A visible light communication system power optimization device and method based on RIS

Abstract

The present invention provides a power optimization device and method for a visible light communication system based on RIS, and relates to the technical field of wireless communication. A working mode switching scheme for a LoS link and a NLoS link is proposed, that is, based on the power consumption in different working modes and the power consumption caused by switching the working modes, a working mode strategy selection problem is defined with the goal of minimizing long-term average power consumption, a feedback signal sent by a receiving end device is received, and the probability of the LoS link being blocked by an obstacle is estimated in combination with the feedback signal, and the defined strategy selection problem is solved based on the probability of the LoS link being blocked by the obstacle, so as to obtain a working mode selection strategy for the next time period, thereby reducing the long-term average power consumption of the RIS-VLC system. In addition, considering the use of spatial modulation for RIS when transmitting data using an NLoS link, the data rate can be increased and the power required by the transmitting end device can be reduced.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of wireless communication, and in particular to a visible light communication system power optimization device and method based on RIS. Background Art

[0002] In recent years, with the rapid development of communication technology, the explosive growth of emerging services such as augmented reality / virtual reality (AR / VR), high-definition video, and cloud computing has brought huge traffic demand. Traditional wireless communications based on radio frequency (RF) are facing an increasingly serious spectrum shortage problem. Visible light communication (VLC), as a communication technology that uses visible light for data transmission, has become a promising alternative to traditional RF communication due to its advantages such as rich spectrum resources, anti-electromagnetic interference, and high security.

[0003] However, VLC relies heavily on line-of-sight (LoS) links. Once the LoS link is blocked, VLC communication will be interrupted. To address this challenge, an effective measure is to transmit signals through non-line-of-sight (NLoS) links. Among them, reconfigurable intelligent surfaces (RISs) (also called RIS smart metasurfaces) can be used to reflect optical signals and have been widely studied in VLC systems.

[0004] Existing VLC communication systems mainly adopt two solutions to deal with the blocking of LoS links: 1) mixing with traditional networks such as IR or RF, switching to IR links or RF links when the VLC link is blocked; 2) using RIS, enabling NLoS links reflected by RIS when the VLC link is blocked. Both solutions do not consider the power consumption when using different links and when switching links, and do not consider the dynamic changes in the blocking probability of LoS links. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a visible light communication system power optimization device and method based on RIS in view of the deficiencies in the prior art.

[0006] On the one hand, the technical solution of the present invention to solve the above technical problem is as follows: a power optimization device for a visible light communication system based on RIS, comprising a control processing end, a transmitting end device respectively connected to the control processing end, a RIS intelligent metasurface and a receiving end device;

[0007] The control processing end is used to set a first working mode and a second working mode of data transmission, wherein the first working mode is that when the LoS link is not blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the LoS link, and when the LoS link is blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the NLoS link via the RIS smart metasurface reflection; the second working mode is that when the LoS link is blocked by an obstacle, the RIS smart metasurface is spatially modulated, and the transmitting end device transmits data with the receiving end device through the modulated RIS smart metasurface;

[0008] The control processing end is also used to define the strategy selection problem of the working mode based on the power consumption in different working modes and the power consumption caused by switching the working mode, with the goal of minimizing the long-term average power consumption;

[0009] A feedback signal sent by the receiving end device is received, and the probability of the LoS link being blocked by an obstacle is estimated in combination with the feedback signal, and a defined strategy selection problem is solved based on the probability of the LoS link being blocked by an obstacle to obtain a working mode selection strategy for the next time period.

[0010] The beneficial effects of the present invention are: it can consider the power consumption when using different links and when switching links, define and solve the strategy selection problem of the working mode, obtain the selection strategy for switching under different working modes, and determine the working mode for the next time period, which can reduce the long-term average power consumption of the system, thereby realizing an energy-saving system.

[0011] Based on the above technical solution, the present invention can also be improved as follows.

[0012] Furthermore, the strategy selection problem of defining the working mode with the goal of minimizing the long-term average power consumption is specifically as follows:

[0013] The first working mode and the second working mode are represented as M0 and M1 respectively, and the data transmission time t is divided into T time periods, represented by t=0, 1, ..., T. The probability that the LoS link is blocked by an obstacle is p t , and in each time period, p t Keeping the same, in different time periods, p t are independent and identically distributed random variables,

[0014] In working mode M0, when the LoS link is not blocked by an obstacle, the probability that the LoS link is not blocked by an obstacle is 1-p t , then the corresponding power consumption of the transmitting device is P L, when the LoS link is blocked by an obstacle, data is transmitted through the NLoS link, and the power consumption of the transmitting device is P M , in working mode M1, the RIS smart metasurface is spatially modulated, and the power consumption of the transmitting end device is P N ; Assume that the power consumption caused by switching between working mode M0 and working mode M1 is P S ;

[0015] The problem of selecting a working mode is defined based on a Markov decision process, wherein the definition of the problem of selecting a working mode includes the definition of behavior, state, transition probability, immediate cost and working mode selection strategy.

