Geometrically weighted power control method for underlying d2d communication in cellular networks

Abstract

The geometric weighting power control method of underlay D2D communication in cellular network comprises the following steps: Step 1, obtaining the target function of a pair of "cell link-D2D link" power distribution model; Step 2, establishing constraint conditions according to the characteristics of the cellular link and the D2D link; Step 3, converting the distribution model in Step 1 into a linear programming standard form according to the constraint conditions in Step 2; Step 4, solving the power distribution in Step 3 by graphical method. The purpose of the application is to solve the Underlay mode D2D communication in the cellular network with the maximum throughput or energy efficiency EE or weighted energy efficiency WSEE as the target. Due to the characteristics of the target function, the power distribution problem is generally non-convex, which needs to be obtained by iteration, and the complexity is relatively high, and the optimal solution is difficult to obtain. A power distribution method for a pair of "(uplink) cellular link-D2D link" in underlay D2D communication based on weighted power minimization is provided.

Description

Geometric weighted power control method for underlying D2D communication in cellular networks Technical Field

[0001] This invention relates to the field of communication technology, and more specifically to a power allocation method for a pair of "uplink cellular link-D2D link" in low-level D2D communication based on weighted power. Background Technology

[0002] D2D (device-to-device communication) refers to a technology that allows direct communication between two peer user nodes without relying on network infrastructure such as base stations (BSs) or access points (APs). The 3GPP organization began discussing this technology in 2013. Developed since 4G, it is now widely used in 5G communication systems. D2D communication multiplexing in cellular networks utilizes licensed frequency bands from cellular users. There are two main multiplexing methods: Overlay mode and Underlay mode. The former opportunistically accesses idle licensed cellular frequency bands, while the latter can access frequency bands currently being used by cellular users. Although the latter may cause interference to cellular users, it can improve the spectrum utilization of licensed frequency bands, thus attracting extensive research.

[0003] In D2D communication in the Underlay mode, most previous wireless resource allocation schemes focused on maximizing system throughput. In recent years, with the growing popularity of green and low-carbon development concepts and the limitations of battery capacity in mobile terminals, energy efficiency (EE) has become an important performance indicator for measuring the performance of mobile communication systems and achieving green communication. See the article "Fractional Programming for Communication Systems - Part I: Power Control and Beamforming".

[0004] The energy efficiency of a communication system is expressed by the following formula:

[0005]

[0006] In the above formula This indicates the number of nodes in the network. and They represent the first The spectral efficiency and power consumption of each network node are considered. The optimization objective of wireless resource allocation algorithms is to maximize the system's energy efficiency while ensuring the Quality of Service (QoS) of each node in the network. As can be seen from the formula, the essence of this type of scheme is solving a fractional programming problem, the analytical optimal solution of which cannot be obtained. Traditional methods solve suboptimal solutions to this type of problem iteratively; however, their algorithmic complexity is high, and the convergence calculation time is long, thus consuming a great deal of computational resources and having poor timeliness, making them difficult to apply to practical communication systems. Furthermore, this performance indicator does not consider the energy consumption priority of different nodes in the network.

[0007] Weighted sum energy efficiency (WSEE) is a weighted sum of the energy efficiencies of each node, expressed as follows (see the article "Energy-Efficient D2D Overlaying Communications With Spectrum-Power Trading").

[0008]

[0009] In the above formula Indicates the first The weight of each node is a metric that considers the priority of different nodes in the system. The energy consumption performance of nodes can be customized by preset weights, making it particularly suitable for heterogeneous networks. However, using WSEE as the objective function for optimizing wireless resource allocation still results in high complexity.

[0010] Existing power allocation techniques have the following defects and shortcomings: In cellular network Underlay mode D2D communication, whether the goal is to maximize throughput, energy efficiency (EE), or weighted energy efficiency (WSEE), the power allocation problem is generally non-convex due to the characteristics of the objective function. It requires an iterative approach, which is complex and the optimal solution is difficult to obtain. Summary of the Invention

[0011] The purpose of this invention is to address the technical problem that, in cellular networks where the goal is to maximize throughput, energy efficiency (EE), or weighted energy efficiency (WSEE), the power allocation problem in Underlay mode D2D communication is generally non-convex due to the characteristics of the objective function. This requires an iterative approach, which is complex and makes it difficult to obtain the optimal solution. The invention provides a power allocation method for a pair of "(uplink) cellular link - D2D link" in the underlying D2D communication based on weighted power minimization.

