KR100983513B1 - Method of Controlling Wireless Sensor Network - Google Patents

Abstract

The present invention relates to a wireless sensor network control method, comprising: a sensor node and a sensor node for collecting and transmitting data in a wireless sensor network performing multi-input multi-output (MIMO) based cooperative communication; Calculating a change in energy consumption by changing a training symbol overhead of the data while maintaining a constant data transmission / reception rate between data collection nodes for collecting the collected data; Calculating a change amount of energy consumption by changing the data transmission / reception rate between the sensor node and the data collection node while maintaining a constant size of the training symbol overhead of the data; And determining the training symbol overhead and the speed for minimizing the energy consumption based on the energy consumption change amount according to the change of the training symbol overhead and the energy consumption change amount according to the speed change. do. Accordingly, in the MIMO cooperative communication-based wireless sensor network, the speed of the sensor node and the threshold of the training symbol overhead of the packet may be estimated to reduce the overall energy consumption of the wireless sensor network.

Description

Wireless Sensor Network Control Method {Method of Controlling Wireless Sensor Network}

The present invention relates to a method for controlling a wireless sensor network, and more particularly, to estimate the total value of energy consumption of a wireless sensor network by estimating a speed of a sensor node and a threshold of training symbol overhead of a packet in a MIMO cooperative communication-based wireless sensor network. A wireless sensor network control method can be reduced.

A wireless sensor network (WSN) is a network designed to detect and collect information generated in a specific area and deliver it to a user through a wireless communication technique. A wireless sensor network is multi-hop to a data collection node whose sensor node collects various data over a distributed area, which is responsible for data recording, management, and delivering specific information to a desired user. Send the data.

Here, the sensor node may be integrated with the RF transceiver, the A / D and D / A converters, the baseband processor, and other application interfaces to perform one full function. Since these sensor nodes operate on small batteries, the life of the battery determines the lifetime of the network. Therefore, minimizing energy consumption is a very important consideration when designing wireless sensor networks.

In recent years, a technology for improving energy efficiency by applying a cooperative communication system based on MIMO (Multi-Input Multi-Output) has been proposed. The concept of MIMO-based cooperative communication and virtual antenna arrangement is to achieve MIMO performance in a network of single-input single-output (SISO) nodes using a single antenna. Research on energy efficiency and delay analysis has shown that MIMO-based cooperative communications outperform SISO after a certain distance.

However, since the conventional wireless sensor network technology using the cooperative communication system does not provide a method for analyzing the overhead of the training symbol that affects the energy consumption and the threshold value of the speed of the sensor node, the energy efficiency of the wireless sensor network is reduced. There is a limit to improving this.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-described problems, and in this case, the total energy consumption of the wireless sensor network can be reduced by estimating the speed of the sensor node and the threshold of the training symbol overhead of the packet in the MIMO cooperative communication-based wireless sensor network. It is an object of the present invention to provide a wireless sensor network control method.

Wireless sensor network control method according to the present invention for achieving the above object, in the wireless sensor network performing a multi-input multi-output (MIMO) based cooperative communication, collecting and transmitting data Calculating a change in energy consumption by changing a training symbol overhead of the data while maintaining a constant data transmission / reception rate between a sensor node and a data collection node for collecting data collected by the sensor node; Calculating a change amount of energy consumption by changing the data transmission / reception rate between the sensor node and the data collection node while maintaining a constant size of the training symbol overhead of the data; And determining the training symbol overhead and the speed for minimizing the energy consumption based on the energy consumption change amount according to the change of the training symbol overhead and the energy consumption change amount according to the speed change. do.

The determining of the training symbol overhead of the data may include: training the data while maintaining a constant data transmission / reception rate when performing single-input single output (SISO) based communication. Calculating an amount of change in energy consumption by changing the symbol overhead; And setting the training symbol overhead such that the energy consumption according to the training symbol overhead of the data is smaller than the energy consumption consumed in the single input single output communication.

The determining of the speed may include changing the data transmission / reception rate while maintaining a training symbol overhead of the data when performing single-input single-output (SISO) based communication. Calculating an amount of change in energy consumption; It is possible to include setting the speed such that the energy consumption according to the speed change has a value smaller than the energy consumption consumed in the single input single output communication.

