CN111132261A - Power control, relay selection and time slot allocation method based on gait cycle - Google Patents

Power control, relay selection and time slot allocation method based on gait cycle Download PDF

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CN111132261A
CN111132261A CN201911217864.8A CN201911217864A CN111132261A CN 111132261 A CN111132261 A CN 111132261A CN 201911217864 A CN201911217864 A CN 201911217864A CN 111132261 A CN111132261 A CN 111132261A
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time slot
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CN111132261B (en
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柯峰
刘堃钤
彭一鸣
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South China University of Technology SCUT
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/12—Communication route or path selection, e.g. power-based or shortest path routing based on transmission quality or channel quality
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W40/00—Communication routing or communication path finding
    • H04W40/02—Communication route or path selection, e.g. power-based or shortest path routing
    • H04W40/22—Communication route or path selection, e.g. power-based or shortest path routing using selective relaying for reaching a BTS [Base Transceiver Station] or an access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/24—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters
    • H04W52/242—TPC being performed according to specific parameters using SIR [Signal to Interference Ratio] or other wireless path parameters taking into account path loss
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0446—Resources in time domain, e.g. slots or frames
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0473—Wireless resource allocation based on the type of the allocated resource the resource being transmission power
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W84/00—Network topologies
    • H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

Abstract

The invention discloses a power control, relay selection and time slot allocation method based on a gait cycle, which comprises the following steps: the sensor node detects the periodicity of the channel condition change, calculates the gait cycle and predicts the channel condition of the next cycle; dividing a gait cycle into more than two subframes, representing the channel condition by average channel path loss for each subframe, screening out candidate relays for each sensor node according to the channel condition, and then combining a power control algorithm to obtain a relay selection scheme with minimized network total energy consumption; after obtaining the relay node of each sensor for each subframe, in order to ensure that the time delay does not exceed the time length of one subframe, the time slot of the relay node needs to be arranged after the time slot of the source node, and under the constraint, a time slot allocation scheme with minimum network total energy consumption is obtained by combining a power control algorithm. The invention can minimize the total energy consumption of the whole network and ensure the stability of transmission.

Description

Power control, relay selection and time slot allocation method based on gait cycle
Technical Field
The invention relates to wireless body area network communication, in particular to a power control, relay selection and time slot allocation method based on a gait cycle.
Background
With the development of wireless communication technology, wireless body area network technology is gradually applied to a plurality of fields in recent years, and particularly, physiological indexes of patients can be monitored in real time, which also provides a technical basis for the development of intelligent medical treatment. The wireless body area network is a near-human body wireless sensor network and consists of a plurality of sensor nodes for sensing and acquiring human body information and a central node serving as a coordinator. After the sensor node collects physiological data of a human body, the data needs to be wirelessly transmitted to the central node, and then the central node uploads the data to the cloud. Since the sensor nodes have a small size, the capacity of the battery is very limited, and the battery replacement is very troublesome, improving the energy efficiency becomes a primary consideration in the body area network technology. .
In the past research of wireless body area networks, methods such as relay transmission and power control are often used to improve the energy efficiency of the body area network. The relay transmission is mainly used for improving the condition that the channel between some sensor nodes and the central node is poor and is not suitable for direct transmission. The power control is to adjust the transmission power of the sensor node, so that the energy consumption of the sensor node is reduced as much as possible on the premise of ensuring the reliability of transmission. Hussein Moosavi et al propose an optimal relay selection and power control algorithm based on the game theory, which selects the best relay node for each node according to the statistical characteristics of the channel and adjusts the transmission power thereof, so that the energy efficiency of the whole network is maximized. However, the algorithm ignores the dynamic variability of the channel, the channel condition of the communication link in the body area network is frequently changed due to the movement of the human body, and the fixed relay and transmission power can not adapt to the dynamic variability of the channel. Therefore, the relaying and power of each sensor node needs to be continuously adjusted as the condition of the channel changes.
Since the motion of the human body is mostly periodic, for example: walking and running, etc., the channel conditions in the body area network may also change periodically. The method has the defect that in a network with many sensors, different sensors inevitably detect peaks at the same time, and collision occurs when the sensors transmit simultaneously.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a power control, relay selection and time slot allocation method based on gait cycles, which predicts the channel condition of the next cycle according to the statistical characteristics of the channels of the previous cycles after detecting the periodicity of the channels, selects the most appropriate relay node for each sensor node based on the predicted channel condition, enables the sensor node to transmit data in the time slot with good channel condition through reasonable time slot allocation, and adjusts the transmission power of each sensor node, so that the whole body area network can meet the requirement of transmission reliability and improve the energy efficiency as much as possible.