[0016] The behavior is defined as follows: In the tth time period, behavior a t Select from the set {0, 1}, a t =0 means selecting working mode M0, a t =1 means selecting working mode M1;

[0017] The state is defined as follows: In the tth time period, the state definition s t For t =(p t , a t-1 ), where p t is the probability that the LoS link is blocked by an obstacle in the tth time period, a t-1 is the behavior in the (t-1)th time period, the transmitting device is based on the state s t Select Behavior a t , get the state s of the next period t+1 ;

[0018] The transition probability is defined as follows: The transition probability Pr(s′|s, a) is defined as Pr(s′|s, a)=Pr(p′|p)=Pr(p′), which is the probability that the system transfers to a new state s′ after executing behavior a in state s;

[0019] The instantaneous cost is defined as: t Execute behavior a t The immediate cost is c(s t , a t ) indicates that the total power consumption of the system is measured as:

[0020] c[s t =(p t , a t-1 ), a t ]=#

[0021]

[0022] The working mode selection strategy π is defined as: a t =π(s t );

[0023] Based on the definition of the working mode selection problem, the long-term average power consumption of the system is expressed as:

[0024]

[0025] The strategy selection problem with the goal of optimizing long-term average power consumption is expressed as:

[0026]

[0027] The beneficial effect of adopting the above further scheme is: based on Markov decision, the working mode selection problem is defined in terms of behavior, state, transition probability, immediate cost and working mode selection strategy, and the long-term average power consumption and strategy selection problem of the system are expressed in combination with the above definitions, laying the foundation for the subsequent rapid solution to the strategy selection problem.

[0028] Furthermore, the probability of the LoS link being blocked by an obstacle is used to solve the defined strategy selection problem, and the working mode selection strategy for the next time period is obtained, which is specifically:

[0029] Solving the strategy selection problem through an optimal strategy includes:

[0030] (P1) satisfies the Bellman equation:

[0031]

[0032] in, For state s in the optimal strategy π * The relative value function under * is the corresponding average cost, Pr(s′|s,a) is the transition probability, c(s,a) is the immediate cost of executing behavior a in state s,

[0033] The optimal strategy is:

[0034]

[0035] in,

[0036]

[0037]

[0038] is the p that satisfies the working mode switching condition under the optimal strategy t The lower threshold, p tis the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the optimal strategy t The upper threshold of

[0039] Furthermore, the probability of the LoS link being blocked by an obstacle is used to solve the defined strategy selection problem, and the working mode selection strategy for the next time period is obtained, which is specifically:

[0040] The strategy selection problem is solved by a greedy strategy, including:

[0041]

[0042] in,

[0043]

[0044]

[0045] is the p that satisfies the working mode switching condition under the optimal strategy t The lower threshold, p t represents the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the optimal strategy t The upper threshold of

[0046] Furthermore, the probability of the LoS link being blocked by an obstacle is used to solve the defined strategy selection problem, and the working mode selection strategy for the next time period is obtained, which is specifically:

[0047] The strategy selection problem is solved by machine learning strategies, including:

[0048] Construct a neural network with parameter θ, the dimension of the input layer of the neural network is 2, which represents the current working mode and the probability p that the LoS link is blocked by an obstacle in the tth time period t , the output layer of the neural network is used to output a t =0 and a t =1,

[0049] The neural network with parameter θ is:

[0050] a t =π θ (s t ).

[0051] The beneficial effect of adopting the above further scheme is that the strategy selection problem can be solved by three strategies, namely the optimal strategy, the greedy strategy and the machine learning strategy. According to the probability that the LoS link is blocked by an obstacle in the current period and the switching behavior of the system in the previous period, the working mode of the system in the next period is determined, the best selection of the working mode is achieved, and the long-term average power consumption of the system is reduced.

[0052] Furthermore, in the control processing end, the RIS intelligent metasurface is spatially modulated, specifically:

[0053] The multiple array elements in the RIS smart metasurface are divided into multiple RIS groups, and the data to be transmitted is divided into multiple data groups. The corresponding RIS groups are activated according to the bit data specified in the data groups. The activated RIS groups are used to reflect optical signals to transmit the data of the transmitting device to the receiving device.

[0054] When the system works in M1 mode, the RIS array is spatially modulated, that is, the RIS elements are divided into different groups. At each moment, only one group of RIS elements is activated to reflect signals. The transmitted data determines which group of elements is activated. Compared with the system that only uses RIS to reflect signals, spatial modulation can further increase the data rate. Moreover, for the same NLoS link, to achieve the same bit error rate, the transmission power required by using spatial modulation is lower than that required by not using spatial modulation, which can reduce power consumption.

[0055] Furthermore, the transmitting end device includes a light source; and the receiving end device includes a photodetector.

[0056] On the other hand, the present invention provides a visible light communication system power optimization method based on RIS smart metasurface, which is applied to a visible light communication system power optimization device based on RIS smart metasurface, including a control processing end, a transmitting end device respectively connected to the control processing end, a RIS smart metasurface and a receiving end device; the method includes:

[0057] The control processing end sets a first working mode and a second working mode of data transmission, wherein the first working mode is that when the LoS link is not blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the LoS link, and when the LoS link is blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the NLoS link via the RIS smart metasurface reflection; the second working mode is that when the LoS link is blocked by an obstacle, the RIS smart metasurface is spatially modulated, and the transmitting end device transmits data with the receiving end device through the modulated RIS smart metasurface;

[0058] Based on the power consumption in different working modes and the power consumption caused by switching working modes, the strategy selection problem of defining the working mode is to minimize the long-term average power consumption;

[0059] A feedback signal sent by the receiving end device is received, and the probability of the LoS link being blocked by an obstacle is estimated in combination with the feedback signal, and a defined strategy selection problem is solved based on the probability of the LoS link being blocked by an obstacle to obtain a working mode selection strategy for the next time period. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A schematic diagram of a scenario of an operating mode M0 of a visible light communication system power optimization device provided by an embodiment of the present invention;

