LoRa system and physical layer enhancement method based on intelligent reflective surface beam forming and index modulation

Abstract

The invention provides a LoRa system and a LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation, in the system, a transmitting side at least comprises Nk LoRa nodes equipped with single transmitting antennas and an RIS with N passive reflective elements, the RIS is used for improving a wireless propagation environment, beamforming is realized by controlling the phase of each passive reflective element, and the LoRa physical layer enhancement method is used for enhancing the physical layer of the LoRa. The instantaneous signal-to-noise ratio under the antenna combination is activated to the maximum, and the bit error rate performance is improved; a receiver at least comprises a LoRa gateway equipped with NR receiving antennas, multiple receiving antennas at the LoRa gateway are used for index modulation, and Nk receiving antennas in the NR receiving antennas are activated in each symbol period and serve as information transmission entities to bear additional information, so that the transmission throughput is remarkably improved. According to the LoRa physical layer enhancement method applied to the LoRa system, the wireless propagation environment is controlled through RIS beam forming to improve the quality of received signals, and the spectrum efficiency is improved by ingeniously utilizing the IM principle of multiple receiving antenna indexes, so that the LoRa physical layer enhancement method has high transmission rate and high reliability.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a LoRa system based on intelligent reflective surface beamforming and index modulation and a physical layer enhancement method. Background Art

[0002] The growing development and maturity of IoT (Internet of Things) is promoting social transformation and ushering in a new social form under the in-depth application of IoT technology. The IoT in the 5G era is greatly changing people's previous business models and lifestyles by providing real-time information, analysis and decision-making, thus bringing unlimited possibilities for the future development of society. LPWAN (Low Power Wide Area Network), which has the ability to communicate under extremely low signal-to-noise ratio, fills the technical gap that other transmission technologies cannot achieve long-distance low-power transmission in complex environments, and has become an important foundation for supporting IoT connections. Many outstanding technologies have emerged as a result, among which LoRa (Long Range Radio) using spread spectrum technology has become one of the most promising solutions in LPWAN. LoRa uses CSS (Linear Spread Spectrum Modulation, Chirp Spread Spectrum) at the physical layer to effectively expand the coverage of the network and enable it to recover from interference and fading. In addition, LoRa supports multiple spreading factors to achieve a trade-off between distance and data rate, and uses different possibilities such as carrier frequency (CF) and spreading factor (SF) to orthogonalize transmission as much as possible.

[0003] Although LoRa has a wide coverage range and can change the data rate by changing the spreading factor, its maximum transmission rate is still low. A rigorous analysis of LoRa's potential bit error rate shows that in an urban environment with Rayleigh fading characteristics, LoRa may not be able to maintain long-distance communication, resulting in a decrease in transmission quality. Worse, the interference caused by the unavoidable use of the same spreading factor in a large-scale connected LoRa network will lead to further deterioration of LoRa system performance.

[0004] At present, the research on LoRa physical layer enhancement is mainly carried out from two aspects: improving the LoRa transmission rate and reducing the impact of fading channels on LoRa:

[0005] On the one hand, in order to increase the transmission rate of LoRa to be suitable for applications with higher data throughput, a system called FSCSSIM is proposed in the document "Frequency-Shift Chirp Spread Spectrum Communications With Index Modulation", which combines LoRa with IM (Index Modulation) and uses a combination of orthogonal linear frequency modulation signals for message representation. Regarding how to incorporate IM into LoRa modulation as an ideal solution to increase the data rate of LoRa modulation, the document "A New Index Modulation for LoRa" proposes that the new index modulation specifically refers to multiple quasi-orthogonal chirps modulated at different spreading factors being sent simultaneously, thereby using the SF domain as a means of carrying more information.

[0006] On the other hand, in order to solve the problem that the performance of the LoRa system will seriously deteriorate in the fading channel environment, the document "Design and Performance Analysis of a New STBC-MIMO LoRa System" introduces a multiple-input multiple-output configuration using a space-time block coding (STBC) scheme in the LoRa system to formulate an STBC-MIMO LoRa system, and studies the theoretical performance of the proposed system on Rayleigh fading channels. Jae-Mo Kang proposed a new integration of MIMO and LoRa systems for high data rate IoT, and designed a received signal-to-noise ratio maximization precoding to balance data rate and link reliability. The document "A New Reconfigurable Intelligent-Surface-Assisted LoRaSystem" uses intelligent reflective surfaces as another promising solution in the LoRa system, using M-ary differential phase shift keying to generate the reflection coefficient of RIS (Reconfigurable Intelligent Surface) to reduce the impact of fading channels while transmitting additional information.

[0007] Among the related technologies, although IM and RIS technologies have shown good performance improvement effects in their respective application fields, there has been no research on how to intelligently combine these two technologies and apply them to LoRa modulation in order to simultaneously optimize its transmission throughput and bit error performance. Summary of the invention

[0008] In order to solve the above problems existing in the prior art, the present invention provides a LoRa system and a physical layer enhancement method based on intelligent reflective surface beamforming and index modulation. The technical problem to be solved by the present invention is achieved through the following technical solutions:

[0009] In a first aspect, the present invention provides a LoRa system based on intelligent reflective surface beamforming and index modulation, characterized in that it includes: a transmitter and a receiver, wherein the transmitter includes at least: N k A LoRa node equipped with a single transmitting antenna and a smart reflective surface RIS having N passive reflective elements, the receiving side at least includes: R A LoRa gateway with 1 receiving antenna;

[0010] The LoRa node is used to generate a LoRa linear spread spectrum modulation signal;

[0011] The intelligent reflecting surface RIS is used to perform beamforming by controlling the phases of different passive reflecting elements to maximize the instantaneous signal-to-noise ratio of the activated receiving antenna combination;

[0012] The LoRa gateway is used to activate N in each transmission cycle R N of the receiving antennas k index modulation.