The purpose of the invention is realized by the following technical scheme:
a power control, relay selection and time slot allocation method based on a gait cycle comprises the following steps:
step 1: the sensor node detects the periodicity of the channel condition change, calculates the gait cycle and predicts the channel condition of the next cycle;
step 2: dividing a gait cycle into more than two subframes, representing the channel condition by average channel path loss for each subframe, screening out candidate relays for each sensor node according to the channel condition, and then combining a power control algorithm to obtain a relay selection scheme with minimized network total energy consumption;
and step 3: after obtaining the relay node of each sensor for each subframe, in order to ensure that the time delay does not exceed the time length of one subframe, the time slot of the relay node needs to be arranged after the time slot of the source node, and under the constraint, a time slot allocation scheme with minimum network total energy consumption is obtained by combining a power control algorithm.
The step 1 comprises the following sub-steps:
step 1-1: the sensor node carries out periodic detection of channel condition change on a section of past sample data, and calculates the gait cycle;
step 1-2: and after the gait cycle is detected, predicting the channel condition of the next cycle by adopting a cycle moving average method.
The step 2 comprises the following sub-steps:
step 2-1: calculating an average channel path loss for each subframe to represent channel conditions;
step 2-2: screening a candidate relay set for each sensor node according to the channel condition, wherein the screening condition is that the sensor node can find a multi-hop link transmitted to the central node through the candidate relay, and the channel path loss of each hop of the link is lower than the direct transmission link from the sensor node to the central node;
step 2-3: and traversing all combinations of relay selection, combining a power control algorithm, calculating the total energy consumption of the network, and selecting the optimal relay combination to minimize the energy consumption of the network.
The step 3 comprises the following sub-steps:
step 3-1: dividing the sensor nodes into class A nodes and class B nodes; the class-A node is a node which is directly transmitted to the central node without the help of a relay and is not used as a relay of other nodes, and the class-B node is a node which is transmitted by the help of a relay and is used as a relay of other nodes;
step 3-2: for the node B, the time slot allocated by the constraint relay node is required to be behind the time slot allocated by the source node when the time slot of each subframe is allocated;
step 3-3: allocating a time slot with the minimum channel path loss in the selectable time slots for the class B node, calculating the total energy consumption of the class B node by adopting a power control method, then calculating the energy consumption required by the class A node for sending data in each remaining time slot by combining a power control algorithm to form a utility matrix, solving an optimal allocation scheme by adopting a Hungary algorithm to obtain the minimum total energy consumption allocated by the class A node in the remaining time slots, and further obtaining the total energy consumption of the network; since the result of allocating the best currently selectable time slot to the class B node is influenced by the allocation order of the class B node, it is necessary to traverse the allocation order of any class B node, repeat the above steps to calculate the total energy consumption, and finally select the time slot allocation scheme with the smallest total energy consumption.
The power control, relay selection and time slot allocation method based on the gait cycle is based on an MAC protocol of a superframe structure, and the superframe structure is shown in figure 2 and is divided into three stages:
and an uplink beacon phase: the sensor node transmits the channel condition of each communication link to the central node in a beacon frame mode;
a downlink beacon stage: the method comprises the steps that a central node broadcasts a beacon frame, wherein the beacon carries time slot information distributed to each sensor node, a transmission destination node of each time slot and information of transmission power;
and (3) a data transmission stage: the stage is divided into more than two subframes with fixed lengths, each subframe is divided into more than two time slots with fixed lengths, the number of the time slots is equivalent to that of the sensor nodes, namely, each sensor node only sends data once in each subframe; the communication in each time slot comprises an uplink data frame and a downlink response frame; after all the nodes receive the beacon frame, the data packet is transmitted to the appointed destination node in the appointed time slot according to the appointed transmitting power, and the destination node replies an acknowledgement frame ACK.
A power control, relay selection and time slot distribution method based on a gait cycle is used in a body area network and comprises N sensor nodes and a central node S.
Compared with the prior art, the invention has the following advantages and beneficial effects:
the invention predicts the future channel condition by using the periodicity of the channel based on the gait cycle of the human body, minimizes the total energy consumption of the network by power control, relay selection and time slot allocation methods according to the predicted value of the channel condition, and simultaneously ensures the stability of transmission.
Drawings
Fig. 1 is a flow chart of a power control, relay selection and timeslot allocation method based on gait cycles according to the invention.
