Power distribution method of large forwarding system under imperfect channel estimation

Abstract

The invention relates to the technical field of wireless communication, in particular to a power distribution method of a large forwarding system under imperfect channel estimation. The method comprises the following steps: firstly, sequentially sending pilot frequency information through a source node and a relay node to carry out channel estimation, and obtaining a channel estimation value by adopting a minimum mean square error estimation criterion; the destination node estimates the signal-to-noise ratio of a received signal and the total energy consumption in the data transmission process, wherein the transmission of data information adopts an amplification forwarding mode; and the destination node realizes joint optimization distribution on the data transmitting power of the source node and the relay node through an iterative algorithm according to the defined system objective function. According to the invention, the utilization efficiency of energy resources is improved in an amplification forwarding relay system with imperfect channel estimation.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communications, and in particular to a power allocation method for an amplification and forwarding system under imperfect channel estimation. Background Art

[0002] Multi-hop wireless networks such as Internet of Vehicles and wireless sensor networks have a large number of application scenarios in intelligent industrial manufacturing, smart city construction, smart agriculture and other industries. In order to improve the efficiency of energy resource utilization, two nodes that are far apart usually use relay nodes to transmit data in a multi-hop manner. In the amplification and forwarding system, the relay node amplifies the received signal and transmits it directly to the destination node without decoding in the process, which can reduce the hardware support of the relay node. In addition, in actual communication systems, accurate channel state information is difficult to obtain. The channel state information estimated by sending pilot sequences is often imperfect. Therefore, it is very necessary to study an efficient power allocation method for a class of amplification and forwarding relay systems under imperfect channel estimation, so that it can improve the energy utilization of the network system.

[0003] For amplify-and-forward relay systems, there are many studies on energy-efficient data transmission. For example, Y. Guo et al. proposed an energy-efficient multi-relay selection and power allocation algorithm in the 2022 article "An Energy-Efficiency Multi-Relay Selection and Power Allocation Based on Deep Neural Network for Amplify-and-Forward Cooperative Transmission". However, the related work did not consider the impact of imperfect channel estimation on the power allocation method. Yao Junteng and other scholars from Ningbo University proposed a relay-assisted dual-network air calculation method to improve the accuracy of calculation by optimizing the transmission parameters of each sensor in the patent "A relay-assisted dual-network air calculation method under imperfect channel state information". However, the related work did not consider the high energy efficiency of data transmission in the network system. Therefore, it is necessary to further design an energy-efficient power allocation method for network systems under imperfect channel estimation. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a power allocation method for an amplification and forwarding system under imperfect channel estimation, and the technical solution adopted is as follows:

[0005] The source node and the relay node send pilot information in turn to perform channel estimation, and use the minimum mean square error estimation criterion to obtain the channel estimation value;

[0006] The destination node estimates the signal-to-noise ratio of the received signal and the total energy consumption during data transmission, where the data information is transmitted using an amplify-and-forward method;

[0007] The destination node realizes joint optimization allocation of the data transmission power of the source node and the relay node through an iterative algorithm according to the defined system objective function.

[0008] Furthermore, the amplification and forwarding method includes:

[0009] The amplify-and-forward relay system includes a source node S, a destination node D and a relay node R. The distance between the source node and the destination node is L, the distance between the source node and the relay node is L1=αL, (0<α<1), and the distance between the relay node and the destination node is L2=(1-α)L.

[0010] Furthermore, the communication channel h between the source node and the relay node SR , and the communication channel h between the relay node and the target node RD All of them are Rayleigh block fading channels, that is, h SR and h RD is a random variable that obeys a Gaussian distribution. Its mean is 0 and its variance is

[0011] Furthermore, the channel estimation adopts two stages. In the first channel estimation stage, the source node sends a pilot sequence to the relay node, wherein the wireless channel between the source node and the relay node is the relay node estimating channel h SR In the second channel estimation phase, the relay node sends a new pilot sequence to the destination node, where the wireless channel from the relay node to the pilot sequence is the target node estimated channel h RD .

