플의 인덱스 집합을 가리킬 수 있다. 또한, 수신 신호를

이라 할 때,

는 수학식 2와 같이 정의될 수 있다.In Equation (1)

Is a quantity indicative of the synchronization error of the OFDM symbol and may indicate how far the measured received sample is at the start of the CP. And,

May point to the set of indices of the received samples belonging to the CP. Also,

In other words,

Can be defined as Equation (2).

는 시간 i 에서 수신 신호 샘플을 나타내며,

는 연산에 사용되는 OFDM 심볼의 개수를 나타낼 수 있다. 그리고

는

의 실수부를 의미하고,

는 검파 임계값으로서, 오경보 확률에 따라 결정되는 값일 수 있다.In Equation 2,

Represents a received signal sample at time i,

May represent the number of OFDM symbols used in the operation. And

The

Quot; means < / RTI >

Is a detection threshold value, and may be a value determined according to the false alarm probability.

As a result, the wireless device can determine whether or not an OFDM signal exists in a reception signal generated in the ISM band, taking into consideration the probability of erroneous notification according to the number of OFDM symbols based on the GLRT method.

(2) Bluetooth signal

The wireless device can determine whether the received signal includes the Bluetooth signal according to the comparison result between the maximum value of the power spectrum and the detection threshold value based on the power spectrum analysis method. In detail, a Bluetooth signal generally uses a frequency hopping method, and can be regarded as a narrowband signal based on a time when a constant frequency is maintained. Accordingly, if the Bluetooth signal exists in the spectrum sensing period, the wireless terminal can be expected to have a narrowband spectrum form using only a part of the 20 MHz bandwidth unlike the wireless LAN (WLAN) signal.

Accordingly, the wireless terminal can detect the power spectrum of the received signal in order to perform spectral sensing utilizing the characteristic of the Bluetooth signal using the narrowband signal. Then, the wireless terminal extracts a maximum value from the detected power spectrum, and compares the extracted maximum value with a detection threshold value to determine whether or not the Bluetooth signal exists.

More specifically, the power spectrum analysis method can be performed through the following steps.

을 N=64샘플 단위로 구분할 수 있다. 이 때, 전력 스펙트럼 분석 방식은 각 데이터 조각 단위로 다음과 같이 FFT를 수행할 수 있으며,

번째 데이터 조각 단위에 대한 FFT를

이라고 하면, 수학식 3이 도출될 수 있다.In the power spectrum analysis method, the received signal generated in the ISM band is sampled data

Can be divided into N = 64 sample units. At this time, the power spectrum analysis method can perform the FFT as follows for each data fragment unit,

FFT for the first data fragment unit

, Equation (3) can be derived.

로부터 전력 스펙트럼

을 수학식 4와 같이 계산할 수 있다.And the power spectrum analysis method

The power spectrum

Can be calculated as shown in Equation (4).

는 샘플링 주기를 나타내고,

은 데이터 조각의 개수를 나타낼 수 있다. 그리고, 통계량

는 전력 스펙트럼

중에서 최대값에 해당됨에 따라 수학식 5와 같이 정의할 수 있다.In Equation 4,

Represents a sampling period,

Can represent the number of data pieces. Then,

The power spectrum

And the maximum value is defined as Equation (5).

는 목표로 하는 오경보율

에 따라 수학식 6과 같이 결정될 수 있다.Here, the detection threshold value

The target false alarm rate

As shown in Equation (6).

으로 정의되며,

는 잡음의 분산이다.Referring to Equation 6,

Lt; / RTI >

Is the variance of the noise.

The wireless device can determine whether or not the Bluetooth signal is included in the reception signal generated in the ISM band by comparing the maximum value and the detection threshold value in the power spectrum based on the power spectrum analysis method.

(3) WS (white space) channel

The wireless device can analyze the reception signal generated in the ISM band and determine the WS channel, which is a frequency band that is not currently used.

