CN101729105A - Power control structure and method thereof based on game theory model in network - Google Patents

Abstract

A power control structure and method based on a game theory model in a network, used to calculate the transmission power that a node in the network should use to send a message to an adjacent node, the structure includes a physical layer SNR calculation module and a power control module, And the received message processing module and the adjacent node information table of the network layer. The method includes: establishing an adjacent node information table, recording the adjacent node ID, the interference power value of the adjacent node, the distance between the adjacent node and the node, and the income of sending messages with this transmission power; when the node sends When sending a message, according to the adjacent node information table, the interference value of the adjacent node corresponding to the maximum value of the income of sending the message with this transmission power and the distance value between the adjacent node and the node are obtained, and the transmission power that should be used is calculated. power. On the premise of maximizing the network capacity and minimizing the network radius, the present invention reduces the transmission power of the nodes as much as possible, thereby reducing the energy consumption of the nodes and prolonging the survival time of the network.

Description

Power Control Structure and Method Based on Game Theory Model in Networks

【Technical field】

The present invention relates to a power control structure and method based on a game theory model in a network, more specifically, to a power control structure and method based on a game theory model applied in an Ad Hoc network.

【Background technique】

As a key technology in wireless Ad hoc networks, power control plays an irreplaceable role in effectively using and managing wireless resources. In terms of power control, many algorithms and protocols have been proposed. In a wireless Ad hoc network, the transmit power of a node determines which nodes in the network can receive signals, thus affecting the connectivity of the network. At the same time, due to the existence of hidden terminals, the transmit power of a node also affects the The size of the interference caused by the hidden terminal, so adjusting the transmit power of the nodes will have an important impact on the performance of the entire network. When designing the power control algorithm, the resulting impact on network performance must be considered to be considered.

若节点i与节点j间的距离可以用跳数h_ij表示，用H表示节点间跳数集合，H＝{_ij}，i，j∈V，则网络半径R_G可以表示为R_G＝min(H)，e_i表示节点i的剩余能量，则功率控制问题的数学模型可以描述为：In an Ad hoc network, the essence of power control is how to make use of limited network information and adjust the transmit power of nodes under the conditions of limited node energy, channel attenuation, and shared channels to maximize network connectivity and capacity. , The target with the smallest network radius is a very difficult problem. If C _i is used to represent the capacity or transmission rate of link l _i (l _i ∈ E′), then the network capacity or its bottleneck bandwidth can be expressed as

If the distance between node i and node j can be represented by the number of hops h _ij , and H is used to represent the set of hops between nodes, H={ _ij }, i, j∈V, then the network radius R _G can be expressed as R _G =min (H), e _i represents the remaining energy of node i, then the mathematical model of the power control problem can be described as:

${\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; C</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; P</span>}}{\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; (</span>\underset{{\mathrm{<span\; class="notranslate">\; l</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; E.</span>}}{\mathrm{<span\; class="notranslate">\; min</span>}}<span\; class="notranslate">\; \{</span>{\mathrm{<span\; class="notranslate">\; C</span>}}_{{\mathrm{<span\; class="notranslate">\; I</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; \}</span><span\; class="notranslate">\; )</span>$

(1)

${\mathrm{<span\; class="notranslate">\; f</span>}}_{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; P</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; P</span>}}{\mathrm{<span\; class="notranslate">\; min</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; G</span>}}<span\; class="notranslate">\; )</span>$

$\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; .</span>\left\{\begin{array}{c}{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ></span>{\mathrm{<span\; class="notranslate">\; e</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; V</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; <</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; \&le;</span>\mathrm{<span\; class="notranslate">\; 2</span>}\\ \mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&le;</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; max</span>}}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; ,</span><span\; class="notranslate">\; |</span>\mathrm{<span\; class="notranslate">\; V</span>}<span\; class="notranslate">\; |</span>\end{array}\right.$

Among them, e ₀ is the node remaining energy threshold, when the node remaining energy is less than this value, the node will turn off its wireless receiving module.