로 나타낼 수 있으며, 여기서 R_b는 실제 비트율로서

로 대체될 수 있고, 트레이닝 심벌 pN_T는 채널을 추정하기 위해서 각각의 블록으로 삽입 되며, 블록 크기는 심벌 F로써

이고, 여기서 R_S는 심벌률이고 페이딩 간섭시간인

로 주어지고, 최대 도플러 쉬프트

로 주어지고, v는 속도이고, λ는 캐리어 파장이다.On the other hand, the energy consumption per bit is

Where R _b is the actual bit rate

The training symbol pN _T is inserted into each block to estimate the channel, and the block size is represented by the symbol F.

Where R _S is the symbol rate and fading interference time

Given by, shift up Doppler

Where v is the velocity and λ is the carrier wavelength.

로 나타내고, 전체적인 통신을 위한 비트당 평균 에너지는

로 나타내며, 상기 각각의 센서노드가 상기 데이터 수집노드로 전송하기 위한 비트 수 L _i 를 갖는 경우, 상기 모든 센서노드에서 상기 데이터 수집노드까지 데이터를 전달하기 위해서 필요한 전체 에너지는 <수학식>

를 통해 산출되는 것이 가능하다.In addition, the average energy per bit of the sensor node

The average energy per bit for the overall communication is

When each sensor node has the number of bits L _i for transmitting to the data collection node, the total energy required to transfer data from all the sensor nodes to the data collection node is represented by

It is possible to calculate through.

를 통해 산출되는 것이 가능하다.And, in the single-input single-output based wireless sensor network, the total energy required to transfer such data is expressed by Equation

It is possible to calculate through.

As described above, the wireless sensor network control method of the present invention enables estimating the speed of the data collection node and the threshold of the training symbol overhead.

Accordingly, the overall energy consumption of the wireless sensor network can be reduced.

Hereinafter, a wireless sensor network control method according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. However, in describing the present invention, when it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the subject matter of the present invention, a detailed description thereof will be omitted.

1 illustrates a configuration of a wireless sensor network (WSN).

The wireless sensor network is distributed and distributed to perform sensor node 20 for collecting and wirelessly transmitting various data, and to record and manage data received from the sensor node 20 and to transmit specific information to a desired user. It may be configured as a data collection node (sink node 30).

Here, the sensor node 20 forms a multi-input multi-output (MIMO), a multi-input single-output (MIS), a single-input multi-output (SIMO), and a single-input single-output (SISO) structure. can do.

The data collection node 30 may function as a coordinator for controlling data transmission and reception of the sensor node 20 in the cluster.

In a wireless sensor network having such a configuration, information collected from sensor nodes 20 in multiple regions is transmitted to the data collection node 30. If the data collection node 30 is far apart, the information will be sent first to the relay node, and then multi-hop based routing will be used to deliver the data to its final destination.

In the wireless sensor network, the transmitter and the receiver each have a transmitting antenna (N _T ) and a receiving antenna (N _R ), and on the transmitter side, N _T antennas are distributed to the N _T sensor nodes 20 so that they are multi-input for cooperative communication. Used as

In such a wireless sensor network, total energy consumption can be expressed as two important items. The total power consumption P _T is classified into the power consumption P _PA of all power amplifiers as a function of the transmission power P _OUT and the power consumption P _C of the other circuit blocks. This is represented by Equation 1 below.

Where P _PA is the amplifier power consumption and P _C is the circuit power consumption. The amplifier power consumption can be calculated by the following [Equation 2].

이고,

는 드레인 효율이고,

는 평균율의 최대값이다. 본 실시예에서는 비부호화 MQAM을 기반으로 분석을 하며 MQAM에서

이고 심벌당 비트 수(성상도 값)는

으로 정의된다. here

ego,

Is the drain efficiency,

Is the maximum value of the average rate. In this example, the analysis is based on an unsigned MQAM.

And the bits per symbol (constellation value)

Is defined.

은 다음의 [수학식 3]과 같이 표현될 수 있다.If the channel has a k-pass pass loss with additive white Gaussian noise (AWGN),

May be expressed as Equation 3 below.