[0013] In a second aspect, the present invention provides a LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation, which is applied to the transmitting side of the LoRa system described in the first aspect, and the method includes:

[0014] Converting serial information bits to be transmitted in the current symbol period into parallel information bits, wherein the parallel information bits include one modulation bit and one index bit;

[0015] N is activated in each symbol period R N of the receiving antennas k Generate a valid set of activated antenna combination matrices;

[0016] Convert the index bit into an index symbol, and select from the valid activation antenna combination matrix set according to the index symbol to obtain an activation antenna combination;

[0017] According to the phase of each passive reflective element in the smart reflective surface configured by the activated antenna combination, the instantaneous received signal-to-noise ratio under the activated antenna combination is maximized;

[0018] The modulation bits are converted into modulation symbols, and the modulation symbols are subjected to LoRa linear spread spectrum modulation to obtain N kThe spread spectrum modulation signal of N LoRa nodes is k The transmission of each LoRa node is superimposed on the phase-configured smart reflective surface and reflected to the receiver, which receives and demodulates it.

[0019] In one embodiment of the present invention, N activated in each symbol period R N of the receiving antennas k The steps of generating a valid set of activated antenna combination matrices include:

[0020] N is activated in each symbol period. R N of the receiving antennas k There are a total of possible combinations of activated antennas, where

[0021] The activation antenna combinations with Q activation antenna combinations among the possible activation antenna combinations are regarded as legal activation antenna combinations, and the others are regarded as illegal activation antenna combinations to generate a valid activation antenna combination matrix set. Among them, A i represents the i-th one of Q valid activated antenna combinations,

[0022] In one embodiment of the present invention, the step of maximizing the instantaneous received signal-to-noise ratio under the activated antenna combination according to the phase of each passive reflective element in the smart reflective surface configured by the activated antenna combination includes:

[0023] The smart reflective surface is divided into N k RIS sub-blocks, so that each RIS sub-block configures the phase of its own passive reflective element according to the receiving antenna it serves to achieve the maximum instantaneous received signal-to-noise ratio; wherein the number of passive reflective elements in each RIS sub-block is

[0024] In a third aspect, the present invention further provides a LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation, which is applied to the receiver of the LoRa system described in the first aspect, and the method includes:

[0025] Obtaining received signals via multiple receiving antennas and generating a received signal matrix;

[0026] Sorting the signals in the received signal matrix according to their strengths, and determining the receiving antenna that is most likely to be activated;

[0027] Calculating the occurrence probability of each of the receiving antennas that are most likely to be activated;

[0028] Calculate, according to the occurrence probability of each of the receiving antennas most likely to be activated, the occurrence probability of all activated antenna combinations including the receiving antennas most likely to be activated;

[0029] The activation antenna combinations are sorted according to their occurrence probabilities to obtain a set C of legal activation antenna combinations sorted by probability. s , select C s The first Λ legally activated antenna combinations with the highest probability appear in the algorithm to narrow the solution space;

[0030] The index symbol estimation value of the activated antenna combination and the LoRa symbol estimation value are obtained through Λ iterations;

[0031] Based on the index symbol estimation value and the LoRa symbol estimation value, a bit stream is generated and output.

[0032] In one embodiment of the present invention, the step of sorting the signals in the received signal matrix according to their strengths and determining the receiving antenna most likely to be activated includes:

[0033] Take the absolute value of each column element in the received signal matrix and sort them, and get the top element with the largest absolute value in each column. The index of the elements generates an index set;

[0034] Count the number of times each index appears in the index set;

[0035] The receiving antenna corresponding to the index that appears most times is determined as the receiving antenna that is most likely to be activated.

[0036] In one embodiment of the present invention, the step of calculating the occurrence probability of each of the receiving antennas most likely to be activated includes:

[0037] Calculate the total number of occurrences of all indexes in the index set;

[0038] The occurrence probability of each receiving antenna is calculated by calculating the ratio of the occurrence number of each index in the index set to the total number.

[0039] In one embodiment of the present invention, the step of calculating the occurrence probability of all activated antenna combinations including the receiving antenna most likely to be activated according to the occurrence probability of each receiving antenna most likely to be activated includes:

[0040] Calculate N for each activated antenna combination k The product of the occurrence probabilities of the receiving antennas is obtained to obtain the occurrence probability of each activated antenna combination.

[0041] In one embodiment of the present invention, the activated antenna combinations are sorted according to their occurrence probabilities to obtain a set C of legal activated antenna combinations sorted by probability. s , select C s The steps of narrowing down the solution space by finding the first Λ legally activated antenna combinations with the highest probability in , include:

[0042] Sorting the activated antenna combinations according to their occurrence probabilities to obtain a set of activated antenna combinations sorted by occurrence probabilities;

[0043] Check the activated antenna combination set sorted by occurrence probability, delete the illegal activated antenna combination from it, and obtain the legal activated antenna combination set C sorted by probability s ;

[0044] From the legally activated antenna combination set C sorted by possibility s The Λ with the largest probability is selected as the number of activated antenna combinations to be traversed to narrow the solution space.