At present, most of the power control algorithms or protocol research focuses on reducing the power of nodes to transmit messages to achieve the purpose of energy saving, and it is believed that reducing the power of nodes to transmit messages can reduce the mutual interference between nodes and increase the network capacity. Purpose. But recent research suggests otherwise. Literature Behzad, A., Rubin, I..Impact of power control on the performance of ad hoc wireless networks.in Proc.INFOCOM 2005, Miami, FL, USA.2005.102-113, Behzad and Rubin on power control in Ad hoc networks The influence of the maximum throughput of the network is studied, and it is concluded that the throughput between the source node and the destination node has nothing to do with the node distribution, business load and business mode, and the maximum transmission power between the source node and the destination node can be obtained by increasing the node transmission power. throughput. Literature Qiang Sun, Layuan Li, Niansheng Chen, SadiaAziz, Impact of Power Control on Wireless Ad Hoc Network Capacity.Workshop Proceedings of the Third IEEE International Conference on Distributed Computing in Sensor Systems(DCOSS 07), Santa Fe, A NewMexico .2007, pp.73-82. analyzed the impact of the interference generated by nodes transmitting messages on network capacity. The results show that increasing the transmit power of nodes can not only reduce node interference but also improve network capacity. Since the Ad hoc network does not have the support of the base station, the communication method adopts a multi-hop method, and the network topology changes dynamically, it is difficult for a node to obtain relevant information about other nodes in the network. maximization strategy.

In summary, the prior art has the following shortcomings and deficiencies:

(1) Without considering the fully distributed structural characteristics of the Ad hoc network, a centralized algorithm is used to realize power control;

(2) The impact of power control on network performance such as network connectivity and network capacity is not considered;

(3) The revenue function is proposed according to a specific channel model (such as orthogonal CDMA or orthogonal FDMA channel), and cannot be used universally.

In recent years game theory has been used as a tool to study different aspects of computer networks and wireless communication networks, and has been used to solve problems in traditional wired networks. Because in the wireless cellular network, the global information of the network can be obtained through the base station, so the centralized algorithm can be adopted. As for the Ad hoc network, its dynamically changing network environment makes it very difficult for nodes to obtain global network information, so that it is unrealistic. Therefore, the mobile node can only decide what kind of behavior it should take according to the local information of the network (the information of its adjacent nodes), and a certain behavior of the mobile node must bring certain results to itself or to the entire network. If we use utility to express this result, then the interaction between nodes in the Ad hoc network can be described by a non-cooperative game model, that is, each node chooses an action to maximize its own income according to the current network environment.

Therefore, the present invention proposes an application of non-cooperative game theory to solve the power control problem in the Ad hoc network.

【Content of invention】

The purpose of the present invention is to provide a power control structure and method based on a game theory model in the network, which can reduce the transmission power of nodes as much as possible under the premise of maximizing network capacity and minimizing network radius, thereby reducing energy consumption of nodes. Extend the life time of the network, and has universality.

In order to realize the aforesaid object of the present invention, the present invention provides a kind of power control structure based on game theory model in the network, is used for calculating the transmit power that a node should adopt to send message to an adjacent node, and this structure comprises: The SNR calculation module and the power control module of the network layer and the received message processing module of the network layer are characterized in that: the information exchange of the structure is a cross-layer information exchange, and the structure also includes an adjacent node information table positioned at the network layer. To record the adjacent node ID, the interference power value of the adjacent node, the distance between the adjacent node and the node, and the income of using this transmission power to send the message; the SNR calculation module judges the message that the adjacent node sends to the node Whether the message is a valid message, if it is a valid message, the message frame is uploaded; the received message processing module is used to analyze the adjacent node ID in the message, the interference power value of the adjacent node, the adjacent The distance between the node and the node and the income information of sending messages with this transmission power, and store the parsed information in the adjacent node information table; the power control module based on the interference power value of the adjacent node and the adjacent node The distance value between the node and the node calculates the transmission power that the node should use to send messages to the adjacent nodes.

The present invention also provides a power control method based on a game theory model in the network, which is used to calculate the transmission power that a node in the network should use to send a message to an adjacent node. It is characterized in that: the method includes the following steps:

Establishing an adjacent node information table at the network layer for recording the adjacent node ID, the interference power value of the adjacent node, the distance between the adjacent node and the node, and the income of sending messages with this transmission power;

When a node sends a message to the adjacent node, according to the adjacent node information table, the interference value of the adjacent node corresponding to the maximum value of the income of sending the message with this transmission power and the adjacent node and the node are obtained. The distance value between them, and use the following equation to calculate the size of the transmit power that should be used:

${\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; \&mu;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}}{\mathrm{<span\; class="notranslate">\; ln</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; infer</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}$

Among them, μ is the profit coefficient, p _infer ^j represents the interference power value of the adjacent node, the hop number h _ij represents the distance between the node and the adjacent node, and σ(t) ² represents the thermal noise power.