[0012] Further, the adopting the minimum mean square error estimation criterion to obtain the channel estimation value includes:

[0013] The channel estimation value h in the first channel estimation stage e,SR The calculation formula is:

[0014]

[0015] The channel estimation value h in the second channel estimation stage e,RD The calculation formula is:

[0016] Where x represents a pilot symbol, l represents the pilot sequence length; p ps represents the pilot transmission power of the source node; p prrepresents the pilot transmission power of the relay node; n1, n2 represent additive Gaussian white noise with a mean of 0 and a variance of G SR represents the large-scale fading coefficient between the source node and the relay node; G RD Represents the large-scale fading coefficient between the relay node and the destination node;

[0017]

[0018] Where d0 represents the reference distance; λ represents the wavelength; τ∈[2,4] represents the path fading index;

[0019] Channel estimate h e,SR ,h e,RD The corresponding mean square errors are:

[0020]

[0021] Furthermore, after the channel estimation stage, the source node sends the data signal to the target node through the relay node in an amplified forwarding manner, and the target node calculates the signal-to-noise ratio γ of the received signal. D And the energy consumption E of one data transmission;

[0022] Signal-to-noise ratio D The calculation formula is:

[0023]

[0024] in, represents the ratio of channel to noise, p s represents the data transmission power of the source node; p r Indicates the data transmission power of the relay node;

[0025]

[0026] The calculation formula of energy consumption E is:

[0027]

[0028] Among them, p c represents the circuit power consumption of the transmitting and receiving nodes for each data transmission hop, ξ represents the transmission power amplification factor, M represents the packet length, and R b Indicates the data transfer rate.

[0029] Furthermore, the objective function of the system is defined as the ratio of the total energy consumption to the actual throughput during data transmission, that is, C = E / T, where T represents the actual throughput and E represents the energy consumption. b ×f(γ D ) / 2; here f(γD ) is the validity function:

[0030]

[0031] Where c1, c2 are constants that depend on coding and modulation; M represents the length of the data packet; γ D represents the signal-to-noise ratio; log represents the logarithmic function.

[0032] Furthermore, the transmission power of the source node and the relay node is jointly optimized based on minimizing the system objective function.

[0033] Furthermore, the joint optimization of the data transmission power of the relay nodes first initializes the transmission power value Iteration index i = 1, iteration error ε>0; then alternate calculation The calculation formula is:

[0034]

[0035] in, Calculation error

[0036] Repeated iterative calculation Until the error Until convergence, the optimal transmission power of the source node and the relay node are

[0037] Furthermore, assuming that the maximum transmission power of the source node and the relay node is p max , if the optimal transmit power generated by the algorithm is Greater than p max , then p max is the optimal transmission power.

[0038] The embodiments of the present invention have at least the following beneficial effects:

[0039] The method first performs channel estimation by sending pilot information in sequence through the source node and the relay node, and obtains the channel estimation value by using the minimum mean square error estimation criterion; the destination node estimates the signal-to-noise ratio of the received signal and the total energy consumption during the data transmission process, wherein the transmission of data information adopts the amplification and forwarding method; the destination node realizes joint optimization allocation of the data transmission power of the source node and the relay node through an iterative algorithm according to the defined system objective function. The present invention proposes a high-energy-efficiency power allocation method, which can improve the utilization efficiency of energy resources in the amplification and forwarding relay system with imperfect channel estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0041] Figure 1 A method flow chart of a power allocation method for an amplify-and-forward system under imperfect channel estimation provided by one embodiment of the present invention;

[0042] Figure 2 A schematic diagram of a source node, a destination node and a relay node in an amplify-and-forward relay system provided by an embodiment of the present invention;

[0043] Figure 3 A schematic diagram of the relationship between energy consumption and communication distance provided by an embodiment of the present invention;

[0044] Figure 4 A schematic diagram of the influence of a relay position on an objective function value provided by an embodiment of the present invention;

[0045] Figure 5 A schematic diagram of the influence of channel estimation parameters on objective function values ​​provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the power allocation method of the amplification and forwarding system under imperfect channel estimation proposed by the present invention, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0047] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0048] The following describes in detail a specific scheme of a power allocation method for an amplify-and-forward system under imperfect channel estimation provided by the present invention in conjunction with the accompanying drawings.

[0049] See also Figure 1 , which shows a flowchart of a power allocation method for an amplification and forwarding system under imperfect channel estimation provided by an embodiment of the present invention, the method comprising the following steps:

[0050] In step S100, the source node and the relay node send pilot information in sequence to perform channel estimation, and use a minimum mean square error estimation criterion to obtain a channel estimation value.