The wireless device may utilize periodic steadiness to more accurately distinguish between the ODFM signal and the Bluetooth signal. In other words, the periodic steady state means that the mean E [x (n)] of the probability process and the autocorrelation function R _x (n, τ) are random functions in a random process x (n) It can be defined that normality is established. The mean and autocorrelation functions of the stochastic processes that define periodic steady state can be expressed as in Equation (7).

가 주기 함수인 경우, 수학식 8과 같이 푸리어 급수로 전개할 수 있다.Here, the wireless device has an autocorrelation function

Is a periodic function, it can be expanded to a Fourier series as shown in equation (8).

는 cyclic autocorrelation function(CAF)이라고 하고, CAF의 값이 0이 되지 않는 α를 cyclic frequency(CF)라고 하며, CF의 집합을 K로 표시할 수 있다. 그리고, 무선 장치는 수학식 7에 도시된 x(n)의 길이가 L일 때, CAF 추정값

는 수학식 9와과 같이 정의할 수 있다.At this time,

Is called a cyclic autocorrelation function (CAF), and an α that does not have a CAF value of 0 is called a cyclic frequency (CF), and a set of CF can be denoted by K. Then, when the length x (n) shown in Equation (7) is L, the wireless apparatus calculates the CAF estimate

Can be defined as shown in Equation (9).

에 대한 공분산 행렬을

라고 할때, 수학식 10과 같이 시험 통계량

을 계산할 수 있다.The wireless device

The covariance matrix for

, The test statistic < RTI ID = 0.0 >

Can be calculated.

을 검파 임계값과 비교하여

가 CF가 되는지 여부를 판정할 수 있다. 그리고,

가 여러 가지

에 대해서 주기성을 가질 때는 길이가 1 이상인 벡터가 되기 때문에, 주기적 정상성을 이용하는

방법을 활용하여 계산량이 다른 방법에 비해 커질 수 있다는 것을 알 수 있다.Finally,

To the detection threshold

It can be judged whether or not it is CF. And,

There are many ways

Is a vector having a length of 1 or more when having a periodicity,

It can be seen that the calculation amount can be made larger than the other methods by utilizing the method.

The spectral sensing method using periodic steady state can estimate the CF and CAF from the received signal and determine whether it matches the CF characteristic of the appearing receivable signal. At this time, the spectrum sensing method can use a hypothesis testing method to determine whether or not the CF matches.

3 is a view for explaining a configuration for identifying a communication method using a frequency component of a radio signal according to an embodiment.

Referring to FIG. 3, when a wireless signal of a channel is an OFDM signal, a wireless device can identify a communication method corresponding to the frequency component using a frequency component of an OFDM signal.

More specifically, the OFDM signal is a signal transmitted by dividing data as mentioned above, and may be a signal having a similar periodicity steadily. Therefore, conventionally, it is difficult to distinguish the communication method used in the OFDM signal as the characteristics of the transmission parameters included in the OFDM signal are similar.

However, the OFDM signal can be classified into IEEE 802.11a and IEEE 802.11n in the WLAN (WLAN) communication method using the ISM band. In addition, IEEE 802.11a and IEEE 802.11n contain different signal bandwidths. Therefore, the wireless terminal can identify the communication method used in the OFDM signal by using the difference between the signal bandwidth used in IEEE 802.11a and IEEE 802.11n.

In detail, the 802.11n communication method uses a subcarrier of 27th, 28th, 36th and 37th subcarriers in addition to the subcarrier used in the 802.11a scheme. In order to utilize this, the 802.11n communication method can be referred to as a received signal existing in the frequency band occupied by the 802.11n method compared with 802.11a. If the received signals are 802.11a and 802.11n, respectively, the wireless terminal can formulate a problem of hypothesis testing as shown in Equation (11), thereby distinguishing these two signaling methods.

는 802.11n 신호가 해당 대역에서 갖는 신호 성분을 가리키며, 여기에는 채널 특성이 이미 반영되어 있다고 가정할 수 있다. 그리고 n(t)는 해당 대역에 포함된 가우시안 잡음을 나타낼 수 있다.Referring to Equation (11)

Indicates the signal component that the 802. < RTI ID = 0.0 > 11n < / RTI > signal has in the corresponding band, and it can be assumed that the channel characteristic is already reflected. And n (t) may represent the Gaussian noise included in the corresponding band.