[0012] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0013] A geometrically weighted power control method for low-level D2D (device-to-device) communication in cellular networks includes the following steps:

[0014] Step 1: Obtain the objective function of the power allocation model between a pair of uplink cellular links and D2D links;

[0015] Step 2: Establish constraints based on the characteristics of uplink cellular links and D2D links;

[0016] Step 3: Based on the constraints in Step 2, transform the allocation model in Step 1 into the standard form of linear programming.

[0017] Step 4: Solve the power distribution problem in Step 3 using a graphical method.

[0018] In Step 1, the objective function of the power allocation model is the weighted sum power (WSP). :

[0019] , (1);

[0020] in and These are the weights of the uplink cellular link (the communication link between a cellular user and a base station) and the D2D link (the communication link between a D2D transmitter and a D2D receiver). and These are the transmit power for cellular users (CU) and D2D transmitters (DT), respectively.

[0021] In Step 2, the constraints established include:

[0022] Transmit power and transmission power Meets transmit power constraints:

[0023] , (2);

[0024] Among them and It refers to the transmitter, that is, the minimum and maximum transmit power of CU and DT;

[0025] Furthermore, the QoS (Quality of Service) requirements of the uplink cellular link and D2D link also need to be met. Assuming that the QoS requirements are measured by the achievable spectrum efficiency (SE) of the uplink cellular link and D2D link, the following constraints apply:

[0026] , (3);

[0027] , (4);

[0028] in , , , These refer to the channel gains between the cellular user (CU, i.e., mobile terminal) and the base station (BS), the D2D transmitter (DT) and the base station (BS), the D2D transmitter (DT) and the D2D receiver (DR), and the cellular user (CU) and the D2D receiver (DR). It is the power spectral density of Gaussian white noise. and It is the QoS requirement for uplink cellular links and D2D links, measured in terms of achievable spectrum efficiency (SE).

[0029] Step 3 includes the following steps:

[0030] Step 3-1) Based on the constraints in Step 2, use variables ,variable Replacement of cellular user CU transmit power The transmit power of the D2D transmitter (DT) , will solve and The optimal power allocation problem is transformed into a linear programming problem in the xOy plane (in a Cartesian coordinate system) as follows:

[0031]

[0032] Step 3-2) Based on problem (4), constraints (4c) (from (3)) and (4d) (from (4)), set the equipotential lines as follows:

[0033] Isopotential lines : (5)

[0034] Isopotential lines : (6)

[0035] Isopotential lines : , (7);

[0036] Step 3-3) Obtain equipotential lines Isopotential lines Isopotential lines The slope:

[0037] Isopotential lines The slope is , Isopotential lines The slope is , Isopotential lines The slope is ;

[0038] Steps 3-4) Obtain equipotential lines and equipotential lines and axis, Intersection of axes:

[0039] Isopotential lines and Intersection point E of the axes ,

[0040] Isopotential lines and The intersection point F of the axes ,

[0041] Isopotential lines and The intersection point G of the axes ,

[0042] Isopotential lines and The intersection point H of the axes ,

[0043] Steps 3-5) yield the following:

[0044] Isopotential lines With line CD: Intersection I ,

[0045] Isopotential lines With line BC: Intersection J ,

[0046] Isopotential lines With equipotential lines intersection point K .

[0047] In Step 4, when solving for the power allocation in Step 3, the goal is to find the value that minimizes the weighted power (WSP) of a pair of uplink cellular links (D2D links). The specifics depend on and Classify and judge the size relationship;

[0048] The specific steps are as follows:

[0049] Step 4-1) Judgment Does it satisfy the condition? If so, then the equipotential lines are... With equipotential lines Parallel (as shown in Figure 1) or equipotential lines With equipotential lines If they intersect in the third quadrant (as shown in Figure 2), then No solution found; otherwise, proceed to step 4-2.

[0050] Step 4-2) (At this time) )judge (As shown in Figure 3) or (As shown in Figure 4) Does it satisfy the condition? If it does, then No solution found; otherwise, proceed to step 4-3.