[0045] In one embodiment of the present invention, the step of obtaining the index symbol estimation value of the activated antenna combination and the LoRa symbol estimation value through Λ iterations includes:

[0046] Let u=1;

[0047] Determine whether u≤Λ is satisfied;

[0048] When u≤Λ, taking the uth valid activated antenna combination among the first Λ valid activated antenna combinations as the current receiving antenna combination;

[0049] Calculating a smart reflection surface phase vector corresponding to the current receiving antenna combination;

[0050] Based on the current receiving antenna combination, a superposition signal of a corresponding row is selected from the receiving signal matrix, and the superposition signal is subjected to ZF equalization and LoRa incoherent demodulation using the smart reflecting surface phase vector to obtain the strongest node signal;

[0051] Let v = 2;

[0052] Determine whether v≤N k If yes, then use the strongest node signal to cancel interference, and perform ZF equalization and LoRa incoherent demodulation on the solved second strongest node signal, and further set v = v + 1, and return to the judgment whether v ≤ N is satisfied. k Steps;

[0053] If not, the F norm of the difference between the received signal and the predicted signal is calculated; the predicted signal is: the channel matrix, the smart reflection surface phase vector corresponding to the current receiving antenna combination and the estimated N k The product of the superimposed signal vector reconstructed by the LoRa modulation symbols of the nodes;

[0054] Determine whether the F norm of the difference between the received signal and the predicted signal is less than a preset threshold; if so, update the F norm of the difference between the received signal and the predicted signal, the index symbol estimation value of the activated antenna combination obtained in the previous round of estimation, and the LoRa symbol estimation value, and further set u=u+1, and return to the step of determining whether u≤Λ is satisfied;

[0055] When u>Λ, the index symbol estimate and LoRa symbol estimate of the current activated antenna combination are output.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention provides a LoRa system based on intelligent reflective surface beamforming and index modulation, the system includes a transmitter and a receiver, the transmitter at least includes: k A LoRa node equipped with a single transmitting antenna and a RIS with N passive reflective elements, the RIS is used to improve the wireless propagation environment, realize beamforming by controlling the phases of different passive reflective elements, maximize the instantaneous signal-to-noise ratio under a specific activated antenna combination, and thus improve the bit error performance; further, the receiving side at least includes: a LoRa node equipped with N R The LoRa gateway has multiple receiving antennas. The multiple receiving antennas at the LoRa gateway are used for index modulation. N are activated in each symbol period. R N of the receiving antennas k It is used as an information transmission entity to carry additional information, thereby significantly improving the transmission throughput.

[0058] The present invention also provides a LoRa physical layer enhancement method based on intelligent reflective surface and index modulation applied to the transmitter, which intelligently combines RIS and IM and applies them to the LoRa system, not only improving the quality of received signals by controlling the wireless propagation environment through RIS beamforming, but also cleverly utilizing the IM principle of multi-receiving antenna indexing to improve spectrum efficiency, so that it has both high transmission rate and high reliability. In addition, the present invention extends this LoRa physical layer enhancement to the scenario where multiple LoRa nodes use the same spreading factor for parallel transmission, which can effectively solve the serious data packet conflict problem that is prevalent in the LoRa network caused by large-scale connections, avoid the waste of channel resources caused by data damage and packet loss during transmission, and save energy consumption and increase the service life of low-power Internet of Things nodes.

[0059] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a structural block diagram of a LoRa system based on intelligent reflective surface beamforming and index modulation provided by an embodiment of the present invention;

[0061] Figure 2 It is another structural block diagram of a LoRa system based on intelligent reflective surface beamforming and index modulation provided by an embodiment of the present invention;

[0062] Figure 3 It is a flow chart of the transmitting side of the LoRa physical layer enhancement method based on intelligent reflection surface beamforming and index modulation provided by an embodiment of the present invention;

[0063] Figure 4 It is a flow chart of a LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation provided by an embodiment of the present invention;

[0064] Figure 5 It is a receiving flow chart of a LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation provided by an embodiment of the present invention;

[0065] Figure 6 is a comparison diagram of bit error rate performance under different numbers N of smart reflective surface elements and spreading factors SF provided by an embodiment of the present invention;

[0066] Figure 7 4 is a throughput performance comparison diagram under different numbers N of smart reflective surface elements and spreading factors SF provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The present invention is further described in detail below with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0068] Figure 1-2 : is a block diagram of a LoRa system based on intelligent reflective surface beamforming and index modulation provided by an embodiment of the present invention. Figure 1-2 As shown, the embodiment of the present invention provides a LoRa system based on intelligent reflective surface beamforming and index modulation, including: a transmitter and a receiver, the transmitter at least includes: N k A LoRa node equipped with a single transmitting antenna and a smart reflective surface RIS with N passive reflective elements, the receiving side at least includes: R A LoRa gateway with 1 receiving antenna;

[0069] LoRa node, used to generate LoRa linear spread spectrum modulation signal;

[0070] Intelligent Reflecting Surfaces (RIS), used to perform beamforming by controlling the phase of different passive reflective elements to maximize the instantaneous signal-to-noise ratio of the active receive antenna combination;

[0071] LoRa gateway is used to activate N in each transmission cycle R N of the receiving antennas k index modulation.