를 구체적으로 기술하는 것은 어려울 수 있다. 다시 말해,

는 신호 자체가 복잡할 수 있으며, 더욱이 불규칙한 채널 특성이 반영되어 있기 때문에 구체적인 기술이 어려울 수 있다. 따라서, 본 발명에서는 기술이 어려운

에 대한 가설을 검정 문제를 해결하기 위하여 에너지 검파(energy detection) 방식을 사용할 수 있다.At this time, from the viewpoint of spectrum sensing,

May be difficult to describe in detail. In other words,

The signal itself may be complicated, and moreover, irregular channel characteristics may be reflected, so that detailed techniques may be difficult. Therefore, in the present invention,

The energy detection method can be used to solve the problem of hypothesis.

Specifically, the wireless device proposed in the present invention can extract a specific band component used in the 802.11n communication method among frequency components of a reception signal generated in the ISM band. Then, the wireless device can identify the communication method of the wireless LAN by comparing the power or energy of the OFDM signal with the detection threshold based on the extracted component of the specific band.

In other words, the wireless device may determine that the OFDM signal uses an 802.11n communication scheme if it represents a particular band component used in the 802.11n communication scheme. Conversely, the wireless terminal may determine that it uses the 802.11a communication scheme when the OFDM signal does not represent a specific band component used in the 802.11n communication scheme.

이라고 하고, 역통과필터에 입력되는 잡음을

이라고 하며, 대역통과필터 출력 잡음을

이라 정의할 수 있다. 그리고

은 평균이 '0'의 값을 나타내고, 이고 분산이

인 AWGN이라고 가정할 수 있다. 이에 기초하여, 출력 잡음은 수학식 12과 같이 나타낼 수 있다.In step 301, the wireless device may use a band-pass filter to extract a band component only used by the 802.11n signal. Specifically, the wireless terminal determines the impulse response of the bandpass filter in a situation where the hypothesis H ₀ is valid

, And the noise input to the inverse pass filter

, And the bandpass filter output noise

. And

Represents an average value of " 0 &

Can be assumed to be AWGN. Based on this, the output noise can be expressed by Equation (12).

의 평균은 수학식 13와 같이 나타낼 수 있으며, 분산은 수학식 14과 같이 나타낼 수 있다.In Equation 12, L may represent the impulse response length of the band pass filter. Then,

Can be expressed by Equation (13), and the variance can be expressed by Equation (14).

와 수학식 14에서

은 각각 평균 연산과 분산 연산을 의미할 수 있다. 그리고,

은 가우시안 잡음을 나타냄으로, 출력 잡음

도 가우시안 분포에 따라

로 표현될 수 있다. 그리고

의 분산을

이라고 한다. 이 때, 출력 잡음

은

으로 정규화할 경우, 출력 잡음의 실수부와 허수부가 모두 정규 분포를 따르게 될 수 있다. 따라서,

는 2차의 카이 제곱(chi-square) 분포를 따를 수 있다.In Equation (13)

And in Equation (14)

May mean an average operation and a distributed operation, respectively. And,

Represents the Gaussian noise, so that the output noise

Depending on the Gaussian distribution

. ≪ / RTI > And

The dispersion of

. At this time,

silver

, Both the real part and the imaginary part of the output noise may follow a normal distribution. therefore,

May follow a second-order chi-square distribution.

을 계산할 수 있다. 구체적으로, 무선 장치는 대역통과필터의 출력 샘플 하나만을 사용하여 가설 검정을 한다면

을 계산한 후 이 값을 기준 임계값과 비교함으로써, OFDM 신호의 통신 방식을 구별할 수 있다.In step 302, the wireless device transmits a test statistic

Can be calculated. Specifically, if the wireless device performs a hypothesis test using only one output sample of the bandpass filter

And comparing this value with the reference threshold value, it is possible to distinguish the communication method of the OFDM signal.