Fig. 2 is a diagram illustrating a superframe structure according to the present invention.
Fig. 3 is a system model diagram of the body area network according to the present invention.
Fig. 4 is a graph comparing a predicted channel condition curve to an actual channel condition curve according to the present invention.
Fig. 5 is a graph of threshold variation of total network energy consumption with packet loss rate obtained by using different relay selection algorithms according to the present invention.
Fig. 6 is a graph showing the total energy efficiency of the network obtained by using different relay selection algorithms according to the present invention as a function of the number of bits of a data packet.
Fig. 7 is a graph of threshold variation of total network energy consumption with packet loss rate obtained by using different time slot allocation algorithms according to the present invention.
Fig. 8 is a graph of the total energy efficiency of the network obtained by using different time slot allocation algorithms according to the present invention, as a function of the number of bits of the data packet.
Fig. 9 is a bar graph of the life cycle of a portion of nodes obtained using different slot allocation algorithms in accordance with the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
As shown in fig. 1, the body area network model contains ten sensor nodes, which are placed on the head, chest, right arm, left arm, right wrist, left wrist, right leg, left leg, right foot, and left foot of the body, respectively. The center node S is placed in the middle of the waist.
The method comprises the following steps:
step 1: the sensor node detects the channel period by adopting an AMDF method to obtain a gait period T, and then predicts the channel condition value of the next period by adopting a moving average method.
The step 1 comprises the following sub-steps:
step 1-1: the AMDF is used to detect the channel period, and for samples of past channel conditions PL of length L, the function value of its AMDF is calculated:
Figure BDA0002299987650000051
assuming that the minimum value of the AMDF function is below 50% of the maximum value and is very close to 0, we consider the current channel condition to be periodic and the value τ of the minimum value of the AMDF function is considered as the gait cycle T.
Step 1-2: after the gait cycle T is detected, predicting the channel condition of the next cycle by adopting a three-order moving average method, wherein the prediction formula is as follows:
Figure BDA0002299987650000052
step 2: dividing a gait cycle into a plurality of subframes, representing the channel condition by average channel path loss for each subframe, screening out candidate relays for each sensor node according to the channel condition, and then combining a power control algorithm to obtain a relay selection scheme with minimized network total energy consumption
Figure BDA0002299987650000053
The step 2 comprises the following sub-steps:
step 2-1: since the length of the sub-frame is small enough, the channel condition does not vary much, and for the transmission link < i, j >, i.e. the transmission link between node i and node j, the channel condition PL (i, j) in the sub-frame is represented by the average channel loss in the sub-frame.
Step 2-2: is each one ofSelecting a candidate relay set by each sensor node, node n2Can be used as a node n1Is that there is one node n1Multi-hop links l, n to a central node S1Is n2And the channel loss per hop of the link is greater than for node n1The channel loss of the direct transmission link to the central node S is small, i.e.:
Figure BDA0002299987650000061
s.t.PL(ni,ni+1)＜PL(ni,S)i＝1,2,Λk-1
PL(nk,S)＜PL(n1,S)
and searching the whole body area network to obtain a set of candidate relays of each sensor node.
Step 2-3: and traversing various possible relay selection combination schemes, calculating the minimum energy consumption value of each combination, and selecting the relay selection combination scheme with the minimum energy consumption as the optimal relay selection scheme. The method for calculating the energy consumption is as follows:
Figure BDA0002299987650000062
s.t.pi＜pmax,i＝1,2,Λ,N
Figure BDA0002299987650000063
wherein p isiRepresenting the transmission power, p, of the ith sensormaxRepresents the nominal power of the sensor, i.e. the maximum value of the transmitted power. DiThe data volume of the ith sensor is represented, and the data volume comprises the data generated by the ith sensor and the data volume of other nodes taking the ith sensor as a relay. RbThe data transmission rate is indicated.
Figure BDA0002299987650000064
The packet loss rate of the transmission link l is shown, and in order to ensure the stability of the transmission, a threshold value λ is set to be smaller.
Figure BDA0002299987650000065
Dependent on the transmit power, for one-hop links<i,j>The formula for calculating the packet loss rate is as follows:
Figure BDA0002299987650000071
wherein W represents a bandwidth, N0Representing the thermal noise of the receiver, MbRepresenting the number of bits of the data packet.
For a k-hop transmission link l ═ n1,n2,Λ,nkAnd S > the calculation formula of the packet loss rate is as follows:
Figure BDA0002299987650000072
the problem is a nonlinear programming problem, and the set of constraints is a convex set, so that an optimal solution can be solved.