[0072] Specifically, the LoRa system consists of N k A LoRa node with a single antenna, a R The LoRa gateway consists of a LoRa gateway with 10 antennas and a smart reflective surface with N passive reflective elements. Consider the scenario where multiple LoRa nodes use the same spreading factor to transmit in parallel, and use smart reflective surfaces and index modulation to assist LoRa transmission. The smart reflective surface RIS is very close to the LoRa node and as part of the transmitter, it can provide adjustable phase shift to replace the traditional beamforming process. The receiving antenna at the LoRa gateway is used for index modulation, activating N in each symbol period. R N of the receiving antennas k It is used as an information transmission entity to carry additional information.

[0073] When the LoRa node is close enough to the RIS, its transmission is not affected by fading. The wireless channel matrix between the LoRa gateway and the RIS is recorded as The elements That is, it represents the channel between the lth antenna of the gateway and the nth reflector element of the RIS. Under the assumption of uncorrelated flat Rayleigh fading, Follow independent Complex Gaussian distribution, where l = 1, 2, ..., N R ,n=1,2,...,N. The phase vector of the passive reflector element of RIS is recorded as

[0074]

[0075] Figure 3 is a flow chart of the transmitting side of the LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation provided by an embodiment of the present invention, Figure 4 1 is a flow chart of a LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation provided by an embodiment of the present invention. Figure 3-4 As shown, an embodiment of the present invention provides a LoRa physical layer enhancement method based on intelligent reflection surface beamforming and index modulation, which is applied to the transmitting side of the LoRa system, including:

[0076] S101, converting serial information bits to be transmitted in a current symbol period into parallel information bits, where the parallel information bits include one modulation bit and one index bit;

[0077] S102: N activated in each symbol period R N of the receiving antennas k Generate a valid set of activated antenna combination matrices;

[0078] S103, converting the index bit into an index symbol, and selecting from a valid activation antenna combination matrix set according to the index symbol to obtain an activation antenna combination;

[0079] S104, configuring the phase of each passive reflective element in the intelligent reflective surface according to the activated antenna combination to maximize the instantaneous received signal-to-noise ratio under the activated antenna combination;

[0080] S105, converting the modulation bits into modulation symbols, and performing LoRa linear spread spectrum modulation on the modulation symbols to obtain N k The spread spectrum modulation signal of N LoRa nodes is k The transmission of each LoRa node is superimposed on the phase-configured smart reflective surface and reflected to the receiver, which receives and demodulates it.

[0081] Optionally, the LoRa system further includes a serial / parallel converter. In step S101, the step of converting the serial information bits to be transmitted in the current symbol period into parallel information bits includes:

[0082] The serial / parallel converter is used to convert the serial information bits to be transmitted in the current symbol period into two parallel information bits:

[0083] The first path is the modulation bit, which is modulated into N k The linear spread spectrum modulation signal of a LoRa node is expressed as L1=N k log2M, where M = 2 SF is the number of chips after spreading. The other is the index bit, which is used to select the activated receiving antenna combination, expressed as Therefore, in one LoRa symbol period, the number of bits that can be transmitted is expressed as:

[0084]

[0085] Furthermore, the bit transmission rate is expressed as:

[0086]

[0087] Where SF is the common spreading factor N kThe spreading factor currently used by the LoRa node, is the symbol period, and B is the LoRa transmission bandwidth.

[0088] Optionally, in step S102, N activated in each symbol period R N of the receiving antennas k The steps of generating a valid set of activated antenna combination matrices include:

[0089] S1021, activate N in each symbol period R N of the receiving antennas k There are a total of possible combinations of activated antennas, where

[0090] S1022: Among the possible activation antenna combinations, activation antenna combinations with an activation antenna combination number of Q are regarded as legal activation antenna combinations, and the rest are regarded as illegal activation antenna combinations, to generate a valid activation antenna combination matrix set. Among them, A i represents the i-th one of Q valid activated antenna combinations,

[0091] In this embodiment, the LoRa gateway has N R The number of receiving antennas activated at each moment is N k , then all possible combinations of activated antennas are kind, represents the binomial coefficient, Since binary bit information is modulated, the number of activated receiving antenna combinations must be an integer power of 2, that is, the number of valid activated antenna combinations is Therefore, in step S1022, Q receiving antenna combinations can be randomly selected from all possible activation antenna combinations as legal activation antenna combinations, and the remaining activation antenna combinations are considered illegal activation antenna combinations. All valid activation antenna combinations constitute a valid activation antenna combination matrix set.

[0092] Optionally, in step S104, the step of maximizing the instantaneous received signal-to-noise ratio under the activated antenna combination according to the phase of each passive reflective element in the smart reflective surface configured by the activated antenna combination includes:

[0093] Divide the smart reflective surface into N equal parts kRIS sub-blocks, so that each RIS sub-block configures the phase of its own passive reflective element according to the receiving antenna it serves to achieve the maximum instantaneous received signal-to-noise ratio; wherein the number of passive reflective elements in each RIS sub-block is

[0094] Specifically, in each symbol period, the LoRa gateway has N k The receiving antennas are activated, so the RIS needs to be divided into N k To achieve multi-directional passive beamforming, the RIS dedicated to each selected receiving antenna is called a RIS sub-block, and the number of its elements is Exemplarily, the selected receiving antenna combination index is q, q = 1, 2, ..., Q, then the target channel determined by the receiving antenna combination index can be expressed as in, Finally, the phase vector of the reflection unit assigned to the kth active antenna by RIS according to the received receive antenna combination index q is expressed as:

[0095]

[0096] where k = 1, 2, ..., N k .