[0061] Figure 2 A schematic diagram of a scenario of working mode M1 of a visible light communication system power optimization device provided by an embodiment of the present invention;

[0062] Figure 3 A state transition diagram under the optimal strategy provided by an embodiment of the present invention;

[0063] Figure 4 This is a comparison chart of the long-term average power consumption of the three switching schemes provided in the embodiment of the present invention and the traditional scheme. DETAILED DESCRIPTION

[0064] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0065] The technical solution in the embodiment of the present application will be described below in conjunction with the drawings in the embodiment of the present application. In the description of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; "and / or" in the present application is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

[0066] Furthermore, in the description of this application, unless otherwise specified, "plurality" means two or more than two. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0067] In addition, in order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, words such as "first" and "second" are used to distinguish the same items or similar items with substantially the same functions and effects. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference.

[0068] Meanwhile, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete manner for ease of understanding.

[0069] In recent years, with the rapid development of communication technology, the explosive growth of emerging services such as augmented reality / virtual reality (AR / VR), high-definition video, and cloud computing has brought huge traffic demand. Traditional wireless communications based on radio frequency (RF) are facing an increasingly serious spectrum shortage problem. Visible light communication (VLC), as a communication technology that uses visible light for data transmission, has become a promising alternative to traditional RF communication due to its advantages such as rich spectrum resources, anti-electromagnetic interference, and high security.

[0070] However, VLC relies heavily on line-of-sight (LoS) links. Once the LoS link is blocked, VLC communication will be interrupted. To address this challenge, an effective measure is to transmit signals through non-line-of-sight (NLoS) links. Among them, reconfigurable intelligent surfaces (RISs) (also called RIS, smart reflective surfaces or RIS smart metasurfaces) can be used to reflect optical signals and have been widely studied in VLC systems. RIS consists of many artificial components that can be individually programmed to modify the characteristics of the incident signal, including amplitude and phase, without incurring additional power consumption. Currently, researchers have explored the role of integrating RIS into VLC systems in improving performance such as data rate and bit error rate (BER).

[0071] The traditional RIS-VLC system ignores the power change of the light source (such as LED) to achieve the same system performance when the LoS link is blocked by an obstacle, or does not consider the power change caused by the switching of the system working mode (i.e., using LoS link or NLoS link).

[0072] In view of the fact that the existing technology does not consider the long-term power consumption of the RIS-VLC system, the present invention considers the dynamic change of the blocking probability of the LoS link while ensuring that the data rate and target bit error rate of the communication system remain unchanged, and proposes a switching method between the LoS link and the NLoS link, aiming to reduce the long-term average power consumption of the RIS-VLC system. In addition, the use of spatial modulation on the RIS when transmitting data using the NLoS link is considered to increase the data rate and reduce the power required by the transmitting device.

[0073] like Figure 1 , Figure 2 As shown, an embodiment of the present invention provides a visible light communication system power optimization device based on a RIS smart metasurface, including a control processing end, a transmitting end device respectively connected to the control processing end, a RIS smart metasurface, and a receiving end device;

[0074] The control processing end is used to set a first working mode and a second working mode of data transmission, wherein the first working mode is that when the LoS link is not blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the LoS link, and when the LoS link is blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the NLoS link via the RIS smart metasurface reflection; the second working mode is that when the LoS link is blocked by an obstacle, the RIS smart metasurface is spatially modulated, and the transmitting end device transmits data with the receiving end device through the modulated RIS smart metasurface;

[0075] The control processing end is also used to define the strategy selection problem of the working mode based on the power consumption in different working modes and the power consumption caused by switching the working mode, with the goal of minimizing the long-term average power consumption;

[0076] A feedback signal sent by the receiving end device is received, and the probability of the LoS link being blocked by an obstacle is estimated in combination with the feedback signal, and a defined strategy selection problem is solved based on the probability of the LoS link being blocked by an obstacle to obtain a working mode selection strategy for the next time period.

[0077] For example, Figure 1 , Figure 2 As shown, the power optimization device of the visible light communication system includes a RIS-VLC communication system (referred to as the system), and the RIS-VLC communication system includes a transmitting end device (such as a light source), a receiving end device (such as a photodetector) and a RIS smart metasurface. The light source can be an LED lamp, and the photodetector can be a single PD or a PD array.

[0078] For example, the RIS-VLC communication system includes an LED lamp, a RIS smart metasurface, and a PD array. The RIS smart metasurface only adjusts the reflection direction of the incident light, but does not change the amplitude of the incident light. The total power consumption of the system comes only from the LED.

[0079] It should be understood that LED has both lighting and data transmission functions. It can be considered that the power consumed by lighting is certain. The present invention only focuses on the optimization of power consumption for data transmission.

[0080] It should be understood that when the LoS link is not blocked by obstacles, data is mainly transmitted through the LoS link. At this time, the NLoS link is also used to transmit data, but only plays an auxiliary role to enhance the received signal.