And step 3: after obtaining the relay node of each sensor for each subframe, in order to ensure that the time delay does not exceed the time length of one subframe, the time slot of the relay node needs to be arranged after the time slot of the source node, and under the constraint, a time slot allocation scheme with minimum network total energy consumption is obtained by combining a power control algorithm;
the step 3 comprises the following sub-steps:
step 3-1: sensor nodes are divided into two categories, a and B. The class a node is a node which is directly transmitted to the central node without relay and is not used as a relay of other nodes, and the class B node is a node which is transmitted by relay and is used as a relay of other nodes.
Step 3-2: in order to control the time delay of transmission in one sub-frame, namely, the data arriving in the sub-frame does not wait for the next sub-frame to reach the central node. Thus, for a class B nodej, its relay node RjThe assigned time slot needs to be defined after the time slot assigned by the node j. The minimization problem of the whole slot allocation and power control is as follows:
Figure BDA0002299987650000073
s.t.pi,pj＜pmax
Figure BDA0002299987650000074
Figure BDA0002299987650000075
step 3-3: in the above problem, the present invention proposes a slot allocation algorithm that solves the problem. The specific process is as follows:
1. for each B-type node, the longest transmission link is found according to the given relay selection, the hop count of the transmission link is k, the hop count of the node in the link is k ', the scheduled time slot of the node meets the following interval [ k ', N +1+ k ' -k ], and N is the number of sensor nodes.
2. Randomly selecting a node i 'from the B-type nodes, and allocating the time slot with the minimum channel loss in the selectable interval to the node, wherein the allocated time slot is assumed to be t'.
3. The remaining nodes update the optional intervals of their slots, i.e.: the left end point of the relay node selectable interval of the node i 'becomes t' +1, and the right end point of the node selectable interval with the node i 'as the relay becomes t' -1.
4. Steps 2 and 3 are repeated until all class B nodes are assigned a time slot.
5. Calculating to obtain E by adopting a power calculation method in the step 2-3B。
6. For the class-A nodes and the remaining unallocated timeslots, assuming that the number is m, the power calculation method in step 2-3 is adopted to calculate the transmission power of each node in each timeslot, and an m-dimensional utility matrix is constructed as follows:
Figure BDA0002299987650000081
wherein the content of the first and second substances,
Figure BDA0002299987650000082
and the energy value required to be consumed by the ith class A node for transmitting data is distributed to the jth time slot.
7. The best distribution scheme is obtained by solving the utility matrix through the Hungarian algorithm, the Hungarian algorithm is an optimal solution for solving the distribution problem, and the minimum energy consumption E is obtainedA. Therefore, the total energy consumption to obtain this allocation scheme is E ═ EB+EA。
8. And changing the selection sequence of the B-type nodes, repeating the steps 2-7, and adopting a time slot allocation scheme with the minimum total energy consumption.
The simulation results of this example were obtained using the simulation software Matlab.
The basic parameters of the simulation experiment are set as follows: according to the IEEE 802.15.6 working group, the transceiver at the physical layer is set to operate in the 2.4GHz band, the transmission rate is 1024kbps, and the average noise power is set to-100 dB.
Fig. 3 shows the prediction result of the channel, the periodic variation of the channel can be well predicted, and the average prediction error obtained by calculation does not exceed 1.5 dB. The detected gait cycle is 1.2s, so the time of the superframe is set to 1.2s, the time of the data transmission is set to 1s, and the time of each subframe is set to 100 ms. Each sensor node transmits data ten times in total in the whole period.
Fig. 4 and fig. 5 show the variation of energy efficiency with the threshold of packet loss rate and the size of the data packet, respectively, comparing the performances of different relay selection algorithms. From the two graphs, we first see that the curve trends of the algorithms adopting different relay selection are basically the same, which shows that the energy efficiency is reduced along with the increase of the threshold of the packet loss rate and is reduced along with the increase of the size of the data packet. This is because the threshold increase of the packet loss rate requires higher power to achieve the stability requirement. To maintain transmission stability, higher transmission power is also required to transmit larger data packets. The simulation experiment is compared with a two-hop relay power control algorithm and a direct transmission method which are proposed by the document 'Jointrelay selection and transmit power control for wireless body area network foundation', and the performance of the method is far superior to that of the two methods.