[0097] Further, in step S105, the bit / symbol converter in the LoRa system is used to complete the conversion of the modulation bit to the modulation symbol, and then the LoRa modulator performs LoRa linear spread spectrum modulation.

[0098] Under the channel access mechanism of the ALOHA protocol, N k LoRa nodes select the same spreading factor to transmit on the same frequency channel at the same time, which is different from the N R When the LoRa gateway with 4 antennas communicates, the N k The spread spectrum modulation signal of N LoRa nodes is k The transmission of each LoRa node is superimposed on the phase-configured smart reflective surface and reflected to the receiving LoRa gateway.

[0099] The received signal at the LoRa gateway is shown below:

[0100] Y=Gθ q x p +Z;

[0101] Among them, x p N is the common spreading factor k The superimposed signal of the LoRa nodes, α i represents the transmission power allocation coefficient of the i-th LoRa node, represents the LoRa discrete-time signal emitted by the i-th LoRa node at the m-th sampling time, Z is the additive white Gaussian noise (AWGN) sample at the LoRa gateway, and obeys Complex Gaussian distribution.

[0102] After receiving the received signal, the receiver demodulates it.

[0103] Figure 5 This is a flowchart of the receiver of the LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation provided by an embodiment of the present invention. Figure 4-5 The embodiment of the present invention also provides a LoRa physical layer enhancement method based on intelligent reflection surface beamforming and index modulation, which is applied to the receiver of the LoRa system, including:

[0104] S201, obtaining a received signal via multiple receiving antennas, and generating a received signal matrix;

[0105] S202, sorting the signals in the received signal matrix according to their strengths, and determining the receiving antenna that is most likely to be activated;

[0106] S203, calculating the occurrence probability of each receiving antenna that is most likely to be activated;

[0107] S204, calculating the occurrence probability of all activated antenna combinations including the receiving antenna that is most likely to be activated according to the occurrence probability of each receiving antenna that is most likely to be activated;

[0108] S205: Sort the activated antenna combinations according to their occurrence probabilities to obtain a set C of legal activated antenna combinations sorted by probability. s , select C s The first Λ legally activated antenna combinations with the highest probability appear in the algorithm to narrow the solution space;

[0109] S206. Obtain an index symbol estimation value of the activated antenna combination and a LoRa symbol estimation value through Λ iterations;

[0110] S207. Generate and output a bit stream based on the index symbol estimation value and the LoRa symbol estimation value.

[0111] Based on the transmitter modulation process, the embodiment of the present invention proposes a corresponding maximum likelihood ML detection algorithm as the optimal performance upper limit. By traversing all activated antenna combination indexes and LoRa symbols, among all possible transmitted signal vectors, the vector with the smallest Euclidean distance to the received signal vector is selected as the decision output, that is:

[0112]

[0113] in, and are the estimated values ​​of the index symbol of the activated antenna combination and the estimated values ​​of the LoRa symbol, respectively, and p and q are the index symbols and LoRa symbols of all possible activated antenna combinations, respectively.

[0114] However, considering the characteristics of exhaustive search, the computational complexity of the ML algorithm will increase sharply with the increase of the number of receiving antennas and the number of LoRa spreading factors, making it difficult to apply in practice. Therefore, the embodiment of the present invention adopts a low-complexity two-stage sequential detection algorithm, that is, in the first stage, the solution space of the activated receiving antenna combination is reduced, and in the second stage, the phase vector of the smart reflective surface is obtained according to the receiving antenna combination index in the reduced solution space, and the superimposed LoRa-Like signal decoding based on the successive interference cancellation (SIC) algorithm is performed.

[0115] In step S202, the step of sorting the signals in the received signal matrix according to their strengths and determining the receiving antenna most likely to be activated includes:

[0116] S2021. Take the absolute value of each column element in the received signal matrix and sort them, and obtain the top element with the largest absolute value in each column. The index of the elements generates an index set;

[0117] S2022. Count the number of times each index appears in the index set;

[0118] S2023: Determine the receiving antenna corresponding to the index that appears most frequently as the receiving antenna that is most likely to be activated.

[0119] Optionally, step S203, the step of calculating the occurrence probability of each receiving antenna most likely to be activated, includes:

[0120] S2031. Calculate the total number of times all indexes appear in the index set;

[0121] S2032. Calculate the occurrence probability of each receiving antenna by calculating the ratio of the occurrence number of each index in the index set to the total number of occurrences.

[0122] Furthermore, in step S204, the step of calculating the occurrence probability of all activated antenna combinations including the receiving antenna that is most likely to be activated according to the occurrence probability of each receiving antenna that is most likely to be activated includes:

[0123] Calculate N for each activated antenna combination k The product of the occurrence probabilities of the receiving antennas is used to obtain the occurrence probability of each activated antenna combination.

[0124] Here, the probability of occurrence of each activated antenna combination is:k The product of the probability of each receiving antenna appearing on its own.