[0051] Step 4-3) (At this time) )judge and (As shown in Figure 5) Do they simultaneously satisfy the following conditions? If so, the optimal power solution is: Otherwise, proceed to step 4-4;

[0052] Step 4-4) (At this time) )judge or ,and (As shown in Figure 6) Do they satisfy simultaneously? If so, then Otherwise, proceed to steps 4-5;

[0053] Steps 4-5: (At this time) )judge or ,and (As shown in Figure 7) Do they satisfy simultaneously? If so, then ;

[0054] Based on the above, the optimal power allocation with the minimum weighted power WSP is obtained. and .

[0055] The power allocation method described herein aims to minimize the system weighted power (WSP) of a pair of uplink cellular links (D2D links).

[0056] An uplink cellular link-D2D link system includes a base station (BS), a cellular user (CU), a D2D transmitter (DT), and a D2D receiver (DR). It is assumed that the transmission directions of the uplink cellular link and the D2D link remain constant throughout the communication process; the link from the CU to the BS is called the uplink cellular link, and the link from the DT to the DR is called the D2D link; spectrum resources are allocated by the network's central control node, the base station (BS).

[0057] Compared with the prior art, the present invention has the following technical effects:

[0058] 1) This invention employs weighted sum power (WSP) as a novel system performance evaluation metric and objective function for wireless resource optimization allocation. This metric is defined as the sum of weighted power consumption of system nodes. Compared to energy efficiency (EE) (the ratio of system throughput to power consumption, which, as an objective function, does not consider the fractional programming problem arising from the priorities of different nodes) and weighted sum energy efficiency (WSEE) (which considers both global system performance and the priorities of different nodes, but whose numerators represent reachability rates, expressed in logarithmic Shannon formulas, and whose denominators represent power consumption; maximizing WSEE remains challenging), minimizing weighted sum power (WSP) can, in most cases, be transformed into a convex optimization form, thereby significantly reducing the complexity of solving the resource allocation problem.

[0059] 2) On the other hand, this invention, by dynamically adjusting node weights, directly controls the node power consumption rate through weighted power scaling (WSP), facilitating the management of the system's energy budget and thus indirectly achieving the goal of extending the lifespan of the IoT network. This method transforms the power allocation problem between a pair of matched (uplink) cellular links—D2D links—into a linear programming problem, which is solved graphically. The solution has low computational complexity and is suitable for real-time deployment on low-hardware-complexity network infrastructures. Attached Figure Description

[0060] The present invention will be further described below with reference to the accompanying drawings and embodiments:

[0061] Figure 1 shows the invention. And equipotential lines With equipotential lines A schematic diagram of the parallel configuration, where there is no solution for power distribution.

[0062] Figure 2 shows the invention. And equipotential lines With equipotential lines The diagram shows the intersection in the third quadrant, where there is no solution for power distribution.

[0063] Figure 3 shows the invention. Furthermore, rectangle ABCD lies on the equipotential lines The diagram above shows that there is no solution for power allocation at this point;

[0064] Figure 4 shows the invention. Furthermore, rectangle ABCD lies on the equipotential lines The diagram below shows that there is no solution for power allocation at this point;

[0065] Figure 5 shows the invention. The diagram shows that point K is inside rectangle ABCD. In this case, the optimal power allocation is... ;

[0066] Figure 6 shows the invention. And the diagram shows point I on line segment CD. The optimal power allocation at this point is... ;

[0067] Figure 7 shows the invention. And the diagram shows point J on line segment BC, where the optimal power allocation is... ;

[0068] Figure 8 is a schematic diagram comparing the weighted power WSP and D2D link QoS requirements of four schemes, including the method proposed in this invention, in the embodiments of this invention.

[0069] Figure 9 is a schematic diagram comparing the energy efficiency (EE) and D2D link QoS requirements of four schemes, including the method proposed in this invention, in the embodiments of this invention.

[0070] Figure 10 is a schematic diagram comparing the computation time and D2D link QoS requirements of four schemes, including the method proposed in this invention, in the embodiments of this invention.