[0081] The power optimization device of the visible light communication system also includes a central controller (i.e., a control processing end) for analyzing and processing the working mode selection strategy, and switching the working mode according to the working mode selection strategy result. When the rate and bit error rate requirements set by the RIS-VLC communication system are met, by adopting a dynamic link selection scheme of LED direct link and RIS link, when the LoS link is blocked by an obstacle with a dynamically changing probability, compared with the traditional RIS enhanced VLC system, the traditional RIS-VLC system ignores the LED power change when the LoS link is blocked by an obstacle to achieve the same system performance, or does not consider the power change caused by the switching of the system working mode (i.e., using the LoS link or the NLoS link), the proposed method reduces the long-term average power consumption of the system.

[0082] In the above embodiment, the power consumption when using different links and when switching links can be considered, the strategy selection problem of the working mode can be defined and solved, and the selection strategy for switching between different working modes is obtained to determine the working mode for the next time period, which can reduce the long-term average power consumption of the system, thereby realizing an energy-saving system.

[0083] In some embodiments, the strategy selection problem of defining the working mode with the goal of minimizing the long-term average power consumption is specifically:

[0084] The first working mode and the second working mode are represented as M0 and M1 respectively, and the data transmission time t is divided into T time periods, represented by t=0, 1, ..., T. Suppose the probability that the LoS link is blocked by an obstacle is p t , and in each time period, p t Keeping the same, in different time periods, p t are independent and identically distributed random variables,

[0085] In working mode M0, when the LoS link is not blocked by an obstacle, the probability that the LoS link is not blocked by an obstacle is 1-p t , then the corresponding power consumption of the transmitting device is P L , when the LoS link is blocked by an obstacle, data is transmitted through the NLoS link, and the power consumption of the transmitting device is P M , in working mode M1, the RIS smart metasurface is spatially modulated, and the power consumption of the transmitting end device is P N ; Assume that the power consumption caused by switching between working mode M0 and working mode M1 is P S ;

[0086] It should be understood that, in general, the path loss of a LoS link is lower than that of an NLoS link, so that in order to achieve the same bit error rate (BER) performance, the required transmit power is also lower; in addition, for the same NLoS link, if spatial modulation is used, the required transmit power is also lower than the transmit power when spatial modulation is not used. L <P N <P M In addition, suppose the power consumption caused by switching between working mode M0 and working mode M1 is P S For example, the power consumption caused by the LED switching between the two working modes M0 and M1 is P S .

[0087] Afterwards, in order to save long-term average power consumption, the transmission mode in each period should be selected according to the system status. In order to find the optimal selection strategy, the mode selection problem is modeled as a discrete Markov decision process to determine the continuous transmission mode to minimize the long-term average power consumption.

[0088] The problem of selecting a working mode is defined based on a Markov decision process, wherein the definition of the problem of selecting a working mode includes the definition of selection behavior, state, transition probability, immediate cost and working mode selection strategy.

[0089] The behavior is defined as follows: In the tth time period, behavior a t Select from the set {0, 1}, a t =0 means selecting working mode M0, a t =1 means selecting working mode M1;

[0090] The state is defined as follows: In the tth time period, the state definition s t For t =(p t , a t-1 ), where p t is the probability that the LoS link is blocked by an obstacle in the tth time period, at-1 is the behavior in the (t-1)th time period, the transmitting device is based on the state s t Select Behavior a t , get the state s of the next period t+1 ;

[0091] The transition probability is defined as follows: The transition probability Pr(s′|s, a) is defined as Pr(s′|s, a)=Pr(p′|p)=Pr(p′), which is the probability that the system transfers to a new state s′ after executing behavior a in state s;

[0092] The instantaneous cost is defined as: t Execute behavior a t The immediate cost is c(s t , a t ) indicates that the total power consumption of the system is measured as:

[0093] c[s t =(p t , a t-1 ), a t ]=#

[0094]

[0095] The working mode selection strategy π is defined as: a t =π(s t )

[0096] Based on the definition of the working mode selection problem, the long-term average power consumption of the system is expressed as:

[0097]

[0098] The strategy selection problem with the goal of optimizing long-term average power consumption is expressed as:

[0099]

[0100] In the above embodiment, the behavior, state, transition probability, immediate cost and working mode selection strategy of the working mode selection problem are defined based on Markov decision making. The long-term average power consumption and strategy selection problem of the system are expressed in combination with the above definitions, laying the foundation for the subsequent rapid solution to the strategy selection problem.

[0101] The receiving end device feeds back a signal of received data to the control processing end. The control processing end estimates the probability that the LoS link is blocked by an obstacle based on the feedback signal, and solves the defined strategy selection problem based on the probability that the LoS link is blocked by an obstacle to obtain the working mode selection strategy for the next time period. The following embodiments provide three strategy solution solutions, but are not limited to these three solutions.

[0102] Specifically:

[0103] Solving the strategy selection problem through an optimal strategy includes:

[0104] (P1) satisfies the Bellman equation:

[0105]

[0106] in, The relative value function of state s under the optimal policy π*, g* is the corresponding average cost, Pr(s′|s,a) is the transition probability, c(s,a) is the immediate cost of executing behavior a in state s,

[0107] The optimal strategy is:

[0108]

[0109] in,

[0110]

[0111]

[0112] is the p that satisfies the working mode switching condition under the optimal strategy t The lower threshold, p t is the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the optimal strategy t The upper threshold of

[0113] Figure 3 is the state transition diagram under the optimal strategy. Figure 3 As shown, when When , the working mode is M0; when When , the working mode is M1; when When the working mode switches from M0 to M1, , the working mode switches from M1 to M0.