[0125] Optionally, in step S205, the activated antenna combinations are sorted according to their occurrence probabilities to obtain a set C of legal activated antenna combinations sorted by probability. s , select C s The steps of narrowing down the solution space by finding the first Λ legally activated antenna combinations with the highest probability in , include:

[0126] S2051. Sort the activated antenna combinations according to their occurrence probabilities to obtain a set of activated antenna combinations sorted by occurrence probabilities;

[0127] S2052, check the activated antenna combination set sorted by occurrence probability, delete the illegal activated antenna combination from it, and obtain the legal activated antenna combination set C sorted by probability s ;

[0128] S2053, from the legally activated antenna combination set C sorted by possibility s The Λ with the largest probability is selected as the number of activated antenna combinations to be traversed to narrow the solution space.

[0129] Further, in step S206, the step of obtaining the index symbol estimation value of the activated antenna combination and the LoRa symbol estimation value through Λ iterations includes:

[0130] Let u=1;

[0131] Determine whether u≤Λ is satisfied;

[0132] When u≤Λ, the uth valid activated antenna combination among the previous Λ valid activated antenna combinations is used as the current receiving antenna combination;

[0133] Calculate the smart reflection surface phase vector corresponding to the current receiving antenna combination;

[0134] Based on the current receiving antenna combination, the superimposed signal of the corresponding row is selected from the receiving signal matrix, and the superimposed signal is ZF equalized and LoRa incoherently demodulated using the smart reflection surface phase vector to obtain the strongest node signal;

[0135] Let v = 2;

[0136] Determine whether v≤N k If yes, then use the strongest node signal to cancel the interference, and perform ZF equalization and LoRa incoherent demodulation on the solved second strongest node signal. After further setting v=v+1, return to determine whether the above condition satisfies v≤N. k Steps;

[0137] If not, the F norm of the difference between the received signal and the predicted signal is calculated; the predicted signal is: the channel matrix, the smart reflection surface phase vector corresponding to the current receiving antenna combination and the estimated N k The product of the superimposed signal vector reconstructed by the LoRa modulation symbols of the nodes;

[0138] Determine whether the F norm of the difference between the received signal and the predicted signal is less than a preset threshold; if so, update the F norm of the difference between the received signal and the predicted signal, the index symbol estimation value of the activated antenna combination obtained in the previous round of estimation, and the LoRa symbol estimation value, and further set u=u+1, and return to the step of determining whether u≤Λ is satisfied;

[0139] When u>Λ, the index symbol estimate and LoRa symbol estimate of the current activated antenna combination are output.

[0140] Specifically, let Λ be the number of iteration cycles. In each iteration cycle, the target channel determined by the current receiving antenna combination is expressed as Correspondingly, the phase vector of the smart reflection surface assigned to the kth activated receiving antenna obtained according to the current receiving antenna combination is expressed as:

[0141]

[0142] After obtaining the phase vector of the smart reflective surface, the continuous interference cancellation algorithm is applied to the decoding of the superimposed LoRa-Like signal received at the LoRa gateway. The first step is to identify the strongest signal and decode the strongest signal information: first apply ZF to the received signal for linear equalization, and then directly demodulate the strongest signal. The steps of LoRa non-correlated demodulation are: first despread the spectrum, then apply DFT to the despread signal, and then estimate the LoRa symbol by selecting the index of the frequency bit with the largest amplitude. Except for the first step, the decoded LoRa symbols must be used for interference cancellation before each other step of detection. Therefore, for the second strongest node signal, the received signal is still equalized, and then the reconstructed strongest node signal is subtracted from the received signal, and finally the LoRa symbol to be decoded is non-correlated demodulated. Repeat the above operation until N k All LoRa symbols of nodes are decoded.

[0143] Finally, the F norm between the received signal and the predicted signal is calculated by Among the solutions of Λ activated receiving antenna combinations, the solution with the smallest F norm is selected as the final estimation result. and from N k LoRa symbol of nodes All have been detected.

[0144] Further, in step S207, the LoRa system also includes a symbol / bit converter and a parallel / serial converter;

[0145] The step of generating and outputting a bit stream based on the index symbol estimation value and the LoRa symbol estimation value includes:

[0146] Using a symbol / bit converter, the LoRa symbol estimate is converted into a modulation bit estimate, and the index symbol estimate is converted into an index bit estimate;

[0147] The modulation bit estimation value and the index bit estimation value are converted into a bit stream by using a parallel / serial converter and then output.

[0148] Next, the LoRa physical layer enhancement method based on intelligent reflection surface beamforming and index modulation applied to the sender and receiver is further explained through simulation experiments.

[0149] Specifically, numerical simulation experiments are conducted using MATLAB simulation software. In the simulation experiment, the numerical analysis results of the LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation are given, including bit error rate performance and throughput performance, where throughput is defined as the number of bits successfully transmitted per unit time and correctly received by the receiver. Optionally, the number of LoRa nodes is set to 2, the spreading factor used by the LoRa nodes is set to 7, the LoRa transmission bandwidth is set to 250kHz, and the number of receiving antennas at the LoRa gateway is N. R Set to 6, the number of activated receiving antennas N k Set to 2. We demonstrate the bit error rate and throughput performance of the scheme under the conditions of the number of smart reflective surface elements N = 64, 128 and SF = 7, 8, 9, 10.