[0071] Figure 11 is a schematic diagram of two pairs of "(uplink) cellular link-D2D link" and their corresponding wireless frame structures under the Underlay mode D2D communication of the present invention. Detailed Implementation

[0072] A geometrically weighted power control method for low-level D2D (device-to-device) communication in cellular networks includes the following steps:

[0073] Step 1: Obtain the objective function of the power allocation model between a pair of uplink cellular links and D2D links;

[0074] Step 2: Establish constraints based on the characteristics of uplink cellular links and D2D links;

[0075] Step 3: Based on the constraints in Step 2, transform the allocation model in Step 1 into the standard form of linear programming.

[0076] Step 4: Solve the power distribution problem in Step 3 using a graphical method.

[0077] In Step 1, the objective function of the power allocation model is the weighted sum power (WSP). :

[0078] , (1);

[0079] in and These are the weights of the uplink cellular link (the communication link between a cellular user and a base station) and the D2D link (the communication link between a D2D transmitter and a D2D receiver). and These are the transmit power for cellular users (CU) and D2D transmitters (DT), respectively.

[0080] In Step 2, the constraints established include:

[0081] Transmit power and transmission power Meets transmit power constraints:

[0082] , (2);

[0083] Among them and It refers to the transmitter, that is, the minimum and maximum transmit power of CU and DT;

[0084] Furthermore, the QoS (Quality of Service) requirements for both the uplink cellular link and the D2D link also need to be met. Assuming that the QoS requirements are measured by the achievable spectrum efficiency (SE) of the uplink cellular link and the D2D link, the following constraints apply:

[0085] , (3);

[0086] , (4);

[0087] in , , , These refer to the channel gain between the cellular user (CU, i.e., mobile terminal) and the base station (BS), the D2D transmitter (DT) and the base station (BS), the D2D transmitter (DT) and the D2D receiver (DR), and the cellular user (CU) and the D2D receiver (DR). It is the power spectral density of Gaussian white noise. and It is the QoS requirement for uplink cellular links and D2D links, measured in terms of achievable spectrum efficiency (SE).

[0088] Step 3 includes the following steps:

[0089] Step 3-1) Based on the constraints in Step 2, use variables ,variable Replacement of cellular user CU transmit power The transmit power of the D2D transmitter (DT) , will solve and The optimal power allocation problem is transformed into a linear programming problem in the xOy plane (in a Cartesian coordinate system) as follows:

[0090]

[0091] Step 3-2) Based on problem (4), constraints (4c) (from (3)) and (4d) (from (4)), set the equipotential lines as follows:

[0092] Isopotential lines : (5)

[0093] Isopotential lines : (6)

[0094] Isopotential lines : , (7);

[0095] Step 3-3) Obtain equipotential lines Isopotential lines Isopotential lines The slope:

[0096] Isopotential lines The slope is , Isopotential lines The slope is , Isopotential lines The slope is ;

[0097] Steps 3-4) Obtain equipotential lines and equipotential lines and axis, Intersection of axes:

[0098] Isopotential lines and Intersection point E of the axes ,

[0099] Isopotential lines and The intersection point F of the axes ,

[0100] Isopotential lines and The intersection point G of the axes ,

[0101] Isopotential lines and The intersection point H of the axes ,

[0102] Steps 3-5) yield the following:

[0103] Isopotential lines With line CD: Intersection I ,

[0104] Isopotential lines With line BC: Intersection J ,

[0105] Isopotential lines With equipotential lines intersection point K .

[0106] In Step 4, when solving for the power allocation in Step 3, the goal is to find the value that minimizes the weighted power (WSP) of a pair of uplink cellular links (D2D links). The specifics depend on and Classify and judge the size relationship;

[0107] The specific steps are as follows:

[0108] Step 4-1) Judgment Does it satisfy the condition? If so, then the equipotential lines are... With equipotential lines Parallel (as shown in Figure 1) or equipotential lines With equipotential lines If they intersect in the third quadrant (as shown in Figure 2), then No solution found; otherwise, proceed to step 4-2.

[0109] Step 4-2) (At this time) )judge (As shown in Figure 3) or (As shown in Figure 4) Does it satisfy the condition? If it does, then No solution found; otherwise, proceed to step 4-3.