[0114] Alternatively, the strategy selection problem is solved by a greedy strategy, including:

[0115]

[0116] in,

[0117]

[0118]

[0119] is the p that satisfies the working mode switching condition under the greedy strategy t The lower threshold, p t is the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the greedy strategy t The upper threshold of

[0120] Alternatively, the strategy selection problem is solved by a machine learning strategy, including:

[0121] Construct a neural network with parameter θ, the dimension of the input layer of the neural network is 2, which represents the current working mode and the probability p that the LoS link is blocked by an obstacle in the tth time period t , the output layer of the neural network is used to output a t =0 and a t =1,

[0122] The neural network with parameter θ is:

[0123] a t =π θ (s t ).

[0124] According to the above strategy, the working mode of the system in the next time period can be determined (ie, M0 or M1 is selected).

[0125] In order to intuitively illustrate the power consumption of the solution proposed by the present invention compared with the traditional system, the simulation results are given below. Among them, the strategy based on machine learning takes deep reinforcement learning (DRL) as an example. The simulation parameters are shown in Table 1:

[0126] Table 1

[0127] Physical quantity symbol value <![CDATA[LED power in M0 mode when not blocked]]> <![CDATA[P L ]]> 2.24mW <![CDATA[LED power in M0 mode when LoS link is blocked]]> <![CDATA[P M ]]> 12.59mW <![CDATA[LED power in M1 mode]]> <![CDATA[P N ]]> 6.8mW <![CDATA[Power consumption of LED conversion between two working modes M0 and M1]]> <![CDATA[P S ]]> 1.5mW

[0128] The simulation results are as follows Figure 4 As shown, it can be seen that, compared with a constant system that continuously uses one working mode, the three switching schemes proposed by the present invention are all helpful in reducing the long-term average power consumption, thereby realizing an energy-saving system.

[0129] In the above embodiment, the strategy selection problem can be solved by three strategies, namely, the optimal strategy, the greedy strategy and the machine learning strategy. According to the probability that the LoS link is blocked by an obstacle in the current period and the switching behavior of the system in the previous period, the working mode of the system in the next period is determined to achieve the best selection of the working mode, thereby reducing the long-term average power consumption of the system.

[0130] In some embodiments, in the control processing end, spatial modulation is performed on the RIS smart metasurface, specifically:

[0131] The multiple array elements in the RIS smart metasurface are divided into multiple RIS groups, and the data to be transmitted is divided into multiple data groups. The corresponding RIS groups are activated according to the bit data specified in the data groups. The activated RIS groups are used to reflect optical signals to transmit the data of the transmitting device to the receiving device.

[0132] For example, assuming that RIS is divided into 4 groups, the index of each group can represent 2 bits. For example, the first group is represented by bit 00; the second group is represented by bit 01; the third group is represented by bit 10; and the fourth group is represented by bit 11. It is stipulated that the system transmitter transmits 4 bits to the receiver at each moment. The first 2 of these 4 bits are represented by the index of the RIS group, and the last 2 are transmitted by the light source. Assuming that a string of bits 01101000 is to be transmitted now, then 0110 is transmitted at the first moment, and the first two bits 01 are reflected by the second group RIS, that is, at this moment, the first, third, and fourth groups of RIS are not activated and do not reflect optical signals. Only the second group of RIS is activated to reflect optical signals, thereby representing the first two bits 01; the last two bits 10 modulate the light source and are transmitted through optical signals.

[0133] When the system works in M1 mode, the RIS array is spatially modulated, that is, the RIS elements are divided into different groups. At each moment, only one group of RIS elements is activated to reflect signals. The transmitted data determines which group of elements is activated. Compared with the system that only uses RIS to reflect signals, spatial modulation can further increase the data rate. Moreover, for the same NLoS link, to achieve the same bit error rate, the transmission power required by using spatial modulation is lower than that required by not using spatial modulation, which can reduce power consumption.

[0134] In some embodiments, the receiving end device is a PD array, and the PD array includes a plurality of units;

[0135] The control processing end is also used to reflect the transmission data of all array elements in the RIS intelligent metasurface in the form of optical signals to the units specified by the PD array.

[0136] When the system works in M1 mode, not only can the RIS array be spatially modulated, but also the RIS array can be generalized spatially modulated, that is, more than one group of RIS array elements can be activated each time according to the data; the PD array can also be spatially modulated, that is, all RIS array elements can be controlled to reflect light to only one of the PD arrays; the PD array can also be generalized spatially modulated, that is, all RIS array elements can be controlled to reflect light to multiple PDs in the PD array; the RIS and PD arrays can also be jointly spatially modulated, that is, different groups of RIS can be activated each time to reflect light to different PDs, so as to transmit more information and further improve the communication rate.

[0137] The embodiment of the present invention further provides a visible light communication system power optimization method based on RIS, which is applied to a visible light communication system power optimization device based on RIS, including a control processing end, a transmitting end device respectively connected to the control processing end, a RIS smart metasurface, and a receiving end device; the method includes:

[0138] The control processing end sets a first working mode and a second working mode of data transmission, wherein the first working mode is that when the LoS link is not blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the LoS link, and when the LoS link is blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the NLoS link via the RIS smart metasurface reflection; the second working mode is that when the LoS link is blocked by an obstacle, the RIS smart metasurface is spatially modulated, and the transmitting end device transmits data with the receiving end device through the modulated RIS smart metasurface;

[0139] Based on the power consumption in different working modes and the power consumption caused by switching working modes, the strategy selection problem of defining the working mode is to minimize the long-term average power consumption;

[0140] A feedback signal sent by the receiving end device is received, and the probability of the LoS link being blocked by an obstacle is estimated in combination with the feedback signal, and a defined strategy selection problem is solved based on the probability of the LoS link being blocked by an obstacle to obtain a working mode selection strategy for the next time period.