[0150] Figure 6 is a comparison chart of bit error rate performance under different numbers N of smart reflective surface elements and spreading factors SF provided by an embodiment of the present invention. Figure 6It can be seen that as the number of smart reflective surface elements N increases from 64 to 128, the bit error rate of the LoRa system is significantly reduced and the bit error rate performance is significantly improved. In other words, increasing the number of smart reflective surface elements N and the spreading factor SF are both helpful in improving the bit error rate performance of the system. This is because the smart reflective surface intelligently controls the reflection characteristics of the incident wave through passive reflective elements, thereby dynamically changing the wireless channel and improving the signal quality at the receiving end. In traditional LoRa, in order to achieve a longer communication distance and stronger anti-interference ability, a larger spreading factor is usually used. However, a larger SF will significantly increase the symbol duration, thereby reducing the data transmission rate. Increasing the number of smart reflective surface elements can achieve the same effect as expanding the SF, making the system more robust in challenging wireless environments without increasing the symbol duration, thereby better achieving a trade-off between communication distance and data rate.

[0151] Figure 7 is a throughput performance comparison diagram under different numbers of smart reflective surface elements N and spreading factors SF provided by an embodiment of the present invention. Figure 7 It can be seen that in N R 6, N k When the value is 2, the maximum throughput of the LoRa system can reach 3.3×10 4 b / s, which is 2.7×10- 4 b / s, which has been significantly improved. At the same time, the larger the number of smart reflective surface elements N, the earlier the throughput growth starts, and the faster the maximum throughput is reached. However, when the spreading factor SF reaches a certain level, the impact of the number of smart reflective surface elements N on the speed of reaching the maximum throughput becomes less significant. This is because a larger spreading factor brings a greater spectrum broadening and provides strong anti-interference capabilities. At this point, further optimization of the smart reflective surface has limited impact on achieving the maximum throughput speed.

[0152] It can be seen from the above embodiments that the beneficial effects of the present invention are:

[0153] The present invention provides a LoRa system based on intelligent reflective surface beamforming and index modulation, the system includes a transmitter and a receiver, the transmitter at least includes: k A LoRa node equipped with a single transmitting antenna and a RIS with N passive reflective elements, the RIS is used to improve the wireless propagation environment, realize beamforming by controlling the phases of different passive reflective elements, maximize the instantaneous signal-to-noise ratio under a specific activated antenna combination, and thus improve the bit error performance; further, the receiving side at least includes: a LoRa node equipped with N RThe LoRa gateway has multiple receiving antennas. The multiple receiving antennas at the LoRa gateway are used for index modulation. N are activated in each symbol period. R N of the receiving antennas k It is used as an information transmission entity to carry additional information, thereby significantly improving the transmission throughput.

[0154] The present invention provides a LoRa physical layer enhancement method based on intelligent reflective surface and index modulation applied to the transmitter, which intelligently combines RIS and IM and applies them to the LoRa system, not only improving the quality of received signals by controlling the wireless propagation environment through RIS beamforming, but also cleverly utilizing the IM principle of multi-receiving antenna index to improve spectrum efficiency, so that it has both high transmission rate and high reliability. In addition, the present invention extends this LoRa physical layer enhancement to the scenario where multiple LoRa nodes use the same spreading factor for parallel transmission, which can effectively solve the serious data packet conflict problem that is prevalent in the LoRa network caused by large-scale connections, avoid the waste of channel resources caused by data damage and packet loss during transmission, and save energy consumption and increase the service life of low-power Internet of Things nodes.

[0155] In the description of the present invention, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification.

[0156] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the present application for which protection is sought, a person skilled in the art may understand and implement other variations of the disclosed embodiments by reviewing the drawings, the disclosure, and the appended claims.

[0157] The above contents are further detailed descriptions of the present invention in combination with specific preferred embodiments, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A LoRa system based on intelligent reflective surface beamforming and index modulation, characterized in that: include: A transmitter and a receiver, wherein the transmitter at least includes: N k A LoRa node equipped with a single transmitting antenna and a smart reflective surface RIS having N passive reflective elements, the receiving side at least includes: R A LoRa gateway with 1 receiving antenna; The LoRa node is used to generate a LoRa linear spread spectrum modulation signal; The intelligent reflecting surface RIS is used to perform beamforming by controlling the phases of different passive reflecting elements to maximize the instantaneous signal-to-noise ratio of the activated receiving antenna combination; The LoRa gateway is used to activate N in each transmission cycle R N of the receiving antennas k index modulation.

2. A LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation, characterized in that: Applied to the transmitter of the LoRa system according to claim 1, the method comprises: Converting serial information bits to be transmitted in the current symbol period into parallel information bits, wherein the parallel information bits include one modulation bit and one index bit; N is activated in each symbol period R N of the receiving antennas k Generate a valid set of activated antenna combination matrices; Convert the index bit into an index symbol, and select from the valid activation antenna combination matrix set according to the index symbol to obtain an activation antenna combination; According to the phase of each passive reflective element in the smart reflective surface configured by the activated antenna combination, the instantaneous received signal-to-noise ratio under the activated antenna combination is maximized; The modulation bits are converted into modulation symbols, and the modulation symbols are subjected to LoRa linear spread spectrum modulation to obtain N k The spread spectrum modulation signal of N LoRa nodes is k The transmission of each LoRa node is superimposed on the phase-configured smart reflective surface and reflected to the receiver, which receives and demodulates it.