는 주어진 BER(Bit Error Rate)값을 충족시키는데 필요한 비트당 평균 에너지이다. R_b는 전송 비트율이고, d는 전송거리이다. G_t와 G_r은 각각 송신기와 수신기 안테나 이득이고, λ는 캐리어 파장, N_l은 하드웨어 프로세스 변화와 배경 잡음을 보상하는 링크 마진이다. N_f는 수신기 잡음값이고, N_f=N_r/N₀로 정의된다. 여기서 N_r는 수신기 입력 측에서 잡음의 전력 스펙트럼 밀도(PSD; power spectrum density)이고, N₀는 실내 온도에서 단방향(single-sided) 온도 잡음 PSD이다.here,

Is the average energy per bit needed to meet the given Bit Error Rate (BER) value. R _b is the transmission bit rate and d is the transmission distance. G _t and G _r are the transmitter and receiver antenna gains respectively, λ is the carrier wavelength, and N _l is the link margin that compensates for hardware process variations and background noise. N _f is the receiver noise value and is defined as N _f = N _r / N ₀ . Where N _r is the power spectrum density (PSD) of noise at the receiver input side and N ₀ is the single-sided temperature noise PSD at room temperature.

On the other hand, in [Equation 1] showing the total power consumption (P _T ), the circuit power consumption P _C is the power consumption of the transmitter and receiver circuit.

2 is a circuit block diagram of a transmitter and FIG. 3 is a circuit block diagram of a receiver.

As shown in FIG. 2, the transmitter circuit includes a digital-to-analog converter (DAC) 210 for converting digital transmission data into an analog signal, a first transmission filter 212 for filtering the converted analog signal, A mixer 216 for mixing the filtered signal with a Local Oscillator (LO) signal 214, a second transmission filter 218 for filtering the mixed signal, and amplifying the filtered signal to an antenna Transmit amplifier (PA) 220 for transmitting through. Here, the first transmission filter 212 and the second transmission filter 218 may be configured using an active filter.

As shown in FIG. 3, the receiver circuit includes a first reception filter 310 for filtering a received signal, a low noise amplifier (LNA) 312 for amplifying the filtered received signal, and an amplified signal. A second receiver filter 314 for filtering, a mixer 316 for mixing a signal filtered through the second receiver filter 314 with a local oscillator (LO) 318 signal, and a mixture A third reception filter 320 for filtering the signal, an Iniermadiate Frequency Amplifier (IFA) 322 for amplifying the filtered signal, and an ADC (analog-to) for converting and outputting the amplified signal into a digital signal a digital converter 324. Here, the reception filters 310, 314, and 320 may be configured using an active filter.

In consideration of the detailed circuit configuration of the transmitter and the receiver, the circuit power consumption P _{C is represented} by the circuit power consumption P _ct of the transmitter and the circuit power consumption P _cr of the receiver as shown in Equation 4 below.

P _ct and P _cr are the circuit power consumptions of the transmitter and receiver, respectively. P _mix is the power consumption of the mixers 216 and 316, P _syn is the power consumption of the frequency synthesizer, P _filt is the power consumption of the active filters 212, 218, 310, 314 and 320 of the transmitter and receiver, and P _LNA is low noise. The power consumption of the amplifier 312, P _IFA represents the power consumption of the intermediate frequency amplifier 322, P _DAC represents the power consumption of the DAC 210, and P _ADC represents the power consumption of the ADC 324.

And, the total energy consumption per bit can be expressed as Equation 5 below.

로 대체될 수 있다. 트레이닝 심벌 pN_T는 채널을 추정하기 위해서 각각의 블록으로 삽입된다. 블록 크기는 심벌 F와 같고

이다. 여기서 R_S는 심벌률이고 T_C는 페이딩 간섭시간이다. 페이딩 간섭시간은

로 계산될 수 있다. 여기서 최대 도플러 쉬프트 f_m은

로 주어지고, v는 속도이고, λ는 캐리어 파장이다. 전체 에너지 소비는 E_bt에 곱과 전송되는 비트 수 L_i를 곱하여 계산된다. Where R _b is the actual bit rate,

Can be replaced with Training symbol pN _T is inserted into each block to estimate the channel. The block size is equal to the symbol F

to be. Where R _S is the symbol rate and T _C is the fading interference time. Fading interference time

It can be calculated as Where the maximum Doppler shift f _m is

Where v is the velocity and λ is the carrier wavelength. The total energy consumption is calculated by multiplying E _bt by the product and the number of transmitted bits L _i .