Fig. 6 and fig. 7 show the variation of energy efficiency with the threshold of packet loss rate and the size of the data packet, respectively, comparing the performances of different time slot allocation algorithms. The simulation experiment is compared by an algorithm of random time slot allocation and a method of exhaustively obtaining an optimal solution. As can be seen from simulation results, the performance of the invention is superior to the algorithm of random time slot allocation, and the difference from the optimal solution is not very large. It is calculated that the calculation efficiency of the invention is five times of the exhaustive method. This also demonstrates the superiority of the present invention.
Fig. 8 shows the life cycle of a part of nodes, and comparing the method of the present invention with the method of randomly allocating time slots, it can be seen that the present invention can extend the life cycle of each sensor node by 5% -15%.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.

Claims (5)

1. A power control, relay selection and time slot allocation method based on a gait cycle is characterized by comprising the following steps:
step 1: the sensor node detects the periodicity of the channel condition change, calculates the gait cycle and predicts the channel condition of the next cycle;
step 2: dividing a gait cycle into more than two subframes, representing the channel condition by average channel path loss for each subframe, screening out candidate relays for each sensor node according to the channel condition, and then combining a power control algorithm to obtain a relay selection scheme with minimized network total energy consumption;
and step 3: after obtaining the relay node of each sensor for each subframe, in order to ensure that the time delay does not exceed the time length of one subframe, the time slot of the relay node needs to be arranged after the time slot of the source node, and under the constraint, a time slot allocation scheme with minimum network total energy consumption is obtained by combining a power control algorithm.
2. The gait cycle-based power control, relay selection and timeslot assignment method according to claim 1, wherein said step 1 comprises the sub-steps of:
step 1-1: the sensor node carries out periodic detection of channel condition change on a section of past sample data, and calculates the gait cycle;
step 1-2: and after the gait cycle is detected, predicting the channel condition of the next cycle by adopting a cycle moving average method.
3. The gait cycle-based power control, relay selection and timeslot assignment method according to claim 1, wherein said step 2 includes the sub-steps of:
step 2-1: calculating an average channel path loss for each subframe to represent channel conditions;
step 2-2: screening a candidate relay set for each sensor node according to the channel condition, wherein the screening condition is that the sensor node can find a multi-hop link transmitted to the central node through the candidate relay, and the channel path loss of each hop of the link is lower than the direct transmission link from the sensor node to the central node;
step 2-3: and traversing all combinations of relay selection, combining a power control algorithm, calculating the total energy consumption of the network, and selecting the optimal relay combination to minimize the energy consumption of the network.
4. The gait cycle-based power control, relay selection and timeslot assignment method according to claim 1, wherein said step 3 includes the sub-steps of:
step 3-1: dividing the sensor nodes into class A nodes and class B nodes; the class-A node is a node which is directly transmitted to the central node without the help of a relay and is not used as a relay of other nodes, and the class-B node is a node which is transmitted by the help of a relay and is used as a relay of other nodes;
step 3-2: for the node B, the time slot allocated by the constraint relay node is required to be behind the time slot allocated by the source node when the time slot of each subframe is allocated;
step 3-3: allocating a time slot with the minimum channel path loss in the selectable time slots for the class B node, calculating the total energy consumption of the class B node by adopting a power control method, then calculating the energy consumption required by the class A node for sending data in each remaining time slot by combining a power control algorithm to form a utility matrix, solving an optimal allocation scheme by adopting a Hungary algorithm to obtain the minimum total energy consumption allocated by the class A node in the remaining time slots, and further obtaining the total energy consumption of the network; since the result of allocating the best currently selectable time slot to the class B node is influenced by the allocation order of the class B node, it is necessary to traverse the allocation order of any class B node, repeat the above steps to calculate the total energy consumption, and finally select the time slot allocation scheme with the smallest total energy consumption.
5. The gait cycle-based power control, relay selection and timeslot allocation method according to claim 1, characterized in that it is based on the MAC protocol of superframe structure, and is divided into three phases:
and an uplink beacon phase: the sensor node transmits the channel condition of each communication link to the central node in a beacon frame mode;
a downlink beacon stage: the method comprises the steps that a central node broadcasts a beacon frame, wherein the beacon carries time slot information distributed to each sensor node, a transmission destination node of each time slot and information of transmission power;
and (3) a data transmission stage: the stage is divided into more than two subframes with fixed lengths, each subframe is divided into more than two time slots with fixed lengths, the number of the time slots is equivalent to that of the sensor nodes, namely, each sensor node only sends data once in each subframe; the communication in each time slot comprises an uplink data frame and a downlink response frame; after all the nodes receive the beacon frame, the data packet is transmitted to the appointed destination node in the appointed time slot according to the appointed transmitting power, and the destination node replies an acknowledgement frame ACK.
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