을 계산하고, 이를 합산하여 가설 검정을 수행하는 방식을 제안할 수 있다.However, if multiple samples are used rather than one sample as the output sample of the bandpass filter, the wireless device can further improve the discrimination performance of the OFDM signal communication scheme. However, it is preferable that a plurality of output samples are statistically independent from each other. To this end, the wireless device may extract samples from the output samples of the bandpass filter at certain time intervals

And then performing a hypothesis test.

In other words, if the length of the bandpass filter is L, the wireless device can obtain statistically independent samples by extracting the output samples of the bandpass filter at intervals of L + 1 or more. If the test statistic is made by extracting N samples, the test statistic X may have a chi-square distribution of 2N. In addition, if the number of samples is large enough, the wireless device can approximate the distribution of the test statistic to the Gaussian distribution using the central limit theorem, and the mean and variance can be 4N.

보다 클 확률을

이라고 할 때, 수학식 15와 같이 나타낼 수 있다.In step 303, the wireless device may compare the test statistic with a reference threshold. In other words, the wireless device can determine that the test statistic X exceeds the reference threshold

The greater the probability

, It can be expressed as Equation (15).

에 대한 기준 임계값

는 수학식 16와 같이 결정할 수 있다.Thus, given

Reference threshold for

Can be determined as shown in Equation (16).

Then, if the test statistic is greater than the reference threshold, the wireless device may determine in step 304 that the OFDM signal is being transmitted in the 802.11n communication scheme. Conversely, if the test statistic is less than the reference threshold, then in step 305 the wireless device may determine that the OFDM signal is being transmitted in the 802.11a communication scheme.

4 is a graph for explaining a configuration for designing a band-pass filter according to a frequency component of a radio signal according to an embodiment.

Referring to FIG. 4, the graph may represent a frequency response characteristic of a band pass filter used to obtain a signal corresponding to x (t) in Equation (11) of FIG. Here, the band-pass filter uses a 375th order FIR filter, and the transmission frequency of the 28th and 36th subcarriers, which are filters used in 802.11n, is included in the passband to include only the band used by 802.11n.

5 is a graph for explaining a configuration for setting a reference threshold value for identifying a communication method according to an embodiment.

=0.1로 설정할 수 있다. 여기서,

은 802.11a 신호가 있는 상황에서 802.11n 으로 잘못 판단하는 확률을 의미합니다. 이에 따라 도 5는 전산 모의 실험에 따른 결과를 나타낼 수 있다The wireless device of the present invention performs a computer simulation of the Monte Carlo method in order to examine the performance for distinguishing the communication method. For the simulation, we assumed that the spectrum sensing time is 5ms and 802.11a or 802.11n signal is always in the sensing time interval. And

= 0.1. here,

Means the probability of misjudging 802.11n in the presence of an 802.11a signal. Accordingly, FIG. 5 shows the result of the computer simulation

Referring to FIG. 5, the wireless device can set a reference threshold value used for distinguishing the communication method of the OFDM signal based on the transmission described in FIG. In this case, the graph of FIG. 5 may be obtained by comparing the target false alarm probability value with the value obtained through experiments in setting the reference threshold value.

Here, referring to the graph of FIG. 5, it can be seen that the wireless device obtains a false alarm probability that is close to an ideal value (target false alarm probability) in the presence of noise only. However, the probability of false alarms is higher when the 802.11a signals are mixed in the noise, and the false alarm probability is slightly higher than the target value.

At this time, the difference in the probability of false alarm occurs because the band-pass filter is different from the ideal band-pass filter. That is, this is because some of the signal components of the adjacent band are included in the output of the band-pass filter.

6 is a graph illustrating performance of identifying a communication method through a communication method identification method according to an exemplary embodiment.

Here, the graph shown in FIG. 6 shows the performance of the proposed scheme in an AWGN channel environment and a fading channel environment.