Compared with the prior art, the power control structure and method based on the game theory model in the network of the present invention are designed for the optimization of two indexes of network capacity and network radius. On the premise of maximizing the network capacity and minimizing the network radius, the present invention reduces the transmission power of the nodes as much as possible, thereby reducing the energy consumption of the nodes and prolonging the survival time of the network. The present invention adopts a distributed algorithm, which can work only with local information, so that it can well adapt to the fully distributed characteristics of the Ad hoc network, and overcomes the shortcomings of the centralized algorithm; The income function has universality; the present invention introduces network connectivity and network capacity factors into the design of the income function, thereby realizing the optimization of channel capacity, network radius and node transmission power. It improves the network capacity and prolongs the life time of nodes and network.

In order to make the above and other purposes, features, and advantages of the present invention more obvious and understandable, the detailed description is as follows in conjunction with the accompanying drawings:

【Description of drawings】

Accompanying drawing 1 is the schematic diagram of the power control structure based on game theory model in the network of the present invention;

Accompanying drawing 2 is a schematic diagram of the adjacent node information table of the power control structure based on the game theory model in the network of the present invention.

【Detailed ways】

The technical content of the present invention will be described in detail below with reference to the accompanying drawings.

Please refer to Fig. 1, the power control structure 100 based on game theory model in a kind of network of the present invention, is used for calculating the transmission power that a node should adopt to send message to an adjacent node in the Ad hoc network, this structure comprises: The SNR calculation module 11 of layer 1, the interference calculation module 12 and the power control module 13, the adjacent node information table 31 of the MAC layer 2 and the network layer 3, the local node information table 32, the received message processing module 33 and the sent message In the processing module 34, the information exchange of the power control structure 100 based on the game theory model in the network of the present invention is cross-layer information exchange.

Many nodes are included in the Ad hoc network. For example, when a node i receives a message frame from an adjacent node j, the SNR calculation module 11 judges whether the message frame is valid by calculating the signal-to-noise ratio of the message frame message. For example, if the signal-to-noise ratio SNR(T) of the message frame is greater than or equal to a signal-to-noise ratio threshold γ ₀ , the message frame is considered to be a valid message. If it is a valid message, send the message frame to the upper layer for processing, and calculate the distance between the node i and the adjacent node j that sent the message frame, and send it to the network layer 3. Otherwise, if the signal-to-noise ratio SNR(t) of the message frame is less than the signal-to-noise ratio threshold γ ₀ , then the message frame is an interference signal, and node i discards the message frame, and runs the interference calculation module 12, It is used to calculate and obtain the interference power value received by the node i.

Please refer to FIG. 2 , the adjacent node information table 31 is used to record the adjacent node ID, the interference power value of the adjacent node, the distance between the adjacent node and the node, and the income of sending messages with this transmission power. The form of the local node information table 32 is shown in FIG. 1 , which is used to record the interference power value of the interference received by each node in the network itself, for example, storing the interference power value received by node i calculated by the interference calculation module 12 . When node i serves as a sending node to send a message to adjacent node j, it will add the interference power value of node i itself when sending the message. Similarly, when adjacent node j serves as a sending node to send a message to node i, it will also add the interference power value of node j itself when sending the message.

The received message processing module 33 is used to analyze the adjacent node ID in the message, the interference power value of the adjacent node, the distance between the adjacent node and the node, and the information on the income of using this transmission power to send the message. The resolved information is stored in the adjacent node information table 31 . The sending message processing module 34 is used to obtain the interference power value of the neighboring node and the distance value between the neighboring node and the node from the neighboring node information table 31 , and send them to the power control module 13 . In another embodiment, the SNR calculation module 11 can directly obtain the ID of the adjacent node, the interference power value of the adjacent node, the distance between the adjacent node and the node, and the benefit of using this transmission power to send the message through calculation. The information is uploaded to the network layer 3 and stored in the adjacent node information table 31.

The power control module 13 calculates, according to the interference power value of the adjacent node and the distance value between the adjacent node and the node, the transmit power that the node should use to send messages to the adjacent node.

A power control method based on a game theory model in a network of the present invention is used to calculate the transmission power that a node in the network should use to send a message to an adjacent node. The power control method based on a game theory model in the network of the present invention first needs to be The network layer 3 establishes an adjacent node information table 31 . Adjacent node j establishes an adjacent node information table 31 by periodically sending HELLO messages to node i.