[0141] In some embodiments, the strategy selection problem of defining the working mode with the goal of minimizing the long-term average power consumption is specifically:

[0142] The first working mode and the second working mode are represented as M0 and M1 respectively, and the data transmission time t is divided into T time periods, represented by t=0, 1, ..., T. Suppose the probability that the LoS link is blocked by an obstacle is p t , and in each time period, pt Keeping the same, in different time periods, p t are independent and identically distributed random variables,

[0143] In working mode M0, when the LoS link is not blocked by an obstacle, the probability that the LoS link is not blocked by an obstacle is 1-p t , then the corresponding power consumption of the transmitting device is P L , when the LoS link is blocked by an obstacle, data is transmitted through the NLoS link, and the power consumption of the transmitting device is P M , in working mode M1, the RIS smart metasurface is spatially modulated, and the power consumption of the transmitting end device is P N ; Assume that the power consumption caused by switching between working mode M0 and working mode M1 is P S ;

[0144] The problem of selecting a working mode is defined based on a Markov decision process, wherein the definition of the problem of selecting a working mode includes the definition of behavior, state, transition probability, immediate cost and working mode selection strategy.

[0145] The behavior is defined as follows: In the tth time period, behavior a t Select from the set {0, 1}, a t =0 means selecting working mode M0, a t =1 means selecting working mode M1;

[0146] The state is defined as follows: In the tth time period, the state definition s t For t =(p t , a t-1 ), where p t is the probability that the LoS link is blocked by an obstacle in the tth time period, a t-1 is the behavior in the (t-1)th time period, the transmitting device is based on the state s t Select Behavior a t , get the state s of the next period t+1 ;

[0147] The transition probability is defined as follows: The transition probability Pr(s′|s, a) is defined as Pr(s′|s, a)=Pr(p′|p)=Pr(p′), which is the probability that the system transfers to a new state s′ after executing behavior a in state s;

[0148] The instantaneous cost is defined as: t Execute behavior a t The immediate cost is c(s t , a t) indicates that the total power consumption of the system is measured as:

[0149] c[s t =(p t , a t-1 ), a t ]=#

[0150]

[0151] The working mode selection strategy π is defined as: a t =π(s t );

[0152] Based on the definition of the working mode selection problem, the long-term average power consumption of the system is expressed as:

[0153]

[0154] The strategy selection problem with the goal of optimizing long-term average power consumption is expressed as:

[0155]

[0156] In some embodiments, the probability of the LoS link being blocked by an obstacle is used to solve the defined strategy selection problem to obtain the working mode selection strategy for the next time period, specifically:

[0157] Solving the strategy selection problem through an optimal strategy includes:

[0158] (P1) satisfies the Bellman equation:

[0159]

[0160] in, is the relative value function of state s under the optimal strategy π*, g* is the corresponding average cost, Pr(s′|s, a) is the transition probability, c(s, a) is the immediate cost of executing behavior a in state s,

[0161] The optimal strategy is:

[0162]

[0163] in,

[0164]

[0165]

[0166] is the p that satisfies the working mode switching condition under the optimal strategy t The lower threshold, p trepresents the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the optimal strategy t The upper threshold of

[0167] In some embodiments, the probability of the LoS link being blocked by an obstacle is used to solve the defined strategy selection problem to obtain the working mode selection strategy for the next time period, specifically:

[0168] The strategy selection problem is solved by a greedy strategy, including:

[0169]

[0170] in,

[0171]

[0172]

[0173] is the p that satisfies the working mode switching condition under the greedy strategy t The lower threshold, p t is the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the greedy strategy t The upper threshold of

[0174] In some embodiments, the probability of the LoS link being blocked by an obstacle solves the defined strategy selection problem to obtain the working mode selection strategy for the next time period, specifically:

[0175] Solving the strategy selection problem through machine learning includes:

[0176] Construct a neural network with parameter θ, the dimension of the input layer of the neural network is 2, which represents the current working mode and the probability p that the LoS link is blocked by an obstacle in the tth time period t , the output layer of the neural network is used to output a t =0 and a t =1,

[0177] The neural network with parameter θ is:

[0178] a t =π θ (s t ).

[0179] The advantages of the present invention are:

[0180] (1) A dynamic link selection scheme is proposed to switch between different working modes of the RIS-VLC system. When the LoS link is blocked by obstacles with a changing probability, the scheme dynamically selects between the transmission mode based on the LoS link and the transmission mode using the NLoS link. While meeting the rate and bit error rate requirements set by the RIS-VLC communication system, the long-term average power consumption of the system is reduced compared with the traditional RIS-enhanced VLC system.

[0181] (2) The dynamic link selection scheme proposed in the present invention aims to minimize the long-term average power consumption of the system, comprehensively considers the probability of the LoS link being blocked by obstacles in the current period and the switching behavior of the system in the previous period, and determines the working mode of the system in the next period;

[0182] (3) When the system operates in M1 mode, the RIS array is spatially modulated. Compared with the system that only uses the RIS reflected signal, the use of spatial modulation can achieve the same data rate and bit error rate with lower power consumption.