3. The LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation according to claim 2 is characterized in that: N is activated in each symbol period R N of the receiving antennas k The steps of generating a valid set of activated antenna combination matrices include: N is activated in each symbol period. R N of the receiving antennas k There are a total of possible combinations of activated antennas, where The activation antenna combinations with Q activation antenna combinations among the possible activation antenna combinations are regarded as legal activation antenna combinations, and the others are regarded as illegal activation antenna combinations to generate a valid activation antenna combination matrix set. Among them, A i represents the i-th one of Q valid activated antenna combinations, 4. The LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation according to claim 2 is characterized in that: The step of maximizing the instantaneous reception signal-to-noise ratio under the activated antenna combination according to the phase of each passive reflection element in the intelligent reflection surface configured by the activated antenna combination comprises: The smart reflective surface is divided into N k RIS sub-blocks, so that each RIS sub-block configures the phase of its own passive reflective element according to the receiving antenna it serves to achieve the maximum instantaneous received signal-to-noise ratio; wherein the number of passive reflective elements in each RIS sub-block is 5. A LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation, characterized in that: Applied to the receiver of the LoRa system according to claim 1, the method comprises: Obtaining received signals via multiple receiving antennas and generating a received signal matrix; Sorting the signals in the received signal matrix according to their strengths, and determining the receiving antenna that is most likely to be activated; Calculating the occurrence probability of each of the receiving antennas that are most likely to be activated; Calculate, according to the occurrence probability of each of the receiving antennas most likely to be activated, the occurrence probability of all activated antenna combinations including the receiving antennas most likely to be activated; The activation antenna combinations are sorted according to their occurrence probabilities to obtain a set C of legal activation antenna combinations sorted by probability. s , select C s The first Λ legally activated antenna combinations with the highest probability appear in the algorithm to narrow the solution space; The index symbol estimation value of the activated antenna combination and the LoRa symbol estimation value are obtained through Λ iterations; Based on the index symbol estimation value and the LoRa symbol estimation value, a bit stream is generated and output.

6. The LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation according to claim 5 is characterized in that: The step of sorting the signals in the received signal matrix according to their strengths and determining the receiving antenna most likely to be activated comprises: Take the absolute value of each column element in the received signal matrix and sort them, and get the top element with the largest absolute value in each column. The index of the elements generates an index set; Count the number of times each index appears in the index set; The receiving antenna corresponding to the index that appears most times is determined as the receiving antenna that is most likely to be activated.

7. The LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation according to claim 6 is characterized in that: The step of calculating the occurrence probability of each of the receiving antennas most likely to be activated comprises: Calculate the total number of occurrences of all indexes in the index set; The occurrence probability of each receiving antenna is calculated by calculating the ratio of the occurrence number of each index in the index set to the total number.

8. The LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation according to claim 7 is characterized in that: The step of calculating the occurrence probability of all activated antenna combinations including the receiving antenna most likely to be activated according to the occurrence probability of each receiving antenna most likely to be activated comprises: Calculate N for each activated antenna combination k The product of the occurrence probabilities of the receiving antennas is obtained to obtain the occurrence probability of each activated antenna combination.

9. The LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation according to claim 5, characterized in that: The activation antenna combinations are sorted according to their occurrence probabilities to obtain a set C of legal activation antenna combinations sorted by probability. s , select C s The steps of narrowing down the solution space by finding the first Λ legally activated antenna combinations with the highest probability in , include: Sorting the activated antenna combinations according to their occurrence probabilities to obtain a set of activated antenna combinations sorted by occurrence probabilities; Check the activated antenna combination set sorted by occurrence probability, delete the illegal activated antenna combination from it, and obtain the legal activated antenna combination set C sorted by probability s ; From the legally activated antenna combination set C sorted by possibility s The Λ with the largest probability is selected as the number of activated antenna combinations to be traversed to narrow the solution space.

10. The LoRa physical layer enhancement method based on intelligent reflective surface beamforming and index modulation according to claim 6, characterized in that: The steps of obtaining the index symbol estimation value of the activated antenna combination and the LoRa symbol estimation value through Λ iterations include: Let u=1; Determine whether u≤Λ is satisfied; When u≤Λ, taking the uth valid activated antenna combination among the first Λ valid activated antenna combinations as the current receiving antenna combination; Calculating a smart reflection surface phase vector corresponding to the current receiving antenna combination; Based on the current receiving antenna combination, a superposition signal of a corresponding row is selected from the receiving signal matrix, and the superposition signal is subjected to ZF equalization and LoRa incoherent demodulation using the smart reflecting surface phase vector to obtain the strongest node signal; Let v = 2; Determine whether v≤N k If yes, then use the strongest node signal to cancel interference, and perform ZF equalization and LoRa incoherent demodulation on the solved second strongest node signal, and further set v = v + 1, and return to the judgment whether v ≤ N is satisfied. k Steps; If not, the F norm of the difference between the received signal and the predicted signal is calculated; the predicted signal is: the channel matrix, the smart reflection surface phase vector corresponding to the current receiving antenna combination and the estimated N k The product of the superimposed signal vector reconstructed by the LoRa modulation symbols of the nodes; Determine whether the F norm of the difference between the received signal and the predicted signal is less than a preset threshold; if so, update the F norm of the difference between the received signal and the predicted signal, the index symbol estimation value of the activated antenna combination obtained in the previous round of estimation, and the LoRa symbol estimation value, and further set u=u+1, and return to the step of determining whether u≤Λ is satisfied; When u>Λ, the index symbol estimate and LoRa symbol estimate of the current activated antenna combination are output.

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