On the other hand, in the general wireless sensor network, information collected from sensor nodes 20 in multiple regions is transmitted to a remote central processor, that is, the data collection node 30. If the data collection node 30 is far apart, the information will be sent first to the relay node, and then multi-hop based routing will be used to deliver the data to its final destination. Taking advantage of the fact that MIMO (including MISO, SIMO, MIMO) can provide energy savings in the fading channel, the present invention enables cooperative communication using multiple sensor nodes 20, and multiple sensor nodes 20 ) Can be treated as multiple antennas of the destination node. The sensor node 20 serving as a cluster head among the sensor nodes 20 operates as a coordinator for cooperative communication in such a cluster-based wireless sensor network.

로 나타낼 수 있고, 전체적인 또는 장거리 통신을 위한 비트당 평균 에너지는

로 나타낼 수 있다. 각각의 센서노드(20)가 데이터 수집노드(30)로 전송하기 위한 비트 수 L _i 를 갖는다고 가정한다면, 모든 노드에서 데이터 수집노드(30)까지 데이터를 전달하기 위해서 필요한 전체 에너지는 다음의 [수학식 6]과 같이 표현될 수 있다.The energy consumption of the MIMO based cooperative communication network consists of two elements: energy required for local communication between sensor nodes 20 and energy required for long distance communication from sensor node 20 to data collection node 30. do. Average energy per bit per sensor node 20 for local communication

The average energy per bit for overall or long distance communication is

It can be represented as. Assuming that each sensor node 20 has the number of bits L _i to transmit to the data collection node 30, the total energy required to deliver data from all nodes to the data collection node 30 is It can be expressed as shown in Equation 6].

The present invention assumes that the maximum distance between two sensor nodes 20 is d _m meters and that the total communication distance d >> d _m . In addition, it is assumed that the distances from all the sensor nodes 20 to the data collection node 30 are the same.

In the SISO-based traditional wireless sensor network, the total energy required to deliver such data can be expressed as Equation 7 below.

는

일 경우의 MIMO 기반 통신의 특별한 경우로 간주할 수 있다.Here, the average energy per bit for transmitting from the sensor node 20 i to the data collection node 30

Is

One case may be regarded as a special case of MIMO based communication.

값을 알아야 한다. MQAM의 알라모티(Alamouti)구조를 이용하는 MIMO 시스템의 평균 BER 값은 다음의 [수학식 8]과 같이 주어진다.With this configuration, in order to obtain the total energy consumption value of the wireless sensor network, the average energy per bit required to satisfy a given bit error rate (BER)

You need to know the value. The average BER value of the MIMO system using the Alamouti structure of MQAM is given by Equation 8 below.

는 변수 H를 포함하는 기대값이고,

는

와 같이 정의되는 Q-함수이다. here

Is the expected value containing the variable H,

Is

Q-function defined as

의 값을 구한다. 여기서, 복잡성을 피하기 위해 알라모티 구조를 기반으로 하는 M-ary QAM의 2×2 MIMO 시스템을 예시하기로 한다. 알라모티 구조는 안테나 다이버시티 방식을 효율적으로 적용하기 위해 알라모티(Alamouti)에 의하여 제안된 시공간 블록부호 기법으로써, 송수신기에 다수의 안테나를 사용하여 무선채널에서의 페이딩을 극복하는 대표적인 송신 다이버시티 기술이다. In the present invention, using a numerical search method

Find the value of. Here, to avoid complexity, a 2 × 2 MIMO system of M-ary QAM based on the Alamoti structure will be illustrated. The Alamoti architecture is a space-time block coding technique proposed by Alamouti to efficiently apply the antenna diversity scheme, and is a representative transmit diversity technique that overcomes fading in a radio channel by using multiple antennas in a transceiver. to be.

In Rayleigh fading, the BER of the M-ary QAM MIMO system ( M = 2 ^b , b is even) is given by Equation 9 below.

항에 의존하고 경계조건은

이다. At constant speed, change the training symbol overhead (p) to find the change in energy consumption. It also predicts energy consumption by varying speed while maintaining constant training symbol overhead. When the speed is constant, the block size F is constant for a particular carrier frequency and the threshold of p is

Depend on terms and boundary conditions

to be.

For example, if the speed v = 5.82 m / s, the block size F is 87, and if p = 50, N _T = 2, the total energy consumption is greater than SISO, so it can be seen that the threshold is out of range.