[0183] In some schemes, multiple embodiments of the present application can be combined, and the combined scheme can be implemented. Optionally, some operations in the process of each method embodiment are optionally combined, and / or the order of some operations is optionally changed. In addition, the execution order between the steps of each process is only exemplary and does not constitute a restriction on the execution order between the steps. There can also be other execution orders between the steps. It is not intended to indicate that the execution order is the only order in which these operations can be performed. A person of ordinary skill in the art will think of a variety of ways to reorder the operations described herein. In addition, it should be noted that the process details involved in a certain embodiment of this article are also applicable to other embodiments in a similar manner, or different embodiments can be used in combination.

[0184] In addition, some steps in the method embodiment may be equivalently replaced by other possible steps. Alternatively, some steps in the method embodiment may be optional and may be deleted in certain usage scenarios. Alternatively, other possible steps may be added to the method embodiment.

[0185] Furthermore, the various method embodiments may be implemented separately or in combination.

[0186] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0187] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A visible light communication system power optimization device based on RIS, characterized in that: It includes a control processing end, a transmitting end device, a RIS smart metasurface and a receiving end device respectively connected to the control processing end; The control processing end is used to set a first working mode and a second working mode of data transmission, wherein the first working mode is that when the LoS link is not blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the LoS link, and when the LoS link is blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the NLoS link via the RIS smart metasurface reflection; the second working mode is that when the LoS link is blocked by an obstacle, the RIS smart metasurface is spatially modulated, and the transmitting end device transmits data with the receiving end device through the modulated RIS smart metasurface; The control processing end is also used to define the strategy selection problem of the working mode based on the power consumption in different working modes and the power consumption caused by switching the working mode, with the goal of minimizing the long-term average power consumption; A feedback signal sent by the receiving end device is received, and the probability of the LoS link being blocked by an obstacle is estimated in combination with the feedback signal, and a defined strategy selection problem is solved based on the probability of the LoS link being blocked by an obstacle to obtain a working mode selection strategy for the next time period.

2. The visible light communication system power optimization device according to claim 1, characterized in that: The strategy selection problem of defining the working mode with the goal of minimizing the long-term average power consumption is specifically: The first working mode and the second working mode are represented as M0 and M1 respectively, and the data transmission time t is divided into T time periods, represented by t=0, 1, ..., T. The probability that the LoS link is blocked by an obstacle is p t , and in each time period, p t Keeping the same, in different time periods, p is an independent and identically distributed random variable, In working mode M0, when the LoS link is not blocked by an obstacle, the probability that the LoS link is not blocked by an obstacle is 1-p t , then the corresponding power consumption of the transmitting device is P L , when the LoS link is blocked by an obstacle, data is transmitted through the NLoS link, and the power consumption of the transmitting device is P M , in working mode M1, the RIS smart metasurface is spatially modulated, and the power consumption of the transmitting end device is P N ; Assume that the power consumption caused by switching between working mode M0 and working mode M1 is P S ; The problem of selecting a working mode is defined based on a Markov decision process, wherein the definition of the problem of selecting a working mode includes the definition of behavior, state, transition probability, immediate cost and working mode selection strategy. The behavior is defined as follows: In the tth time period, behavior a t Select from the set {0,1}, a t =0 means selecting working mode M0, a t =1 means selecting working mode M1; The state is defined as follows: In the tth time period, the state definition s t For t =(p t ,a t-1 ), where p t is the probability that the LoS link is blocked by an obstacle in the tth time period, a t-1 is the behavior in the (t-1)th time period, the transmitting device is based on the state s t Select Behavior a t , get the state s of the next period t+1 ; The transition probability is defined as: transition probability Pr(s ′ |s,a) is defined as Pr(s ′ |s,a)=Pr(p ′ |p) = Pr(p′), which means the system transfers to the new state s after executing behavior a in state s ′ probability; The instantaneous cost is defined as: t Execute behavior a t The immediate cost is c(s t ,a t ) indicates that the total power consumption of the system is measured as: c[s t =(p t ,a t-1 ),a t ]=# The working mode selection strategy π is defined as: a t =π(s t ); Based on the definition of the working mode selection problem, the long-term average power consumption of the system is expressed as: The strategy selection problem with the goal of optimizing long-term average power consumption is expressed as:

3. The visible light communication system power optimization device according to claim 2, characterized in that: The probability of the LoS link being blocked by an obstacle is used to solve the defined strategy selection problem, and the working mode selection strategy for the next time period is obtained, which is specifically: Solving the strategy selection problem through an optimal strategy includes: (P1) satisfies the Bellman equation: g * +h π* [s]=min a∈{0,1} {c(s,a)+∑ s′ Pr(s′|s,a)h π* [s′]}, Among them, h π* [s] is the optimal strategy π for state s * The relative value function under * is the corresponding average cost, Pr(s′|s,a) is the transition probability, c(s,a) is the immediate cost of executing behavior a in state s, The optimal strategy is: in, is the p that satisfies the working mode switching condition under the optimal strategy t The lower threshold, p t represents the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the optimal strategy t The upper threshold of 4. The visible light communication system power optimization device according to claim 2, characterized in that: The probability of the LoS link being blocked by an obstacle is used to solve the defined strategy selection problem, and the working mode selection strategy for the next time period is obtained, which is specifically: The strategy selection problem is solved by a greedy strategy, including: in, is the p that satisfies the working mode switching condition under the greedy strategy t The lower threshold, p t is the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the greedy strategy t The upper threshold of 5. The visible light communication system power optimization device according to claim 3, characterized in that: The probability that the LoS link is blocked by an obstacle solves the defined strategy selection problem to obtain the working mode selection strategy for the next time period, which is specifically: Solving the strategy selection problem through machine learning includes: Construct a neural network with parameter θ, the dimension of the input layer of the neural network is 2, which represents the current working mode and the probability p that the LoS link is blocked by an obstacle in the tth time period t , the output layer of the neural network is used to output a t =0 and a t =1, The neural network with parameter θ is: a t =π θ (s t )。 6. The visible light communication system power optimization device according to claim 1, characterized in that: In the control processing end, the RIS intelligent metasurface is spatially modulated, specifically: The multiple array elements in the RIS smart metasurface are divided into multiple RIS groups, and the data to be transmitted is divided into multiple data groups. The corresponding RIS groups are activated according to the bit data specified in the data groups. The activated RIS groups are used to reflect optical signals to transmit the data of the transmitting device to the receiving device.