Here, the fading environment uses the 802.11a fading channel model provided by MATLAB, the sampling frequency is 20 MHz, and the delay spread of the multipath channel is set to 200 ns. The probability of occurrence of the 802.11a signal and the 802.11n signal is set to be 1/2, respectively.

In the fading channel environment, the improvement rate of the identification performance according to the increase of the SNR is relatively slow compared to the AWGN channel environment, which can be judged to be due to the fading effect.

7 is a flowchart of a communication method identification method according to an exemplary embodiment.

In step 701, the wireless device may analyze the received signal occurring in the ISM band. At this time, the wireless device can determine whether the channel is being used by the first user based on the OFDM signal detection method, the periodic steady state analysis, and the power spectrum analysis result.

In step 702, if there is a currently used channel, the wireless device can determine which of the OFDM signal and the Bluetooth (BT) signal is the corresponding channel. If the wireless device is not an OFDM signal or a Bluetooth (BT) signal, it can determine whether it is a WS channel.

Specifically, the wireless device can determine if the OFDM signal is using the channel. At this time, the wireless device can determine whether the received signal includes the OFDM signal by using the OFDM signal detection method based on the generalized likelihood ratio (GLRT) method and the periodicity steadiness.

For example, if the result of a received signal according to the GLRT scheme represents a Y symbol and the periodicity steadily represents a Y symbol, then the wireless device may determine that the received signal comprises an OFDM signal.

If the OFDM signal is not used, the wireless device can determine whether it is using the Bluetooth signal. At this time, the wireless device can determine whether or not the received signal includes the Bluetooth signal by using the power spectrum and the periodicity normality based on the power spectrum analysis method. Here, the wireless device can determine whether the received signal includes the Bluetooth signal according to the comparison result between the maximum value of the power spectrum and the detection threshold value.

For example, if the result of the received signal according to the power spectrum analysis scheme indicates the Y symbol and the periodicity normality indicates the N symbol, the wireless device can determine that the received signal includes the Bluetooth signal.

Conversely, when the OFDM signal and the Bluetooth signal are not used, it can be confirmed that the wireless device is a temporarily unused frequency space, that is, a WS channel.

For example, if the result of a received signal according to the GLRT scheme represents an N symbol and the periodicity steadily represents a Y symbol, then the wireless device can verify that the received signal is a WS channel.

In another example, if the result of a received signal according to a power spectrum analysis scheme represents an N symbol and the periodicity steadiness represents an N symbol, then the wireless device can verify that the received signal is a WS channel.

을 결정할 수 있다. 그리고, 무선 장치는 시험 통계량

을 계산할 수 있다.If an OFDM signal is used, then in step 703 the wireless device may analyze the frequency component of the OFDM signal. The wireless device uses the output of a bandpass filter that is not used in 802.11a but extracts only the frequency band components used in 802.11n

Can be determined. And,

Can be calculated.

In step 704, the wireless device may determine whether the test statistic value according to the analysis frequency component is greater than a reference threshold value.

If the test statistic value is greater than the reference threshold, then in step 705 the wireless device may determine that the OFDM signal is using the 802.11n communication scheme. Conversely, if the test statistic value is less than the reference threshold, then in step 706 the wireless device may determine that the OFDM signal is using the 802.11a communication scheme.

The methods according to embodiments of the present invention may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions recorded on the medium may be those specially designed and constructed for the present invention or may be available to those skilled in the art of computer software.

While the invention has been shown and described with reference to certain preferred embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. This is possible.

Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined by the equivalents of the claims, as well as the claims.

Claims (1)

Analyzing a received signal generated in the ISM band to determine whether a channel having a specific band is used;
Determining whether a radio signal of the channel indicates an OFDM signal or a Bluetooth signal when the radio signal using the channel exists;
Determining that the wireless signal is a WS channel if the wireless signal is not an OFDM signal or a Bluetooth signal and there is no signal using the channel; And
If the radio signal is an OFDM signal, identifying a communication method corresponding to the frequency component using a frequency component of the OFDM signal
Including the
Wherein identifying the communication scheme comprises:
And identifying the communication method using the size of the bandwidth indicated by the frequency component.

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