[0051] The amplify-and-forward relay system includes a source node S, a destination node D and a relay node R. The distance between the source node and the destination node is L, the distance between the source node and the relay node is L1 = αL, (0 < α < 1), and the distance between the relay node and the destination node is L2 = (1-α)L. Please refer to Figure 2 , Figure 2 A schematic diagram of a source node, a destination node and a relay node in an amplification and forwarding relay system; Figure 2 Here S is the source node, D is the destination node, and R is the relay node.

[0052] Among them, the communication channel h between the source node and the relay node SR , and the communication channel h between the relay node and the target node RD All of them are Rayleigh block fading channels, that is, h SR and h RD is a random variable that obeys a Gaussian distribution. Its mean is 0 and its variance is

[0053] The channel estimation adopts two stages. In the first channel estimation stage, the source node sends a pilot sequence to the relay node, where the wireless channel between the source node and the relay node is the relay node estimated channel h SR In the second channel estimation phase, the relay node sends a new pilot sequence to the destination node, where the wireless channel from the relay node to the pilot sequence is the target node estimated channel h RD After the channel estimation phase, the source node forwards the data signal to the destination node through the relay node.

[0054] The minimum mean square error estimation criterion is used to obtain the channel estimation value;

[0055] The channel estimation value h in the first channel estimation stage e,SR The calculation formula is:

[0056]

[0057] The channel estimation value h in the second channel estimation stage e,RD The calculation formula is:

[0058] Where x represents a pilot symbol, l represents the pilot sequence length; p ps represents the pilot transmission power of the source node; p prrepresents the pilot transmission power of the relay node; n1, n2 represent additive Gaussian white noise with a mean of 0 and a variance of G SR represents the large-scale fading coefficient between the source node and the relay node; G RD Represents the large-scale fading coefficient between the relay node and the destination node;

[0059]

[0060] Where d0 represents the reference distance; λ represents the wavelength; τ∈[2,4] represents the path fading index;

[0061] Channel estimate h e,SR ,h e,RD The corresponding mean square errors are:

[0062]

[0063] Step S200, the destination node estimates the signal-to-noise ratio of the received signal and the total energy consumption during data transmission, wherein the data information is transmitted in an amplify-and-forward manner.

[0064] After the channel estimation stage, the source node sends the data signal to the target node through the relay node in an amplified forwarding manner. The target node calculates the signal-to-noise ratio γ of the received signal. D And the energy consumption E of one data transmission;

[0065] Signal-to-noise ratio D The calculation formula is:

[0066]

[0067] in, represents the ratio of channel to noise; p s represents the data transmission power of the source node; p r Indicates the data transmission power of the relay node;

[0068]

[0069] The calculation formula of energy consumption E is:

[0070]

[0071] Among them, p c represents the circuit power consumption of the transmitting and receiving nodes for each data transmission hop, ξ represents the transmission power amplification factor, M represents the packet length, and R b Indicates the data transfer rate.

[0072] The objective function of the system is defined as the ratio of the total energy consumption to the actual throughput during data transmission, that is, C = E / T, where T represents the actual throughput and E represents the energy consumption. b ×f(γ D ) / 2. Here f(γ D ) is the validity function:

[0073]

[0074] Where c1, c2 are constants that depend on coding and modulation; M represents the length of the data packet; γ D represents the signal-to-noise ratio; log is the logarithmic function; exp is the exponential function with the natural constant e as the base.

[0075] Step S300: The destination node implements joint optimization allocation of data transmission power of the source node and the relay node through an iterative algorithm according to the defined system objective function.

[0076] Based on minimizing the system objective function, the transmission power p of the source node and the relay node is s ,p r Perform joint optimization.

[0077] The system objective function is p s ,p r is a concave function. So given p r , there is an optimal Minimize the system objective function.

[0078]

[0079] Where Δ1=(1+γ RD ×p r )×(c1 logM+c2).

[0080] Similarly, given p s , there is an optimal Minimize the system objective function;

[0081]

[0082] Where Δ2=(1+γ SR p s )×(c1 logM+c2).

[0083] Since the objective function C is p s ,p r Convex function of joint power optimization It can be calculated by an iterative optimization algorithm. The joint optimization of the transmission power of the source node and the relay node can be calculated in an iterative manner.

[0084] Initialize the transmit power value Iteration index i=1, iteration error ε>0;

[0085] Then alternately calculate The calculation formula is:

[0086]

[0087] in, Calculation error

[0088] Repeated iterative calculation Until the error Until convergence.