Establishing the adjacent node information table 31 includes the following steps:

Step 1: Set the initial transmission power p _i of each node to the maximum power p _max , and send an initial message with this maximum power p _max , the value of the interference power p _infer ⁱ of the node itself in the initial message is zero, and initialize the phase Adjacent node information table 31.

Step 2: When node i receives a message frame from neighboring node j, the SNR calculation module 11 judges whether the message frame is a valid message. If it is a valid message, upload the message frame and proceed to step three; otherwise, the message frame is an interference signal, and node i discards the message frame and proceed to step four.

Step 3: the message processing module 33 of the network layer 3 parses the message, obtains the adjacent node ID, the interference power value of the adjacent node and the distance between the adjacent node and the node and the income of using this transmission power to send the message information, and store the parsed information in the adjacent node information table 31.

Step 4: run the interference calculation module 12, calculate and obtain the interference power value of the interference received by the node i, and upload it to the local node information table 32 of the network layer.

Among them, the revenue of node i using this transmission power to send messages is calculated according to the following formula:

u _i ＝μlog ₂ (1+SIR _i )-c(p _i ) (1)

Calculate the income of node i to send messages with this transmit power, and update the adjacent node information table 31, where c(p _i ) is the linear cost function of transmit power, SIR _i is the signal-to-interference ratio of the node, and its value is given by The formula is obtained:

${\mathrm{<span\; class="notranslate">\; SIR</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ik</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; infer</span>}}^{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span>$

p _infer ⁱ represents the interference power value of the interference signal received by the node i, with k represents an interfering node.

The quality of a wireless network is often affected by factors such as signal modulation methods and coding methods used by nodes. Different types of modulation methods and coding methods will have different effects on the channel. The income function formula (1) of the power control method based on the game theory model in the network of the present invention simplifies the design of the income function and does not depend on the node physical layer signal processing mode.

c(p _i ) is the linear cost function of the transmit power. The performance of the system can be improved by introducing a cost function into the power control method based on the game theory model in the network of the present invention. The cost function is usually defined as an increasing function of user transmission power. The cost function is usually divided into two categories: linear cost function and nonlinear cost function. The linear cost function has the advantages of simple form, low computational complexity, and can be realized by distributed algorithms, but it usually cannot reach the global optimum. The nonlinear cost function can achieve the global optimum, but its operation is more complicated, and it can only be realized by centralized solution, so it is not suitable for Ad hoc network. Therefore, the power control method based on the game theory model in the network of the present invention uses a linear cost function here. Considering the network radius we adopt the following cost function:

$\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}$

Where h _i is the path gain when the node transmits with power p _i , usually represented by the distance between the transmitting node and the receiving node.

If the power control problem of nodes in the Ad hoc network is regarded as a non-cooperative game problem, the basic formula of the game can be used to express it as: Г=<N, A, {u _i }>. In the power control problem, the strategy space of each node is expressed as A _i =[0,p _max ]. N={1, 2,...,n} means all the nodes in the network, and {u _i } means the expected income of the node using the income function set. Each node in the network determines the strategy that maximizes its own income according to the income function, that is,

$\underset{{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Element;</span>{\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}{\mathrm{<span\; class="notranslate">\; max</span>}}{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1,2</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; \&CenterDot;</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}$

p _i represents the transmit power selected by node i, and p _-i represents the transmit power selected by nodes other than i.

Utilizing the power control method based on the game theory model in the network of the present invention, when node i sends a message to the adjacent node j, the sending message processing module 32 obtains from the adjacent node information table 31 and obtains the transmission power using the transmission power For the maximum value of the income of the message, select the interference value of the adjacent node corresponding to the maximum value of the income and the distance value between the adjacent node and the node, and send it to the power control module 13 . The power control module 13 uses the following equation to calculate the size of the transmit power that should be used:

${\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; \&mu;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}}{\mathrm{<span\; class="notranslate">\; ln</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; infer</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

Where μ is the profit coefficient, p _infer ^j represents the interference power value of the adjacent node j, the hop number h _ij represents the distance between the node i and the adjacent node j, and σ(t) ² represents the thermal noise power.

When node i serves as the sending node to send messages to adjacent node j, each message includes a field for storing the interference power value of the node itself. For example, each HELLO message includes a field storing the interference power value of the node itself. The sending message processing module 32 obtains the interference power value of the node i itself from the local node information table 32, and adds the interference power value of the node i itself in the sending message.