In this way, we can find the threshold of the training symbol overhead and speed that provide MIMO cooperative communication with less energy consumption than SISO. Table 1 is an example of the threshold pairs of p and v obtained through the above experiments. If you lock one variable, the other value becomes its threshold.

TABLE 1

Training symbol overhead value, p Velocity, v ( m / s ) 10 24 15 16 20 12 25 09

As described above, the present invention analyzes the overall energy consumption in the case of MIMO based cooperative communication and SISO based cooperative communication of the wireless sensor network, and estimates the threshold of the training symbol overhead and speed, thereby making it possible to use an energy efficient wireless sensor. You can design your network.

Although the present invention has been described in detail with reference to exemplary embodiments above, those skilled in the art to which the present invention pertains can make various modifications to the above-described embodiments without departing from the scope of the present invention. Will understand. Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined not only by the claims below but also by the equivalents of the claims.

1 illustrates a configuration of a wireless sensor network (WSN),

2 is a circuit block diagram of a transmitter;

3 is a circuit block diagram of a receiver.

*** Explanation of symbols for the main parts of the drawing ***

 20: sensor node 30: data collection node

210: DAC 212: first transmission filter

214, 318: local oscillator 216, 316: mixer

218: second transmission filter 220: transmission amplifier

310: first receiving filter 312: low noise amplifier

314: second receiving filter 320: third receiving filter

322: intermediate frequency amplifier 324: ADC

Claims (6)

In the wireless sensor network control method for performing multi-input multi-output (MIMO) based cooperative communication, Training symbol overhead of data collected by all the sensor nodes is maintained while maintaining a constant data transmission / reception rate between one or more sensor nodes that collect and transmit data and a data collection node that collects data collected by all the sensor nodes. Calculating a change amount of energy consumption by changing; Calculating an energy consumption change amount by changing the data transmission / reception rate between all the sensor nodes and the data collection node while maintaining a constant size of the training symbol overhead of the data collected by all the sensor nodes; And determining the training symbol overhead and the speed for minimizing the energy consumption based on the energy consumption change amount according to the change of the training symbol overhead and the energy consumption change amount according to the speed change. Wireless sensor network control method. The method of claim 1, Determining the training symbol overhead of the data collected from all the sensor nodes, When performing Single-Input Single-Output (SISO) -based communication, the energy consumption change amount is changed by changing the training symbol overhead of the data collected from all the sensor nodes while maintaining the data transmission / reception rate constant. Calculating a; And setting the training symbol overhead such that the energy consumption according to the training symbol overhead of the data collected by all the sensor nodes has a value smaller than the energy consumption consumed in the single input single output communication. Wireless sensor network control method. The method of claim 1, Determining the speed, When performing single-input single-output (SISO) -based communication, the amount of change in energy consumption by changing the data transmission / reception rate while maintaining a constant training symbol overhead of data collected by all the sensor nodes. Calculating a; And setting the speed such that the energy consumption according to the speed change is smaller than the energy consumption consumed in the single input single output communication. The method of claim 1, Energy consumption per bit, &Lt; Equation &

Where P _PA is the power consumption of the amplifier and P _C is the power consumption of the circuit. Where R _b is the actual bit rate

The training symbol pN _T is inserted into each block to estimate the channel, and the block size is represented by the symbol F.

Where R _S is the symbol rate and fading interference time

Given by, shift up Doppler

Where v is velocity and λ is the carrier wavelength. The method of claim 1, The average energy per bit of each sensor node

The average energy per bit for the overall communication is

When each sensor node has the number of bits L _i to transmit to the data collection node, the total energy required to transfer data from all the sensor nodes to the data collection node is  &Lt; Equation &

Where N _T is the number of transmit antennas transmitted simultaneously on the sensor node. Wireless sensor network control method, characterized in that calculated through. The method according to claim 2 or 3, In the single input single output based wireless sensor network, the total energy required to deliver the data collected from all the sensor nodes is &Lt; Equation &

Where N _T is the number of transmit antennas transmitted simultaneously from the sensor node, L _i is the number of bits for each sensor node to transmit to the data acquisition node,

Is the average energy per bit to transmit from sensor node i to data collection node) Wireless sensor network control method, characterized in that calculated through.

Images