[0089] The optimal transmission power of the source node and the relay node are

[0090] Assume that the maximum transmission power of the source node and the relay node is p max , if the optimal transmit power generated by the algorithm is Greater than p max , then p max is the optimal transmission power.

[0091] The present invention can be further illustrated by the following simulation:

[0092] 1. Simulation conditions:

[0093] In the simulation, several nodes are randomly and evenly distributed in a 500×500m 2 Each sensor node initializes its active / sleep scheduling sequence within a working cycle according to the duty ratio. The duty ratio is defined as the ratio of the number of time slots in the active state to the total number of time slots. The transmission range of all sensor nodes is assumed to be r max The network topology for each time slot is generated according to the active / sleeping state of the node and the maximum transmission range (corresponding to the maximum transmission power of the node). The number of sink nodes is always 1. Unless otherwise specified, other simulation parameters are shown in Table 1.

[0094] 2. Simulation content and results:

[0095] See also Figure 3 , Figure 3 It reflects the relationship between the objective function value of the relay system and the communication distance between the source node and the destination node. The objective function value of the relay system here is the energy consumption of successfully transmitting a unit bit of data. Figure 3This is a schematic diagram of the relationship between energy consumption and communication distance. In this simulation, the communication distance L between the source node and the destination node changes from 100m to 400m, and the relay node is located in the middle of the source and destination nodes, that is, α = 1 / 2. The length of the pilot sequence is set to l = 5bits. The calculation of the objective function value is based on the optimal power allocation of the source node and the relay node. Obviously, the energy consumption per bit of data is an increasing function of the communication distance. In particular, when the communication distance is small, direct transmission (DT) is better than relay transmission (RT); when the communication distance becomes larger, the energy consumption of direct transmission will increase rapidly, and relay transmission will be better than direct transmission. Since the effectiveness function is a decreasing function of the data packet length, using small data packets for data transmission can effectively reduce energy consumption.

[0096] Please refer to Table 1, which is a schematic diagram of simulation parameter values.

[0097] Simulation parameters Simulation value <![CDATA[p c =0.218W]]> <![CDATA[d0=1m]]> <![CDATA[p max In]]> λ=0.08m ξ=0.2 τ=3.5 <![CDATA[R b =10 5 bit / s]]> <![CDATA[σ n 2 =-170dBM]]> <![CDATA[σ0 2 =1]]>

[0098] Table 1

[0099] See also Figure 4 , Figure 4 Schematic diagram of the influence of relay position on the objective function value. In this simulation example, the relay position α changes from 0.1 to 0.9, the communication distance between the source node and the destination node is set to L = 250m, and the length of the pilot sequence is l = 5bits. It can be seen that when the relay node is located in the middle of the source node and the destination node, the amplification and forwarding relay transmission has the lowest energy consumption; when the relay node is closer and closer to the source node or the destination node, the energy consumption of the amplification and forwarding relay transmission will gradually increase, and even be higher than the direct transmission.

[0100] See also Figure 5 , Figure 5 Figure 1 is a schematic diagram of the influence of channel estimation parameters on the objective function value. The channel estimation parameters are the pilot transmission power and the length of the pilot sequence. In this simulation example, the pilot transmission power varies from 0.04W to the maximum transmission power, and the length of the pilot sequence is l = 5 bits or 10 bits. In addition, the communication distance between the source and destination nodes is set to L = 250m, and the relay position α = 1 / 2. Figure 4 It can be seen that under the given communication parameters, relay transmission is better than direct transmission. For relay transmission, when the pilot transmission power is low, a longer pilot sequence should be selected; when the pilot transmission power is high, a shorter pilot sequence can be selected. This is because energy-efficient system design requires channel state information with a certain accuracy. In particular, there is an optimal pilot transmission power that minimizes the energy consumption of the amplify-and-forward relay system.

[0101] Figure 3 , Figure 4 and Figure 5 The simulation shows that the implementation of an energy-efficient communication system should take into account different communication parameters and transmission strategies. Communication parameters include communication distance, relay location, pilot transmission power and pilot sequence length, and transmission strategies include relay transmission or direct transmission.