7. The visible light communication system power optimization device according to claim 6, characterized in that: The transmitting end device includes a light source; the receiving end device includes a photodetector.

8. A visible light communication system power optimization method based on RIS, characterized in that: A power optimization device for a visible light communication system based on RIS includes a control processing end, a transmitting end device respectively connected to the control processing end, a RIS smart metasurface, and a receiving end device; the method includes: The control processing end sets a first working mode and a second working mode of data transmission, wherein the first working mode is that when the LoS link is not blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the LoS link, and when the LoS link is blocked by an obstacle, the transmitting end device transmits data with the receiving end device through the NLoS link via the RIS smart metasurface reflection; the second working mode is that when the LoS link is blocked by an obstacle, the RIS smart metasurface is spatially modulated, and the transmitting end device transmits data with the receiving end device through the modulated RIS smart metasurface; Based on the power consumption in different working modes and the power consumption caused by switching working modes, the strategy selection problem of defining the working mode is to minimize the long-term average power consumption; A feedback signal sent by the receiving end device is received, and the probability of the LoS link being blocked by an obstacle is estimated in combination with the feedback signal, and a defined strategy selection problem is solved based on the probability of the LoS link being blocked by an obstacle to obtain a working mode selection strategy for the next time period.

9. The visible light communication system power optimization method according to claim 8, characterized in that: The strategy selection problem of defining the working mode with the goal of minimizing the long-term average power consumption is specifically: The first working mode and the second working mode are represented as M0 and M1 respectively, and the data transmission time t is divided into T time periods, represented by t=0, 1, ..., T. The probability that the LoS link is blocked by an obstacle is p t , and in each time period, p t Keeping the same, in different time periods, p is an independent and identically distributed random variable, In working mode M0, when the LoS link is not blocked by an obstacle, the probability that the LoS link is not blocked by an obstacle is 1-p t , then the corresponding power consumption of the transmitting device is P L , when the LoS link is blocked by an obstacle, data is transmitted through the NLoS link, and the power consumption of the transmitting device is P M , in working mode M1, the RIS smart metasurface is spatially modulated, and the power consumption of the transmitting end device is P N ; Assume that the power consumption caused by switching between working mode M0 and working mode M1 is P S ; The problem of selecting a working mode is defined based on a Markov decision process, wherein the definition of the problem of selecting a working mode includes the definition of behavior, state, transition probability, immediate cost and working mode selection strategy. The behavior is defined as follows: In the tth time period, behavior a t Select from the set {0,1}, a t =0 means selecting working mode M0, a t =1 means selecting working mode M1; The state is defined as follows: In the tth time period, the state definition s t For t =(p t ,a t-1 ), where p t is the probability that the LoS link is blocked by an obstacle in the tth time period, a t-1 is the behavior in the (t-1)th time period, the transmitting device is based on the state s t Select Behavior a t , get the state s of the next period t+1 ; The transition probability is defined as follows: The transition probability Pr(s′|s,a) is defined as Pr(s′|s,a)=Pr(p′|p)=Pr(p′), which is the probability that the system transfers to a new state s′ after executing behavior a in state s; The instantaneous cost is defined as: t Execute behavior a t The immediate cost is c(s t ,a t ) indicates that the total power consumption of the system is measured as: c[s t =(p t ,a t-1 ),a t ]=# The working mode selection strategy π is defined as: a t =π(s t ); Based on the definition of the working mode selection problem, the long-term average power consumption of the system is expressed as: The strategy selection problem with the goal of optimizing long-term average power consumption is expressed as:

10. The visible light communication system power optimization method according to claim 8, characterized in that: The probability of the LoS link being blocked by an obstacle is used to solve the defined strategy selection problem, and the working mode selection strategy for the next time period is obtained, which is specifically: Solving the strategy selection problem through an optimal strategy includes: (P1) satisfies the Bellman equation: Among them, h π* [s] is the optimal strategy π for state s * The relative value function under * is the corresponding average cost, Pr(s ′ |s,a) is the transition probability, c(s,a) is the immediate cost of executing behavior a in state s, The optimal strategy is: in, is the p that satisfies the working mode switching condition under the optimal strategy t The lower threshold, p t represents the probability that the LoS link is blocked by an obstacle in the tth time period, is the p that satisfies the working mode switching condition under the optimal strategy t The upper threshold of

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