[0110] Step 4-3) (At this time) )judge and (As shown in Figure 5) Do they simultaneously satisfy the following conditions? If so, the optimal power solution is: Otherwise, proceed to step 4-4;

[0111] Step 4-4) (At this time) )judge or ,and (As shown in Figure 6) Do they satisfy simultaneously? If so, then Otherwise, proceed to steps 4-5;

[0112] Steps 4-5: (At this time) )judge or ,and (As shown in Figure 7) Do they satisfy simultaneously? If so, then ;

[0113] Based on the above, the optimal power allocation with the minimum weighted power WSP is obtained. and .

[0114] The power allocation method described herein aims to minimize the system weighted power (WSP) of a pair of uplink cellular links (D2D links).

[0115] An uplink cellular link-D2D link system includes a base station (BS), a cellular user (CU), a D2D transmitter (DT), and a D2D receiver (DR). It is assumed that the transmission directions of the uplink cellular link and the D2D link remain constant throughout the communication process; the link from the CU to the BS is called the uplink cellular link, and the link from the DT to the DR is called the D2D link; spectrum resources are allocated by the network's central control node, the base station (BS).

[0116] Example:

[0117] This embodiment (see Figure 11) verifies the optimality of the proposed solution and evaluates its performance through numerical simulation. A single-cell cellular network with a radius of 500 meters is used, where CU (cell users), DT (D2D transmitter), and DR (D2D receiver) are randomly distributed, and statistical reliability is ensured through 1,000 Monte Carlo experiments. Key parameter settings are as follows: dBm, dBm; dBm / Hz; and ; bps / Hz, bps / Hz.

[0118] The channel model incorporates the following elements: (i) a log-distance path loss model with a path loss exponent of 3.8; (ii) log-normal shadowing fading with a standard deviation of 8 dB; and (iii) independent and identically distributed cyclic symmetric complex Gaussian coefficients. Rayleigh's decline.

[0119] This scheme is compared with three benchmark schemes: (i) based on exhaustive search (power step size is...) The optimal scheme (dB); (ii) a random power allocation scheme; (iii) an energy efficiency (EE) maximization scheme (also using a step size of dB). Exhaustive search of dB).

[0120] Table 1 Weighted Power (WSP) of Four Schemes Relationship

[0121]

[0122] Figure 8 or Table 1 shows the link-to-weighted power WSP. The changing trend of the weighted power WSP for all schemes except the random scheme. The curve increases monotonically. It is noteworthy that the curve of the optimal solution based on exhaustive search completely overlaps with that of the solution in this invention, verifying that the solution in this invention achieves the minimum weighted power WSP. The random solution has the highest weighted power WSP (i.e., worst performance), while the energy efficiency (EE) maximization solution has a weighted power WSP that is 15 times that of the solution in this invention.

[0123] Table 2 Energy Efficiency (EE) of Four Schemes Relationship

[0124]

[0125] Figure 9 or Table 2 shows the energy efficiency EE as a function of... The changes are similar to those in Figure 8. The EE performance curves of the proposed solution are completely consistent with those of the optimal solution based on exhaustive search. The EE difference between the energy efficiency EE maximization solution and the proposed solution (approximately a 4-fold difference) is smaller than the weighted power WSP difference in Figure 8, indicating that the proposed solution maintains relatively superior energy efficiency while minimizing the weighted power WSP.

[0126] Table 3 shows the calculation time for the four schemes. Relationship

[0127]

[0128] Figure 10 or Table 3 compares the computation time of different schemes (based on an AMD R9 7945HX CPU, tested on a MATLAB R2023b platform). The scheme of this invention exhibits ultra-low computation time (when...). Only 1.22×10 at bps / Hz -5 The time taken (seconds) is significantly better than the optimal solution based on exhaustive search and the energy efficiency (EE) maximization solution (0.18 seconds). This verifies the feasibility of real-time deployment of the proposed solution.