[0102] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0103] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A power allocation method for an amplify-and-forward system under imperfect channel estimation, characterized in that: The method comprises the following steps: The source node and the relay node send pilot information in turn to perform channel estimation, and use the minimum mean square error estimation criterion to obtain the channel estimation value; The destination node estimates the signal-to-noise ratio of the received signal and the total energy consumption during data transmission, where the data information is transmitted using an amplify-and-forward method; The destination node realizes joint optimization allocation of the data transmission power of the source node and the relay node through an iterative algorithm according to the defined system objective function.

2. The power allocation method for amplification and forwarding system under imperfect channel estimation according to claim 1, characterized in that: The amplification and forwarding method includes: The amplify-and-forward relay system includes a source node S, a destination node D and a relay node R. The distance between the source node and the destination node is L, the distance between the source node and the relay node is L1=αL, (0<α<1), and the distance between the relay node and the destination node is L2=(1-α)L.

3. The power allocation method for amplification and forwarding system under imperfect channel estimation according to claim 1, characterized in that: The communication channel h between the source node and the relay node SR , and the communication channel h between the relay node and the target node RD All of them are Rayleigh block fading channels, that is, h SR and h RD is a random variable that obeys a Gaussian distribution. Its mean is 0 and its variance is 4. The power allocation method for amplification and forwarding system under imperfect channel estimation according to claim 1, characterized in that: The channel estimation adopts two stages. In the first channel estimation stage, the source node sends a pilot sequence to the relay node, where the wireless channel between the source node and the relay node is the relay node estimated channel h SR In the second channel estimation phase, the relay node sends a new pilot sequence to the destination node, where the wireless channel from the relay node to the pilot sequence is the target node estimated channel h RD .

5. The power allocation method for amplification and forwarding system under imperfect channel estimation according to claim 1, characterized in that: The adopting the minimum mean square error estimation criterion to obtain the channel estimation value comprises: The channel estimation value h in the first channel estimation stage e,SR The calculation formula is: The channel estimation value h in the second channel estimation stage e,RD The calculation formula is: Where x represents a pilot symbol, l represents the pilot sequence length; p ps represents the pilot transmission power of the source node; p pr represents the pilot transmission power of the relay node; n1, n2 represent additive Gaussian white noise with a mean of 0 and a variance of G SR represents the large-scale fading coefficient between the source node and the relay node; G RD Represents the large-scale fading coefficient between the relay node and the destination node; Where d0 represents the reference distance; λ represents the wavelength; τ∈[2,4] represents the path fading index; Channel estimate h e,SR ,h e,RD The corresponding mean square errors are:

6. The power allocation method for amplify-and-forward system under imperfect channel estimation according to claim 5, characterized in that: After the channel estimation stage, the source node sends the data signal to the target node through the relay node in an amplified forwarding manner. The target node calculates the signal-to-noise ratio γ of the received signal. D And the energy consumption E of one data transmission; Signal-to-noise ratio D The calculation formula is: in, represents the ratio of channel to noise, p s represents the data transmission power of the source node; p r Indicates the data transmission power of the relay node; The calculation formula of energy consumption E is: Among them, p c represents the circuit power consumption of the transmitting and receiving nodes for each data transmission hop, ξ represents the transmission power amplification factor, M represents the packet length, and R b Indicates the data transfer rate.

7. The power allocation method for amplification and forwarding system under imperfect channel estimation according to claim 1, characterized in that: The objective function of the system is defined as the ratio of total energy consumption to actual throughput during data transmission, that is, C = E / T, where T represents actual throughput and E represents energy consumption. b ×f(γ D ) / 2; here f(γ D ) is the validity function: Where c1, c2 are constants that depend on coding and modulation; M represents the length of the data packet; γ D represents the signal-to-noise ratio; log represents the logarithmic function.

8. The power allocation method for amplification and forwarding system under imperfect channel estimation according to claim 1, characterized in that: The transmission power of the source node and the relay node is jointly optimized based on minimizing the system objective function.

9. The power allocation method for amplification and forwarding system under imperfect channel estimation according to claim 1, characterized in that: The joint optimization of data transmission power of relay nodes first initializes the transmission power value Iteration index i = 1, iteration error ε>0; then alternate calculation The calculation formula is: in, Calculation error Repeated iterative calculation Until the error Until convergence, the optimal transmission power of the source node and the relay node are 10. The power allocation method for amplify-and-forward system under imperfect channel estimation according to claim 1, characterized in that: Assume that the maximum transmission power of the source node and the relay node is p max , if the optimal transmit power generated by the algorithm is Greater than p max , then p max is the optimal transmission power.

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