Similarly, when adjacent node j serves as a sending node to send a message to node i, it will also add the interference power value of node j itself when sending the message.

Obtain the calculating equation of the transmission power of the present invention by following principle:

Since the strategy space of each node is defined on the interval [0, p _max ], the strategy space A is a non-empty, closed and bounded convex set in Euclidean space. u _i (p) is continuous on p, and has

$\frac{<span\; class="notranslate">\; \&PartialD;</span>{\mathrm{<span\; class="notranslate">\; u</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; )</span>}{<span\; class="notranslate">\; \&PartialD;</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; \&mu;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}{\mathrm{<span\; class="notranslate">\; ln</span>}\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&sigma;</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; infer</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}}\frac{<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; b</span>}<span\; class="notranslate">\; \&PlusMinus;</span>\sqrt{{\mathrm{<span\; class="notranslate">\; b</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 4</span>}\mathrm{<span\; class="notranslate">\; ac</span>}}}{\mathrm{<span\; class="notranslate">\; 2</span>}\mathrm{<span\; class="notranslate">\; a</span>}}$

According to the maximum value theorem, the calculation method of transmitting power of node I is obtained

${\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; \&mu;</span>}{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}}{\mathrm{<span\; class="notranslate">\; ln</span>}\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>\frac{\mathrm{<span\; class="notranslate">\; \&sigma;</span>}{<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; p</span>}}_{\mathrm{<span\; class="notranslate">\; infer</span>}}^{\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}{{\mathrm{<span\; class="notranslate">\; h</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

The power control method based on the game theory model in the network of the present invention is described as follows:

PROCEDURE Init

while t=0

do

p _i =P _max

p ⁱ _infer =0

Initialize(other_table) (initialize adjacent node information table)

end while

PROCEDURE HandleMessage(HELLO)

while i receive HELLO

do

refresh(other_table) (update adjacent node information table)

end while

PROCEDURE Send(M)

while i sends M

do

u←find_payoff(other_table) (get the maximum gain from the adjacent node information table)

p _i ←compute_trans_power(u) (calculate transmit power)

if M=HELLO

then add_infer_field(p ⁱ _infer ) (add the interference power plant of the local node)

end if

end while

The power control structure and method based on the game theory model in the network of the present invention are designed for the optimization of two indexes of network capacity and network radius. On the premise of maximizing the network capacity and minimizing the network radius, the present invention reduces the transmission power of the nodes as much as possible, thereby reducing the energy consumption of the nodes and prolonging the survival time of the network. The present invention adopts a distributed algorithm, which can work only with local information, so that it can well adapt to the fully distributed characteristics of the Ad hoc network, and overcomes the shortcomings of the centralized algorithm; The income function has universality; the present invention introduces network connectivity and network capacity factors into the design of the income function, thereby realizing the optimization of channel capacity, network radius and node transmission power. It improves the network capacity and prolongs the life time of nodes and network.

Claims (17)

1. In the network based on the Poewr control method of game theoretical model, be used for computing network one node and send the transmitting power that message should adopt to adjacent node, it is characterized in that this method may further comprise the steps:

   Set up the adjacent node information table in network layer, be used to write down interference power values, adjacent node and this internodal distance of described adjacent node ID, adjacent node and adopt this transmitting power to send the income of message;

   When node when described adjacent node sends message, according to the adjacent node information table, interference value and adjacent node and this internodal distance value of pairing this adjacent node of maximum of the income of this transmitting power transmission message of acquisition employing, and adopt following equation to calculate the size of the transmitting power that should adopt:

   $p_i=\frac{{\mathrm{\&mu;h}}_{\mathrm{ij}}}{\ln 2}-\frac{\mathrm{\&sigma;}{\left(t\right)}^2+p_{\mathrm{infer}}^j\left(t\right)}{h_{\mathrm{ij}}\left(t\right)}$