Claims

1. A geometrically weighted power control method for bottom-layer D2D communication in cellular networks, characterized in that, Includes the following steps: Step 1: Obtain the objective function of the power allocation model between a pair of uplink cellular links and D2D links; Step 2: Establish constraints based on the characteristics of uplink cellular links and D2D links; Step 3: Based on the constraints in Step 2, transform the allocation model in Step 1 into the standard form of linear programming; Step 4: Solve the power allocation problem in Step 3 using a graphical method; In Step 1, the objective function of the power allocation model is the weighted power... ： , (1); where and These are the weights for the uplink cellular link and the D2D link, respectively; and These represent the transmit power for cellular users and D2D transmitters, respectively. In Step 2, the established constraints include: transmit power. and transmission power Meets transmit power constraints: , (2); among them and These are the minimum and maximum transmit powers of the transmitters, i.e., the CU and DT; the QoS (Quality of Service) requirements of the uplink cellular link and D2D link also need to be met; assuming that the QoS requirements are measured by the achievable spectrum efficiency of the uplink cellular link and D2D link; then the following constraints apply: , (3)； (4); among which 、 、 、 These refer to the channel gains between cellular user CU and base station BS, D2D transmitter DT and base station BS, D2D transmitter DT and D2D receiver DR, and cellular user CU and D2D receiver DR. It is the power spectral density of Gaussian white noise. and This refers to the QoS requirements for uplink cellular links and D2D links, measured in terms of achievable spectrum efficiency. Step 3 includes the following steps: Step 3-1) Based on the constraints of Step 2, use variables... ,variable Replacement of cellular user CU transmit power The transmit power of the D2D transmitter (DT) , will solve and The optimal power allocation problem is transformed into a linear programming problem in the Cartesian coordinate system xOy plane as follows: , (4)s.t. , (4a) , (4b) , (4c) (4d); Step 3-2) Based on problem (4), constraints (4c) (from (3)) and (4d) (from (4)), set the equipotential lines as follows: equipotential lines : (5) Equipotential lines : (6) Equipotential lines : (7); Step 3-3) Obtain the equipotential lines Isopotential lines Isopotential lines Slope: Isopotential lines The slope is , Isopotential lines The slope is , Isopotential lines The slope is Steps 3-4) Obtain equipotential lines and equipotential lines and axis, Intersection of axes: equipotential lines and Intersection point E of the axes equipotential lines and The intersection point F of the axes , Isopotential lines and The intersection point G of the axes , Isopotential lines and The intersection point H of the axes Steps 3-5) Obtain equipotential lines Intersection with line CD, equipotential lines The intersection with line BC, and the equipotential lines With equipotential lines The intersection point.

2. The method according to claim 1, characterized in that, in, Isopotential lines With line CD: The intersection point is I 。 3. The method according to claim 1, characterized in that, in, Isopotential lines With line BC: The intersection point is J 。 4. The method according to claim 1, wherein, Isopotential lines With equipotential lines intersection point K 。 5. The method according to claim 1, characterized in that, In Step 4, when solving for the power allocation in Step 3, the goal is to find the value that minimizes the weighted power (WSP) of a pair of uplink cellular links (D2D links). The specifics depend on and Classify and judge the size relationship; the specific steps are as follows: Step 4-1) Judge Does it satisfy the condition? If so, then the equipotential lines are... With equipotential lines Parallel or equipotential lines With equipotential lines If they intersect in the third quadrant, then No solution found, otherwise proceed to step 4-2; Step 4-2) At this point Judgment or Does it satisfy the condition? If it does, then... No solution found, otherwise proceed to step 4-3; Step 4-3) At this point Judgment and Do they satisfy the following conditions simultaneously? If they do, then the optimal power solution is: Otherwise, proceed to step 4-4; Step 4-4) At this point Judgment or ,and Do they satisfy simultaneously? If so, then Otherwise, proceed to step 4-5; Step 4-5: At this point judgment or ,and Do they satisfy simultaneously? If so, then The above steps yield the optimal power allocation with the minimum weighted power (WSP). and 。 6. The method according to claim 5, characterized in that, The goal is to minimize the system weighted power (WSP) encompassing the entirety of a pair of uplink cellular links – D2D links. The uplink cellular link-D2D link system includes a base station (BS), a cellular user unit (CU), a D2D transmitter (DT), and a D2D receiver (DR). Assume that the transmission directions of the uplink cellular link and the D2D link remain unchanged throughout the communication process; The link from a cellular user (CU) to a base station (BS) is called an uplink cellular link, and the link from a D2D transmitter (DT) to a D2D receiver (DR) is called a D2D link. Spectrum resources are allocated by the network's central control node, namely the base station (BS).

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