   Wherein μ is the income coefficient, p _Infer ^jThe interference power values of representing this adjacent node, jumping figure h _IjRepresent the distance between this node and described adjacent node, σ (t) ²The expression thermal noise power.
2. 2. the method for claim 1, it is characterized in that: the Initial Trans of setting each node is a maximum power, and sends initial message with this maximum power, the interference power values of node itself is zero in the initial message.
3. 3. the method for claim 1, it is characterized in that: also be included in physical layer one SNR computing module is provided, when node is received the message frame of described adjacent node transmission, utilize the SNR computing module to judge whether this message is effective message, if effectively message is then uploaded message frame.
4. 4. the method for claim 1, it is characterized in that: also be included in physical layer one SNR computing module is provided, when node is received the message frame of described adjacent node transmission, utilize the SNR computing module to judge whether this message is effective message, if effective message, directly by calculating interference power values and adjacent node and this internodal distance that obtains described adjacent node ID, adjacent node and adopting this transmitting power to send the information of the income of message, be uploaded to network layer, be stored in the adjacent node information table.
5. 5. method as claimed in claim 3, it is characterized in that: also be included in physical layer one interference calculation module is provided, if the SNR computing module judges that this message is an interference signal, this interference signal is sent to the interference calculation module, calculates by the interference calculation module and obtain the interference power values that this node is received this interference signal.
6. 6. method as claimed in claim 5 is characterized in that: when this node is received message, then according to formula u _i=μ log ₂(1+SIR _i)-c (p _i) computing node adopts this transmitting power to send the income of message and upgrade the adjacent node information table, c (p wherein _i) be the linear cost function of transmitted power, SIR _iBe the signal interference ratio of this node, its value is tried to achieve by following formula:

   

   p _Infer ⁱThe interference power values of representing the interference that this node is received.
7. 7. method as claimed in claim 5 is characterized in that: also be included in network layer one local node information table is provided, itself receive the interference power values of interference in order to write down in described node and the adjacent node each node.
8. 8. method as claimed in claim 5, it is characterized in that: if this node sends message as sending node to adjacent node, if perhaps described adjacent node sends message as sending node to this node, in message, add the interference power values of sending node itself.
9. 9. method as claimed in claim 8 is characterized in that: comprise a territory of preserving the interference power values of node itself in each message.
10. 10. method as claimed in claim 3, it is characterized in that: also being included in network layer provides one to receive message processing module (MPM), in order to analytic message, the interference power values of described adjacent node ID, adjacent node and adjacent node and this internodal distance and the information that adopts this transmitting power to send the income of message obtain by analytic message, receive message processing module (MPM) with the information stores that is resolved to the adjacent node information table.
11. 11. any described method as in the claim 1 to 10 is characterized in that: described adjacent node sends the HELLO message by the cycle to described node and sets up the adjacent node information table.
12. 12. method as claimed in claim 11, it is characterized in that: also be included in physical layer one power control module is provided, calculate this node according to the interference power values of this adjacent node and adjacent node and this internodal distance value and send the transmitting power that message should adopt to adjacent node.
13. 13. method as claimed in claim 12, it is characterized in that: also being included in network layer provides one to send message processing module (MPM), in the adjacent node information table, obtain interference power values and adjacent node and this internodal distance value of this adjacent node, and send to this power control module.
14. 14. in the network based on the power control structure of game theoretical model, be used to calculate a node and send the transmitting power that message should adopt to an adjacent node, this structure comprises: the SNR computing module and the power control module that are positioned at physical layer, and network layer receive message processing module (MPM), it is characterized in that: the information interchange of this structure is to stride a layer information interchange, this structure also comprises the adjacent node information table that is positioned at network layer, is used to write down described adjacent node ID, the interference power values of adjacent node, adjacent node is with this internodal distance and adopt this transmitting power to send the income of message; The SNR computing module judges whether the message that adjacent node sends to this node is effective message, if effective message is then uploaded message frame; Receive message processing module (MPM) in order to interference power values, adjacent node and this internodal distance of the described adjacent node ID in the analytic message, adjacent node and adopt this transmitting power to send the information of the income of message, and with the information stores that is resolved to the adjacent node information table; Power control module calculates this node according to the interference power values of this adjacent node and adjacent node and this internodal distance value and sends the transmitting power that message should adopt to adjacent node.
15. 15. structure as claimed in claim 14, it is characterized in that: physical layer is provided with an interference calculation module, be connected with the SNR computing module, if the SNR computing module judges that this message is an interference signal, this interference signal is sent to the interference calculation module, and the interference calculation module obtains the interference power values that this node is received in order to calculate.
16. 16. structure as claimed in claim 15 is characterized in that: network layer is provided with a local node information table, in order to write down the interference power values of the interference that each node is received in described node and the adjacent node itself.
17. 17. structure as claimed in claim 16, it is characterized in that: network layer is provided with one and sends message processing module (MPM), in the adjacent node information table, obtain interference power values and adjacent node and this internodal distance value of this adjacent node, and send to this power control module.

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